VOLUME 3(1)Edited by
Md. Zakaria Hossain
Hossain Md. Shahin

GEOMATE 2013 NAGOYA, JAPANGEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENTiPROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE – GEOMATE 2013
GEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENT NAGOYA, JAPAN
13-15 NOVEMBER, 2013

Geotechnique, Construction
Materials and Environment
Edited by

Md. Zakaria Hossain
Graduate School of Bioresources
Mie University

Hossain Md. Shahin
Graduate School of Engineering
Nagoya Institute of Technology

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2013 by The GEOMATE International Society
All rights reserved. In principle, no part of this publication or the information contained herein may be
reproduced in any form or by any means, translated in any language, stored in any data base or retrieval system,or transmitted in any form or by any means without prior permission in writing from the publisher.
Disclaimer: The editors and the publisher have tried their best effort to ensure the integrity and the quality ofthis publication and information herein. However, they give no warranty of any kind, expressed or impliedwith regard to the material contained in this book, and will not be liable in any event for the consequences of
its use.
Published by:
The GEOMATE International Society
Tsu city, Mie, Japan
E-mail: geomate@gi-j.com
www.gi-j.com

ISBN Number: 978-4-9905958-2-1 C3051

iii

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Table of Contents

PrefaceOrganizationx
xi

ID Keynote Papers

1

GROUND DEFORMATION DURING AND AFTER EARTHQUAKES–SIMULATION AND PREDICTION BASED ON ELASTO-PLASTIC SOIL MECHANICSAkira Asaoka

2

1k

2k

USE OF RECYCLED AGGREGATES FROM CONSTRUCTION AND DEMOLITION WASTES FOR THE
CONSTRUCTION OF FLEXIBLE PAVEMENTS
Márcio Muniz de Farias, Alejandra María Gómez Jiménez and Ferney Quiñones Sinisterra

12

3k

EFFECTIVE STRESS IN UNSATURATED GRANULAR MEDIA IN THE PENDULAR REGIME
Richard Wan, Sarah Khosravani and Mehdi Pouragha

24

4k

RECENT GEOTECHNICAL RESEARCH ADVANCES IN UNIVERSITY PUTRA MALAYSIA
Bujang B.K.Huat and Afshin Asadi

32

Technical Papers

40

ID

Geotechnique

41

3102

LANDSLIDES IN BANGLADESH: CAUSES AND RECOMMENDATION
Musahaq Ali, Zakaria Hossain and Shigeko Haruyama

42

3110

PRECAST SPREAD FOUNDATION IN INDUSTRIALIZED BUILDING SYSTEM
Ramli Nazir, Ehsan Momeni, A. Kadir Marsono, Houman Sohaie

47

3114

CATEGORISING GEOTECHNICAL PROPERTIES OF SUBSOIL IN SURFERS PARADISE USINGGEOGRAPHIC INFORMATION SYSTEM (GIS)
Haider Al-Ani, Leila Eslami-Andargoli, Erwin Oh and Gary Chai

53

3116

EVALUATION OF CONSTITUTIVE MODEL IN SIMULATING THE BEHAVIOR OF CEMENT-TREATED SOIL
Ay Lee Saw, C F Leung and S A Tan

59

3122

UPDATING THE PREDICTIVE MODEL FOR THE VERTICAL COLLAPSE PERCENTAGE OF COLLAPSIBLE
SOIL SUBGRADES
Moshe Livneh and Noam A. Livneh

65

3123

INFLUENCE OF FREEZE-THAW ACTION ON AIR-PERMEABILITY OF UNSATURATED SOIL GROUND
Tatsuya Ishikawa, Tetsuya Tokoro, Dai Nakamura and Satoshi Yamashita

71

iv

3144

EFFECT OF ROCK SOCKET CHARACTERISTICS ON LOW STRAIN INTEGRITY TEST OF PILES
Ramli Bin Nazir and Osman El Hussien

77

3148

CHARACTERISTICS OF SLOPE FAILURES IN MAKINOHARA, JAPANJun Sugawara

83

3151

S-PSA WITH USING FEM FOR AN EXISTING ESTUARY DAM
T. Hara, M. Iwata, Y. Otake, Y. Honjo, T. Kato, A. Nishida and H. Yukimoto

89

3155

THE ROTATIONAL HARDENING RULE WITHOUT THE LIMIT SURFACE OF HARDENING
Hiroyuki Kyokawa, Ryoki Ohashi and Teruo Nakai

95

3157

A STUDY OF THE FORMATION MECHANISM OF BEACHROCK IN OKINAWA, JAPAN: TOWARD
MAKING ARTIFICIAL ROCK
Takashi Danjo and Satoru Kawasaki

101

3161

A STUDY ON THE SLAKING-INDUCED CREEP DEFORMATION CHARACTERISTICS OF CRUSHEDMUDSTONE
Sharma Keshab, Kiyota Takashi and Kyokawa Hiroyuki

107

3163

ASTUDY ON GROWTH OF VETIVER GRASS IN TROPICAL REGION FOR SLOPE PROTECTION
Mohammad Shariful Islam, B. A. M. Shahriar, Md. Shahidul Islam and Hossain Md. Shahin

113

3164

INTERACTION MECHANISMS OF SOIL-GEOSYNTHETIC REINFORCEMENT
Mabrouk Touahmia

119

3165

SIMULATION AND PREDICTION OF LARGE-SETTLEMENT IN ULTRA-SOFT PEAT GROUND BY
DEDUCING THE IN-SITU INITIAL CONDITIONS CONSIDERING ARTESIAN PRESSURE
Mutsumi Tashiro, Toshihiro Noda and Nguyen Hong Son

124

3175

SEISMIC RESPONSE ANALYSIS OF GEOTECHNICAL STRUCTURES BUILT OF CEMENT-TREATED
DREDGED SOIL
Takayuki Sakai, Masaki Nakano and Shotaro Yamada

130

3176

3178

3184

3193

3211
3217

3223

DEVELOPMENT OF SPH METHOD WITH AN ELASTO-PLASTIC CONSTITUTIVE MODEL CONSIDERING
SOIL SKELETON STRUCTURE AND ITS APPLICATION TO EXCAVATION PROBLEMS
Hideto Nonoyama, Masaki Nakano and Toshihiro Noda
SOUNDNESS EVALUATION OF THE EMBANKEMNTS FOR EFFECTIVE MAINTENANCE AND LONG-LIFE
OF SHIN-TOMEI EXPRESSWAY
Masaya Hinokio, Hiroshi Yamato, Kazunari Suzuki, Takayuki Sakai, Masaki Makano and Minoru
KawaidaEVALUATION OF GLASS FIBERS DERIVED-THREE DIMENSIONAL GEOMATERIAL FOR PROBLEMATIC
SOIL APPLICATIONS
Donovan Mujah, Hemanta Hazarika, Fauziah Ahmad and Muhammad Ekhlasur Rahman
STUDY ON MONITORING METHOD OF RETAINING WALL BEHAVIOR USING MEMS SENSOR
NETWORKN Minakata, S Nishiyama, T Yano, D.H Lee, J Wu and M Ryu
CASE STUDY ON THE USE OF HIGH-RESOLUTION SURFACE WAVE SURVEY FOR EXAMINING THE
CAUSE OF SUBSIDENCE OF RECLAIMED ROAD
Miura Minami and Shibuya Satoru
MODIFICATION OF KAOLIN MINERALOGY AND MORPHOLOGY BY HEAT TREATMENT AND
POSSIBILITY OF USE IN GEOTECHNICAL ENGINEERING
Nurmunira Muhammad, Ideris Zakaria and Abdoullah Namdar
SIMULATING THE EFFECT OF FLOW VOLUME ON SCOURING PROCESS AROUND BREAKWATERUNDER TSUNAMI CONDITION BY SPH METHOD
M.R. Islam, K. Hayano and A.M.K.N. Nadeesha

v

136

142

148

154

160

164

169

3226

DEVELOPING A NUMERICAL MODEL FOR THE STABILITY DESIGN OF TUNNEL HEADING
Jim Shiau and Ryan Kemp

175

3228

INVESTIGATION OF THE OPTIMAL SUPPORT PATTERNS IN BRACED EXCAVATION USING GROUNDANCHORS
H. M. Shahin, Teruo Nakai, Okuda Kazuaki and Kato Morihiro

181

3232

SHEAR MODULUS REDUCTION CURVES OF GUAYURIBA SANDS BY CYCLIC TRIAXIAL AND BENDER
ELEMENT TESTS
J.F. Gaitán-Serrano, M.P. Ortiz-Pulido and J.F. Camacho-Tauta

187

3234

WATER DIVERSION AND DRAINAGE IN SHALLOW LAND WASTE REPOSITORY CONSTRUCTED USING
CAPILLARY BARRIER OF SOIL
Toshihiro Morii, Kaoru Kobayashi, Kazunobu Matsumoto and Satoru Nakafusa

193

3236

REINFORCING EFFECT OF GEOSYNTHETICS
ON BEARING CAPACITY
Masuda Saki, H. M. Shahin, Nakai Teruo, Morikawa Yukihiro and Mio Susumu

199

3237

INFLUENCE OF THE STRESS HISTORY ON THE STIFFNESS OF SOIL
Asano Kanako, H.M. Shahin, Hiroyuki Kyokawa, Teruo Nakai and Ohashi Ryoki

205

3238

EFFECTIVENESS OF CRASHED TILE IN COUNTERMEASURE AGAINST LIQUEFACTION
Morikawa Yukihiro, Maeda Kenichi and Zhang Feng

211

3246

PREDICTION OF NATM TUNNEL EXCAVATION UNDER SHALLOW OVERBURDEN IN PAHANGSELANGOR RAW WATER TRANSFER TUNNEL PROJECT, MALAYSIA
Mohd Ashraf Mohamad Ismail, Goh Chin Ong, Romziah Azit, Zulkifli Nordin, Norzani Mahmood

217

3250

FUNDAMENTAL STUDY ON LATERAL RESISTANCE CHARACTERISTICS OF BALLASTED TRACKSSUBJECTED TO PSEUDO-STATIC INERTIA FORCE
Ryuta Ogawa and Kimitoshi Hayano

223

3251

USE OF ACOUSTIC EMISSION TECHNOLOGY TO STUDY THE MECHANICAL BEHAVIOUR OF VARIOUS
SANDSTONES: GEOTHERMAL ENERGY
Shao, S.S., Ranjith, P.G. and Chen, B.K.

229

3262

UNCONFINED COMPRESSIVE STRENGTH OF CEMENT TREATED SOIL/RAP MIXTURE
Jirayut Suebsuk, Aniroot Suksan, Suksun Horpibulsuk and Apichit Kumpala

235

3267

INVESTIGATION OF STRESS REDUCTION EFFECT ON STRUCTURE DUE TO BASEMAT UPLIFT USING
ENERGY CONCEPT
Takafumi Inoue and Atsushi Mikami

241

3271

SWELLING DEFORMATION OF BENTONITE MIXED WITH INORGANIC MATERIALS IN ALKALINESOLUTION
Yuki Yokoyama and Kenichiro Nakarai

247

3274

USE OF FULLY SOFTENED VERSUS PEAK STRENGTH TO PREDICT THE CAPACITY OF FOOTINGS ONGEOSYNTHETIC REINFORCED SOIL
Melia K. Iwamoto, Phillip S.K. Ooi, Jennifer E. Nicks and Michael T. Adams

252

3296

THREE DIMENSIONAL FINITE ELEMENT ANALYSIS OF SOIL NAILS IN GRANITIC SOILS
G. Ren and H. Tokhi

258

3298

SIMPLIFIED DYNAMIC AXIAL HEAD PILE STIFFNESS IMPROVEMENT ANALYSIS FOR EXISTING PILED
VIADUCT WITH BASE REINFORCEMENT
Aglipay Mary Roxanne and Konagai Kazuo

262

3312

PFC3D NUMERICAL EXPERIMENTS OF SELF-BORING IN-SITU SHEAR PRESSURE-METER MODEL TEST
Yafei Zhang, Guangli Xu and Jidong Teng

268

vi

3318

DYNAMIC ANALYSIS OF SLOPE FAILURE USING THE MESH-FREE SPH METHOD
N. Hiraoka, A. Oya, Ha H. Bui, P. Rajeev and R. Fukagawa

274

3320

ELECTRICAL RESISTIVITY TOMOGRAPHY TO INSPECT BRIDGE FOUNDATIONS
Helsin Wang, Chih-Hsin Hu, and Chung-Yue Wang

280

3323

ULTIMATE BEARING CAPACITY ANALYSIS OF GROUND AGAINST INCLINED LOAD BY TAKINGACCOUNT OF NONLINEAR PROPERTY OF SHEAR STRENGTHDu N L, Ohtsuka S, Hoshina T, Isobe K, and Kaneda K

286

3326

PREDICTION OF SLOPE DEFORMATIONS BY ELASTIC WAVE VELOCITIES IN RELATION TO LANDSLIDEFAILURES
Muhammad Irfan and Taro Uchimura

292

3329

BOX-SHAPE RETAINING WALL SYSTEM: EXPERIMENT AND NUMERICAL PREDICTION
C.T. Nguyen, Ha H. Bui, and R. Fukagawa

298

3343

PERMEABILITY AND CONSOLIDATION BEHAVIOR OF COMPOSITE GROUND REINFORCED WITH
SAND COLUMNS
B. A. Mir and Ashish Juneja

304

3347

LABORATORY EVALUATION OF PHYSICO-CHEMICAL VARIATIONS IN BENTONITE UNDERELECTROKINETIC ENHANCEMENT
Nasim Mosavat, Erwin Oh and Gary chai

310

3358

FLOW PATTERN FOR MULTI-SIZE SILOSYi Yang, Na Li, PengYin and YM Cheng

317

Construction Materials

322

3132

IMPROVING ENGINEERING PROPERTIES OF FINE-GRAINED SOIL WITH STEEL SLAG FOR USING IN
EMBANKMENT EARTHFILL
Je-Min Baek, Satoru Shibuya, Jin-Suk Hur and Tara Nidhi Lohani

323

3156

EVALUATION EQUATION OF DIFFUSION COEFFICIENT OF CHLORIDE ION FOR CRACKED CONCRETE
Junpei Saito and Satoru Shimobe

327

3160

OPTIMIZATION OF EFFECTIVE DEPTH OF COMPACTION FOR FINE-GRAINED SOILS
Girum Y. Yesuf, Inge Hoff and Jan Vaslestad

333

3197

COMPRESSIVE STRENGTH OF CEMENT PASTES EXPOSED TO ELEVATED TEMPERATURE AND
DETERIORATION MITIGATION
Abdoullah Namdar, Ideris Bin Zakaria and Gurumurthy Hegde

339

3201

PARTICLE SIZE AND OTHER FACTORS AFFECTING THE PULLOUT BEHAVIOR OF GEOCELLSEMBEDDED IN GRAVELLY SOIL BACKFILL
Xinye Han, Takashi Kiyota, Michiyuki Harata and Fumio Tatsuoka

345

3202

EFFECT OF LOADING RATE ON STRENGTH CHARACTERISTICS OF GRANULAR BASE COURSE
MATERIAL
Yuan Zhang, Tatsuya Ishikawa and Tetsuya Tokoro

351

3207

EXPERIMENTAL STUDY OF PLYWOOD COMPARING TO FOAM FILLED HONEYCOMB STRUCTURE
Phacharaporn Bunyawanichakul, Chattarin Sunsin, and Thammakorn Sasanawin

357

3249

X-RAY IMAGE ANALYSIS OF POROSITY OF POROUS CONCRETES
Jaehun Ahn, Jinwoo Jung and Seungbae Kim

363

ID

vii

3252

STRESS - STRAIN BEHAVIOUR OF SLAG CEMENT CONCRETE
Mustapha Boukendakdji

367

3256

ESTIMATION AND EXPERIMENTAL STUDY ON DIVERSION LENGTH OF CAPILLARY BARRIER USING
CRUSHED SHELL PARTICLESKazunobu Matsumoto, Kaoru Kobayashi , Satoru Nakafusa and Toshihiro Morii

373

3268

EXPERIMENTAL STUDY OF CONCRETE AND MORTAR MIXING WASTE TIRE RUBBER
Man-Kwon Choi, Yuki Hasegawa, Shushi Sato, Shinsuke Matsumoto and Hyeon-Tae Kim

379

3287

PILE DRIVING EFFECTS ON NEARBY BUILDING
Adhilla Ainun Musir and Abdul Naser Abdul Ghani

384

3317

LABORATORY STUDY ON THE PERFORMANCE OF RECYCLED CONCRETE AGGREGATES BLENDED
WITH RECLAIMED ASPHALT PAVEMENT AS A PAVEMENT GRANULAR MATERIAL
S. Jayakody, C. Gallage, J. Ramanujam, A.Kumar

389

3322

BEHAVIOR OF PENETRATION AND LEACHING OF CESIUM IN MORTAR HAVING VARIOUS FINE
AGGREGATES AND MOISTURE CONTENT
Masashi Ito, Kenichiro Nakarai Akihiko Hayashi and Kenji Kawai

394

3324

EFFECTS OF COARSE AGGREGATE CONTENT ON THE EROSION RATE OF CONCRETE DUE TO
SULFURIC ACID ATTACK
Yuji Hatano, Yutaka Okame and Kenji Kawai

400

3357

STUDY ON PHYSICAL PROPERTIES AND USABILITY OF SOME SELECTED RECYCLED FINE
AGGREGATESMohammad Raihanul Islam, Satoru Ishiguro

406

ID

Environment

410

3145

COMPUTER MODELING AND ANALYSIS OF THREE PHASE INDUCTION MOTOR UNDER TEMPORARYSHORT CIRCUIT FAULT IN STATOR USING WAVELET TRANSFORM
Dicky Nova Wardana, Dimas Anton Asfani, Ardyono Priyadi, and Mauridhi Hery Purnomo

411

3147

ANALYTICAL SOLUTION TO CONTAMINANT EXTRACTION CONSIDERING SMEAR EFFECT
H.Y Wang , X.W Tang and B. Bai

416

3152

MECHANISM OF C6H6 OXIDATION IN THE THREE-WAY CATALYTIC CONVERTER EQUIPPED AGASOLINE ENGINE
Akio Takigawa, Akihiro Mieda and Yongzhen Peng

422

3177

ROLE OF CURBSIDE CRACK OF ROAD IN URBAN BIODIVERSITY
Taizo Uchida, Xue J. Huan, Daisuke Hayasaka, Teruo Arase, William T. Haller and Lyn A. Gettys

427

3185

DYE TRACER EXPERIMENTS FOR IDENTIFYING SOLUTE DISPERSIVITY IN UNSATURATED POROUS
MEDIA
Kazuya Inoue, Takayuki Fujiwara and Tsutomu Tanaka

433

3188

REUSE OF AGRICULTURAL AND FOOD RESIDUES FOR RETARDING AND ATTENUATING NITRATE IN
POROUS MEDIA
Kazuya Inoue, Saki Matsuyama and Tsutomu Tanaka

439

3196

MICROSCOPIC RANGE OF IMMOBILIZATION BETWEEN HEAVY METALS AND AMENDMENT IN SOIL
THROUGH WATER MIGRATION
Shouhei Ogawa, Masahiko Katoh and Takeshi Sato

445

3198

SUB-DARCY-SCALE MODELING OF NON-UNIFORM FLOW THROUGH POROUS MEDIA WITH MIXEDWETTABILITES
Junichiro Takeuchi, Takuya Takahashi, and Masayuki Fujihara

452

viii

3218

3222

3224

3243

3244

CAPTURING PEDESTRIAN MOVEMENT SAFETY AND SECURITY ISSUES AT MAJOR TRANSPORTATIONINTERCHANGES
Zulfadly Azizi Bohari, Syahriah Bachok and Mariana Mohamed Osman
ASSESSMENT OF CHROMIUM CONTAMINATION IN SEDIMENTS OF SOUTHERN KAOHSIUNG
HARBOR, TAIWAN
Cheng-Di Dong, Chih-Feng Chen and Chiu-Wen Chen
GPS/GIS IDENTIFICATION OF POTENTIAL BUS STOP LOCATIONS AND PASSENGER’S ACCESS AND
EGRESS POINTS
Syahriah Bachok, Zakiah Ponrohono, Mariana Mohamed Osman, Zulfadly Azizi Bohari
GEOCHEMISTRY OF PALEOGENE RED BEDS IN THE NORTHERN IRAQ FORELAND BASIN: EVIDENCE
FOR PROVENANCE
Muatasam Hassan, Brian G. Jones, Ali Ismail Al Jubory, Sabah Ahmed Ismail,Abdual Salalm Mehdi Saleh
DEVELOPMENT OF BASE MATERIALS FOR SEAWEED BEDS USING VOLCANIC ASHES AND RECYCLING
MATERIALS OF INDUSTRIAL WASTESK. Yamamoto, T. Negami, T. Nakajima, H. Yano, Y. Futsuhara and K. Shima

458

464

469

475

481

3247

CARBON FOOTPRINT AWARENESS – AN INVESTIGATION FROM TRAVEL DIARY SURVEY
Nur Sabahiah Abdul Sukorand Nur Khairiyah Basri

487

3248

OPTIMAL MONITORING NETWORK DESIGN FOR EFFICIENT IDENTIFICATION OF UNKNOWNGROUNDWATER POLLUTION SOURCES
Om Prakash and Bithin Datta

493

3257

SPATIAL DISTRIBUTION CHARACTERISTICS OF SUBTERRANEAN HOT WATER EVALUATED USINGWATER QUALITY CONCENTRATION DATA
Takamitsu Kajisa, Si Senfi, Yasunori Mori, Homayoon Ganji, Abdul Saboor Rahmany, Masaaki Kondo
and Hajime Narioka

3258

IDENTIFICATION OF POLLUTANT SOURCE CHARACTERISTICS UNDER UNCERTAINTY IN
CONTAMINATED WATER RESOURCES SYSTEMS USING ADAPTIVE SIMULATED ANEALING AND FUZZY
LOGIC
Mahsa Amirabdollahian and Bithin Datta

505

3270

POINT-BASED RENDERING FOR MASSIVE POINT CLOUD VISUALIZATION
Masafumi Nakagawa

511

3325

REDRAWING AN UNKNOWN MASONRY CAISSON BY GEOPHYSICAL METHODS
Ming-Hung Chen, Shun-Min Lee, Yung-Chuan Chou, Yao-Jen Hsu and Chih-Hsin Hu

517

3335

CONTRIBUTION OF GEOLOGICAL MAPPING AND NEW TECHNOLOGIES TO THE IDENTIFICATION OF
A MAJOR, PRE-EXISTING AND ACTIVE FAULT OVER THE CAPITAL OF TUNISIA
Adnène Kassebi and Fouad Zargouni

523

499

3338

EFFECT OF GRAIN SIZE ON MINERAL CARBONATION OF COAL COMBUSTION FLY ASH FOR CO2
SEQUESTRATION
N. L Ukwattage and P.G Ranjith

530

3349

STUDY SEISMICITY PARAMETERS OF RUDBAR REGION AND SEISMOLOGICAL ASSESSMENT OF
RUDBAR-MANJIL (IRAN) EARTHQUAKE OF JUNE1990
Noushin Naraghi Araghi, Mohd. Nawawi and Syed Mustafizur Rahman

535

3351

UNDERSTANDING TO PREDICT SOIL BEHAVIOR
J. Rajaraman, K.Thiruvenkatasamy and S. Narasimha Rao

540

3356

CASE STUDY ON SHALLOW FAILURE OF CONGLOMERATE AND SILTSTONE SLOPES DUE TO A HEAVYRAINFALL
Satoshi Kagamiahra, Satoru Shibuya, Byeong - su Kim, Shunzo Kawajiri, Tara Nidhi Lohani and
Takashi Okimura

545

Authors index

551

Contents of GEOMATE 2011 – Volume 1(1) & 1(2)557

Contents of GEOMATE 2012 – Volume 2(1)

564

ix

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PrefaceOn behalf of the GEOMATE 2013 Organizing Committee, it is our great pleasure to welcome you to theInternational Conference on Geotechnique, Construction Materials and Environment held at the Meitetsu New
Grand Hotel, Nagoya, Japan organized in conjunction with Nagoya Institute of Technology, GEOMATEInternational Society, Japanese Geotechnical Society, AOI-Engineering, Useful Plant Spread Society, HOJUN
and Glorious International. On Friday 11 March 2011, at 14:46 Japan Standard Time, the north east of Japanwas struck and severely damaged by a series of powerful earthquakes which also caused a major tsunami. Thisconference was dedicated to the tragic victims of the Tohoku-Kanto earthquake and tsunami disasters. Since
this is the third conference in this series, we have received a lot of positive feedback from the participants.
The conference covers three major themes with 17 specific themes including:●
Advances in Composite Materials●
Computational Mechanics●
Foundation and Retaining Walls●
Slope Stability●
Soil Dynamics●
Soil-Structure Interaction●
Pavement Technology●
Tunnels and Anchors●
Site Investigation and Rehabilitation●
Ecology and Land Development●
Water Resources Planning●
Environmental Management●
Public Health and Rehabilitation●
Earthquake and Tsunami Issues●
Safety and Reliability●
Geo-Hazard Mitigation●
Case History and Practical Experience
This year we have received many paper submissions from different countries all over the world, including
Albania, Algeria, Australia, Bahrain, Bangladesh, Belarus, Benin, Canada, China, Colombia, Czech Republic,
Egypt, Ethiopia, Germany, Hong Kong, India, Indonesia, Iran, Iraq, Japan, Kenya, Libya, Malawi, Malaysia,
Norway, Poland, Romania, Russia, Saudi Arabia, Singapore, South Korea, Sri Lanka, Sudan, Taiwan, Thailand,
Tunisia, Ukraine, United Arab Emirates, United States and Vietnam. The technical papers were selected fromthe vast number of contributions submitted after a review of the abstracts. The final papers in the proceedings
have been peer reviewed rigorously and revised as necessary by the authors. It relies on the solid cooperationof numerous people to organize a conference of this size. Hence, we appreciate everyone who support as wellas participate in the joint conferences. Last but not least, we would like to express our gratitude to all theauthors, session chairs, reviewers, participants, institutions and companies for their contribution to GEOMATE
2013. We hope you enjoy the conference and find this experience inspiring and helpful in your professional
field. We look forward to seeing you at our upcoming conference next year.
Best regards,
Prof. Teruo Nakai, Conference Chairman
Dr. Md. Zakaria Hossain, Conference General Secretary
Dr. Hossain Md. Shahin, Conference Secretary
Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

x

Organization
Scientific Committees:
Conference Chairman: Prof. Dr. Teruo Nakai, Nagoya Institute of Technology, Japan
Conference Honorary Chairman: Emeritus Prof. Dr. Sohji Inoue, Mie University, Japan
Conference Organizing Committee:
Prof. Dr. Teruo Nakai, Nagoya Institute of Technology, Japan
Prof. Dr. Feng Zhang, Nagoya Institute of Technology, Japan
Prof. Dr. Kenichi Maeda, Nagoya Institute of Tech., Japan
E/Prof. Dr. Sohji Inoue, Mie University, Japan
A/Prof. Dr. H.M. Shahin, Nagoya Institute of Tech
A/Prof. Dr. Zakaria Hossain, Mie University
National Advisory Committee:
Prof. Dr. Fumio Tatsuoka, Tokyo University of Science, Japan
Prof. Dr. Toshinori Sakai, Mie University, Japan
Prof. Dr. Masaki Nakano, Nagoya University, Japan
Prof. Dr. Toshihiro Noda, Nagoya University, Japan
Prof. Dr. Jing-Cai Jiang, University of Tokushima, Japan
Prof. Dr. Noriyuki Yasufuku, Kyushu University, Japan
Prof. Dr. Masuya Hiroshi, Kanazawa University, Japan
Prof. Dr. Toshihiro Morii, Niigata University, Japan
Prof. Dr. Nishimura Tomoyoshi, Ashikaga Inst. of Tech., Japan
Prof. Dr. Yoshihiro Kimura, Tohoku University, Japan
Prof. Dr. Kimitoshi Hayano, Yokohama National Univ., Japan
A/Prof. Dr. Kenichiro Nakarai, Hiroshima University, Japan
International Advisory Committee:
Prof. Dr. Sai Vanapalli, University of Ottawa, Canada
Prof. Dr. M. Bouassida, National Sch. of Engg. of Tunis
Prof. Dr. L.R. Austriaco, Angles Univ. Found., Philippines
Prof. Dr. A.S.M. Abdul Awal, Univ. Technology Malaysia
Prof. Dr. M. Ibn Ibrahimy, Int. Islamic Univ., Malaysia
Prof. Dr. Md. Zahurul Islam, BUET, Bangladesh.
Prof. Dr. Bujang B.K. Huat, Univ. Putra Malaysia
Prof. Dr. Nemy Banthia, UBC, Canada
Prof. Dr. Ian Jefferson, Univ. of Birmingham, UK
Prof. Dr. John Bolander, Univ. of California, USA
Prof. Dr. Shamsul Chowdhury, Roosevelt Univ., USA
Prof. Dr. Isabel Pinto, University of Coimbra, Portugal
Prof. Dr. Mark Jaksa, University of Adelaide, Australia
A/Prof. Dr. Mohamed Shahin, Curtin University, Australia
A/Prof. Dr. Jim Shiau, Univ. of Southern Queensland Toowoomba
A/Prof.. Dr. Hj. Ramli Bin Hj. Nazir, UTM, Malaysia
A/Prof. Dr. Aly Ahmed, Beni-Suef University, Egypt
Dr. J.N. Mukabi, President of Kenya Geotech Soc., KenyaxiConference Secretariat:
Dr. H.M. Shahin, Secretary, A/Prof. NIT, Japan
Dr. Zakaria Hossain, General Secretary, A/Prof. MU, Japan
Mr. Musahaq Ali, Assistant Secretary
Division of Environmental Science and Technology
Graduate School of Bioresources
Mie University, 1577 Kurima Machiya-cho
Tsu-city, Mie 514-8507, Japan
E-mail: geomate@gi-j.com
Tel+Fax: +81-59-231-9578
Editorial Committee:
Dr. Md. Zakaria Hossain
Dr. Hossain Md. Shahin
Executive Committee:
A/Prof. Dr. Md. Zakaria Hossain
A/Prof. Dr. Hossain Md. Shahin
Prof. Dr. Teruo Nakai
E/Prof. Dr. Sohji Inoue
Mr. Musahaq Ali

Note- A: Associate, E-EmeritusxiiGEOMATE-Nagoya, Nov.13-15, 2013

Keynote Papers

1Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

GROUND DEFORMATION DURING AND AFTER EARTHQUAKES–SIMULATION AND PREDICTION BASED ON ELASTO-PLASTIC SOIL MECHANICSAkira Asaoka1
1

Association for the development of earthquake prediction, Japan
ABSTRACTSpecialization may be an unavoidable accompaniment to development in science but specialization that runs
to excess can actually hinder development. This paper tries to explain briefly how the current level of knowledgein civil engineering, particularly in geomechanics and geotechnical engineering, is useful in analysis andprediction of surface ground deformation caused by earthquakes. The paper is delivered under the two content
heads of “What are the difference between sand and clay?” which will be the introduction of the advanced SYS
Cam-clay constitutive model, and “four application examples” in which subsurface ground deformation during
and after an earthquake. All calculations in this paper have been performed using a single analysis tool i.e.,
GEOASIA.
Keywords: Elasto-plastic soil mechanics, Seismic response analysis, SYS Cam-clay model, GEOASIA
mixed phases, the soil skeleton and pore water. To
deal with the stresses in this case, they are divided
into two types. One is the pore water pressure
mentioned above and the other is the effective stress,
which is obtained by subtracting the pore waterpressure from the stress (total stress). It is thevariations in the effective stress that produce thechanges in the state of deformation of soils (theprinciple of effective stress).
Volume changes in soil is dependent on waterand air, moving in and out of its pores. Suchmovements are, of course, due to variations in theeffective stress that acts on the soil skeleton.
Consider sand that has been placed into a tea can sothat it is deposited loosely at the bottom of the can.
No one would try to compress the sand by placing acircular disc weight on top of it. The sand would
remain almost uncompressed by the forces producedby such a weight. However, if the side of the can istapped lightly so as to subject the sand to marginal
cyclic shear forces, the sand will exhibit large
compression. This is known as “compaction”.
Compaction is characterized by the fact thatcompression occurs although there has been no
increase in the effective stress p (i.e., no increasein the forces acting on the sand). This compressionis plastic compression because the sand, once it has
been compressed, will not loosen even if tapping isthen applied from the opposite side of the can. In theabove example, the sand is dry and only air exists
within the pores. If the pores are saturated withwater, liquefaction will occur first. After that,
accompanied by the drainage of water, consolidation
settlement will occur because of recovery of selfweight by the sand. Because of the difference in thehistory of effective stress experienced, there is a

INTRODUCTION
This paper tries to explain briefly how thecurrent level of knowledge in civil engineering,particularly in geomechanics and geotechnicalengineering, is useful in analysis and prediction of
surface ground deformation caused by earthquakes.
The essence of geomechanics and the elasto-plastic
constitutive equation of soils are outlined first in
Sections 1 and 2 so as to make it easy to read andunderstand Section 3, which deal with grounddeformation due to earthquakes. Although only themechanics of saturated soils are discussed here, theauthor believes that this is quite sufficient for the
purpose.
Whether it be sand or clay, soil consists ofnumerous soil particles forming a skeleton structure,and the pores are filled with water (in case ofsaturated soil). By themselves, both soil particles
and pore water cannot be compressed by the forcesthat are encountered in civil engineering andarchitecture. However, accompanied by expulsion of
the pore water, the soil skeleton structure will easily
undergo large compression when it is subjected toexternal forces. Vice versa, it can also exhibit large
expansion by absorbing water into the pores. In suchcases, since the pore water movement will tend to
conform to Darcy’s Law of potential flow, themechanics of saturated soil essentially possess thequality of being non-localized. To put it differently,
saturated soil is a material in which any volumetricchange in the soil skeleton is constrained by the
incompressible pore water, and the reaction to thisconstraint force appears as (excess) pore waterpressure. The mechanical behavior of saturated soil
is described by the continuum mechanics of the two2GEOMATE-Nagoya, Nov.13-15, 2013that deals with “overconsolidation.”) In fact,
although its state is different from that of sand, clay
also possesses a structure. This is depicted in Fig. 2.
Along with the progress of plastic deformation, thedeveloped structure of naturally deposited clay
collapse gradually until the compression line
overlaps from above the normal consolidation line ofclay that has been remolded and has lost its structure.
The entire behavior can be explained by introducing
the concept of a superloading surface1), 4), which lies
outside the normal yield surface and is similar to it
in shape with respect to the origin as shown in Fig. 3.
In Fig. 3, p and q are the mean effective stressand deviator stress, respectively, which are definedby the effective stress tensor T  ((tension positive)
and the deviator stress tensor S as p   trT  3 ,q  3 2 S  S and S  T   pI . Although thenormal yield surface is described by the modified
Cam-Clay model5), its explanation is omitted here
because anisotropy is not brought up as a topic inslight difference between the amount of compression
in dry sand due to compaction and the amount ofcompression in saturated sand after liquefaction. But
all in all, the level of difference is small. Therefore,
it can be said that compaction and liquefaction arecontrasting phenomena that are dependent only on
whether volume change is permitted or not during
cyclic shear. The compaction behavior of loose sandis illustrated in Fig. 11) by the calculation of
responses using the elasto-plastic constitutive
equation that is described later in this paper. It canbe observed that large compression has occurred
after the first few cycles.
Next, consider the situation that clay saturated
with water, somewhat like Japanese bean jelly, isplaced in the tea can instead of sand. In this case,lightly tapping the side of the can would have no
meaning. The only way of compressing the clay is toplace a porous disc on top of the clay, place a heavy
weight on top of that disc, and then wait a sufficientamount of time for the water to seep out. This typeof compression is called “consolidation”. Unlike
compaction, an increase in the effective stress p isindispensable for compression to occur by
consolidation. That is to say, the force needs to be
applied continuously for a certain length of time.
As described above, sand and clay behave quite
differently. Then, is there no consolidation of sandor no compaction of clay? How should one think
about compaction and consolidation for theintermediate soils?

400

q

q=Mp

Deviator stress q (kPa)

Deviator stress (kPa)

200

0

–q

q=–Mp

Void ratio e

–200
0
200
400
M ean effective stress p(kPa)
1.2

DIFFERENCE BETWEEN SAND AND CLAY
If it were possible to describe the behavior ofboth sand and clay within the same framework usingelasto-plastic mechanics, it would permit to describe
the elasto-plastic behavior of the many intermediatesoils that actually exist in a state between sand andclay too. The reason why there is no necessity todeal with sand and clay separately is that theconcepts
ofboth“structure2), 3)”
and“overconsolidation” are common to sand and clay. It
was only in 1997 that the concept of structure, which
had been an intuitive concept until then, wassuccessfully described through elasto-plastic
mechanics. This paper explains first the concepts ofstructure and overconsolidation using the mostrecent elasto-plastic constitutive equation of soils
named the SYS Cam-Clay model1), 4) and thenproceeds to clarify the differences between sand andclay.
The compaction of loose sand illustrated in Fig.
1 occurs because the highly developed structure of
the soil skeleton is destroyed rapidly by plastic
deformation accompanied by cyclic shear. (It may
appear strange for plastic deformation to occur due
to cyclic loads of the same amplitude. How this
could be understood is explained in a later section

[1]
1.0

0.8

[2]
[3]
[4]

NCL
CSL

[5]

0
200
400
M ean effective stress p(kPa)

[4]
[3]

200

q=Mp

[5]

[2]
[1]
0
0
200
400
M ean effective stress p(kPa)[1] Loose sand
n=1, e=1.065
OCR≒1.11[2] M edium loose sand
n=5, e=0.981
OCR≒1.7[3] M edium dense sand
n=13, e=0.918
OCR≒4[4] Dense sand
n=20, e=0.887
OCR≒6[5] Very dense sandn=125, e=0.776
OCR≒50Fig. 1 Compaction of loose sand and various typesof undrained shear behavior exhibited by the same
sand with different densities

Fig.2 Compression behavior of naturally depositedclay with well-developed structure3

GEOMATE-Nagoya, Nov.13-15, 2013

this paper. Along with the collapse/decay of thestructure due to progress of plastic deformation, thesuperloading surface gradually moves from theoutside to overlap the normal yield surface.
Therefore, the similarity ratio R* ( 0  R*  1 ) of thesuperloading surface to the normal yield surface
approaches 1 gradually from lower values as theplastic deformation progresses. The structure,
expressed by R* , indicates the bulkiness of the soil
skeleton. The collapse/decay of structure isaccompanied by the loss of bulkiness, that is to say,plastic compression (see Fig. 2). This corresponds tothe saying, "The structure falls apart like a house ofcards, and the soil undergoes massive compression."
Overconsolidation and loss of overconsolidation
are explained next. In the table within Fig. 1, theoverconsolidation ratio (OCR, described below) has
become larger along with the degree of compaction.
This is because, with the current stress levelremaining the same, sand shows an elasto-plastic
response for each repeated load during cyclicloading, which leads to expansion of both thesuperloading and normal loading surfaces. In otherwords, because of compaction/cyclic shear, the sandis in a condition that is apparently the same as thatreached by massive unloading from a very highlypressurized state. As explained above, the fact thatsoil that has undergone unloading once
(overconsolidated soil) exhibits an elasto-plastic
response and not an elastic response when it isreloaded is as important as the concept of structure.
This is illustrated in Fig. 4 using the compression
curve for clay.
If, during reloading from the unloaded(overconsolidated) state, the soil exhibits only anelastic response (i.e., if the symbol ■ were tooverlap ○ ), which is the basis of the old elastoplastic theory, there would be no accumulation ofplastic deformation due to cyclic loading. This
would mean that nothing will happen to the soil due
to an earthquake. The above is the reason why theelasto-plastic response of the soil during reloading isimportant, and it can be expressed by introducing
again a subloading surface6) (Fig. 3), which lies
inside the superloading surface and is similar to it inshape with respect to the origin. The current stressalways lies on the subloading surface. The unloaded
soil, which is in an overconsolidated state, graduallyloses its overconsolidation with the progress ofplastic deformation during reloading, and thesubloading surface gradually moves from the inside
to overlap the superloading surface to approach thestate of normal consolidation. This is always
accompanied by plastic expansion as shown in Fig.
5. The expansion phenomenon corresponds to thesaying, “Soil will exhibit large expansion when thestrong forces of engagement between the soil
particles are relaxed.” The level of overconsolidation
is expressed by the similarity ratio R ( 0  R  1 , Fig.

3) of the superloading and subloading surfaces. The
inverse of R is the overconsolidation ratio OCR
shown within Fig. 1.
Naturally deposited soils, whether sand or clay,
have developed structures and are more or less in an
overconsolidated state. These can be considered toqq = Ma p

Superloading
yield surface
~ ~

– –
(p,
q)

(p, q )(p, q )Axis of rotationq = p
Subloading yield surface

0

~
p
0

p
Cam–Clay yield surface(Normal yield surface)

–q

~
p
q~
R* = —
– =—
p q–

p q
R=—
– =—
p
q–

Fig. 3 Three yielding surfaces of the SYS CamClay Model

Fig. 4 Elasto-plastic behavior during reloading

Fig. 5 Plastic expansion resulting from loss ofoverconsolidation
4

GEOMATE-Nagoya, Nov.13-15, 2013

be living soils. When a living soil undergoes plastic
deformation, collapse/decay of structure will
progresses ( R*  1 ) while compression occurs, orloss of overconsolidation will progress while
expansion occurs ( R  1 ). This gives rise to thefollowing straightforward question: for a given unitof plastic deformation, which is faster, the decay ofstructure or the loss of overconsolidation? The
difference between sand and clay lies in this aspect.
To answer this question first, even a slight plastic
deformation causes very rapid decay/collapse ofstructure in sand, whereas loss of overconsolidation
is extremely slow. Very large plastic deformationthat is quite unlikely to occur in a practical situation
would be required for sand to reach the state ofnormal consolidation. On the other hand, clay is thecomplete opposite of sand. Under even slight plastic
deformation, loss of overconsolidation occurs
rapidly in clay, and it will approach the state ofnormal consolidation (in Fig. 4, ■ is close to ○).
However, its structure will not collapse easily. A
large plastic deformation would be required to cause
decay of structure in clay. The above is illustrated inFig. 6. If someone ask which is faster, the answer
would be that it is a matter of level. It is likely that
there would be soils that exhibit the same level of
rapidity or the same level of slackness. In otherwords, between sandy soils and clayey soils, there isvarious number of real soils, as represented by thecolor gradation in Fig. 6.
Consider the case of liquefaction of sandy soil in
Fig. 6. In sand, the structure collapses first, and large
plastic volumetric compression occurs during thisstage. Under cyclic shear during earthquakes, etc., if
there is not sufficient time for the pore water toescape, the collapse of structure occurs nearly under
undrained conditions (constant volume conditions),
and large elastic expansion is necessary tocompensate for the plastic compression. Elastic
expansion is related to the mean effective stress p .
Since the total stress (pore water pressure + effective
stress) remains nearly constant during an earthquake,the pore water pressure will increase steadily, andthis increase will continue until the effective stressp approaches zero. In other words, liquefaction ofthesand
occurs.
Theaccumulationofoverconsolidation during cyclic shear loading causedby an earthquake is the same as the phenomenon ofcompaction shown in Fig. 1. In sand, for the state ofoverconsolidation to return after the earthquake tothe original state of effective stress (near the state ofnormal consolidation) while recovering its own
weight, large plastic deformation is necessary (inFig. 4, ■ is far removed from ○). It is for thisreason that the amount of consolidation settlement ofsand after liquefaction is larger than what would
usually be expected. It is only through these twoconcepts of structural decay and loss ofoverconsolidation that one is able to obtain a

Sandy soils

Clayey soils
Structured, andoverconsolidated state

Almost non-structured,but
overconsolidated state

Plastic
deformation

Still structured, butalmost normallyconsolidated stateNon-structured, andnormally consolidated stateFig. 6

Differences between sand and clay

continued understanding of not only compaction ofsand but also the phenomena of liquefaction ofsaturated sand and the subsequent large settlementthat occurs in it.
Next, consider the behavior of clay in Fig. 6. A
slight plastic deformation causes a clayey soil to first
approach the state of normal consolidation (in Fig. 4,■ is close to ○). This is followed by gradualdecay/collapse of structure accompanied by large
plastic deformation. Of course, the decay ofstructure is accompanied by large compression as in
the case of sand. However, since the permeability ofclay is less than 1/100,000th of that of sand, the timerequired for compression to occur is long.
Furthermore, the delay in compression is aggravatedby the decrease in rigidity that results from structural
decay. These phenomena were referred to as“delayed compression/secondary consolidation” inthe past. “Secondary consolidation” tends to takeplace in the loading range that straddles the states ofoverconsolidation and normal consolidation, and in
addition, the time required for large settlement to

Fig. 7 Attainment of a high degree of structureduring plastic expansion
5

GEOMATE-Nagoya, Nov.13-15, 2013

occur is very long. These phenomena can beunderstood fully only by recognizing that both lossof overconsolidation and decay/collapse of structure
take place at a sluggish pace7). In addition, from thefact that decay/loss of structure is a phenomenoncommon to both sand and clay, it can be understoodthat compaction/liquefaction of sand is the same
phenomenon as delayed compression/secondary
consolidation of clay. It would be correct to say that thephenomena of compaction/liquefaction of sandy groundand delayed compression/secondary consolidation that
continues forever in clayey ground occur only because allthese soils are still living soils that possess structure andare in a state of overconsolidation. However, it would be
unfortunate if Fig. 6, which illustrates the concept ofliving soils, were to give one the impression that progressof plastic deformation takes the soils on a one-way pathleading to death only. It has been mentioned earlier thatthe state of overconsolidation is recovered by cycling
loads such as those caused by earthquakes.

Fig. 8 Pulsating wave in vertical direction observedon ground surface

Fig. 7 illustrates the cyclic mobility of sand intriaxial testing and the high ductility of naturally
deposited diluvial clay8). Both of these cannot be
replicated without the attainment of a high degree ofstructure during plastic expansion, i.e., without theregeneration of structure.

ANALYSIS
EXAMPLESOFGROUND
DEFORMATION DURING AND AFTER
EARTHQUAKES

Fig. 9 Normal waveform observed within groundThe so-called “trampoline effect”

1.6

1.6

1.4

During the 2008 Iwate-Miyagi Nairiku
earthquake, a strong earthquake motion (3component synthesis value: 4022 gal) was recordedon the ground surface at KiK-net station IWTH25(West-Ichinoseki) located almost directly above theepicenter. Aoi and his colleagues have stated that theaccelerometers on the ground showed clear
asymmetric pulsating waves in the vertical (updown) direction. They observed that the accelerationin the upward direction reached nearly 4000 gal,
whereas that in the downward direction was limited
only to 1 gal (See Fig. 8), and they named thisphenomenon the “trampoline effect”10), 11). On thesame ground surface, no pulsating waves wereobserved in the horizontal direction, and at a depthof 260 m, the tremors in the horizontal and verticaldirections were symmetric, as is normal, without any
asymmetric pulsations (See Fig. 9). As a result, theground surface rose up an additional 28 cm
compared with the ground interior, and the soil layeron the ground surface exhibited significant
expansion.
The ground’s surface layer is a terrace sedimentlayer of Tuffaceous sandstone in an air-dried
condition. Samples taken after the earthquake
showed that the soil in this layer consisted of

n=100

1.4

1.2

Void ratio e

Void ratio e

1.2

1.0

Loosening

1.0

0.8

0.8

0.6

0.4
-300

n=28

0.6

Compaction

-200

-100

0

100

200

300

0.4
-300

-200

-100

0

100

Shear stress  (kPa)Shear stress  (kPa)(a) Compacton(b) Loosening

200

300

Fig. 10 Compaction of sand and the loosening that
follows it
crunchy porous gravel mixed in sand. Focusing
attention on this layer (thickness=approx. 20 m), theswelling that appeared on the ground surface in thevertical direction due to the nonlinear response to
the horizontal cyclic shear that it was subjected to is
replicated here using elasto-plastic geomechanics.
That the above replication is not difficult can beunderstood from Fig. 10, which illustrates at thelevel of elements the constitutive equation responseof sand during compaction and the subsequent“loosening” that occurs.
During compaction, the first few cycles produce
6GEOMATE-Nagoya, Nov.13-15, 2013as an elasto-plastic body. It needs to be added that
according to the results of the calculations, thetrampoline effect appears in the high frequency
range above 10 to 100 Hz, and that is in agreementwith the actual observations made at the site10).

Post-seismic slope failure
The phenomenon of expansion of the ground
during earthquakes such as the trampoline effectdescribed above is rare. However, there are many
instances of ground deformation that are caused byplastic expansion occurring in compacted soils andembankments due to earthquakes. A number ofembankments built on inclined ground along
highways and other locations in Japan collapsed
during the Chuetsu, Noto Hanto, Chuetsu-Oki, andSuruga Bay Earthquakes. In many of these instances,the collapse occurred not during the earthquake but
after a period of delay ranging from tens of minutes
to a few hours following the earthquake. Sliding of
the valley fill embankment at Takarazuka occurred
only on the day after the Great Hanshin-Awaji
Earthquake. A computational replication of thedelayed collapse of an embankment built on inclined
ground along the Noto toll road during the 2007
Noto Hanto Earthquake is presented here as an
example13). Although the inclined ground, which
was composed of tuff breccia, did not deform during
the tremors, embankment that had been built withcrushed tuff stone suffered extensive damage. A partof the computed replication is shown in Fig. 12.
From the shear strain distribution within theembankment approximately 10 seconds after
earthquake occurrence soon after the main motion,some slippage between the incline and theembankment is observed, but no abnormality is seenin the embankment body. After sufficient time has
elapsed after earthquake occurrence, the slip shapeexhibited by the embankment body is a traditional

Fig. 11 Comparison of the results obtained throughanalysis with observed results
large compression. However, as can be seen in Fig.
10, when sand that has been compacted once issubjected to horizontal cyclic loading with greater
amplitude than previously, the sand will not loosen
in the beginning, but does so suddenly during thelast few cycles. Utilizing the above results asbackground knowledge, the soil layer was extracted
horizontally, and the horizontal component only of
the seismic wave that had been observed at a depthof 260 m was input at the extracted layer’s bottom
surface. Figure 11 is a comparison of the results ofanalysis with the results of actual measurements.
(Material constants, initial conditions, otheranalytical conditions, and a discussion can be foundin reference 12.)
Although quantitative comparison is insufficient,
there is very close resemblance between theobserved results and the results of analysis withrespect to the “asymmetry” of the acceleration
waveform at the ground surface in the verticaldirection (U-D direction). The observed andcalculated results both show that the acceleration in
the downward direction does not exceed 1 g. Thismay be thought to be logical for soil that cannot
withstand tension, but the result is a natural outcomeof the computational boundary condition of notallowing expansion of the ground in the downward
direction. In the calculated results, the magnitude of
the vertical component of the upward acceleration issomewhat small but becomes a little larger if theactuallymeasured verticalcomponent ofacceleration is added to the seismic wave motionthat was input at the bottom surface of the layer.
What is important is to observe that although only
the horizontal component of the seismic wave was
input, the response motion of the ground surface inthe up-down direction is larger than what was input.
Dilatancy, which is never seen in elastic bodies anddoes not appear in the case of metal plasticity either,is a type of plastic deformation that is unique to soil

Fig. 12 Delayed failure of an embankment on
inclined ground (shear strain distribution)
7

GEOMATE-Nagoya, Nov.13-15, 2013

circular slip. Since a circular slip is a type of failurethat is caused by the weight of the soil acting in thevertical direction and does not occur if there areinertial forces, the lower figure in Fig. 12 clearly
indicates that the failure occurred after theearthquake ended. During the earthquake, because of
the large cyclic shear produced on the incline, plastic
expansion tends to occur in the embankment
material (compacted sand gravel). However, since
replenishment of water and air in the soil pores is
not possible within the very short duration of thetremors, there is not sufficient time to allow
volumetric expansion of the soil to take place. For
this reason, large elastic compression is generated
during the earthquake, and the effective constraintpressure on the soil skeleton increases. As a result,the embankment does not fail during the quake.
Therefore, it is only after the earthquake thatembankment failure eventually occurs as a result of
the expansion (decrease of effective stress) that takes
place due to water/air absorption. Even now, morethan two years after the March 2011 earthquake,slippage and arrest of embankments, etc. have been
taking place repeatedly in the housing area on thehill behind Tohoku University. The surface soil ismade up of unsaturated soil. Study and clarificationof the mechanism of such delayed progressive
failures is one of the research tasks of The Japanese
Geotechnical Society’s concerted efforts in responseto the March 2011 earthquake14).

liquefaction. Based on initial studies made in the
Urayasu area, where there was much damage tohouses, the distinctive nature of this liquefaction
phenomenon is described very briefly in this section.
When compared with loose sand, whose

Fig. 14 One-dimensional seismic response analysis
based on the ground’s geological profile

Liquefaction phenomenon in Urayasu
The March 2011 earthquake caused liquefaction
to occur in wide areas centered on the reclaimed
land along the Tokyo Bay. Not only the groundsurface deposit of naturally deposited alluvial sandbut also the soil layer above it, which containedlarge amounts (20 to 60%) of fine fraction (clay, silt),
was liquefied extensively, and the amount of sandboil was great15). Although the acceleration on the
ground surface was less than 100 to 200 gal, the long
duration of the earthquake led to the extensive
Liquefaction

point A0

0.00

Reclaimedsoil-10.00Alluvial
sand-20.00Alluvial
clay

0

25 50

point
C
A地点

point B

標高
B地点
TP(m)

0

25 50

25 50
0

25 50

0

0.00

埋土
沖積砂

-10.00-20.00沖積粘土-30.00

標高
TP(m)

25 50

Excess pore water pressure ratio

No-liquefaction

Fig. 15 Horizontal acceleration responses andFourier amplitude spectra after the seismic wave
passed through the alluvial clay layers-30.00Diluvial layer-40.00-40.00-50.00-50.00-60.00-60.00

1

C
B
A

0.5

0
0

100

200

300

Time (s)Fig. 13 Cross-section showing the geological profileof the ground in Urayasu City

Fig. 16 Excess pore water pressure ratios at eachlocation
8

GEOMATE-Nagoya, Nov.13-15, 2013

thickens from about 10 m at location A, whereliquefaction damage was light, to about 50 m at
location C, where heavy liquefaction damage
occurred. Taking into consideration the above, the 1dimensional analysis illustrated in Fig. 14 was
carried out. The results are shown in Fig. 15. (Since
the soil properties of the backfill soil layer, alluvial
sand layer, and alluvial clay layer are still
provisional, the results shown in this figure arepreliminary.) It is seen that due to seismic motion

structure can collapse easily, accumulation of greater
plastic deformation is required to cause decay of thestructure in backfill soils that contain large fine
fraction. Therefore, if liquefaction extends up tosuch layers, it is expected that ① the seismic motion
input to this layer was a long-period wave and that
② the duration of the earthquake motion was long(i.e., the number of cycles was large).
Figure 13 outlines the geological profile in
Urayasu City. The bottom alluvial clay deposit

Fig. 17 Conditions for 2-dimensional analysis

Fig. 18 Shear strain and excess pore water pressure ratio distributions 300 sec after earthquake occurrence

Fig. 19 Acceleration responses at the interlayer boundaries in liquefied locations of the sloped layers
9GEOMATE-Nagoya, Nov.13-15, 2013engineering and architecture, “accurate prediction ofliquefaction is not possible anymore.” This is why
the author has stressed that the analysis ispreliminary. Please note that the effects ofaftershocks have not been taken into account here.

transmitted from the alluvial clay layer to the topliquefied layer, the longer-period components ofacceleration amplify as the clay layer thickness
increases. As depicted in Fig. 16, although the porewater pressure has peaked 120 to 130 seconds after
earthquake occurrence, liquefaction has not occurredat locations A and B. This result is inconsistent withthe actual liquefaction damage observed at Urayasu.
Therefore, 2-dimensional analysis was carriedout under the conditions set out in Fig. 17, although
the stratum organization was significantly simplified
for the analysis. It was assumed that the soil
properties were uniform along the horizontal
direction. Only the variation of the alluvial clay
layer thickness was taken into account. The
analytical results are illustrated in Figs. 18 and 19.
Figure 18 shows the conditions 300 sec after
earthquake occurrence. Liquefaction has occurred
widely from location A to location C, not only in the
alluvial sand layer, but also in the backfill soil layer
above it. Comparing Fig. 19 with the input seismic
waveform in Fig. 14, it can be observed that in the
120 sec before liquefaction occurred, the long-period
components in the above strata have been amplified
significantly—roughly four fold. It can also be seenfrom the acceleration responses of the groundsurface that at any point between locations A and C,
a wave with a period of about 20 sec has been
overlapped by another wave with a period of about 4
sec (figure omitted), indicating that these seismic
tremors were such that they could even cause sea
sickness (as some readers may have seen in
YouTube videos of the March 2011 earthquake). The
calculations also indicated that the amountconsolidation settlement occurring within 2 to 10
days after the earthquake in the liquefied layers
would be roughly 20 cm at location A and 50 to 60
cm at locations B and C, the settlement at location B
being the largest. These values too were in good
agreement with the actual amount of settlement that
occurred.
The degree of liquefaction damage to houses in
the area varied in a complex manner in thehorizontal direction. For this reason, the nonuniformity of the soil properties of the surface layer
has become a major issue at Urayasu. This, of course,
is true. However, the current analysis makes it clearthat the non-uniformity in the degree of liquefactionis heavily influenced even by a slight inclination of
the stratum as shown in Fig. 17. The ground surface
deformation shown in Fig. 18 is indeed quite uneven,and the ground surface accelerations obtained in thecourse of the calculations vary greatly by as much as
100 to 160 gal at locations that are just a few metersapart. More important than the above is thatcomparison of Figs. 16 and 18 should not makeanyone jump to the conclusion that 1-dimensional
analysis is without meaning. That would beequivalent to saying that in practical civil

Ground deformation resulting from delayedcompression of alluvial clay
Runway D at Haneda International Airport wasconstructed on reclaimed land and encountered the
March 2011 earthquake about a year after its
construction had been completed. Under the landfill
is a naturally deposited alluvial clay stratum that is
approximately 20-m thick. This stratum is subjected
to eccentric earth pressure from the landfill. There
was a possibility of structural decay in this clay
being promoted by cyclic shear. It has been
explained earlier that it takes time for deformation to
occur in clayey ground due to structural decay.
Figure 20 shows the predicted deformation of
Runway D at Haneda International Airport obtained
through analysis (details of the analytical conditions
are omitted).
To the right of Point 2, the runway is a pier type,and Point 2 is the interface that connects the runway
on the landfill with that on the pier. The amount ofsettlement at Point 2 is a few centimeters and hasnearly reached a steady state already. Calculations
indicate a lateral displacement of about 20 cm

Fig. 20 Prediction of future ground behavior ofHaneda Airport’s Runway D
10GEOMATE-Nagoya, Nov.13-15, 2013[6] Hashiguchi, K.: Plastic constitutive equations of
granular materials, Proc. of US-Japan Seminaron Continuum Mechanics and Statistical
Approaches in the Mechanics of GranularMaterials (Cowin, S.C. and Satake, M. eds.),
Sendai, JSSMFE, pp. 321-329, 1978.
[7] Noda, T., Asaoka, A., Nakano, M., Yamada, E.
and Tashiro, M.: Progressive consolidation
settlement of naturally deposited clayey soil
under embankment loading, Soils andFoundations, 45 (5), pp. 39-51, 2005.
[8] Noda, T., Asaoka, A., Nakai, K. and Tashiro,
M.: Structural upgradation in clay and sandaccompanying plastic swelling, Proc 13th AsianReg. Conf. on Soil Mech. Geotech. Eng., pp.
175-178, 2007.
[9] Noda, T., Asaoka, A., Nakano, M.: Soilskeleton-water coupled finite deformation
analysis based on a rate-type equation of motion
incorporating the SYS Cam-clay model, Soils
and Foundations, 48 (6), pp. 771-790, 2008.
[10] Aoi, S., Kunugi, T. and Fujiwara, H.:
Trampoline effect in extreme ground motion,
Science, Vol. 322, pp. 727-730, 2008.
[11] Aoi, S.: Discovery of asymmetric groundmotion and the “trampoline effect” (INJAPANESE), Science, Vol. 79, No. 4, pp. 366370, 2009.
[12] Asaoka, A., Sawada, Y., Noda, T., Yamada, S.
and Shimizu, R.: An Attempt to Replicate the
So-Called“Trampoline
Effect”
inComputational Geomechanics, Proc. of 15th
World Conference on Earthquake Engineering,
Lisbon, 2012.
[13] Sakai, T., Nakano, M.: Reproduction of largescale failure after an earthquake of anembankment on inclined ground through soilwater coupled finite deformation analysis (INJAPANESE), Japanese Geotechnical Journal, 7(2), pp. 421-433, 2012.
[14] Research Committee on Ground Deformation
Mechanisms (Chairman: Asaoka, A.) of theJapanese Geotechnical Society’s Investigative
Commission for Research Response to the Great
East Japan Earthquake.
[15] Yasuda, S., Harada, K., Ishikawa, K.: Damage
to structures in Chiba Prefecture during the2011 Tohoku-Pacific Ocean Earthquake (INJAPANESE), Japanese Geotechnical Journal, 7(1), pp. 103-115, 2012.
[16] Yamada, S., Takamori, T. and Sato, K.: Effects
on reliquefaction resistance produced bychanges in anisotropy during liquefaction, Soils
and Foundations, 50 (1), pp. 9-25, 2010.

towards the pier between now (1.5 years after theearthquake) and the next 20 years. The revetment
will slant about 1 degree towards the pier during thenext 20 years. Since the soil properties allotted to thelandfill were on the hazardous side, the calculated
value seems to be somewhat large. Even so, thislevel of deformation can be absorbed easily by
maintenance and repair operations in the future.
Although Urayasu is a painful contrast, the author
believes that virtually no damage was caused to
Runway D by the March 2011 earthquake.
CONCLUSION AND REMARKSThis introduction to geomechanics, in spite of
having taken up a few pages of space, paints only apart of the whole spectrum because it has limited
itself to soil structure and overconsolidation only
without touching on the evolution laws ofanisotropy. Anisotropy too, is closely connected to
re-liquefaction, which is an important issue16). At
long last, it has become possible to calculate surface
ground deformation during and after earthquakes.
However, as ground surfaces are the places of daily
activities of people and society, it may be natural toexpect that certain restrictions need to be applied on
the disclosure of the true picture of grounddeformation behavior and mechanism. Therefore,high-level engineering ethics would be expectedfrom research personnel too.
REFERENCES[1] Asaoka, A., Noda, T., Yamada, E., Kaneda, K.
and Nakano, M.: An elasto-plastic descriptionof two distinct volume change mechanisms ofsoils, Soils and Foundations, 42 (5), pp. 47-57,
2002.
[2] Mikasa, M.: On the significance of soil structure
in soil mechanics (IN JAPANESE), Proceedingsof the Annual Meeting of the JSCE, 1962.
[3] Mikasa, M.: A classification chart forengineering
properties
of
soils
(IN
JAPANESE), Tsuchi to Kiso, 12 (4), pp. 14-24,
1964.
[4] Asaoka, A., Nakano, M. and Noda, T.: Superloading yield surface concept for highly
structured soil behavior, Soils and Foundations,40 (2), pp. 99-110, 2000.
[5] Roscoe, K. H., and Burland, J. B.: On thegeneralized stress-strain behavior of ‘ wet ’clay, in J. Heyman and F. A. Leckie (eds.),
Engineering plasticity (Cambridge: Cambridge
University Press), pp. 535-609, 1968.

11

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

USE OF RECYCLED AGGREGATES FROM CONSTRUCTION AND
DEMOLITION WASTES FOR THE CONSTRUCTION OF FLEXIBLEPAVEMENTS
Márcio Muniz de Farias,1, Alejandra María Gómez Jiménez and Ferney Quiñones Sinisterra2
1
Faculty of Technology, University of Brasilia, Brazil; 2Universidad del Tolima, Colombia
ABSTRACTThe industry of civil construction generates huge amounts of wastes during the construction of new buildings
and the demolition or reformation of old structures. Construction and demolition wastes (CDW) comprise soils
from excavations, asphalt concrete from old pavement surfaces, and a large variety of material from buildings,
such as concrete, ceramics, sand and rock chips, gypsum boards, among others. These materials may be recycled
and reused for the construction of road pavement layers. This kind of application was chosen taking into accountthe large amount of materials required and the possible economic impacts. CDW was recycled to produce
aggregates that could be used as granular layers or asphalt concrete. The materials were used raw or mixed withother ingredients. The research shows the pros and cons of using recycled aggregates in different pavement
layers. The major problem is related to aggregate crushing and high porosity. Overall the research concludes forthe economic, environmental and technical feasibility of recycling construction and demolition wastes forpavement construction.
Keywords: Construction and Demolition Wastes, Recycled Aggregates, Flexible Pavements, Particle Crushing
porosity, particle crushing and heterogeneities. The
problem of particle crushing and its impacted ofsome relevant properties for the use of recycled
aggregates for the construction of flexible
pavements are analyzed in the following sections.

INTRODUCTION
The amount of construction and demolition
waste (CDW) generated in global and local levels
are significant. The volume of these materials isincreasing with the construction of new buildings
and the demolition of old structures that havereached their project life, or due to natural hazards
such as earthquakes, storms and floods andanthropic disasters like wars.
Around 300 million tons/year of CDW aregenerated in Europe, about 170 million tons/year in
the United States and 68 million tons per year are
produced in Brazil. The Federal District (Brasilia,
Brazil) has a daily production of 6000 tons,
equivalent to a production of 2.2 million tons/year.
The volume of CDW in Brazil has increased
dramatically in cities that will host the 2014 Soccer
World Cup due to the demolition of old stadiums
and the construction of new facilities, such as roadand airport expansions.
Innovation and development of wastes recycling
technology are necessary to make these materials
suitable for reuse. Applications of CDW, recycledconcrete aggregates (RCA), and reclaimed asphalt
pavement (RAP) in civil engineering works andinfrastructure are now common practice in many
countries [1]. Several researches show that CDW is
an attractive alternative material for bases and subbases of highway pavements due to its highresistance and its non-expansive behavior [2]-[5].
However, there are a few disadvantages such as high

CDW FOR GRANULAR BASE LAYERS
Typical construction and demolition wastes are a
mixture of reinforced concrete blocks, mortar,
plaster, ceramics, soils, steel, plastic, wood, ink andsolvents. Most of these can be recycled and thosewhich can be ground or directly used was granularmaterials are classified as class A for recycling
purposes according to the Brazilian environmental
regulation CONAMA N°307/2002. Class A
materials, subjected to other requirements, may be
used as sub-base and base layer in high pavements.
When the amount of granular material exceeds aminimum of 85%, besides other requirements to be
described later, the material is classified as recycled
aggregates and may even be used as component of
concrete mixtures.
Characterization of the CDW
The recycled material investigated in thisresearch was collected from wastes of the National
Soccer Stadium of Brasilia, which was imploded togive rise to a brand new stadium for the 2014 World
Cup in Brazil. For this study a representative sample
of about 1.6 tons of CDW aggregate was used for12

GEOMATE-Nagoya, Nov.13-15, 2013

In order to determine the composition of the
CDW used in this study, the coarse aggregate
fraction retained in the 4.75 mm sieve was examinedvisually and segregated manually. The CDW
aggregate was separated into four main groups: (i)cementitious materials (the major component of the
CDW aggregate, comprised mainly of concrete andmortar, 41%); (ii) crushed rock chips (about 15%);(iii) red ceramics (bricks and roof tiles, 1%); and(iv) white ceramics (floor and wall tiles, 1%).
The fine aggregate fraction, passing the 4.75 mm
sieve but retained in the 0.075 mm sieve (#200),
represented 42% of the total sample. Undesirable
materials retained in sieve #200 such as metals,
wood and plastic represented only a very small
proportion in weight of 0.6% of the total sample.
This value is far below the limit value of 3%
imposed by Brazilian standards for the use of
construction and demolition wastes in pavement
layers.

norm DNIT – ES 141/10.
All the results above comply with the minimum
requirements for the material to be used in granular
pavement layers. For base layers the norm requires aplastic index inferior to 6% and expansion inferior to
0.5%. The material is non-plastic and does not show
swelling characteristics. This is due to the lowamount of grains passing sieve #200, which shows
little contamination by silt and clay size particles.
This is corroborated by the good value (70%) ofsand equivalent ratio, higher than minimum norm
requirements of 30% for base layers.
In fact the grain size analysis with less than 15%
passing sieve #200 qualifies the material by
Brazilian standards as construction and demolition
aggregates (CDA) rather than wastes (CDW). The
additional tests (abrasion, shape, soundness) indicatethat the CDA can be considered even for
applications on asphalt concrete mixes to be used in
flexible pavement surface layers.
The low value of particle specific gravity is dueto the presence of ceramics chips and also mortar
adhered to the rock chips used in the Portland
cement concrete and wall rendering. These materials
are responsible for the high water absorption value
and the characteristic particle breakage to beanalyzed in the next sections.

Physical properties of the CDW used

Breakage of Particles from CDW

The physical properties of CDW used in thisresearch were determined using Brazilian (NBR)
and American (ASTM) standards. Tests like water
absorption, grain shape, grain-size distribution, sandequivalent, soundness and Atterberg limits wereused to determine the physical properties of therecycled aggregate and to define whether it was
suitable as base material for highway pavements.
The results are summarized in Table 1.

Research results from [3] show that the bulk of
CDW particle breakage occurs during compaction
process rather than other tests emulating service life.
In order to evaluate particle breaking the grain-size
distribution curves before and after the compaction
process were compared. Due to the expected
breakage, the initial grain size distribution was
adjusted to the so called envelope or “band C”,
prescribed by Brazilian code (DNIT – ES 141/10).
This envelope is commonly used for base and subbase materials in highways with medium to heavy
traffic volume.
The material was then compacted at its optimum
conditions determined using Modified andIntermediate Proctor energy (1263 kN.m/m3). The
laboratory compaction tests were performed
according to the American Standard procedure(ASTM D1557-07). The observed values of
optimum water content and maximum dry density
were 13.0% and 16.5 kN/m3, respectively, for theintermediate Proctor energy. Other water contents(8%, 10%, 14% and 19%) were also investigated tocheck the effect of this index on particle breakage.

the laboratory evaluation. Two grinding process
were necessary to obtain the CDW aggregate withthe desired grain size distribution required for thisinvestigation.
Composition of the CDW used

Table 1 Physical characteristics of CDW aggregates
Property
Value
Limit**
Uniformity coef. (Cu)61
≥ 10
% Passing sieve N°40
15
10-40
% Passing sieve N° 200
12%15%% of contaminants
0.56≤3Liquid limit %32≤ 25
Plasticity index %NP≤6Expansion %0≤ 0.5
Solid specific gravity, Gs
2.14 - 2.38
Absorption %7.7
Sand equivalent
≥ 70
≥ 30
Soundness in MgSO4 (%)
6.0 – 11.0*
30%
Shape Index
0.9 – 0.8
Los Angeles Abrasion (%)
35 – 38*≤55%
Note: * 1st value refers to tests performed on coarse(gravel) fraction and 2nd value to tests performed onfine (sand) fraction. ** Limits according to Brazilian

Index for CDW particle breakage
Reference [6] developed a measure of particle
breakage during the construction of earth androckfill dams. His method was originally based on
13

GEOMATE-Nagoya, Nov.13-15, 2013

breakage index and the same parameter decreases
with the increase in moisture content, as indicated by
the arrow in the figure.

large-scale triaxial compression tests and computes
the changes in individual particle sizes between theinitial and final grain size distributions. The
difference in the percentage retained is computed foreach sieve size. This difference will be positive or
negative. Marsal´s breakage factor (Bg) is the sum of
the differences having the same sign:

Bg   W  Wk
i
k

(1)
f

(1)

k

in which

Wki and Wk f are the initial (before

compaction) and final (after compaction)
percentages in weight retained in sieve “k”. Only
positive differences are considered in the summation
as indicated by the Mc Cauley bracket <x>. The
lower limit of Marsal’s index is 0% and thetheoretical maximum is 100%.
Results of particle breakage and Bg index
The original and after compaction grain size
distribution curves for different initial values ofwater content (8%, 10%, 14% and 19%) are shownin Figure 1.

Figure 2
Lines of equal degradation indicesaccording to compaction energy and water content.
Water Absorption and Suction in CDW
Aggregates
The particle breakage and compaction
characteristics discussed above are explained by thepresence of ceramics and mortar in the constitutionof the CDW. This also explains the high value ofwater absorption of 7.7 % shown in Table 1. Thisvalue is rather high when compared to natural rockchips, but it is not uncommon in CDW which canreach absorption values as high as 15%.
The absorption value of 7.7% also explains thehigh value of apparent optimum water content (wopt)
around 13% for the intermediate Proctor energy.
Natural granular materials and rock chips tend toshow lower values of wopt. The effective compaction
water content, discounting water absorption, should
be in the range of 5%. In fact the optimum watercontent of 13% was rather arbitrary, because thecompaction curves were erratic or very flat.
However the samples would not stand for watercontents lower than 8% and would exude water forcontents higher than 20%.
The discussion above prompts to the existence ofat least two families of pores: inter-particles andintra-particles. The water inside these pores should
affect the mechanical (and the hydraulic) behavior indifferent ways. In order to investigate these
conjectures the authors carried out a series of studies
about the Soil Water Characteristic Curves (SWCC)
or water retention curves (WRC) of the CDW.

Figure 1
Grain-size distribution of CDW andeffect of water content during compaction.
The change of grain sizes is evident from theleftwards shift in the curves towards the center of thegradation envelope, the gray zone in Figure 1. The
most significant change occurs for the samples withlower initial water content (8%). Less crushing isobserved as the water contents increases. This is dueto the fact that water absorbs part of the compactionenergy.
The effect of compaction water content andenergy can be better appreciated by computing
Marsal’s degradation indices (Bg) for different
compaction conditions. Figure 2 shows lines of
equal degradation (iso-Bg). Note that by increasing
the energy of compaction, there is an increase in
14

GEOMATE-Nagoya, Nov.13-15, 2013

correspond to the voids between the finer sandgrains. The intermediate pores with diameter around1.6 m correspond to voids in the finer silt and clay
particles originally present in the CDW and further
generated due to particle breakage during
compaction. It is supposed that the smaller pores(around 0.03 m) correspond to voids within themortar or even within the calcareous aggregate chips
used to make the concrete, however this hypotheses
should be checked later using nitrogen absorption
technique directly in the aggregate chips.
The dominant pores can be better visualized byplotting the pore size density (PSD) curves. These
curves are obtained from axis transformations on thewater retention curves. The ordinates are changed
from gravimetric water content (w) to air void
indices (ea) as follows:

Water retention properties
Specimens of CDW were specially prepared for
determination of the WRC. The samples werecompacted using intermediate Proctor energy anddifferent water contents (9%, 13% and 17%). The
samples were 100 mm in diameter and 35 mm inheight and the original grain size distribution fitted
the coarser limit of envelope C, shown in Figure 1.
The water retention tests were performed using a
specially devised pressure plate apparatus based on
the axis translation technique (ATT) for suction
values between 3 and 200 kPa and the filter paper
method (FPM) for the remainder of the WRC [7].
The water retention curves were obtained
primarily by following a drying or desorption
process. Figure 3 shows the curves that describes thechange in gravimetric water content in the CDW
with respect to the change in matric suction. It isnoted that for suction values below 100 kPa, where
the desaturation process of the CDW begins, theresults of with the filter paper method (FPM) arelower than those obtained by the axis translation
technique (ATT).

ea  e  Gs w

in which e is the total void ratio and Gs is the
specific gravity. On the other hand the abscissa axis
is transformed from capillary suction (s) to pore
diameter (D), assuming that in each pore, water andair are separated by a concave interface represented
by Laplace equation from which:D

Figure 3

(2)

4
s

(3)

in which  is the surface tension of the water
assumed as 0.072 N/m at 20 oC. The transformed
ea-log(D) curve has a shape similar to that of the
WRC in Figure 3, and its slope (first derivative)
for each diameter value represents the poredensity from which the pore size density curve isconstructed as shown in
Figure 5.

Water retention curve of CDW.

Observing the results in Figure 3, very littlechange is noted between the WRC of the different
samples for the higher suction values at the right endof the curves. Most differences in the water retention
capacity of the samples are observed in the initialpart of the WRC. These changes in the initial formof the WRC have a connection with the breakage ofthe particles during the compaction process which isprimarily affected by the initial compaction watercontent and the compaction energy as discussed in
the previous section.
The shape of each curve suggests a multi-modal
distribution of pores. This is clear for the WRCof the CDW with 13% water content in
Figure 4, where it is possible to distinguish atleast three dominant pore sizes, from the sharpchanges of inclination in the w-log(s) curve. The
larger pores with diameter around 113 m

Figure 4 Multi pore shape in the water retention
curve for the compaction water content of 13%.
Similar curves were obtained for other values of
initial water content, but the shapes of the WRCs forlow suctions (i.e. <100 kPa) were affected by
15

GEOMATE-Nagoya, Nov.13-15, 2013

be computed. Both soak and unsoaked tests CBR
tests were performed and the results are summarizedin Table 2 according to the Proctor energy applied.
The results shown in Table 2 are quite interesting.
First the absolute values of CBR qualify the CDW as
potential material to be used in sub-base layers(CBR ≥ 20% at PN) and base layer even in the caseof highways with heavy volume of traffic(CBR ≥ 80% at PI).

compaction water content. As compaction watercontent grows, the magnitude of the first air entry
value increases; this value is related to the largest
pore size. The final part of the curves converges.
This occurs for water content values lower than 9%,
which is close to the amount of water absorbed by
the recycled aggregates studied.

Table 2

Results of CBR test.

Compaction Energy
NormalIntermediate
Modified

Soaked
43%
96%
175%

Unsoaked
55%
128%
247%

Second the soaked CBR in all cases were higher
than the unsoaked values. For natural soils, it isgenerally expected a decrease in soaked CBR since
the increase in water degree of saturation causes thecollapse of aggregates or lumps of fine particles thatare produced during the sample preparation.
The increase in soaked or immerse CBR is
attributed to chemical reactions of the pozzolanicmaterials remaining in the mortar and Portland
cement concrete fractions. This was further
investigated using unconfined compression tests insamples aged with different curing periods.

Figure 5
Pore size density (PSD) curve for thecompaction water content of 13%
Mechanical Properties of the CDW
The most important engineering properties of
granular materials such as stiffness moduli, shear
strength, volumetric compressibility, consolidation
coefficient, and permeability depend on the integrityof the particles or the amount of particle crushingthat occurs due to changes in stress. Therefore, it isimportant to be able to identify and quantify theeffects of particle crushing on these engineering
properties [8].
The basic mechanical properties of granularmaterials of interest for the design of flexible
pavements were investigated. These include
California bearing ratio (CBR), conventional
uniaxial compression and cyclic triaxial tests (CTT)
for the determination of Modulus of Resilience(MR).

Unconfined compression strength (UCS)
The gain in soaked CBR values prompted thepossibility of pozzolanic reactions that should bevariable with time. This was investigated by
preparing compacted samples of 100 mm diameterby 200 mm of height in the optimum conditions forthe intermediate Proctor energy (1263 kN.m/m3).
The samples were allowed to rest or cure underconstant humidity and temperature conditions for thefollowing time periods: 0, 1, 7, 30, 60 and 90 days.
Later the samples were sheared under static
unconfined tests and dynamic confined triaxial tests
described in the next subsection.
The results of unconfined compression tests areshown in Figure 6 in which each point represents anaverage of three tests. The result for the samples
tested immediately after compaction (without cureor 0 curing days) gave an average unconfinedstrength of 120 kPa. This value was used tonormalize the strengths obtained after different
curing periods as shown in Figure 6.
The results clearly show the increase of
unconfined strength and corroborate the initial
hypothesis that further pozzolanic reactions aretaking place due to the reminiscent cementitious
material present in the CDW. The increase wasaround three folds after three months tending tostabilize after that.

California bearing ratio (CBR)
Despite generalized criticism, the design offlexile pavements based only on the CBR properties
is still a reality in many countries, including Brazil,
and any research about materials for pavement
construction would be incomplete without this test.
Different compaction efforts were studied
corresponding to Normal (PN), Intermediate (PI)and Modified Proctor (PM) compaction energies.
Samples were prepared at maximum dry density andoptimal water content condition for each compactionenergy. The CBR standards generally require thatthe samples should be soaked in water during fourdays, during which swell or expansion index should
16

GEOMATE-Nagoya, Nov.13-15, 2013

The authors believe that the initially erratic
behavior of MR with time is due to stabilization ofsuction between the different families of pore sizes
within the CRW sample. It was shown in previous
sections that three dominant pore sizes are present in
the CDW specimens.
In recent publications it is assumed that themechanical behavior is primarily controlled bysuction in the inter-granular pores and that strengthand deformability is less or little affected by suctionin the intra-granular pores present in lumps of clay
particles and in the mortar in the case of CDW [1],[7], [10].

Dynamic triaxial tests
The modern trend in most countries is to movefrom the empirical design methodology based on
CBR and migrate to more advanced procedure as theone prescribed in the MEPDG, MechanisticsEmpirical Pavement Design Guide [9]. In this casethe most relevant mechanical property of granularmaterials is the modulus of resilience which is
obtained from a dynamic triaxial test normalized by
AASHTO T307-99. The procedure prescribes
variable confinement stresses and variable cyclic
deviatoric stresses preforming a total of 16
determinations of moduli for each test batch.

Modulus of Resilience - CTT (MPa)

700

3.5
3.0

USC/USCref

2.5
2.0
1.5

600

MR-Max

MR-Min40

60

MR- Average

500
400
300
200
100
0

R2=0.9979

0

1.0

20

80

100

Curing Time (days)

Standarized values
0.5

Figure 7
Change in the modulus of resilience
with curing time.

Regression curve
0.0
0

5

10

15

20

25

30

35

Curing Time (days)

Inter-granular suction takes little time to equalizein the larger pores and tend to increase stiffness
initially. The water tends to migrated to the interiorof the porous aggregates where internal suction ishigher. This would lead to decrease in inter-particle
suction and hence a decrease of deformability
modulus. In the absence of further evidence this isjust a conjecture, but the authors sustain it as afeasible explanation.

Figure 6
Averagenormalized
unconfinedcompression strength versus curing days.
Similar to the unconfined compression tests thevalue of modulus of resilience (MR) also varied withcuring time. The lower values were observed for
uncured samples and MR varied between aminimum of 70 MPa and a maximum of 250 MPa,
depending on the stress state. The highest values
were obtained after 7 days of curing and varied in
the range between a minimum of 300 MPa and amaximum of 600 MPa. These values are inaccordance with those expected for good naturalrock chips used for base layers in heavy traffic
highways.
The variation of MR with curing time is shown in
Figure 7. The average values increase rapidly
from 172 MPa immediately after compaction to avalue of 426 MPa after 7 days of curing. Then an
unexpected drop of stiffness is observed after 15days of cure and after that the moduli turns toincrease and maybe stabilize as curing time proceeds.
The long term increase in stiffness might be related
to real cementation due to pozzolanic reactions as
discussed in the previous subsection. The apparent
decrease of MR after 90 days is not in line withexpectations and should be further investigated.

Modeling the variation of MR
The value of the dynamic modulus of resiliencetends to vary both with the confining pressure andthe deviatoric stress. The effect of confinement isgreater in loose granular materials and correlates
positively with the increase of modulus of resilience.
On the other hand, the effect of the cyclic deviatoricstresses is more pronounced in cohesive materials
and generally tends to correlated negatively with the
MR in the case of natural clays.
Several models have been proposed in theliterature of pavements for the non-linear behaviorof the modulus of resilience with the stress state.
One widely accepted is the so-called Universal
model proposed originally by [11] which takes thefollowing mathematical expression:

17

GEOMATE-Nagoya, Nov.13-15, 2013k2

   MR  k1 pa    oct  1 pa   parock chip aggregates for the construction of surface
courses with Hot Mix Asphalt (HMA) concrete.
Unfortunately, in the Central Highland of Brazil the
only type of rock available is calcareous and it ismainly exploited for the production of Portland
cement. The portion which is not consumed for the
production of cement is sold as aggregate chips forthe ever expanding building industry. The road
construction sector is left with the residues.

k3

(4)

in which pa is the reference atmospheric pressure, is the first invariant of stress, oct is the octahedral
shear stress and k1, k2 and k3 are non-dimensional
materials properties obtained from regression ofexperimental data.
The numeric results for the constants of themodel described above were obtained from
regression for all tests performed and the best fit issummarized in Table 3.

Curingtime(days)
0
1
7
15
30
60
90

Modulus of Resilience - Universal
Model (MPa)

Table 3700

Coefficient of Universal MR model.
Universal Model
MR
(MPa)
171
299
425
280
224
293
239

k1

k2

k3

745
1764
2754
1318
1302
1747
1480

0.84
0.64
0.55
0.52
0.01
-0.07
0.45

-0.35
-0.49
-0.45
0.37
1.25
1.52
0.00

0 days
1 day
7 days15 days
30 days
60 days
90 days

600
500
400
300
200
100
0
0

100

200

300

400

500

600

Modulus of Resilience - Ciclic Triaxial Test (MPa)700

Figure 8
Experimental values of MR versus
Universal model predictions.
Although the use of calcareous in pavement
surface is limited or even forbidden in somecountries, there is other alternative within viableeconomic distance to be used in Brasilia. In otherregions like the Amazon, which is a huge
sedimentary basin, there is also very little rockavailable. This shortage of natural aggregates for theconstruction of unbound and cohesive pavement
layers in the many regions of Brazil has led to anincreasing interest for the use of recyclable materials,
such as construction and demolition waste – CDW.
However, all these researches concentrated on theuse of CDW for sub-base or base layers as describedin the previous section. Very little has been done
about the potential use of CDW in Hot Mix Asphalts.
Previous researches by [3] showed that a CDW fromthe demolition of the old National Soccer Stadium in
Brasilia met all the requirements to be used as baselayer, even in the case of heavy traffic, although thematerial showed clear tendency of changing grain
size distribution depending on several factors, suchas compaction energy and water content. These
results encouraged the investigation about thefeasibility of using the recycled aggregate from thisCDW to produce dense graded hot mix asphalt(HMA) concrete for the surface course of medium
and low traffic pavements in the region. However,particle breakage and high water absorption of therecycled aggregate remained a major cause ofconcern.
On the other hand the advantages of asphalt
rubber for the reduction of permanent deformationand increase in fatigue life of flexible pavements has

The value of k1 gives a measure of MR at thereference atmospheric pressure. It controls theoverall trend observed. The value of k2 is related to
the nonlinearity typical of unbound granularmaterials like natural sands and gravels. The values
show that this behavior is dominant in the initialperiods up to one or two weeks of curing time. Later
this parameter is approximately zero indicating thedominance of cementation factors. Finally the valueof k3 is related to the nonlinearity caused by thedeviatoric stress. This value is initially negative as
for natural clays where shear stresses tend to
decrease stiffness due to structural damage. The
results corroborate with the conjecture of an initialstage dominated by inter-aggregate suction effects.
For longer curing times the value of k3 becomes
positive indicating the dominance of bonding effects
over suction. Again the value obtained for 90 days
requires further analysis.
The overall adherence between the model andthe experimental values is excellent. This can beappreciated in Figure 8 where all experimental
values are plotted against the theoretical values
computed using the universal model and theparameters described in Table 3. The equality line
(at 45o degrees) is also plotted.
CDW IN HOT MIX ASPHALTS FOR
SURFACE COURSES
Flexible pavements demand a high amount of18

GEOMATE-Nagoya, Nov.13-15, 2013

been widely reported in many paper journals and theproceedings of five editions of the Asphalt Rubber
conference for instance [12] .
The main assumption here is that asphalt rubber
may also help to mitigate crushing of the recycled
CDW aggregates due to the elastic behavior of theremaining particles of crumb rubber. In order tocheck this hypothesis the authors prepared several
samples of dense graded asphalt concrete using
recycled aggregates and asphalt rubber withdifferent rubber contents. Different energies wereapplied during the sample compaction and thesamples were later destroyed to recover theaggregates and the final grain size distribution
curves were analyzed. The degradation wasmeasured by the index described in the next sections.

The crumb rubber used in this research wasrecycled from scrap tires in a commercial recycling
plant in Sao Paulo, Brazil. It was tested at the
University of Brasilia (UnB) according to therecommendations of the American Standard ASTM
D 6114/97. The rubber grains were loose, dry anddid not foam in contact with the asphalt binder. The
results of control tests for textile and metallic fiber
contents, water content and density met all
requirements for the production of asphalt rubber.
The gradation of the crumb rubber grains wascontrolled in order to meet the standards prescribedby the Arizona Department of Transportation(ADOT). Figure 9 shows the ADOT limits andadopted grain size distribution curves.

Physical and Mechanical Properties of the
Modified Asphalt Binder

100
90
80

The straight asphalt binder used in this project isclassified as CAP 50-70, according to thepenetration grade used in Brazilian standards. Thiswas chosen because it is the main binder used in theregion of the Federal District in Brasilia as well as in
Brazil as whole. The binder was tested at the
Highway Engineering Laboratory at the Universityof Brasilia for quality control and to verify if itsatisfied the Brazilian Standard requirements.
The binder was subjected to conventional tests
such as penetration grade, softening point, ductility,
flame and fire temperature, etc. Non-conventional
tests prescribed by the Superpave Standards werealso carried out, including Dynamic Shear
Rheometer (DSR) for the determination of complex
shear modulus (G*) and phase angle (), Rotational
Viscosity and aging tests in a Rolling Thin Film
Oven (RTFO). The results are shown in Table 4 andsatisfied all reference intervals required by theBrazilian Petroleum Agency ANP N°19/2005.
Table 4

Percent passing (%)

70

Unit

Penetration

0,1mm

Reference

Results forlimitsCAP 50-70

50-70

53

Softening Point

°C

>46

47

cP

>112

165

kPa

>1

22

%

≤ 0.5

Inc. Softening point

°C

≤8

1.5

Inc. penetration

%

≥ 55

73%

kPa

>2

33

G*/senδ (46°C)

30

0,010

0,100

1,000

10,000Sieve opening (mm)Figure 9
Crumb rubber grain size distribution
curve and ADOT limits.
Modifiedasphalt
rubberbinderwas
manufactured in laboratory at UnB. The equipment
consists of a mechanical agitator coupled with arotational bar with a helicoidal blade at its ending, ametallic recipient to heat the binder and rubber
mixture and a thermometer to control the mixing
temperature. The mixing speed varied in the range of
250 to 300 rpm in order to assure a homogenous
mixture. The digestion process was carried out at atemperature of 170°C during a period of one hour
following suggestions from [13]. Modified binders
were prepared mixing CAP 50-70 (penetration
grade) with 10% and 20% in weight of crumb rubber(AR-10 and AR-20).
Asphalt Rubber HMA
Different types of hot mix asphalts wereprepared in order to check the influence of theamount of crumb rubber and the compaction energy.
All fractions of aggregates (coarse, fine and filler)
were recycled from civil construction anddemolition wastes (CDW-RA). The aggregates
grading fitted a dense gradation envelope (C)prescribed by the Brazilian authorities. This
envelope is not the same as band C used in base

(RTFOT) @ 163°C, 85 min
Loss of mass

40

0°C, sp21 (20rpm)
G*/senδ (46°C)

50

10(100g,5s,25°C)
Viscosity @ 150

60

20

Asphalt binder characterization test.

Test

Gradation of crumb rubber grainsprescribed by ADOT.
Gradation of crumb rubber grainsused in research

0.16%

Asphalt Rubber properties
19

GEOMATE-Nagoya, Nov.13-15, 2013

samples in order to avoid the loss of fine crushed
particles.
The mixing temperatures for the binders andaggregates, besides the compaction temperature aresummarized in Table 5. In order to assure statisticalsignificance, each test was repeated two times, thus
resulting in a total of 24 samples (4 cases, 3 energies,
2 repetitions). The samples are illustrated in Figure
10. The reader may see the recycled aggregateschips, including pieces of bricks and ceramics in the
cut and polished samples.

layers. The binders include the straight CAP 50-70,
the modified CAP 50-70 with 10% of crumb rubber(AR-10) and with 20 % of crumb rubber (AR-20).
The following cases were tested:Case 0-0: Unbound CDW-RA (only therecycled aggregates)
Case 6-0: HMA 6% of straight binder (recycled
aggregates + CAP 50-70)
Case 6-10: HMA 6% of asphalt rubber AR-10(recycled aggregates + CAP 50-70 +10% of
crumb rubber)
Case 6-20: HMA 6 % of asphalt rubber AR-20(recycled aggregates + CAP 50-70 +20% of
crumb rubber)Table 5Mixing and compaction temperatures.

Temperatures (°C)
Binder temperature at
Aggregates temperature
Compaction temperature

The case nomenclature uses two numbers B-R, inwhich B is the percentage of binder (0 or 6%) and R
is the percentage of rubber in the binder (0, 10 or20%). The idea was to test initially the crushingpotential of the unbound recycled aggregate under
Marshall energy, then to verify the mitigating effectof the binder with different amounts of crumb rubber(0%, 10% and 20%) on the particle breakage process.
Hence the binder content was kept constant at 6% in
the HMA.
The amount of binder in the dense graded hot
mix asphalt concrete was determined using theconventional Marshall design procedure with anautomatic compactor: 50 blows in each face of thesample using a 4.54 kg hammer falling from a heightof 457 mm. The ideal amount of 6% was obtainedusing straight binder CAP 50-70 and it was kept
constant for the asphalt-rubber mixes for the sake ofcomparison. The initial number of 50 blows waschosen because this HMA was initially intended tobe applied in medium traffic highways.
This binder content of 6% is slightly higher thanthe usual amount (around 5%) obtained for hot mix
asphalt concrete manufactured with calcareous
aggregate chips, commonly used in the Federal
District region of Brazil. This higher asphalt
consumption is believed to be related to the porous
nature of the recycled aggregate chips used in thisresearch, which had water absorption of about 7.7%.
Besides the rubber content, the authors also
investigated the influence of the compaction energy
on the crushing of the recycled aggregate particles,by varying the number of hammer blows in eachface of the sample (35, 50 and 75). According to theBrazilian standards, the number of hammer blows ineach face of the Marshall samples varies with theforecasted traffic during the project life: 35 blows
for low volume traffic, 50 blows for medium volume
traffic and 75 blows for high volume traffic.
Therefore the number of hammer blows varied
accordingly for all combinations proposed. In thecompaction of the unbound aggregates, it wasnecessary to use filter paper in both faces of the

Figure 10

CAP 50153
166
138

Asphalt
170
190
164

Cut and polished samples.

Binder extraction and final grain size evaluation
After compaction, the samples were extracted
from the metal cylinders and immediately taken to acentrifuge (Rotarex) with organic solvent. Thisfacilitated the separation process. The binder
extraction process continued with several solvent
soaking and centrifuging stages until the aggregateswere completely clear. Figure 11 illustrates theaggregate recovery process. The clean aggregateswere then subjected to a new sieving process inorder to determine any changes in the grading curves
due to recycled aggregate particle crushing.
For the quantification of particle breakage in
flexible pavements, the Brazilian Department ofTransport Infrastructure (DNIT, former DNER)
prescribes the so-called Marshall Degradation Index,
denoted by IDM, when the aggregate is unbound(without asphalt binder), or IDML, when theaggregate is coated with asphalt binder. The test is
described in the Brazilian norm DNIT ME-401/99. It
uses a standard gradation curve and determines thedifferences (Di) between the percentages before andafter compaction passing through six sieves withpre-determined openings. In the case of IDML theasphalt binder should first be extracted using an
20

GEOMATE-Nagoya, Nov.13-15, 2013

recycled aggregates for HMA yet in Brazil, but theaggregates used in this research presented maximum
abrasion loss of 38% [3] and therefore satisfies therequirements of ES-031/2006.
The introduction of asphalt binder leads to asignificant reduction of aggregate crushing,irrespective of the compaction energy. This is
illustrated in the grain size distribution curve shownin Figure 13 for the cases with 75 blows ofcompaction energy. Observe that the gradation
curves of the HMA are below that of the crushed
unbound aggregate (0% asphalt). Again the effect of
the binder type on aggregate crushing is better
captured by means a single numerical measure suchas the IDML. The absolute reduction in crushingindex varied between a minimum of 1.0% and amaximum of 3.5%, depending on the type of binderand compaction energy. The relative differenceswith respect to the original degradation indices vary
between 14% and 41%.

appropriate procedure as previously described. The
degradation index ID is computed as follows:1 6
ID    Di 
6  i 1 

(5)where Di is the % passing before compaction minus
the % passing after compaction. The following sieve
openings are prescribed: 25.4 mm (1”), 12.5 mm(1/2”), 9.5 mm (3/8”), 4.75 mm (#4), 2.0 mm (#10),
0.425 mm (#40) and 0.075 mm (#200).

Figure 11 Extraction
aggregate recovery.

ofasphalt

binder

and

100
90

75 Blows
50 Blows
25 Blows
Lower limit (DNIT HMA gradation C)
Upper limit (DNIT HMA gradation C)= initial gradation

80
70

Percent passing (%)

Results of Marshall compaction degradation
Figure 12 shows the effect of the compactionenergy on the degradation of the unbound recycled
aggregates. The initial gradation fitted the coarser
limit of the gradation envelope known as “gradationC”, prescribed by the Brazilian Department ofTransportation Infrastructure (DNIT). In normalcases, the ideal is to aim the center of the envelope
when using conventional rock chipped aggregates,
but the authors purposely choose to upper limit(lower curve in the figure) in order to account forpossible particle crushing of the recycled aggregate.
This was based on previous experience using thisrecycled material for granular pavement base layer[3].
The reader can clearly see the shift of thegradation curve towards the center of the envelopein Figure 12. This shift increases with the increase incompaction energy; however the influence ofcompaction energy on the unbound particle breakage
is more evident when this is quantified by means of
the unbound Marshall Degradation index (IDM). The
authors obtained: IDM=6.98% for 35 blows;
IDM=7.81% for 50 blows and IDM=8.59% for 75
blows.
The Brazilian standard for dense graded asphalt
concrete (ES-031/2006) suggests “tentative” limiting
values of IDM ≤ 8 % and IDML ≤ 5% (supposedlyfor 75 blows) for rock aggregate chips. However thiscondition should be verified only in cases when therock aggregate fails the limit value of 50% for theLos Angeles abrasion loss. There is no standard for

60
50
40
30
20
10
0
0.010

0.100

1.000

10.000100.000

Sieve opening (mm)Figure 12 Unbound recycled aggregate. Effect ofcompaction energy.
100
90
80

Case 0‐0Case 6‐0
Case 6‐10
Case 6‐20
Limit s(DNIT HMA gradation C)

Percent passing (%)

70
60
50
40
30
20
10
0
0.010

0.100

1.000

10.000100.000

Sieve opening (mm)Figure 13 Effect of binder on the crushing index
of the recycled aggregate. 75 blows.
Table 6 summarizes the results for all cases
investigated. The overall picture is illustrated in
Figure 14. Here the effect of compaction energy andtype of binder can be clearly appreciated. It isinteresting to observe the effect of the crumb rubberon the degradation index of the recycled aggregate.
For 75 blows, for instance, the IDML was 6.47% in
21GEOMATE-Nagoya, Nov.13-15, 2013

the higher binder viscosity and therefore thicker
binder films coating the aggregates. This is actuallyobserved in cases (b) and (d) and the values are inaccordance with typical binder contents published in
the AR literature. For these cases, it is also observed
a higher binder content for case (d), and the authors
attribute this fact to the higher absorption of therecycled aggregates.
The values of indirect tensile strength (ITS) are
shown in Figure 15. All mixtures satisfy the strength
minimum requirement of 0.65 MPa set by Brazilian
standards (DNIT 031/2004 - ES). The HMA usingasphalt rubber presented low ITS which notuncommon for this type of binder.

the case with straight binder (case 6-0), 6.15% in thecase with 10% of rubber (case 6-10) and 5.05% in
the case with 20% of crumb rubber (case 6-20). The
differences are statistically significant using analysis
of variance (ANOVA). Hence it may be concluded
the rubber grains act as elastic springs, absorbing theshock impact from the compacting hammer andtherefore reducing the crushing of the recycled
aggregates.
Table 6
Marshall degradation index for all cases
investigated.
Case
B-R

Binder,B(%)

Rubber
R(%)

0-0
6-0
6-10
6-10

0%
6%
6%
6%

0%
0%
10%
20%

IDML or IDM (%)
Number of blows
35
50
75
6.98 7.81 8.59
5.69 6.39 6.47
5.94 6.07 6.15
5.63 5.69 5.05

0.859

0.9

0.789

0.8
0.647

0.665

Calcareous Asphalt Rubber

CDW - Asphalt
Rubber

0.7
0.6
0.5
0.4

Marshal Degradation Index (%)

1035 blows

0.3

850 blows

0.2

775 blows

9

0.1

6

0

5
4

Calcareous CAP 50/70

CDW - CAP
50/70

3Calcareous - CAP 50/70

CDW - CAP 50/70

2

Calcareous - Asphalt Rubber

CDW - Asphalt Rubber

1
0
0‐0

6‐0

6‐10

Figure 15

6‐20

Indirect Tensile Strength.

Case B‐R (Binder content ‐ Rubber content)

Figure 14
cases.

Indirect tensile stress is an important property
related to mixture design or composition. However,from a mechanistic design point of view, the most
relevant structural properties are those related tofatigue-life and rutting due to permanent
deformations. The later aspect was analyzed using a
LCPC traffic simulator prescribed by French
standards. The test is illustrated in Figure 16.

Marshall degradation indices for all

Results of Marshall compaction degradation
Besides particle crushing degradation indices, themost important is to investigated which impact thischaracteristic might have on the relevant properties
of HMA to be used on flexible pavement surface
courses. The properties to be investigated depend on
the specific requirements of each country. In the caseof Brazil, besides Marshall Stability values, thepavement authorities require the determination ofindirect tensile strength by means of the Brazilian
test. For types of dense HMA were prepared at theiroptimum Marshall design conditions: (a) Calcareous
aggregates with straight CAP 50-70 asphalt binder(the reference mixture); (b) Recycled aggregates
CDW-RA and straight CAP 50-70 asphalt binder; (c)Calcareous aggregates with modified AR-17 asphalt
rubber binder; (d) Recycled aggregates CDW-RA
with modified AR-18 asphalt rubber binder.
Optimum binder contents were 5.1%, 7.3%,
6.8% and 8.9%, respectively. The binder contents
are typically higher for asphalt-rubber HMA due to

Figure 16

Traffic simulation.

The values of permanent deformation after
30.000 load cycles are summarized in Figure 17.
The HMA using recycled aggregates, with straightbinder and asphalt-rubber, presented the best
performances and met the French requirements ofpermanent deformation inferior to 10%. The
conventional mixture using natural calcareous
22

GEOMATE-Nagoya, Nov.13-15, 2013

into consideration in the case of granular layers.
A positive characteristic revealed in this researchis the trend of recycled granular layers to gainstrength and stiffness with time due to chemical
reactions. This should be dependent on the amountof pozzolanic material available in the concretemortar.
A few words of caution, however: (1) the
material used in this research was exceptionally
good, but general construction and demolition
wastes are quite heterogeneous and must be
analyzed case by case; (2) the user should pay
attention to the possibility of contamination andperform the additional tests according toenvironmental regulations (this was done and thematerial was good); (3) the use of CDW inpavements must be decided on an economical bases
subjected the amount available and distances oftransportation.

aggregate normally used in Brasilia presented thehighest rutting and does not meet the requirementsof French standards. This bad performance isattributed to the poor lamellar shape of thecalcareous chips. The performance improves whenasphalt-rubber is used due to the better resilienceand elastic properties attained with this kind of
modified binder.
Rutting %Calcareous - CAP 50/70

14.54%

16.00%

Calcareous - Asphalt Rubber
CDW - CAP 50/70

14.00%

CDW - Asphalt Rubber
12.00%
8.68%

10.00%

6.95%

8.00%

7.26%

6.00%
4.00%
2.00%

REFERENCES

0.00%
Calcareous - CAP
50/70

Figure 17

Calcareous Asphalt Rubber

CDW - CAP
50/70

CDW - Asphalt
Rubber[1] H. Rahardjo, K. Vilayvong, E. C. Leong, “Water
Characteristic Curves of Recycled Materials,” Geot.
Testing Jr, v. 34, no. 1, pp. 1–8, 2011.
[2] F.D.C. Leite, R.D.S. Motta, K.L. Vasconcelos, and L.
Bernucci, “Laboratory evaluation of recycled construction
and demolition waste for pavements,” Constr and Building
Materials, v. 25, no. 6, pp. 2972–2979, Jun. 2011.
[3] A.M.J. Gómez, “Experimental study of construction
and demolition waste for pavement applicatiosn”. In
Portuguese, Univ. de Brasília, 2011.
[4] G.M.T. Hendriks, C.F. Janssen, “Reuse of construction
and demolition wastein the Netherlands for road
constructions.,” HERON, v. 46, no. 2, pp. 109–117, 2001.
[5] T. Park, “Application of Construction and Building
Debris as Base and Subbase Materials in Rigid
Pavement,” Transportation Eng., Oc, pp. 558–563, 2003.
[6] D. Marsal, R.J. & Resendiz, Earth and Earth-RockDams (in Spanish). Mexico, 1975, p. 546.
[7] A.M.J. Gómez, M.M.Farias, M.V.R. Souza, and I.F.O.
Otálvaro, “Water retention properties of a demolition
waste,” Advances in Unsat. Soils, 2013, pp. 237–241.
[8] P.V. Lade, J. A. Yamamuro, and P. A. Bopp,“Signifiance of Particle Crushing in Granular Materials,”
Geotechnical Eng., vol. 122, no. 4, pp. 309–316, 1996.
[9] H. Theyse, “A Mechanistics-Empirical Design Modelfor Unbound Granular Pavement Layers,” Univ. ofJohannesburg, 2007.
[10] S. Gupta, D. H. Kang, and A. Ranaivoson, Hydraulicand Mechanical Properties of Recycled Materials. MDOT
395,, 2009, p. 94.
[11] J. Uzan, “Characterization of granular material,”
Transp. Research Record, no. 1022, pp. 52–55, 1985.
[12] G. Zareh, A. & Way, “Asphalt-Rubber: 40 years ofuse in Arizona,” in Asphalt Rubber, 2009, pp. 25–45.
[13] Dantas Neto, S.A., Farias, M.M., Pais, J.C., Pereira,
P.A. and Souza, J.B. "Influence of Crumb Rubber andDigestion Time on the Asphalt Rubber Binders". Road
Materials and Pav. Design, v. 1, n.2, p. 131-148, 2006.

Rutting in LCPC traffic simulator.

CONCLUSIONSThis paper analyses the feasibility of using
construction and demolition wastes (CDW) for theconstruction of different layers of flexible
pavements.
Aggregates were recycled from the demolition of
the National Stadium in Brasilia, Brazil, andsubjected to a series of laboratory test. The results
were compared with the requirements necessary foruse in granular sub-bases and bases, and also for
dense asphalt concrete surface courses.
The loose aggregates met all the requirements set
by Brazilian standards to be used in sub-base andbase layers, even for the case of pavements ofhighways with heavy traffic.
When used in dense hot mix asphalts, withconventional and modified asphalt-rubber binders,
the recycled mixtures also met all requirements set
by Brazilian standards. In some case, such as rutting
in traffic simulator, the recycled mixtures performed
even better than traditional mixtures using natural
calcareous aggregates.
In both cases, granular layers and dense asphalt
mixtures, the recycled aggregates tend to show
particle breakage. This characteristic was analyzed
carefully and some directives may be drawn withrespect to compaction conditions: (1) limit theamount of brick and ceramics materials in the CDW;
(2) start with a coarser grain size distribution; (3) use
lower compaction energy; (4) take water absorption

23

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECTIVE STRESS IN UNSATURATED GRANULAR MEDIA IN THE
PENDULAR REGIME
Richard Wan, Sarah Khosravani and Mehdi Pouragha
Department of Civil Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
ABSTRACTThe paper investigates the mechanical behaviour of a granular material at low moisture content whereisolated pendular water bridges (menisci) at the interface of particles give rise to capillary forces in addition toexisting interparticle contact forces. During an increase in moisture content, the contribution of the capillary
forces is lost, which may give way to a collapse type of failure in the absence of any change in mechanicalloading. In this connection, we derive a single effective stress tensor that encapsulates evolving liquid bridges,
interfaces, particle packing, and water saturation, thus providing a link to failure through a micromechanicalanalysis of force transport in an unsaturated pendular-state granular material. Apart from the fact that the stressdue to contact forces is dependent on fabric, it is also found that the so-called suction stress arising from liquid
bridges is direction dependent, i.e. anisotropic. The latter is at odds with the common belief that suction stress isisotropic. We demonstrate that suction stress is a function of the distribution of liquid bridges, degree ofsaturation as well as particle packing, and thus provide an adequate effective stress definition to describe bothconstitutive behaviour and strength of unsaturated media.
Keywords: Unsaturated Soils, Pendular Regime, Anisotropic Suction, Generalized Effective Stress.
of the phases such as saturation, and othermicrostructural quantities such as fabric.
The paper presents such a generalized effective
stress variable starting from basic micromechanicalformulation of force transport in a three-phasesystem composed of idealized soil particles andisolated pore water menisci. A tensorial effective
stress equation which can be viewed as a generalized
Bishop’s equation is explicitly written as a functionof evolving spatial distribution of water menisci andskeleton fabric. In short, if the matric suction anddegree of saturation are known together with fabricof both solid skeleton and water menisci distribution,a generalized effective stress can be computed thatwill lead to the expected irreversible deformations
encountered in unsaturated soils. Other higher ordereffects are discussed in the context of strength suchas the anisotropic nature of the suction stress and the
additional surface tension created by the contractile
skin formed by interfaces between water menisci
and solid particle boundaries.

INTRODUCTION
Many emerging geotechnical problems implicate
unsaturated or variably saturated conditions in soils.
As such, unsaturated soils display rich anddistinctive deformational behaviours that make theiranalysis quite challenging. For instance, a slope may
succumb to shallow failure above the water table in
the unsaturated (vadose) zone due to the loss ofcapillary effects under variable environmental
conditions despite the absence of mechanicalloading. The failure that ensues is typically of acollapse type related to changes in internal stresses
resulting from capillary effects, pore water pressure,water intake, shrinkage and swelling, as well as
strength reduction mechanisms akin to material
instability.
In order to predict such failures, we need tounderstand the mechanics of the governing physicalprocesses so as to build physically and mechanically
representative analytical models. The question that iscentral to the above issue is whether there is a single
controlling (constitutive) stress variable that would
substitute for the role of the effective stress in the
fully saturated conditions. The idea is that suchgeneralized effective stress variable would give theexpected irreversible deformations when used in any
soil constitutive model based on elastoplasticity. For
this to work, the stress variable would have toincorporate various internal processes such as partialpressures of water and air phases in the form of
matric suction as well as evolving volume fractions

PRELIMINARIESThe point of departure of this study is the classic
example of an unsaturated soil at the low end ofwater saturation ( S r  30% ) in which the air phaseis discontinuous with the solid particles being
connected by discrete water menisci. As shown in
Fig. 1, deformations in this unsaturated soil can be
induced in two ways: (a) applying externalmechanical loads such as in a stress increment  ,24

GEOMATE-Nagoya, Nov.13-15, 2013

 '      uw  (1   )ua and (b) increasing the water saturation by S r . In
the former case, it is the increase in interparticle
forces caused by the external loads that leads to areorganization of particles, and hence densification.
On the other hand, an increase in water saturation in
the absence of mechanical loading erases any
capillary forces in the water menisci, thereby
disrupting the particle force equilibrium. A
densification also ensues in this case due to amodification of force transport within the particle
assembly.

Fig. 1 (  ua )   (ua  uw )(1)

where  and  ' are the total and effective stresses
respectively, and  is a weighted parameter usually
arbitrarily made a function of the degree ofsaturation S r . Understanding the capillary (suction)
stress as a function of the difference between air andwater pressures as well as its dependency on the
degree of saturation, void ratio and soil structure is alongstanding problem. This issue establishes a directconnection between constitutive behaviour andstrength of unsaturated media in providing anadequate expression for effective stresses.
When arbitrarily confounding  with the degreeof saturation, both the dry and fully saturated
conditions can be recovered readily in Eq. (1).
However, due to this rather simplified hypothesis,
the ability of Bishop’s equation to explain thecollapse of soils upon wetting has been historicallychallenged [4]. Also, experimental determination of
the so-called effective stress parameter  oversuction ranges and wetting/drying paths is difficult[5]. The above difficulties led to the necessity ofcircumventing  by introducing two independentstress variables [6], namely the net stress as
 net  (  ua ) and the matric suction ass  (ua  uw ) that would control deformations
instead of the effective stress. A soil water
characteristic curve (SWCC) describing how muchwater can be retained in the soil through a water
saturation versus matric suction relationship is also
introduced. With these two independent variables,
Alonso et al. [7] developed their celebrated
Barcelona Basic Model (BBM) within theframework of critical state and as such thephenomenon of collapse upon wetting could well be
described. Many other models followed suit, adding
more complexities to the already developed
framework [8], [9], [10].
It is essential to know the formal meaning of  ,including its experimental verification over all
suction ranges and for both wetting and drying paths.
Certainly, the literature abounds with empirical
relationships for defining  [11]. Relationships
using one or more parameters of the soil-water
characteristic curve such as the air entry value incombination with the residual water content havebeen proposed; but both experimental andtheoretical evidences point that void ratio andmicrostructural parameters such as soil fabric arealso other contributing factors. With a view toaccount for the link between the microscopic andmacroscopic properties of an unsaturated medium,
many researchers have worked on the intergranular

Permanent skeleton deformations inducedby mechanical and hydraulic loadings.

It is interesting to imagine cycles ofwetting/drying inducing permanent (plastic)
deformations in very much the same way as cycles
of loading/unloading. In both cases, there is a single
effective stress that would describe the deformations
caused by both mechanical and hydraulic processes.
Experimental evidences highlighting the abovementioned observations can be found in [1] and [2]where skeleton plastic strains were measured for
both
water
suctionandmechanicalloading/unloading cycles. Given the central role offorce transport in such processes, a micromechanicalformulation is warranted.
Bishop’s Effective Stress
The presence of an air phase in an unsaturated
soil was examined by Bishop [3] who extended
Terzaghi’s effective stress principle by intuitively
introducing an average pore fluid pressure weighted
over the pore air ( ua ) and water ( uw ) pressures.
Using soil mechanics sign convention, i.e. positive
stresses mean compression, Bishop’s equation is
given by:25

GEOMATE-Nagoya, Nov.13-15, 2013

stress in the solid skeleton under the action of poresuction and surface tension forces [12], [13], [14],[15].
For the above reasons, it appears that analternative approach that involves micromechanicalanalysis is needed to get constitutive insights inunsaturated
soils
ratherthan
makingphenomenological assumptions that may lead to
unnecessary empiricism and complexity.

radius R joined by independent concave liquid
bridges with negligible inter-particle contact area, anassumption which will become evident below. Since
we are primarily interested in the transport of forcesin the REV, we will then focus on the first term on
the right hand side of Eq. (2) related to particle
interactions. Applying Gauss’ divergence theorem tothe above-mentioned term as an integration overmultiple particles with a closed boundary (due tonegligible contacts) for the case of static andweightless media, the following so-called granular
stress tensor is obtained:

STRESS DERIVATION IN A THREE-PHASESYSTEM
We consider an ensemble of interacting solid
particles in the presence of a water phase and an air
phase in a representative elementary volume (REV)in equilibrium with applied loads on its boundaries
as shown in Fig. 2.

  ij  g 

1 N
1 N
 ij dV    p xi t j d 

p

V

V
V

(3)

where  p is the surface of a particle, xi the spatial
position of points on  p at which various surface
tractions t j act. Among the various surface tractions

Fig. 2exerted on an individual particle, we will findcontributions from pair-wise particle contact forces
due to external loading, actions of air and waterpressures on dry (  dp ) and wetted (  wp ) surfaces
respectively, and surface tension forces arising fromair/water/solid interfaces formed by water menisci
along contour  m at a particle’s surface.
It can be readily shown when considering
equilibrium of forces on the closed surface of eachparticle that:

Representative Element Volume (REV)with solid, air and menisci.

The (Cauchy) stress tensor for such a composite
system can be readily calculated as a volume
average of the various constituents (phases) just as
in the case of a solid body consisting of interacting
point masses in the REV of total volume V , i.e.
  ij 

1 N V p  ij dV
V


w

a

V
V
uw ij ua ijVV  ij  g 

1 N   ua .R N
 f j  i  V  dp n j ni d V 

uw R N L
R N L
n j ni d     T j ni d 

p


m
w
V
V
(4)

where n j is the outward normal to the particle(2)

surface, f j is the mutual contact force between
the so-called branch
particle pair  and  , ivector defining to the separation distance between
the same two particles, T j the surface tension forceswhere V  ,   p, w, a , represents solid particle,
water and air phase volumes respectively, N thenumber of particles and  ij the Kronecker delta.

per unit length related to water meniscus action on
 m formed by the intersection of the water
meniscus with the particle’s surface, L the numberof liquid bridges,  wp is the part of the particle

In Eq. (2), the stress in both the water and air
phases has been considered to be hydrostatic andequal to uw and ua respectively. As a result, the last
two terms on the right hand side of Eq. (2) simply
refer to the partial pressures due to air and waterphases with their respective volume fractions
applied to each individual pressure.
Next, suppose the above system is idealized as
an ensemble of mono-disperse spherical particles ofwetted by the liquid bridge, whereas  dp is the unionof all dry parts of the particle’s surface. Interestingly,
the air/water interface at the particle’s surface, seen
as a contractile skin, allows the REV to withstandtensile stresses.
The tensor moment of force, defined by the first26

GEOMATE-Nagoya, Nov.13-15, 2013

term to the right hand side of Eq. (4), as a dyadic
product between f  and  , is easily identified as
the effective stress tensor that is responsible forskeleton deformation. Finally, substituting Eq. (4)into Eq. (2) and regrouping terms, we get a
generalized Bishop’s effective equation:

volumetric density of menisci. This engenders ameniscus based shear strength that increases with theanisotropy of the packing. Finally, it can be easily
shown that Terzaghi’s effective stress is recovered in
the saturated case when S r  1 in which case ij   ij and M ij  0 since the half filling angle  ij  ( ij  ua ij )  ij (ua  uw )becomes 180 .

(5)

CAPILLARY STRESS AND STRENGTH

in which  ij is a dimensionless tensor that replaces
the scalar parameter  in Bishop’s equation, withij  ij 

M ij(ua  uw )We next explore the implications of the newly
derived effective stress equation (Eq. 5) byconsidering periodic or regular packings of monosize spherical particles wetted in the pendular
regime.

(6)

containing microstructural information through  ij

Isotropic Packings

which describes the spatial distributional nature of
the water menisci, i.e.

ij   Sr  ij 

R N L wp n j ni d wp
V

The REV of a given packing can be described asa unit cell which essentially is the simplest repeating
unit of the packing. Two limiting cases, namely
simple cubic (SCP) packing (loosest state) and facecentered (FCP) packing (densest state) areconsidered. Figures 3a,b (as insets) show SCP and
FCP geometries respectively with liquid bridges
between each pair of particles. The objective is toanalytically compute the tensorial effective stressparameter  ij introduced in Eq. (5) as a function ofdegree of saturation, among other things. Since one
liquid bridge is associated with each contact andgiven the packing is regular, the distribution ofliquid bridges is isotropic. Furthermore, if we
assume a zero contact angle, the surface tension
forces become orthogonal to a radial outward normal
vector, and because of symmetry and isotropy
conditions there is no contribution from surface
tension forces arising from a meniscus/particle
interface when summing over all contacts and liquid
bridges within the granular assembly. The vanishingof M ij under such conditions is to be expected since
it represents a tensor moment of forces in the
granular assembly. Thus, in this special case, ij   ij is an isotropic tensor with no contributions
from surface tension forces. As a result, the diagonalterms of the tensor  ij being all equal can be
identified with Bishop’s effective stress parameter which can now be analytically calculated atvarious degrees of saturations for both SCP and FCP
configurations. Numerical results are shown in Fig.
3c together with actual experimental data for various
soils in the background for comparison purposes. It
should be noted that the range of degree ofsaturation examined in the numerical computations(7)

where  is porosity. Also, this tensorial quantity
originates from the suction forces acting between
particles due to water menisci.
As additional contributions emanating from thewater menisci are surface tension forces whose
distribution in space is represented by:
M ij 

R N L
 m Tj ni d m ,V

(8)a new tensorial quantity, herein coined as thecontractile skin tensor, that involves a surface
integral of a dyadic products of surface tension force( T ) and radial normal ( n ) along the contour of theparticle-meniscus interface summed over allparticles containing a liquid bridge. This represents atensor moment of surface tension forces on theparticles, easily identified as contractile (cohesive)internal force in addition to other microstructuralforces.
Following the newly derived Eq. (5), theeffective stress is thus governed by a net stress( ij  ua ij ) and a matric suction (ua  uw ) thatgives rise to a so-called capillary stress tensor
ij (ua  uw ) . In keeping the analogy with Bishop’s
equation, we denote  ij as the tensorial effective
stress parameter. It is noteworthy that the latter leads
to a suction stress that is obviously anisotropic innature following the distribution of the contractile
skin surface tension and liquid bridges that in turnvary as a function of the fabric of the granularmaterial, as well as the degree of saturation and27

GEOMATE-Nagoya, Nov.13-15, 2013

materials and at low matric suctions, i.e. high water
saturations when the menisci are well developed.

is based on idealized mono-sized spheres and falls
below 30% since the menisci are not allowed tomerge to give full water saturation. Also, theexperimental data in this range of small degrees ofsaturation are scare and not quite reliable, given
known difficulties in measuring low suction in soils.
The numerical results clearly show that the effective
stress parameter  is invariably a function of
packing and water menisci as illustrated in Fig. 3 forthe isotropic case.

(a) capillary stress contributions for loose
packing

Fig. 3(b) capillary stress contributions for dense
packing

Computed effective stress parameter versus
degree of saturation for various packingsand comparison with experimental data.

It is also interesting to investigate the relative
contributions of the surface tension forces (termM ij ) and the suction forces between particles (term ij ) to the capillary stress  ij   ij (ua  uw )experienced by the unsaturated granular assembly.
We thus re-examine the two packings (SCP and
FCP) with now a contact angle   30 and using aparticle radius of R  0.1 mm for illustrative
purposes. Here again, because the packings are
isotropic, the capillary stress tensor is isotropic withthe difference that it has both suction and surface
tension contributions.
Figure 4a shows that the relative contributions ofsurface tension and suction cross over at acharacteristic matric suction of about 1 kPa for theloose case. At small matric suctions, the surface
tension effect arising from the particle/meniscus
interface dominates, but is ultimately overtaken by
the suction effect at large matric suctions. Referringto the dense case in Fig. 4b, the contribution of
surface tension is always smaller than that of suction.
This suggests that the contractile effect of surface
tension is more likely to be important for loose(c) soil water characteristic curve for loose anddense packings
Fig. 4

Variouscomputedsaturation.

quantities

withFinally, Fig. 4c shows the computed soil water
characteristic curves (SWCC) for both loose anddense packings. The whole range of saturation
cannot be covered as only the pendular regime isherein considered. However, the theory developed inthis study shows that the SWCC can indeed beanalytically determined rather than using empirical
relationships as proposed in the literature [11].

28GEOMATE-Nagoya, Nov.13-15, 2013

Anisotropic Packings
Evolution of capillary stress
We now consider anisotropic assemblies ofmono-sized spheres through the tensorial effective
stress parameter  ij that confers anisotropic

The components of fabric as obtained from Eq.
(9) and given in Table 1 allow us to computeanalytically the effective stress parameter  ij

character to the suction stress. A body centred cubic
packing (BCC) is evoked with its unit cell at acoordination number of 8 and with reference frame 1,
2 and 3 as shown in Fig. 5. By varying the size ofthe unit cell through lengths L and L ' , a family of
anisotropic BCC packings with different particle
separations can be generated.

Fig. 5through Eqs. (6) and (7) for various anisotropic
packings. These relations ultimately define thedependence of the effective stress on degree ofsaturation, fabric and menisci distribution as
represented in Eq. (5).

Body centred cubic packing in various
configurations parametrized by interparticle
distance L’.

The anisotropy of the family of BCC packings
can be readily evaluated through the fabric tensor
Fij normally defined as the summation of dyadic
product of contact normals ni n j throughout theassembly:
Fij 

1 2N
 ni n j
2N(9)Fig. 6

In principal axes relative to reference frame(1,2,3) in Fig. 5, the fabric components ( F1 , F2 , F3 )for different values L ' can be calculated and are
given in Table 1. We herein introduce the parameter' a ' [16] to describe packing anisotropy, i.e.
a

5 ( F1  F3 )2 ( F1  F2  F3 )Figure 6 illustrates the evolution of various
tensorial parameters  ij ,  ij , M ij / (ua  uw ) that
control the capillary stress  ij in a BCC packing
with cell spacing L '  2.7 as a function of degree ofsaturation. The anisotropic nature of suction isclearly demonstrated with the major and minor
principal directions of the capillary stress beingaligned with the vertical direction 1 (axial) and 2(lateral) respectively.
The capillary stress component in each one of theprincipal directions is further shown in Fig. 7 as afunction of matric suction. As the wetting angle issmall, the amount of capillary stress induced bysurface tension forces ( M ij ) is smaller incomparison with the capillary stress due to suction
forces  ij (ua  uw ) .
Finally, Fig. 8 shows the totally induced
anisotropic capillary stress which decreases withincreasing degree of saturation, as expected.

(10)

Table 1 Values of components of the tensor Fij
according to packing
L'
2.10
2.20
2.3094
2.40
2.50
2.60
2.70

F1
0.276
0.335
0.333
0.360
0.391
0.422
0.456

F2
0.362
0.332
0.333
0.320
0.305
0.289
0.272

F3
0.362
0.332
0.333
0.320
0.305
0.289
0.272

Polar plot of various parameters controlling
capillary stress and anisotropy

a
-0.22
0.01
0
0.1
0.21
0.33
0.46
29

GEOMATE-Nagoya, Nov.13-15, 2013

The origins of such factor are in the computationof the ratio of mean stress p to deviatoric stress q
in a granular assembly (   q / p ) with theanisotropies of microscopic variables such as
interparticle force and contact normal distribution.
Thus, the anisotropy factor (a ) represents ananalogous fictitious ‘friction angle’ as a result ofwater menisci. As illustrated in Fig. 9, the meniscusbased anisotropy (a ) for each packing coincides
with packing anisotropy (Table 1).

Fig. 7

Fig.8

Principal capillary stresses with various
contributions in axial and lateral directions.

Fig. 9Upon wetting, the degree of saturating increases
since liquid bridges develop between particles,
resulting into an increase in anisotropy of thecapillary stresses following the anisotropy of thepacking in the background. This increase inanisotropy is induced by the enlargement of thewetted contours of the menisci with higher degrees
of saturations, while at the same time, the capillarystresses decrease (Fig. 8). The rate of increase inmeniscus-induced anisotropy is greater the more
prominent the anisotropy of the packing is, i.e.
increasing values of L ' in Fig. 9. For the isotropic
packing case ( L '  2.3) , there is obviously no
meniscus-based anisotropy induced upon wetting.
Contrary to the assumption classically made withregard to isotropic pore pressures in unsaturated soil,
the derived tensorial equation for effective stressshows the directional nature of the capillary stresses
induced by liquid bridges. One of the consequencesof this finding is that the meniscus-based anisotropy
can increase drastically with water saturation the
more anisotropic the packing is. As such, any
perturbation to such state of high anisotropy in
combination with a decrease in capillary stress may
make the unsaturated sample succumb to sudden
collapse. This combined increase in capillary stressanisotropy and decrease in capillary stresscomponents with saturation can be made the basis ofcollapse failure in unsaturated samples in theabsence of any increase in external mechanical loads.

Decrease in capillary stresses following
increased degree of saturation.

Evolution of degree of anisotropy and link tostrength
There is a compelling connection between themeniscus-based anisotropic capillary stress in unsaturated granular soils and the shear strength
contribution that it engenders. As an extension to theprevious discussions we next analyze the evolutionof such anisotropy with the degree of saturation byintroducing an anisotropy factor a similar to what
was defined for contact fabric, i.e.
a 

5 ( 1  3 ) 5 ( 1  3 )
2 trace( ij ) 2 ( 1  2  3 )Meniscus-based anisotropy with saturationfor various anisotropic BCC packings.

(10)

30

GEOMATE-Nagoya, Nov.13-15, 2013[3] Bishop AW, “The principle of effective stress”,
Teknisk Ukeblad, Vol. 106, No. 39, 1959, pp.
859-863.
[4] Jennings JE, Burland JB, “Limitation to the useof effective stress in partly saturated soils”,
Géotechnique; Vol. 12, No. 2, 1962 pp. 125–
144.
[5] Blight GE, “Effective stresses evaluation forunsaturated soils”, J. of Soil Mechanics andFoundations Division, ASCE, USA, Vol. 93,
1967, pp. 125-148.
[6] Fredlund DG, Morgenstern NR, “Stress statevariables for unsaturated soils”, J. Geotech.
Eng. Div., ASCE, Vol. 103, No. 5, 1977, pp.
447-466.
[7] Alonso EE, Gens A, Josa A, “A constitutive
model
for
partiallysaturatedsoils”,
Géotechnique, Vol. 40, No. 3, 1990, pp. 405430.
[8] Wheeler SJ, Sivakumar V, “An elasto-plastic
critical state framework for unsaturated soil”,
Géotechnique, Vol. 45, No. 1, 1995, pp. 35-53.
[9] Cui YJ, Delage P, “Yielding, plastic behaviour
and critical state of a collapsible unsaturated
silty soil”, Géotechnique, Vol. 46, No. 2, 1996,
pp. 465-477.
[10] Khalili N, Loret B, “An elasto-plastic model for
non-isothermal analysis of flow and deformation in unsaturated porous media:
formulation”, Int. J. Solids Struct., Vol. 38,
2001, pp. 8305–8330.
[11] Garven E, Vanapalli SK, “Evaluation of
empirical procedures for predicting the shear
strength of unsaturated soils”, American Societyof Civil Engineers Geotechnical Special
Publication No. 147, Vol. 2, 2006, pp. 25702581.
[12] Pietruszczak S, Pande GN, “On the mechanicalresponse of partially saturated soils at low andhigh degrees of saturation”, Numerical Models
in Geomechanics, 1995, pp 33-38, Balkema,
Rotterdam.
[13] Cho G, Santamarina J, “Unsaturated particulatematerials, particle-level studies. Journal of
Geotechnical & Geo-environmental Eng.”, 2001,
pp. 84-96.
[14] Molenkamp F, Nazemi A, “Micromechanicalconsiderations of unsaturated pyramidal
packing”, Geotechnique, Vol. 53, 2003, pp.
195–206.
[15] Lu N, Likos W, “Suction stress characteristic
curve for unsaturated soil”, Journal of
Geotechnical and Geo-environmental Eng., Vol.
132, 2006, pp. 131–142.
[16] Radjai F, “Particle-scale origins of shear
strength in granular media”, arXiv:0801.4722v1[cond-mat.soft].

CONCLUSIONSThe physical significance of the effective stressparameter  as originally introduced in Bishop’s
equation has been formally derived throughmicromechanical analysis of a three phase medium(air/water/solid) with isolated water menisci, i.e. in
the pendular regime. It turns out that  is generally
not a scalar, but is rather a tensorial quantity
described that is generally a function of degree ofsaturation, particle packing as well as water menisci
distribution. This leads to the possibility of the socalled capillary stress to be anisotropic in nature as
dictated by the spatial distri-bution of water menisci
and fabric of the solid skeleton evolving during
deformation history. The capillary stress is shown tohave two contributions: one emanating from suction
between particles due to air-water pressure
difference, and the second arising from surface
tension forces along the contours between particles
and water menisci.
Although the latter may be small at small water
saturations, it becomes prominent as water saturation
increases. The implication is that granular materials
in the pendular regime can engender an internal
suction based shear (deviatoric) effect under evenisotropic loading. Also, this issue becomes
particularly relevant when studying the material
instability behaviour of unsaturated soils in thependular regime where failure is characterized by asudden collapse. In this paper, it is demonstrated thatthe more anisotropic the packing and capillary stressare, the higher the potential for collapse uponsaturation. It is seen that the capillary stress tensor,
while decreasing in magnitude upon wetting, also
evolves with an increase in anisotropy that leads to acollapse failure in the absence of mechanical loading.

ACKNOWLEDGEMENTS
The authors acknowledge the Natural Scienceand Engineering Research Council of Canada andthe Computer Modelling Foundation for theirfinancial support through a NSERC-CRD project.

REFERENCES[1] Sivakumar V, “A Critical State framework forunsaturated soils”, PhD thesis, University of
Sheffield, UK, 1993.
[2] Sharma RS, “Mechanical behaviour of
unsaturated highly expansive clays, PhD thesis,
University of Oxford, UK, 1998.

31

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

RECENT GEOTECHNICAL RESEARCH ADVANCES IN UNIVERSITYPUTRA MALAYSIA
Bujang B.K.Huat1 and Afshin Asadi2
1

Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM, Serdang,Selangor, Malaysia
2

Housing Research Centre, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor,
Malaysia
ABSTRACTThis paper aims to present the recent geotechnical research advances in the field of geotechnical engineeringin Universiti Putra Malaysia as follows; (i) Electro-biogrouting method for soft soil stabilization. In this method,
the live bacteria or their production are induced by electrical gradient. The soft soil is then stabilized through aphysicochemical reaction. (ii) Soil improvement using nano particles, in this method, the effect of nano SiO2 on
residual soil treated by cement was investigated. The results showed that nano SiO2 increased the shear strengthof the soil effectively. (iii) Effect of coir fiber on flexural strength of the soil was investigated to evaluate themechanical properties of reinforced marine soft clay as earth structures. The results revealed that the coir fiber
increased the flexural strength of the marine soil. (iv) Effect of acid rain on engineering properties of soil wasinvestigated. Significant changes in engineering properties of soils under effect of acid rain were shown.
Keywords: Electro-biogrouting, Bacteria, Nano particle, Shear strength, Coir fibre, Flexural strength, Acid rain
gradient. The uniform injection can be acquired by
selection of appropriate position of electrodes.
Therefore, it is possible to control the direction of
the materials movement.

ELECTRO-BIOGROUTING STABILIZATIONOF SOFT SOILSThis project was carried out by Hamed Keykhah
under supervision of Prof. B.K.Huat and Dr. Afshin
Asadi. A new method of soil stabilization wasdeveloped. Electro-biogrouting method is a novel
combined techniques of electrokinetic andbiogrouting /biocement. The most advantages ofthis invention are explained as follows:(i)The method is able to be applied in fine grainsoils with low permeability. The method uses theelectrical gradient to flow and transport of bacteria,
Bacillus pasteurii, and essential materials (i.e. urea
and calcium chloride) instead of hydraulic gradientin the soil.
(ii)The bacteria are transported in the soil. The
most bacteria have a net negatively charged surface
at high pH values and a net positive charge at low
pH value due to a number of polymers, which carryionizable groups in the membrane. Sinceelectrokinetic technique is capable to induce charged
particles and biocolloids such as bacteria, it is able
to distribute bacteria in porous media of soils
uniformly by electrophoresis.
(iii)This method is able to control the direction ofmaterials movement in soil fabric. The distributionof bacteria, urea, Ca+2 and Co3-2 in EK depends on
position, power and the period of applied electrical(iv)In this method, the pH can be controlled to
optimize the condition for the culture media of thebacteria. During EK process, H+ and OH− aregenerated from the anode and the cathode,respectively. The pH is reduced at the anode, andincreases at the cathode. Since, the growth andactivity of the bacteria are often pH dependent, thisEK system is able to regulate appropriate
environment for them.
(v)In this method, the oxygen released in EK
helps the bacterial activity. The electrolyzing ofwater in the anode and cathode chambers cause torelease oxygen and hydrogen. Since, the applied
bacteria are aerobic and need O2 for growth andactivity, the system is able to regulate appropriate
environment for them.
The EK not only is capable to transport thebacteria in soils, but also is able to transport CO3-2
which is the production of bacterial activity in soil.
The hydrolysis of urea by bacteria releases CO3-2.
Then, the Ca+2 and Co3-2 can be injected in the soil
by electrokinetics, resulting precipitation of CaCO3[1]-[5].

32

GEOMATE-Nagoya, Nov.13-15, 2013

Fig.1. b) Electro-biogrouting setup

There are two possible methods as follows;(a)Elector-biogrouting
bybacteria
injection; we injected 2M CaCl2 and 1M
urea solution in the anode chamber, waiting
to be transferred by electromigration andelectroosmotic procedures completely inthe soil for 72 hours. Then, the live culture
bacteria were added with optical density
around 0.5 into the cathode chamber totransport as particles by electromigration
process. When the bacteria were exposed tothe urea, they released the enzyme andmade bicarbonate (CO3-2) which quickly
joined to the calcium ions (Ca+2) and
precipitate CaCO3 (Fig.1).
(b)

Figure 2 shows the undrained shear strengthchanges of the soil under electrical potential of 5-10
mV/cm after 72 hours EBM treatment in two
different described methods. The undrained shear
strength was measured using a vane shear apparatus.
The study revealed that the method (b) was more
effective than method (a) because of some reasons
as follows [5]-[10];(i) The usage of bacterial production (CO3-2 ),(ii) The movement of CO3-2 ions in an electrical field
was easier than the bacterial movement in the soil,
and(iii)Reduction of bio clogging as a result of bacterial
concentration in porous media.

Elector-biogrouting
bybacterial
products injection; we initially added 2 M
CaCl2 into the anode chamber to be
induced form anode to cathode byelectromigration. Then, the mixed bacteria
and urea solution were added to the cathodechamber. The bacteria quickly released
enzyme to hydrolyze urea, and thebicarbonate (CO3-2) is produced in thecathode chamber. Then, the bicarbonate
which has a negative charge was moved
directly to the anode in the soil. Finally, thecalcium carbonate was precipitated in thesoil (Fig.1).

Fig.2. Undrained shear strength of the soil before
and after treatment
EFFECT OF NANO PARTICLESPROPERTIES OF RESIDUAL SOILON

The research was conducted by Sayed Hessam
Bahmani, MSc student, under supervision of Prof.
Bujang B.K.Huat and Dr. Afshin Asadi.
Nanoparticles are small objects, which are sized
between 1 and 100nm, Because of extremely small
size in nano-scale (10-9m) and ultra-high surface
area, some nano particles show unique properties
that can improve physical and mechanical propertiesof the materials. Engineered nanomaterials can be
categorized into four groups as follows; (i) carbonbased materials, usually including fullerene, single
walled carbon nanotube (SWCNT) and multi walledcarbon nanotube (MWCNT); (ii) Metal-basedmaterials such as quantum dots, nanogold, nanozinc(nano-Zn), nanoaluminum (nano-Al), and nano scale
metal oxides like SiO2 ,TiO2, ZnO and Al2O3; (iii)
dendrimers, which are nano-sized polymers built
from branched units capable of being tailored toperform specific chemical functions; and (iv)composites, which combine nanoparticles with othernanoparticles or with larger bulk-type materials. The
first two types are common and are often studied.

Fig.1. a) Schematic diagram of Electro-biogrouting
setup

33

GEOMATE-Nagoya, Nov.13-15, 2013

Silicon dioxide as a nanoparticle, also known assilica, is the oxide product of silicon (SiO2) with
commonly spherical morphology (Fig. 3) [11]-[15].
A typical residual soil, which is residual granite
soil in Malaysia, the SiO2 nanoparticles and ordinary
Portland cement (OPC) were used in this study. The
nano particles and distilled water were mixed bystirrer. The mixture was then sprayed on the
different mix proportions for exchanging moistureamong the particles, forming homogenous blend,and prevent agglomeration of nano particles. The
mixtures were kept in sealed plastic bags for
24hours. Finally, geotechnical tests were carried out
on the specimens.

Fig. 5. Variation of compaction characteristics soil
treated by cement and nano particles
Effect of Nano Particles on
Compressive Shear Strength of Soil

The effect of the addition of SiO2 nanoparticles(15 and 80 nm) and cement on the unconfinedcompressive strength of the soil is shown in Fig. 6. It
can be observed that both cement and nanoparticles
led to increase the shear strength and lower SiO2
nanoparticles ratios in both sizes 15-80nm resulted
in higher strengths.

Fig. 3 SiO2 nano particles
Effect of Nano
Properties of Soil

Particles

UnconfinedonEngineering

The effect of cement and nanoparticles on liquid
limit (LL) and plasticity index (PI) of the soils areshown in Fig. 4. It can be observed that addition of
cement initially increased the LL and PI. However,higher percentages of the additives have led toreduction in PI. In this context, it is illustrated that
reduction in the plasticity of cement/nanoparticles
stabilized-residual soils was as a result of theincrease in LLs and PLs. Variation of OMC and
MDD weight of the soils at different mixture content
are shown in Fig. 5. It can be clearly seen that theaddition of cement and nano particles led to anincrease in OMC. The increasing OMC is may becaused by the additional water held with theflocculent soil structure resulting from cement andcement/nanoparticles. It also can be observed that
MDD of the treated soils decreased slightly as aresult of cement and nanoparticles treatment.

Fig.6 Variation of shear strength characteristics soil
treated by cement and nano particles
The addition of nano particles (SiO2) in Portland
cement marks a novelty in the high performance soil
stabilization technology. The nano particles silica
behaved not only as a filler to improve soil/cement
microstructure, but also as a promoter of pozzolanic
reaction by transforming portlandite into C–S–H gel(Fig. 7) [15]-[20].

Fig. 7 XRD from soil treated by cement and nanoparticles

Fig. 4. Effect of nano particles SiO2 on Atterberg
limits of soil treated by cement
34

GEOMATE-Nagoya, Nov.13-15, 2013

EFFECT OF COIR FIBRE ON FLEXURALSTRENGTH OF SOFT MARINE SOILf 

The research was conducted by Vivi Anggraini,
Ph.D student, under supervision of Prof. Bujang
B.K.Huat and Dr. Afshin Asadi. Soft marine clay
deposit used in the construction of earth structures
has recently come under focus because of its
potential to resist cracking of the compacted layer
after construction. Due to that soft marine clay is
weak in tension and gives rise to the risk of certain
areas of the layer being subjected to flexure, atesting program was undertaken to determine theeffects of compaction and internal reinforcement on
the potential failure of clay liners. A schematic

Where r is the radius of the specimen.

FL

r 3

(2)

Then the Young's modulus of the specimen is
calculated as follows;EFL
12r 4 y(3)Where y is the deflection at the centre of the beam.
Effect of Coir Fibres on Mechanical Properties ofSoft Marine Clay Soil

illustration of localized subsidence due to post closure
decomposition for a landfill site is shown in Fig. 8
along with the flexural distress caused due todifferential settlements.

The load deflection response of the soil fibre
inclusion subject to extended deformation is shownin Fig 9.

Fig.8 Flexural Distress in clay-based coversystem.(Viswanadham, 2010)
The stabilization of soft marine clay soil withrandomly inserted natural fibres for earth structures
applications has been investigated in this research.
The methods of in-situ reinforced soil are based on
the principle of stabilizing natural soils by the
inclusion of elements capable of resisting forces
associated with tension and/or bending [21]-[25].

Fig. 9 Flexural load-extension relationship withvarious fibre contents at 7 and 14 day-curing
This initial peak load is directly related to theflexural tensile strength of the coir fibre reinforced
soft marine clay, the region in which pronounced
cracking occurs within the middle third of thespecimen. An increasing the fibre content enhances
the degree of plastic straining at constant load, withthe load deflection response a ductile plastic
deformation.

Three-point bending test is a conventional
mechanical test which is generally used for concrete
specimens. It represents the case of a plane beamplaced on two simple supports and subjected to avertical load at the middle. The test is attracting due
to the fact that the Young's modulus obtained fromthe three-point-bending tests may represent the
behaviour of the earth platform under surface loads.
Bending moment is equal to:
FL
M
4

(1)

Where F is the maximal applied load; L is distance
between the supports.

Fig 3 The values of flexural strength of specimen
tested at 7 and 14-days curing

Flexural stress for circular section of the specimen isequal to:35

GEOMATE-Nagoya, Nov.13-15, 2013

Artificial acid rain used in this experiment was
prepared by diluting sulfuric acid H2SO4 and nitricacid HNO3. Tests were conducted at five pH levels:
pH 2.0, pH 3.0, pH 4.0, pH 5.0 and pH 5.6, whichwere arranged using 1N H2S04 and HNO3 in distilledwater. Two test methods of infiltration and soak
methods were selected to investigate the physicochemical and engineering behavior of soils eroded
due to acid rain. Infiltration and soak tests
simulating the erosion process of soils due to acidrain were made for this study.

Fig. 11 The values of young’s modulus of specimen
tested at 7 and 14 day- curing
From the results presented in Fig 9, the computed
flexural strength from in Eq.(1) and (2) was
evaluated based on the maximum applied load. The
distance between the supports applied was 60 mm
specimens and radius 25 mm applied for all
specimens. Young's modulus of the specimen was
calculated from the deflection of the specimen after
testing in Eq (3). The maximum value of flexuralstrength and young’s modulus are shown in Fig 10
and Fig.11. Due to the slab action of the soil layers,
the result of flexural tension test was appropriate toevaluate the mechanical properties of reinforced
marine soft clay as earth structures [26]-[28].

(a) Infiltration setup

EFFECT OF ACID RAIN ON ENGINEERINGPROPERTIES OF SOILSThis research is being conducted by Zeinab
Bakhshipour, PhD student, under supervision ofProf. Bujang. B.K.Huat, and Dr. Afshin Asadi. Acid
rains is a broad term referring to a mixture of wet
and dry deposition (deposited material) from theatmosphere containing higher than normal amountsof nitric and sulfuric acids. The precursors, or
chemical forerunners, of acid rain formation result
from both natural sources, such as volcanoes anddecaying vegetation, and man-made sources,
primarily emissions of sulfur dioxide (SO2) andnitrogen oxides (NOx) resulting from fossil fuelcombustion. Acid rain occurs when these gases react
in the atmosphere with water, oxygen, and otherchemicals to form various acidic compounds. The
result is a mild solution of sulfuric acid and nitricacid with an acidic pH lower than 5.6 (Fig. 12)[29][33].

(b) Soak setup
Fig. 13 Experimental setup for (a) infiltration and (b)soak test
Fig. 14 and 15 show the consistency andunconfined compressive shear strength of the soil in
different pH respectively. The liquid limit
significantly decreased in the artificial acid rain with
pH 2.0 because of a large of exchangeable cations
were exchanged. In addition, the diffuse double
layer became thinner because the concentration of
the water-soluble cations increased. The unconfinedcompressive strength of the soils increased with anincrease in pH. The reason for this is the formationof the crystalline CaSO4 and CaCO3, which may
plug the pores of the specimens to cement the soil
particles together.

Fig. 12 Formation of acid rain in the environment byanthropogenic sources
36

GEOMATE-Nagoya, Nov.13-15, 2013

improvement using nano particles. In this study, theeffect of nano SiO2 on residual soil treated bycement was investigated. The results showed that thenano SiO2 increased the shear strength of the soil
effectively. (iii) Effect of coir fiber on flexuralstrength of the soil was investigated to evaluate themechanical properties of reinforced marine soft clay
as earth structures. The results revealed that the coirfiber increased the flexural strength of the marine
soil well. (iv) Effect of acid rain on engineering
properties of soil. In this study, effect of acid rain on
soil consistency and shear strength of soil are being
investigated. However, the research is ongoing andthe outcomes will be released in the future[34]-[38].

Fig. 14 Soil consistency in different pH value

ACKNOWLEDGEMENTS
Financial supports from research grants
No.5527094 (ERGS), No.5524133 (FRGS), andNo.9346000 (RUGS), for conducting theseexperiments are gratefully acknowledged.

Fig. 15 Unconfined shear strength of soil in different
pH value
The infiltration and soak methods were used inthis study, to illustrate the erosion process of the soil
due to acid rain. We have obtained some evidence ofthe engineering behaviors of acidified soils bymeans of an experiment simulating the erosion
process. This data may be helpful in assessing thedamaged condition of the soil due to acid rain and to
estimate the effects of acid rain on soil in the future.
The erosion by acid rain caused an increase in thesensitivity ratio of the soils. There was a comparablyincrease in the liquid limit of the soils. An increasein the unconfined compressive strength of them
could be observed in higher ranges of pH. We areplanning to investigate the underlying behavior ofdifferent soils and their mechanisms under effect ofacid rain with different compositions. The physicchemical properties of the soils will also be
investigated in this project. It can be predicted thatthe effect of acid rain on the properties of soils will
become serious if the rainwater is further acidified
due to industrialization in the future. However, theproject is ongoing further information will be
released in the future.

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CONCLUSION
This paper presents the recent geotechnicalresearch advances in the field of geotechnicalengineering in Universiti Putra Malaysia.
Concurrently, there are some research projects asfollows; (i) Electro-biogrouting method for soft soil
stabilization which is a new method. The live
bacteria or their production are injected to the soil
using an electrical gradient. The soft soil is thenstabilized through the CaCO3 precipitation. (ii) Soil
37

GEOMATE-Nagoya, Nov.13-15, 2013

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39

GEOMATE-Nagoya, Nov.13-15, 2013

Technical Papers

40GEOMATE-Nagoya, Nov.13-15, 2013

Geotechnique41

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

LANDSLIDES IN BANGLADESH: CAUSES AND RECOMMENDATION
Musahaq Ali, Zakaria Hossain and Shigeko Haruyama
Graduate School of Bioresources, Mie University, Japan

ABSTRACTThis paper gives an account of the investigation carried out to review and analyses of floods and landslides insome selected areas in Bangladesh. The study aimed to determine the main causes of failure of slope orlandslides and to suggest remedial measures for minimizing natural disasters in the country. Information on
landslide and slope failure were collected from daily newspapers, available internet sources, statistical yearbook,and technical research reports. On the basis of such information, five major devastations were taken into
consideration in this paper for detailed study. The results of analyses and discussion revealed that the major
causes of landslides were due to illegal cutting of slope by public. Other causes were identified as poor planningand faulty construction of structures neighboring to landslides sites. Analyses of slope stability with and without
pore water demonstrated that the factor of safety of slope decreased with an increase in pore water pressureduring rainfall causing the landslide devastation in Bangladesh during rainy season.
Keywords: Landslide, Flood, Heavy Rain, Bangladesh, Stability Analysis

Bangladesh but also outbreak many parts of theworld [3]. In Japan, a lot of devastating landslides
occurred almost every year. It can be noted that a
wealth of experience in understanding, recognition
and treatment of landslide hazards is needed [4].
Particular area requiring attention concerning theselection and design of appropriate, cost-effective
remedial measures which in turn requires a clear
understanding of the mechanisms and processes thatcaused the landslide [5]. Especial attention had beenrequired for the hills of Chittagong in Bangladesh as
it was particularly badly hit caused devastation due
to heavy monsoon rainfall. Sudden landslides not
only destroying lives, crops, agricultures, poultry,
fisheries and many other things but also it creates
simultaneous accumulation of silts in the river beds
and floodplains. Unfortunately, very little or no
study is available which specifies the main reasonsfor such disasters. It is therefore felt that a researchreviewing the causes of landslide in Bangladesh
should be undertaken. In order to fulfill the above
objectives, information on landslides or failure ofslopes was collected from different sources such as
daily newspaper, web page, statistical year book andtechnical reports. Discussion has been made toreveal the causes of landslides and recommendations
are made for minimizing the landslide hazard in
Bangladesh

INTRODUCTION
Heavy rains and landslides in Bangladesh
occurred during the last couple of years had killed atleast 329 people and left stranded over 1950000
people in the south-east Bangladesh. The landslides
are also a great concern in Bangladesh as they
threaten the life and property of the people in the
hilly areas of Bangladesh such as Chittagong,
Rangamati, Cox’s Bazar, Hobigonj and like othernatural disasters those frequently occurred in
Bangladesh such as tropical cyclone, flood, draught
etc. The recent Cox's Bazaar, Bandarban andChittagong landslides in 2012 that occurred on June
27 is another devastating natural disasters since theindependent of Bangladesh in terms of humancasualties damage and personal. The indiscriminate
cutting of hill that made it very steep slope, faulty
construction of homes, embankments, roads andmiscellaneous structures in the mountainous areas,
worsen by the heavy rains; had increased theoccurrences of frequent landslides especially during
the last two decades in the southern part of
Bangladesh [1]. A catastrophic super landslide likethat took place in 2007 was the most damaging one,claimed 130 lives, rendered nearly 150 families
homeless and left over 300000 people without
secure accommodation.. The tragic landslide of 1986
and 1989 claimed 51 and 300 lives respectively [2].
In recent years, the loss of life and property
which occurred due to these landslides still causing
staggering situation such as landslides in 2009, 2010
and 2011 had killed at least 81 peoples and affected
more or less all the seven landslide prone districts of
the hilly region. Landslides and related slope
instability phenomena was not only the problem in

LOCATION OF LANDSLIDESThe geographical position of landslide occurredin Bangladesh is shown in Fig. 1. The place ofoccurrence is mainly Chittagong and Cox’s Bazar
district as shown in the south-East location on themap of Bangladesh.
42

GEOMATE-Nagoya, Nov.13-15, 2013

Cox’s Bazar top tourist city of Bangladesh close to
Bay of Bengal facing heavy rains during monsoon
season in the month of June and July. Large part ofthe port city of Chittagong are badly affected byfloods (Fig.2) causing multiple landslides (Fig.3).

Fig.2 Heavy rain causing flood in Chittagong city(source: BBC)[6]Fig.1 Geographical location of landslide
Death of People During Past Five Years
The number of death of people occurred during
the past five years are given in Table 1. It is notedthat there were many other landslides took place
after the independence of Bangladesh in 42 year. In
this paper, the recent casualties are emphasized. As
can be seen in Table 1, the devastation that took
place in 2012 claimed over 118 lives along with over
250000 peoples left homeless or stranded without
proper accommodation.

Fig.3a Destruction of houses due to landslide (2012)(source:: reliefweb)[7]Table 1 Recent death of people due to landslide
Date ofoccurrence

Death ofpeopleLeftstrandedPlace2007 June 11130300000Chittagonj

2009 July 4

6500000Hobi-gonj

2010 June 1558200000Cox's Bazar

2011 July 1

17700000Chittagong

2012 June 27118250000Chittagong,
Cox's Bazar

Fig.3b Destruction of houses due to landslide (2007)(source: reliefweb)[8]
It is known that there are lot of illigal cutting of hills
in the Chittagongcity took place every year by the
influencial people. Owing to cutting of natural slope,the slope became heay stiff and sometimes theinclination were over 70 to 80 degree or close toFact findings
The Chittagong district is second largest city and43

GEOMATE-Nagoya, Nov.13-15, 2013

vertical as can be seen in Fig.4.

side soil-block, the Hi and Vi are acted in the
opposite direction due to the reaction of the left-sidesoil-block. The self-weight of right-side soil-block isdenoted by Wir. The center angle formed by thelines connecting to the center of the arc and the point
which is the cross-section of slip line and acting lineof Wir is denoted by αir., The horizontal distance
between the i-section and the acting line of Wir isdenoted by Xir and the vertical distance between the
point of action of internal forces and the slip line isgiven by Li.
Alike the right-side soil-block, the parameters
Wil, αil, Xil are also defined in the case of left-sidesoil-block.Another feature of this method is that the
point of action of internal forces to the slip circle(Li) is common for both left and right group. The
radius of the circular arc is defined by r. The
horizontal distance between the bottom edge of theslip circle and i-section is defined as Xi and thecenter angle formed by the line passing through thecross-section of i-section and slip-line with thevertical direction is defined as
i. The details omethod can be found elsewhere (Hossain and Inoue,2007). By using the determinate method, the factorsof safety of the landslide section are calculated by
the following equation.

Fig.4 Natural slope was illegally cut to stiffer
inclination susceptible to failure (source: Daily star)

CHECKING STABILITY OF SLOPE BEFORE
AND AFTER CUTTING
In order to check the effect of rainfall on thestability of slope, it is necessary to perform theanalyses considering the existence and non-existenceof pore water inside the slope for both the naturaland cut slopes. Considering the facts above, theanalyses were performed using the method ofdetermination. The main feature of this method isthat it calculates the factor of safety of a slope basedon moment equilibrium of simultaneous blocks
dividing the whole slope into two major blocks ofleft and right sides as shown in Fig.5.

FS ={H n −1 sin α n + (Wn − Vn −1 ) cosα n − unln }η
(Wn − Vn −1 ) sin α n −1 − H n −1 cosα n(1)where, n indicates the number of vertical slices,
indicates effective angle of internal friction andindicates effective cohesion of soil. Here, H is thehorizontal force component, V is the vertical force
component, W is the self weight of slice, α is theangle to the center of the circle, u is the pore waterpressure and l is the base length of the slice along
the circle. The η given in the above equation isdefined as follows.

η = tan φ ' + c ' l(2)

Figures or Tables should be sized the whole width ofa column, as shown in Table 1 or Fig.1 (Figs. 1
and/to n) in the present example, or the whole width
over two columns. Do not place any text besides thefigures or tables. Do not place them altogether at theend of manuscripts.

Fig.5 Forces acting on a slope for stability check
Where, Hi is the horizontal component of internal
force and Vi vertical component of internal force
both are acted at the vicinity of i-section owing to
the self-weight of the right-side soil-block when
considering the free-body of left side soil block. In
the same way, considering the free body of the right-

RESULTS AND DISCUSSION
The properties of soil obtained by laboratory
tests are given in Table 2.The results of analyses ofnatural slope (Fig.6) are compared to that of the cut
slope (Fig.7) in Table 3.
44

GEOMATE-Nagoya, Nov.13-15, 20131.10 respectively indicating that the factor of safety
decreased significantly with the increase in porewater pressure which leads to the failure of the slope
during rainfall because the recommended factor ofsafely values are over 1.8 or more.

Table 1 Materials properties used instability checking
Parameters

Values3

Dry density, t/m
Optimum watercontent, %Specific gravity

01.64
Table 3 Results of stability checking
21.4
02.7232

Cohesion, kN/m
Angle of internal
friction, degree
Sand, >75µm (%)

95.71

Silt, 5-75µm (%)

44.00

Clay, <5µm (%)

40.00

Liquid limit

52.0%

Plastic limit

29.7%

Plasticity index
Unified Classification
System22.3

Pore waterpressurecondition

24.21

Factor of safety
before hill
cutting

Factor ofsafety after hill
cutting

2.35

1.48

1.98

1.10

Withoutpore waterWith pore
water

16.00

CONCLUSION
From the results and discussion given above,
the following conclusions can be drawn:
1. The natural slope in the failure location in
Bangladesh was stable both in the dry season andrainy season as the factor of safety are found to beequal or more than the required factor of safety of astable slope.
2. The major cause of landslide was found to be
man-made through illegal hill cutting by influential
people of Bangladesh.
3. The other causes of landslides were identified as
the increase in pore water pressure during rainfall.
4. It is recommended that unless serious steps aretaken to correct this way of hill, the landslides in
Bangladesh are plausible to turn into even worsewith time and achieve eventually devastating
magnitude.

CH

Fig.6 Before cut: facing of natural slope

REFERENCES[1] Roy, P. (2007) Mindless hill-cutting caused
mudslide, The Daily Star, 2007-06-12.
[2] Schuster, R.L. (1991) Landslides analysis andcontrol, National Research Council, p.1-10.
[3] Sikdar, Z.H. (2007) Over 100 people were killed
and hundreds more injured due to devastatinglandslides in these areas on June 11, The Daily
Star, 2007-06-12.
[4] Iai, S., Mimura, M., Chigira, M., Kamai, T.,
Sidle, R.C., Suwa, H., Saito, T and Tobita, T.
(2006) Geo-disaster prediction and geo-hazard
mapping in urban and surrounding areas,
progress report in FY 2005, Annuals of Disas.
Prev. Res. Inst., Kyoto Univ., (49) C, 23-38.
[5] Chigira, M. and Yokoyama, M. (2005)
Weathering profile of non-welded ignimbrite andthe water infiltration behavior within it inFig.6 After cut: facing of natural slope
The factors of safety of the natural slope before
cutting are 1.98 and 2.35 with and without porewater pressure respectively. This indicates that thestability of the slope decreases due to the increase in
the pore water pressure during rainfall. After cutting
the hill, the safety values are obtained as 1.48 and45

GEOMATE-Nagoya, Nov.13-15, 2013

relation to the generation of shallow landslides,
Engineering Geology, 78, 187–207.
[6] BBC“Heavy rains and landslides in Bangladesh
kill 90”[7] reliefweb“Bangladesh: Situation Report No.233(as of 26 June 2012)”[8] reliefweb“Bangladesh Landslide and Flood
Situation Report No.234”

46

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan,Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PRECAST SPREAD FOUNDATION IN
INDUSTRIALIZED BUILDING SYSTEM
Ramli Nazir1, Ehsan Momeni2, A. Kadir Marsono3, Houman Sohaie4
Faculty of Civil Engineering, Universiti Teknologi Malaysia, Malaysia1,2,3,4

ABSTRACTThe use of IBS in construction is of interest mainly due to its relatively green technology and the fact that byimplementing IBS, the cost of construction and its required time are decreasing remarkably. Finding a total
precast solution for low to moderate rise buildings is the aim for Malaysian Construction Industry Development
Board (CIDB). However, the aim is not totally achieved yet, although many precast structures have been built,
none of them are totally precasted. In fact, the substructures are cast in place. The current aim of the research in
Universiti Teknologi Malaysia (UTM) is to develop and introduce a new thin wall precast spread foundation
known as IBS footing for low to moderate rise buildings to complete the cycle of using precast elements foraffordable houses. This study reviews developed precast spread foundation as well as investigates the axial
bearing capacity of a new proposed IBS footings as this parameter plays an important role in the design offooting. For this reason, a set of parametric studies using finite elements code, PLAXIS,were conducted toevaluate the optimum shape of spread foundation suitable for rapid construction. The parametric study results
show that the effect of increasing the length of foundation thin walls on axial bearing capacity is much more thanthat of wall thickness. Based on the results of the parametric study, the new IBS footing was proposed.
Consequently, the proposed IBS footing was analyzed numerically by implementing the finite element software,
ABAQUS. The numerical results reveal that the bearing capacity of the proposed IBS footing is 380 kPa for 25
mm settlement. In general, numerical results confirm that the proposed IBS footing can be considered for further
investigation to be used as a substructure system in low to moderate rise buildings.
Keywords: ABAQUS, Bearing Capacity, Granular Material, PLAXIS, Precast Spread Foundation

Apart from economical perspective, the use of
IBS has other advantages such as rapid construction,
reduction in site workers and wastes, less affection
by weather condition, relatively higher quality andsafer construction. On the other hand, IBS
implementation has some disadvantages such as theneed for high initial capital cost, competent andcertified assembler,and site accessibility requirement[11]. Although IBS implementation has somedisadvantages, the advantages of IBS usage
outweighted the disadvantages.The use of precast
elements such as beam, column, wall and panels iswell established. However, when it comes to precast
spread footing, only a relatively few numbers ofreported cases can be found in literature. This
excludes the use of precast driven piles as a kind ofdeep foundations. In fact, from the economical pointof view, many studies show that spread foundations
are more preferable. In other words, the use ofshallow foundations instead of deep foundations can
reduce the cost of project from 20 to 70 percents[12].

INTRODUCTION
Implementation of Industrial Building System(IBS) has recently become highlighted inconstruction industry [1]. Among many technicaldefinition of IBS [2]-[6]Warszawski [7] expoundedthat an industrialization process is an investment inequipment, facilities, and technology with theobjective of maximizing production output,
minimizing labor resource, and improving quality
while a building system is defined as a set ofinterconnected element that joint together to enable
the designated performance of a building. However,Kamar [8] mentioned that in Malaysia, IBS
definition represents the concept of prefabricationand industrialization of construction. A survey on
the usage of IBS [9] in Malaysian constructionindustry shows that almost 70 percent of engineers
have positive point of view towards IBS
implementation in construction. This is due tonumerous advantages of IBS implementation incomparison to the conventional method of
construction. Many researchers have investigated theadvantages of IBS usage. Among others, study by
Cheong [10] shows that through IBS implementation,
the cost of project can be reduced up to 46% of thetotal cost.

INTRODUCTION OF A NEW PRECAST THIN
WALL FOUNDATION
The idea of precast thin wall foundation
originated from the Malaysian`s ancestors usage of47

GEOMATE-Nagoya, Nov.13-15, 2013

invert bottles or barrels as a foundation for theirhouses. In order to investigate the geotechnicalperformance of such thin wall foundation as well as
develop its optimum shape, the initial idea wasevolved and extended through a comprehensive
parametric study.
The finite element code, PLAXIS [13], was used
for the course of the parametric study mainly due toits availability and ease of use. In this parametricstudy, the effect of some parameters including theeffect of both wall length and wall thickness on the
bearing capacity of the proposed IBS footing isinvestigated.
It is apparent that soil strength and foundation
width also can effectively increase the bearing
capacity of foundation [14]. However, due to their
obvious effects on bearing capacity, these factors are
excluded in the parametric study.

Fig.1

Different foundations used for parametricstudy

The prescribed displacement method for which a
certain displacement will be imposed on the top of
the footing was considered for analysis. The
maximum allowable settlement was considered to be
20 mm [13].The calculation was divided into twophases. In the first step, water level was defined andthe initial effective stresses are generated by K oprocedure.

Parametric Study
In order to conduct a parametric study for precast
thin wall spread foundation or IBS footing, someplane strain models were considered in PLAXIS
version 2010 (see Figure 1). A working area of 10 m
width and 10 m depth was used to minimize theboundary effects. The width and wall length ofdefault footings (Figure 1-b)were equal to 1 m anddefault wall thickness was equal to 10 cm. The cap
was set to be 20 cm by 20 cm.
The soil was modelled as one layer of sand. The
Mohr-Columb (MC) model was considered for soil
constitutive model. The drained behavior was
assumed due to the type of material i.e sand.
On the other hand, for concrete material i.efooting, a Linear Elastic (LE) model was selected todefine the concrete behavior. The concrete wasselected as a non-porous material.
The coefficient of earth pressure, K o , in analysis
was approximated by considering Jacky`s estimateof K o =1-sinφ [15]. The materials properties forparametric study were taken from the study
conducted by Momeni et al.[14] and they aretabulated in Table 1.
To define boundary conditions, standard fixities
PLAXIS tool were used. These boundaries aredefined in a way that for vertical geometry line,
there is a horizontal fixity while the bottom
horizontal geometry line is fixed vertically andhorizontally.
According to a study conducted by Lebeau[16] insandy soils, the size of mesh in PLAXIS does nothave considerable effect on output curves. Therefore,
in this study, course mesh size was considered forthe further finite element analysis as shown in
Figure 2.

Table 1 Material Properties for parametric study
Material

SymbolSand

Footing

Unit

Material Model

-

MC

LE

-

Unit Weight

18

24

kN/m3

Stiffness

γ
E

14.4

26E3

MPa

Poisson`s Ratio

υ

0.35

0.15

-

Friction Angle

φ
c

30.5

-

degree

0.06

-

kPa

Cohesion

The initial phase also dealt with generating thehydrostatic pore water pressure based on the waterlevel. The water was leveledon the bottom geometryline to represent the dry condition. In the second
phase, the static plastic analysis was selected for thetype of analysis. Since the analysis was
static,thewhole analysis can be applied in one
stage.Both stage construction and total multipliertechniques could have been used in this study,
however, the results are obtained using stage
construction method.
Different analyses were performed to investigate
the effect of important structural elements on the
bearing capacity of IBS footing. In fact, theparametric study dealt with the effect of wall and its
size variation on geotechnical performance offooting. The analysis began with bearing capacity
estimation of simple footing (Figure 1-a). The
analysis was then repeated for default footing(Figure 1-b).

48

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 2

Generated mesh for footing before analysis.

Fig. 3

Deformed mesh after analysis

Fig.4

Schematic figure of the parametric study
results

In order to investigate the effect of wall length on
the bearing capacity, third analysis was conductedon the aforementioned footing except that the lengthof walls was increased 1.5 times (See Figure 1-c).
For last analysis, to investigate the effect of wall
thickness on bearing capacity, the wall thickness ofdefault footing was increased two times while thewall length was kept constant (Figure 1-d).
the deformed mesh of one of the footing in addition
to the results of four different analyses is shown in
Figure 2 and 3 respectively.
Figure 4 shows that, for 20 mm settlement, themaximum axial bearing capacity is almost 90 kN/m.
However, by adding the embedded walls, the axial
bearing capacity was increased up to 110 kN/m. Thisis almost 25% higher than simple footing whichshows the importance of such walls on the axial
bearing capacity. Figure 4 also depicts theeffectiveness of wall length and thickness on thegeotechnical performance of footing.
As shown in this schematic figure, for the casethat wall length is increased 1.5 times and the wall
thickness remained constant (Figure 1-c), the rate of
the increase in bearing capacity is much more thanthe case that wall length is kept constant and thewall thickness increased two times (Figure 1-d).
In other words, in comparison to the default
footing (Figure 1-b), there is 10% increase inbearing capacity for the latter case while for theformer case this rate is 15%. In interpreting theresults, it is worthy to note that the wall length isincreased 1.5 times while the thickness of the walls
is increased two times. In fact, it can be determinedfrom the results of the parametric study, the effect ofincreasing wall length on axial bearing capacity ismuch more than that of wall thickness.

Proposed IBS Footing
Based on the results of parametric study, andengineering judgment, a thin wall precast spreadfoundation (IBS footing) suitable for low tomoderate rise buildings is proposed. The proposed
IBS footing is shown in figure 5. In the proposed
footing, some other factors such as transportability
are considered. Hence, the wall thickness which
does not have remarkable effect on the bearing
capacity of footing is considered to be 5 cm. On theother hand, to prevent the walls from brittle failure, abracing system was developed as shown in figure5(b). The wall length was set to be 1.1 m and thewhole square IBS footing was selected to be 1.5 m
by 1.5 m. Other dimensions are shown in the Figure
5.
FINITE ELEMENT ANALYSIS OF THE IBSFOOTING
The proposed precast thin wall spread foundation(IBS footing) was modelled numerically using finite
element technique. Discretization of continuous
media by finite number of elements is known as
Finite Element (FE) method [17]. Due to specific49

GEOMATE-Nagoya, Nov.13-15, 2013

layer is fixed in all directions while for verticalboundaries only the horizontal movement is fixed.
The automatic meshing technique was employedmainly due to the specific shape of the IBS footing.
Nevertheless, in the vicinity of the footing, finermesh was considered because of significant
displacement change in this area as well as the factthat this zone is the zone of stress concentration.
It is worthy to note that Four-node linear
tetrahedron coupled displacement-pore pressure
elements (C3D4P) were considered for FE analysis.
The finite element mesh used in the analysis consistsof 5571 nodes and 27652 elements. The generated
mesh is shown in Figure 6.
In the analysis of the foundation, as mentioned
earlier, the load is applied using a constant downward displacement boundary condition at the normalsoil-footing interface areas. This type of boundary
condition causes the footing to settles uniformly.
The sum of reaction forces over the area, in which
the downward displacement boundary condition isdefined, is considered as the bearing capacity of thefooting [21], [25].
Due to the static nature of the problem, static
analysis was performed. In the beginning of theanalysis, gravity loads were applied to the soil body.
Subsequently, geostatic command was invoked for
determination of the initial stresses in all
soilelements and to make sure that equilibrium issatisfied within the sand layer.

shape of the proposed IBS footing, the finite element
code, ABAQUS [18], was implemented in this study.

Fig.5

Proposed IBS footing: a) isometric view,b) Bracing system, c) bottom view, d) crosssectional view

One layer of sand with c’=0 kPa and φ’=37o wasconsidered for FE analysis. The surface area of sandstratum was 81 m2 while its depth was 7m. The
boundaries were selected in accordance to previous
literature suggestions [13]. However, in order toreduce the computation time, only one-fourth of thefooting was modelled. This can be done due tosymmetry of the problem.
For successful numerical analysis to be
performed, the soil behavior should be definedproperly and realistically. Hence, modified DruckerPrager constitutive model with cap was considered
for defining the soil behavior. It is well establishedthat the soil behavior is stress dependent [20] and thecap model used in this study considers thissignificant factor. The cap eccentricity value, R,
used in this study was 0.4 [19]. Table 2 shows othercap model parameters which are taken fromHelwany [19].
The IBS footing was considered to be rigid and it
is assumed to be in perfect contact with soil. Studyby Merifield and Nguyen [21] shows that the soilfooting interface strength has little or no effect on
the calculated bearing capacity. In order to model arigid footing, a downward displacement boundary
condition was applied on the soil stratum [22]-[24].
Since the maximum allowable settlement forbuildings is often considered to be 25 mm, thisamount was applied on the soil body in 25
subsequent steps. In each step, 1 mm prescribed
downward displacement was applied over thenormal soil-footing interfaces area. The sand bottom

Table 2 The Modified Drucker-Prager
Parameters for sand layer
Parameters
Density
Initial void ratio
Elasticity
Poisson`s ratio
Cohesion
Friction Angle(3-D model)
Eccentricity
Coefficient of transition
surface
Initial Yield

Fig. 6
50(D-P)

Symbol

Sand

Unit

ρ
e0
E
υ
d
β

1923
1.5
182
0.28
10-5
55

kg/m3
MPa
kPa
degree

R
α

0.4
0.05

-

0

-

IBS footing Generated Meshes

GEOMATE-Nagoya, Nov.13-15, 2013

remarkable. Based on the results of the parametricstudy and some other factors such as transportabilityof the footing, a precast thin wall spread foundation
known as IBS footing was introduced.

RESULTS AND DISCUSSION
The results of the aforementioned finite element
analysis are discussed in this section. The deformed
mesh is shown in Figure 7 while the influenced zoneof the soil due to vertical displacement is shown in
Figure 8. The blue color indicates zero displacement.
As shown in this figure, the soil defined boundaries
are assigned properly. It is worthy to note that, inFigure 8, the ABAQUS mirror tool was used forvisualization purpose. Based on the results, thesignificant displacement occurs within vertically 2B(B is the footing`s width) below the footing andhorizontally 1.5B from the center point of thefooting which is in good agreement with Boussinesq
theory and the well-established experimental study
by Briaud and Gibbens [12]. According to the wellestablished literature, the horizontal influenced zone
is often 2.5B to 3B for simple footing. Nevertheless,the remarkable decrease inhorizontal influenced
zone might be due to embedded thin walls.
The load-settlement curve of the footing for 25
mm settlement is shown in the figure 9. As shown
schematically in this figure, the bearing capacity ofthe proposed IBS footing for allowable settlement is
380 kPa. It is discussed earlier that the bearing
capacity of the footing is obtained by summation ofreaction forces over the applied prescribed
displacement area using history output menu in
ABAQUS.

Fig. 7

Fig.8

Influenced zone of the soil under 25 mm
settlement

Fig. 9Load-displacement curve under the IBS
Footing

The proposed IBS footing was analyzed
numerically by using the finite element software,
ABAQUS. From the finite element analysis, it isfound that the bearing capacity of the proposed
footing is 380 kPa for 25 mm settlement. Apart from
that, the numerical analysis of the IBS footing showsthat the vertical zone of influence of the soil body is
within 2B from the center point of the footing whilehorizontal zone of displacement is located in area
between the center of the footing and 1.5B after it.
The influenced zone of the sand layer consideredin this analysis lies inside the suggested range ofinfluenced zone of displacement provided byresearchers in well-established empirical studies.

IBS footing deformed mesh

SUMMARY AND CONCLUSION
The importance of IBS and precast spreadfoundations was investigated through a criticalreview. Apart from that, a parametric study fordeveloping a new precast foundation was conducted.
The results of the parametric study reveal that theeffect of embedded wall on bearing capacity is
51

GEOMATE-Nagoya, Nov.13-15, 2013

Bearing Capacity of Driven Piles in GranularMaterials. Jurnal Teknologi, Vol. 61, 2013.
[15] Jaky J, The Coefficient of Earth Pressure atRest. In Hungarian (A nyugalmi nyomas
tenyezoje), J. Soc. Hung. Eng. Arch.
(MagyarMernok es Epitesz-Egylet Kozlonye),
1944,pp. 355–358.
[16] Lebeau JH,FE-Analysis of piled and piled raftfoundations, Graz University of Technology.
Project Report, 2008.
[17] Chen WF,Limit Analysis and Soil Plasticity,
US: Ross J, Publishing,2008. Ch. 12.
[18] Abaqus 6.9 FEA software manual,SIMULIA,
Rising Sun Mills, 166 Valley Street,
Providence: RI 02909-2499, USA, 2009.
[19] Helwany S,Applied soil mechanics withABAQUS` applications. Hoboken, New Jersey:
John Wiley & Sons, INC, 2007.
[20] Brinkgreve RBJ, Selection of Soil Models andParameters for Geotechnical Engineering
Application, Journal of Geotechnical andGeoenvironmental Engineering,ASCE, 2005.
[21] Merifield RS, Nguyen VQ,Two- and threedimensional bearing–capacity solutions forfootings on two-layered clays." Geomechanics
and Geoengineering: An Intl. J., Vol. 1(2),2006, pp. 151-162.
[22] Gu J, Computational Modeling of Geogrid
Reinforced Soil Foundation and Geogrid
Reinforced Base in Flexible Pavement,
Louisiana State University. PhD Dissertation,
2001.
[23] Zhu M, and Michalowski RL, Shape factors forlimit loads on square and rectangular footings. J.
Geotech. Geoenviron. Eng., Vol. 131(2), 2005,
pp. 223-231.
[24] Gourvenec S, Randolph M, Kingsnorth O,
Undrained Bearing Capacity of Square andRectangular Footings, International Journal of
Geomechanics, Vol. 6,2006, pp. 147-157.
[25]
Zhu M, Bearing Capacity of Strip Footings
on Two-layerClay Soil by Finite Element
Method, ABAQUS Users’ Conference, 2004.

ACKNOWLEDGEMENT
The authors would like to thank the Research
Management Centre of Universiti Teknologi
Malaysia (UTM) and Ministry of Science,
Technology and Innovation (MOSTI) for providing
financialsupportthrough
research
vote:
R.J130000.7822.4L130 for bringing the idea into
fruition.
REFERENCES[1] Elliot KS, Precast concrete structures. Spon
Press, 2002.
[2] CIB. New Perspective in Industrialization inConstructionstate-of-art
Report,CIB
Publication 329, 2010.
[3] Richard RB, Reproduction before automation
and robotics. Journal of Automation inConstruction, Vol. 14, 2005,pp. 251-441.
[4] Cooper R,Progress management in Design andConstruction, Oxford London: Blackwell
Publishing , 2005.
[5] Trikha DN, Industrialised Building System:
Prospect in Malaysia. Kuala Lumpur: In
Proceeding of World Engineering Congress,
1999.
[6] Junid SMS, Industrialised Building SystemProceedings of a UNESCO/FEISEAP Regional
Workshop, 1986.
[7] Warszawski A, Industrialised and Automatedbuilding systems. Technion-Israel Institute ofTechnology, E & FN Spon, 1999.
[8] Kamar KAM, Industrialized building System(IBS): Revisiting Issue of Definition andClassification.
International Journal of
Emerging Sciences, Vol. 1(2), 2011, pp. 120132.
[9] Shaari and Nizar, Survey on the Usage ofIndustrialised Building Systems (IBS) in
Malaysian Construction Industry, CIDB
Malaysia Publication, 2003.
[10] Cheong GK, Fully precast system at Choa Chu
Kang. Precastech Newsletter On Line,Vol. 8,
1997.
[11] Badir YF, Kadir MRA, and Ahmed HH,
Industrialized building systems construction in
Malaysia, Journal of Architectural Engineering
8, Vol. 1, 2002, pp. 19-23.
[12] Gibbens RM, and Briaud JL, Load tests on fivelarge spread footings on sand and evaluation ofprediction methods, Rep. to the Fed. Hwy.
Admin., Dept. of Civ. Engrg., Texas A&M
University, College Station, Tex, 1995.
[13] US Army Corps of Engineers, Bearing Capacityof Soils, Engineering Manual,1992.
[14] Momeni, E, Maizir, H, Gofar N, Ramli, N,
Comparative Study on Prediction of Axial

52

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CATEGORISING GEOTECHNICAL PROPERTIES OF SUBSOIL IN
SURFERS PARADISE USING GEOGRAPHIC INFORMATIONSYSTEM (GIS)
Haider Al-Ani1, Leila Eslami-Andargoli2, Erwin Oh1, and Gary Chai3

3

1School of Engineering, Griffith University, Australia

2

School of Environment, Griffith University, Australia

Centre for Infrastructure and Engineering Management, Griffith University, Australia
ABSTRACTPeat is a highly organic and compressible soil. Surfers Paradise (as a study area) has problematic peat layer which hasdifferent thickness at different locations between R.L. -10 to -19.6 m below the ground surface. Buildings in Surfers
Paradise are using piled foundations to avoid the high compressibility and low shear strength peat layer. In this paper,
geotechnical borelogs are compiled from 51 sites in the study area. These borelogs data are then imported into
ArcGIS10 as digital layers and converted into assessable formats by Geographic Information System (GIS). This
technique has been utilised to produce digital zonation maps for the study area. The application of interpolation
techniques allows the production of zonation maps and bring together years of geotechnical data. Standard Penetration
Test (SPT) N values have been selected to determine the soil stiffness in the study area. These SPT-N values are thencategorised to produce different zonation maps. The occurrence of peat layers can be located using these zonation maps.
These GIS-based zonation maps will provide a better overview of subsurface geology, bed rock elevations, andgeotechnical properties of the various soil types found in the study area.
Keywords: Peat, Geographic Information System, Standard Penetration Test, Spatial Analyst.
In addition, in Greece, GIS has been used to produce athematic map for the geotechnical, geological,
seismological, and geomorphological data of Athens[5]. In Turkey, reference [6] has used GIS to produce
zonation maps and to estimate if a further precaution isrequired for a safer area. Cross sections which include
SPT-N blow count with depth have been performed todetermine the soil strength. Further, GIS-based
geotechnical information systems have been establishedin the USA, Singapore, Brazil, and Japan in 2003, 2005,
2003, and 2010 respectively. The purpose of this is a
web-based easy access to the geotechnical data of any
area of interest to have an idea about geotechnicalconditions of this area. In addition, four case studies ofsmall scale geotechnical projects have been studied by[7] to verify the benefits of using GIS in geotechnicalengineering in The United Kingdom. The outcome ofthis study indicated that GIS output improved theanalytical and technical range of these projects incomparison with traditional techniques and the highquality produced maps are comprehensible and popularwith engineers.

INTRODUCTION
GIS has the capability to manage, store, andreferencing geotechnical data to its geographic
locations. It has been used to integrate existing datasuch as soil investigations aided by geographic
coordinates with specific project data to identify
potential geotechnical challenges. For instance, a casestudy has been presented by [1] where a geotechnicalinvestigation data has been managed by using GIS for
design purposes in transportation projects. The outcomeof this study was an early identification of thegeotechnical problems which require an additional
budget and time consuming design’s substantialchanges. It is generally accepted that the organic matterpresence in soils causes a detriment of theirgeotechnical and engineering qualities [2]. Peats andorganic clays cause typical geotechnical problems as aresult of their characteristics such as compressibility,
lightness, creep ability, weatherability, and low strengthand stiffness [3].
GIS Application in Geotechnical data

This paper shows the identification of peat layer
occurrence in Surfers Paradise as a case study inAustralia. The occurrence of peat has been identified byproducing the interpolated SPT-N value zonation maps
by using the Spatial Analyst extension and interpolation

GIS has been used in many geotechnicalapplications ubiquitously over the world. For example,
in Brazil, GIS used for geotechnical and environmental
risk management of Brazilian oil pipeline in 2010 [4].

53Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

techniques. Peat occurrence’s depth and thickness havebeen also determined in the study area.
METHODOLOGY
Two approaches have been utilised to produce GISbased SPT-N value zonation maps. The first approach
was by collecting the geotechnical data from thegeotechnical investigation reports. These data wereavailable in many different locations and forms. Next,
data has been tabulated by using Excel to make itfamiliar with the GIS environment. The spatial
locations of boreholes have been designated by using
Google Earth based on boreholes actual locations oneach project’s site plan. By calculating the distances
between separate boreholes and the distance between
the borehole itself and the adjacent boundaries on thesite plan, boreholes’ coordinates can be acquired from
Google Earth. Randomly chosen boreholes have beenchosen to validate coordinates before transferring thesecoordinates into GIS environment.

Fig 1 Designation of boreholes geographic coordinates.

Figure 1 shows the procedure of obtaining theboreholes coordinates from a project site plan. Figure 2
illustrates the transformation of geotechnical data from
Excel spread sheets into ArcMap. The red dots on the
GIS map represent the borehole’s spatial locations.
Each borehole has its own spatial data as well as
geotechnical data which have been uploaded from
Excel. It can be observed from Fig.3 that thegeotechnical data has been horizontally tabulated in
Excel sheet in a way to be compatible with the GIS
setting.
The second approach has been achieved byexamining eight interpolation techniques in the Spatial
and Geostatistical Analyst in ArcMap10. The purposeof this approach is to interpolate the SPT-N value andproducing the zonation maps.
The eight interpolation techniques examined were:(1) Geostatistical Analyst Tools, IDW method (2)Geostatistical Analyst Tools, Diffusion method (3)Geostatistical Analyst Tools, Global Polynomial
method (4) Geostatistical Analyst Tools, Kernel method(5) Spatial Analyst Tools, Ordinary Kriging (6) Spatial
Analyst Tools, Universal Kriging (7) Spatial Analyst
Tools, Spline (8) Spatial Analyst Tools, IDW method.

Fig. 2 Geotechnical data transformation into GIS
environment
STUDY AREA
Surfers Paradise has a unique prominent location
which increases the tourism and commercial activities
in Gold Coast in the state of Queensland, Australia. It
has been an iconic tourist destination since 1950s and itis the most famous location in Australia. Surfers
Paradise has an area about 4 by 1.3 km2 and the NerangRiver divided it into two main parts Nerang River parts
and Beach side part. The study area includes the area
which is located between the Nerang River and theCoral Sea (Fig.3).

The interpolation technique of Spatial Analyst
Inverse Distance Weighting method (IDW) was themost suitable technique which gives a better
representation for the SPT-N data in Surfers Paradisewith specific parameters. This is consistent with what[8] has found.
The spatial analyst extension employs the Inverse
Distance Weighting (IDW) interpolation method tocreate these maps. The interpolation, in turn, is aprocedure being used to predict the values of cells at
certain locations that lack sampled points [9].

The soil profile of the study area is based on [10] and it
is as follow:

54

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

•
•
•
•

•

•

Further, peat existence locations map is alsopresented for the study area. These locations areassociated with its boreholes to show the peat depth andthickness in each location.
The first zonation map is nearly shallow in depth
R.L. 2.3 to 0 m. The Australian Height Datum (AHD)
has been used for the depth considerations. Figure 4
shows the distribution of the soil stiffness values in the
study area. It can be observed that the SPT-N value inthe northern parts of the study area was between 0-10
blows for very loose to loose sand. Whereas, in thesouthern parts was quite high > 30 blows which
represents dense sand. The sand classification has been
adopted based on [12] in terms of number of blows of
the SPT. There are some locations within the study area
are not spatially interpolated and it seems to be blankdue to the lack of geotechnical data in this depth atthese locations.

Loose to medium dense sand starts from theground surface to R.L. 2.3 m.
Medium dense to dense sand is underlain from
(R.L. 2.3 m) to (R.L. -3.2 m).
Very dense sand is encountered from (R.L. 3.2 m) to (R.L. – 20 m).
Within the very dense sand layer, a varying
thickness peat layer is occurred at depth
between (R.L. -10 to R.L. -19.6 m) at different
locations with thickness ranges from (0.1 – 7m).
An interbedded firm to very stiff clay layers
are found up to (R.L. -26.6 m) where a layer offirm to hard clay is occurred below it until thedepth (R.L. -29 m).
The last layer of this soil profile varies within
the study area where in some locations there isan interbedded layer of medium dense sand,gravelly sand, clayey sand, sandy clay, or hardsilty clay can be observed.

The second SPT-N value zonation map has been
performed for the depth between R.L. -13 to -15 m (Fig.
5). It can be seen that the dominant soil stiffness value
for this depth is between 31-49 blows which can beclassified as dense sand. There are also some locationsof very loose sand and loose sand of SPT-N value
between 0-10 blow.

This soil profile is consistent with the description
given by [10] and [11].

Fig. 3 the location of the study area
RESULTS
Twenty six interpolated maps have been performed
for the study area at depths ranged between the groundsurfaces until depth of R.L -40. These maps have been
produced by using the Spatial Analyst IDW techniquewhich has been selected among eight interpolation
techniques to give a better representation of the datawith specific parameters. These parameters are: output
cell size: 2.719E-05, power 2, search radius: fixed, anddistance 0.25.
In this paper, only four GIS-based SPT-N value
zonation maps have been provided to represent different
depth classes. These four zonation maps represent
different depth levels (near the surface until R.L. -26.6m). Also, it shows variety of soil classes in terms of
SPT-N values.

Fig.4 SPT-N value zonation map at depth R.L. 2.3-0 m.

55

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Figure 6 shows the third zonation map for the SPTN value at depth between R.L. -20 to -21.6 m. It can benoticed that the extent of this zonation map is smaller
than the previous zonation maps. That is because thelacks of data at this depth level which prevent theinterpolation process to be completed in the unclassified(un-interpolated) areas.
The last zonation map for the soil stiffness in thispaper is located at depth between R.L. -25 to -26.6 m.
Figure 7 shows the distribution of the SPT-N value
within the study area and indicates that the dominantvalue for this depth is between 11-30 blows. This isbecause of interbedded layers of soft to firm clay andmedium dense sand. Very loose sandy clay is also
existed in the northern part of the study area.
Nonetheless, Peat locations have been identified
within the study area in 16 locations (Fig. 8). These
locations represent already existed buildings and otherengineering structures in Surfers Paradise [10]. Eachlocation in this figure has been given a number todenote peat’s depth and thickness in this particularlocation (Table 1). Figure 9 shows the borehole
distribution of these locations within the study area.
These boreholes contain peat in its soil profile.
It can be seen from Table 1 that peat layer has avarying thickness which ranges between 0.1-7.0 m at
depth between R.L. -10 to -19.6 m below the groundsurface. As mentioned, peat is geotechnicallyproblematic soil and many engineers try to avoid theadventure of construction over peat. Therefore,
attention should be required for the already existedbuildings and safety precaution is also necessary for the
proposed new engineering structures in the peat
locations. Approximately all the buildings in the study
area are supported by pile foundations. Thus, this study
will be useful for the potential engineering structures totake into account the depth and the thickness of peat fora suitable, economic, and safe design in Surfers
Paradise.

Fig. 5 SPT-N value zonation map at depth R.L. -13 to 15 m.

CONCLUSION
To conclude, eight interpolation techniques havebeen used to characterise the subsoil conditions in
Surfers Paradise. The Inverse Distance Weighting (IDW)
technique within the Spatial Analyst in ArcMap10
showed a better representation for the Standard
Penetration Test (SPT) N values with a certain
parameters. Based on this, 26 interpolated SPT-N
values zonation maps have been performed tocharacterise the soil in terms of soil stiffness by using
the IDW technique.
Peat is highly organic and compressible and it has
been considered as a geotechnically problematic layer.
This layer has a varying thickness ranges between 0.17.0 m at depth between R.L. -10 to -19.6 m below theground surface in the study area.

Fig.6 SPT-N value zonation map at depth R.L. -20 to 21.6 m.

56

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Fig. 7 SPT-N value zonation map at depth R.L. -25 to 26.6 m.

Fig. 9 Peat contained boreholes in the study area.
In addition, attention should be paid in terms ofpotential foundations challenges, to locations whichhave a high thickness of peat such as a location in thecore of the study area which has a peat thickness of 7.0
m. This study might be beneficial for public agency
geotechnical engineers and decision makers at local andstate levels.
This paper is a part from an ongoing research tocharacterise physical and engineering properties of peatand soil in Surfers Paradise in Southeast Queensland,
Australia.

REFERENCES[1] Player RSV, “Geotechnical Engineering forTransportation Projects”, GeoTrans 2004, 2004,
p.p. 886-893.
[2] Malkawi AIH, Alawneh, AS & Abu-Safaqah,“Effects of organic matter on the physical and thephysicochemical properties of an illitic soil”,
Journal of Applied Clay Science, Vol. 14, no. 5-6,
1999, pp. 257-78,[3] Haan EJ and Kruse GAM, “Characterisation andengineering properties of Dutch peats”, Vol. 3, Ed.
Tan TS , Phoon KK , Hight DW & Leroueil S,
Taylor & Francis Group, London, , 2007, pp. 210133.
Fig. 8 Peat occurrence locations in the study area

57

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Table 1 Peat thickness and its depths below the ground surface in the study area.
Location
1
2
3
4
5
6
7
8

Peat Depth(m)27.2 - 32.2
1.2-6.7
14.9-17.5
12.6-14.4
16.0-23.0
17.75 - 21
17.1-18.3
18.0-22.5

Peat Thickness
(m)
5.0
5.5
2.6
1.8
7.0
3.25
1.2
4.5

Location
9
10
11
12
13
14
15
16

Peat Depth(m)17.0-20.0
15.4-19.4
17.7-21.7
11.6 -12.4
11.3-12.5
21.4 - 23
17.0 - 22.0
0 - 1.5

Peat Thickness
(m)
3.0
4.0
4.0
0.8
1.2
1.6
5.0
1.5

Surfers Paradise, Southeast Queensland, Australia”,
Electronic Journal of Geotechnical Engineering,Vol. 18, June 2013, Bund.I, 171.
[9] Childs, C, “Interpolating Surfaces in ArcGIS
Spatial Analyst”, ArcUser, Vol. July-September,
2004, pp. 32-5.
[10] Al-Ani H, Oh E, Chai G, “Engineering propertiesof peat in estuarine environment”, in in Proc. 1st
Int. Conf. on Foundation and Soft GroundEngineering Challenges in Mekong Delta, 2013,
pp. 181-191.
[11] Oh, EYN, Huang M, Surarak, C, Adamec, R &Balasurbamaniam, AS, “Finite Element Modellingfor Piled Raft Foundation in Sand”, in Eleventh
East Asia-Pacific Conference on StructuralEngineering&
Construction(EASEC-11)“Building a Sustainable Environment”, Taipei,
Taiwan, 2008, p. 8.
[12] Look, BG, “Handbook of Geotechnical
Investigation and Design Tables”, London, Taylor& Francis, 2007, ch.5.

[4] Augusto FO, Hirai JN, Oliveria AS & Liotti ES,“GIS applied to geotechnical and environmental
risk management in a Brazilian oil pipeline”,
Bulletin of Engineering Geology and The
Environment, Vol. 69, 2010, pp. 631-41.
[5] Antoniou AA, Papadimitriou AG & Tsiambaos G,“A geographical information system managing
geotechnical data for Athens (Greece) and its use
for automated seismic microzonation”, Natural
Hazards, Vol. 47, 2008, pp. 369-95.
[6] Orhan A and Tosun H, “Visualization of
geotechnical data by means of geographic
information system: a case study in Eskisehir city
(NW Turkey)”, Environmental Earth Sciences, Vol.
61, 2010, pp. 455-65.
[7] Hellawell EE, Lamont-Black J, Kemp AC, andHughes J, “GIS as a toll in GeotechnicalEngineering”, Geotechnical Engineering, Vol. 149(2), 2001, pp. 85-93.
[8] Haider A., Oh E, Leila E, Chai G, “Subsurface
Visualization of Peat and Soil by using GIS in

58

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EVALUATION OF CONSTITUTIVE MODEL IN SIMULATING THE
BEHAVIOR OF CEMENT-TREATED SOIL

1,2&3

Ay Lee Saw1, C F Leung2 and S A Tan3
Centre for Soft Ground Engineering, National University of Singapore, Singapore

ABSTRACT
Owing to presence of thick soft marine clay in Singapore, it is often required to improve the in-situ weak soilfor various construction purposes especially for excavation works. One such ground improvement technique is totreat the soft clay with cement. The treatment may be conducted at shallow depths not far below the ground levelto facilitate an open excavation or at greater depths as embedded struts to support deep basement excavation
works. However, relatively little studies had been performed to study the former treatment method. The current
design practice evaluates the problem as an embankment stability situation where the focus is drawn to theshearing and sliding failure modes. Very often, elastic-perfectly plastic soil model using the material shear
strength is adopted to simulate the behavior of cement-treated soil in the analyses. However, other failure modes
such as bending and tensile failure may be overlooked. In this study, the use of three types of constitutive model,
i.e. elastic-perfectly plastic Tresca, isotropic hardening/softening and concrete damage plasticity model insimulating the cement-treated soil behavior are examined. Available compression and tension laboratory tests for
cement-treated sand are calibrated to compare the use of selected constitutive models. Calibration results showthat the concrete damage plasticity model is able to capture the softening behavior of cement-treated sand in bothcompression and tension. This constitutive model is further validated by simulating a full scale test of cantilevercement-treated soil column under lateral load. 3-D finite element analysis result shows that the load-deflection
relation is in good agreement with field measurement. Moreover, the predicted crack development in the treatedcolumn agrees well with the field observation.
Keywords: Cement-treated soil, Constitutive model, Concrete damage plasticity, Tension-softening

capacity are examined. Generally, the weighted
average method is adopted to obtain the average
properties of the improved ground. For internalstability analysis, rupture breaking failure is
examined by a slip circle analysis where the shear
failure of treated column is assumed and the induced
stress on the column should be less than theallowable strength. Nevertheless, some studies
revealed several failure modes that are not coveredby current design practice such as bending andtensile failure [4]. It is also proposed that finite
element (FE) analysis should be conducted to study
the development of stress and strain in the improved
ground by CDIT 2002.
In this paper, numerical constitutive models in
simulating the cement-treated soil are evaluated.
Three types of constitutive soil model, i.e. Tresca,
isotropic hardening/softening and concrete damage
plasticity (CDP) are compared to examine the mostappropriate model to describe the behavior of
cement-treated soil. Then, a full scale bending test oflaterally loaded cantilever cement-treated column isanalyzed using the CDP model. The simulations aremodeledwithfiniteelement
softwareAbaqus/Standard 6.10.

INTRODUCTION
Cement is often used as a binder in ground
improvement work to increase the strength andstiffness of in-situ soft soil. Generally, a soft soil
layer of certain thickness is improved by installing
overlapping treated columns and employed as anembedded strut supporting the retaining wall system
in deep basement excavation work. The successful
case histories of adopting this method to facilitate
deep excavation work in soft clay have been well
documented [1]-[3]. In view of the cost and timesavings as compared to the conventional method,
constructing a shallow depth ground improvement
layer not far below ground level has been attempted
to facilitate an open excavation in Singapore in
recent years.
For shallow open excavation, column-shaped
cement-treated soil in different layouts is analternative design to retaining wall. In current design
practice, engineers often regard the improved layer
as a composite material gravity wall. As such, twostability analyses involving external and internal
wall stability are evaluated. For external stability
analysis, three failure modes of the treated soil mass(assuming no failure occurred within the treated soil
and untreated soil): sliding, overturning, and bearing
59

GEOMATE-Nagoya, Nov.13-15, 2013

CONSTITUTIVE MODEL FOR
TREATED SOIL

appropriate constitutive model is adopted to simulate
the material behavior. Therefore, the constitutive
model prediction is first examined in the present
study using available laboratory test results.
Laboratory data by [7] and [8] for cement-treatedsand in triaxial compression test and direct tensile
test respectively are adopted in the present study.
Three constitutive models, i.e. elastic-perfectly
plastic Tresca, isotropic hardening/softening andconcrete damage plasticity model are adopted tocalibrate the laboratory test data. These threeconstitutive models are the built-in material model
available in Abaqus/Standard.

CEMENT-

Behavior of Cement-treated Soil
Cement-treated soil is a product of mixing
cement to in-situ soil aiming to increase the strengthand stiffness by bonding the particles together. The
increase in strength of the mixture is mainly
attributed to three reactions happened during themixing, namely: hydration, ion exchange(flocculation), and pozzolanic reaction. Many
researchers had studied the behavior of cementtreated soil experimentally. It is established that
addition of cement has transformed the in-situ soil
from ductile into brittle behavior [5-6]. As shown in
Fig. 1 and Fig. 2, the brittle behavior is manifested
both in tension and compression. Generally, thetreated soil stress increases abruptly associated witha low strain followed by sudden reduction of post
peak stress to a very low value.

Model and Parameters
An elastic-perfectly plastic Tresca model can beused to define a material which upon reachingcertain stress state, undergoes irreversible
deformation. This model is commonly used inpractice due to its simplicity with few parameters
needed. The required design parameters are E and ν
defining the elastic regime; and Cu used to define
the yield surface. In addition, a tension truncated
Tresca yield criterion is considered in present study
by adopting a tension cut-off parameter.
For isotropic hardening/softening model, theyield surface changes size (increase/decrease)uniformly in all directions as plastic straining occurs.
In Abaqus, the yield stress σI can be defined as atabular function of equivalent plastic strain, εpl(i).
The elastic regime is similarly defined in Tresca
model.
Concrete damage plasticity (CDP) model has
been widely used to simulate the crack development
and strength degradation due to damage for quasibrittle material such as concrete. Therefore, it isstrongly believed that this model can workreasonably well for cement-treated soil which is also
known as a quasi-brittle material. CDP model
assumes that the two main failure mechanisms as
tensile cracking and compressive crushing. The
design parameters needed for CDP model can beextracted from the experimental σ - ε curve for both
uniaxial compression and tension tests as shown in
Fig. 3 and Fig. 4, respectively. Details regarding thismodel are available in Abaqus manual.

C: cement content

Fig. 1 UCT stress-strain curve for cemented
marine clay with various cement content [5]Fig. 2 Direct tensile test stress-strain curve forcemented sand [6]Constitutive Model
Finite element analysis can simulate the cementtreated soil behavior accurately only if anFig. 360

Dependence σ - ε in compression for CDPGEOMATE-Nagoya, Nov.13-15, 2013

verticality. The cell pressure of 49 kPa wasrepresented by distributed load acting around all theplanes except the bottom plane. The testing processusing vertical displacement control was simulated byapplying prescribed displacement from top. The
element type used in this model was an 8-node linear
brick (C3D8R).
For direct tensile test, the test was simplified
with one quarter model where the symmetriccondition was modeled by constraining thetangential degree of freedom on the bottom plane
and left plane from moving. The test using verticaldisplacement control was simulated by applying
prescribed displacement from top. 4-node bilinear
axisymmetric quadrilateral (CAX4R) element was
adopted in this case.

Dependence σ - ε in tension for CDP

Fig. 4

Laboratory Data
The stress-strain relationships for a drained
triaxial compression test and direct tensile test forcement-treated Toyoura sand are calibrated in thepresent study. The specimen test results are shown in
Fig. 5 and Fig. 6, while the test details are available
in [7-8].

Deviator stress (kPa)

2000

1500

z
y

Fig. 7 Finite element model: drained triaxial
compression test (left) and direct tension test (right)

1000
x

x
y

500

εx (%)

0-0.3

The parameters used to simulate elastic regime
were similar for three aforementioned constitutive
models with Young’s modulus E = 2400 MPa andPoisson’s ratio ν = 0.167. The parameters used todescribe the yield criterion of the three models are
summarized in Tables 1-3.

εz (%)
-0.1

0.1

0.3

0.5

Fig. 5 Stress-strain curves for drained triaxial
compression test (initial confining stress=49kPa) [7]

Table 1 Model parameters for Tresca model-0.4

Cohesion
900kPaTensile stress (MPa)-0.3

Table 2 Model parameters for Isotropic model-0.2

Yield Stress
1200kPa
1800kPa
1800kPa
1500kPa

-0.1
0
0.000

Fig. 6

Tension Cutoff
380kPa-0.005-0.010-0.015strain εz (%)-0.020Stress-strain curve for direct tensile test [8]Plastic Strain
00.00150.00320.0053

Table 3 Model parameters for CDP model

Finite Element Model
The drained triaxial compression test was
simulated using a 3-D single element as displayed inFig. 7. The boundary condition was modeled byconstraining the bottom plane from moving

Compression
Yield
1100kPa
1650kPa

61

Inelastic
Strain00.0015TensileYield
380kPaFracture
Energy9N/m

GEOMATE-Nagoya, Nov.13-15, 2013

1650kPa
1400kPa

crack using brittle fracture concept. This model thenassumes a linear loss of strength after cracking.
Despite of G f , this fracture energy cracking model
can be invoked by specifying the post-failure stressas a tabular function of cracking displacement.
These built-in functions make the CDP model
capable of better simulating the behavior of cementtreated soil, as illustrated in Fig. 9.

0.0032
00053

Result and Discussion
The calibration results are shown in Figs. 8-9. In
compression test, the elastic-perfectly plastic Tresca
model is not able to simulate the material stressstrain behavior after the specimen experiences
0.05% axial strain. Owing to a single stiffness andperfectly plastic criteria assumed in this model, thehardening as well as the softening behavior after the
specimen undergoes 0.05% axial strain cannot be
simulated by this model. On the other hand,isotropic hardening/softening and CDP are capablein capturing the material nonlinear behavior and thecalibrated results yield closely with experimental
results.

-0.5

Tensile stress (MPa)

-0.4

-0.2

Experiment
TrescaIso-Har/Soft

-0.1

CDP

0
0.000

2000

-0.005-0.010-0.015strain εy (%)-0.020-0.025

Fig. 9 Calibration results for direct tensile test
modeled by 3 types of constitutive model

1500
Deviator stress (kPa)

-0.3

1000
Experiment
TrescaIso-Har/Soft
CDP

500

εx (%)

0
-0.3

-0.1

FE ANALYSIS OF A FULL SCALE TEST
A full scale test of cantilever cement-treated soilcolumn under lateral load (Fig. 10) was simulated
here to validate the use of CDP model in simulating
an actual field problem. Details of the in-situ fullscale test can be referred to [10]. The design
parameters for untreated soil, concrete and steel
plate are similar to those given in [11] while theparameters for treated columns using CDP model aresummarized in Table 4.

εz (%)
0.1

0.3

0.5

Fig. 8 Calibration results for compression test
modeled by 3 types of constitutive model
Nevertheless, a representative model shall beable to capture both the compressive and tensile
behavior of the cement-treated soil. As shown in Fig.
9, the post peak stress modeled by Tresca model
remains at the input tension cut-off strength 380kPa.
However, in reality the material experiences post
peak tensile softening as illustrated in the test result.
Although the isotropic hardening/softening model
could simulate the compression test well, theisotropic yield criterion which allows for thedevelopment of any value of tensile stress has
overestimated the actual material strength. This isevident in the calibration result shown in Fig. 9
where the predicted tensile stress-strain curvealways exceeds the experimental peak tensile
strength. Without the tension cut-off function as
built
inTrescamodel,
theisotropic
hardening/softening model is not able to evaluate thetensile behavior of cemented soil. Nonetheless, theabove mentioned shortcoming of the two models canbe overcome by CDP model. In CDP model, thetensile softening behavior of the material can be
simulated by the parameters of tensile stress andfracture energy G f . Fracture energy G f proposed by[9] is defined as the energy required to open a unit ofFig. 10 Full scale test by [10-11]
A 3-D finite element analysis was conductedusing 4-node linear tetrahedron (C3D4) element.
The element length varied from 0.05m to 0.015m.
Fig. 11 shows the finite element model and its
62GEOMATE-Nagoya, Nov.13-15, 2013

boundary conditions for this field test. Generally, theembedded surrounded soil was not permitted frommoving tangentially. Although cyclic loading wasapplied in the field test, a monotonic loading
condition was assumed in the present analysis. The
test was modeled by applying prescribed
displacement at the center point of the steel plate.

column was conducted. However, the analysis was
not stable due to the convergence problem once thetensile stress reached peak. As a result, classicalTresca model was adopted and the analysis resultscompared with CDP model are displayed in Fig. 14.
80

Table 4 Parameters for CDP model in full scale test
Inelastic
Strain0

TensileYield
440kPaDensity
1700kg/m3

E
8800MPa

ν
0.167

60
Lateral Load (kN)Compression
Yield
4400kPa

FEM-CDP
Test-1st cyc
Test-2nd cyc
Test-3rd cyc

Fracture
Energy
9N/m

40

20

0
0

0.5

1
1.5
Lateral Displacement (mm)2

Fig. 12 Lateral load-displacement relations for fieldtest and FEM(a) FE Result(b) Field Result
300mm

Front View

Side View

Fig. 11 FE model used to analyze the full scale test
Result and Discussion
The analysis result for lateral load-displacement
relation is presented in Fig. 12 for the CDP model,
which shows that there is good agreement between
the analysis and the field measurement. Furthermore,
the crack development in the cantilever treatedcolumn can be reasonably well modeled as displayedin Fig. 13a. In CDP model, the tensile damage isrepresented by the tensile damage variable, d t whichtakes values from zero, representing the undamaged
material, to one, which represents a total loss ofstrength. The first damage crack occurs
approximately at 300 mm above the ground level infinite element analysis coinciding with the fieldobservation (Fig. 13b). Hence, the use of CDP
model in simulating cement-treated soil problem inthe field is promising.
Beyond this, an attempt of using tension
truncated Tresca model to simulate the cemented

Fig. 13 Crack formation in cemented column

160

CDP
TrescaLateral Load (kN)

120
80
40
0
0

1

2
3
Lateral Displacement (mm)Fig. 14 Lateral load-displacement relations for
CDP model and Tresca model
63

4

GEOMATE-Nagoya, Nov.13-15, 2013

Prior to damage, both materials yield similarload-displacement relationships within the elastic
state. Once damage has occurred, the increment oflateral load resistance is significantly reduced.
Classical Tresca model shown in Fig. 13 grossly
overestimates this load. This is believed to be
attributed to the shear failure mechanism assumed,
thus any tensile or bending failure is not captured by
the classical elastic-perfectly plastic Tresca model.
Although Tresca model is commonly used inpractice to simulate cement-treated soil, it is not anappropriate model for this kind of problem involving
lateral stresses as demonstrated in the present study.

[2] Sugawara S, Shigenawa S, Gotoh H, and Hosoi
T, “Large-scale jet grouting for pre-strutting insoft clay”, Grouting and Deep Mixing,
Rotterdam: Balkema, 1996, pp. 353-356.
[3] Lim PC and Tan TS, “A floating type braced
excavation in soft marine clay”, UndergroundSpace Singapore, 2003, pp. 326-337.
[4] Kitazume M, “Stability of group ground column
type DM improved ground under embankmentloading behavior of sheet pile quay wall”
Report of the Port and Airport ResearchInstitute, Nagase, Yokosuka, Japan, Port andAirport Research Institute, Vol. 47, 2008.
[5] Kamruzzaman AHM., “Physico-chemical andengineering behavior of cement treated
Singapore marine clay”, Ph.D, NUS, 2002.
[6] Das BM and Dass RN, “Lightly cemented sandin tension and compression”, Geotech. andGeol. Eng., Vol. 13, 1995, pp. 167-177.
[7] Namikawa T, “Study on tensile and shear
failure characteristics of cement-treated sand’,
Ph.D, Uni. Of Tokyo, 2006.
[8] Koseki J, Sato T and Nishimoto T, “Anisotropy
in strength characteristics of cement-treatedsand prepared by compaction”, Proc. Symp.
Cement-Treated Soils, JGS, 2005, pp. 365-368.
[9] Hillerborg A, Modeer M and Petersson PE.,
“Analysis of crack formation and crack growthin concrete by means of fracture mechanics andfinite elements”, Cement and Concrete
Research, Vol. 6, 1976, pp. 773-782.
[10] Babasaki R, Suzuki Y, Nakama T and Yamada
K, “Study for reinforced earth retaining wall by
deep mixing method (Part 2)”, Proc. 32th
Annual Conf. of JGS, 1997, pp. 1733-1734.
[11] Namikawa T, Koseki J and Suzuki Y, “Finite
element analysis of a full scale bending test of
cement treated soil column”, IACMAG, India,
Oct 2008, pp. 3635-3641.

CONCLUSION
Three constitutive models, namely Tresca,
isotropic hardening/softening and concrete damage
plasticity (CDP) were used to simulate the behaviorof cement-treated sand. Analysis result shows that
CDP model is able to simulate both compressive andtensile behavior of cemented soil. The lack oftension-softening feature in the other two models
tends to grossly overestimate the tensile strength.
Back-analysis of a field problem also shows that
CDP model performs well in modeling the tensile
crack development for a cantilever cement-treatedsoil column under lateral load. In conclusion, CDP isa more appropriate model so simulate cementtreated soil behavior compared to elastic-perfectly
plastic Tresca and isotropic hardening/softening
model.

REFERENCES[1] Gaba AR, “Jet grouting at newton station,
Singapore”, 10th Southeast Asian GeotechnicalConf., Taipei, 1990, pp. 77-79.

64Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

UPDATING THE PREDICTIVE MODEL FOR THE VERTICALCOLLAPSE PERCENTAGE OF COLLAPSIBLE SOIL SUBGRADES
Moshe Livneh1 and Noam A. Livneh2
Civil and Environmental Engineering Faculty, Technion-Israel Institute of Technology, Haifa, Israel
2
Noam Livneh Engineering Ltd., Haifa, Israel

1

ABSTRACT
Since the publication of the Israeli model for the vertical collapse percentage of collapsible soil subgrades in
2012, new collapse test results have become available (all together, for 123 undisturbed and remolded silt or silty
clay specimens), enabling an updating of the existing collapse model. In addition, old available collapse test datathat do not contain all the necessary parameters of the materials tested (all together, for 189 undisturbed silt or silty
clay specimens) have also become available for use. Thus, updating is logical so as to obtain a more accurate
prediction of vertical collapse under a given vertical pressure exerted on the silt or silty clay under consideration.
This paper concentrates on the required updating, together with (a) a search for the true impact of the verticalinduced pressure on the predicted vertical collapse values and (b) an elaboration of the practical use of the updated
model in collapse settlement calculations for a given local project, together with its limited local collapse testresults, all in order to enhance the accuracy of collapse settlement calculations. The final recommendation is to use
the new updated vertical collapse model together with the limited local collapse tests results of a given project. Thisis done in a combined way that adjusts the new updated model to fit the specific collapse characteristics of thegiven project.
Keywords: Collapse, Embankment, Settlement, Silty characteristics
instructions of the single-odometer test, known also as
the ASTM D 5333 collapse test. In this test, an
undisturbed or remolded specimen is first driven into
the odometer ring and then subjected to increasing
vertical loads. The specimen is permitted to attainequilibrium deformation at each level of pressure. It isthen inundated at a prescribed applied pressure, andthe deformation is measured. The deformationinduced by the addition of water, divided by the initialheight of the specimen, expressed in percentage
terms, defines the collapse potential, which this paper
also terms vertical collapse.
Since the publication of the aforementioned Israeli
collapse model in 2012 [1], new collapse test results
have become available (all together, from 123
undisturbed silt or silty clay specimens), enabling an
updating of the existing collapse model. In addition,
old available collapse test data that do not contain all
the necessary parameters of the materials tested (alltogether, from 119 undisturbed silt or silty clay
specimens) have also become available for use. Thus,
it seems to be only logical to update the existingmodel in order to obtain a more accurate prediction ofvertical collapse under a given vertical pressure
exerted on the silt or silty clay under consideration.
To sum up, this paper concentrates on the required
updating, together with (a) a search for the true
impact of the vertical induced pressure on thepredicted vertical collapse values; (b) an elaborationof the practical use of the upgraded model in collapse

INTRODUCTION
Pavement and railway bed design involves a stability
analysis of their earthwork material. In this respect,predicting the vertical collapse of embankments basedon silts or silty clays is a necessary step. To recall,silts or silty clays in semi-arid zones areconventionally considered problematic, since they
exhibit a high potential for collapse under loading. All
soils settle upon loading, but the amount of settlement
varies from soil to soil and is dependent on loadinduced stresses. Although such settlement will
eventually cease after a certain period of time,
subsequent wetting under certain conditions may
cause additional settlement, known as collapse.
The required prediction of the vertical collapse of
these embankments is aided by a collapse model thatreflects the relationship between the predicted verticalcollapse and the vertical surcharge acting on the silt or
the silty clay at a given depth. The development of
this model is shown by the authors in [1]. Tosummarize, this collapse model was obtained fromlaboratory tests on 73 undisturbed silt or silty clay
specimens. The curves of this model are dependent on
knowledge of the following parameters thatcharacterize the silt or silty clay being studied: (a)liquid limit, (b) the ratio between in-situ moisture
content and plasticity limit, and (c) in-situ dry density.
The suggested collapse model is based on 73 local
collapse tests that were conducted according to the65GEOMATE-Nagoya, Nov.13-15, 2013settlement calculations for a given local project,
together with its limited local collapse test results, allin order to enhance the accuracy of collapse
settlement calculations.

specimens of Fig. 1. The average value of the W/PL
measured values for these specimens is 0.565.
25

20

Measured vertical pressure [%]EXISTING VERTICAL COLLAPSE MODEL
As mentioned, predicting the settlement of anembankment-base surface as a result of subgradecollapse necessitates knowledge of the collapsepressure characteristics of the silt or the silty clay
strata under consideration, and these are usuallyobtained from laboratory tests on undisturbed anddisturbed silt or the silty clay specimens. Thisprediction model denotes a statistical relationshipbetween the vertical collapse (Cp), in percentages,that is due to applied vertical pressure (Pp), in kPa,
and the following parameters characterizing the silt or
the silty clay specimens under examination: moisture
content (W) in percentages, in-situ dry density (D) in
kN/m3, and dry density at liquid limit (D LL ) in kN/m3
as defined by Eq. (2). For 73 local specimens
extracted from a silt or a silty clay subgrade situatedin the southern part of the country, more specificallyfrom the construction site of Goral Junction-Netivot
railway line, the best formulation of this model,
reproduced from [1], is as follows:
Cp=28.5354-27.0305×(D/D LL )0.9825+(1)+0.0001196×[log(Pp)]11.3741/(W/PL)1.4908(2)
D LL =9.807×100/(100/G+LL)
In Eq. (2), G denotes the solid specific gravity ofthe silt or the silty clay specimen, and LL denotes its
liquid limit in percentages. Here it should be notedthat Eq. (1) was derived with the aid of the Excel
Solver command.
As shown in Fig. 1, the R2 (coefficient ofdetermination) value obtained for the vertical collapse
model presented in Eq. (1) is 0.535. In addition, theaccompanying SE (standard error) value obtained is
4.206%, and the SE/SY (ratio of standard error tostandard deviation of the measured vertical collapse
values) is 0.707. In other words, 68 percent of all
predictions using Eq. (1) may be expected to beaccurate within ±4.206%, and 95 percent to beaccurate within ±8.412%.
Here, it should be mentioned that Eq. (1) was
formulated to yield the highest R2 value from among
all possibilities that (a) include the independent
variables of the soil's plasticity and (b) yield true
physical behavior as clearly described in [3] (i.e., anincrease in Cp with increasing Pp, and a decrease in
Cp with increasing W, D, and LL). The density-ratio(D/D LL ) variable of Eq. (1) follows this finding exactly
as given in [4] or indirectly as given by a similarfinding in [5].
In addition, Fig. 2 depicts Eq. (1) graphically forthe silt or the silty clay material. For comparison
purposes, this figure also includes the collapse results
obtained from the laboratory testing of the 73

y = 1.0092x - 0.0445
R² = 0.5350
15

10

5

0
-10

-5

0

5

10

15

20

-5
Undisturbed specimens
Remolded specimens-10

Predicted vertical collapse [%]Fig. 1: Measured vertical collapse versus verticalcollapse predicted from Eq. (1) for the 73 local
specimens of [1]30W/PL=0.25

25

Vertical collapse [%]Undisturbed Pp=200 kPa
Undisturbed Pp=100 kPa
Remolded Pp=200 kPa
Combined Pp=200 kPa
Combined Pp=100 kPa

20

0.50
0.25 0.75
0.50

15

0.75
10

5

0
0.0

0.3

0.6

0.9

1.2

1.5

1.8

2.1

Ratio of in-situ dry density to dry density at liquid limit

Fig. 2: Vertical collapse versus density ratio (D/D LL )for vertical pressures of 100 kPa and 200 kPa as
derived from Eq. (1) for the 73 local specimens of [1]Finally it is worthwhile mentioning that (a) Eq.
(1) and Eq. (2) have recently served as the verticalcollapse model in the settlement calculations carriedout in [2]; and (b) in the following sections, silt also
refers to silty-clay.
USE OF ADDITIONAL TEST DATA
Recently, an additional 50 new collapse test results
have become available from another construction site
in the southern part of the country, more specificallyfrom the southern part of Highway No. 6 (Section No.
21) near the city of Beersheba. Combining these new
results with the 73 old ones yields the following
modified vertical collapse model:
Cp=1.7341×105-1.7341×105×(D/D LL )0.00008+(3)+0.6840×[log(Pp)]0.9941/(W/PL)1.4739
As shown in Fig. 3, the R2 (coefficient ofdetermination) value obtained for the vertical collapse
model of Eq. (3) is 0.312, or lower than that of Eq.
(1). In addition, the accompanying SE (standard error)
value obtained is 4.591%, and the SE/SY (ratio ofstandard error to standard deviation of the measured
vertical collapse values) is 0.847. In other words, 68
66

GEOMATE-Nagoya, Nov.13-15, 2013

percent of all predictions from Eq. (1) may be
expected to be accurate within ±4.591%, and 95
percent to be accurate within ±9.182%.

INDUCED VERTICAL PRESSURE IMPACT
In order to determine the impact of the induced verticalpressure on the calculated vertical collapse results,
additional old collapse test-results data, reported in [5]and [7], the latter for three airbase locations again in
the southern part of Israel, were analyzed as describedin following paragraphs. As these data do not containall the necessary parameters for characterizing thetested soil, it was not possible to include them in theprevious calculations of Eq. (1) or Eq. (3).
The test-results data from these three sites, whengathered in a united pool, yield the following
regression equation:
Cp=2.3953-12.9186×(D/D LL )+ 7.7727×log(Pp) (4)The use of the linear regression model of Eq. (4)instead of that of Eq. (1) was necessary in order toovercome the absence of the measured W values inthe data tested. The following values hold for Eq. (4):(a) Pp is given in kPa, (b) the R2 value equals 0.491,
and (c) the SE value equals 2.460%.

25
Undisturbed specimens
Remolded specimens

Measured vertical pressure [%]20
y = 1.0049x + 0.0478
R² = 0.3124
15

10

5

0
0

2

4

6

8

10

12

14

16

18

Predicted vertical collapse [%]Fig. 3: Measured vertical collapse versus predictedvertical collapse from Eq. (3) for the old 73 and new
50 local specimens
Fig. 4 depicts Eq. (3) graphically for the siltmaterial. For comparison purposes, this figure also
includes the collapse results obtained from thelaboratory tests of the 123 specimens of Fig. 3. For
these specimens, the average value of the W/PL
measured values is 0.560; i.e., almost identical to theprevious value of the73 specimens, which was 0.565.

15

Vertical collapse [%]1030
Undisturbed Pp=200 kPa
Undisturbed Pp=100 kPa
Remolded Pp=200 kPa
Combined Pp=200 kPa
Combned Pp=100 kPa

25
W/PL=0.25
Vertical collapse [%]Pp=25 kPa [5]Pp=50 kPa [5]Pp=100 kPa [5]Pp=25 kPa [7]Pp=50 kPa [7]Pp=100 kPa [7]Pp=200 kPa

5

Pp=100 kPa
Pp=50 kPa

020
Pp=25 kPa

0.50

15

-5
0.7

10

5
0.50
0.75
0
0.3

0.9

1.0

1.1

1.2

1.3

1.4

Fig. 5: Vertical collapse versus density ratio for verticalpressures of 25, 50, 100 and 200 kPa as derived from
Eq. (4) for the old 189 local specimens of [5] and [7]
Eq. (4) indicates that the dependence of Cp
values on the induced vertical pressure ischaracterized by the 7.7727×log(Pp) expression.
Thus, it is interesting to compare the contents of thisexpression to other sources. To this end, theregression equation of [6] is given below:
Cp=48.496+0.102×Cu-0.457×W-3.533×D++6.447×log(Pp)(5)
3
For Eq. (5), Pp is given in kPa, D in kN/m , and
W and Cu in percentages. The R2 value of thisequation obtained for its experimental data (138remolded specimens) was rather high, 0.94.
Furthermore, the associated SE value obtained for its
experimental data was rather a low value, 1.94%
It is to be noted that Eq. (5) contains an additional
independent variable, Cu, which denotes thecoefficient of uniformity of the prescribed silt. For thecase of the 73 specimens of Fig. 2, the average Cu
value equals 80%. This equation also indicates thatthe dependence of Cp values on the induced verticalpressure is characterized by the 6.447×log(Pp)

0.25

0.0

0.8

Ratio of in-situ dry density to dry density at liquid limit

0.75

0.6
0.9
1.2
1.5
Ratio of in-situ dry density to dry density at liquid limit

1.8

2.1

Fig. 4: Vertical collapse versus density ratio for
vertical pressures of 100 and 200 kPa as derived from
Eq. (3) for the old 73 and new 50 local specimens
Moreover, Fig. 4 indicates that the modified
vertical collapse model is practically not sensitive tovariations in the induced vertical pressure. The
increase in Cp values when Pp varies between 100
kPa and 200 kPa is almost zero for W/PL=0.75, andabout 1.5% for W/PL=0.25. This behavior should be
regarded as totally unacceptable when compared withthat characterized by the curves of Fig. 2 or with thatdefined by other sources, such as [6].
The main conclusion drawn from the findings ofthe present section is that the use of Eq. (3) is not
acceptable for prediction purposes and that the 123
test-results data should be analyzed in a way thatmaintains the impact of the Pp input on the Cp
calculated results.

67

GEOMATE-Nagoya, Nov.13-15, 2013

Finally, the Pp impact on the calculated Cp values
as defined by Eq. (10)--i.e., its increased capacity forlower W/PL values when D/D LL is kept constant-seems to be compatible with the physical behavior of
the collapse process. In other words, for lower W/PL
values when D/D LL is kept constant, the initial degreeof saturation is lower, thus the collapse potential ishigher.

expression, which is very similar to that of Eq. (4). As
for the comparison with the regression equation of thedata of the 73 specimens (Fig. 2) and also that of the
123 specimens (Fig. 4), the following linear
regression study should first be conducted.
The regression equations for the old 73 specimensthat serve as other regression options for Eq. (1) are
shown in the two expressions that follow, for which
R2=0.493 and SE=4.327% in the first expression, and
R2=0.452 and SE=4.467% in the second expression:
Cp=14.5465 -6.7860×W/PL-29.9013×D/D LL ++10.9013×log(Pp)(6)(7)
Cp=5.0010-32.9836×D/D LL -14.7602×log(Pp)In a similar manner, the regression equations forthe old 73 specimens and the new 50 specimens thatserve as other regression options for Eq. (3) are
shown in the next two expressions, for which
R2=0.351 and SE=4.421% in the first expression, and
R2=0.235 and SE=4.781% in the second expression:
Cp=40.6598 -11.1960×W/PL-16.2179×D/D LL ++4.9255×log(Pp)(8)(9)
Cp=38.8035-19.9464×D/D LL -5.1744×log(Pp)Now, the dependence of Cp values on the induced
vertical pressure as characterized by Eq. (6) and Eq.
(7) is more pronounced than that characterized by Eq.
(4). As for the comparison of the dependence of Cp
values from Eq. (8) and Eq. (9) with that from Eq. (4),the latter is much less pronounced. Thus, it seems thatthe vertical collapse model of Eq. (1) in regard to the
induced vertical pressure impact is more appropriate
than that of Eq. (3).

25
Undisturbed Pp=200 kPa
Undisturbed Pp=100 kPa
Remolded Pp=200 kPa
Combined Pp=200 kPa
Combined Pp=100 kPa

W/PL=0.25

Vertical collapse [%]

20

0.75
0.25
0.50

15
0.50

10

0.75

5

0
0.0

0.3

0.6
0.9
1.2
1.5
Ratio of in-situ dry density to dry density at liquid limit

1.8

2.1

Fig. 6: Vertical collapse versus density ratio for
vertical pressures of 100 kPa and 200 kPa as derived
from Eq. (10) for the old and new 123 local specimens
5

W/PL=0.25
4

0.50

Ratio of vertical collapse

0.75

UPGRADED VERTICAL COLLAPSE MODEL

3

0.75
2

0.50 0.25

1

The main conclusion from the previous section is thenecessity of keeping the Pp impact on Cp values, as
defined by Eq. (1), in the present updated regression
analysis for the total available 123 specimens. The
equation obtained in this analysis, which presents the
final upgraded vertical collapse model, is (see Fig. 6):
Cp=1.73415×105-1.73410×105×(D/D LL )0.0001+(10)+0.0001196×[log(Pp)]11.3741/(W/PL)1.0532
Eq. (10) is limited for the following range ofvalues: 0.25-1.10 for W/P values and 0.75-1.35 for
D/D LL values. In addition, although the accuracy ofthis equation is very low (R2=0.195 and SE=4.947%),
it is still considered to be preferable to Eq. (1), forwhich R2=0.535 and SE=4.206%. In any case, theratio of the calculated vertical collapse, Eq. (10), in
contrast to Eq. (1), versus the density ratio (D/D LL ) is
close to the value of 1.0 for high (critical) Cp values(see Fig. 7). It can be seen, furthermore, that thecomputed Cp values of Fig. 5 are almost identicalwith those of the W/PL=0.5 curves of Fig. 6. Indeed,
the 0.5 value for W/PL is actually the average of theexperimental data of Fig. 5. This fact may serve as
another justification for the preference of Eq. (10).

Equality Line
Combined Pp=200 kPa
Combined Pp=100 kPa

0
0.0

0.3

0.6
0.9
1.2
1.5
Ratio of in-situ dry density to dry density at liquid limit

1.8

2.1

Fig. 7: Ratio of calculated vertical collapse, Eq. (10),as opposed to Eq. (1), versus density ratio
SPECIFIC VERTICAL COLLAPSE MODEL
The specific equation for predicting the verticalcollapse percentage that characterizes the specific data
values prevailing at a given project (say, the specificvalues of liquid limit, ratio of moisture content toplastic limit, and dry density of the subgrade site) isdetermined by combining Eq. (2) and Eq. (10) withthe specific, limited results of the laboratory collapse
tests, which are conducted as part of the in-situ
investigations for a given project. Following theprocedure given in [8] for the vertical swell model,
the local values and the two given equations are
combined by determining the regression coefficients
α and β of the linear regression carried out between
the dependent variable Cp and the independent
variable, the latter as specified in Eq. (11). In otherwords, the formulation of this linear regression
equation is as follows:
68

GEOMATE-Nagoya, Nov.13-15, 2013

Cp=α+β×[1.73415×105-1.73410×105×(D/D LL )0.0001+(11)+0.0001196×log(Pp)]11.3741/(W/PL) 1.0532)]
where α and β are the linear regression coefficients.
In greater detail, the α-coefficient of Eq. (11) is
the intercept value with the measured Cp-axis (Yaxis) and the β coefficient is the slope value with theEq. (10) Cp axis (X-axis). Here it should be noted thatwhen α=0 and β=1, Eq. (11) is the same as Eq. (10),which, as mentioned, constitutes the accepted generalvertical collapse model for settlement calculations. In
addition to the regression of Eq. (11) (known also as
the simple linear regular regression), a supplementary
regression is suggested, in which the prerequisite
constraint of α=0 exists. For this type of regression(known also as the zero-intercept regression, or
regression through the origin), the β-coefficient serves
as the multiplier for the increase or decrease in thegeneral vertical collapse percentage. In this regression,
furthermore, the predicted vertical collapse value isequal to 0% for the same input data of the tested
material that causes the predicted vertical collapse
value to be equal to 0% when the general model--i.e.,
Eq. (10)--is followed. Similarly, in the simple linear
regular regression, the predicted vertical collapse
value is equal to α % for the same input data of thetested material that, again, causes the predictedvertical collapse value to be equal to 0% when thegeneral model--i.e., Eq. (10)--is followed.
This calculation method to find the equation of thespecific vertical collapse model that defines thevertical collapse percentage value as a function of thevertical induced pressure is based on the following
assumption: the internal interrelationship of W/PL,
D/D LL , and Pp is a predetermined system,
characterized by the outputs of Eq. (10). Hence, Eq.
(11) contains only one independent variable. The
sample size needed for making this kind of regression
is much smaller than that needed for making the full
regression, which contains six regression parameters.
It should be emphasized that for a given project, theuse of limited specific collapse tests for conducting an
Excel-solver analysis using six regression parametersfrom Eq. (2) and Eq. (10) can cause a substantial
distortion of the true collapse picture. Therefore, themethod based on Eq. (11) is to be preferred.
As a result of the foregoing argumentation and inorder to implement the preferred method, it isimportant that limited collapse tests be carried out
under several values of vertical pressure, such as 100
and 200 kPa. These vertical pressures will cover the
potential vertical pressures that act along the depth of
the wetted zone of the silt. For these tests, furthermore,undisturbed subgrade specimens are to be extracted
from at least three borings each at two depths,
depending on the size of the given site and thestatistical distribution of its subgrade properties. It is
important to emphasize that when the number of
specimens is below the minimum required value(about twelve), the derivation of the specific collapse

model is questionable. In this context, it is worth
noting that the average of these twelve specimen
results according to the ASTM E122-09 standard
represents the average of the results of the entire
population, with an accuracy of about 0.55 of the true
standard deviation and at a 95% reliability level.
An example illustrating the derivation procedureof the aforementioned α and β coefficients for 12
undisturbed specimens extracted from the silt
subgrade of a railway line construction site in thesouthern part of Israel is shown in Fig. 8. These 12
undisturbed specimens were tested for their verticalcollapse percentage under an induced verticalpressure of 100 and 200 kPa. The undisturbed
specimens were also tested to obtain their LL, PL, W,
and D values.
Fig. 8 indicates that the regular regression yields
an α-coefficient of 3.609 and a β-coefficient of 0.847.
As for the constrained regression (i.e., the zerointercept regression), the value yielded for the latter is
1.097. These coefficients characterize the local
vertical collapse model according to Eq. (11).
Finally, the question arises as to the specificregression that is to be preferred, the simple linear
regression or the zero-intercept regression; The
answer lies in the comparison of the two rates of thecollapse settlements calculated for a given
embankment, using these two models and theprocedure outlined in [2]. The higher of the two
calculated rates is considered to be the determinantvalue. However, when the number of local tests is lessthan the minimum required--i.e., 12--or when thecoefficient of determination (R2) obtained from theabove two regressions is very low, the calculated rateaccording to α=0 and β=1.0 is considered to be thedeterminant value.
35
Equality-Line

Measured vertical collapse [%]30

y=1.097xR²=0.627

25

20

15
y=0.847x+3.609
R²=0.707
10

5

0
0

5

10

15

20

25

30

35

Calculated vertical collapse according to Eq. (2) and Eq. (10) [%]Fig. 8: Derivation of the α and β coefficients for 12
undisturbed specimens extracted from the silt
subgrade of a railway line construction site
SUMMARY AND CONCLUSIONSThis paper dealt with the issue of (a) updating thegeneral vertical collapse model given previously by
the authors in [1] and [2] and (b) deriving the specificvertical collapse model for a given site by combining
69

GEOMATE-Nagoya, Nov.13-15, 2013

limited vertical collapse test results obtained for thissite with the general vertical collapse model.
The routine updating procedure using the old 73
collapse test results together with the new 50 collapse
test results yields an unacceptable model with respect
to the impact of the vertical induced pressure on thevertical collapse results.
Thus, an additional study was needed to confirm
the impact of the vertical induced pressure calculated
from the existing model presented in [1] or [2] on thevertical collapse results. This study was performed
using old available collapse test data (all together, 119
undisturbed silt specimens) that do not contain all thenecessary parameters of the materials tested. This
showed that the impact of the vertical inducedpressure on the vertical collapse results is actuallysimilar to that of the existing model found in [1] or [2].
Given the above findings, it was understandable
that a new regression analysis had to be run on the
123 collapse test results of the undisturbed anddisturbed specimens of Fig. 3. The new regression
equation (Eq. 10) in this analysis maintained theimpact of the vertical induced pressure on the verticalcollapse results as defined by the existing model--i.e.,
Eq. (1) and Eq. (2).
The appropriate vertical collapse model should be
employed for vertical collapse settlement calculations.
As developed in the paper, three models exist: (a) thegeneral vertical collapse model derived from the
Excel-solver analysis carried out on 123 undisturbed
and disturbed specimens, using the impact of thevertical induced pressure on the calculated verticalcollapse results as defined by Eq. (2) and Eq. (10); (b)the specific vertical collapse model derived from thesimple linear regression analysis carried out on thedata of the specific local tests, combined with thegeneral updated vertical collapse model--i.e., Eq. (2)and Eq. (10); (c) the specific swelling model derived
from the zero-intercept linear regression analysis
carried out, again, on the data of the specific local
tests, combined with the general updated verticalcollapse model--Eq. (2) and Eq. (10)--in which,however, the α-coefficient always equals 0.
For the latter two vertical collapse models, it isrecommended that the one that yields the higher
calculated settlement rate should be adhered to as the
final result. It should be emphasized, furthermore, thatin order to use the specific vertical collapse model
described above, collapse tests must be performed ona sufficient number (at least 12) of undisturbed
specimens, as this will better reflect the site's silt
variability along both the horizontal axis and thevertical axis. When the coefficient of determination(R2) obtained for the above two models is, however,very low, the calculated rate according to α=0 and
β=1.0 is considered to be the determinant value. In theabsence of local tests, moreover, only the general
updated vertical collapse model need be adopted;
namely, Eq. (2) and Eq. (10). In any case, the use of

the specific collapse tests for applying the Excelsolver analysis directly to a given project isinappropriate, as it may lead to erroneous results.
The final conclusion is that all the above findings
can serve as a proper tool for calculating the verticalcollapse settlement of the base of an embankment
constructed on a collapsible silt subgrade. This is
illustrated in [1] and [2] by utilizing an Excel
spreadsheet for a given practical example.
ACKNOWLEDGMENTS
The paper is based on engineering studies conducted
for Olizky Earthworks Roads & Development Ltd.
under assignment by Israel Railways Ltd., and on thedata taken from the engineering study conducted by
M.N.M. Engineers Ltd. for Cross-Israel Highway Ltd.
Thanks are due these firms.
REFERENCES[1] Livneh, M. and Livneh, N.A., "CollapseSettlement Calculations for Embankments
Founded on a Collapsible Soil Subgrade,"
Proc. of the 2nd Int. Conf on Geotechnique,
Construction Materials and Environment,
GEOMATE 2012, Kuala Lumpur, Malaysia,
2012.
[2] Livneh, M. and Livneh, N.A., "On CollapseSettlement Calculations for Heterogeneous
Collapsible-Soil Subgrade," International Journalof GEOMATE, Vol. 3, No. 2 (Sl. No. 6), 2012,
pp. 363-368.
[3] Lawton, E.C., Fragaszy, R.J., and Hardcastle,
J.H., "Collapse of Compacted Clayey Sand,"
Journal of Geotechnical Engineering, Vol. 115,
No. 9, 1989, pp. 1,252-1,267.
[4] Zur, A. and Wiseman, G., "A Study of Collapse
Phenomena of an Undisturbed Loess," Proc. ofthe 7th Int. Conf. on Soil Mechanics andFoundation Engineering, Vol. 2.2, Moscow,
1973, pp. 265-269.
[5] Austerlitz, G., Ishai, I., and Komornik, A.,"Prediction of Collapse Potential in Israeli Loess
Subgrade," Proc. of the 7th Asian Regional Conf.
on Soil Mechanics and Foundation Engineering,Vol. 1, Haifa, 1983, pp. 106-111.
[6] Basma, A.A. and Tuncer, E.R., "Evaluation andControl of Collapsing Soils," Journal of
Geotechnical Engineering, Vol. 118, No. 10,
1992, pp. 1491-1504.
[7] Livneh, M., "The Engineering Properties ofLocal Loess as Subgrade for Roads andRunways," Publication No. 80-32, Transportation
Research Institute, Technion, Haifa, Israel, 1980.
[8] Livneh, M., "Recent Developments in the
Swelling Model of Expansive Clays for
Pavements Upheave Calculations," Journal of
Testing and Evaluation, JTEVA (ASTM), Vol.
40, No. 2, 2012, pp. 310-318.

70

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INFLUENCE OF FREEZE-THAW ACTION ON AIR-PERMEABILITY
OF UNSATURATED SOIL GROUND

1

Tatsuya Ishikawa1, Tetsuya Tokoro2, Dai Nakamura3 and Satoshi Yamashita3
Faculty of Engineering, Hokkaido University, Japan; 2Tomakomai National College of Technology
Japan; 3Faculty of Engineering, Kitami Institute of Technology, Japan

ABSTRACTThis study proposes a testing method of air-permeability for unsaturated soil ground subjected to freeze-thaw
action and to evaluate the effects of freeze-thawing and moisture content on air-permeability of soil ground. In
this study, we develop a new test device for the evaluation of air-permeability of unsaturated model soil groundand perform a series of air-permeability tests for soil ground made of non-frost susceptible sand and frost
susceptible volcanic cohesive soil under various freeze-thaw histories and moisture contents. As the results, it
was revealed that the test device could evaluate air-permeability of freeze-thawed geomaterials in unsaturated
condition, and that the freeze-thaw action has strong influences on the air-permeability of frost-susceptible
geomaterials in unsaturated condition.
Keywords: Unsaturated soils, Air-permeability, Freeze-thaw action, Moisture content, Frost susceptibility

method that can assess the variations in the airpermeability of unsaturated soils in the verticaldirection, which are attributable to the changes in thetemperature like freeze-thaw of soil ground.
The objective of this study is to propose a testing
method of air-permeability for unsaturated soil
ground subjected to freeze-thaw action and toevaluate the effects of freeze-thaw and moisture
content on the air-permeability. To this end, wedevelop a new test device suitable for the evaluationof air permeability of model soil ground inunsaturated condition and perform a series of airpermeability tests for soil grounds made of non-frost
susceptible sand and frost susceptible volcanic
cohesive soil under various freeze-thaw histories andmoisture contents. Based on the test results, first, theapplicability of the newly developed test device tothe air permeability test for unsaturated geomaterials
was examined by comparing the results with those inexisting literatures. Next, the effects of freeze-thawand moisture content on the air-permeability of soil
ground were examined.

INTRODUCTION
At frozen soil grounds where gases (e.g., toxic gases
or greenhouse gases) are stored and accumulated, insome cases these gases are ejected to the groundsurface in thawing season, thereby causing the gas
leakage accident from subsurface layer and theglobal warming. In this case, there is a possibility
that freeze-thaw action affects the air-permeability
in cold regions because it results in the fluctuation ofmoisture content and frost heave phenomenon. For
example, Seyfried and Murdock [1] reported that if
the soil temperature falls below 0 °C, the airpermeability decreases very rapidly by performing
air permeability tests on frozen sand. Moreover,Kamiya et al. [2] showed that the air permeability
drops with increasing the degree of saturation basedon the results of air permeability tests on unsaturated
sandy soil and silty soil. Accordingly, it is important
for the preventive maintenance of the abovementioned geotechnical disasters to develop a
testing method for the evaluation of the airpermeability in unsaturated soil grounds subjected tofreeze-thaw actions.
However, there are few researches which
examine the effect of freeze-thaw action on airpermeability of unsaturated soils. For example,
although the “Method for Air Permeability Test In
Vadoze Zone (JGS1951-2006)” [3] has beenstandardized for testing the air-permeability ofunsaturated soils, the objective is not to measure thecoefficient of air-permeability for soils subject tofreeze-thaw actions because the standard only
evaluates the air-permeability in the horizontal
direction. Therefore, currently in Japan, there is no

TEST DEVICE FOR MODEL TEST
Figure 1 shows a schematic diagram of the airpermeability test device for model soil ground,which consists of a polyvinyl chloride pipe (1.12 m
in height and 0.59 m in diameter), a vacuum pomp
for suction of air, a flowmeter and differential
pressure gauges attached to monitoring wells. The
device causes a flow of air within the model soil
ground by applying a negative pressure in the lower
end of the device with a vacuum pump, andmeasures the air flow rate (1atm, 20°C) at that time,71

GEOMATE-Nagoya, Nov.13-15, 2013

Pressure gauge

Dry density, ρd (g/cm3)

Drainage tankDifferential
micropressure
gauge

Screen0.20m

Air flow rate meter
Vacuum pump
Monitoring well

0.20m

Polyvinyl chloride pipe

0.20m

Exhaust path

0.22m

0.20m

1.55
1.54
1.53
1.52
1.51
1.50
1.40
1.30
1.20
1.10
0

Drainage path
0.59m

Fig. 1

Fig. 2

Air permeability test device of soil ground.

5

10 15 20 25 30
30 35
35 40
40
Moisture content, w
w (%)
(%)

Compaction curves of samples.

100

Percent finer (%)

the pore air pressure, the moisture content by
volume, and the temperature distribution inside themodel soil ground. The coefficient of air
permeability between two adjacent monitoring wells,or between the ground surface and the monitoring
well (referred to below as “layers”), was calculatedusing Darcy’s law (Eq.(1)). In this case, in thecalculation of the air pressure gradient (i), to exclude
the effect of the compressibility of the permeatedgas, corrections are applied according to thetemperature and pressure using Eq.(2) [4].

Q = Aka i: Toyoura
Toyoura sandsand
: Touryo
Touryo soil
soil

: Toyoura sand: Touryo soil

80

Touryo soil

ρs = 2.56 g/cm3

60

Fc = 46.7 %Ip = 5.41

40

Toyoura sandρs = 2.65 g/cm3

20

Fc = 0 %Ip = NP

0
1E-3

0.01
0.1
1
Grain size (mm)

10

(1)
2


T1
T2
 T 0  
T0
+ ha1   −  ha0'
+ ha2   ha0'
T 0'
 T 0'
 T 1  
T2
i=
2ha0l

2

Fig. 3Grain size distribution curves of samples.

from the compaction test (JIS A1210, A-a method)
are shown in Fig. 2, and the grain size distribution
curves and the physical properties are shown in Fig.
3. Toyoura sand has an optimum moisture content ofw opt =13.2% and the optimum dry density ofρ dmax =1.85g/cm3, and it is a non frost-susceptible
material without fine fraction. In contrast, Touryo
soil has a higher optimum moisture content(w opt =32.5%) than Toyoura sand and a smaller
optimum dry density of ρ dmax =1.34 g/cm3. Also,
Touryo soil has a high fine fraction content of
46.98%, and in frost heave tests (JGS 0172-2003) itshowed a frost heave ratio of 89.7%, which indicateshigh frost susceptibility.

(2)
where, k a : coefficient of air permeability (m/s), Q :flow rate (m3/s), A : cross-sectional area (m2), i : airpressure gradient (m/m), T 0 : 293.15 (K), h a0 :10.332 (m), T 0 ' : air temperature at the time of thetest (K), h a0 ' : atmospheric pressure at the time of thetest (m), T 1 : soil temperature of the uppermonitoring well (K), h a1 : differential pressure of theupper monitoring well (m), T 2 : soil temperature of
the lower monitoring well (K), h a2 : differential
pressure of the lower monitoring well (m), and l :thickness of the layer (m).

Air Permeability TestTESTING METHOD

The air permeability tests were conducted as indoor(Fig. 4a) and outdoor (Fig. 4b) tests in a closedsystem frost heaving condition where the supply or
drainage of water to or from the specimen during thefreeze–thaw was not allowed, as described below.

Test Samples
The samples used in this study are Japanese standard
sand (Toyoura sand) and a volcanic cohesive soil
sampled in Kitami, Japan (hereafter referred to as“Touryo soil”). The compaction curves obtained

Indoor tests

72

GEOMATE-Nagoya, Nov.13-15, 2013

Soil
: moisture
meter
5cm
10cm
10cm
10cm
12cm

Pumping flow rate, Q (m3/s): Thermo
meter

0.59m

6.0x10-4

2.5cm
7.5cm
10cm
10cm
10cm
10cm
10cm
10cm
10cm
10cm
12cm

0.59m

5.0x10-4
4.0x10-4
3.0x10-4
Indoor Test
: Unfrozen, Srr=20%, t=5cm: Unfrozen, Srr=20%, t=20cm: Frozen, Srr=20%, t=5cm: Unfrozen, Srr=20%, t=20cm

2.0x10-4
1.0x10-4
0.0
0.00

0.05

0.10

0.15

0.20

Air pressure gradient, i (m/m)
Fig. 4

Measurement in air permeability tests.
(a: indoor test, b: outdoor test)

Fig. 5

A model soil ground (H=0.47m, D=0.59m) wereprepared by placing a sample with adjusted moisture
content into the cylinder soil tank in 5 cm layers to
obtain a given initial degree of saturation (Toyoura
sand: S r0 =0, 20, 40, 60%, Touryo soil: S r0 =15, 37.5,
60, 80%), and each layer compacted for the desired
initial dry density (Toyoura sand: ρ d0 =1.51g/cm3(D c =82%), Touryo soil: ρ d0 =1.10g/cm3(D c =82%)).
At this procedure, soil moisture sensors and T-type
thermocouple thermometers were buried at equalintervals.
After specimen preparation, a negative pressure(from −1 to −10 kPa) was applied in stages in orderto calculate the coefficients of air permeability (k a )for unfrozen soil ground by using Eqs.(1) and (2)with measured values. Next, dry ice was put on topof the model soil ground to artificially freeze it down
to the monitoring well with a depth of 5 cm from thesurface, after which the k a for frozen soil ground
was found by carrying out the air permeability test in
the same way as for unfrozen soil ground. For only
Touryo soil, in addition to the test described above,
air permeability tests on the frozen soil ground underconditions that easily give rise to the frost-heave
phenomenon were conducted by reducing thefreezing rate (U) with a heat insulating material. For
example, in case of S r0 =60%, the freezing rate (U)was 16.07 mm/h without any heat insulating
material, while was 1.28 mm/h with the insulating
material. Finally, the air permeability test on freezethawed soil ground was conducted after model soil
ground had thawed at room temperature.

Examples of air permeability test results.

similar procedure to the indoor test to obtain thecoefficient of air permeability for both unfrozen andfrozen soil ground. However, for the air permeability
test with frozen soil ground, it was performed at thetime that the frost depth reached each of themonitoring wells, as estimated from the groundtemperature measured by the thermometers. Notethat the freezing index in Kitami city at the year
when the outdoor tests were conducted was
461°C∙days with an average temperature from
December to February of −5.6°C, and a freezing rate
was approximately 0.7 mm/h. Here, the freezing
index is defined as the number of cumulative
degree-days during freezing season.
RESULTS AND DISCUSSIONSApplicability of Device to Air Permeability Test
The relationships of each layer between flow rate(Q) and air pressure gradient (i) are shown in Fig. 5
for the indoor test using Toyoura sand underS r0 =20%. The Q-i relationships seems to be linear,regardless of freeze-thaw history and depth of thelayer. Similar tendency was observed at the airpermeability tests under different experimental
conditions, irrespective of moisture content, soil
sample, and testing location. Accordingly, Darcy’s
law is applicable to the calculation of the coefficientof air permeability (k a ).
Figure 6 shows the relationships between k a anddegree of saturation (S r ), which were obtained fromthe indoor and outdoor tests on Toyoura sand,together with past test results conducted under thesimilar experimental conditions [5]. The coefficientof air permeability increases with decreasing S r , andthis increasing tendency of k a is in fair good
agreement with that in the previous test results. As
pointed out in past studies, this is because theincrement of moisture content in voids decreases the
air channels, thereby obstructing the air permeabilityof soils. Besides, Fig. 7 compares the relationshipbetween the coefficient of air permeability and the

Outdoor tests
The moisture content of a sample used was adjusted
for the desired initial degree of saturation (Toyoura
sand: S r0 =40%, Touryo soil: S r0 =60%), and a model
soil ground (H=1.02m, D=0.59m) was prepared bycompacting the sample to achieve an initial dry
density (Toyoura sand: ρ d0 =1.51g/cm3, Touryo soil:
ρ d0 =1.10g/cm3) in the same way as for the indoor
test. The air permeability test was carried out using a
73

10-1

: Indoor test (unfrozen): Outdoor test (unfrozen): Sugii et al.(2002)

10-2

102
1

10

100

TouryoTouryoToyouraTouryoTouryoToyoura=15~80% SSrr=60%=60%(Frost(Frost heaving)heaving) SSrr=0~60%=0~60%
SSrr=15~80%
Unfrozen
Unfrozen
FrozenFrozen
Thaw
Thaw

10-1
10-2

10-3-3

Toyoura sandIndoor & Outdoor tests : ρd=1.51g/cm33
d
Sugii et al.(2002) : ρd=1.50g/cm33

10-3

10-4
0

d

10-4-40

Fig. 6

Coefficient of air permeability, ka (m/s)

Coefficient of air permeability, kaa(m/s)

Coefficient ofof airair permeability,
permeability, kkaa (m/s)(m/s)
Coefficient

GEOMATE-Nagoya, Nov.13-15, 2013

20
40
60
80
Degree of saturation, Sr (%)
r100

Fig. 8

Effect of moisture content on ka.

10-2

Toyoura sand
-4

10Fig. 7-10 -5

Effect of freeze-thaw action on ka.

(θ), which were obtained from the indoor tests on
Touryo soil, are shown in Fig. 8, together with thosefor Toyoura sand (Fig. 6). Note that in the case of insitu freezing, assuming that the volume of the porewater expands by 9%, the θ for frozen soils on thehorizontal axis was found to be 1.09 times the θ
before freezing, while in the case of frost heaving,the θ for frozen soils was 1.09 times the θ after
freeze-thawing since the moisture content in thelayers with frost heaving increases beyond that whenunfrozen. According to the frost heave ratio obtained
from the freezing procedure of each air-permeability
test, the frost-heave phenomenon has not occurred inother tests except the indoor test with Touryo soil at
an initial degree of saturation of 60% and a freezing
rate of 1.28 mm/h, and in these tests the model soil
ground is assumed to have been frozen in themanner of in-situ freezing.
As for Toyoura sand, k a decreases with anincrease in the moisture content by volume,
regardless of frozen or unfrozen soils. In addition,although there was no difference in the coefficientsof air permeability before and after freezing andthawing, the coefficient for frozen soil is slightly
smaller than that for unfrozen. This can bereasonably explained by the fact that for highmoisture content, or when the pore water contained
within the unfrozen soil freezes and expands, theproportion of pore air that forms the channels for thepermeating air is reduced.
As for unfrozen Touryo soil, it shows thedifferent tendency to Toyoura sand in that the k aincreases with increasing moisture content at therange lower than the optimum moisture content(equivalent to about θ=36%) but it dramaticallydecreases at higher moisture content. This is thought
to be because at a low moisture content the additionof water increased the aggregation of soil particles
only for Touryo soil and resulted in an increase in
the number and size of voids. For example, Nikol etal. [6] showed that the aggregation occurs in clay as
a result of the increased moisture content, and that

10-1

10-3

50
10
20
30
40
50
(%)
Moisture content by volume, θ (%)

Indoor test (ρdd=1.51g/cm33): Srr=24.0~28.0%
Seyfried & Murdock (1997)(ρdd=1.53g/cm33): Srr=11.8%: Srr=42.6%

0 5 10 15 20 25 30
Ground temperature, T (oC)

Effect of ground temperature on ka.

ground temperature during freezing, which wereobtained from the indoor tests for Toyoura sand withroughly the same degree of saturation (S r =24~28%)
with that in the past study [1]. Over the groundtemperature of 0 °C, the change in k a with thedecrement of ground temperature can hardly beseen, while below 0°C, together with the drop in the
ground temperature, the k a slightly decreases. In Fig.
6, for the plots with the same S r , the k a of frozen soil
is a little smaller than that of unfrozen soil. This isbecause the air channels in the frozen soil became
narrow in comparison with those in the unfrozen soil
due to the volume expansion of pore water duringphase-change from fluid to solid. The dependence ofk a on the ground temperature in this study can berecognized even in the previous test results.
Accordingly, it seems reasonable to conclude that atest device newly developed in this study canevaluate air-permeability of soil ground.
Effect of Moisture content on Air Permeability
The relationships between the coefficient of air
permeability (k a ) and moisture content by volume74

Coefficient ofof airair permeability,
permeability, kaa(m/s)
Coefficient

Ratio of coefficient of air permeability rate, kaT / kaT=20

GEOMATE-Nagoya, Nov.13-15, 201310
Touryo (θ=21～23%)
Toyoura (θ=10～12%)

8
6
4
2
0
-5

Fig. 9

0

5

10

15

20

Ground temperature, T (oC)

100
10-1
10-2
10-3
-4
-4

10

θ =22.4%
θ =29.2%
θ =22.8%

θ =28.2%: Thaw layer(1st layer): Deeper than thaw layer(2nd layer)

10-5-5
Unfrozen

FrozenThaw

RefrozenFig. 10 Change in ka during cyclic freeze-thawing.

Dependency of ka on ground temperature.

degree of saturation of 80% (close to θ=40%),though the k a for unfrozen soil showed a high value
despite the high moisture content since theaggregation had occurred to an extent by which it
could be verified visually, the k a for frozen soil
decreased. The reason for these can be explained asfollows. At a low moisture content, pore water
inside unfrozen soil ground moves along with theflow of air and as the result air is less likely to passthrough, while when frozen, the air can easily passthrough as the pore water freezes on the spot.
Whereas, at a high moisture content, the existence ofa large amount of pore water makes air flow moredifficult because the volume expansion of frozen
pore water is bigger as compared to the low moisture
content.
Furthermore, from the circles in Fig. 8, the k a forfrozen soil with frost heave has a high value
compared to that for unfrozen soil, and it showed adifferent tendency to the non-frost heave case in thatthe k a after thawing also slightly increased over thevalue before freezing. This is because in addition to
the increase in the k a when freezing compared to theunfrozen case, due to the voids increasing with thelocally occurring frost-heave phenomenon, voids
still remain following thawing, thus increasing thecoefficient compared with the unfrozen case.

the number of large-sized pores increases, which
implies that the phenomenon may therefore occur inTouryo soil with particles that are similar in size tothose in clay. Besides, Sugii et al. [7] showed that inaggregated soil that has a double-pore structure, theaggregation is formed due to macropores (50 nm orlarger) which contribute to its permeability, andmicropores (2 nm or smaller) which contribute to its
water retentivity. From this fact, the macropores
may also contribute to the air permeability of soils,
but the effect of aggregation on the air permeability
requires further study.
Effect of Freeze-Thaw on Air Permeability
To reveal how ground temperature affects the airpermeability of the soil, Fig. 9 compares therelationships between the ratio of the coefficient of
air permeability and the ground temperature for the
specimens with roughly the same degree ofsaturation (S r =37~40% for Touryo soil, S r =23~28%
for Toyoura sand) with each other. Here, the ratio of
the coefficient of air permeability is defined as anormalized value of k a for a specimen at a given
temperature with the k a for the specimen at thetemperature of 20°C. At the temperature range over
0°C, the k a remains invariant regardless of theground temperature in test results for both samples,while below 0°C, with decreasing the groundtemperature, the k a drops very slightly for Toyoura
sand but increases very rapidly for Touryo soil.
Therefore, both samples show the temperaturedependency of the coefficients of air permeability.
Next, the influence of the experimental condition
during freezing on the air permeability is discussed.
As can be seen in Fig. 8, with no frost heave, nodifference is observed in the k a of Touryo soil before
and after freeze-thawing, as is the case for Toyoura
sand. However, up to a low moisture content by
volume of 30%, the k a for frozen soil is larger thanthat for unfrozen soil. In contrast, at the initial

Effect of Cyclic Freeze-Thaw on Air Permeability
Figure 10 compares the coefficients of air
permeability (k a ) obtained from outdoor tests
conducted at four different timings during freezethawing, that is, the unfrozen case (“unfrozen” in theFig. 10), the time when frozen to a depth of about 80
cm (“frozen”), the time when thawed uniformly
down to a depth of approximately 1 cm by pouring
warm water after freezing nearly the whole
specimen (“thaw”), and finally, the time whenrefrozen after being thawed out (“refrozen”). Here,the filled circle symbol in the figure represents theuppermost layer of the specimen that has been75

GEOMATE-Nagoya, Nov.13-15, 2013

thawed down to roughly 1 cm, and the hollow circle
symbol represents deeper layers.
There was little visible difference in thecoefficient of air permeability in the depth direction
for the unfrozen case; however, in the frozen andfrost heaving cases, the coefficient became different
depending on the moisture content by volume.
Further, after thawing by warm water, the amount ofpore water increased compared with that amount
before thawing, which resulted in a decreased
coefficient of air permeability. When the pore water
was subsequently refrozen, the coefficient further
decreased. Thus, for Touryo soil, increasing the
moisture content by volume beyond a constant value
makes it more difficult for air to pass through, andthe coefficient of air permeability tends to decrease
further with the added moisture content freezing andfrost heaving.

This research was supported in part by Grant-in-Aid
for Challenging Exploratory Research (21651080 &
24651204) from Japan Society for the Promotion of
Science (JSPS) KAKENHI.
REFERENCES[1] Seyfriend MS, Murdock MD, “Use of air
permeability to estimate infiltrability of frozen
soil”, Journal of Hydrology, 202, 1997, pp. 95107.
[2] Kamiya K, Bakrie R, Honjo Y, “Themeasurement of air permeability coefficient of
unsaturated soil with controlling water
retentivity”, Journals of the Japan Society of
Civil Engineers Division C, 62(3), 2006, pp.
679-688 (in Japanese).
[3] Japanese Geotechnical Society, “Method for air
permeability test in vadoze zone (JGS 19512012)”, Japanese Standards and Explanations ofGeotechnical and Geoenvironmental Investigation Methods, 2013, pp. 23-27 (in Japanese).
[4] Japanese Geotechnical Society, “Evaluation of
unsaturated soil ground behavior”, 2004, pp. 2535 (in Japanese).
[5] Sugii T, Yamada K, Yogo T, “Study on air
permeability test for unsaturated soils”, in Proc.
of the 37th Japan National Conference on
Geotechnical Engineering, 2002, pp. 1275-1276(in Japanese).
[6] Kochmanová N, Tanaka H, “Effects of
microstructure on compacted clay properties”,
in Proc. of Technical report of the Annual
Meeting of the JGS Hokkaido branch, Vol. 50，
2010, pp. 193-198 (in Japanese).
[7] Sugii T, Fang F, “Study on hydraulic propertiesof aggregated soils”, in Proc. of the 46th Japan
National
Conferenceon
GeotechnicalEngineering, 2011, pp. 1025-1026 (in Japanese).

CONCLUSION
In this study, a series of air-permeability tests forsoil ground were conducted on non-frost-susceptible
sand and frost-susceptible volcanic cohesive soil
under various freeze-thaw histories and moisture
contents. Based on the test results, together withdemonstrating the validity and usefulness of a newly
developed test device and a proposed new testing
method when evaluating a temperature-dependent
coefficient of air permeability for unsaturated soil
ground subjected to freeze-thaw action, we revealed
that due to the experimental fact that the airpermeability of unsaturated soil ground is dependent
on the moisture content and freezing rate of soils, it
is significantly affected by material properties ofsoils such as the frost susceptibility, the soil water
characteristics, and the compaction characteristics inaddition to being affected by environmental factors
such as ground temperature and groundwater level.
ACKNOWLEDGEMENT

76

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECT OF ROCK SOCKET CHARACTERISTICS ON LOW STRAIN
INTEGRITY TEST OF PILES
Ramli Bin Nazir1 and Osman El Hussien2
Associate Professor, Faculty of Engineering, Universiti Teknologi Malaysia, 2PhD Student, Faculty ofEngineering, Universiti Teknologi Malaysia

1

ABSTRACT
Recently constructed piles are usually tested in order to evaluate their integrity as part of foundation
construction quality control. The low strain integrity test is routinely performed, because it is fast and costeffective. However, integrity of piles socketed in hard rock strata is usually difficult to assess. This difficulty is
attributed to the dissipation of the stress wave as a result of hard rock resistance effects. A new method ispresented, which used to evaluate rock socket characteristics including rock strength and socket length on
integrity test results. Rock damping effects applied on stress wave were quantified for both skin resistance andtoe reaction for different rock strengths and socket lengths using numerical solution of wave equation afterincorporating soil effects. The generated results were compared with a wave propagation simulation software
output, and the accuracy of the model was validated. It was found that rock socket characteristics play a majorrole in evaluating integrity of piles cast in hard rock, using low strain test method, and may lead to inconclusive
assessment of piles integrity.
Keywords: Pile, Integrity, Rock, Socket

INTRODUCTION

MODEL FORMULATION

Currently there is no clear idea about the effectof soil resistance on the stress wave propagation into
piles as well as the soil impact on the applied
analysis methodologies. This fact had caused
engineers to go through assumptions in order tocompensate for lack of proper identification ofpile/soil interaction, which may jeopardize thequality of the test output. In addition, soil resistanceand damping effects may lead to inconclusive
assessment of pile integrity, while it is difficult todistinguish soil response from pile response [1].
Soil resistance effects are required to be properly
considered for calculation of impedance profile.
However, soil effects are never definitely known andfor that reason engineering judgment may seriously
affect the results [9]. Note that direct measurementof soil resistance or other soil parameters is not theobjective of low strain integrity testing. Therefore no
attempt has been made to formulate mathematicalexpressions relating soil resistance as a function of
any of the parameters from the mobility spectrum[7]. In construction practice, piles are commonlysocketed in hard strata such as rocks in order totransfer the structural loads to the competent deep
layers. However, in such condition the hard layer,
which surrounds pile toe, may affect the accuracy of
low strain test of pile, while the increase in soil
resistance force results in a decrease in the measured
pile top velocity [4].

During integrity test, the pile is subjected to an
impact with a light hammer. Upon hammer strike,the impact will produce the following:
1- Downward displacement of pile body.
2- Mobilization of soil friction at the surface areaof the pile.
3- Stress wave propagation through pile body,which will be:a) Attenuated by soil friction.
b) Partially reflected at pile toe after been
attenuated by soil resistance.
Hence, soil effects on pile tested by low strain
integrity test can be categorized as follows:
1- Skin friction mobilization.
2- Soil – Pile interaction at pile toe.
Assuming a bar as shown in Fig. 1 having
density (ρ) is subjected to dynamic force (F) resulted
in linear displacement (w) in the (x) direction at time(t). The basic mathematical formulations based onforce equilibrium and Newton’s second law of
motion will be as follows:−σ +σ +

77∂σ
∂2w
dx = ρ dx 2
∂x
∂t

(1)

E=

σ
ε

(2)

ε=

∂w
∂x

(3)

GEOMATE-Nagoya, Nov.13-15, 2013

Substituting Eq. (2) and Eq. (3) in Eq. (1), thepartial differential equation, which known as thewave equation, can be arrived:

∂2w

∂2w

∂t

∂ x2

= c2
2

r
r0 . ln( m )
r0

wi

(9)

Where (G) is soil shear modulus, (r0) is pile
radius and (rm) is the pile influence zone, which canbe estimated using ground vibration attenuation
equation [2] as follows:(5)ρ

A1 = A0 (r0 / r1 ) (γ ) eα ( r0 −r1 )Schematic diagram for a bar subjected to
dynamic impact

Fi − Fi −1 = ρ A ∆zv i (t + ∆t ) − v i (t )∆twi (t + ∆t ) − wi (t )∆tw − wiFi = EA i +1
∆z

(10)

Where, (A0), (A1) are vibration amplitudes at (r0),(r1) distances respectively, (γ) is a coefficientdepends on wave type and (α) is material damping
coefficient. Summary of some published values ofgeometric attenuation coefficient (γ) and material
attenuation coefficient (α) are shown in Tables 1 and
2, respectively.
When the incident force (F i ) reaches pile-soil
interface of a pile cast in hard soil, the following is
expected to occur:
1- Partial transmission of force (F t ).
2- Partial reflection of force (F r ).
3- Generation of soil reaction at toe (F R ).
Force transmission/reflection at interface iscaused by impedance change. Figure 3 illustrates theabove mentioned scenario.

For the pile segment shown in Fig. 2, whichshows the axial force acting on segment top and thefrictional forces acting on segment circumference,
the numerical solution for the wave equation afterincorporation of soil friction will be as follows:vi = .

G(4)

Where,
Ec=

Fig. 1fi =Table 1 Some published (γ) values [2]Investigator
-Wiss

(6)

-Brenner &Chittikuladilok(7)-Attewell & Farmer-Nicholls, Johnson& Duvall-Martin(8)-Amick & Ungar

Soil Type
Sands
Clays
Surface sands
Sand fill over soft
clays
Various soils (firm)
Firm soils and rock
Clay
Silt
Clay

(γ)
1.0
1.5
1.5
0.8–1.0
1.0
1.4–1.7
1.4
0.8
1.5

Table 2 Some published (α) values [2]Investigator-Forssblad
RichartFig. 2-Woods-Dalmatov, etal.
- Barkan
Clough andChameau

Forces acting on pile segment

The skin friction is assumed to be proportional todisplacement as per the following frictiondisplacement correlation [6]

-Peng
78

Soil TypeSilty gravelly sand4-6 in. concreteslab over compact
granular fill
Silty fine sand
Sand and silts
Marly chalk
Sand fill over Bay
Mud
Dune sandSoft Bangkok clay

(α)
0.13
0.02

0.26
0.026–0.36
0.10
0.05-0.20
0.026–0.065
0.026–0.44

GEOMATE-Nagoya, Nov.13-15, 2013

MODEL VERIFICATION

Fig. 3The numerical formulation output is comparedwith PIT-S computer software output. PIT-S issimulation software, which takes soil properties, piledetails and low strain hammer impact information,and displays force and velocity curves versus timeand pile length. Specific soil, pile and dynamic load
data were used in the comparison between bothmethods. The PIT-S software is based on wave
equation analysis and Smith model of pile driving.
In Smith model, the resistance to driving force issimulated by series of springs and dashpots, and thespring stiffness is defined by ratio of maximum
elastic deformation or quake. Typical quake values
are in 2.0 to 5.0mm range. However, soils with highrebound have high quake values in excess of
25.0mm [3]. Hence, in Smith model, soil resistanceto pile driving is given as follows [8]:Forces acting on pile bottom segment

At the pile-soil Interface, the force caused by thereflected wave (Fr) in terms of the incident wave
caused force (Fi) isρ s vs−1
ρ v] Fi
Fr = [ c c(11)ρ s vs+1
ρ c vcWhere, (ρs) is soil density, (vs) is wave velocity
in soil and (vc) is wave velocity in concrete.
Soil reaction (FR) at pile toe is calculated as per
Kagawa correlation [5]FR = E sb r0b δ 0b z + 2(1 + ν sb ) ρ sb G sb r02b δ 0b T3 v p

Rt = R s (1 + Jv )(13)

Where, (R t ) is total soil resistance to driving,(R s ) is static soil resistance, (J) is soil damping
coefficient and (v) is velocity of pile toe.
The analysis for both PIT-S software and thenumerical model was carried out assuming concrete
pile cast in very dense granular soil. The set data
used in the analysis is shown in Table 3(12)

Where:F R : Soil reaction at pile tip
E sb : Young’s modulus of soil
r 0b : Radius of pile tip
δ 0b : Soil reaction coefficient
z: Pile tip displacement
ν sb : Poisson’s ratio of soil at pile tip
ρ sb : Soil density at pile tip
G sb : Shear modulus of soil at pile tip
T 3 : Polynomial function coefficient
vp: Pile tip velocity
Based on the above mentioned theories, themodel was assembled and executed using computer
programmed spreadsheets. The input data in theanalysis are the dynamic load details in addition to
pile and soil characteristics. The pile is discretized
into small segments as in Fig. 2. Force, velocity anddisplacement values are calculated for each pilesegment utilizing the numerical solution of wave
equation after incorporation of soil friction provided
in equations 6, 7 and 8. Soil friction was calculatedusing the friction-displacement and attenuation
correlations provided in equations 9 and 10,
respectively.
The toe segment is analyzed basedon impedance change as well as soil reaction effects,
which are provided in equations (11) and (12),respectively.
Based on the above methodology, the force andvelocity values were obtained for both downward
and upward movement of stress wave in order to
identify stress wave characteristics at different pile
depths.

Table 3 Soil, pile and load data used in the analysis
Item
Pile Length, L (m)Concrete Density, ρ c (t/m3)
Pile elastic modulus, E (kN/m2)
Pile Radius, r 0 (m)Soil Density, ρ s (t/m3)
Poisson's Ratio, νSoil Shear Modulus, G (kN/m2)
Force Amplitude, F (kN)
Pulse duration, (sec)
Attenuation coefficient(γ)
Attenuation coefficient(α)

Value
10.0
2.5
4x107
0.18
2.0
0.4
50,0005.0
0.00025
1.0
0.13

Pile influence zone (r m ) was calculated based on
the assumption that pile influence zone is the
distance where 95% attenuation in vibration
amplitude occurs. PIT-S software generated velocity
curve and the proposed model generated velocity
curve for a signal received at pile top using the data
shown in Table 3, for circular concrete pile cast invery dense granular soil, are provided in Fig. 4 andFig. 5, respectively.
To compare both models, force and velocity
amplitudes versus time are plotted at signal
receiving depths of 0.0m, 5.0m and 9.875m. It has
been found that the force and velocity amplitudes
produced using the proposed model and PIT-S
79

GEOMATE-Nagoya, Nov.13-15, 2013

00..0011

software are close to each other for signals received
at 0.0m and 5.0m depths of pile as shown in Fig. 6
and Fig. 7.

V (P
V
PIIT
T--S
S)
V (M
V
Mooddeell)

Veelloocciitty (mVm//sseecc)

00..000088

00..000066

00..000044

00..000022

00
0Fig. 4Tiim
Tmee (sseecc)

0..0020..003

PIT-S velocity curve at pile top
Fig. 70 ..0 10 ..0 0 7 5ROCK SOCKET EFFECT
Effect of strength of rock in terms of dynamic shear
modulus value and the effect of rock socket length
were evaluated using the numerical analysis
illustrated above. Pile, soil, rock and impact load
data for a sample integrity test used for the analysis
is shown in Table 4.

0 ..0 0 2 5

ello
Ve
V
occiitty (ccm
m/sse
ecc)

Velocity amplitudes from model and PIT-Sm/sm/s
0..00500 cs)s (0 ..500 m
cm

0 ..0 0 5

1
00
01
0..0
0

0
0

2
00
02
0..0
0

3
00
03
0..0
0

4
00
04
0..0
0

6
00
06
0..0
0

5
00
05
0..0
0

0

me
ecc)
e (sseTim
T--0 ..0 0 2 5-- 0..00270 c
cm
s)
m/s
s (-- 0..270 m
m/s
--0
05
5
0 ..0
00

--0
5
75
07
00
0 ..0

--0
01
1
0 ..0

Table 4 Soil, rock, pile and load data used in
evaluation of rock socket effect--0 ..0 1
5
12
25

Fig. 50..001

New model velocity curve at pile top

Item
Pile Length, L (m)Concrete Density, ρ c (t/m3)
Pile elastic modulus, E (kN/m2)
Pile Radius, r 0 (m)Soil Density, ρ s (t/m3)
Rock Density, ρ s (t/m3)
Soil Poisson's Ratio, ν sRock Poisson's Ratio, ν r
Soil Shear Modulus, G (kN/m2)
Force Amplitude, F (kN)
Pulse duration, (sec)
Attenuation coefficient(γ) for soil
Attenuation coefficient(α) for soil
Attenuation coefficient(γ) for rock
Attenuation coefficient(α) for rock

As shown in the figures, relatively higher
differences between PIT-S software and model
generated force and velocity values were observed
near pile toe. These differences are attributed to thedifferences
betweenpile-soilinteractions
assumptions incorporated in both models.
PIT-S software is based on Smith modeling forpile driving, which incorporates static soil
resistance; however, in low strain integrity test, thedynamic load is very light compared to pile driving
load and does not mobilize full static resistance ofsoil. For this reason, the proposed model had utilized
a dynamic reaction theorem for pile toe analysis,
which does not require full mobilization of soil
resistance.

Value
10.0
2.5
4x107
0.18
2.00
2.25
0.40
0.25
50,0005.0
0.00025
1.0
0.13
1.7
0.10

88

Effect of Rock Strength below Pile Tip

T--S)
F
PIIT
Foorrccee (PF
Moodeel)Foorrccee (MThe first run of analysis was carried out assumingthat the study pile is resting on a rock stratum, which
does not extend above pile tip level (i.e. zero lengthrock socket). The analysis was conducted for two
different rock strength values in terms of shear
module. The first rock type has a shear modulus of
250,000 kN/m2, while the second rock type has
500,000 kN/m2 shear modulus value. This change inshear modulus values facilitates the study of rockstrength effect, in terms of its shear modulus value,on the generated pile tip reaction. A reduction instress wave force and velocity amplitudes of 15.4%

FN)
Foorrccee (kN

66

44

2

00

0

Fig. 60..001T
Tiim
mee (sseecc)

0..0020..003Force amplitudes from model and PIT-S
80

GEOMATE-Nagoya, Nov.13-15, 201344

and 19.8% were observed when the shear modulus
value was changed from 250,000 kN/m2 to 500,000
kN/m2. These reductions are attributed to theimpedance change as a result of changing rockstrength and to the produced soil reaction at pile toe
for different rock strata. Force and velocity
amplitude values for both rock types at zero lengthrock sockets are provided in Tables 5 and 6.

= 225500,000000 kkN
Foorrccee (SF
Shheeaarr M
Mooduulluuss =N/mm2)= 550000,000000 kkN
Foorrccee (S
N/m
m2)
F
Shheeaarr M
Mooduulluuss =F
N)
Foorrccee (kN

33Table 5 Force and velocity amplitudes for different
socket lengths for G = 250,000 kN/m2 rockSocket Length
(m)
0.0
2.0
4.0
6.0

Force
(kN)
3.190
2.878
2.605
2.343

1

Velocity(m/s)
0.003190.00288
0.00260
0.00234

00

Fig. 8

4

6

Leenngtthh (mRoocckk S
Soocckkeett L
R
m)

10

8

Force amplitudes for different rock socket
lengths of two rock types

00..000044
m22)
V (Sheeaarr Mooduuluuss == 250,000 kN/m
m22)
V (Sheeaarr Mooduuluuss == 500,000 kN/m
00..000033

Veelloocciitty (mm//sseecc)
V

Force
(kN)
2.698
2.165
1.748
1.393

2

0

Table 6 Force and velocity amplitudes for different
socket lengths for G = 500,000 kN/m2 rockSocket Length
(m)
0.0
2.0
4.0
6.0

22

Velocity(m/s)
0.002700.002160.001750.001390..00220..001

Effect of Rock Socket Length00
0The effect of rock socket length on stress wave wasstudied through analyzing the sample pile for 0.0m,
2.0m, 4.0m and 6.0m socket lengths. These analyses
were carried out for shear modulus values of
250,000 kN/m2 and 500,000 kN/m2. For the rockhaving 250,000 kN/m2 shear modulus, the increasesof rock socket length from 0.0 to 2.0m, from 2.0m to4.0m and from 4.0m to 6.0m were found to cause
reductions in stress wave force and velocity
amplitudes by 9.8%, 9.5% and 10.1%, respectively,
while reductions of 19.8%, 19.3% and 20.3%,
respectively, were observed for the rock having
shear modulus of 500,000 kN/m2. These observed
attenuations in stress wave amplitudes were causedby the increase of frictional resistance forces when
the socket length is increased. Furthermore, theincrease in rock shear modulus is found to haveremarkable effect on increasing the attenuation
values as illustrated in the following section. Socket
lengths versus force and velocity amplitudes for bothrock types are plotted in Fig. 8 and Fig. 9,
respectively.

Fig. 92

4

6

R
Leenngtthh (mRoocckk S
Soocckkeett L
m)

8

10

Velocity amplitudes for different rocksocket lengths of two rock types

Effect of Rock Shear Modulus
It had been noticed that for changes of socket
lengths from 0.0 to 2.0m, from 2.0m to 4.0m andfrom 4.0m to 6.0m, the reduction in stress wave
amplitudes were found to change from 9.8% to19.8%, 9.5% to 19.3% and from 10.1% to 20.3%
when the rock shear modulus changed from 250,000
kN/m2 to 500,000 kN/m2. Hence, 100% increase in
dynamic shear modulus of rock had caused about
100% reduction in stress wave force and velocity
amplitudes.

81GEOMATE-Nagoya, Nov.13-15, 2013

Congress 2006: Geotechnical Engineering in the
Information Technology Age, Georgia, USA.
[4] Johnson, M., Rausche, F., “Low Strain Testingof Piles Utilizing Two Acceleration Signals”.
September, 1996. Proceedings of the Fifth
International Conference on the Application ofStress-wave Theory to Piles 1996: Orlando,
USA, FL; pp. 859-869.
[5] Kagawa T., “Dynamic Soil Reaction to Axially
Loaded Piles”, Journal of GeotechnicalEngineering, Vol. 177, No. 7, July 1991.
[6] Kraft, L. M., Ray, R. P., and Kagawa, T. (1981).
Theoretical t-z curves, Journal GeotechnicalEngineering Division, Proceedings Paper
16653, American Society of Civil Engineers,
Vol 107(GT11).
[7] Liang, M and Wu J, “Predicting the Integrity of
Existing Concrete Bridge Deck Using Sonic
Method”, Journal of Marine Science andTechnology, Vol. 9, No. 1, pp. 45-52, 2001.
[8] Mc Vay M. and Kuo C., “Estimate Damping
and Quake by using Traditional Soil Testings”,
Final Report for Florida Department ofTransportation, Nov. 1999.
[9] Rausche, F., Likins, G. E., Ren-Kung, S.,
September, 1992. “Pile integrity testing andanalysis”. Proceedings of the FourthInternational Conference on the Application ofStress-Wave Theory to Piles, Netherlands, pp.
613-617.

CONCLUSION
Soil resistance effects on stress wave that
propagates during pile integrity test were quantified
using new numerical method to solve the wave
equation after incorporation of soil effects.
The skin friction mobilized as a result of light
impact load on pile top during pile integrity test is
assumed to be directly proportional to pile
displacement.
Soil reaction at pile toe is assumed to be
proportional to pile segment displacement andvelocity. This assumption was found to be suitable
for light dynamic loading on piles such as in the low
strain integrity test, while small and instantaneous
soil reactions can still be quantified.
Generated soil reaction at pile tip was found to
be less sensitive for change of dynamic shear
modulus of the strata below pile toe. This is
attributed to the indirect proportional relation
between soil reaction and pile toe displacement andvelocity.
Rock socket characteristics like socket length androck strength in terms of dynamic shear modulus
were found to have remarkable effect on stress wave
attenuation.
This method of analysis for pile tested underlight dynamic loads can be used further to evaluate
the efficiency of low strain integrity test for piles
socketed inside hard rock. This method can provide
good tool to evaluate the stress wave absorption
phenomenon by the hard strata, which surround thepile.
ACKNOWLEDGEMENTS
The authors would like to thank the Research
Management Centre of Universiti Teknologi
Malaysia (UTM) and Ministry of Science,
Technology and Innovation (MOSTI) for providing
financialsupportthrough
research
vote:
R.J130000.7822.4F118 for this research, and Pile
Dynamic Incorporation for providing the technicalsupport related to PIT-S software.
REFERENCES[1] American Society of Testing and Materials(ASTM), 2007. Section 4, Vol. 04.09, Standard“Test Method for Low Strain Impact Integrity
Testing of Deep Foundations”.
[2] Amick, H., and Gendreau, M., “Construction
Vibrations and Their Impact on VibrationSensitive Facilities”. 2000. Proc., ASCE
Construction Congress 6, Orlando Florida, pp.
1-10.
[3] Hussein, M., Woerner, W., Sharp, M. andHwang, C. “Pile Driveability and Bearing
Capacity in High-Rebound Soils”, Geo82

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CHARACTERISTICS OF SLOPE FAILURES IN MAKINOHARA,JAPAN
Jun Sugawara1
Golder Associates, Australia

1

ABSTRACT
Makinohara City, located in south-central Shizuoka Prefecture in Japan, is renowned for the production ofhigh quality Japanese green tea. Approximately 25% of Makinohara City’s land is used as tea plantation fields
and annually 5,800 tonnes of tea is produced. However, slopes in this region are occasionally subject to failures
following construction activities. In this light, this paper investigates characteristics of slope failures in
Makinohara region. Based on the author’s experience, a number of recommendations are also made for slope
analysis and mitigation works.
Keywords: Makinohara Plateau, Tea Plantation Fields, Slaking, Slope Mitigation, Surface Protection

INTRODUCTION
Makinohara City, founded by the merger of
Sagara Town and Haibara Town in 2005, is locatedin the south-central region of Shizuoka Prefecture in
Japan. The city is known for production of Japanese
green tea for a long period. Approximately 25% of
Makinohara City’s land is used as tea plantation
fields [1]. The Makinohara City Hall also has an
unique department called Tea Promotion Section
which specifically deals with tea related matters.
Today Makinohara City produces 5,800 tonnes oftea, which is approximately 6% of Japan’s overall
tea production.
In this region, a number of major transportation
networks have been developed. These include Tomei
Expressway, Japan National Routes 15 and 473,
Tokaido Shinkansen (Japanese high speed train),Omaezaki Port, and Mt Fuji Shizuoka Airport which
newly opened in 2009.
The author has noted that slopes in this region
are occasionally subject to failures following
construction activities. The author also identified
that the landslide prone areas often impinge on thetea plantation fields [2]. The recent landslide which
occurred in the tea plantation fields in Hamamatsu,
Shizuoka is a good example illustrating theassociation between landslide prone areas and thetea plantation fields.
In this light, this paper investigates thecharacteristics of slope failures in the Makinohara
region. Based on the author’s experience, a numberof recommendations are made for slope analysis andmitigation measures.

Fig. 1 Google Map of Makinohara Region (after [3])GEOGRAPHY AND GEOLOGYThis region principally consists of theMakinohara Plateau with an elevation of less than
200m. A number of gullies are developed on thisplateau. A narrow alluvial plain of the Katsuma
River also lies in the middle of the Makinohara City.
According to relevant geological maps [4 and 5],
the Makinohara Plateau comprises the Makinohara
river terrace gravelly layers, which are in turnunderlain by layers of various degrees ofdecomposed Neogene (Miocene) age Kakegawa
Group and Sagara Group siltstones. The tolerance of
these siltstones to the weathering is relatively low
and their structure often includes advanced
fragmentation and softening. The overlying soils
are usually suitable for growing tea plants due to83GEOMATE-Nagoya, Nov.13-15, 2013

their weakly acidic characteristics.

(a)
(b)
(c)
Fig. 2 Shape of Slope Failures: (a) Convex Hill Type,(b) Concave Mono Hill Type and (c) Concave Poly
Hill Type (after [7])In many cases, determination of the slip surface
based on borehole core observation or monitoring
results (e.g, inclinometer or pipe strain gauge) may
not be difficult in this region. This is because thecore is often slickensided and monitoring results
typically show clear movement at the location of theslip surface. The slip surface is also occasionallyseen on the faces of excavations.
It is noted that when the slope movement issignificant, boreholes and inclinometer casings may
bend making the monitoring of the slip surface
impossible. This is not unusual in this region due tothe relatively fast movement of the slope. Based on
the author’s experience, this phenomenon could
happen within a very short period (e.g., 2 to 3
weeks) if the strength of geomaterial is low. When
this is anticipated, the pipe strain gauge needs to be
used for the slip surface monitoring.

Photo 1 Typical Tea Plantation Fields in the
Makinohara Region
TYPE OF FAILURES AND SLIP SURFACEIDENTIFICATIONIn the Makinohara region, slope failures are often
triggered by the earthwork excavations [6]. The
author also observed a number of failures caused byearthworks during the road and pond constructions
associated with the airport construction. There arealso slope instabilities caused by the construction ofembankments near the crest of past landslide sites.
According to the classification proposed by [7],slope failures in this region can be broadly classified
into the following categories: Weathered rock type: the shape of slope failure isthe convex hill type or the concave mono hill type.
Scarps and a strip of depression zone are often
observed near the slope crest. This type istypically triggered by the intensive rainfall events
after the construction of medium to large size
earthworks.
 Clayey soil type: the shape of slope failure isusually the concave poly hill type. This typeconsists of a number of shallow and small past
failures. Gully features are developed and theterrain topography is generally disturbed. The
groundwater table is usually high.

Photo 2 Slope Failure Triggered by Excavation
FACTOR OF SAFEY AND ANALYSISThe following design Factor of Safeties (FOS)
are usually used for the slope mitigation works inJapan:
 Temporary works: FOS ≧ 1.05
 Permanent works: FOS = 1.12 – 1.20, dependingon the importance of assets to be mitigated orprotected.
In Japan, the design of slope mitigation works is84

GEOMATE-Nagoya, Nov.13-15, 2013

undertaken by back-calculating strength parameters
for the slope, based on certain assumptions
regarding groundwater levels and cohesion.
However the choice of the highest groundwater level(HWL) as the groundwater level for the backanalysis is a relatively arbitrary choice, that may beaffected by a limited duration of monitoring. In
addition, there are always uncertainties indetermination of the slip surface. The required force
to achieve the design FOS could differ significantly
even with a slight difference in the shape of the slip
surface.
Moreover, the following factors need to becarefully considered during analyses and design ofslopes in this region:
 Many clayey soil type slopes appear to be
marginally stable, i.e., their FOS is close to 1.0.
Landslides in this area could be reactivated evenwith relatively minor triggering events.
 The regional geology tends to dip to southeast
direction. This structural geological setting as wellas other adverse geological conditions (e.g.,advanced weathering) often have significant
influence on the stability.
 Strong slaking and erosion events often cause
creep of slope and as a result overall FOS
decreases with time possibly within a short time.
The author encountered a number of instances of
temporary remediated slopes being damaged prior
to the start of permanent mitigation works.
Taking into account all of these factors as well as
the low design FOS commonly adopted in Japan, theauthor considers that a slightly conservative
approach is required particularly during temporary
works in this region.

measures [8].
Among those measures, earth removal, buttress
fill, groundwater control and anchors which arecommonly used in this region will be discussed in
the following sections.

Fig. 3 Landslide Mitigation Measures (after [9])EARTH REMOVAL AND BUTTRESS FILL
Among various slope mitigation measures,
cutting back the upper portion of the slope orbuttress filling near the slope toe is usually thequickest and the most economical mitigation option.
Groundwater can be also effectively lowered byearth removal.
Japan has one of the highest population densities
in the world. Therefore slopes are often designed as
steep as possible in order to minimise thedisturbance to the surrounding areas. For instance,
cut slopes in weathered siltstones are often designed
at 1:1.0 (V:H) in this region. However the author
observed a number of failures under the following
adverse conditions: Long and intensive rainfall events. The averageannual rainfall in this region is more than
2,200mm [1].
 Abundant seepage from the Makinohara gravelly
layers. After daily rainfall events with more than
100mm, groundwater seepage typically lasts for a
few days in tea plantation fields and a few weeks
along cliffs [10].
 Adverse geological structural setting. The
regional geology tends to dip to southeast, thus
bedding is dipping out on slopes facing between
the east to the south.
When earth removal or buttress fill is selected asa slope mitigation measure, the author considers thatthe following slightly conservative slope angles areappropriate in this region:
 Cut Slope = 1:1.5 (V:H) or flatter for moderately
weathered or better siltstones
 Fill Slope = 1:2.0 (V:H) or flatter
It is also prudent to apply surface protection evento the temporary slopes in order to minimise
exposure of the cut surface. It is evident that manycut slope failures in this region occur following thefirst heavy rainfall event after slope construction.
When buttress fill is adopted, it is important not
to use failed materials as buttress fill materials since

Photo 3 Damage to Temporary Slope Mitigation
Works Prior to Permanent Works
SELECTION OF MITIGATION MEASURES
Fig. 3 shows the commonly used landslide
mitigation measures in Japan. They consist oflandslide control measures and landslide restraint85

GEOMATE-Nagoya, Nov.13-15, 2013

surface water tend to concentrate around theseimpermeable materials and causes further instabilityof the slope.
It is noted that earthworks which will beaffecting existing tea plantation fields are often
considered inappropriate by landholders andgovernmental administration bodies since tea
farming is a very important source of income in thisregion. In such a case, more rigorous mitigation
measures (e.g., anchors) need to be considered.

350

30

300

25

250

20
200
15
150
10

100
5

50
0

on

1:1.0

Ave. Monthly
Rainfall
Ave. Monthly
Temperature

0
1

Photo 4 Erosion occurring
Temporary Cut Slope

Ave. Monthly Temperature (Degree C)

Ave. Monthly Rainfall (mm)groundwater control measures, it is essential to carryout detailed investigations to identify thegroundwater table relative to the slip surface. In
addition, the groundwater logging test is useful todetermine the groundwater flow so that drains canbe installed at locations where the groundwater flow
is fast (i.e., the permeability is high).
In cases where the site is located within or
adjacent to the tea plantation fields, it is important
not to drain groundwater completely so that theyremain suitable as tea plantation fields.

2

3

4

5

6

7

8

9 10 11 12

Month

(V:H)

Fig. 3 Rainfall and Temperature of Makinohara City
(after [1])GROUNDWATER CONTROLThe tea plants grow well in areas with yearly
rainfall of more than 1,400 mm [11]. While rainfall
is essential to the growth of tea plants, there are anumber of sediment related disasters due to heavy
rainfall events.
In particular in this region, the steady seepage
flow is located around RL 170m to RL190m. Even if
the groundwater level is low during the dry season,
the rise of groundwater could be significant
following long intensive rainfall events. The
research conducted by [10] also revealed that thevolume of seepage fluctuates significantly at higher
RL. Therefore groundwater control is one of the key
slope mitigation measures in this region.
According to manuals commonly used in Japan(e.g., [9], [12] and [13]), the planned groundwaterlevel (PWL), which is the groundwater level taking
into account effects of groundwater control
measures, is often set lower than HWL, i.e. 3m(gravity drains) and 5m (drainage wells). Whilelowering groundwater to the PWL in gravelly layers
is usually achievable, the response of groundwater insiltstones is often not fast enough to lower the
groundwater due to their relatively low permeability.
As a result, an increase of FOS by thesegroundwater control measures could be much lessthan 3% when they are installed in siltstones.
In order to maximise effects of these

Photo 5 Horizontal Gravity Drains Installed on
Temporary Cut Slope
ANCHORS
Anchors are often required for both temporary
and permanent works in Japan. In the Makinohara
region, tensioned anchors are preferable tocompression anchors for weathered siltstones
because: The extent of anchor forces acting along thetendon is greater in the tension type than in thecompression type for rocks consisting of fineparticles (e.g., siltstone) [14].
 The compression type tends to create the stressconcentration at the bottom of the anchor [15].
The design of anchors in this region is often
based on the circumferential skin friction (τ) of 0.6
MN/m2, which is the smallest τ value for weatheredrocks in accordance with [16]. However many casestudies revealed that the actual τ value could be86

GEOMATE-Nagoya, Nov.13-15, 2013

potentially smaller than this value in this region.
Therefore it is strongly desirable to confirm the τvalue by anchor pullout tests.

Photo 7 Photograph of Anchor Bearing Plate
Indicating Creep Movement of Slope
CONCLUSION
2Photo 6 Pullout Test Revealed τ = 0.5 MN/m for a
Project in the Makinohara Region

In this paper, characteristics of slope failures in
the Makinohara region are described. Based on theauthor’s experience in this region, various
recommendations are made for slope mitigation
works. From a series of studies, the following
conclusions can be drawn:
 Slope failures are often triggered by earthworks
excavations. These failures can be broadlyclassified into the weathered rock type and theclayey soil type.
 Due to various adverse conditions and the low
design FOS commonly used in Japan, a slightly
conservative approach (e.g., conservative slope
angle) is required particularly during temporary
works in this region.
 Protection of the slope surface and the control ofgroundwater and surface water are key to themitigation of slope instability since siltstones
show strong slaking phenomenon in this region.
 The τ value could be smaller than the commonly
adopted design value in this region, andperforming anchor pullout tests is highly desirable.
Re-tensioning of anchors is also often required
and therefore an initial tensioning toapproximately 80% or less of design anchor load
is usually considered appropriate.

Due to the potentially low τ values, additionalanchors may be required in this region in order toachieve the design FOS. A larger anchor bearing
plate is also often necessary due to the low bearing
capacity. Meanwhile increasing the number ofanchors and using a larger anchor bearing plateallows restraint to a wider area of the slope surface,resulting in a reduction of the risk of surface erosion.
In addition to these measures, providing surface
protection and appropriate drainage systems (e.g.,
shotcrete and gravity drains / weepholes) is also
highly desirable.
In this region, installation of anchors ispreferably undertaken in the dry season. The
following steps are also recommended for anchor
installation:
 Undertake excavation and anchor installation instages from top down.
 Install anchors as soon as the slope is trimmed inorder to minimise the unsupported period.
 Fabrication of the precast anchor bearing plate ina factory prior to anchor installation to minimize
the lead time associated with acquisition of theanchor bearing plate.
After initial tensioning, anchor bearing plates
occasionally settle in this region. Slopes also often
show creep movement and the anchor lift off stresscould be much lower than the design stress. Taking
into account these facts, re-tensioning of anchors isoften required and therefore an initial tensioning toapproximately 80% or less of design anchor load isusually considered appropriate.

ACKNOWLEDGEMENTS
Valuable comments were made by Makinohara
City Hall, Aya Green Tea and David Starr during the
preparation of this paper and I am most grateful tothem for their suggestions.
REFERENCES[1] Makinohara City, “Makinohara City Gaikyo”,
2012, http://www.city.makinohara.shizuoka.jp/
ftp/05gt04/1_gaikyou.pdf (in Japanese)87GEOMATE-Nagoya, Nov.13-15, 2013[2] Sugawara J, “Landslides in Tea Plantation
Fields in Shizuoka, Japan”, Int. J. of
GEOMATE, Vol. 4, No. 1 (Sl. No. 7), March,
2013, pp. 495-500.
[3] Google Map, http://maps.google.co.jp/, 2013[4] Shizuoka Prefecture, “Shizuoka Geological
Map”,
2013,
http://www.shimizu-arc.jp/
images/sumaino/geology/geologymapwest.pdf(in Japanese)[5] Japanese Geology Chubu Region Editors,“Japanese Geology (4) Chubu Region I”, 1988
(in Japanese)[6] Makinohara City, Personal Communication,
2013[7] Watari M. and Kobashi S, “Prediction and
Mitigation of Landslides and Slope Failures”,
Sankaido, 1987 (in Japanese)[8] Japan Landslide Society and National
Conference of Landslide Control, “Landslides
in Japan (The Sixth Revision)”, Japan LandslideSociety and National Conference of Landslide
Control, 2002, pp.30[9] Japan River Association, “Manual for River
Works in Japan: Investigation”, Sankaido, 1997
(in Japanese)[10] National Agriculture and Food Research
Organisation, 2002, http://www.naro.affrc.go.jp/
project/results/laboratory/vegetea/2002/vegetea
02-42.html (in Japanese)[11] Rural Cultural Association, “Cha-Daihyakka”,
vol. 1, Rural Cultural Association, 2008, pp.
269 – 302. (in Japanese)[12] Japan Construction Engineers Association,“Saigai Techou”, 2006, pp. 361. (in Japanese)[13] Japan Road Association, “Guidelines for Slope
Stabilization Works and Slope Stability”, Japan
Road Association, 1999 (in Japanese)[14] Sung CH, Bo JL, Wei H, and Juir RL,“Modeling of Anchors in Gravel Formation
Using Discrete Element Method”, Advanced
Materials Research, Vols. 189 – 193, 2011, pp.
1726 – 1731.
[15] Institute of Slope Technology, PersonalCommunication, 2006[16] Japanese Geotechnical Society, “Manual for
Design and Construction of Ground Anchors”,
Japanese Geotechnical Society, 2000 (inJapanese)88Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

S-PSA WITH USING FEM FOR AN EXISTING ESTUARY DAM
T. Hara1, M. Iwata1, Y. Otake1, Y. Honjo1, T. Kato2, A. Nishida2 and H. Yukimoto2
Department of Civil Engineering, Gifu University, Japan; 2 Japan Water Agency, Japan

1

ABSTRACTThis paper presents an example of S-PSA, Seismic Probabilistic Safety Assessment, applied to seismic
verification of an existing estuary dam. Dynamic effective stress FEM analysis was adopted in this S-PSA, inorder to estimate the seismic response of the target structure built on liquefiable ground during earthquake. In
this paper, details of S-PSA with using FEM is introduced, and seismic safety and seismic retrofit necessity are
discussed from both results of severe damage occurrence probabilities in respective parts constituting the dam
and probabilistic damage curves of the parts corresponding to increscent seismic intensity.
Keywords: S-PSA, FEM, Probabilistic seismic hazard, Damage occurrence probability, Existing structure

INTRODUCTIONTARGET STRUCTURE

Seismic design with considering occurrence
probability of larger earthquake than the design one
has been an important issue in Japan, because
several large earthquakes caused tremendous
damages to human and social economy, such as
Kobe quake in 1995 and Tohoku quake in 2011.
Therefore, the authors have conducted a study on
application of S-PSA, Seismic Probabilistic Safety
Assessment [1], [2], to common infrastructures
except nuclear plant. In this paper, an example of SPSA applied to seismic verification of an existing
estuary dam is presented. Effective stress dynamic
FEM analysis is adopted in this S-PSA, in order toestimate the seismic response of the dam built onliquefiable ground during earthquake, by using
response surface method [3]. And following
uncertainties are considered in the reliability
analysis.
Response uncertainties: Earthquake intensity
based on probabilistic seismic hazard curve at thesite, reproducibility of the FEM analysis adopted inthis study with respect to experimental responses ofthe structure built on liquefied ground, andreproducibility of the assumed response surface withrespect to the seismic responses estimated by FEM
analysis.
Resistance uncertainties: Strength estimation of
the structural members and bearing capacity of pilefoundation, and spatial variation and transformation
error of geotechnical parameters.
In this paper, details of S-PSA with using FEM is
introduced, and seismic safety and seismic retrofit
necessity are discussed from both results of severe
damage occurrence probabilities in respective parts
constituting the dam and probabilistic damage
curves of the parts corresponding to increscentseismic intensity.

The target facility is an existing estuary dam tosupply city, industrial and agricultural water due toprevent running up of seawater to the river. The
facility length is 192.3m and it consists of six gates(25m in width, 7.3m in height) and seven hanging up
structures of the gates. Fig.1 shows the external
appearance of the dam. The target structure in thisstudy is the hanging up structures of the gates. This
structure is built on the liquefiable ground during
earthquake with steel pipe pile foundation (φ600, t =9mm, l = 25m, n = 35).

Fig. 1

External appearance of the target dam.

PROCEDURE FOR S-PSA
Fig.2 shows the procedure for the S-PSA in thisstudy. At first, the uncertainty of seismic intensity is
set as a probabilistic density function from thepublished probabilistic seismic hazard curve at thesite, which corresponds to residual service term of
the target facility. And then, response surfaces (RS)of respective verification points are estimated fromsensitivity analyses with respect to contribution
factors to each response of the points. At last,damage occurrence probabilities and probabilistic
damage curves of the verification points are89

GEOMATE-Nagoya, Nov.13-15, 2013

estimated by Monte Carlo Simulation (MCS) withboth uncertainties of response and resistance. And
safety verification is conducted from both thecomparison with allowable damage occurrence
probability determined by one of recently built
similar structures, and the probabilistic damage
curve in the extent close to predictable large
earthquake level.

The probabilistic seismic hazard curve
corresponding to 30 and 50 years term at the target
site (J-SHIS, 2010) is shown in Fig.3. And Fig.4 andTable 1 present the probabilistic density function,
the uncertainty of seismic intensity at the site, whichis assumed from the hazard curve.

Fig. 4

Uncertainty of seismic intensity.

Table 1 Uncertainty of seismic intensity

Fig. 2

Designterm
30-years
50-years

Procedure for S-PSA.

Mean(cm/s)
34.9
42.6

SD
(cm/s)
19.4
20.2

Distribution
Lognormal
Lognormal

UNCERTAINTY OF SEISMIC INTENSITY
Basically seismic wave
Uncertainty of Seismic Intensity
Fig.5 shows the basically seismic wave [4]adopted in this study. The seismic effect in thisstudy is considered from the basically seismic wave
calibrated by the uncertainty of seismic intensity.

Residual service term of the target facility, “30years”, is determined as a basic term though, “50years” is also considered in this study from a
concern of the safety in case that the term is
postponed.

(a) Acceleration wave.

(b) Velocity wave.
Fig. 3

Probabilistic seismic hazard curve.

Fig. 590

Basically seismic wave.

GEOMATE-Nagoya, Nov.13-15, 2013

Table 2 Ground condition

RESPONSE SURFACE (RS) ESTIMATION
Response Estimation Method
Effective stress dynamic FEM analysis, FLIP
(Ver. 6.0.6), is adopted in this study, in order toevaluate the seismic response of the dam built onliquefiable ground during earthquake, by using
response surface method [3]. Fig.6 shows the FEM
mesh of both river axis cross section and dam axis
one. Ground condition of top three strata ispresented on Table 2 and A s2 stratum is theliquefiable ground during earthquake.

A s2
A c3
A s3

70.0m

1:2
1:2

1:11:1Model Test

154.8ma

9.5m 8.5m

14.8m

As2

0.5:
0.5:1

0.0
0.0 0.5
0.5 1.0
1.0 1.5
1.5 2.0
2.0 2.5
2.5 3.0
3.0
FEM analysis
40.0m

Ac3-1

SPT-N value
Mean
SD
15.2
4.4
12.4
3.0
33.4
10.4

The uncertainty of the FEM reproducibility withrespect to the experimental responses of structure
built on liquefied ground during earthquake, whichwere obtained from blind tests [5], is shown in Fig.7.
Because of blind test, the transformation error of thegeotechnical parameters used in the FEM is includedin the uncertainty. Although the reproducibility of
the FEM was obtained from analyzed ones withrespect to experimental data of river dike, it wasreferred as one to estimate response of piled
structure in this study.
Model test
0.0 0.5
0.5 1.0
1.0 1.5
1.5 2.0
2.0 2.5
2.5 3.0
3.0
0.0

70.0m

Thickness
(m)
14.5
7.0
10.0

(a) Comparison of experiments and analyzed
structural displacement.
44

As3-1

n= 13
mean= 1.11
sd= 0.33

Probabilistic density
11
22
33

Ac3-2
As3-2

Number = 13
Mean = 1.11
Standard deviation = 0.33

DensityLognormal distribution

00(a) River axis cross section.

0.0
0.0

0.5
1.0
1.5
2.0
0.5
1.0
1.5
2.0
Model test / FEM analysis

2.5
2.5

(b) FEM reproducibility with respect toexperimental response.
Fig. 7

Uncertainty of FEM reproducibility.

Verification Points
A lot points have to be verified in normal seismic
design though, in this study, the minimum
verification points, which possess the possibility thatthe response corresponding to increscent seismic
intensity exceeds the limit state, are selected fromsensitivity analyses of responses at each point. The
selected verification points are presented on Table 3(b) Dam axis cross section.
Fig. 6

FEM mesh.

91

GEOMATE-Nagoya, Nov.13-15, 2013

T = 1.2985 ⋅ Vm + 559.95

Table 3 Verification points

Gate Pier

Curvature
Shear force

Dam Pier
Pile
Displacement
Entirely structural inclination

Verification axis
River
Dam
VerifyN/A
VerifyVerifyN/A
N/A
VerifyVerifyVerifyVerify(1)where, T = maximum shear force of gate pier(kN), V m = maximum velocity of seismic wave
(cm/s)
LIMIT STATE UNCERTAINTY
The uncertainty of shear strength is presented on
Table 4, which was referred from the existing
research on the reproducibility of the shear strength
estimated by Eq. (2)-(4) with respect to experimental
ones [6].

In this paper, because of paper limitation, safetyassessments of gate pier shear force in the dam axis
cross section with respect to 30-years term are only
introduced.

Table 4 Model error of shear strength estimation
Response Surface
Mean
1.93

It was confirmed that the uncertainty of seismic
intensity is only influential one to the response of therespective verification points from sensitivity
analyses with respect to uncertainties of seismic
intensity,
groundcondition,
deformation
characteristic of gate pier and pile. Therefore,
response surfaces (RSs) focused on only seismic
intensity are estimated. Equation (1) and Figure 8
show RS of gate pier shear force in the dam axis
cross section and its uncertainty of reproducibility
with respect to the responses estimated by FEM
analyses.

Probabilistic density
10
15
55
10
15
2020

(2)

Sc = c c ⋅ c e ⋅ c pt ⋅ τ c ⋅ b ⋅ d(3)

A w ⋅ σ sy ⋅ d ⋅ (sin θ + cos θ)
1.15 ⋅ α(4)where, P s = shear strength of reinforced concrete
structure (N), S c = shear strength boar by concrete(N), S s = shear strength boar by reinforcing bar (N),c c , c e and c pt = compensation coefficientsconcerning cyclic loading action, effective height ofthe section (d) and, ratio of axial tensile reinforcing
bars’ area and sectional one, τ c = mean shear stressboar by concrete (N/mm2), b = section width (mm),A w = area of shear reinforcing bars (mm2), σ sy =yield strength of shear reinforcing bar (N/mm2), θ =angle of shear reinforcing bar and vertical axis (deg),
α = pitch of reinforcing bars (mm).
DAMAGE OCCURRENCE PROBABILITY
AND PROBABILISTIC DAMAGE CURVE
Damage occurrence probability and probabilistic
damage curve are estimated by MCS with one
millionruns
withconsideringrespective
uncertainties.

Mean = 1.0
Standard
deviation = 0.038
平均=1.0
標準偏差 =0

Damage Occurrence probability

Normal distribution

00

Equation (5) expresses the performance function.
And the shear collapse occurrence probability ofgate column (dam axis) for 30-year term, 0.27%, isshown in Fig.9

0.95
1.00
1.05
0.95
1.00
1.05
FEM analysis / RS

1.10
1.10

(b) Uncertainty of RS.
Fig. 8Distribution
NormalPs = Sc + Ss

Ss =(a) Estimation of RS.

0.90
0.90

SD
0.273

1.2985 ⋅ δ v ⋅ Vm  ⋅ δ FEM ⋅ δ RS ≥ 0
g = δ T ⋅ T − 
 + 559.95
RS of maximum shear force of gate pier.

92

(5)

GEOMATE-Nagoya, Nov.13-15, 2013

where, δ T , δ V , δ FEM , and δ RS = random variablesof shear strength (kN), maximum seismic velocity(cm/s), FEM reproducibility and RS reproducibility,
presented on Table 5.

the Tables, the values noted in the brackets are thedamage probability in 50-year term. According to
the results, shear collapse occurrence probability of
the gate column in dam axis cross section is only notsatisfied the allowable one

Table 5 Random variables for estimation of shear
collapse occurrence probability (30 years)
δT
δV
δ FEM
δ RS

Mean
1.93
37.6
1.11
1.0

SD
0.27
19.4
0.33
0.038

Table 6 Allowable damage probability

Distribution
NormalLognormal
Lognormal
NormalGatecolumnPile
Incline

Flex.
Shear

Allowable probability (%)
Probabilistic Deterministic
earthquake
earthquake
0.15
1.5
0.15
1.0
0.35
7.5
0.15
1.5

Table 7 Safety verification, dam axis, 30 (50) years

Fig. 9

Shear collapseof gate column
Group pile
displacement
Residual
inclineShear collapse occurrence probability.

NG
OK
OK

Table 8 Safety verification, river axis, 30 (50) years

Probabilistic Damage Curve
Equation (6) expresses the performance function.
And the probabilistic shear collapse curve of gatecolumn (dam axis) corresponding to increscentdeterministic seismic intensity is shown in Fig.10
together with other results of respective verification
points.
g = δ T ⋅ T − Re s T ⋅ δ FEM ≥ 0

Damage probability (%)
Estimated
Allowable
0.27
0.15(0.29)
2.7E-30.35(3.1E-3)< 1.0E-4
0.15(< 1.0E-4)

Flex. collapseof gate column
Shear collapseof gate column
Group pile
displacement
Residual
incline(6)

where, Res T = shear force occurring in the gatecolumn estimated by FEM with respect to eachdeterministic seismic intensity. And randomvariables are the same as ones presented on Table 5.

Damage probability (%)
Estimated
Allowable
1.0E-40.15(2.0E-4)
7.7E-30.15(0.01)
7.0E-40.35(9.0E-4)
1.0E-40.15(1.0E-4)

OK
OK
OK
OK

Safety verification with respect to probabilistic
damage curve (deterministic earthquake)
Fig.10 shows normalized probabilistic damage
curves by allowable probabilities (deterministic
earthquake) of respective verification points in dam
axis. In this figure, the intensity of Nankai-troughearthquake [10] that the occurrence is predicted in
the near future is also presented.
According to the results, it can be confirmed thatshear collapse occurrence probability of gate column
in dam axis, which is judged as NG in the safety
verification with respect to probabilistic earthquake,rises sharply at the point exceeded the seismic
intensity of Nankai-trough earthquake. Namely, thedangerous of the gate column is also confirmed insafety verification with respect to probabilistic
damage curve from viewpoint of seismic intensity
uncertainty.

SAFETY VERIFICATION
Allowance damage occurrence probability
Damage occurrence probability of the recently
built similar structures [7]-[9] is referred to specify
the allowable ones for the target facility in this study.
Table 6 presents the allowance damage probabilities.
Safety verification with respect to probabilistic
earthquake
The comparison of the allowable damage
occurrence probabilities and estimated ones of all
verification points in this study on Table 7 and 8. In

93

GEOMATE-Nagoya, Nov.13-15, 2013

Nankai-trough earthquake

Pile
displacement

1.0
0.8
0.2

0.4

0.6

/受容損傷確率

Shear force ofgate column

Entireinclination

0.0

Probability (estimated / allowable)

1.2

wave on engineering basement (Vs = 400 m/s):
www.bousai.go.jp/jishin/chubou/. html.
[5] Japan Institute of Construction Engineering(JICE). 2002. Analysis method of seismic riverdike deformation: JICE Document, Vol. 102001.
[6] Watanabe, H., Koga, H. & Nakamura, H. 2007.
A study on installation of International standardof design on concrete structure: Report ofgeneral research by government subsidy.
[7] Osumi, M., Unjo, S., Adachi, S. & Hoshikuma J.
2000. A study on seismic reliability evaluationof highway bridges: proc. of the 4th symp. on
seismic design based on ductility design method
for bridges: 13-16.
[8] Unjo, S. & Zhang, K. 2009. A study on partial
factor design for highway bridge seismic
design: Report of road development research by
government subsidy.
[9] Nakatani, S., Shirato, M., Kono, T., Nakamura,Y., Nomura, T., Yokomaku, K. & Iochi, H.
2009. A study on stability verification methodof bridge foundation based on performancebased design concept: Technical Note of Public
Works Research Institute (PWRI), No.4136.
[10] Cabinet Office, Government of Japan (COGJ).
2012. Nankai-trough seismic (acceleration)
wave on engineering basement (Vs = 350-700m/s):
www.bousai.go.jp/jishin/chubou/nankai_trough/data_teikyou. html.

0

50

100

150

200

250

300

Maximum velocity (cm/s)

Fig. 10 Probabilistic damage curve (dam axis).

CONCLUSIONS
A concrete example of S-PSA application withusing FEM analysis to an existing facility was
introduced in this paper. This paper can beconcluded as follows;a) Application of S-PSA to common
infrastructure is not so difficult.
b) S-PSA with using FEM is possible byresponse surface method.
c) Both damage occurrence probability andprobabilistic damage curve are available for safetyassessment.
Furthermore, if the damage probability isexpressed as risk with considering damage cost, it
can be expected that this approach apply to making
priority decision for seismic retrofit of multiple
facilities despite building region and structural typeand so on. The authors recommend to apply S-PSA
to common infrastructures from the viewpoints ofaccountability to public and reasonable use oflimited public investment to seismic retrofit.
REFERENCES[1] International Atomic Energy Agency (IAEA).
1993. Probabilistic safety assessment forseismic events.
[2] International Atomic Energy Agency (IAEA).
2009. Evaluation of seismic safety for existing
nuclear installations.
[3] Honjo, Y. 2011. Challenges in geotechnicalreliability based design: Proc. of the 3rd intern.
symp. on Geotechnical Safety and Risk, 11-27,
Munich,
2-3
June
2011.
Germany:
Bundesanstalt fur Wasserbau.
[4] Cabinet Office, Government of Japan (COGJ).
2006. Tonankai-Nankai seismic (acceleration)

94

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

THE ROTATIONAL HARDENING RULEWITHOUT THE LIMIT SURFACE OF HARDENING
Hiroyuki Kyokawa1, Ryoki Ohashi2 and Teruo Nakai3
Institute of industrial science, University of Tokyo, Japan; 2Nagoya city office, Japan; 3Nagoya Institute ofTechnology, Japan

1

ABSTRACTThe rotational hardening rule has been used for describing the induced anisotropy of the geo-materials,
especially the Bauschinger effect, in a constitutive modeling. Some of the evolution rules of the back stress ratio
tensor indicating the center axis of the yield surface have also been proposed. In a lot of those evolution rules,
the back stress ratio tensor shifts with the plastic deformation, and the limit surface of hardening is required tosatisfy the appropriate failure condition. However, the physical meaning of the limit surface and its transition
due to some properties of soil seem to be not clear. Fully new evolution rule of the back stress ratio tensor is
proposed in this study. The proposed method, which distinctly considers the development of the stress history
during non-monotonic loading path, and its decay with plastic deformation, can suitably address the complicatedstrength and deformation characteristics of soil due to stress history without the limit surface.
Keywords: Constitutive model, Soil, Elastoplasticity, Rotational hardening rule, Stress induced anisotropy
given is not clear. In addition, the size of the limit
surface is basically a constant determined by amaterial parameter. Since the (peak) strength of soil
is fairly changeable due to the influences of somemechanical factors (e.g. density, cementation,
temperature, suction and others), it is natural that thesize of the limit surface of hardening is not constantbut changes under the influence of some factors aswith the strength. It would be, however, quite
complicated to change the size of the limit surface ofhardening taking every factor into consideration.
A new rotational hardening rule, in which theyield surface is shifted faithfully reflecting on the
stress history, is developed in this study. The backstress ratio develops when the stress path deviate
from the monotonic loading path, i.e., the stresshistory occurs, in the proposed method. It would be,therefore, a rational method that the proposed modelshows different behavior from the original model
without the rotational hardening only when soil has
the stress history. By describing not only thedevelopment of the stress history but also its
dissipation, the proposed method can appropriately
describe the failure state without the limit surface ofhardening.
The proposed rotational hardening rule is applied
to subloading tij model [1] considering the influenceof the relative magnitude of the intermediate stress,
thus the proposed rotational and isotropic hardening
model describes the influence of the intermediate
stress and the stress history simultaneously. In thispaper, the outline of the proposed rotational
hardening rule and the formulation of the proposed

INTRODUCTION
Soil shows a complicated anisotropic behavior
due to the stress history. For instance, in thereloading shear process, the shear stiffness is larger
than that of virgin shear. Conversely, since the yieldstrength decreases when the direction of loading ischanged, the shear stiffness becomes lower in thereverse loading process. This sort of property inreverse loading is, particularly, well known as the
Bauschinger effect. These mechanical characteristics
of soil due to the stress history are, moreover,collectively called as “thestress induced
anisotropy”. The stress induced anisotropy is
considerable feature for the failure and deformation
prediction of ground and earth structure, and should
be properly considered in a constitutive model ofsoils.
In order to represent the soils induced anisotropy,
the rotational hardening rule, in which the yieldsurface and/or the plastic potential is rotated by theback stress ratio tensor, namely the center axis ofsurface, has been used in the ordinary model. In
addition, some evolution rule of the back stress ratio
has also been proposed, and most it is continuously
rotated with the plastic deformation. The monotonic
shear behavior of the rotational hardening model is,therefore, different from that of the original model
without rotational hardening. Furthermore, the limit
surface of hardening indicating the motion space ofthe back stress ratio is required to satisfy theprescribed failure state. It seems, however, that thephysical meaning of the limit surface arbitrarily95

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Comparison of stress and strain increment
parameters in ordinary stress ij and tij concept
ordinary concepttransform tensor tomodified stress-q

tij concept
aij  I 3 I 2 rij1rik rkj   ij unit tensor normal to ij (Oct. plane)reference plane ijstress tensorp   ij ij / 3
mean stressdeviatoric stress tensor sij   ij  p ij
deviatoric stressX   xij  bij

3 2sij sij

d , d 

N


S

aij (SMP)

tij  aik kj
t N  tij aij
t ij  t ij  t N aijt S  tij tij

stress ratio q pX  tS t N
strain increment normal d  d 
d N  d ij aijv
ij ij
to reference plane
deviatoric strain
deij  d ij  d v ij 3 d ij  d ij  d N aij
increment tensor
strain increment paralleld d  2 3deij deij d S  d ij d ij
to reference plane

Fig. 1 Yield surface based on the rotational hardeningX   xij  nijYM   X 
X  1

 Y   d N d Smodel are presented, and the proposed model isverified by comparison with the experimental resultsof triaxial test and isotropic compression test on
medium dense Toyoura sand.

Fig. 2 Relation between stress ratio and dilatancy
describe anisotropic behavior of soils. Among them,
Sekiguchi and Ohta model [5], in which the yieldsurface is oriented around the origin of ordinarystress space for describing the anisotropic behavior
of initially K0-overconsolidated soil, is a simple
extension of the original Cam clay model and has
been commonly used in practice. However, thismodel cannot represent the induced anisotropy, since
the oriented yield surface is not mobilizing with any
stress change which means that the anisotropy is
persistent like the inherent anisotropy in this model.
On the other hand, Hashiguchi [6] proposed therotational hardening and its evolution rule byextending the concept of Sekiguchi and Ohta model.
Hashiguchi and Chen [7] developed the rotational
and isotropic hardening model with subloading
surface [8]. The proposed rotational and isotropic
hardening model based on the tij concept isformulated in the track of those models.

THE MODIFIED STRESS tij CONCEPT
In most of isotropic hardening models such as
Cam clay model [2], their yield functions areformulated using parameters of Cauchy stress tensor
ij and the flow rule is given in ij-space. Suchmodels, however, cannot describe the strength andthe deformation of soils under three-dimensional
stresses in a uniform manner. Nakai & Mihara
proposed a method, in which the yield function isformulated using the parameters of the modified
stress tij (= aikkj) and the flow rule is assumed in tij
space [3]. This method can suitably consider the
influence of the intermediate principal stress by theparameters of stress and strain increments based on
the spacially mobilized plane: SMP [4] listed inTable 1. Only by replacing the ordinal stress andstrain parameters of the ordinary model with thecorresponding parameters of tij concept, the ordinarymodel can be automatically extended to consider the
influence of the relative magnitude of theintermediate stress.
Although the proposed rotational hardening ruleand constitutive model are explained and formulated
by using the modified stress tij in this study, it ispossible to apply the concept to models based on the
Cauchy stress tensor ij just by replacing tij with ij.

The Rotational and Isotropic Hardening
Constitutive Model Based on tij Concept
In this paper, a rotational hardening model is
proposed and it applied to the isotropic hardening
model named subloading tij model which considers
not only the influence of the intermediate stress by
the modified stress tij concept, and the influence ofdensity and/or confining pressure by using theconcept of subloading surface [8]. Since the detailsof the original model are explained in another paper[1], the application of the proposed rotational
hardening rule is mainly presented here.
The yield function of soil is formulated as alogarithmic function of the mean stress plus an

THE ROTATIONAL AND ISOTROPICHARDENING MODEL WITHOUT THE LIMITSURFACE OF HARDENING
Various models adopt different approaches to96GEOMATE-Nagoya, Nov.13-15, 2013

 ln





tN
t
t
1X 
  ln N 1e  ln N 1e  0 t N 0   M  
tN 0
tN1


X' = const

X   xij

(1)

k=0

(monotonic loading)dx'ij

k = cos( / 2)

x'1
b'ij
x'3

Schematic yield surface on tN - tS plane is shown in
Fig. 1. X * is the modified stress ratio, and given as
follows using the back stress ratio tensor bij.
X   xij xij where xij  xij  bij

*

k



x ij (current stress)xxij  xij  kk  ij3bkk
bij  bij  ij
3xij  xij  bij(u = 1
nlo
ad
ing
)

increasing function of the stress ratio in the originalCam clay model [1]. Similarly, considering an
orientation of the yield surface, the yield function of
the proposed rotational and isotropic hardening
model based on subloading tij model is presented asf  ln t N   X  , M   ln t N 1  0

k=

co
s

(4
5

°)

x'2
x'ij-space

Fig. 3 Judgment of loading condition by stress ratio
tensor and its increment in x'ij sape(2)

where  is a material parameter which determines
the shape of the yield surface. M * is a vertex of thenonrotating (original) yield surface, and composedof the principal stress ratio at the critical state intriaxial compression RCS = (1/3)CS. The stressdilatancy relation is illustrated in Fig.2. tN1 and tN1e
are the value of tN at X * = 0 of the subloading surface
on which the current stress state always exist, andthe normal yield surface. Defining tN1e as theisotropic hardening parameter and tN10 is its initialvalue, the third term in right side of Eq. (1) is linked
with the plastic volumetric strain and is fiven ast
1  e0 p
ln N 1e v(3)tN 0   
Similarly, the forth term in right side of Eq. (1) is afunction of the density parameter , which
represents the distance between void ratio on thenormally consolidated line and the current void ratio
under tN1 and is given ast
ln N 1e (4)
tN1   
Additionally, the following function is assumed as
the evolution rule of the density parameter .
a 2d    1  e0 
(5)tNFinally, Eq. (1) is rewritten as

strength and deformation characteristics of soils are
independent of the stress histories at the failure stateeven if soils had the complex stress path histories [9].
The essentials of the evolution rule of bij aresummarized as follows.
(a) bij is equal to zero during monotonic loading
paths, and the stress history develops (dbij ≠ 0)
when stress path derivate from monotonic
loading path (non-monotonic loading path).
(b) The stress history: bij develops in the directionof the current stress state: xij*(= xij - bij) withchange in stress ratio: dxij.
(c) The stress history decays with progress of theplastic deformation (bij → 0 with dijp ), andcompletely disappears at failure state evenundergoing complex loading history (bij = 0 at
failure state).
An evolution rule of bij which satisfies all of theabove conditions is given as
dbij  kxij  lbij  (8) n   xij  ijxij 
First term of right side in Eq. (8) represents thedevelopment of the stress history, and is composedof the direction: nij*, the magnitude of development:nkl*dxkl ( is a newly added material parameter),and the loading judgment, namely, monotonic
loading (cos(/2) = 0), non-monotonic loading (0 <cos(/2) < 1), and unloading (cos(/2) = 1).  isgiven as follows and a schematic view of the loading
judgment is shown in Fig. 3.
 b   x    dx  

ij 
(9)
  cos 1  ij ij bij  xij  dxij    cos  nkl dxkl nij   d klp bij
2






1  X 
1  p
tN
 
0
  v (6)    
1  e0 
tN 0   M 
Cp 
Here, Cp indicates (-)/(1+e0). The plastic strain
increment is obtained by assuming the associatedflow rule in tij-space asf (tij , bij )d ijp  (7)
tijf  ln

The Evolution Rule of the Back Stress Ratio bijNote that new parameter xij' and its space are usedhere to consider every stress state on the samereference plane, since the reference plane of tij
concept whose normal is aij changes continuouslywith stress state.
Conversely, second term of right side in Eq. (8)The evolution rule of the back stress ratio tensor
is bij determined reflecting on the following
experimental evidences. (a) Soil shows complicatedanisotropic behavior due to the stress history only
when non-monotonic loading is applied, (b) The
97

GEOMATE-Nagoya, Nov.13-15, 2013

Table 2 Constitutive parameters for Toyoura sandSubloading
surfacexij (current stress)
dxij

Decay
(with d p)x1
x3

x*ij = xij - bij

in the same manner as the original model, the details
are handed over to reference [1].

bij
dbij

RESULT AND DISCUSSIONx2

In this section, the feature of the proposedrotational and isotropic hardening model describing
the influence of the intermediate principal stress andthe stress history simultaneously is verified by thecomparison of the calculated results with theexperimental results of triaxial tests and isotropic
compression test with non-monotonic loading pathon medium dense Toyoura sand (emax = 0.95, emin =0.58, Gs = 2.65, Dr = 72 %). The material parametersof the proposed model are listed in Table 2.  and 
are newly added to the material parameters oforiginal model for controlling the development anddecay rate of the stress history respectively. Other
parameter values are the same as those of theoriginal subloading tij model for Toyoura sand.
These parameters can be determined from isotropic
compression and triaxial compression test.

xij-space

Fig. 4 Evolutions of the back stress ratio when theinfluence of the stress history develops and decays
indicates the decay of the stress history, which isrepresented as bij going to zero with the plastic
deformation. l is proportional to the magnitude of
the plastic strain increment, while  is also a newly
added material parameter controlling the rate of the
decay of the influence of stress history. Figure 4
illustrates the evolution of the back stress ratio when
the stress history develops and decays respectively.
Stress and Strain Relation

The proportionality constant  representing themagnitude of the plastic strain increment in Eq. (7)is obtained by solving Prager’s consistency equation(df = 0).



 f
  f    xkl     cos 
nmn nkld  ij   ij
2  bmn  ija 2 
f
f
1  fbij
C p  tkk
t N 
bij
tkl

Triaxial Tests – Reverse Loading and Reloading

Figure 5 presents the non-monotonic loading
paths of triaxial test, namely, reverse loading(ABCD) and reloading (ABCE). Fig. 6, 7 and 8
show the observed results, the computed results by
the original isotropic hardening model, and those by
the proposed rotational and isotropic hardening
model, respectively. The monotonic shear behavior
is also indicated in each figure for comparison.
Diagram (a) and (b) indicate the relation between
axial strain and stress ratio, and the relation between
stress ratio and volumetric strain, respectively.
It can be observed from these figures that, during
triaxial compression test (path A→B), the results ofthe proposed model coincide with those of theoriginal model, and both agree well with theexperimental result though the volumetriccontraction is slightly overestimated. During
unloading (B → C) and subsequent reverse loading(10)

The elastic strain follows the generalized
Hooke’s law as
1  ed ije d ij  e d kk  ij
(11)
Ee
Ee
Young's modulus Ee is expressed in terms of theswelling index  and Poisson’s ratio e as31  2 e 1  e0  p
Ee 
(12)



Although the influence of stress path on theplastic flow is also considered in the proposed model

98

Comp.

-1

Stress ratio q/p

GEOMATE-Nagoya, Nov.13-15, 2013

1.5
1.0
Computed(Subloading tij)

0.5
0.0

Ext.

0

1

-0.5
(a)

-0.5

Stress ratio q/p

Fig. 5 Stress paths of reverse loading and reloading

Stress ratio q/p-0.5 0.00.0

-1.0

(b)

0.5
0

1

0.5

1.0

1.5

Fig. 7 Computed results by the isotropic hardening
model (subloading tij model)

0.5

0.5

1.0

1.5

Volumetricstrain v [%]

0.0
0.0

Stress ratio q/p

-0.5

-0.5

Monotonic loading (Comp.)
Reverse loading (A-B-C-D)
Reloading (A-B-C-E)

Y

-1.0

Computed(Subloading tij)

0.5

2

Axial strain a [%]

-0.5

-1.0

Comp.

1.0

0.0

-1

Volumetricstrain v [%]

-1.0

Ext.

1.5

2

Axial strain a [%]

1.5
1.0
0.5
0.0

-1

0

1

2

Axial strain a [%]

-0.5

-0.5

Fig.6 Observed results of reverse loading andreloading path
(C→D), the proposed model is capable of suitably
describing both the reduction of the shear stiffness
and the dilatancy before isotropic stress state as canbe seen in the observed results, i.e. the Bauschinger
effect, while the original isotropic hardening model
exhibits only elastic deformation. An overestimatedvolume contraction by the proposed model inreverse loading is, additionally, assumed to not be
due to the rotational hardening, since the computed
results evaluate more compressible behavior than theobserved ones even in monotonic loading path. On
the other hand, during reloading path (C → E), theproposed model represents the increasing of stiffness
in the direction of past shear history as well as theobserved results. It is finally worth observing that, inthe simulation by the proposed model, the gradualdissolution of the influence of the stress history
along with the plastic deformation is well described.
Therefore, the shear strength reaches its appropriate

-1.0

-0.5

Volumetricstrain v [%]-1.0

0.00.0

0.5

1.0

1.5

0.5

Fig. 8 Computed results by the proposed rotational
and isotropic hardening model
final value without the limit surface of hardening,
and the orientated yield surface coincides with theyield surface of the original isotropic hardening
model, i.e., bij = 0 at failure state. Naturally, theproposed model considers the final state dependingon the relative magnitude of the intermediate stress.

99

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 9 Stress path of isotropic compression with shear
history

Volumetric strain v [%]1.0

ACKNOWLEDGEMENT

0.5

0.0

in the proposed one. In addition, by considering the
decay of the influence of the stress history with
progress of the plastic deformation, the failure state
could be described without the limit surface ofhardening.
The proposed rotational hardening rule isapplicable to most constitutive models, and theisotropic hardening model named subloading tij
model was extended describe induced anisotropy ofsoil. It was indicated from a comparison with theexperimental results that the proposed model welldescribes a complicated anisotropic behavior bycontrolling the development and decay of theinfluence of stress history.

We would like to thank Mr. Anteneh Biru
Tsegaye, PhdD candidate at Norwegian Universityof Science and Technology, for valuable discussion
and reading the manuscript.
0.0

0.3

0.0

0.3

0.0

0.3

Fig. 10 Results of isotropic compression test withshear history
Triaxial Test – Isotropic Consolidation Test with
Shear History

Figure 9 illustrates the stress path of isotropic
compression test with shear history, and Figure 10
shows its observed and computed results, which areorganized as the relation between axial andvolumetric strain during isotropic compression path
(A→C'). It can be seen form observed result that soil
deforms anisotropically even under isotropic
compression, once it experienced shear history.
However, from the gradient dv/da gradually
decreasing with increasing of means stress, it can beassumed that the influence of the stress history alsoceases with progress of the plastic deformation
under isotropic condition. Although the computed
result by the proposed model slightly underestimatesthe influence of the stress history, it fairly describes
such development and decay of the influence of thestress history.

CONCLUSION

A new rotational hardening rule describing theevolution rule of the back stress ratio was proposedin this paper. Unlike the ordinary rotational
hardening rule, the back stress ratio develops when
the stress state deviates from monotonic loading path

REFERENCES[1] Nakai T. and Hinokio M, “A simple
elastoplastic model for normally and overconsolidated soils with unified material
parameters”, Soils and Foundation, Vol. 44, No.
2, 2004, pp. 53-70.
[2] Schofield A. N. and Wroth C. P., “Critical State
Soil Mechanics”. McGraw Hill, London, 1968.
[3] Nakai T. and Mihara Y, “A new mechanicalquantity for soils and its application toelastoplastic constitutive models”, Soils andFoun-dations, Vol. 24, No. 2, 1984, pp. 82–94.
[4] Matsuoka H. and Nakai T, “Stress-deformationand strength characteristic of soil under threedifferent principal stresses”, Proc. JSCE, 232,
1974, pp.59-70.
[5] Sekiguchi H and Ohta H, “Induced anisotropy
and time dependency in clays”, Proc. 9th
ICSMFE, 1977, pp. 229-238.
[6] Hashiguchi K, “An expression of anisotropy ina plastic constitutive equation of soils”, Proc. 9th
ICSMFE, 1977, pp. 302-305.
[7] Hashiguchi K and Chen X. P., “Elasticplastic
constitutive equation of soils with thesubloading surfaced and the rotational
hardening”, Int. J. for Numerical and Analytical
Methods in Geomechanics, Vol. 22, 1998, pp.
197-227.
[8] Hashiguchi K, “Subloading surface model in
unconventional plasticity”, International Journalof Solids Structure, Vol. 25, 1989, pp. 917-945.
[9] Nakai T et.al., “Formulation of the influence ofthe density and the stress path dependency ofplastic flow in sand”, Proc. of Powders andGrains, 2001, pp. 217-221.

100

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

A STUDY OF THE FORMATION MECHANISM OF BEACHROCK IN
OKINAWA, JAPAN: TOWARD MAKING ARTIFICIAL ROCK

1

Takashi Danjo1 and Satoru Kawasaki2
Graduate School of Engineering, Hokkaido University, Japan; 2 Faculty of Engineering, Hokkaido
University, Japan

ABSTRACT
Beachrock is coastal sediment that has been cemented mainly by calcium carbonate within the intertidal zone
in tropical and subtropical regions. Man-made beachrock has the potential to inhibit coastal erosion. Considering
this important application, we performed field investigations and laboratory tests to understand the formation
mechanism of beachrock in Nago, Okinawa, Japan. We performed a needle penetration test, microbial
population count and urease activity test, and conducted elemental and mineral analyses of the beachrock andsand. Some microorganisms at the site showed urease activity and the beachrock cement comprised high Mg
calcite (HMC). Our investigation showed that evaporation of seawater and/or urease activity of bacteria may
have resulted in precipitation of HMC, leading to formation of the beachrock, with partial solidification of somesandy specimens.
Keywords: Beachrock, Formation Mechanism, Cement, Microorganism, Urease Activity

important step in making artificial beachrock. As
part of this analysis, we performed a needle
penetration test, determined the viable bacterial
count, conducted a urease activity test andperformed elemental and mineral analyses of thebeachrocks and sand. Our focus is on the cement
formation mechanism of beachrock, which occurs in
the intertidal zone. Cement type and content havethe potential to influence the strength of thematerial; hence, detailed knowledge of beachrock
cements is valuable for producing a man-madeequivalent. In addition, we conducted laboratory
solidification experiments using local bacteria.

1. INTRODUCTION
On the world’s coasts, erosion is a significant
problem.
To
preserve
coastlines,
variouscountermeasures are used to combat coastal erosion.
These include construction of artificial reefs,
headlands, detached breakwaters and hard shore
protection, all of which control the amount of drift
sand and/or beach nourishment and sand bypassing,thus overcoming shortages of drift sand. However,these solutions are expensive, and require long time
periods for implementation, as well as theengineering of large amounts of materials, especiallyfor heavyweight sand coasts [1], [2].
We consider here a new method to protect
coastlines – the use of artificial rock that autorepairs by means of sunlight, seawater, and bacteria.
Our model of artificial rock is beachrock. Beachrock
is a type of sedimentary deposit that generally
occurs on tropical and subtropical beaches as a resultof intertidal lithification of loose beach sands andgravels by carbonate cementation [3]. Beachrocks
around the world have been reported to form over
several thousand years [4] owing to interactions
among sand supply, cement precipitation fromseawater and coastal erosion by ocean waves.
Therefore, it may be possible to slow the erosion ofcoasts by making man-made beachrock from coastal
sands. Because this artificial rock is made of local
materials, it has the potential to be an eco-friendly
product.
In this study, we examined the formation
mechanism of beachrock in Okinawa, Japan,
because understanding this mechanism is an

2. STUDY SITE AND METHODS
2.1

Study Site

The geology of Sumuide, Nago, Okinawa, Japan(Fig. 1) comprises limestone and calcarenite of the
Quaternary Ryukyu Group [5]. The location is 26°
40’ 74” N and from 126° 00’ 73” to 126° 00’ 74” E.
2.2

Needle Penetration Test

At the site, needle penetration inclination (N P )values of some beachrock samples were measured
five closely spaced points at each location by using aneedle penetration device (SH-70, Maruto Testing
Machine Company, Tokyo, Japan). Samples
measured exposed beachrock at the shoreline (twotest sections) and buried beachrock underneath thecoastal sand (one test section). Unconfinedcompressive strength, q u , was estimated from N P by
101

GEOMATE-Nagoya, Nov.13-15, 2013

2.5

N

N

Study site

Study area

500 kmElemental Analysis and SEM Observations

Samples of exposed beachrock, buried beachrock,and adjacent sand were analyzed by X-ray
fluorescence analysis (XRF). The surfaces of thesamples were observed microscopically andelemental measurements were made using scanningelectron microscopy (SEM) (SuperScan SS-550,
Shimadzu Corporation, Kyoto, Japan) and energydispersive X-ray spectroscopy (EDX) (SEDX-500,
Shimadzu Corporation).

30 km

2.6

Mineralogical Analysis

The same samples used for XRF and EDX
analyses were further subjected to mineralogicalstudy using X-ray diffraction (XRD) (MultiFlex
2kW, Rigaku Corporation, Tokyo, Japan) with CuKα radiation, with 2θ between 5 and 70°.
3. RESULTS
3.1
Fig. 1

Maps showing study site and view of
exposed beachrock.

The q u values of exposed beachrocks were larger
than those of buried beachrock (Table 1). This result
is similar to that of Vousdoukas et al. [4].
Furthermore, to the best of our knowledge, thisstudy is the first to report q u of buried beachrock.
Only three previous studies from Japan and Scotland[7]–[9] have addressed the mechanical properties of
exposed beachrocks.

the correlation chart of N P and q u described in the
instruction manual.
2.3

Microbial Population Count

Seawater, some beachrock samples, and sand at
both sites were sampled in sterile test tubes andrefrigerated at 4 °C in our laboratory. Subsequently,
1.0 g of each sample was mixed with 9 mL ofartificial seawater or saline solution, and 10 μL of
the supernatant was added to ZoBell2216E medium(for marine bacteria) or polypeptone-yeast extract
medium [6] (for viable bacteria). After inoculation,
the media were incubated at 25 °C for 7 days.
Subsequently, each population (colony count) was
counted by the plating method.
2.4

Needle Penetration Test

Table 1 Unconfined compressive strength, q u of
the beachrocks estimated by the needle
penetration test, and microbial population
counts.
Test
Section

NeedlePenetration test
NP
qu
N/mm
MPa

Urease Activity Test
Seawater
ExposedBeachrock1
ExposedBeachrock2
BuriedBeachrockSand

We isolated colonies from the sand adjacent tothe beachrocks using ZoBell2216E medium. Eachcolony was mixed with 20 mL of solution (25 g/L
CO(NH 2 ) 2 and 20 mL/L cresol red solution with
distilled water) in a 20 mL bottle. Under sealedconditions, the samples were left standing at 45 °C
for 2 hours. To determine whether the colonies haveurease activity, we observed the solution color after
2 hours. For cresol red, a change from yellow to
purple can be observed from pH 7.2 to pH 8.8.
Those samples that changed to purple were
measured for their pH values. For comparison, a
non-bacterial sample also was measured.

102

Microbial
population countMarine Viable
×104
×104
CFU/
CFU/
mL
mL
1.3
0

-

-

80±22

28±6.9

410

45

51±12

19±4.71500

8.15

8.9±5.4

3.4±2.2

460

13.6

-

-

500

5.4

GEOMATE-Nagoya, Nov.13-15, 2013

3.2

Microbial Population Count

100

Exposed Beachrock 1

90aPercentage (wt%)

For each sample, marine microbial populations
showed viable values (Table 1). Bacterial
morphologies and colors differed on ZoBell2216E
medium and polypeptone-yeast extract medium (e.g.
Fig. 2). The populations in the beachrock samples
tended to be smaller than bacterial populations
reported from soil (106 to 1014 g-1) [10], but larger
than in the seawater, despite the fact that thebeachrock is washed by seawater every day.
Therefore, this result suggests that the
microbiological properties of the beach at this site
affect beachrock formation.

Buried Beachrock

80

Sand

70
60
50
40
30
20
10
0

Element

Fig. 3Elemental percentage of site O samples byusing XRF.

b
a

b

HMC
P2

P1

P3

c

Fig. 2 Microorganisms in exposed beachrock 1 on(a) ZoBell2216E medium and (b) polypeptone-yeast
extract medium.
3.3

P6
P4
HMC

Urease Activity Test

P5

About 156 colonies were isolated from the soil
near beachrocks. Of these, five colonies changed thesolution color to purple after 2 hours at 45 °C,
indicating urease activity. Moreover, the pH range ofthe five samples was 9.0–9.3. In comparison, the pH
value of the non-bacterial sample was 7.1.
3.4

d

e

f

P8

Elemental Analyses and SEM Observation

P7

Fig. 4 SEM images of the samples. (a), (b):exposed beachrock 1 (×1200, ×4800), (c), (d):buried beachrock (×1200, ×4800), (e), (f): sand insite O (×1200, ×4800).

Results of XRF analysis of the samples areshown in Figure 3. All samples were composed
mainly of CaO, and beachrock samples contained
more MgO than adjacent sand. By contrast, the sandcontained more SiO 2 .
Subsequently, to identify the beachrock cement,
we analyzed sample surfaces by performing SEMEDX. Figure 4 shows that, only in association withthe beachrocks, the microparticulates covered withsand particles and the morphologies (Fig. 4 (b) and(d)) were similar to that of high Mg calcite, HMC[11]. HMC is a polymorph of CaCO 3 , containing
more than 4 mol% MgCO 3 , or 1.2 wt%. Moreover,
the MgCO 3 found in the microparticulates wascalculated to be 16–18 wt% (>1.2 wt%) based on the
Mg percentage about P1–P6 in Figure 5. Therefore,
we can conclude that the cement of beachrock at site
O is HMC.

Point

8
P1

C

O

Mg

Ca

7
P2

C

6
P3

O
Mg

P4
5

Al

P5
4

Si

P6
3

Ca
Fe

2
P7
1
P8
0

Fig. 5

103

20

40

60

Elemental Percentage (wt%)

80

100

Elemental percentage from P1 to P8 of Fig.
4 using EDX.

GEOMATE-Nagoya, Nov.13-15, 2013

3.5

properties may affect beachrock formation at thisstudy site based on the above microbial population
count. Other effects on beachrock formation are
outside the scope of this study and require further
consideration in the future.
First, with respect to PSW, Raz et al. [14]reported that to better understand the depositional
process of high-magnesian calcitic skeletons, theystudied the CaCO 3 precipitates formed fromsolutions with Mg/Ca ratios ≥4. We conducted water
analyses at the study site by performing ion
chromatography (ICS-1000, Dionex Corporation,
Osaka, Japan) (Table 2). The molar ratio Mg/Ca of
the seawater was approximately 6.3; this ratio
satisfies the conditions under which HMC could
precipitate. In addition, according to experiments by
Kitano et al. [15], sodium citrate and sodium malate
favor the precipitation of MC, whereby an increasein concentration of magnesium ion and these organic
materials cause formation of Mg-rich calcite. The
present study site is rich in organic matter, such assea algae, shells, corals, and bacteria, which may besources of citrate and malate.

Mineralogical Analysis

The samples contained the following minerals:
Mg calcite (MC), aragonite, and quartz (Fig. 6). MC
can be divided into HMC and low Mg calcite(LMC). LMC contains less than 4 mol% MgCO 3[4]. The highest peaks (around 30°) of the samples
were closer to the peak of HMC than that of LMC,
about 2θ value [12].
Mg-Calcite
Aragonite
Quartz1

Fig. 6

XRD patterns of (a) exposed beachrock 1,(b) buried beachrock and (c) sand.

Table 2 Chemical composition of seawater at the
study site.

4. DISCUSSION
4.1

Na+
(ppm)
11000

Formation Mechanism of the Beachrock

Beachrocks cemented by HMC have beenreported at 16 sites [4], [13] around the world, andtheir formation mechanisms are shown in Figure 7.
We focused further investigations of thebeachrock cements on the influence of precipitationfrom seawater and/or seawater evaporation (PSW),
and o n sur face micr o o r gani s ms, which we
considered as one biological process (BIOL). This isbecause (1) PSW is the factor most reported to berelated to the formation mechanism of beachrock
cemented by HMC (Fig. 7) and (2) microbiological
PSW
1

S-FWM

1

BIOL and P/C-F

1

Listedness

CO(NH 2 ) 2
(1)
+
Ca2+
(2)

3

0

2

4

6

8

10

12

Number of sites

Fig. 7

K+
(ppm)
486

Ca2+
(ppm)
348

pH

EC
(mS/cm)51

7.9

A second factor—the microbiological effect—
was indicated by the microbial population count andurease activity test. We found five colonies ofbacteria exhibiting urease activity in the sand near
the beachrock. The bacteria stimulate the hydrolysis
of urea, CO(NH 2 ) 2 . This reaction leads to anincrease in pH and precipitation of CaCO 3 , as shown
Eq. (1) and (2) [16]. At this site, there are abundantorganisms, and the mammalia, amphibia andchondrichthyes void urea.

10

PFW

Mg2+
(ppm)
1330

Formation mechanisms of beachrocks that
contain HMC cements. [4], [13] (PSW,
Precipitationfromseawater/seawater
evaporation ; PFW, precipitation from fresh
water ; S–FWM, Sea – fresh water mixing ;BIOL, biological processes; P/C–F,
Physico/chemical factors)
104+

2H 2 O

CO 3 2-→→2NH 4 +CaCO 3+

CO 3 2-,↓.

GEOMATE-Nagoya, Nov.13-15, 2013

Proposed

formation

Cement of beachrock

Fig. 8mechanism

Ar
Ar, C
C
HMC
HMC, Ar
HMC, Ar, LMC
MC
MC, ArLMC
Ar, LMC
SilicaListedness

4
1

Fig. 91

2

beachrock at the study site.
3

1

11
2
1

1

1

1

1

1

This study site

2

1

1

1

1

1

1

2

1

2

3

2

1
1
1

3

1

1

1

5
10
15
Site number of formation mechanism
PFW
BIOL, CO2-DEG
BIOL, S-FWM

CO2-DEG
PSW, BIOLVM

BIOL
PFW, S-FWM
Listedness

20
S-FWM
PSW, PFW

Cements and formation mechanisms of beachrocks in the world including the study site. [4], [17](Cement type: Ar, Aragonite; C, Calcite; HMC, High Mg calcite; LMC, Low Mg calcite; MC, Mg
calcite; Al, Element of Al; Si, Element of Si. Formation process: CO 2 –DEG, CO 2 – degassing; VM,
Various mechanisms.)

Moreover, MgCO 3 is expected to precipitate
with CaCO 3 . To the best of our knowledge, this is
the first time that bacteria exhibiting urease activity
have been recorded near beachrock.
Therefore, our investigation into the formation
mechanisms of beachrock at this study site (Fig. 8)
has shown that the evaporation of seawater and/or
the urease activity of microorganisms might haveresulted in the precipitation of HMC, leading toformation of beachrock.
Furthermore, we considered the relationship of
cements and formation mechanisms of beachrocks
around the world, including the present study site
(Fig. 9). We found six processes to be reported:
PSW; precipitation from fresh water (PFW); CO 2 –degassing; BIOL; sea–fresh water mixing;
physico/chemical factors; and various othermechanisms. Some beachrock sites have developed
from more than one mechanism. Moreover, thebeachrock examples cemented by calcite tend tohave been formed by PFW. In contrast, aragonite
and MC tend to have been precipitated fromseawater, as beachrock cements. In addition, thebeachrocks formed by BIOLs are cemented by
HMC, MC and/or Ar (Fig. 9).
4.2

1

1

1

1
3

1

8

1

1
7

0
PSW
PSW, CO2-DEG
BIOL, P/C-F

1

ofnovel and expandable.
Based on the method of Inagaki et al. [18], we
conducted a solidification test using a local
microorganism that raised the pH value to thehighest with respect to the above urease activity test.
The microorganism was estimated as Paracocus sp.
by the analysis of a partial base sequence of 16S
rDNA using the Apollon DB-BA 8.0 database. First,
the bacterium was shaken in the ZoBell 2216E
culture solution for 3 days at 30 °C. Second, coralsand dried at 110 °C for more than 2 days was added
into a 15 mL syringe (inner diameter 15 mm). Third,
the culture medium solution and 0.3 equimolar urea
and calcium chloride solution were sequentiallyinjected into the syringe and drained up to 1 mL
above the top surface of the sand. The specimens
were kept in wet conditions throughout. Thereafter,in the same manner, the urea and calcium chloride
solution was injected and drained once a day and thesyringe test was conducted at 30 °C.
Results indicate that the upper, side portions, andbottom areas of the specimens were solidified after 2
weeks (Fig. 10). The q u values were estimated, by
the needle penetration test, up to 2 MPa. Thismaximum strength was obtained from an upper

Ground Solidification using the Bacteria

We discuss here the tendency for solidificationof sand using microorganisms from the study site.
Recently, several investigations of microbial
ground improvement technologies have beenreported globally. The major cementation method is
to stimulate calcium carbonate to precipitate by theureolytic reaction of Sporosarcina pasteurii, a wellknown urease positive bacterium [16], [18], [19].
The solidification technique using local bacteria isFig. 10 Solidified parts of sediments using a
105

GEOMATE-Nagoya, Nov.13-15, 2013

bacterium obtained from near the Okinawa
beachrocks.
solidified part that was ≤10 mm thick and 54 mmhigh). To the best of our knowledge, this is thehighest q u measured by all reported solidification
methods using local bacteria.
Hereafter, by finding optimal compositions of
the solutions and curing temperatures, we plan tomake higher mechanical strength materials andlarger specimens to create artificial beachrock.

[7] Danjo T, Kawasaki S, “Physical andMechanical Properties of Beachrocks in
Okinawa Island”, Journal of JSEG. Vol. 53,
2012, pp. 191-200 (in Japanese with English
abstract).
[8] Ogasawara H, Yoshitomi K, Jijyu K,“Beachrock in Sosogi coast, Wajima, Japan”, In
Proceedings of the JSEG Tyugoku-shikoku
Meeting, 2004, pp. 31-34 (in Japanese).
[9] Selby MJ, “Hillslope Materials and Processes”,
Oxford University Press, Vol. 2, 1993.
[10] Pandey S, Singh DK, “Total bacterial andfungal population after chlorpyrifos andquinalphos treatments in groundnut (Arachis
hypogaea L.) soil”, Chemosphere, Vol. 55, 2004,
pp. 197-205.
[11] Erginal AE, Kiyak NG, Bozcu GM, Ertek A,
Gungunes H, Sungur A, Turker G, “On theOrigin and Age of the Ariburnu Beachrock,Gelibolu Peninsula, Turkey”, Turkish J. Earth
Sci., Vol.17, 2008, pp. 803-819.
[12] Henderson GM, Slowey NC, Fleisher MQ, “UTh dating of carbonate platform and slope
sediments”, Geochimica et Cosmochimica Acta,
Vol. 65, 2001, pp. 2757-2770.
[13] Erginal AE, Kiyak NG, Ozturk B,“InvestigationofBeachrock
Using
Microanalyses and OSL Dating: A Case Study
from Bozcaada Island, Turkey”, Journal of
Coastal research, Vol. 26, 2010, pp. 350-358.
[14] Raz S, Weiner S, Addadi L, “Formation ofHigh-Magnesian Calcites via an Amorphous
Precursor
Phase:
Possible
Biological
Implications”, Adv. Mater, Vol. 12, 2000, pp.
38-42.
[15] Kitano Y, Kanamori N, “Synthesis ofmagnesian calcite at low temperatures andpressures”, Geochemical Journal, Vol. 1, 1966,
pp. 1-13.
[16] Whiffin VS, Van Paassen LA, Harkes MP,“Microbial carbonate precipitation as a soil
improvement technique”, Geomicrobiology
Journal, Vol. 24, 2007, pp. 1-7.
[17] Kneale D, Viles HA, “Beach cement: incipient
CaCO 3 -cemented beachrock development in theupper intertidal zone, North Uist, Scotland”,
Sedimentary Geology. Vol. 132, 2000, pp. 165170.
[18] Inagaki Y, Tsukamoto M, Mori H, Nakajima S,
Sasaki T, Kawasaki S, “A centrifugal model testof microbial carbonate precipitation asliquefaction
countermeasure”,
Japanese
Geotechnical Journal, Vol. 6, 2011, pp. 157-167(in Japanese with English abstract).
[19] Van Paassen LA, Daza CD, Staal M, Sorokin
DY, Van Der Zon W, Van Loosdrecht CM,“Potential soil reinforcement by biologicaldenitrification”, Ecological Engineering, Vol.
36, 2010, pp. 168-175.

5. CONCLUSIONS
We performed needle penetration tests, viablebacterial count and urease activity tests, as well as
conducted elemental and mineral analyses ofbeachrock and sand to investigate the formation ofbeachrock at Okinawa in Japan. These results
revealed a probable formation mechanism.
In particular, evaporation of seawater and/or
urease activity of microorganisms may have resulted
in precipitation of HMC, leading to formation ofbeachrock. In addition, the microorganisms partly
solidified coral sand specimens.
For future studies, we plan to conductsolidification tests with bacteria and an evaporation
test with seawater to create artificial beachrock on alarge scale.
ACKNOWLEDGEMENTS
This research was supported by JSPS Grants-inAid (21300326 and 24･1036). We are grateful to
Suguru Shimazaki and Nao Aoki of Hokkaido
University for conducting the urease activity test.
REFERENCES[1] Pranzini E, Williams A, Coastal and Erosion
and Protection in Europe. New York: Routledge,
2013.
[2] Torii K, “Recent Trend of the Beach Erosion
Control”, Suikougaku ni kansuru kaki
kensyukai kougisyu, JSCE, 2002 (in Japanese).
[3] Ginsburg RN, “Beachrock in South Florida”, J.
Sediment. Petrol, Vol. 23, 1953, pp. 85-92.
[4] Vousdoukas MI, Velegrakis AF, Plomaritis TA,“Beachrock
occurrence,characteristics,
formation mechanisms and impacts”, EarthScience Reviews, Vol. 85, 2007, pp. 23-46.
[5] Kamiya K, “Geography and Geology of Yagaji
Island” Okinawa Prefectural Museum, Vol. 27,
2001, pp. 15-28 (in Japanese).
[6] Oshima T, Imahori K, “Description of Thermus
thermophilus (Yoshida and Oshima) comb.
nov., a Nonsporulating Thermophilic Bacterium
from a Japanese Thermal Spa.”, Int. J. Syst.
Bacteriol, Vol. 24, 1974, pp. 102-112.

106

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

A STUDY ON THE SLAKING-INDUCED CREEP DEFORMATIONCHARACTERISTICS OF CRUSHED MUDSTONE
Sharma Keshab1, Kiyota Takashi2 and Kyokawa Hiroyuki3
1

3

Former student, University of Tokyo, Japan; 2University of Tokyo, Japan; University of Tokyo, Japan

ABSTRACT
In order to study the slaking induced creep deformation characteristics of crushed mudstone, a series of direct
shear tests were conducted on the crushed mudstone under different stress ratio by using a modified direct shear
apparatus. Similar tests were also performed on the crushed sand stone, silica sand and glass beads to compare
the creep deformation characteristics with crushed mudstone. In each cyclic wetting and drying test, three cyclesof drying and wetting were carried out under constant shear load. Creep shear deformation in the first wetting
becomes larger as increase in the stress ratio, while it decreases with the progress of cyclic wetting and drying,almost zero in third wetting. During the drying process, initially, no appreciable creep deformation is found tooccur at higher water content. When the water content of specimen has reached a certain value, creep
deformations occur progressively with water loss. These tests show that the creep deformation during the drying
is more significant than during the wetting with the progress of wetting and drying cycles. On the other hand, theinfluence of cyclic wetting and drying on crushed sand stone, silica sand and glass beads is almost negligible.
Keywords: Slaking, Mudstone, Creep, Deformation, Wetting and Drying
ultimately the stability of the natural and artificial
slopes. Slaking of mudstone has been studied bymany researchers [13]-[17]. Traditionally, these
phenomena have very often been dealt with solely
from the viewpoint of durability, not deformationand strength. Only slaking or durability tests havebeen carried out in various forms which deal withthe change in physical properties such as density,
particle size distribution etc. of mudstone due toslaking. The precise mechanism of creep
deformation due to slaking is imperfectly understood[18].
A large creep deformation of crushed mudstone
after immersion was reported by many authors (e.g.,[1], [19]). Some researchers tried to evaluate theimpact of slaking on the engineering behaviour of
mudstones under unconfined condition. However,cyclic wetting and drying in the field typicallyoccurs under anisotropic stress condition. Similarly,
deformation characteristics of these mudstones havegenerally been studied either at a constant watercontent equal to the initial one, or after soaking atzero suction, or at dry condition. Since these
conditions only represent the two extreme conditionsof the mudstone, however, ones are lacking forinvestigating the deformation behavior of mudstones
under variable water contents and stress condition.
Therefore, in order to predict the long term responseof various natural slopes and other geotechnicalstructures, a better understanding of the deformation
characteristics of mudstones undergoing slaking isessential. So, the author tries to achieve a better
understanding of mudstone through this research.

INTRODUCTION
Mudstone tends to slake and has given rise tonumerous stability and settlement problems aroundthe world. For example, the landslide dam formedby the 2005 Kashmir earthquake was breached in2010 during moderate rainfall. It is assumed that thedam was breached due to the slaking of mudstones[1]. Mudstones can also accelerate soil creep and are
physical processes that have been recognized as
causal factors of landslide development on slopes[2], [3]. In addition, when high embankment madeof these materials is considered, long term stability
and settlement problems may possibly arise from theoccurrence of slaking of geo-materials due torepeated wetting and drying cycles [4], [5].
This deformation behavior becomes more
complicated when mudstone is exposed to cyclic
wetting and drying [6]. Structures, pavements,
concrete slab and other engineering structures canexperience significant damage from this slaking
induced shrinkage and swelling process if notdesigned for the presence of mudstone [7], [8].
Similarly, structures have experienced heave inmany parts of the world, including Saudi Arabia,
Canada, Australia, Oman, UK, USA, Japan,
Norway, and Ireland [9], [10]; for example,
approximately 1000 homes in Japan were damagedby mudstone heave in 2002 [11] and in Canada ongoing mudstone heave issues have already impacted
upon an estimated 10,000 buildings [12].
It is necessary to evaluate the creep deformation
characteristics of mudstone against slaking and107

GEOMATE-Nagoya, Nov.13-15, 2013

In this study, a series of direct shear tests were
performed with advanced direct shear apparatus
under different stress ratio. Specimens wereconsolidated at prescribed stress ratio, then they
were wetted and dried alternatively under constantshear loading. During the test, vertical and shear
loads, and vertical and shear displacements weremonitored, recorded, and processed in a personal
computer.

deformation of crushed mudstones. The insidespecimen size is 20cm x 20cm x 9.14cm. The initial
opening between upper and lower boxes was fixed
as 10 mm. The apparatus has the following essential
features: 1) a possible feedback control on bothnormal load and shear load to impose any prescribedstress path in the shear stress-normal stress space; 2)
a lower shear box moving on a very low-friction
rail, with two friction load cells to evaluate any
friction at the bottom of the lower shear box; 3)
shear load applied by a high precision gear loading
device driven by a servo-motor, allowing easy andexact control of arbitrary shear displacement ratio as
well as sustained loading (by a feedback control on
the shear load). The importance of all these features
to obtain reliable data of direct shear tests on
granular material was demonstrated by [21]. A
moisture sensor was inserted into shear box tomeasure the water content of the specimen
instantaneously as shown in Fig. 2.
In this study, loading process during the test
consisted of two stages: 1) the specimen was
subjected to shear and average normal stresses
keeping their ratio, R (= τ /σ v ) constant (R = 0.3, 0.5
and 0.7). Both shear stress (τ ) and normal stress(σ v ) were steadily increased up to respectively 15
kPa and 50 kPa for R= 0.3, 25 kPa and 50 kPa for
R= 0.5 and 35 kPa and 50 kPa for R= 0.7; 2) Afterthe prescribed shear (τ ) and normal stress (σ v )values were reached, these values were kept constantuntil the stabilization of both shear and verticaldeformations are achieved. After both shear andvertical deformations stabilization, the first wetting
was carried out by supplying distilled water from thebottom of shear box until the specimen was fully
immersed. Two cylinders with valves were used tocontrol the water flow inside and outside of the shear
box. The overflow of water was collected by fixing
an external container around the shear box as shown

TESTING APPARATUS AND MATERIALSThe Hattian Bala mudstone used in thisinvestigation as shown in Fig. 1, was obtained fromthe earthquake induced landslide dam, formed by the2005 Kashmir earthquake, which is locatedsoutheast of Muzaffarabad, Pakistan. As alreadymentioned, the earthquake induced landslide dam
was suddenly breached on 9th February, 2010 justafter moderate rainfall preceded by drought. Slakingof mudstone was assumed to be one of the major
causes of the failure [1], [20]. The specimens ofoven dried crushed mudstone were prepared byremoving particles finer than 2 mm and larger than
4.75 mm as a necessary adjustment to the apparatus
dimension. The specimens were not thoroughly
compacted to prevent from particle breakage and to
make similar conditions as those of the landslidedam, which was dynamically deposited without
strong compaction. The slaking index (JGS 2132) of
the mudstone was evaluated as level 1, while theslaking ratio (NEXCO-110, 2006) was 96.86 %.
Similarly, the crushed sand stone, silica sand andglass beads were also used for the comparative study
with crushed mudstones. The specimen of ovendried sand stones also consist of particles finer than
4.75 mm and larger than 2 mm. Similarly, the mean
size of glass beads and silica sand is 4 mm and 0.48
mm respectively.

10mm
Fig.1

Fig. 2

Hattian Bala mudstone

Moisture sensor and shear box withlarge containerin Fig. 2. This creep loading process represents asituation that slope ground is saturated by rain fallunder constant stress condition. When deformation

The performed laboratory tests comprise a seriesof direct shear tests with a modified direct shear
apparatus in order to study slaking induced creep

108

GEOMATE-Nagoya, Nov.13-15, 2013

In addition, from Fig. 3 a), the creep shear
deformation caused by wetting seems to be
decreased with progress of wetting and drying cycle,
almost zero during the third wetting. The watercontent of specimen before third wetting is about 0.7%. The effect of water content before wetting on
creep deformation will be discussed later.

TEST RESULTS AND DISCUSSION

3

water content

2

shear deformation

2nd drying
15

B

10

1

5

A

w= 2.5%

0

0
0

72

144

216

360

432

504

576

648

b)

3rd wetting 20

2nd wettingst

2.0 1 wetting

1st drying

2nd drying
15

1.5

Vertical deformation
1.0

10

water content

5

0.5

B

w = 2.5%
0.0

0

A
-0.5

b)

288

Elapsed time during creep (hour)a)Creep vertical deformation, n (mm)Figure 3 shows the instantaneous response of creep
deformations and water content of the crushedmudstone specimen during the wetting and drying
cycles under stress ratio (R) 0.5. Each cyclic wetting
and drying creep test took about one month tocomplete. The influence of wetting in the first cycle
upon shear deformation appears to be significant for
all specimens. Similarly, negative verticaldeformation (expansion) occurs due to wetting.
Positive value of vertical deformation is taken as
contraction. This expansive behavior of crushedmudstone would consist of two phases, swellingcaused by water absorption of clay mineral anddilatancy due to shearing.
For the second and third wetting processes, theincrement of shear deformations are relatively small,almost 1/8 times the increment of shear deformationin the first wetting. However, substantial negative
vertical deformation occurs during the second andthird wetting processes. Figure 3 also shows thatwater content decreases gradually during the firstand second drying processes. Initially, noappreciable creep deformation is found to occur at
higher water content. When the water content
becomes about 2.5 % (points A and B in Fig. 3),
both vertical and shear deformations occur
progressively with water loss and finally tend
towards an asymptotic value at water content of
about 0.7 %. As seen from the Fig. 3, both creep
curves during drying are composed of two welldefined curvilinear parts. Figure 4 shows schematic
sketch of crushed mudstone particles which consistof two pore systems, inter (macro) and intra-primary(micro) porosity [23]. It is assumed that water leaves
the crushed mudstones from the inter-pedal (macro)pores causing shrinkage of inter-pedal (macro) pores(first part of curvilinear). When the inter-pedal(micro) pores empty out, intra-primary (micro) pores
begin to shrink, losing its water content (second partof curvilinear).

1st drying

Water content, w (%)

Creep shear deformation, s (mm)a)

3rd wetting 20

2nd wetting

4 1st wetting

Water content, w (%)

due to immersion led to stabilize, water was drainedout (the first drying). Dry air was pumped from thebottom of the shear box and the shear box wascovered by silica gel to absorb moisture from
specimen while room temperature was maintained at
30°C. When both shear and vertical deformations aswell as water content had reached an almost constantvalue, water was supplied again to the specimen (thesecond wetting). The same process of drying andwetting was repeated (the second drying and thethird wetting). The detail information about testing
apparatus and procedure was given by [22]. The
above mentioned processes were also applied forcrushed sand stones, silica sand and glass beads
specimen.

0

72

144

Test No:
MS002
216

288

360

432

504

576

-5
648

Elapsed time during creep (hour)Fig. 3 Time histories of water content and creep
deformation (a) Shear (b) Vertical under cyclic
wetting and drying for 3 times for R= 0.5
Macro pore

Crushed mudstone

Micro poreFig. 4 Macro and micro pores system [23]109GEOMATE-Nagoya, Nov.13-15, 2013

WettingDrying
1stnd
2
3rd

3

st

1 wetting

1st drying

2

2nd drying

1
2nd wetting0

3rd wetting
0.3

0.4

a)

Increment
shear∆s(mm)(mm)
Increment
sheardisplacement,
displacement, ∆sduringfirst
firstwetting
wettingduringFig. 50.5
0.6
StressRR
Stressratio,
ratio,

0.7

∆v
(mm)
Increment verticalverticaldisplacement,
displacement, ∆v
v (mm)(mm)4

slopes.
The specimens prepared at high initial dry
density showed smaller shear displacement during
wetting. The shear displacement of the specimen
with initial dry density of about 1.50 gm/cm3 wasabout 0.9 mm while 0.3 mm shear displacement
occurred in case of the specimen with initial dry
density of about 1.60 gm/cm3 under R = 0.5 (Fig. 6).
The creep shear displacement caused by wetting
seems to be decreased with the progress of wetting
and drying cycle. The water content before eachwetting was not same. Figure 7 shows therelationship between water content before wetting
and wetting induced shear displacement. The shear
displacement during wetting became higher as thewater content before wetting of the specimen
become lower. Reference [24] also reported that theslaking level of clay aggregates became higher as
the initial water content of the specimen became
lower. Therefore, it can be understood that the
maximum displacement was observed during thefirst wetting because the specimen in this study was

2.0
1.5
1.0

2nd drying

0.5
0.0

1st wetting-0.5

2nd wetting-1.0

3rd wetting

Expansion
-1.5

0.3

0.4

0.5

0.6

0.7

StressRR
Stressratio,
ratio,

Increment value of creep (a) Shear (b) Vertical displacement at each stress ratio, R

0.8
0.6
0.4
0.2

1.54

1.56

1.58

1.6

4
3.5

R=0.5

R=0.7

Dry density (ρd) in gm/cm3

2.5
2
1.5
1
0.5
0

ρd = 1.538

ρd = 1.538
ρd = 1.538
ρd = 1.538 ρ = 1.538
d

-0.5

Dry
density,ρρρddd(gm/cm
Drydensity,Drydensity,(gm/cm ))Relationship between density of the specimen Fig. 7
and shear displacement during first wetting
110ρd = 1.538

3(gm/cm 33)3

Fig. 6

1st drying

WettingDryingContraction
1st
nd
2
3rd

b)

1

0
1.52

2.5

Increment
sheardisplacement,
displacement,(mm)
Increment shear
∆s∆v
(mm)

Increment shear
shear displacement,
displacement, ∆ss (mm)(mm)

Figure 3 b) shows considerable verticaldeformation that occurred in each wetting process.
The vertical deformation in case of R= 0.3, however,is almost negligible except in the first wetting
because of having higher water content (more than 3%) of specimen before the second and third
wettings. The wetting behavior would compose ofcontraction due to The vertical deformation in thewetting is affected by both R values during creep
shear loading and the progress of wetting and drying
cycles.
The above test results are summarized in Fig. 5,
showing the increment values of creep shear andvertical deformations at each stress ratio, R. The
wetting-induced maximum creep shear deformationof 3.4 mm was observed at R= 0.7 during the firstwetting (see Fig. 5a). Similarly, wetting-induced
creep failure was observed at R= 0.8 on the samematerial as the one in this study. Therefore, it seems
that the creep shear deformation during wetting is
proportional to the value of R, which would indicate
high risk of slaking-induced instability at steep-0.1 Water
0.3 before
0.7 w (%)
0.1 content
0.5wetting,
0.9
Watercontent
content before
Water
beforewetting,wetting,w w(%)(%)

Relationship between water content before
wetting and creep shear displacement

0.2

1st wetting

2nd wetting
1 drying
2nd drying
st

0.1

0

-0.1

Glass beads
Silica sand
Crushed sand stone

-0.2
0

a)
Fig. 848
96
144 192 240
Elapased creep time, t (hour)

Creep vertical deformation, ∆v (mm)

Creep
shear
deformation,
∆s∆s
(mm)
Creep
shear
deformation,
(mm)
Creep
shear
deformation,∆s(mm)

GEOMATE-Nagoya, Nov.13-15, 2013

0.2

1st wetting

2nd wetting
1st drying

2nd drying

0.1

0

-0.1

Glass beads
Silica sand
Crushed sand stone

-0.2

288

0

b)

48
96
144 192 240
Elapased creep time, t (hour)

288Time histories of water content and creep deformation (a) Shear (b) Vertical deformation undercyclic wetting and drying for 2 times for R= 0.5

prepared by oven-dried crushed mudstone. The
lowest water content during drying step is quite
large (about 3 %) in case of R= 0.3. This may bereason for almost negligible creep shear
displacement during the second wetting process at R
= 0.3. It can be deduced from this result that longer
and more severe droughts before rainfall events
could be more detrimental to slope stability asreported by [1].
One of the noticeable behaviors observed inthese experiments is a quite large creep deformation
during the drying processes. As shown in Fig. 5 a),the creep shear deformation during drying increase
with the increase in the stress ratio, R. However, inthe case of sress ratio, R= 0.3, the lowest watercontent during the drying step is quite large (about 3%). This may be reason for relatively small creep
deformation during the drying process at stress ratio,
R equal to 0.3.
Signigicant amount of mudstone particles werecrushed due to slaking. After experiment, it was
found that about 6 % particles became finer than 2
mm.
Figure 8 shows the instantaneous response of
creep deformations of glass beads, silica sand andcrushed sandstone specimen during the wetting anddrying cycles under stress ratio (R=0.5). The water
was supplied to the glass beads specimen after 24hours creep loading. The Influence of wetting in thefirst cycle upon both shear and vertical displacement
appears to be negligible (Fig. 8). Then, after 24hours of creep loading under saturated condition, thewater was removed from the specimen. The watercontent of the specimen decreased gradually andbecame almost zero after 6 days. As in the wetting,the influences of drying upon both shear and verticaldisplacements were not noticed. Similarly, for thesecond wetting processes, the increments of shear
and vertical displacements were again almost zero.
Similarly, in case of crushed mudstone and silica

sand, the influence of cyclic wetting and drying
upon creep deformation seemed to be neglible i.e.
no slaking effect on crushed sandstone and silica
sand. The particles size distribution of all threematerials i. e. glass beads, crushed mustone and slica
sand remained same even after cylic wetting anddyring which indicate the nonslakeble gematerial
does not have any influcens of cylcic wetting anddrying.
CONCLUSIONSIn order to study the slaking induced creep
deformation of crushed mudstone, a series of direct
shear tests were conducted. The following
conclusions were obtained in this study.
A significant creep shear deformation could befound in the first wetting process. However, theamount of creep shear deformation during wetting isdecreased with step of the drying and wetting cycles.
Almost equal vertical deformation occurs in eachwetting step if the water content of the specimen
before wetting becomes quite smaller. Creep shear
displacement during the wetting phase increases
with a higher stress ratio, R which would indicate ahigher slaking-induced instability at steeper slopes.
Shear displacement during the first wetting phase isvery large as compared to the second and third
wetting. During the drying process, a significant
creep deformation is found to occur when watercontent becomes less than 2.5 %. These tests showthat the creep deformation during the drying is moresignificant than during the wetting with the progressof wetting and drying cycles. On the other hand, it
was observed that creep deformation that occurred in
the glass beads, crushed sandstone and silica sandwere relatively insignificant and may not cause
instability of any slopes or structures.
However, there is no doubt that extended workand further validation are required to describe this111

GEOMATE-Nagoya, Nov.13-15, 2013

behaviour more completely in full drying/wetting
paths.

[13] Ladd CC, “Mechanisms of swelling bycompacted clay”, Highway Research Board
Bulletin, abstract, Vol. 245, 1960, pp. 10–26.
[14] Nakano R, “On weathering and changes ofproperties of tertiary mudstone related tolandslide”, Soils and Foundation, Vol. 3, 1967,
pp. 1-14.
[15] Franklin JA and Chandra R, “The slake
durability test”, International journal of Rockmechanics and mineral science, Vol. 9, 1972,
pp. 325-34.
[16] Moriwaki Y, “Causes of slaking of argillaceous
materials.” Ph. D dissertation, University ofCalifornia, Berkeley, 1974.
[17] Botts ME, “The effects of slaking on theengineering behavior of clay shales”, Ph. D.
dissertation, University of Colorado, Boulder,
1986[18] Morris PH, Graham J and Williams DJ,“Crackingindryingsoils”,
CanadaGeotechnical Journal, Vol. 29, 1992, pp. 263–
277.
[19] Yoshida N, Enami K and Hosokawa K, “Staged
compression-immersion direct shear test on
compacted mudstone”, Journal of Test
Evaluation, Vol. 30, No. 3, 2002, pp. 239-244.
[20] Sattar A, Konagai K, Kiyota T, Ikeda T and
Johansson J, “Measurement of debris masschanges and assessment of the dam-break flood
potential of earthquake-triggered Hattian
landslide dam”, Landslides, 2010, DOI:
10.1007/s10346-010-0241-9.
[21] Shibuya S, Mitachi T, and Tamate S, (1997).
“Interpretations of direct shear box testing ofsands as quasi-simple shear”, Geotechnique,Vol. 47, No. 4, 1997, pp. 769-790.
[22] Sharma K, “Slaking characteristics of geomaterials in direct shear test”, Master thesis,
University of Tokyo, Japan, 2012.
[23] Braudeau E, Mohtar RH and chahinian N,“Estimating soil shrinkage parameters”,
Development in Soil Science, Vol.30, 2004, pp.
225-240.
[24] Panabokke CR and Quirk JP, “Effect of initialwater content on stability of soil aggregates inwater”, Soil Science, Vol. 83, No. 3, 1987, pp.
185-196.

REFERENCES[1] Kiyota T, Konagai K., Sattar A, Kazmi ZA,
Okuno D and Ikeda T, “Breaching failure of ahuge landslide dam formed by 2005 Kashmir
earthquake”, Soil and Foundation, Vol. 51, No.
6, 201, pp. 1179-1190.
[2] Yatabe R, Yagi N, Yokota K and Bhandary NP,“Influence of Expansive Chlorite on theStrength of Weathered Green Rock at Mikabu
Belt of Japan”, In Proc. International
Conference on Geotechnical and GeologicalEngineering, Melbourne, 2000.
[3] Popescu, ME, “Landslide causal factors andlandslide remedial options”, in Proc. 3rd Int.
Conf. on Landslides, slope stability and safety
of infra-structures, Singapore, 2002, pp. 61–81.
[4] Cetin H, Laman H and Ertunc A, “Settlement
and slaking problems in the world’s fourthlargest rock-fill dam, the Ataturk Dam in
Turkey”, Engineering Geology, Vol. 56(3-4),
2000, pp. 225-242.
[5] Tovar RD and Colmenares JE, “Effect of drying
and wetting cycles on the shear strength ofargillaceous rocks”, Unsaturated Soils – Alonso& Gens (eds), Taylor & Francis Group, London,
2011, ISBN 978-0-415-60428-4, 1471-1476.
[6] Pejon OJ, Zuquette LV, “Analysis of cyclic
swelling of mudstones”, Journal of Engineering
Geology, Vol. 67, 2002, pp. 97–108.
[7] Shima H, and Imagawa S, ‘‘Compressive
settlement of slakable material and its
countermeasures.’’ Tsuchi-To-Kiso, Vol. 28(7),1980, pp. 45–52 (in Japanese).
[8] Nelson JD and Miller DG, “Expansive soil:
problems and practice in foundation andpavement engineering” John Wiley & Sons,
1997.
[9] Mochizuki A, Mikasa M and Kawamoto S,“Investigation of settlement of clay fill at a
housing development site’’ Tsuchi-To-Kiso,
Vol. 33, No. 4, 1985, pp. 25–32 (in Japanese).
[10] Noda T, and Nishi M, “A study of soft-rockembankment deformation due to water
increase’, in Proc., JSCE, Vol. 391No. 8, 1988,
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[11] Yamanaka T, Miyasaka H, Aso I, Tanigawa M,
and Shoji K, “Involvement of sulfurand irontransforming bacteria in heaving of housefoundations”, Geomicrobiology, Vol. 19, 2002,
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[12] Sutton D, McCabe B, O'Connell A and Cripps J,“A laboratory study of the expansion of an Irish
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112

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan,Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STUDY ON GROWTH OF VETIVER GRASS IN TROPICAL REGIONFOR SLOPE PROTECTION
Mohammad Shariful Islam1, B. A. M.Shahriar1, Md. Shahidul Islam1 and Hossain Md. Shahin2
1
Department of Civil Engineering, Bangladesh University of Engineering and Technology,
Bangladesh; 2Department of Civil Engineering, Nagoya Institute of Technology, Japan

ABSTRACTRiver bank erosion and embankment failures happen continuously throughout Bangladesh. From a strictly
economic point of view, the cost of remediating these problems is high, and the state budget for such works isnever sufficient. This confines rigid structural protection measures to the most acute sections. General reasons ofembankment failure are erosion due to rain splash, wave action, overtopping of storm surge. Faulty design, poor
maintenance and poor construction also cause failure. The use of CC blocks, stone revetments, geo-bags, andplantation etc. are commonly used for protection of embankment in traditional practices. These materials are
expensive and sometimes are not effective to protect the embankments and river bank for an expected design
life. On the other hand, slopes stability can be augmented by using bio-engineering techniques. Vetiver grass(Vetiveriazizanioides) is being used as an efficient bio-technology for slope protection in many countries, for it’s
special attributes like longer life, strong and long finely structured root system and high tolerance of extreme
climatic condition. A few steps have only been taken recently to employ this technique for slope protection
purposes in Bangladesh. This paper presents three case studies of vetiver plantation in slope protection against
rain-cut erosion. It is found that vetiver grass grows in different soil and climatic conditions of Bangladesh andeffective for slope protection. Prospect of vetiver plantation in protecting haor low-land is also discussed.
Keywords: Bio-technology, erosion, low-land protection, salinity, vetiver

construction cost of embankment would be a great
relief for Bangladesh.
Cultivation and export of shrimp is very
successful in the coastal region and it contributes 4%of national GDP every year [1]. For shrimp
cultivation, ponds are dug side by side. These ponds
are separated by common dikes around each pond.
Slopes of these ponds are also to be maintained forhassle free cultivation [2]. Cropping time is all roundthe year except November to January. During thesethree months farmers refurnish their ponds as it
becomes a dry season. In Satkhira region, flood
occurs during rainy season (July to August) in a
regular basis. The whole area becomes flooded andpond boundaries go under water. Flood causes
damages to the dikes boundary of the shrimp ponds.
Very often farmers engage themselves in boundary
deciding argument [3].
During monsoon season, basin type low lands ofnorth eastern part of Bangladesh (called “Haor”)
become flooded every year under water of 2 to 6
meters. Erosion in these areas is the main cause ofloss of home for a good number of people every year.
The common causes for embankment slope
failure in Bangladesh are heavy rainfall, wave action
from river, and inadequate protection of slopes
against overtopping of storm surge. Protection
against these types of failures can be divided into
three types like – i) structural, ii) non-structural and

INTRODUCTION
Bangladesh is a small riverine country located inSouth East Asia. In total, it has 700 rivers including
tributaries which have a total length of 24,140km. It
also carries two months of monsoon period in a year.
As a result, embankment failure due to erosion andbank breaching is very common phenomena in thiscountry. Embankment failure is a big setback fortransportation sector of Bangladesh. High cost ofland in this over populated country forces toeconomic design of road embankment which is often
failed by the wave action of heavy tidal force.
Bangladesh managed to construct about 7,555km
of embankment including 4,000km of coastal
embankments during the last few decades. It protects
about 24% of total land area and 39% of net
cultivation area. These embankments are constructedto protect land from tidal inundation, but cannot
prevent overtopping of cyclonic surges and tidal
bores. In addition, due to increased agricultural
production, these embankments provide good roadcommunication and contribute in the growth of theoverall socio-economic condition at the coastal zone.
Coastal region of Bangladesh is about 700km long.
To protect such long length of embankment against
natural calamity and erosion, every year governmentof Bangladesh has to allocate huge amount of money
in its annual budget. So, cheaper maintenance and113

GEOMATE-Nagoya, Nov.13-15, 2013iii) biological protection. Among the structuralprotections revetment, guide bunds, boulders andbrick matressing are common, while dredging,channelization geo-bag dumping etc. are common in
non-structural protections. Biological protections
refer to bank vegetation, wooden pilling, willow post,
bandallings and crisscross porcupines [4]. Most ofthese are expensive solutions against desired design
life for the protection.
Now–a-days, bio-engineering technique isbecoming popular in other countries. As Bangladesh
could be one of the most affected countries for
global warming [5], implementation of biotechnology would be the best solution against global
warming. Moreover, it is cheaper than typicalstructural solutions that are provided for slope
protection. Vetiver grass (Vetiveriazizaniodes) is
being used as an efficient bio-technology for slope
protection purpose in many countries. The special
attributes of vetiver is that it can grow on sites whereannual rainfall ranges from 200mm to 5000mm [6].
It can survive in temperature ranging from 0˚C to50˚C. It grows on highly acidic soil types (pH ranges
from 3.0 to 10.5) and also tolerant to high content ofAl, Mn, As, Cd, Cr, Ni, Pb, Hg, Se and Zn in thesoil. The saline threshold (EC) of vetiver is 7.8
dS/m. However, in soil with EC values of 10~20
dS/m, the yield of vetiver is reduced by 10%~50%[7].It’s roots are very strong with a diameter of 0.66
± 0.32mm having a high tensile strength of around85.10 ± 31.20 MPa. It is also found that vetiver
hedges can survive even for more than 100 years [8].
Recently, few efforts have been made toinvestigate the effectiveness of vetiver in slope
protection in Bangladesh [9, 10]. In this paper,
application of vetiver grass to protect roadembankment, shrimp pond sides in saline zone andpond slope in barind tract zone has been presented.
Finally, possibility of vetiver application in haor
low-land protection is discussed.

road is 23.01km and average width is 3.80m. The
chainage of the field trial is 17+700m to 17+800m.
Annual Average Daily Traffic of the road is 71.38.
Temperature and humidity of this area ranges
between 14°Cand 34°C and between 45% and 79%,
respectively. Average annual rainfall is 1875mm.
Specific gravity of the slope soil is 2.70. Sand,silt, and clay content are 10%, 80% and 10%,respectively. Mean grain size, D 50 and coefficient of
uniformity, C u of the soil are 0.048mm and 7.5,
respectively. It is seen that the soil is sandy silt. It
seems that the soil is erodible.
Rajshahi Site
A pond was selected to evaluate the growth andeffectiveness of vetiver grass to control erosion of
pond bank soil. The pond is situated at Godagari
Upazilla in Rajshahi District. The region consists ofbarind tract, Diara and Char lands. Annual averagetemperature ranges between 11.2°C and 37.8°C.
Average annual rainfall is 1862mm.
Specific gravity of the slope soil is 2.64. Sand,
silt and clay content of the soil are 13%, 75% and12%, respectively. Mean grain size, D 50 andcoefficient of uniformity, C u is 0.016mm and 7.4,
respectively. According to percentage of contents
the soil is sandy silt. It seems that the soil is erodible.
Satkhira Site
Satkhira is a district of south western part of
Bangladesh under Khulna division. It is close to Bay
of Bengal. Being coastal district, salinity is a key
feature for soil and water of this district. The annual
average maximum and minimum temperatures are
35.5°C and 12.5°C, respectively. The annual rainfall
is 1710mm. Most of the population is involved withshrimp cultivation in this district. Plantation was
done in two areas.
Plantation Area-1 was a plane land and part of awell maintained garden. Specific gravity of the soil
sample is 2.64. Sand, silt and clay content are 2%,
and 97%, and 1%, respectively. Mean grain size,
D 50 and coefficients of uniformity, C u are 0.025mm
and11.87, respectively. It is to be noted here that thisplantation area is not a slope. However, this trial was
employed to compare the growth in the same region.
Plantation Area-2 was a slope of a shrimp pond.
The soil of this site is organic soil with organic
content of about 10%. Specific gravity of the soil
sample is 2.52. Sand, silt, clay content are 3%,
88%and 9%, respectively. According to percentage
of contents the soil is CH. D 50 and C u are 0.022mm
and 9.56, respectively. Liquid limit and plasticity
index of the soil are 63 and 38, respectively.
pH level of the soil varies between 6.2 and 8.4.
Cation exchange capacity is 14.2 to 25.5 m.e%. Na,
K, Ca and Mg content ranges are 0.5 to 0.6, 0.2

DESCRIPTION OF STUDY AREAS
Trials are made in three different geographic
regions of Bangladesh. Possibilities of using thedeveloped method are also proposed for haor village
protection. Road embankment slope, pond slope inbarind tract and saline zone were selected for fieldtrials. General descriptions, climatic data, and soil
characteristics of the sites are given below.
Keraniganj Site
A road embankment named as KonakholaKholamura-Hazratpur-Itavara-Hemayetpur of Roads
and Highway Department of Bangladesh wasselected to investigate the effectiveness of vetiver atroad side slope. The site is situated at Keraniganj
under Savar Upazilla, Dhaka. Total length of the114

GEOMATE-Nagoya, Nov.13-15, 201318

Table 1 Index and physical properties of soils
Pond 1
Pond 2
Pond 3

Saline content (ppt)

16

Site

Gs

Sand
(%)

Silt
(%)

Clay
(%)

PI
(%)

OC
(%)

Site-1

2.70

10

80

10

-

-

Site-2Site-3

2.64
2.64

13
2

75
97

12
1

-

-

Site-4

2.52

10

3

88

38

10

14
12
10
8
6

Note: G s : specific gravity, PI: plasticity index, OC:organic content
January February MarchMonths

April

Watering had been done for 1 month on a regularbasis. Detail about this trial is presented in Islam etal., 2013 [10].
The growth of shoot and root was monitored
regularly. Figure 2 presents the site view and vetiver
shoot &root after 52 weeks. Figure 3 shows theshoot and root growth with time. It can be seen thatroot grew up to 52cm at the end of 52nd week whilelength of shoot was grew up to 180cm. It is foundthat although both the shoot and root length
increased with time the rate of growth became slow
after 40weeks. No sort of geo-jute was found at theFig. 1 Variation of salinity content of water of theponds with time at Plantation Area-2.
to 1.2, 6.3 to 16.2 and 2.8 to 11.4 m.e%, respectively.
Content of P, Zn and Cu ranged between 12 to 24,
0.1 to 0.8 and 0.08 to 0.30 ppm, respectively. Salinecontent of three ponds near the Plantation Area-2 aregiven in Fig. 1. Salinity is highest in March.
Haor Area
Haor is a basin type low land area in the northeastern part of Bangladesh. This zone contains about
400 haors and beels. The haor basin is a remote anddifficult access area that is flooded every year during
monsoon. The climate of the area is subtropicalmonsoonal with an average annual rainfall of 4,000
mm. Temperature varies between 26°C and
31°C.The surface soil of the area is mainlycomposed of yellowish grey silts which are very
erosion prone and problematic from filtration pointof view.
Index and physical properties of the soils from
Keraniganj (Site-1), Rajshahi (Site-2), Satkhira(Plantation Area-1: Site-3; Plantation Area-2: Site-4)
are presented in Table 1. It is seen that soil from
Keraniganj and Rajshahi are sandy silt. Soil of the
Plantation Area-1 of Satkhira is mainly silt while thesoil from Plantation Area-2 is organic clay.

(a)

FIELD TRIALSApplication in Road Embankment
Field trial was conducted at the Keraniganj site
for a road slope. Before vetiver plantation, site wasprepared by plucking out unwanted grasses andleveling the soil bed. Then geo-jute was placed overthe soil bed using fixing pins at a fixed interval.
700gsmgeo-jute was used in this plantation purpose.
After that vetiver had been planted at an interval of
20cm c/c both in horizontal and vertical direction
using a stick for making hole in the ground throughgeo-jute. Vetiver was planted in October 2011.
These vetiver grasses were collected from a placecalled ‘Pubail’ which is nearby Dhaka city.

(b)Fig. 2 Growth of vetiver grass at Keraniganj site
after 52 weeks of plantation: (a) view of the site and(b) close view of shoot and root.
115

GEOMATE-Nagoya, Nov.13-15, 2013

39

200

Growth length (cm)

150
100

3.5

Growth of shootGrowth of root

50

1

0.15
2

Vetiver
grass

0

Pond

-50

Fig. 4 Schematic diagram showing the plantation ofvetiver grass along the pond slope (dimensions arein meter)

-100
0

10

20
30
Time (week)

40

50

60

Fig.3Growth of vetiver shoot and root with time at
Keraniganj site.
site after 52 weeks which indicates that geo-jute is
totally bio degradable to environment. In the
opposite side of the vetiver plantation, a thickmasonry wall was constructed for protecting theslope from rain-cut erosion. Some parts of the wall
were damaged due to the rain water pressure while
vetiver plantation part worked perfectly. Cost ofvetiver plantation is 4 times lower than that of themasonry wall construction. Vetiver grass increases
the factor safety of the slope from 1.7 to 2.8 [10].
Application in Pond Slope(a)
Trial in barindtract zone in Rajshahi
Field trial was made to protect a pond slope from
erosion in the barind tract zone. The periphery of thepond was about 122m. The pond is used for bathing
and household purpose. There was almost novegetation around the side slope of the pond except
some banana trees. Side slope’s soils of the pond
were highly erodible. In rainy season, top soil is
washed away by runoff which causes the pond water
muddy. In dry season, the top soil is flown awayfrom the bank by wind. The slope of the pond is not
uniform. The slope at the top, middle and lower
portion is 1:1.5, 1:2 and 1:3, respectively.
Vetiver grass was planted in three sides of thepond bank in June 2010 and growth of it’s root andshoot were monitored until November 2010. At firstcow-dung was mixed with the bank soil. Vetivercollected from ‘Shirajganj’ was planted according to
the contour line shown in Fig.4. Spacing of planted
vetiver grass was 15cm both along the slope andperpendicular to the slope directions (Fig. 4). Wellrooted slips was planted 15cm apart to ensure a close
hedge within 6 months of plantation. It was foundthat the root grew up to 25.4cm and shoot grew up to
80cm in 6 months. Figure 5 show the condition of
the pond before and after vetiver plantation. Waterof the pond was turbid before vetiver plantation. But
water became clear even in rainy season. It meansthat application of vetiver was effective to protect
the erosion and migration of soil particles from the(b)Fig. 5 Pond condition: (a) before vetiver plantationand (b) after 6 months of vetiver plantation at the
Rajshahi site.
top and bank of the pond during rainy season andwinter (dry season).
Application in saline zone
At Satkhira, two places were chosen for theplantation program. Plantation Area-1 was a garden
with an area of 100 square meter and Plantation
Area-2 was a side slope of a shrimp pond of about
116

GEOMATE-Nagoya, Nov.13-15, 2013

0.60

150~180
1

1.25
1.5

Pond

0.75
Pond

Pond

Fig. 6 Schematic diagram of a typical shrimp pond
at Satkhira (all the dimensions are in meter)
100 square meter of plantation area which is 35km
away from the Plantation Area-1. Vetiver grasscollected from ‘Pubail’ site was also planted in these
two areas.
For Plantation Area-1, soil bed was watered andploughed using a garden hoe. After that, vetiver
grass was planted in square grid of 30.5cm. Root of
the grasses was inserted at least 7.5cm below the soil
surface. Watering has been done two times everyday.
On the other hand, for Plantation Area-2, which
was a slope of a shrimp pond, vetiver grass wasplanted at 30.5cm distance both in along the slope
and perpendicular to the slope. Here, it is to bementioned that, no geo-jute was used in the slopearea. Watering was done from the shrimp pond itself
to make the grasses habituated with the salinecondition. Figure 6 shows a typical section of shrimp
pond.
After plantation, growth of the shoot of vetiver
are monitored weekly. It is to be noted here thatsalinity content of ponds become very high during
March to April and plantation work had been donein May. Plantation during high saline content period
would help us to monitor vetiver’s sustainability
against hostile soil condition.
Condition of the root and shoot after 45 days forboth the plantation area is presented in Fig.7.
Growth of root and shoot with time has beenpresented in Fig.8. The growth in the Plantation
Area-2 is less than that of the Plantation Area-1.
This might be due to high salinity of the water andsoil in this area. However, it is clear that vetiver
grass can grow even in the saline zone. Similar
results were obtained in Fiji where vetiver grown inhigh saline zone (Truong at al., 2002).
Comparison of vetiver roots and shoot growth indifferent areas that is Keraniganj, Rajshahi andSatkhira is presented in Fig.9. Growth of both theroot and shoot are different for different soil andclimatic conditions. The growth is different even in
the same area. It is seen that in all the cases both theroot and shoot grow with time.

(a)

(b)
Fig. 7 Growth of vetiver shoot at Satkhira site in 45
days at (a) Plantation Area-1and (b) Plantation Area2

Growth of shoot/root (cm)150
GOS Satkhira-1
GOS Satkhira-2
GOR Satkhira-1
GOR Satkhira-2

100

Growth of shoots
50
Growth of roots
0

-50
0

2

4

6
8
Time (weeks)

10

12

14

Fig. 8 Growth of vetiver shoot and root with time
haor areas are made. Unit costs are taken from therate schedule2011 of Public works Department(PWD) [11].It is found that among the four solutions‘Total vegetation protection’ type of protection
system is less costly and very easy for construction.
In general, a 300mm layer of stone is placed overgeotextile. Vertical and horizontal anchor is also
used to attach with ground. It is a hard nature
solution and costs about US$ 19.55 per square meterslope protection. Another hard nature protection

Haor Village Protection
In the haor areas, masonry wall, revetment stonebamboo etc. are used for protecting the villages fromthe wave action. A comparative cost analysis for the
typical slope protection measures that are used in117

GEOMATE-Nagoya, Nov.13-15, 2013

150

100

Growth of shoot/root (cm)cheaper bio engineering solution for a global
warming threatened country like Bangladesh.

GOS - Keraniganj
GOR - Keraniganj
GOS - Satkhira-1
GOR - Satkhira-1
GOS - Satkhira-2
GOR - Satkhira-2

ACKNOWLEDGEMENTS

Growth of shoots
50

The authors are grateful to WAB Trading Intl. (Asia)
Ltd. for their support in plantation of vetiver grass inSatkhira. The authors are also grateful to RHD,
Government of Bangladesh for giving theirpermission in planting vetiver in road embankments.

Growth of roots
0

-50
0

2

4

6
8
Time (weeks)

10

12

14

REFERENCES

Fig. 9 Comparison of vetiver growth in different
regions[1]

Hensler, L, “A sustainable future for shrimp
production in Bangladesh?” Sustaining ethicalaquaculture trade, 2013.
[2] Alam, MN and Philips, MJ “Coastal shrimp
aquaculture
systemsinsouthwestern
Bangladesh”, Asian Fisheries Science 17,
2004, pp. 175-189.
[3] Haque, SA, “Salinity problems and crop
production in coastal region of Bangladesh”,
Pak. J. Bot., Vol. 38, No. 5, 2006, pp.13591365.
[4] Islam, MS, “Riverbank erosion and sustainable
protection strategies”, J. of Engineering
Science, Vol. 2, 2011, pp. 63-72.
[5] Rajib, MA, Rahman, MM, McBean, EA“Global Warming in Bangladesh Perspective:
Temperature
Projection
upto
2010”,
Proceedings of the Global Conference on
Global Warming, 2011, pp. 43-48.
[6] Rahman, MM, Islam, MA, Rashid, SH, Mia,
MMK, and Rahman, MH “Study on the
distribution and potential of vetiver grass in
Bangladesh.” Bangladesh J. of Plant
Taxonomy, 1996, 3(2), pp. 1-16.
[7] Truong, PN, Gordon, I, Armstrong, F, andShepherdson, J, “Vetiver grass for saline land
rehabilitation under tropical and Mediterranean
climate.” Proc, Eighth National Conf. on
Productive Use of Saline Lands, Perth,
Australia, 2002, pp. 71-80.
[8] Verhagen, HJ, Jaspers, Focks, DJJ, Algera, A,
and Vu, MA, “The use of vetiver in coastal
engineering.” Proc., Copedec VII, Dubai,
UAE, 2008, Paper No. 119.
[9] Islam, MN, “Role of vetiver in controlling
water-borne
erosionwithparticularreference to Bangladesh coastal region.”
Proc., 3rd Int. Conf. on Vetiver (ICV3),
Guangzhou, China, 2003, pp. 358-367.
[10] Islam, MS, Nasrin, S, Islam, MS and Moury,
FR, “Use of vegetation and geo-jute in erosion
control of slopes in a sub-tropical climate”,
World Academy of Science, Engineering andTechnology, Vol. 73, 2013, pp. 1162-1170.
[11] Public Works Department, PWD, “Schedule ofrates for civil works”, 2011.

system is ‘Masonry wall protection system’. Itsconstruction cost for per unit square meter is US$38.
This solution is found as the most costly solution
among the others. Another two protection measures
are proposed. One is vetiver grass with revetment
and another is vetiver grass without revetment.
Protection including revetment stone costs US$9.53
per square meter and only vetiver plantation costs
UD$ 4.7 per square meter.
FINDINGS AND RECOMMENDATIONS
Bio-technology in contrast to current practices ofembankment and slope protection around the world
is more sustainable, practical and efficient. In thiscontext, field trials have been made in three different
geographical locations of Bangladesh. The main
findings of these studies are:1) Vetiver plantation works very well on the slopeof road embankment which protects the slope
from rain-cut erosion and sliding. This provesthat vetiver plantation is suitable in a subtropical climate in sandy soil.
2) Vetiver grass also grows well in barind tractzone and works very well against rain-cut
erosion and wind induced erosion to protect
pond slope.
3) Even in high saline zone area, vetiver plantation
is a suitable green solution to protect the sideslopes of shrimp ponds from flood and wave
action.
4) From the study it is clear that vetiver plantation
is suitable for protecting slopes in different
geographic areas with different soil and climaticconditions. However, the growth of vetiver rootand shoot are different in different areas. These
are due to the difference in soil type, nutrient
content and salinity.
5) From comparative cost analysis it is found that
vetiver application is 8 times cheaper thanmasonry wall protection and 5 times cheaper
than revetment stone slope protection system.
Thus application of vetiver grass for erosion
protection could be a sustainable, green and118

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INTERACTION MECHANISMS OF SOIL-GEOSYNTHETIC
REINFORCEMENT
Mabrouk Touahmia1
Department of Civil Engineering, University of Hail, Kingdom of Saudi Arabia

1

ABSTRACTThe pullout performance of geosynthetic reinforcements under static and sustained loading is described inthis paper. Laboratory tests were conducted to investigate the cumulative effects of loading on the pullout
capacity and behaviour of geogrid reinforcements. The test methods and procedures for analyzing andinterpreting the data are presented. The mechanics of load transfer and reinforcement displacement are also
examined. In general, the results showed that under static loading applications the geogrid experienced a gradualdeformation with load increase. No peak load was observed with the system of loading used and the deformationof the geogrid was mainly close to the point of load application. The sustained loading tests showed no cessationof creep displacement of the geogrid throughout the testing periods of this investigation.
Keywords: Geosynthetics; Geogrids; Soil Reinforcement; Static Loading; Creep[4], there is still a lack of understanding about thelong-term interaction mechanism of the composite
system due to the absence of comprehensive andconclusive studies. Geosynthetics are widely used instructures which are subjected to constant loads
throughout their service life. Under these loading
conditions, geosynthetics would exhibit creep strains
which may potentially cause damage to thecorresponding structural system [5], [6]. Creep is thetime-dependent increase in accumulative strain or
elongation in the geogrid resulting from a constant
applied load. Thus, the creep behaviour ofgeosynthetics should be properly evaluated so thatthe appropriate factor of safety can be incorporated
into the long-term design of structural systems.
The main objective of this research was toevaluate the pullout performance of geogrid soil
reinforcements under different loading conditions.
Large-scale experimental program was conducted
aimed at the improvement of the understanding of
the interaction behaviour of soil-geosynthetic
composite systems. This paper presents an
examination of the pull-out performance and failure
machanisms of geogrid reinforcements under staticand sustained loading.

INTRODUCTION
Over the past three decades, geosynthetics havebecome a significant part of civil and environmental
engineering practice in most part of the world.
Various types of geosynthetic products have beenused extensively in a range of engineering
applications such as in road and highways, railways,
soil reinforcement, drainage and erosion control,
waste containment, retaining structures, slopes
stability and embankments stabilization, and in someof these applications they have entirely replaced theconventional construction materials. The use ofgeosynthetics has proven to offer cost-effective
environmentally sustainable alternative solutions tomany soft and unstable ground problems, where theuse of conventional construction materials would be
restricted or significantly expensive.
However,therapiddevelopmentofgeosynthetics technology has been accompanied byrelatively slower development in methods ofanalysis and design. The selection of appropriate
design parameters for geosynthetics reinforced soil
systems has remained variable and sometimes
confusing, due to the lack of data from field andlaboratory models that can optimize current design
methods [1]. Up to now, there are many
uncertainties concerning the structural or loadcarrying capacity of geosynthetic-reinforced soil
systems. Perceptions by users concerning the
durability of geosynthetic materials have caused anumber of designers to be hesitant to use
geosynthetics
forlong-term
reinforcement
applications. Although many research studies havebeen carried out in recent years to investigate theinteraction properties of soils-geosynthetics [2],[3],TESTING APPARATUS AND MATERIALSFor the examination of the interaction
mechanism of soil-geogrid composite systems, alarge scale laboratory pullout device was developed.
The testing program was designed to evaluate theinterlock capacity of the soil-geogrid and to analyse
the failure mode of the composite system.
The main testing apparatus used in thisinvestigation is shown in Fig. 1. It consisted of a119GEOMATE-Nagoya, Nov.13-15, 2013

rigid sand container of inside dimensions 4.0 m x 0.3
m x 0.3 m, a loading system with the capacity toapply axial pullout loads and a surcharge pressure
system. The confining stresses, which could becontrolled up to 300 kPa safely, were applied to the
top of the soil sample via a pressure plate loaded
through a water bag and connected to an air
compressor through a pressure regulator.
Instruments were used to measure pullout forces,
pullout displacements and surcharge pressures. Alldata were recorded and monitored by a computer
based data acquisition system connected to thetesting apparatus.

Fig. 3Fig. 1

The test specimen was located at the mid-heightof the soil sample and connected to the loadinglevels system with a special end clamp. The
displacements along the geogrid were measured
using inextensible steel wires connected to thespecimen, in at least eight different locations, and to
LVDTs fixed to the external back side of the box.
The soil used in testing was a uniformly graded
dry sand of medium size with a coefficient of
uniformity C u = 1.9; a specific gravity G s = 2.67; afriction angle Ф = 39.4o; maximum and minimum
densities of 1.78 Mg/m3 and 1.42 Mg/m3
respectively (Fig. 4). The sand samples wereprepared in the sand container by raining method toa targeted relative density Dr = 53%. To obtain auniform density of sand throughout the filling
operation, the sand was placed in equal layers of 50
mm thickness.

Testing apparatus.

The reinforcements tested in this investigation
were formed by cutting SR2 geogrids into a row of
two ribs in width and 4 m in length. SR2 geogrid is auniaxial geogrid type manufactured from copolymer grade high density polyethylene. Physicaland mechanical properties of SR2 geogrids arereported from manufactures’ data in Fig. 2 and Table
1. The index load (PI) of the geogrid, defined as theultimate rupture load of an identical geogrid in air, isshown in Fig. 3.

Fig. 2

Typical tensile strength extension of thegeogrid (SR2).

Geometry of uniaxial SR2 geogrid.

Table 1 Physical properties of SR2 geogrid
Dimensional Properties
Product width (S L )Transverse bar width (D TH )Max bar thickness (D TV )Min bar thickness (D TV )Rib width (D LH )Rib thickness (D LV )Number of ribs
Mass per unit area

Mean
100 mm
12.69 mm
4.56 mm
4.36 mm5.72 mm
1.34 mm
44 / m972 g/m2

Fig. 4

Particle size distribution of the sand.

PULL-OUT BEHAVIOUR OF THE GEOGRID
A series of static pull-out tests were carried out
to investigate the pullout performance of the geogrid.
120

GEOMATE-Nagoya, Nov.13-15, 2013

The static loading of the reinforcements were carriedout by applying dead weights of 20 kg each 5
minutes and then reduced to 10 kg each 5 minutes athigh extension.
Figure 5 shows the load-displacement
relationships for the 4 m geogrid reinforcementburied under 2 different normal stresses of 50 and
100 kPa.

confining stress be used it would be impossible topull out the reinforcement. Consequently, failure ofthese reinforcements by rupture appears to be aneasier mode.

Fig. 6

Axial displacement of the geogrid withapplied loads.

CREEP BEHAVIOUR OF THE GEOGRID
Fig. 5

Pullout load–displacement relationship of
the geogrid at different confining stresses.

To examine the creep behavior of the SR2
geogrid reinforcement a series of short and longterm sustained loading tests were conducted
throughout this investigation. For the short-term
creep test a loading increment of 5% PI was appliedeach 60 minutes during which the creep
deformations are recorded at 1, 2, 5, 10, 20, 40 and
60 minutes. For the long-term creep test, twoloading levels, namely 25% PI and 35% PI, werechosen to be held for tweleve weeks (2000 hours)
time duration while the creep deformations of thegeogrid reinforcement were recorded at 1, 2, 5, 10,
20, 40, 60 minutes and then after each hour. During
all these tests the surcharge pressure was kept
constant at 100 kPa. These tests were carried out
under very small changes in temperature tominimize the effect of temperature variation on theexperimental results. The temperature recorded
throughout the tests was 18 ± 1o C with a maximum
variation of 2o C.
The results of these tests showed no cessation of
creep displacement of the geogrid reinforcement
throughout the testing period. This trend can beclearly seen in Fig. 7 which illustrates therelationships between creep displacements and time.
The results of these tests indicated that despite noneof the reinforcement failed by pulling through thesand mass, their creep deformation did not cease
throughout the test period and showed a significant
increase with time and applied load increase.

As can be seen, the general pattern of these
relationships is characterized by a rapid increase ofload with an initial small increase in the strip
movement up to a certain level after which thedisplacement continues to increase with loadincrease till the end of the test. No peak load could
be observed with the system of loading used and therelationship between load and deformation became
linear at large displacements. The surcharge pressure
was found to have a great effect on the deformationof the geogrid. The reinforcement mobilized greater
resistance to pulling load when the surchargepressure increased and that is clearly visible underhigh loading increments.
The recorded movements along the length of thegeogrid reinforcement are given in Fig. 6. Thesemovements were expected to be a combination of
two components; the extension induced in thereinforcement together with the slip of thereinforcement. However, as can be seen, the total
displacement of the reinforcement consists only ofan extension of the front half part of the geogrid
reinforcement and neither slip nor extension along
the rear segment of the specimen length wasobserved. This means that no load was absorbed by
the lattermost half length of the reinforcement andhence no frictional or bearing resistances were
mobilized along that part of the strip. Thisobservation would indicate that unless a very low
121GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 7

Displacement-time
relationshipapplied load of the geogrid.

withFig. 9These observations are best illustrated by theform of a plot between creep deformation rate andtime. It may be seen in Fig. 8 that at any sustained
stress level the logarithm of the creep deformation
rate decreases linearly with the logarithm of time.
Furthermore, the slope of this relationship isessentially independent of the stress level, andincreases in stress serve only to shift the line
vertically upwards.

Fig. 8

Creep displacement-log time relationship of
the geogrid.

CONCLUSION
The pull-out performance of the geogrid
reinforcement under static and sustained loading is
described in this paper. The laboratory tests results
demonstrated that the geogrid reinforcement can beused in most loading conditions, although care will
be required in ensuring that appropriate factors ofsafety are applied to control the resulting
deformation.
Under static loading applications the geogrid
reinforcement experienced a gradual deformation
with load increase. No peak load was observed withthe system of loading used and the relationshipbetween load and deformation became almost linear
at larger displacements. The total displacement of
the reinforcement consists only of an extension of
the front half part of the geogrid reinforcement andneither slip nor extension along the rear segment of
the specimen length was observed
The sustained loading tests data indicated thatmaintaining the applied load constant for several
weeks results in a continuous deformation of thegeogrid reinforcement without cessation. This
deformation was mainly close to the point of load
application. Despite none of the reinforcement failed
by pulling through the sand mass, their creep
deformation did not cease throughout the test period
and showed a significant increase with time andapplied load increase.

Creep rate-time relationship of the geogrid.

Figure 9 shows the time-dependent deformation
relationships of the geogrid on a semi-log scale forthe long-term sustained tensile loading. This figure
indicates that maintaining the applied load constantfor several weeks results in a continuous
deformation of the geogrid reinforcement. An
interesting feature is that the rate of displacementlog time was constant during the first few weeks andstarted to decrease slightly towards the end of thetest.

ACKNOWLEDGEMENTS
The author gratefully acknowledges the supportof his research program by The Saudi BinladinGroup. The facilities and assistance provided by theCollege of Engineering at the University of Hail arealso appreciated.

122

GEOMATE-Nagoya, Nov.13-15, 2013

GeotechnicalandGeoenvironmental
Engineering, Vol. 133 (1), 2007, pp. 37-50.
[4] Palmeira EM, “Soil–geosynthetic interaction:
Modelling and analysis”, Geotextiles andGeomembranes, Vol. 27 (5), 2009, pp. 368-390.
[5] Yoo H, Jeon HY and Chang YC, “Evaluation ofengineering properties of geogrids for soil
retaining walls”, Textile Research Journal, Vol.
80 (2), 2010, pp. 184-192.
[6] Bathurst RJ, Huang BQ and Allen TM,“Interpretation of laboratory creep testing for
reliability-based analysis and load andresistance factor design (LRFD) calibration”,
Geosynthetics International, Vol. 19 (1), 2012,
pp. 39-51.

REFERENCES[1] Zornberg JG and Leshchinsky D, “Comparisonof international design criteria for geosyntheticreinforced soil structures”, Landmarks in EarthReinforcement, Ochiai et al., Vol. 2, 2003, pp.
1095-1106.
[2] Moraci N, Romano G and Montanelli F,“Factors affecting the interface apparent
coefficient of friction in pullout conditions’, 3rd
European Geosynthetics Conference, Monaco,Vol. 1, 2004, pp. 313-318.
[3] Teixeira SHC, Bueno BS and Zornberg JC,“Pullout Resistance of Individual Longitudinal
and Transverse Geogrid Ribs”, Journal of123

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SIMULATION AND PREDICTION OF LARGE-SETTLEMENT INULTRA-SOFT PEAT GROUND BY DEDUCING THE IN-SITU INITIAL
CONDITIONS CONSIDERING ARTESIAN PRESSURE
Mutsumi Tashiro1, Toshihiro Noda2 and Nguyen Hong Son3
1,3
Civil Engineering, Nagoya University, Japan;
2
Disaster Mitigation Research Center, Nagoya University, Japan

ABSTRACTIn the Mukasa area of the Maizuru-Wakasa expressway in Japan, delayed settlement as large as 11m has
occurred by the test embankment loading on a ground that includes approximately 50m of ultra-soft sedimentlayers containing peat and clay. While the construction of the embankment could not induce catastrophic sliding
failure, it did dramatically impact the surrounding ground, causing substantial lateral displacement and groundupheaval of up to 2m and 1 m, respectively. In this paper, simulations of the settlement and pore water pressure
observed until now and predictions of future behavior were carried out using soil-water coupled finite
deformation analysis program GEOASIA. The initial in-situ conditions of the ground were deduced considering
effect of the observed artesian pressure and various disturbances that might occur during sampling. The results
showed that improvement of mass permeability of the ground and the slow and/or lightweight banking are
effective means of providing the stability during loading and reducing the residual settlement.
Keywords: Peat, Prediction of settlement, Soil-water coupled analysis, Delayed settlement

INTRODUCTION

GENERAL DESCRIPTION OF THE TESTEMBANKMENT

The soil in the Mukasa area of the MaizuruWakasa expressway in Japan consists of ultra-soft
sediment layers comprising peat and clay with Nvalues on the order of 0 to 1 and a maximum depthof 50 m. Examination of a test embankment
established approximately four years ago reveals
that substantial settlement in excess of 11 m has
occurred. While the construction of the embankment
could not induce catastrophic sliding failure, it did
dramatically impact the surrounding ground, causing
substantial lateral displacement of up to 2 m andground upheaval of up to 1 m as in [1].
In this paper, simulations carried out on the largescale ground settlement observed until now, andpredictions of settlement that could occur in the
future are shown. In addition, the effect ofcountermeasures such as ground improvement bydrain, replacement of existing embankment withlightweight materials, and reduction of the loading
rate, were also investigated using numerical analysis.
These analysis were performed using the soil-water
coupled analysis program GEOASIA (All Soils All
States All Round Geo-Analysis Integration: [2], [3]),in which the SYS Cam-clay model as in [4] wasmounted as the constitutive equation for the soil
skeleton. The initial in-situ conditions of the groundwere deduced considering the effects of the observed
artesian pressure and various disturbances that mightoccur during sampling.

Figure 1 shows a longitudinal cross-section of thesoil strata underlying the test embankment. Threetypes of test embankments were constructed using
the card-board drain method (CBD), the sand drain
method (SD) or no ground improvement with theaim to select an effective method for the ultra-soft
ground. The soft layer of ground directly under thetest embankment constructed with SD method was
thickest among these three embankments and themagnitude of observed settlement was also largest.
For this reason, the following discussion in thisstudy was performed focusing on the SD section.
The total settlement estimated before construction
was 8.6m in the case of considering the settlement of
all layers including even the deep peat layers.
However, as presented in Figure 2, the thickness ofembankment (= embankment height + settlement)reached 15m when the embankment wereconstructed at the planned height of 7m.
The large-scale settlement was accompanied bysubstantial deformations in the surrounding area.
Especially in the vicinity of embankment, ground
uplift of up to 1m and horizontal displacement of up
to 2m have been observed and inclination ofirrigation ditch and cracking of ground surface were
occurred. The range of these influences was about
100m away from the toe of slope. At the point, 4
years after the end of embankment loading, thesettlement has reached 11 m, representing a
124GEOMATE-Nagoya, Nov.13-15, 2013

CBD (50m)

Embankment
Apt
Ac
As
Dpt
Dg

Elevation(m)Unimproved (50m)

SD (50m)

-0.0
-10.0
-20.0
-30.0
-40.0
-50.0

9
8
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12 -1
10

: Artesian pressure is considerd: Artesian pressure is not considerd0
Apt2

embankment thickness
at time of construction(=embankment height+ settlement magnitude)
=15m

Ac1

10
As1 Ac2u20

Depth (m)Settlement (m)Embankment height (m)Fig. 1 Schematic of test embankment and underlying soil strata (longitudinal cross section).

Apt3
Ac2

30

Apt5
Apt6

40
Apt7
0

10
Time (year)

1

50

10

Apt8
Dg

Fig. 2 Embankment height and observed settlement
at the center of embankment (constructed with SD).

60

: Measured before embankment: Measured after embankment: Consolidation yield stress pc(before embankment)
0 200 400 600 0100
200Pore pressure (kPa) Effective overburden (kPa)settlement rate of 3.0 cm/month with little sign ofconvergence.

Fig.3 Estimated distribution of initial pore waterpressure and effective overburden pressure

DEDUCTION OF INITIAL IN-SITU GROUNDCONDITIONS

Subsequently, the material constants and initial insitu conditions of each layer are estimated fromlaboratory test results.
In previous studies as in [5] and [6], the authors
proposed a novel method for predicting long-term
settlement of soft clay ground accompanied bydelayed compression. Natural deposited clays withhigh compressibility possess high degree of structure
and are sensitive to disturbance, i.e. thecompressibility tends to become significantly low inthis type of clay because of the “disturbance” thatmight be occurred between sampling from in-situ
and preparing samples for laboratory tests. Therefore,
it would be necessary to consider the effect of
disturbance in order to deduce a higher
compressibility of in-situ soils.
In this paper, the various insights gained from soft
clay ground were applied to peat ground. In
comparison with inorganic clays, peats are expected
as more desirably impacted by “disturbances” due toextremely high water content, and low shear strength.
In addition, considerable heterogeneity among deeppeat-layers samples regarding to factors such as
mixing of plant fibers was observed. For thesereasons, simulations were conducted based on a

Prior to performing the simulation, in order toestimate the initial in-situ ground conditions,
historical data related to ground formation as well as
various survey data, including pore water pressure
were examined. The area is located between faults,
and there is a possibility that the ground was
deposited through the repeated upheaval, settlement,
and deep accumulation of organic components in thevalley that experienced continuous artesianconditions.
In this paper, the initial distributions of pore waterpressure and effective overburden pressure of theground prior to embankment loading was estimatedin Figure 3. For reference, the distribution whenartesian pressure is not taken into consideration is
included as a dotted line. This represents a special
case in which the initial effective overburdenpressure p 0 becomes greater than the consolidation
yield stress pc (p 0 > p c ). In this region, it is expectedthat the increase in artesian pressure accompanying
the increase in soft ground thickness resulted in acontinuous low effective pressure in the deep ground.
125

GEOMATE-Nagoya, Nov.13-15, 2013

range of assumed initial in-situ conditions deduced
from as many compression curves for undisturbed
samples as possible, and determined the initialconditions that best reproduced the measured
settlement magnitude. Figure 4 shows the examples
of compression curves for laboratory and in-situ
soils.
With regard to the permeability of ground, given
the high compressibility of the peat layers, a positive
relation between the void ratio e and coefficient of
permeability k were assumed by the expression
e=Clnk/k 0 +e 0 , and for the other layers, constantpermeability coefficient were assumed. In addition,in order to represent the improvement inpermeability due to the SD, 100 times as large as
permeability were assigned to finite elements
corresponding to the improved area. Based on theseassumptions, permeability values were also
determined that could simulate the observations assufficiently as possible.
σ 'v0 pc

σ 'v0 pc

5

Ac1-2

v0
Specific volume v

v0Specific volume v

Figure 6 shows the measured and calculated
results on settlements at surface and boundary ofeach layer directly below the center of embankment.
After simulating the observed settlements andadjusting the initial in-situ conditions andpermeability of each layer, the prediction of future
behaviors was performed by continuing thenumerical analysis using the same parameters. As aresult, additional residual settlement on the order of
1.5m was estimated to occur over the next 70 years.
Measured and simulated pore water pressures werecompared in Figure 7 at approximately 1400 days(about 4 years) after the entry of embankmentloading (dotted line in Figure 6). It can be observedthat the measured distribution of pore water pressure
has also reproduced well through the above
computations.
Figures 8 and 9 show the settlements of groundsurface and the horizontal displacements directly
below the both toes of slope, respectively. The largedeformations observed the Mukasa-side (uplift ofground surface and lateral displacement to theoutside of embankment) were also reproduced. It
was estimated that ground deformations of the Tanaside were restrained by the deep rigid layers (As4and Dpt layers). With the progress of consolidation,
the directions of deformations in shallow layers were
shifted to the inside of embankment. In the Tanaside, especially, it could be expected that the surface
layers might be transformed to the inner side than
the initial location. In addition, in the deep layers
around Apt5 layer where their permeability were
gradually changed lower as a result of large
compression, lateral displacement to the outside ofembankment was estimated to occur at the end of
consolidation.

4

3

Apt7

5
4
3
2

2
1

2

3

10
10
10
10
Vertical effective stress σ 'v(kPa)

1

2

3

4

10
10
10
10
Vertical effective stress σ 'v(kPa)

4

Fig. 4 Examples of compression curves forundisturbed samples (gray lines) and estimation for
in-situ soil (thick black lines).
SIMULATION AND PREDICTION OF
LARGE-SCALE SETTLEMENT*Actual mesh width was 200m

Surface of ground and embankment: permeable boundary (atmosphere)
Ac1-1 (3.0)

85.0
68.6
39.0
27.3

SD expansion（34m×85m)
SD (20m×60m)

7.4m

Ac1-2 (5.0)
Apt2(1.8)
As1(1.2)
Ac2u(4.2)
Apt3(6.2)
Ac2 (3.0)
As4
(9.5)

Apt5 (9.5)
Apt6 (5.75)

Dpt(16.0)

Apt7 (7.25)

Measurement of pore pressure
Apt8
Apt7

Apt6
Apt5

Settlement (m)Units(m)

8
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9
10
11
12
13
-1
10

Embankment height (m)The finite element mesh and boundary conditions
are presented by Figure 5. The SD installation
section of the embankment of Figure 1 was modeled
and ground in state of horizontal stratification was
assumed for simplicity.

Apt8 (3.0)

Measurement
Simulation

As1
Apt2

0

10

Time (years)

10

1

Ac2
Apt3
Ac2u
Ac1-2
Ac1-1
2

10

Fig. 6 Simulations and predictions of settlements
directly below the center of embankment.

Left, right and bottom faces: permeable boundary (assuming artesian conditions)Fig. 5 Finite element mesh (after embankment
construction).

126

GEOMATE-Nagoya, Nov.13-15, 2013

consolidation yield stress derived from theirdepositional environments. Therefore, when arelatively high embankment was constructed on the
ground, the stress conditions of even deep layers
were reached beyond the consolidation yield stresseasily and rapid compressions were occurred. Aftera certain degree of volume compression, peats
exhibit extremely poor permeability and havetrouble dissipating excess pore pressure, particularly,
in the area of ground without drain improvement.

Depth (m)-5510Initial condition
Measurement
Simulation

Embankment

0

15 Ac1
Apt2
20 As1Ac2u
25 Apt3
30 Ac2EVALUATION OF COUNTERMEASURESFOR ULTRA-SOFT GROUND CONTAINING
PEAT

35 Apt540 Apt645 Apt7

Effects of Mass Permeability Improvement

50 Apt855 Dg
60In order to evaluate the effect of ground
improvement on the test embankment using SD
method, numerical analyses were performed in threecases as follows:
Case 1: Simulating the actual SD-improved area ofthe test embankment (20×60m (L×W))
Case 2: No SD-improvement
Case 3: Expanding the SD-improved area (length
and wide) for simulating the condition of actual
constructions (34×85m (L×W), i.e., the wholearea under the embankment down to the Apt5 layer)
In each case, based on the records on the actual
construction, the simplest construction history wasused (constant increasing the embankment thickness
at a rate of 2.35 cm/day). And as the same as theabove simulation and prediction, the effect ofimprovement by SD method was represented by thechange of mass permeability on the assumption that
the SD method is equivalent to improve permeability
100 times in comparison with the original soil.
Although the magnitude of the settlement duringinitial embankment loading is lowest in Case 2, alarge-scale circular slip extends suddenly to the deep
ground layers below the embankment center asshown in Figure 10, because the poor permeability
induces shear deformation under undrained
condition. From this result, it appears that ground
improvement by SD-method in this area waseffective in preventing catastrophic slip failure.
Case 3 resulted in most stability, particularly, ofthe deep peat layers, and early settlement
convergence. Figure 11 shows the settlement ofground surface for case 1 and 3. The residual
settlement starting at a point 2 years (assuming theentry into service) after embankment construction is
also illustrated in the lower figure. Expansion of theSD-improved area, particularly in the deep peat
layers, reduces lateral displacement due to undrained
shear deformation and settlement associatedtherewith. The total settlement is reduced by 55 cm

0
200 400 600
Pore water pressure u (kPa)

Settlement of ground surface (m)Fig. 7 Comparison of measured and simulated porewater pressures (about 1400 days after the entry ofembankment loading).
Right (Tana-side)-2 Left (Mukasa-side)0
2
4

Simulation

Measurement

119 days (06/05/31)
188 days (06/08/08)
302 days (06/11/30)
364 days (07/01/31)
End of consolidation

6
8
10
12
-200

-150

-100

119 days (06/05/31)
188 days (06/08/08)
302 days (06/11/30)
364 days (07/01/31)
-50

0

50

100

150

200

Displacement from the center of embankment (m)Fig. 8 Deformations of ground surface.
Horizontal displacement (m)
2

1

0
0

-1
0

10

10

20

30

Left (Mukasa-side)

Depth (m)

3

20

0

1

2

Measurement
119 days (06/05/31)
188 days (06/08/08)
302 days (06/11/30)
364 days (07/01/31)

30

Simulation

40

40

119 days (06/05/31)
188 days (06/08/08)
302 days (06/11/30)
364 days (07/01/31)
End of consolidation

50

50

Right (Tana-side)

Fig. 9 Horizontal displacements directly below theboth toes of slope
As examining in the previous chapter, the deep
peat layers (Apt5-8) in Mukasa area possess lower
127

GEOMATE-Nagoya, Nov.13-15, 2013

across the entire area of ground under theembankment. Furthermore, residual settlement was
reduced by approximately half due to the fact thatthe settlement approached convergence earlier.
However, because consolidation of the deep peat
layers also occurred earlier, deformation wasconcentrated in the upper peat layers, and upheavalof areas near the toe of the slope increased (Figure
omitted). As countermeasures for this problem
associated with expansion of SD-improved area, it
might be better to expanding the area and load of thecounterweight embankment and reducing the rate ofembankment loading, particularly in the initialstages.

Effects of Slow Banking Method
Table 1 shows the results of simulations
performed under the same conditions as Case 3
above, but with lower (1.5 cm/day) or higher (3.0
cm /day) rates of embankment loading. Reducing therate of loading allowed for greater drainage duringloading, which resulted not only in earlier
convergence of settlement and reduction in residual
settlement but also a slight but significant reduction
in total settlement.
Figure 12 shows the effect of loading rate to thelateral displacement at the ends of construction andconsolidation. The lower loading rate was effective
in reducing lateral displacement of the shallow
ground layers, and although the data is not presented
here due to space constraints, also upheaval of thesoil surface. And it resulted in an earlier shift fromoutward deformation to inward deformation in theembankment loading process.

Case 1: SD-improved 20×60m (End of consolidation)

Table 1 Effect of rate of embankment loading
Loading rate
(increase inembankment
thickness/day)
1.5 cm/day
2.35 cm/day
3.0 cm/day

Case2: No SD-improved (circular slip during loading)Total
settlement(m)

Residualsettlement
(cm)

11.7
11.9
12.0

74
87
94

Horizontal displacement (m)
3

2

1

0

0

0

10

10

20

20

-1

0

1

2

0

10

20

over 30(%)

Fig. 10 Effect of ground improvement by SD
method (distribution of shear strain).

30

1.5 cm/day
2.35 cm/day
3.0 cm/day

40

40

Solid: Enf ofconstruction
Dot: Enf ofconsolidation

50

50

Residual settlement (m)Settlement (m)Start ofEnd of loading resifural settlement measurement
0
1
2
3
4
5
6
7
8
9
10
11
12
13 -1
10
0

30
2 years
SD-improved area (L×W)
Case 1: 20×60m
Case 3: 34×85m
Difference of
total settlement
=55cm
0

10

Right (Mukasa-side)

2

1

10

Time (years) 10

Left (Tana-side)

Fig. 12 Horizontal displacements directly below theboth toes of slope (comparison of loading rate).

0.51Depth (m)Case 3: SD-improved 34×85m (End of consolidation)

Although construction of the test embankment
shown in Figure 6 was managed so that theembankment “height” generally increased at a rateof 3.0 cm/day, because obvious settlement occurred
during embankment construction, the actual rate ofloading per unit time (increase in embankment

87cm

1.5
159cm
2 -1
0
1
2
10
10
10
10
Time since start of residual settlement measurements (years)

Fig. 11 Comparison of SD-improvement area.
128

GEOMATE-Nagoya, Nov.13-15, 2013

“thickness”) was higher than that specified in any of
the above-mentioned simulations. Although nocatastrophic slip failure occurred, this rapid
construction
resultedinincreasedlateraldisplacement and upheaval.
As discussed above, slow embankment loading iseffective not only for increasing stability during
construction but also for reducing residual
settlement and impacts on the surrounding ground.
When it is not possible to secure adequate time forembankment construction, combinations with othercountermeasures such as vacuum consolidation
should be considered.

environment, the “disturbances” that might occur
during sampling and the heterogeneity among
samples. In this region, it is expected that theincrease in artesian pressure accompanying theincrease in soft ground thickness resulted in acontinuous low effective pressure in the deep ground.
Therefore, when a relatively high embankment wasconstructed on the ground, the stress states of evendeep layers exceed the consolidation yield stresseasily and rapid compressions were occurred. The
undrained shear deformation resulting from poor
permeability causes the large lateral displacement tooccur, which can lead in severe cases to slip failure.
Furthermore, because rapid compression occurs
even under drained conditions in peat layers,
permeability improvement using SD, reduction of
the loading rate, and the more drastic
countermeasure of reducing the load itself are
effective in increasing stability during loading,
reducing the deformation of the ground surrounding
the embankment, and reducing residual settlement
after the enter into service.

Effects of Lightweight Banking Method

Settlement (m)Embankment load (kpa)

Figure 13 shows the effect of weight reduction of
the existing embankment with lightweight materials.
For simplicity, the reduced loading was represented
by removal of the embankment in the calculation.
Greater reduction in loading was accompanied byless residual settlement and earlier occurrence ofsettlement convergence. Furthermore, although notshown here, it was demonstrated that greater
reduction in loading resulted in reduced inward
deformation of the ground surrounding theembankment.
Based on these simulations, the culvert in actual
construction site has been designed with a 1.2-m
freeboard, and in order to reduce differential
settlement, the material of the embankment in thevicinity of the culvert is planned to be replaced withlightweight material.

REFERENCES[1] Inagaki, M., Sakakibara, K., Yamada, K.,
Tashiro M, Noda T, Nakano A and Asaoka A,“Estimation of the initial conditions of a very
soft peat ground which causes large delayed
settlement due to test embankment loading”,
45th Japan National Conf. on GeotechnicalEngineering, 2011, pp.751-752 (in Japanese).
[2] Asaoka A and Noda T, “All soils all states allround geo-analysis integration”, Int. Workshop
on Constitutive Modeling - Development,
Implementation, Evaluation, and Application,
Hong Kong, China, 2007, pp.11-27.
[3] Noda T, Asaoka A and Nakano M, “Soil-water
coupled finite deformation analysis based on a
rate-type equation of motion incorporating the
SYS Cam-clay model”, Soils and Foundations,Vol.48. 6, 2008, pp.771-790.
[4] Asaoka A, Noda T, Yamada E, Kaneda K and
Nakano M, “An elasto-plastic description of
two distinct volume change mechanisms ofsoils”, Soils and Foundations, Vol. 42. 5, 2002,
pp.47-57.
[5] Inagaki M, Nakano M, Noda T, Tashiro M andAsaoka A, “Proposal of a Simple Method for
Judging Naturally Deposited Clay Grounds
Exhibiting Large Long-term Settlement due toEmbankment Loading”, Soils and Foundations,Vol.50.1, 2010, pp.109-122.
[6] Tashiro M, Noda T, Inagaki M, Nakano M andAsaoka A, “Prediction of Settlement in Natural
Deposited Clay Ground with Risk of Large
Residual Settlement due to Embankment
Loading”, Soils and Foundations, Vol.51.1,
2011, pp.133-149.

400
300
200
100
0
Reduction in load
0 kPa (Current state)
54 kPa (lightweight banking)
79 kPa (replace with curvert)
105 kPa

2
4
6
8
10
12
10

-1

10

0

10

1

2

10

Time (years)

Fig. 13 Effect of weight reduction of the existingembankment.
CONCLUSION
In this paper, simulations of the large-scale
settlement in excess of 11 m and predictions of
future settlement of ultra-soft ground containing peat
due to loading by a test embankment were
performed by deducing the initial in-situ conditionsof ground considering the effect of the depositional
129

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SEISMIC RESPONSE ANALYSIS OF GEOTECHNICALSTRUCTURES BUILT OF CEMENT-TREATED DREDGED SOIL
1

Takayuki Sakai 1, Masaki Nakano2 and Shotaro Yamada3
Disaster Mitigation Research Center, Nagoya University, Japan;
2,3
Civil Engineering, Nagoya University, Japan

ABSTRACTIn this study, firstly, the mechanical properties of cement-treated soil are comprehended through laboratory
tests. Secondly, the mechanical test results are reproduced by using an elasto-plastic constitutive model based on
the action of the soil skeleton structure, SYS Cam-clay model to determine material constants and to interpret thetreatment principle based on concept of soil skeletal structure. Finally, seismic response analysis of geotechnicalcement-treated structure is carried out through a soil-water coupled finite deformation analysis code, GEOASIA.
The new findings are summarized as follows; 1) The effective stress path of the cement-treated soil
approached the tension cut-off line as the cement content is large and confining stress is low. 2) The cementtreated soil can be regarded as a highly structured and heavily overconsolidated soil. 3) In the case of this study(the treated soil with a cement content of 50kg/m3), the cement-treated geotechnical structure does not exhibit
failure, a large deformation by earthquake, and a long-term deformation occurs partition bank after earthquake.
Keywords: cement soil stabilization, mechanical property, seismic response analysis, dredged soil

INTRODUCTION

is widely used for improvement of dredged soil. In
this method, the cement-treated soil must havesuitable fluidity and strength. The unconfinedcompressive with strength in curing 28days should
be more 100kPa, and flow value should be 90100mm. In the result of design of mixture, watercontent of dredged soil is w=120% and cement
content is of C=50kg/m3. Compared with thespecimen of C=50kg/m3, the specimens of cement
content is C=30, 70 kg/3 are made.

About 1.0 million m3 of dredged soil is produced
annually in Nagoya Bay. However, the temporarystorage capacity for the soil at Nagoya Port Island islimited, so effective use of the soil has become apressing issue. A method of the effective use is toimprove the dredged soil by adding cement to use asa geomaterial. Currently, a lot of cement-treated soil
is used for reclamation, backfilling and surface
stabilization in the bay area. However, cementtreated geotechnical structures are almost designed
by unconfined compression strength. Besides,
seismic stability of these structures has not been
examined.
In this study, firstly, the mechanical properties of
cement-treated soil are comprehended throughlaboratory tests. Secondly, the mechanical test
results are reproduced by using an elasto-plastic
constitutive model based on the action of the soil
skeleton structure, SYS Cam-clay model as in [1] todetermine material constants and to interpret thetreatment principle based on a concept of soil
skeleton structure. Finally, seismic response analysis
of cement-treated structures is carried out through asoil-water coupled finite deformation analysis code,
GEOASIA as in [2].

400

300
200
100
0
0

Deviator stress q (kPa)

Deviator stress q (kPa)

C=30kg/m3

600

5
10 15 20
Axial strain a (%)

C=50kg/m3

400
200
0
0

q=3p
300
200
100
0
0
100
200 300400
M ean effective stress p (kPa)25

Deviator stress q (kPa)

Deviator stress q (kPa)

400

600
400
200

5 10 15 20
Axial strain a(%)

600

300

5
10 15 20
Axial strain a (%)

25

Deviator stress q (kPa)

Deviator stress q (kPa)

200

400

600

900

C=70kg/m3

0
0

0
0

Mean effective stress p (kPa)

900

MECNANICAL BEHAVIOR OF CEMENTTREATED SOIL

q=Mp

q=3p

q=Mp

600

300

0

0
300
600
900
M ean effective stress p (kPa)

Improved soil
Dredged soil

The Pneumatic Flow Method was adopted as asoil improvement method in this study. This method

Fig. 1 Triaxial test results for cement-treated soil
130

GEOMATE-Nagoya, Nov.13-15, 2013

Figure 1 shows the test results for the CU triaxial
tests for the cement-treated soils. For the specimenof C=30 and 50kg/m3, an increase in deviator stressq associated with a reduction in mean effective
stress p’ is seen before peak q. Also, a reduction in q
associated with a reduction in p’ is seen after peakstrength. This behavior is similar to the one soft
natural deposited clay. Peak strength of C=50kg/m3
is higher than C=30kg/m3. For cement content of
C=70kg/m3, the peak of q appears clearly and thestiffness is very high. The peak of C=70kg/m3 is thehighest of all the cement-treated soils. The effective
stress path goes up to almost vertical in the
beginning of shearing. From the above, the peak of q
increases as the cement content increases. The
effective stress path of the cement-treated soil
approaches the tension cut-off line as the cement
content is large and confining stress is low.
Especially, the results of cement content C=70kg/m3 under confining pressure 100kPa shows q
becomes large along the tension cut-off line. This isspecial behavior of cement-treated soil of highcement content.
Figure 2 shows the result of oedometer tests forthe cement-treated soils and a dredged soil. A
compression line of the cement-treated soil islocated above a compression line of the dredged soil.
As the cement content increases, the consolidation
yield stress increase and compression value
decreases up to consolidation yield stress. But, highcompressibility appears when the consolidation yieldstress is exceeded.

behavior of remolded samples of treated soil. Figure
3 shows the results of reproducing mechanicalbehavior of remolded treated soil of each cement
content. The solid line shows result of calculationand the dotted line shows results of laboratory test.
The mechanical behavior of each remolded treatedsoils is reproduced by the SYS Cam-clay model. The
elasto-plastic parameters are determined by the
reproduction is shown in Table1. Elasto-plastic
parameters change with cement content. Therefore,
it can be seen that the cement-treated soil becomes
the different materials according to cement constant.
As the cement content increases, compression index
and NCL intercept (98.1 kPa) increase especially.

400

200

0

10
Shear strain

Deviator stress q (kPa)
0

10Shear strain

3.2
4.0
3.6

2.6

3.2

Specific volume v

3
2.8

2.4
2.2

10

10

10

10

3

10

4

q = Mp
400

200

20

0
200
400
600
M ean effect ive stress p (kPa)

s (%)

Test

1.6
0
10
2

0
200
400
600
M ean effect ive stress p (kPa)

2.4

1.8
1

200

2.8

2.0

0

600

Calculation

2

1.6
-1
10

400

q = Mp

600

200

200

M ean effect ive stress p (kPa)

400

20
s (%)

400

3.4

200

600
Deviator stress q (kPa)

Deviator stress q (kPa)
Deviator stress q (kPa)

3.6

400

0

200

0

q = Mp

20
s (%)

400

600

4

v

10
Shear strain

600

3.8

Specific volume600
Deviator stress q (kPa)

Deviator stress q (kPa)

600

1

10

2

10

3

10

4

10

5

10

Vertical stress v (kPa)

5

10

Fig. 3 Reproducing
remolded treated soil

Vertical stress v (kPa)
Improved soil(C=30kg/m3)
Improved soil(C=50kg/m3)
Improved soil(C=70kg/m3)
Dredged soil

mechanicalbehaviorof

Table 1 Elasto-plastic parameters
Plasticity parameters

Fig. 2 Oedmeter test for cement-treated soil

C=30

Cement content (kg/m3)
Compression index
Swelling index
Limit state constant
NCL intercept
Poisson’s ratio

REPRODUCING MECHANICAL BEHAVIOR
OF CEMENT-TREATED SOIL BY SYS CAMCLAY MODEL
The past study as in [3] shows elasto-plastic
parameters are obtained by reproducing mechanical
131

λ
κ
M
N
ν

0.21
0.05
1.70
2.70
0.30

Treated soil
C=50
C=70
0.36
0.05
1.60
3.40
0.30

0.51
0.03
1.65
4.20
0.30

GEOMATE-Nagoya, Nov.13-15, 2013

400

200

0

10
Shear strain

400

200

20
s (%)

600

400

200

0

10
Shear strain

q = Mp

200

20
s (%)

0
200
400
600
M ean effective stress p (kPa)

1000

800
600
400
200
0

10
Shear strain

0
200
400
600
M ean effective stress p (kPa)

400

Deviator stress q (kPa)

1000
Deviator stress q (kPa)q = MpDeviator stress q (kPa)

Deviator stress q (kPa)

600

20
s (%)

q = Mp800

SEISMICRESPONSEANALYSISOFGEOTECHNICAL STRUCTURES BUILT BY
PNEUMATIC FLOW METHOD

600
400
200

In this section, the seismic response analysis of apartition bank. The partition bank was constructed in
the Third Port Island in Nagoya Port through the
Pneumatic Flow Method to prevent contaminationfrom spreading. The partition bank is not an eternal
structure because the partition bank is buried by
dredged soil in the future. Therefore, its function is
not lost by a settlement and a deformation of thebank, and its stability problem is important.
Figure 5 shows a cross-section of the partitionbank and seabed ground used in the analysis. The
seabed ground is modeled in reference to boring
investigation.
The bank is 10m in height with the slopes of
1:1.5. Its crown is 14m in width. The reclamation of
the dredged soil on the west of the bank is 10m inheight and on the east 16m in height. The hydraulicboundary conditions are as shown in Fig. 5; theedges on the left, right and bottom are impermeableboundaries, and the top edge is a permeableboundary (atmosphere). Also, the water level is

0 200 400 600 800 1000
M ean effective stress p (kPa)Calculation

3.8
Specific volume v

increased, reproducibility goes down.. Especially, it
is difficult to reproduce softening behavior withplastic compression above critical state line. Table 2
shows evolution rule parameters and initial values
for this calculation. The cement-treated soil can be
regarded as a highly structured and heavily
overconsolidated soil. It can be seen that large
deformation is caused when cement-treated soil
decays structure and loses overconsolidation. The
overconsolidation ratio increased as the cement
content increased, on the other hand, the degree ofstructure reduced. Evolution ruleparameterschanges by cement constant. As the cement content
increases, the rate of change of the evolution of
structure and overconsolidation increases.

600
Deviator stress q (kPa)

Deviator stress q (kPa)

600

3.4

Test

3.0

2.6
10

0

10

1

10

2

Vertical stress

3

10

4

10

5

10

v (kPa)Fig. 4 Reproducing mechanical behavior of cementtreated soil
Table 2 Evolution rule parameters and Initial values
Plasticity parameters

Cement content (kg/m3)

C=30Evolution rule parameters
Normal consolidated soil indexm0.01
Structure degradation index
a
0.25
b
1.00
c
1.00
Plastic shear:plastic compression cs
0.20
Rotation hardening index
br0.00
Rotation hardening limit index
mb
0.50
Overconsolidation ratio
Extent of structure
Vertical stressSpecific volume
Stress ratio
Initial anisotropy

Initial values
1/R0
1/R0⃰
σv
v0
η0
ζ0

1.03
260
19.6
3.94
0.00
0.00

Treated soil
C=50
C=70
0.60
0.60
1.00
1.00
0.50
0.00
0.50

5.00
1.50
1.00
1.00
0.10
0.00
0.50

20.9
10.00
19.6
3.75
0.00
0.00

63.8
5.00
19.6
3.80
0.00
0.00

The mechanical behaviors of the cement-treatedsoils are reproduced using obtained elasto-plastic
parameters. Figure 4 shows the results ofreproducing mechanical behavior of cement-treatedsoil. The solid line shows result of calculation andthe dotted line shows results of laboratory test. The
mechanical behavior of each cement-treated soils is
reproduced mostly. However, as the cement content

always constant at the ground surface. In otherwords, the ground and embankment are always
saturated. The movement boundary conditions
before the earthquake are as follows: all the nodes
on the left and right edges are fixed horizontally, andall the nodes on the bottom surface are fixedhorizontally and vertically. During and after theearthquake, the boundary condition which gives
simple shear deformation to the finite elements of aside boundary as in [4] was set to both lateral sidesof the ground. In addition, in order to prevent allreflections of the seismic waves, a viscous boundary
as in [5] is provided in the horizontal direction on
the bottom edge during the earthquake.
132

GEOMATE-Nagoya, Nov.13-15, 2013

AcL
Elasto-plastic parameters
Compression index
λ
0.18
Swelling index κ
0.019
Limit state constantM
1.60
NCL intercept N
2.22
Poisson’s ratio ν
0.30
Evolution rule parameters
Normal consolidated soil indexm3.00
Structure degradation index
a
0.30
b
1.10
c
1.00
Plastic shear:plastic compression cs
0.40
br
Rotation hardening index
0.00
mb
Rotation hardening limit index
1.00
Overconsolidation ratio
Extent of structure
Specific volume
Stress ratio
Initial anisotropy

Initial values
1/R0

η0

1/R0⃰
v0
ζ0

As

AcU3

0.05
0.0002
1.1
1.95
0.30

0.18
0.019
1.60
2.22
0.30

0.12
5.00
1.00
1.00
1.00
3.00
0.90

3.00
0.30
1.10
1.00
0.40
0.00
1.00

distribution depending onearth pressure
4.00
2.00
5.00
2.20
1.84
2.30
0.23
0.23
0.23
0.00
0.23
0.00
AcU2
AcU1
Bc
Elasto-plastic parameters

Compression index
λ
0.18
0.18
0.18
Swelling index κ
0.019
0.019
0.019
Limit state constant
M
1.60
1.60
1.60
NCL intercept N
2.22
2.22
2.22
Poisson’s ratio ν
0.30
0.30
0.30
Evolution rule parameters
Normal consolidated soil index
m
3.00
3.00
3.00
Structure degradation index
a
0.30
0.30
0.30
b
1.10
1.10
1.10
c
1.00
1.00
1.00
Plastic shear:plastic compression cs
0.40
0.40
0.40
br
Rotation hardening index
0.00
0.00
0.00
mb
Rotation hardening limit index
1.00
1.00
1.00
Initial values
Overconsolidation ratio
1/R0
distribution depending onearth pressure
Extent of structure
1/R0⃰
7.00
9.00
20.0
Specific volume
v0
2.40
2.5
2.80
Stress ratio
η0
0.23
0.23
0.00
Initial anisotropy
ζ0
0.00
0.00
0.00

Tabale 2 shows material constants and initialvalues of seabed ground. Material constants andinitial value are obtained by reproducing mechanicalbehavior of seabed soils as in [6]. AcU layer is very
soft clay, As layer is rather dense sand and AcL
layer is rather soft clay. The material constant ofpartition bank is the ones of cement-treatedsoil(C=50kg/m3). Figure 6 shows input seismic wave.
The input seismic wave is Tokai-Tonankai-Nankai
multiple-segment type earthquake as in [7]. This
analysis intends for construction of partition bank,reclamation, consolidation after construction, to
input seismic wave and consolidation after theearthquake byusing GEOASIA. Process ofconstruction of partition bank and reclamation of thedredged soil is the same as a real construction
history generally. After 20 years finishingconstruction, the seismic wave is inputted into theground finish construction after 20 years. . The
calculations are carried out under the conditions ofplane strain over the entire cross-section.
Horizontal Acceleration (gal)Table 3 Material constants of seabed ground for thiscalculation

400
300
200
100
0
–100
–200

max: 308.26 [gal]min:–236.98 [gal]

–300
–400
0

50

100

Fig. 6 Input seismic wave
Figure 7 shows the shear strain distribution
before and after the earthquake, 12 years after theearthquake and end of calculation. The bank does
not exhibit failure, while a long-term deformation

Fig. 5 A cross-section of the partition bank and seabed ground used in the analysis
133

150

Time (sec)GEOMATE-Nagoya, Nov.13-15, 2013

Settlement

PointC(m)occurs after earthquake. The largest shear strain
occurs at the layer of dredged soil under the partitionbank, while the shear strain due to the earthquake
does not extend at the partition bank. After theearthquake, the shear strain on the boundary
between the embankment and the ground increases.
PointD

PointB

Elm.1

PointA

1
0.5
0
-0.5
-1
-1.5
-2
-2.5
-3
-3.5
-4
0

PointA

PointC

PointB

PointD

50

100

150

Time t (sec)

Settlement(m)

Immediately before the earthquake

Immediately after the earthquake

1
0.5
0
-0.5
-1
-1.5
-2
-2.5
-3
-3.5
-4
0

50000

100000150000200000Time (day)End of calculation

40

20

0

Shear strain distribution
Pore water pressure u (kPa)

Figure 8 shows settlement during and after
earthquake. The amount of settlement at the crown isabout 1.5m. After the earthquake, settlement
progressed in the long term and about 3.2m
settlement occurred finally. Settlement of only
partition bank is about 1.0m. In the west, partitionbank and reclamation soil swelled during earthquake
and the amount of settlement was smaller than east
finally.
Figure 9 shows the mechanical behavior of theelement 1 in Figure 7. The mean effective stress of
cement treated soil decreased by shearing repeatedly
due to the earthquake, and the shear strain
progresses to around 15%. For the degree ofstructure and overconsolidation, the cement treatedsoil does not lose structure and overconsolidation.
Therefore, the cement treated soil keep stability andthe partition bank is not failure by the earthquake.

10
20
Shear strain s (%)

20

0
20
40
M ean effective stress p (kPa)

200

100

0

10
20
Shear strain s (%)

3.8

3.6

1.0

0.5

0

NCL

4.0

3.4
0
20
40
M ean effective stress p (kPa)

30

1.0

R

q = Mp40

30

R*Fig. 7

Settlement

Deviator stress q (kPa)

Deviator stress q (kPa)

Fig. 8Specific volume v (=1+e)

After 12years the earthquake

10
20
Shear strain s (%)

30

0.5

0

10
Shear strain

20

30

s (%)

During reclamaion
During the earthquake
After the earthquake

Fig. 9134

Element behavior of cement-treated soil

GEOMATE-Nagoya, Nov.13-15, 2013

overconsolidation. However, cement-treated soil
does not lose structure and overconsolidation.
Therefore, the cement-treated soil keep stability and
the Partition bank is not failure by the earthquake.

CONCLUSION
In this study, firstly, the mechanical propertiesof cement-treated soil are comprehended. Secondly,
the mechanical test results are reproduced by using
an elasto-plastic constitutive model based on theaction of the soil skeleton structure, SYS Cam-claymodel to interpret the treatment principle based on
concept of soil skeletal structure. Finally, seismic
response analysis of cement-treated structures iscarried out through a soil-water coupled finite
deformation analysis.
The following are the conclusions obtained
from this study.
1) The mechanical behavior of cement-treatedsoil is similar to soft natural deposited clay. In otherwords, the behavior of cement-treated soil shows
like behavior of overconsolidated and highstructured soil. The increase in peak strength andstiffness associated with the increase in cement
content. Especially, cement-treated soil with C=50kg/m3 shows clear improved effect. The effective
stress path of the cement-treated soil approached thetension cut-off line as the cement content is large
and confining stress is low.
2) The mechanical behavior is reproduced by the
SYS Cam-clay model. It is difficult to reproduce
softening behavior with plastic compression above
critical state line. The obtained parameters shows the
cement-treated soil can be regarded as a highly
structured and heavily overconsolidated soil. The
overconsolidation ratio increased as the cement
content increased, on the other hand, the value ofstructure reduced. Also, the compression index and
the NCL intercept (98.1 kPa) increase and the rate ofchange of the evolution of structure andoverconsolidation increases. The cement-treated soil
becomes the different materials according to cement
constant.
3) In the case of this study (the treated soil witha cement content of 50kg/m3), the partition bankdoes not exhibit failure, and a long-term deformation
occurs after earthquake. A characteristic of thecement-treated soil is that large deformation iscaused when cement-treated soil loses structure and

REFERENCES[1] Asaoka A., Noda T., Yamada E., Kaneda K. andNakano M. 2002. “An elasto-plastic descriptionof two distinct volume change mechanisms ofsoils” Soils and Foundations Vol. 42, No. 6,
2002, pp.47–57.
[2] Noda T., Asaoka A. and Nakano M. “Soilwater coupled finite deformation analysis basedon a rate-type equation of motion incorporating
the SYS Cam-slay model” Soils andFoundations Vol. 48, No. 6, 2008, pp. 771–790.
[3] Yamada, S., Nakano, M., Noda, T., Horiuchi, S.,
and Yoda, H., Sasayama, T. “Mechanicalbehaviour of cement-treated soil and remolded
cement-treated soil and simulation of that by
SYS Cam-clay model”, 45th Japan National
Conf. on Geotechnical Engineering, 2011,
pp.643-644 (in Japanese).
[4] Yoshimi, Y. and Fukutake, K., “Physics andevaluation technology of soil liquefaction
including mitigation method”, 2005, GihodoShuppan. (in Japanese)[5] Joyner W.B., Albert T. and Chen F.
“Calculation of nonlinear ground response inearthquakes. Bulletin of the SeismologicalSociety of America” Vol. 65, No. 5, 1975, pp.
1315–1336[6] Sun. K, “Seismic analysis of reclaimed groundwith dredged soil and effective utilization ofdredged soil treated stabilizers”, Docter
Dissertation, Department of Civil Engineering,
Nagoya University, Nagoya, Japan. (inJapanese), 2010, pp.43-53.
[7] Central Disaster Prevention Council Cabinet
Office, Government of Japan, Published data of
Tohnankai-Nankai earthquake,2004

135

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DEVELOPMENT OF SPH METHOD WITH AN ELASTO-PLASTICCONSTITUTIVE MODEL CONSIDERING SOIL SKELETONSTRUCTURE AND ITS APPLICATION TO EXCAVATION PROBLEMS
Hideto Nonoyama1, Masaki Nakano1 and Toshihiro Noda2
Department of Civil Engineering, Nagoya University, Japan;
2
Disaster Mitigation Research Center, Nagoya University, Japan
1

ABSTRACT
In order to solve large deformation problem of geomaterials, the SPH method is used which is a kind ofparticle method based on the mesh-less Lagrangian scheme. The method can solve large deformation problems
without mesh distortion. Moreover, it can handle the governing equations and existing constitutive models for
geomaterials based on a continuum mechanics. To express various states of the soil, the elasto-plastic
constitutive model taking account of soil skeleton structure is introduced into the method. In this paper, theexcavation problems from loose to dense sand ground are simulated. In order to determine the material
parameters and initial value of the evolution rules, a simulation of simple shear test is carried out. From a seriesof the numerical results, it is demonstrated that the different deformation behaviors for sand ground can be
described by the states of soil.
Keywords: SPH method, Elasto-plastic Constitutive Model, Excavation Analysis

interesting achievements have been published (e.g.,[3]). However, since the geomaterial is assumed to
be an elastic or elastic-perfectly plastic material inmany researches using the SPH method, it isnecessary to introduce the high performance elastoplastic constitutive model to describe complicateddeformation behavior of geomaterial precisely. In
this study, the elasto-plastic constitutive model
taking account of soil skeleton structure [4], [5] isintroduced into the SPH method.
In this paper, firstly, basic theory of the SPH
method and formulation of the SPH method basedon solid mechanics are summarized. Then, theexcavation problems from loose to dense sandground are solved. In order to determine the material
parameters and initial value of the evolution rules, asimulation of simple shear test is carried out. From aseries of the numerical results, the effectiveness of
the SPH method with the constitutive model of highperformance is demonstrated.

INTRODUCTION
In the field of geotechnical engineering, theinfinitesimal deformation theory and the finite
deformation theory have been widely used inconventional deformation analysis of geomaterials.
These theories have been successfully implemented
in several numerical methods, such as the finite
element method (FEM). As a result, it is now
possible to predict a variety of geomaterial
deformation behaviors. However, there are still
difficulties in large deformation analysis. It istherefore difficult to solve the entire deformation
process, from the initial state to subsequent large
deformations. In conventional methods such as theFEM, numerical instabilities arise in the large
deformation region due to mesh distortion. In thelarge deformation problems, important problems
such as slope failure and lateral flow of liquefied
ground are included from the engineering viewpoint.
To solve such problems, various numericalapproaches have been proposed.
In this study, in order to solve large deformation
problem of geomaterial, the Smoothed Particle
Hydrodynamics (SPH) method [1], [2], a kind ofparticle method based on the mesh-less Lagrangian
scheme, is used. The method can solve large
deformation problems without mesh distortion.
Moreover, it can handle the governing equations andexisting constitutive models for geomaterials, since
it is based on a continuum approximation. The
method has already been used to solve many typesof geotechnical problems, and a number of

NUMERICAL METHOD
Basic Theory of the SPH Method
In the SPH method, an object is expressed as an
assembly of particles. If the motions of the particles
are solved individually, the deformation behavior of
the continuum cannot be represented by thistechnique. In order to treat an object as a continuum,a unique interpolation theory is used. This
interpolation
theoryincludestwo
key
approximations: a kernel approximation and a
136

GEOMATE-Nagoya, Nov.13-15, 2013is possible to calculate any physical quantity and its
special derivative of a physical quantity.

particle approximation. The first step is a kernel
approximation of the field functions. The kernel
approximations are based on neighboring particles βlocated at points xβ within the support domain κdh ofa smoothing function W for a reference particle α
located at point xα, as shown in Fig.1. In the firststep of the interpolation, we define a smoothed
physical quantity <f(xα)> for the physical quantityf(xα) at the reference particle α as follows,( )f x α = ∫ f ( x β )W (r , h)dx β

SPH Method Based on the Solid Mechanics
The governing equations used in this study arebased on solid mechanics. The equation ofcontinuity and the equation of motion can be defined
as follows,(1)Ω

where r = |xα‐xβ|, h is the radius of the influence
domain, and Ω is the volume of the integral that
contains xα and xβ.
In the second step of the interpolation, thephysical quantity <f(xα)> for the reference particle α
is expressed as the summation of the distribution of
the assumed physical quantities f(xβ) for eachparticle. Thus, the physical quantity can be
expressed in terms of N discrete points:( )N

f xα = ∑
β

mβ

ρ

β

( )

f x β W αβ∂udρ
= −ρ idt∂xi(4)

dui 1 ∂σ ij
=
+ Fi
dt
ρ ∂x j(5)where u i is the velocity vector, ρ is the density, σ ij isthe stress tensor and F i is the external force vector.
Applying the SPH interpolation theories, theequations are expressed as follows,
N
dρ α
∂W αβ
= −∑ m β uiβ − uiα
dt
∂xi
β

(

)

N
 σα
 ∂W αβσβduiα= ∑ m β  ij 2 + ij 2 − δ ij Π αβ 
+ Fiα
β
 ρα
 ∂x j
dt
β
ρ



(2)

( ) ( )

where mβ is the mass, and ρβ is the density ofneighboring particles β. N is the numbers ofneighboring particles in the support domain, andWαβ is the smoothing function that expressed thecontribution from the neighboring particles β to thereference particle α. In this study, Cubic spline
function [6] is used.

rβFig. 1

(

( )

λ −κ
D=
M(1 + e 0 )

α

N

mβ

(9)

where M is the critical state parameter, D is thedilatancy parameter, p' is the mean effective stress,
η(=q/p') is the stress ratio, q is the deviatoric stress,
R is the inverse of degree of overconsolidation ratio,p
R* is the inverse of degree of structure, ε v is theplastic volume strain, λ is the compression index, κis the swelling index and e 0 is the initial void ratio.
The ~p0′ is found to be the mean effective stress on
the modified Cam-clay yield surface that coincides
with the initial mean effective stress p0′ of the soil in
the reference state. The anisotropy is not taken into
account in this study. Then, the evolution rules for
sub and super loading defining the soil skeleton
structures are expressed as follows, respectively:αβ( ) ∂W∂x

f xβ

(3)
∂xi
ρ
β
i
Based on the two-step interpolation procedure, it
β

)

κdh

An image of basic concept of the SPH
method.

= −∑(8)

MD ln R ∗ − ln R − ε vp = 0Ω

Equation (2) is a formula for evaluating aphysical quantity via the SPH method. It is also
possible to approximate the spatial gradient of aphysical quantity in a similar way, using the spatial
derivative of the smoothing function. The spatial
derivative of Eq. (2) can be written as∂ f xα(7)where δ ij is the Kronecker’s delta, Παβ is theartificial viscosity used to decrease the numericalinstability. In this study, an artificial viscosity
introduced in an earlier study [7] is employed.
In order to describe the complex behavior ofsoils, the Super-subloading Yield Surface Modified
Cam-clay model [4], [5] are used as follows,p′
M2 +η 2f ( p′,η ) = MD ln ~ + MD ln
+
p0′
M2

W

(6)

137

GEOMATE-Nagoya, Nov.13-15, 2013

, U =−mln R
D＜elasto-plastic parameters＞

2 p
Ds  ,
R * = U * (1 − cs ) − Dvp + cs
3


b
c
a
U * = R* 1 − R*
D((

Table 1 Material parameters

(10)

)

(11)

)

where
is the norm, D p is the plastic stretching,
Dvp and Dsp are the volume and deviation componentsof plastic stretching. U and U* are the positive scalarfunctions of R and R*. The parameter groups for theevolution rules in Eqs. (10), (11) all consists ofconstants, and from their respective functions wemay call m the degradation index ofoverconsolidation, a, b, c, c s the degradation indicesof structure.

compression index

λ

0.050

swelling index

κ

0.012

critical state constantM

1.0

NCL intercept

N

1.98

Poisson's ratio

ν

0.3＜evolution parameters＞
degradation index of overconsolidation

m

0.06

degradation index of structurea2.2

degradation index of structureb, c, cs

1.0

1

2

3

4
39.65

Table 2 Initial values
Case

NUMERICAL RESULTS＜initial value＞
initial degree of overconsolidation

1/R0

1.25

4.23

6.58

initial degree of structure

1/R0*

73.62

2.84

2.01

1.13

initial specific volume

v0

2.08

1.91

1.88

1.79

initial mean stress

Determination of Material Parameters and Initial
Values of the Evolution rules

p0[kPa]294

Figure 3 shows obtained (a) shear stress - shear
strain relation, (b) stress paths, (c) R - shear strain
relation and (d) R* - shear strain relation at the centerof the specimen.
In the case 1 for a loose sand, q increased whilewith decreasing p, then q exhibits the peak. After
that, p and q move toward zero. In the case 2 for a
medium dense sand, after reducing q, q increased
again, accompanied by an increase in p. In the cases
3 and 4 for dense and very dense sand, q did notdecrease, and q increased with the increase of p. The
decay of the structure with shearing occurs, and its
gradient for loose sand is greater than that for dense
sand as shown in Fig. 3(d).
From these numerical results, although it is aconstant volume condition, it is possible to simulate
the shear behaviors of loose and dense sand using
the SPH method, shown in the previous research [8].

In order to determine the material parameters andinitial values of the evolution rules, a simulation of
simple shear test under plane strain condition iscarried out using the SPH method considering thesoil skeleton structure. Figure 2 illustrates thenumerical model used in the simulation. As thefigure indicates, the specimen is a square object (10cm by 10 cm), and a virtual area surrounded thespecimen to prevent errors at the free surface. The
solid line denotes the initial configuration of thespecimen, and the dashed line denotes theconfiguration after deformation. In the simulation,
the virtual area is forcibly deformed with a constantdisplacement to represent simple shear conditions,and the deformation of the specimen is calculated.
The parameters used in this simulation aresummarized in Tables 1 and 2. Four different cases(case1: loose sand, case2: medium dense sand,case3: dense sand, case4: very dense sand) areconsidered in this simulation. Also, parameters oftypical sand under constant mean stress and four
different values of the initial degree ofoverconsolidation, structure and the initial specificvolume are utilized.

400

400

[4]

Deviator stress q [kPa]

350

350
Deviator stress q [kPa]R = U D p

300

[3]

250
200
150

[2]

100
50
0

5

10

15

250

[3]

200
150

[2]

100
50 [1]

[1]
0

[4]

300

0

20

0

50 100 150 200 250 300 350 400

Shear strain γxy [%]

γxy

10

(b)

1.2

1.2

1

1

[1]

0.8
R

y

x

Mean stress p [kPa]

(a)

vx

[2]
[3]

0.6
0.4

Center axis

[4]

10

0.2
Measurement point
for stress and strain

Virtual area

Fig. 2

Specimen0

Unit:cm

Fig. 3

Numerical model.
138

[4]

[3] [2] [1]

0.8
R*

10

10

10

10

0.6
0.4
0.2

0

5

10

15

20

0

0

5

10

15

Shear strain γxy [%]Shear strain γxy [%]

(c)

(d)

Numerical results.

20

GEOMATE-Nagoya, Nov.13-15, 2013

and after excavation. Figure 8 shows the time history
of R at points C and D after excavation. Figure 9shows the distribution of accumulation of the
maximum shear strain (γ max = (ε 1 - ε 2 )/2) atdifferent times for cases 1 to 4, respectively. Figure
10 shows the distribution of the overconsolidation
ratio after excavation (0, 900s) for cases 1 to 4,
respectively. Boundary particles were used for thewall, but are not shown in these figures.
Before excavation, in the case 1 for loose sand, it
was found that the structure decayed along with thecompression of the ground in the initial stage ofstatic analysis as shown in Figs. 5(a) and 6(a). On
the other hand, in the cases 2 to 4 for medium dense,
dense and very dense sand, it was found that thecompression of the grounds were not larger than oneof case 1 in the stage of static analysis. For after
excavation, the time of failure was different in eachcase as shown in Fig. 9. In the case 1, a slope failure
was occurred immediately after excavation. Also, inthe cases 2 and 3, a slope failure was occurred withthe progression of time. In the case 4, a slope failure
didn’t occur.
As the cause of these results, it was shown thatthe structure of loose sand can easily decay (R*→1.0) compared with dense sand as shown in Fig. 3(d).
Also, the ground was highly structured soil in thissimulation as shown in Fig. 6(b), and the loss ofoverconsolidation (R→1.0) occurred after the decayof the structure (R*→1.0) as shown in Figs. 6 and7(b). Then, the slope failure occurred because thestate of ground changed from overconsolidation
state to normal state. In the case 1, as the results offocusing on the time history of R at the failure point(Points B and C), the state of ground reached thenormal state as shown in Figs. 7(b) and 8(a). Also, atthe non-failure point (Point D), the state of groundremained the overconsolidation state as shown in Fig.
8(b). On the other hand, in the cases 2 and 3, it was
confirmed that the time of failure was slower thanthe case 1, because the structure was less likely todecay than loose sand as shown in Fig. 6. In thecases 2 and 3, as with the case 1, the state of groundreached the normal state at failure point (Point B),
and the state of ground remained theoverconsolidation state at the non-failure point(Points C and D) as shown in Figs. 7 and 8. In thecase 4, although the decay of the structure occurred
after excavation, the state of the ground remains theoverconsolidation state and the slope failure didn’t
occur because the loss of the overconsolidation
didn’t occur. As shown in Fig. 10, it could be seenthat the loss of the overconsolidation at the ground,which is in the overconsolidation state after
excavation, occurred along with the slope failure,
and the state of the failure part changes normal state.
From a series of the numerical results, thedifferent deformation behaviors from loose to dense
sand are obtained qualitatively. With the

Excavation Analysis from Loose to Dense Sand
GroundAn excavation analysis from loose to dense sandground is carried out, using the SPH method
considering the soil skeleton structure. In thissimulation, the depth of the initial ground is 9m andthe width is 20m. After excavation, the slope heightis set to be 4.5m and slope angle is set at an
inclination of 1H: 2V. Figure 4 illustrates thenumerical model in this simulation. As the figure
shows, the time histories of displacements at the topof the slope (point A), R (points B, C, D), R* (pointB) are checked. The material parameters and initialvalues of the evolution rules determined by thesimple shear simulation in the previous section areused. In this simulation, the ground has
homogeneous initial structure and initial specificvolume in the depth direction. Also, the initialoverconsolidation ratio is calculated from the valueof initial structure and initial specific volumes. The
initial values of the evolution rules used in thissimulation are listed in Table 3. The isotropic stresscorresponding to static earth pressure is used as theinitial stress. For the boundary conditions, thehorizontal direction at the side wall of the ground isfixed, and the vertical direction is free. The
horizontal and vertical directions at the bottom of
the ground are fixed. Fixed boundary particles areused to describe the walls. In this simulation, a static
analysis is carried out until the ground is stable, thenremoved particles instantly in the excavation area asshown in Fig.4.
20.00
2.25

point A
(displacement)
point B(structure・
overconsolidation)
point C
(overconsolidation)

9.00

Excavation area

7.75

2.0 0.5

4.50

10.00

1：0.5

point D(overconsolidation)

Unit：mFig. 4

Numerical model.

Table 3 Initial values
Case

1

2

3

4

1/R0

5.30

17.92

27.93

167.71

1/R0*

73.62

2.84

2.01

1.13

2.08

1.91

1.88

1.79

＜initial value＞
initial degree of overconsolidation
initial degree of structure
initial specific volumev0

Figure 5 shows the simulated displacement at the
top of the slope at point A between before and after
excavation for each case. Figures 6 and 7 show thetime histories of R* and R at point B between before139

GEOMATE-Nagoya, Nov.13-15, 2013

introduction of the Super-subloading Yield Surface
Modified Cam-clay model into the SPH method, it
can be said that it was applicable to the various
ground, such as the highly structured naturally
deposited grounds in the overconsolidation state,
which is difficult to simulate using the simple
constitutive model.
-0.2

20s

-1

0.2
0.4
0.6

[1]

0

4

1

6

10
15
time [s]

20

[1]
[2]
[3]

200s

3

5
5

100s

2

0.8

0

[4]

1

displacement [m]

[4]
[3]
[2]

0

displacement [m]

0s

25

0

300

600

900

time [s](a) before excavation(b) after excavation
Fig. 5 Time history of the displacement at the topof the slope at point A.
1.2

1.2

[1][2] [3]

1

900s

0.8

R*

[3]
[2]

0.6

[4]

1

[4]
[1]

0.8
R*

300s

0.6

0.4

0.4

0.2

0.2

0
5

10
15
time [s]

20

25

0

300

600

900

1.2

1

1

0.8

0.8

0.6

R

R

1.2

[1]

0.4
0.2

[2]
[3]
[4]

0
5

10
15
time [s](c) case3(d) case4

time [s](a) before excavation(b) after excavation
Fig. 6 Time history of R* at point B.

0(b) case20s00(a) case12020s[1] [2][3]

100s

0.6

[4]

0.4
0.2
0

25

0

300

600

200s

900

time [s](a) before excavation(b) after excavation
Fig. 7 Time history of R at point B.
300s
1.2

1.2

1

[1]

1
0.8

0.6

R

R

0.8

[2]

0.4

[3]

0.2

[4]

0
0

300

600

900

time [s]

0.6

900s

[1]

0.4

[2]
[3]
[4]

0.2
0
0

300

600

900

time [s]0.0Fig. 8(a) point C
Time history of R.

0.3(b) point D
Fig. 9140

Distribution of accumulation of the
maximum shear strain at different time.

GEOMATE-Nagoya, Nov.13-15, 2013

results for the validation and also try to improve thenumerical method to be able to take into account thepore water pressure introducing the two phasemixture theory. Moreover, we want to reproduce
deformation behavior of the real phenomenon of theground in the framework of the SPH method with anelasto-plastic constitutive model considering soil
skeleton structure.

0s

900s

(a) case1(b) case2

REFERENCES[1] Lucy, L.B., “A numerical approach to thetesting of the fission hypothesis”, Astronomical
Journal, Vol.82, 1977, pp.1023-1024.
[2] Gingold, R.A. and Monaghan, J.J., “Smoothed
particle hydrodynamics: theory and application
to non-spherical stars”, Monthly Notices of theRoyal Astronomical Society, Vol.181, 1977,
pp.375-389.
[3] Maeda, K. and Sakai, M. “Development of
seepage failure analysis procedure of granularground with Smoothed Particle Hydrodynamics(SPH) method”, Journal of Applied Mechanics,
JSCE, Vol.7, 2004, pp.775-786 (in Japanese).
[4] Asaoka, A., Nakano, M. and Noda, T.,“Superloading yield surface concept for highly
structured soil behavior”, Soils and Foundations,Vol.40, No.2, 2000, pp.99-110.
[5] Asaoka, A., Noda, T., Yamada, E., Kaneda, K.
and Nakano, M., “An elasto-plastic descriptionof two distinct volume change mechanisms ofsoils”, Soil and Foundations, Vol.42, No.5,
2002, pp.47-57.
[6] Swegle, J.W., Attaway, S.W., Heinstein, M.W.,
Mello, F.J. and Hicks, D.L., “An analysis ofsmoothed particle hydrodynamics”, SAND932513,
SandiaNational
Laboratories,
Albuquerque, NM, 1994.
[7] Monaghan, J.J. and Gingold, R.A., “Shocksimulation by the particle method SPH”, Journalof Computational Physics, Vol.52, pp.374-389,
1983.
[8] Nakai, K., “An elasto-plastic constitutive
modeling of soils based on the evolution laws
describing decay of soil skeleton structure, lossof overconsolidation and development of
anisotropy”, PhD. Dissertation of Nagoya
University, Japan, 2005.

0s

900s

(c) case3
1(d) case4
20

Fig. 10 Distribution of the overconsolidation ratio
after excavation (0, 900s).
CONCLUSION
In this paper, the elasto-plastic constitutive
model taking account of soil skeleton structure is
introduced into the SPH method. Also, thesimulation of the excavation problem from loose todense sand ground was carried out. The findings are
summarized as follows.
The excavation problems from loose to dense
sand ground were simulated. In the case for loose
sand ground, the slope failure occurred immediately
after excavation. Also, in the cases for medium
dense and dense sand ground, the slope failure wasoccurred with the progression of time after
excavation. On the other hand, in the case for very
dense sand ground, the slope failure didn’t occur
after excavation. As the cause of these results, thedense sand didn’t easily decay the structure than theloose sand. Moreover, in the case that occurred slope
failure, due to the loss of the overconsolidation after
the decay of the structure, the states of groundchanged from overconsolidation state to normal state.
As the issue on future, we should compare theexperimental results and exciting the numerical141

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SOUNDNESS EVALUATION OF THE EMBANKEMNTS FOR
EFFECTIVE MAINTENANCE AND LONG-LIFE OF SHIN-TOMEIEXPRESSWAY
Masaya Hinokio1, Hiroshi Yamato1, Kazunari Suzuki1, Takayuki Sakai1, Masaki Makano1and Minoru
Kawaida2
1
Department of Civil Engineering, Nagoya University, Japan; 2 Central Nippon Expressway Company
Limited, Japan

ABSTRACTRoad embankments are important infrastructure for modern human life. And it is needed that theperformance of such road embankment is always kept in good condition. For this, they must be well maintained.
However, taking current economic situation into consideration, it is difficult to spend large amounts of cost on
infrastructure construction; therefore, it is important to extend the life of existing structures effectively andeconomically. Generally, it has been thought that structures like embankments become more stable with time andhence the quality of the embankment is ensured through site management during construction. However, in
recent years there have been a series of cases of embankment collapse due to heavy rains or earthquakes. In thisstudy, the Surface Wave Propagation tests are carried out on embankments of Shin-Tomei expressway toevaluate soundness of the embankments. Furthermore, laboratory tests using the soil materials which arecollected from those embankments are carried out to grasp mechanical properties of soils. The laboratory tests
reveal that soils of embankments are easy to compress and have enough strength and stiffness. Moreover, fromresults of the Surface Wave Propagation tests, the S-wave velocity are more than 250m/sec at most places ofembankment. From the Surface Wave Propagation test and laboratory test results, it is judged that theseembankments are compacted enough.
Keywords: Embankment, Maintenance, Evaluation, Surface wave propagation test, Triaxial test

embankment.
To confirm the soundness of inner part ofembankment, surface wave propagation tests [2] arecarried out. In addition to surface wave propagation,
various laboratory tests are performed to investigate
mechanical characteristics of embankment. From
results of surface wave propagation tests andLaboratory tests, it is tried to carry out a simple
soundness evaluation of embankment.

INTRODUCTION
In generally, construction of embankment ischeaper than other structures. In addition, it has beenthought that embankments become more stable overtime. If collapse do not occur during construction
period, then embankments are safer afterwards. So,
during construction appropriate management iscarried out, after construction maintenance isgenerally not carried out. However, in recent years
there have been a series of cases of embankment
collapse due to heavy rains or earthquakes. In thesecases, in addition to collapse due to unexpected
external forces, the loss of soundness of theembankments themselves has contributed to collapse.
In other words, stability of the embankment can be
gradually lost with time due to differences inmaterials of soils or different surrounding situations.
In particular, embankments are constructed on slope
and valley where rainwater can easily infiltrate.
They weaken the embankment and the loss of finematerials can easily reduce the soundness ofembankment [1]. It is difficult to determine risk ofsuch embankment from the surface before theoccurrence of failure and collapse. Therefore, toperform effective maintenance, it is needed toconfirm the soundness of the inner part of the

SURFACE WAVE PROPAGATION TESTS
Surface wave propagation test is one ofnondestructive inspection techniques. This test hasthese properties.
 Can find distribution of S wave velocity of theground.
 Can measure without damage of structure.
 Can easily measure.
To perform effective maintenance, surface wave
propagation tests have to be carried out at the threestages:1) Inspection immediately after construction (newembankments only)
2) Periodic inspection after entering service
3) Inspection after deformation occurs
From a comparison of the results at each of the142GEOMATE-Nagoya, Nov.13-15, 2013stages, it is possible to make a simple evaluation

measurement sites. The blue lines indicate theSampling

Sampling

Samplinga)

The plan view of site 1b)

The plan view of site 2

Sampling

Sampling

Samplingc)

The plan view of site 3d)

The plan view of site 4

Figure 1 The plan view of sites
from the change of results. In addition, byunderstanding the point where the change of the S
wave velocity is remarkable, the point where asounding test should be performed can be chosen.
An understanding of the initial state of theembankment is essential for these evaluations. Just
before and just after start of service of Shin-Tomei
Expressway, surface wave propagation tests arecarried out on embankments not only to evaluate theinternal state of embankments but also to obtain theinitial value that would become the standard when afuture soundness evaluation is carried out. 4 sites are
selected and measurements are made along a total of
14 lines. The embankment of Site 1 consists ofmudstone, sandstone and gravel as main materials.
Site 2 consists of mudstone and gravel soil as mainmaterials. Site 3 consists of sand and sandy gravel as
main materials. Site 4 consists of clay slate, tuff,
limestone and gravel as main materials. In addition
to surface wave propagation test, various laboratory
tests are performed using the soil samples which aregathered from 4 sites.
Figure 1 shows the plan views of the four

location of the measurement lines and blue circles
indicate locations at which soils are sampled.
Figures 2, 3, 4 and 5 show the measurement
results for the four sites. In these figures, the resultsof each measurement line locate them in the same
way as location in the plan view. From these figures,
S wave velocity is more than 250 m/sec at most
locations, and the largest measurement at somelocations is more than 500 m/sec. Therefore, it isconsidered that these embankments are compacted
enough. When these tests are performed regularly,
and the S wave velocity of the same point decreases,
it is considered that stability of the embankment has
decreased. Therefore a simple soundness judgment
can be performed.
However, such an evaluation is a qualitativeevaluation, and it is difficult to directly evaluate it
quantitatively for all embankments. In addition, toknow the initial soundness of the embankments
quantitatively is difficult and to evaluate how muchsoundness is lost with passage of time is moredifficult. Because mechanical properties andcompaction properties differ greatly with the type of143

GEOMATE-Nagoya, Nov.13-15, 2013

soil, quantitative evaluation cannot be performed by
S波

220.0 210.0 200.0 190.0 180.0 170.0 160.0 150.0 140.0 130.0 120.0 110.0 100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
距

-0.0

Depth
深

離

(

程

距

離

( m)
S wave
S波速度縮velocity程

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0 160.0 170.0 180.0 190.0 200.0 210.0 220.0 230.0 240.0 250.0 260.0 270.0 280.0 290.0
清水

( m)

中小段

SS波速度
wave velocity

-0.0

Depth
深

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0 160.0 170.0( m/sec)

( m)

S波速度
S
wave velocity

-0.0

Depth
深

Sampling

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0距

離程( m/sec)( m)Distance
Figure 2 The result of site 1

-0.0

Depth

深

SS波速度
wave velocity
500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
150.0 140.0 130.0 120.0 110.0 100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0
距

-0.0

Depth

深

離

( m/sec)

( m)

程

SS波速度
wave velocity
500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
170.0 160.0 150.0 140.0 130.0 120.0 110.0 100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.000( m/sec)

Distance

-0.0

Depth

Sampling

SS波速度wave velocity
500.00280.00160.00100.00
40.00

10.0
20.0
30.0

( m/sec)

50.0 40.0 30.0 20.0 10.0 0.0
( m)

-0.0

Depth

Sampling

SS波速度wave velocity
500.00280.00160.00100.00
40.00

10.0
20.0
30.0
0.0 10.0 20.0 30.0 40.0 50.0

Distance
Figure 3 The result of site 2

144

( m)

( m/sec)( m/sec)GEOMATE-Nagoya, Nov.13-15, 2013

SS波速度
wave
that velocity
considered the difference in mechanical500.00properties
is tried.

-0.0

Depth

深

10.0

280.00160.00100.00
40.00

20.0

度

30.0

( m/sec)

100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0
-0.0

Depth

深

距

離

( m)

S wave velocity

程

S波速度

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0

Sampling( m/sec)( )Distance
Figure 4 The result of site 3

S wave
S波速度velocity

-0.0

Depth

深

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0-0.0
S波速度 ( m)
距

深

10.0

Depth

20.0

離

S wave velocity

程

縮尺＝1/1000
500.00280.00160.00100.00
40.00

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0

S wave
S波速度velocity

-0.0

Depth

500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0 130.0 140.0 150.0
距

-0.0

Depth

深

( m/sec)( m)Distance

深( m/sec)

離( m/sec)( m)

程Sampling

Sampling

S wave velocity
S波速度500.00280.00160.00100.00
40.00

10.0
20.0

度

30.0

( m/sec)

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 110.0 120.0( m)

Distance

距

離

程

縮尺

/

Figure 5 The result of site 4

LABORATORY TESTS

only considering S wave velocity with disregard of
the characteristics of the soil. In other words,
because there is a large difference in soundness
based on the differences of soil types ofembankments, even if the same S wave velocity ismeasured, the valuation of soundness cannot be
performed uniformly only with numerical values.
Therefore, it is necessary to clarify S wave velocity
and the association with mechanical properties,
properties of compaction, and the density of the soil.
Therefore, laboratory tests are performed for thedifferent soils of embankments and an evaluation

Laboratory tests are carried out using soils
obtained from the sites of surface wave propagation
tests. Six soil samples are collected. From Sites 1
and 3, one sample is collected. And two samples
from each of Sites 2 and 4 are collected. Using eachsample, density of soil particle test, particle size
distribution test, compaction test, and undrained
triaxial compression test are carried out. In particle
size distribution test and compaction test are
performed on samples adjusted below particle sizeof 19 mm. The results of density of soil particle test
and particle size distribution test are shown in Table
145

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 The Density of soil particle
Samplesite1

site2-asite2-bSite3

site4-asite4-b

Density of soil particle
ρs (g/cm3)

2.762

2.708

2.700

2.679

2.822

2.685

1 and Figure 6. From this Table it can be shown thatmost soils have almost the same density of around2.7g/cm3. From Figure 6, it is seen that Site 3 has
the largest proportion of fine particle fraction thanother sites. In consideration of these test results,
compaction test and undrained triaxial compression
test are carried out only for soils of site 2-a and 3.
The soil of Site 3 has the largest proportion of mostfine particle fraction and soil of Site 2-a has thelargest proportion of coarse-grained fraction. And
from S wave propagation test, result of site 3 is thelowest velocity.
The results of compaction test are shown in thisFigure 7. From this Figure, it is understood that it iseasy to compact soil of Site 2-a. This is because soilof Site 2-a comprises the most coarse-grained
fraction.
Figures 8 and 9 show the results of undrained
triaxial compression tests. The results include two
additional specimens (7.5cm in diameter, 15cm inheight) with degree of compaction Dc=85 and 100%.
These figure show that shear strength greatly
increases with the rise in degree of compaction.
Furthermore, it is seen that the effective stress pathof Dc=85% shows behavior similar to that ofnormally consolidated soil from q-p' relations. On
the other hand, the effective stress path of Dc=100%
rises along the critical state line. In addition,negative pore water pressure occurs by shear
deformation, showing behavior similar to that ofdense sand. From this, it can be supposed that
overconsolidation accumulated by compaction. In
addition, from v-p' relations, it can be supposed that

Site2-aSite3

Figure 7 The result of compaction test

200

10

600

400

200

0
0

20

Axial strain εa (%)

200

400

600

10

400

200

0
0

20

Axial strain εa (%)

200

400

600

800

Mean effective stress p′ (kPa)

0
-50
-100
10

Axial strain εa (%)

20

1.5

1.4

1.3

1.2
0

100
50
0
-50
-100
-150

200

400

600

800

0

10

Axial strain εa (%)

Mean effective stress p′ (kPa)

Figure 8 The result of triaxial tests(Site 2-a)Specific volume v (=1+e)50

Dc=85%
Dc=100%

Pore water pressure u (kPa)Specific volume v (=1+e)

Pore water pressure u (kPa)

200

600

150

100

0

400

Mean effective stress p′ (kPa)

150

-150

600

0
0

800

800

Deviator stress q (kPa)

400

800

Deviator stress q (kPa)

600

0
0

Figure 6 The result of particle size distribution test

800

Deviator stress q (kPa)

Deviator stress q (kPa)

800

Site1
Site2-aSite2-b
Site3
Site4-aSite4-b20

Dc=85%
Dc=100%

1.7
1.6
1.5
1.4
1.3
0

200

Figure 9 The result of triaxial tests(Site 3)
146

400

600

800

Mean effective stress p′ (kPa)GEOMATE-Nagoya, Nov.13-15, 2013

as the degree of compaction becomes higher, thequantity of compression becomes small. The
aptitude of these two soils (Site 2-a and Site 3) isjudged by comparing the soils with soils from Soil
A(generally high quality soil) and Soil B(generally
not good quality soil). Figure 10 and 11 show theresults of particle size distribution test andcompaction test. From result of compaction test, it
can be seen that compaction curve of Site 2-a andSite 3 are steeper in comparison with that of Soil A,
and the value of the peak is big. Therefore, soil ofSite 2-a and Site 3 are easy to compact, and they arehigh quality soils.
Figure 12 shows the results of undrained triaxial
compression test. From this Figure, it can be seenthat the shear strengths of Site 2-a and Site 3 arebigger than those of Soil A and Soil B with
Dc=100%. And, the shear strength of Soil B does
not rise with the rise in degree of compaction thatmuch, but the shear strength of Site 2-a and Site 3
greatly rises with the rise in degree of compaction.
From this, it is thought that compaction has a big
effect on the increase in shear strength, and thatthese soils are suitable for embankment

Site2-a
Site3
Site5
Site6

Figure 10 The result of particle size distribution test
Site2-a
Site
2-a
Site3
Site
3
Site5
Soil
A
Site6
Soil
B

CONCLUSIONS
The following conclusions are obtained from
Surface wave propagation tests and Laboratory tests.

[1] M. Hinokio, M. Nakano and M. Kawaida,“Model tests of embankment subjected toseepage water”, Proc. 6th International
Workshop on New Frontiers in Computational
Geotechnics, 2012.
[2] Koichi Hayashi and Haruhiko Suzuki, “Surfacewave propagation in two-dimensional models
and its application to near-surface S-wave
delineation”, The 5th SEGJ International
Symposium -Imaging Technology-, 2001.

800

800

Deviator stress q (kPa)

Deviator stress q (kPa)

Dc=85%
Dc=100%

600

400

200

0
0

10

20

Dc=85%
Dc=100%

600

400

200

0
0

Site2-a800
Dc=85%
Dc=100%

600

400

200

10

20

Dc=90%
Dc=100%
600

400

200

0
0

Axial strain εa (%)

Soil A
Figure 12 Comparison the other site

147

20

Site3

800

0
0

10

Axial strain εa (%)

Axial strain εa (%)

Deviator stress q (kPa)REFERENCES

Figure 11 The result of compaction test

Deviator stress q (kPa) From surface wave propagation tests, the S wave
velocity is more than 200m/sec. It shows theembankment were well compacted.
 From laboratory tests, the soils of embankments
are easy to compact and the strength is high.
Therefore, these soils are suitable forembankment.
 By checking distribution of S wave velocity inthe ground two-dimensionally, it can beinvestigate a relative difference with the initialstate. And it can be developed to simple
evaluation of embankments.
 By collecting these information, the detailed
position that should be examined is pinpointed.
 It leads to the rationalization of the maintenanceand its high efficiency.

10

Axial strain εa (%)

Soil B

20

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EVALUATION OF GLASS FIBERS DERIVED-THREE DIMENSIONALGEOMATERIAL FOR PROBLEMATIC SOIL APPLICATIONS
Donovan Mujah1, Hemanta Hazarika2, Fauziah Ahmad3 and Muhammad Ekhlasur Rahman4
Department of Civil and Construction Engineering, Curtin University Sarawak, Malaysia
2
Department of Civil and Structural Engineering, Kyushu University, Japan3
School of Civil Engineering, Universiti Sains Malaysia, Malaysia

1, 4ABSTRACTThis research was aimed to study the potential reuse of recycled glass fiber-derived three dimensional
geomaterial obtained from industrial glass fiber wastes to innovate a sustainable, cost-effective geosynthetic forground improvement in problematic soil application. The ready availability, high tensile strength, lightweightand non-biodegradable characteristics of glass fibers further elevate their advantages as compared to thepresently adopted geosynthetics in soft soil reinforcement condition. In this study, mechanical properties ofrectangular strip shape, ‘8’ shape and bolted screw ‘8’ shape samples and pullout resistance force of glass fibers
geomaterials were investigated by considering glass fibers’ layer thickness, shape formation and orientation in alaboratory scale model. It was observed that the tensile and yield strengths of overall geomaterial samples
significantly increase as strip layers thickness increase. Results from both the tensile strength and pullout
resistance force indicated similar trend of increasing in strength values with test conducted using other type ofgeosynthetics in various soil media to simulate the action of different soil conditions at real sites.
Keywords: Recycled Glass Fibers, Ground Improvement, Tensile Strength, Pullout Resistance Force.

INTRODUCTION

MATERIALS AND METHODOLOGY

Recently, researchers have engaged in the use ofglass fibers as ground improving geomaterial [1]–[4].
[5] states that glass fibers’ amorphous structures areable maintain internal stability along and across thefibers without further intrusion by foreign addictives
thus ensuring structural durability. In contrast to
carbon fibers, glass fibers are able to undergo
considerably more elongation before rupture whendemonstrated by tensile test. Likewise, [1] reported
that glass fiber is an attractive reinforcing agent
because of their high strength, stiffness, high ratio of
surface area to weight and dimensional stability.
Although earlier studies of glass fiber [1], [5]mentioned its unique properties however none ofthem described their potential use as reinforcing
agent for ground improvement. In this paper, a newgeomaterial called 8FG MAT made from recycled
glass fibers derived from industrial glass wastes is
proposed as a sustainably driven innovative effort
for ground remediation technique whereby its
mechanical properties in terms of the tensile strengthand pullout resistance force were verified throughlaboratory tests in various soil conditions.

Materials
Soil Samples
The laboratory work consisted of testing threesoil samples reinforced and unreinforced withgeomaterial were used in the experiment to simulatedifferent kinds of soil conditions on site. The particle
size distribution of the various soils used in the study
is shown in Figure 1.
Glass Fibers
Polymeric glass fibers derived from industrial
glass wastes were sterilized in an autoclave in atemperature of 120 0C – 150 0C for 1 hour to get ridof micro-organism impurities. Some portions of thefibers were coated with acrylic butadiene styrene(ABS) thermoplastic before proceed to mechanicaltesting. Subsequently, fiberglass yarns were molded
into ‘8’ shape form using a prefabricated mold 1000
mm length, 200 mm width and 150 mm height.
Furthermore, strands of glass fibers were glued
together using resin to ensure that glass fibers were148

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 1 Particle size distribution curves of the various soil media used in the study.
intently intact. Any presence of air bubbles wereclosely observed as they may lead to voids
formation which may result into a lower volume ofglass fibers thus affecting geomaterial’s overall
strength. The sample was then allowed to harden for
two hours before mold was removed.

Samples of glass fiber geomaterials were preparedinto four categories accordingly to their layers which
included (a) 10 mm (b) 20 mm (c) 30 mm and (d) 40
mm thickness as shown in Figure 2.

Fig. 2 Step by step preparations of the 8FG MAT.
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GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 3 Different type of geosynthetics used in the tensile test experiment.
Methodology

strength of polymeric yarns of glass fibers were
tested and compared to coated glass fibers andnatural fibers extracted from oil palm empty fruitbunch (OPEFB). Stress-strain relationship of glass
fiber strands was observed using INSTRON 3690
Electro-Hydraulic Actuator and Universal Tensile
Machine (UTM) according to ASTM C1557-03:
Standard Test Method for Tensile Strength andYoung Modulus of Fibers. Consequently, the tensile
test for ‘8’ shape glass fiber geomaterial was carriedout according to the modified version of ASTM
D7004-03: Standard Test Method for Grab Tensile
Properties of Reinforced Geomembranes. To ourknowledge, this is the first ‘8’ shape form ofgeomaterial glass fibers ever attempted other thanthe presently available steel mesh geocell. The
ultimate tensile strength of the molded ‘8’ shapeglass fiber geomaterial (8FG MAT) is compared toother available geosynthetic products such as woven
geotextile (PYRAMAT), TS570 geotextile and oilpalm empty fruit bunch (OPEFB) Biocoat as shownin Figure 3.

Shear Box Apparatus
In this research, a rigid steel soil box was usedhaving 1200 mm length, 1000 mm width and 500
mm depth. The pullout apparatus system which
comprised of steel box, steel rod and ready filled soil
media was equipped with an electric motor thatrotates with a constant displacement rate of 4.6
mm/min connected to a high tensile 20 mm diameter
steel rod that was clamped to the geomaterial
embedded in the soil box by means of four numbersof 1 mm diameter wire connections. The inlet andoutlet ports were installed at the front and back sidesof the box to enable connections to four number oflinear variable displacement transducers (LVDT)
located at the back side and on top of the box
respectively. During experiment, LVDT’s readingsthat record horizontal displacement of geomaterialand settlement of soil media were monitored througha data logger.
Tensile Test
Two sets of tensile tests were conducted to verify
the tensile strength of glass fibers. Firstly, tensile

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different layer thickness. It was observed that theaddition of layer thickness in molded specimens
contributed to the increased values in tensile stress.
However, the effect of molding glass fibers into the‘8’ shape form does not greatly affecting the peaktensile stress of glass fiber specimens. The recorded
peak tensile stress of uncoated and coated glass
fibers are 9.83 MPa and 11.33 MPa in which arealmost equivalent to the peak tensile stress of thethree and four layers thickness of molded ‘8’ shapespecimen at 9.52 MPa and 11.43 MPa respectively.
In the case of both one and two layers thickness,alteration of glass fibers into ‘8’ shape form
recorded lower tensile stress values than uncoatedglass fibers. This suggests that the process of
converting glass fibers into bundle of layered strands
does not necessarily enhance the overall tensile
strength of glass fibers in bulk.

Pullout Test
The pullout resistance force of glass fiber
geomaterial was observed through pullout test basedon ASTM D6706: Standard Test Method for
Measuring Geosynthetic Pullout Resistance in Soil.
Pullout test is commonly adapted as a crucial
experimental indicator for any geosynthetic
validation because it provides not only soil-structureinteraction between reinforced soil and reinforcing
agent but also visible trend in reinforced soil failure
mechanism. As illustrated in Figure 3, soil media
were filled in and compacted manually using 60 N
weights, 120 mm diameter circular base hammer
dropped from a height of 300 mm for 25 blows per
layer.
RESULTS AND DISCUSSION
Tensile Test Experiment
The result from fibers tensile test experiment byconsidering the effect of ABS thermoplastic coating
between natural and glass fibers is shown in Figure
4. The result shows typical linear relationship of abrittle material due to the fact that both natural andglass fibers exhibit the absence of yield point andstrain hardening region after undergoing elastic
deformation. Compared to the uncoated fibers
specimens, coated fibers show higher peak tensilestress at the same corresponding strain.

Fig. 5 The effect of layer thickness towards thetensile stress-strain behavior of 8FG MAT.
The tensile strength of two commonly usedslope protection materials such as woven geotextile(PYRAMAT) and TS570 geotextile together withnaturally based fiberous oil palm empty fruit bunch(OPEFB) biocoat were compared with ‘8’ shapeglass fiber geomaterial (8FG MAT) as shown in
Figure 6. The ultimate tensile strength of all
specimens in ascending order were recorded as 0.59
kN, 0.61 kN, 0.76 kN and 0.86 kN respectively[PYRAMAT > 8FG MAT > TS570 geotextile >OPEFB biocoat]. It was observed that both ultimate
tensile strength values for TS570 geotextile and
OPEFB biocoat were almost similar. However, due
to the randomly distributed natural fibers that existed
in its structure, biocoat specimen was observed toFig. 4 Tensile stress-strain relationship of the coatedand uncoated fibers.
Figure 5 shows the stress-strain relationship ofthe molded ‘8’ shape 8FG MAT by considering151

GEOMATE-Nagoya, Nov.13-15, 2013

reinforcement in clay and sand soil samples arealmost similar indicating further increase inthickness will not yield further increase in pullout
force.

undergo large horizontal strain before rupture. The
ultimate tensile strength value of 8FG MAT isshown to be higher than that of both TS570 and
OPEFB but lower than that of PYRAMAT. This ismainly due to the effect of 8FG MAT grabbing
during tensile test, in which the region whereconstruction joint is located. The construction joint
is the line where layers of glass fiber strands wereconnected using resin to harden. The occurrence offailures in all samples of 8FG MAT at theconstruction joint regardless of their layer thickness
proved the joint susceptibility in resisting applied
force.

Fig. 7 Pullout force relationship between sand andpeat.

Fig. 6 Comparison of tensile strength values of thevarious geosynthetics.
Pullout Test Experiment
The pullout relationship between sand and peat
reinforced with 8FG MAT is shown in Figure 7. The
result shows linear relationship between pullout
force in sand and that in peat. The slope of theregression line is the pullout force coefficient. The
pullout force coefficients in ascending order ofdifferent layer thickness are 0.47, 1.02, 1.63 and2.02 respectively with all regression coefficientsover than 0.995.
Similarly, Figure 8 shows the pullout
relationship between clay and sand reinforced with
8FG MAT. The result shows linear relationshipbetween pullout force in clay and that in sand. The
pullout force coefficients in ascending order ofdifferent layer thickness are 0.93, 1.53, 2.40 and2.61 respectively with all regression coefficientsover than 0.997. Although the addition of layer
thickness linearly proportional to the pullout force inboth peat and sand soil samples, the pullout
coefficients in three and four layers of geomaterial

Fig. 8 Pullout force relationship between clay andsand.
The pullout force of 8FG MAT was investigatedin different types of soil media to show its reliability
as ground improvement agent. Figure 9(a) and
Figure 9(b) show the pullout–displacement
relationship of reinforced soil media with 8FG MAT
in two different confining vertical stresses
conditions σ v = 100 kN/m2 and σ v = 50 kN/m2
respectively. The results from both figures clarify
that the pullout force is directly proportional to theapplied confining pressure. The increase ofconfining pressure was observed to increase thecorresponding pullout force for all soil samples.

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GEOMATE-Nagoya, Nov.13-15, 2013

the same corresponding strain in that of
uncoated fibers.
2) The pullout test results revealed a linear
relationship between the pullout force values indifferent soil samples as the thickness of glass
fiber strands’ layers and confining pressures
were increased.
3) The ready availability, high tensile strength,
lightweightandnon-biodegradable
characteristics of glass fibers proved to be anadvantage for long term ground improvement
remediation especially in soft soil condition.
The ‘8’ shape form of 8FG MAT provide
strength into reinforced soil by confining effectof its layer that maintains the intactness between
glass fibers and soil particles thus, improving
friction at their interface.

(a) Confining vertical stress σ v = 100 kN/m2

ACKNOWLEDGEMENTS
The financial supports granted by E-Science
Fund (MOSTI) Malaysia and the Japan-East Asia
Network of Exchange for Students and Youths(JENESYS) Program are gratefully acknowledged.
REFERENCES[1] Lutz JT and Grossman RF, “Polymer modifiers
and additives”, Emerging Material for Civil
Infrastructure: State of the Art, Roberto A.
Lopez-Anido, Tarun R. Naik, Gary T. Fry,David A. Lange, & Vistasp M. Karbhari (Eds.),
ASCE, 2001, pp. 233–240.
[2] Mujah D, Ahmad F, Hazarika H, Yasafuku N,
Omine K and Kobayashi T, “Evaluation offiberglass as ground improving geomaterial”, in
Proc. 10th Japan-Korea-France-Canada Joint
Seminar on Geoenv. Eng, Japan, 2011, pp.
189─194.
[3] Ahmad F, Mujah D, Hazarika H, and Safari A,“Assessing the potential reuse of recycled glassﬁbre in problematic soil applications”, J. of
Cleaner Production, Vol. 35, 2012, pp.
102─107.
[4] Mujah D, Ahmad F, Hazarika H, and Safari A,“Evaluation of the mechanical properties ofrecycled glass fibers-derived three dimensional
geomaterial for ground improvement”, J. of
Cleaner Production, accepted, 2013.
[5] Pinzani GP and Sauli G, “Long term efficiencyof erosion control geomats”, Millpress,
Rotterdam, Netherlands, 2006, pp. 103–114.

(b) Confining vertical stress σ v = 50 kN/m2
Fig. 9 Pullout–displacement relationship of thereinforced soil media with 8FG MAT in two
different confining vertical stress conditions.
CONCLUSIONSIn this research, the mechanical properties ofmolded ‘8’ shape glass fiber geomaterial derived
from industrial glass waste was studied. From thefindings, the following conclusions could be made:1) The tensile strength of glass fiber geomaterial
was significantly increased with the addition oflayer thickness while fibers alteration in termsof coating with ABS thermoplastic showed thatcoated fibers exhibit higher peak tensile stress at153

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STUDY ON MONITORING METHOD OF RETAINING WALL
BEHAVIOR USING MEMS SENSOR NETWORKN Minakata1, S Nishiyama2, T Yano3, D.H Lee4, J Wu5 and M Ryu6

Department of Urban Management, Graduate school of Engineering, Kyoto University, Japan
Graduate school of Engineering, Okayama University, Japan
Department of Urban Management, Graduate school of Engineering, Kyoto University, Japan
Department of Civil Engineering, National Cheng-Kung University, Taiwan
Earthtech Toyo Co.,Ltd, Japan

ABSTRACT

For the evaluation of infrastructures, the authors have developed the monitoring method of the stability ofcivil engineering structures using MEMS sensors. MEMS sensors have various advantages as follows. First, theauthors can design the arrangement of MEMS sensors easily and save the monitoring cost. Secondly, the authors
can send data with wireless equipment. Finally, the authors can transform the data of acceleration into the valueof angle, which means the high possibility of calculating the two dimensional angles of inclination of retaining
walls. More specifically the authors can use the acceleration sensors as inclinometers. In addition, the authors
demonstrated that the resolution of MEMS sensors was less than 0.1 degree as the results of the experiments andalso investigated the applicability of monitoring method reported herein at the actual field. From the monitoring
results, it is found that measurement values with using MEMS sensors has the temperature characteristics andthat the temperature correction is very important for the authors to get an exact monitoring data, so that theauthors revealed the temperature characteristics of MEMS sensors. In this paper, the authors showed that the low
pass filter the authors designed for deleting this temperature effect and monitored the retaining wall behavior
with a high accuracy.
Keywords: Inclinometer, Acceleration, Retaining Wall, MEMS, Wireless Sensor Network
The second one is the authors can install sensors inany positions because the authors transmit andreceive measurement data by radio. Finally, it ispossible to reducing a labor and costs required for
management of the measurement system. The
function of MEMS sensor is being developed, butthere are few examples of the practical use in thefield of civil engineering works. The MEMS has
been used as a clinometer mainly until now. We also
make a sensor network using MEMS to measure thetilt angles of a retaining wall for the prevention oflandslides. In this study, the authors develop asensor network system in which measurement datatransmitted from a sensor is prevented from being
affected by vegetation, a distance between a sensor
and a base station collecting the measurement data is
made long, and in addition, precision of a sensor
signal is not affected by temperature. This paperargues the practicability of the proposed
measurement system by evaluating the precision of
the slope behavior monitoring.

INTRODUCTION
Recently the number of natural disasterincreases all over the world, and maintenance of thecivil engineering structure for disaster prevention is
becoming more and more important. Asian countries
are characterized by geological conditions underwhich rocks weather quickly, and these countries
often suffer natural disasters such as earthquakes,
typhoons as well as localized torrential downpours.
Moreover, in many Asian countries, rapid urban
development has been carried out, and lots of slope
hazard damages occur. The prevention of resultant
damages caused by slope hazard requires theestablishment of sound slope behavior monitoring
technology. Considering this situation, the authors
focus on the micro machine technology which has
been greatly advanced, and have developed an early
warning system for the prediction of landslides andthe prevention of resultant damages with the MEMS
sensor network [1]. This system has the following
characteristics. The first one is installation of thesensor is easy because the size of the sensor is small.
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GEOMATE-Nagoya, Nov.13-15, 2013

DEVELOPED MONITORING METHODThe Developed Sensor Network

The authors pay attention to MEMS sensor
and wireless network systems, and the authors
developed the new monitoring method by utilizing
both of them.

The authors installed wireless device into
the developed MEMS sensor. That is why the
MEMS sensor can send measured values without
using any wires to the base station as shown in Fig.5.
Therefore it is possible to decrease the risk ofdamage caused by the thunderbolt. After the datameasured using the wireless communication withfrequency of 434 MHz are sent to the base station,
the sent data are uploaded to the Web site designated
via the Internet. This is why the authors can accessthe collected data via the Internet and the authors
can access the data anywhere a terminal via theInternet browser is utilized, and the acquisition
process is automatic and requires no technicians onsite [5]. Even if it is far from the site to the office, it
is possible that the authors monitor the actual civilengineering structures in real time. For example, theauthors need not to go to the site in order to collectthe measured data and in order to check how to
operate normally [6]. Therefore the authors can savelabor. Also this monitoring system is set in sleep
mode except for completing start-up, measurement,
and transmission in a while time. Thus thismonitoring system achieves low power consumption
and can be free of maintenance.
From these result of experiments performedby the authors, it is found that the MEMS sensor canmeasure very small magnitudes of an inclination of
the civil engineering structures even if the measured
value includes the temperature characteristics.
Therefore the authors applied this monitoring
method to assess an actual retaining wall in Taiwan
for disaster prevention.

The Developed MEMS Sensor
Figure.1 shows the MEMS sensor used inthis study. The size of the MEMS sensor is
W123mm × D76mm × H57mm, therefore the
MEMS sensor is very compact, lightweight, andinexpensive. That is why the problem thatconventional measurements have been widely usedeverywhere in the world and have been effective but
resulting in a limited application only for a few
infrastructures because of high costs, can be solved[2]-[4]. The measurement principle of the MEMS
sensors is shown in Fig.2. The MEMS sensors usedin this monitoring system can measure two-direction
accelerations, and the MEMS proposed herein canmeasure two-direction angles by calculating with
Eq.(1). As a result, the authors can use the MEMS
sensor proposed herein as an inclinometer.
Simultaneously, the MEMS sensors can measuretemperature.

 Accx 2 + Accy 2 θ i = Arccos

Acci

(1)

i = x, yExperiments
For evaluating the accuracy of the MEMS
sensor, the authors performed the experiment.
Figure.3 shows the relation between measured
values with using the MEMS sensors and changed
angles. It is concluded that the precision of the
MEMS sensor network system proposed herein getsthe very high accuracy with the high precise that is
0.1 degree, which is much higher than conventional
methods. To verify the temperature characteristics ofthe MEMS sensor network system, the authors
performed another experiment. The result of thisexperiment is shown in Fig.4, which shows therelation between temperature and inclinations
measured using the MEMS sensors. From the result,
it is found that the temperature characteristic of the
new developed MEMS sensors is less than 0.001
degree per a degree centigrade. This temperature
characteristic is much lower than the MEMS sensors
which the authors developed before. This is because
the MEMS sensors are filled with a bulking agent,
resulting in the temperature characteristics get verysmall.

Fig.1 This figure shows the MEMS sensor usedin this paper. The red lines show the coordinate
system of the MEMS sensors.

155GEOMATE-Nagoya, Nov.13-15, 2013

Fig.2 This figure shows the measurement
principle for the MEMS sensors. The redline shows the gravity direction and theblack lines show the coordinate system of
the MEMS sensors.

Fig.5 This figure shows the base station. The
unit is W380mm × D270mm × H130mm.
The measured values are sent to this basestation, and after that, the sent data are
uploaded to Web site.

y=x

APPLIYNG
WALL

THE

ACTUALRETAINING

Retaining Wall Monitored
The authors applied the monitoring systemdeveloped in this paper to the actual retaining wall in
Taiwan. The retaining wall is shown in Fig.6 and thered point of Fig.6 are respectively locations of
installation of MEMS S11, S12, and S13. The
overall length of the retaining wall is 90m and the
maximum height is about 30m. This retaining wall
was damaged by Morakot in 2009 and collapsed by
the deep sliding as shown in Fig. 7 [7]. Because of
the collapse of this retaining wall, the government of
Taiwan began the reinforcement work of theretaining wall monitored and it was completed asshown in Fig. 8. For preventing the slope sliding
and the collapse of the retaining wall, the authors
monitor this repaired retaining wall in order to check
whether the deep sliding is moving or not, andsimultaneously whether this retaining wall is safe ornot.

Fig.3 This figure shows the result of theexperiment. The blue figures show the
relation between changes of angle andmeasured values.

Fig.4 This figure shows the result of theexperiment for verifying the temperature
characteristics. The blue line shows therelation between temperatures and θx
measured values and the red line shows
the relation between temperatures and θymeasured values, and the black lines
show the linear approximate curves.

Fig.6 This figure shows the retaining wall
monitored using the MEMS sensors
shown in the red points, and the basestation is shown in the blue point.
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GEOMATE-Nagoya, Nov.13-15, 2013

Fig.10 This figure shows S12.
Fig.7 This shows the retaining wall damaged bydeep sliding when Morakot happened in2009.

Fig.11 This figure shows S13.
Monitoring Result of Actual Retaining Wall
Fig.8 This shows the reinforced retaining wall.

In this paragraph, the monitoring result
measured using the MEMS sensors S11, S12 andS13 is shown. The measured angles are respectively
shown in Fig.12, Fig.14 and Fig.16, and themeasured temperatures are shown in Fig.13, Fig.15
and Fig.17. The measured values are shown in solidlines, and the calculated values by using moving
average are shown in dashed black lines. The
amount of change of the calculated values of S11-θx
is approximately 0.2 degree. The amounts ofchanges of the calculated values the others MEMS
sensors which are S11-θy, S12-θx, S12-θy, S13-θx,
S13-θy are less than 0.1 degree. In this paper, when
the amount of change is more than 0.1 degree, theauthors regard this movement as the deformation ofthis retaining wall. Considering the definition theauthors proposed here and the result of thecalculated values, it is found that the measurement
point of S11 is moving gradually while the othermeasurement points are not moving. Therefore it isrecognized that the deep sliding is moving gradually.
In summary, it is necessary to set more measurement
points and monitor the retaining wall and the deep
sliding more densely, and it is required to reveal the
relation between the retaining wall behavior and thedeformation of the deep sliding. Additionally, theearthquake happened in Taiwan on 2nd June. In
regard to this, each of MEMS sensors could capture
the movement caused by the earthquake.

The authors installed 3 monitoring points and thebase station, and the setting situation is respectively
shown in Fig.9, Fig.10 and Fig.11. The distance
between MEMS and the base station isapproximately 20m, and measured values are sent tothe base station via the wireless communication at 1
minute interval, and the data is then uploaded to the
Web site which the authors made in advance. In thismonitoring system, the sampling time is set 1
minutes, and the MEMS sensors equip two dry cells.
In this setting, it is not necessary to change thebatteries for three years.

S11

Fig.9 This shows S11 on the retaining wall.

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GEOMATE-Nagoya, Nov.13-15, 2013

Fig.12 This figure shows the measured values.
The blue line shows θx measured values
and the red line shows θy measured
values, and the black dashed lines show
the calculated values using average
moving.

Fig.15 This figure shows measured temperatures.
The solid line shows the measured
temperatures and the black dashed line
shows the calculated values using average
moving.

Fig.13 This figure shows measured temperatures.
The solid line shows the measured
temperatures and the black dashed line
shows the calculated values using average
moving.

Fig.16 This figure shows the measured values.
The blue line shows θx measured values
and the red line shows θy measured
values, and the black dashed lines show
the calculated values using average
moving.

Fig.14 This figure shows the measured values.
The blue line shows θx measured values
and the red line shows θy measured
values, and the black dashed lines show
the calculated values using average
moving.

Fig.17 This figure shows measured temperatures.
The solid line shows the measured
temperatures and the black dashed line
shows the calculated values using average
moving.
CONCLUSION
The purpose of this paper is to develop theestablishment of the slope behavior monitoring
technology for disaster prevention. That is because
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GEOMATE-Nagoya, Nov.13-15, 2013

the authors focus on the micro machine technology
and developed an early warning system for theprediction of landslides and the prevention of
resultant damages. As a result of the development
the monitoring technology for evaluating thesoundness of the slope, the MEMS sensor could
detect very small magnitudes of a deformation of theretaining wall and proposed monitoring system
featuring simple measurement work and a highdegree of precision was found to be possible.
Therefore the authors applied the measurement
system and monitor the retaining wall behavior andthe deformation of the slope. From the monitoring
result, it was concluded that the retaining wall ismoving partially and simultaneously the deformationof this slope is increasing gradually.

and Materials Engineering, vol.4, 6, 2010, pp.
639-651.
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Engineers, Vol. 43, 3, 2012, pp. 291-294.

ACKNOWLEDGEMENTS
The authors are grateful to National Cheng Kung
University in Taiwan for their matchless technicalcompetence and friendly support. This research was
supported by Zengwun Improvement Engineering
Office, The fifth Maintenance Office, Directorate
General of Highways, Ministry of Transportation
andCommunications,andSHINOTECHENGINEERING CONSLTANTS, INC.
REFERENCES[1] Lee S, “Reliability Assessment of Advanced
Materials And Structure”, J. of Solid Mechanics

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CASE STUDY ON THE USE OF HIGH-RESOLUTIONSURFACE WAVE SURVEY FOR EXAMINING
THE CAUSE OF SUBSIDENCE OF RECLAIMED ROAD

1

Miura Minami1, Shibuya Satoru2
Graduate student, Kobe university, Japan; 2 Professor, Kobe University, Japan

ABSTRACTThis case study deals with the problem of ground subsidence, which took place after backfilling the sewage
pipeline in a small town in Hyogo Prefecture, Japan. The settlement brought about serious damage to theneighboring houses by showing harmful inclination of fence, garage shutter etc. The local government
commissioned to find out the cause of ground subsidence for the remedial work planned in near future. In an
attempt to get an overall image regarding the current conditions of the backfilled portion of the road, a highresolution surface wave survey was performed. The 2-D profile of S-wave velocity provided us with an crucially
important clue that the S-wave velocity of the backfill where the surrounding houses were damaged was
obviously lower than those for the undamaged areas. In order to manifest the cause of ground subsidence, aseries of tests in the laboratory, i.e., the compaction test, direct shear box test etc., was carried out for soil
samples retrieved at various spots along the surveyed line. It was found that i) the backfilled gravelly soil was
similar in all the spots; however, ii) the fines content of soil where the subsidence took place was noticeably
higher. It was concluded that the surface wave survey was of great use for promptly finding out potentially
under-compacted portion of the backfill without damaging the cited ground.
Keywords: Surface Wave Method, Submergence, Settlement, Direct Shear Test

compaction aspect and settlement measurement of
the gravelly soil on submergence were examined in
the laboratory. The HR-SW survey provided a vitalclue about the weakly-compacted state of the sitethat was the cause behind group subsidence andtherefore, was considered to be a vital tool for suchinvestigations.
RESULTS OF HIGH-RESOLUTION SURFACEWAVE (HR-SW) SURVEY

INTRODUCTION
A high-resolution surface wave (HR-SW) survey
enables us of manifesting a 2-D depth profile ofelastic shear wave (S-wave) for a site if interest in a
non-destructive manner [1]. Rayleigh wave has
dispersibility. The short wavelength Rayleigh wave
passes a shallow layer and the long wavelength
Rayleigh wave passes a deep layer. Additionally, avelocity of Rayleigh wave and a velocity of S-wave
are even approximately. Therefore, it is possible toget a 2-D depth profile of elastic S-wave bymeasuring the Rayleigh wave velocity. The HR-SW
survey is quick to perform and cost-effective
compared to other soundings method in geotechnicalengineering practice. This paper describes a casestudy in which a ground subsidence of recently
reclaimed road in Taka-Cho, Hyogo Prefecture,
Japan is cited. The ground subsidence had developed
at some places over several years since the sewage
pipe was mounted and backfilled with a gravellysoil. In the year of 2011, the ground deformation had
eventually triggered a serious damage to local
houses and the local government commissioned us
to investigate the cause of the ground subsidence,
together with countermeasure to prevent further
damage. Accordingly, the HR-SW survey was
performed so as to manifest the 2-D profile of Swave velocity over the reclaimed portion along theroad. The basic physical properties, together with the

Figure 1 shows ground subsidence around asewage manhole, whereas Fig. 2 shows an inclined
fence of a local house due to the ground deformation,

Fig. 1 Subsidence around Fig. 2 Inclined fence of aa manhole at B1
house at B1
160

GEOMATE-Nagoya, Nov.13-15, 2013

respectively. Figure 3 shows the survey lines A(95m long) and B (143m long) along the local roads,
for which the HR-SW survey was carried out. It
should be mentioned that the ground deformation as
well as the damage to the adjacent houses took place
in a narrow area at B1. In the survey, two adjacentreceivers were fixed at 1m interval.
The profile of S-wave velocity, V s , with depth isshown in Fig. 4 As can be seen in Fig. 4 , theLine-A

A1

boundary between the original ground and the filllies at around 2m depth, below which the V s exceeds
300 m/sec. Note that the V s for the point B1, where
the ground subsidence is significant, is lower ataround 150 m/sec when compared to the V s of about
200m/sec at other points A1, A2 and B2, all showing
no subsidence. The difference of V s between B1 andthe others certainly suggests that the gravelly soil inthe deformed zone at B1 may be somewhat in alooser (or under-compacted) by showing lower V s .
Figure 5 shows the profile of SPT N-value whenestimated by using the following empirical
relationship;
Vs = a N b

A2

Line-B

B1

where the constants of a = 80 and b = 0.33 assuggested by IMAI et al (1975) were employed forthe estimation. As shown in Fig. 6, the estimated Nvalue is close to the measured value. Note also thatthe measured N-value of the fill is about 5 on
average to what depth, suggesting a loose state of
the fill.
RESULTS OF LABORATORY TESTS

B2

Fig. 3 HR-SW survey performed(a) Line A

A-1

A-2

S-waveDepth (m)intersection point(1)

Distance (m)
B-1

B-2

intersection point

Depth (m)(b) Line B(front Part)Distance (m)Fig. 4 Profile of Vs along the survey lines A and B

Depth (m)(a) Line A
intersection point(b) Line B(front Part)

A-1

A-2

N-value

Distance (m)intersection point

Depth (m)B-1

Distance (m)Fig. 5 Profile of SPT N-value along the survey lines A and B
161

B-2

GEOMATE-Nagoya, Nov.13-15, 2013

2.15

0

a) TAKA

2.10 (Original grading)3
Ec=550kNm/m

2.05
r-v
ai

1.95

d
oi
rv

cu

1.90

e

3

2.00

ro

2

Ze

Depth, z (m)3

Dry density, ρd (g/cm )

1

1.85
1.80

: A-1
: A-2
: B-1
: B-2

1.75

4

1.70
4

: estimated N−value
: SPT

5
0

20

60
40
N−valueb) TAKA(d < 2mm)

3

3

Dry density, ρd (g/cm )

1.85

e

1.80
1.75
: A-1
: A-2

23

1.3

1.8

0.7

SG-F SG-F

GFS

GS-F

rv

33

cu

20

d
oi

B2

r-v

B1

1.90

1.70
8

0.9

16

ai

Category

A2

2.656 2.627 2.643 2.646
33

14

ro

Coefficient of uniformity
Uc
Coefficient of curvature
Uc'

12

Ze

Soil density, ρs g/cm

310

1.95 Ec=550kNm/mTable 1 Physical properties of four samples
A1

8

Water content, w (%)

2.00

80

Fig. 6 Measured and estimated SPT N-value

Samples

6

10

: B-1
: B-2

12

14

16

18

Water content, w (%)

Fig. 8 Compaction curves of four samples; a)original grading and b) grading less than 2mm [3]Percentage finer (%)

100
TAKA

original grading of sample B1 are the lowest and thelargest than those of the other samples, respectively.
The trend is reasonable since the Fc of sample A1
and B1 is the largest among all the samples.
The settlement of the samples on submergence
was measured in the laboratory. In a rigid-box
consolidometer, the partly-saturated sample having
the optimum water content and the dimension of
6cm in diameter and 4cm in height was subjected tothe prescribed vertical stress of 40 kPa. It was thensubjected to submergence while the vertical stress
was kept constant at 40 kPa. The results are shownin Fig. 9 In each of these figures, the variation ofcompressive strain with time is examined for threesamples having the degree of compaction of 80%,
85% and 90%. It should be mentioned here that theamount of settlement on submergence increased as
the nominal degree of compaction increased. The
trend is more clearly seen in Fig. 10, in which theaxial strain on submergence is plotted against thedegree of compaction. The following should be
noted;.
i) For all the samples, the settlement whensubmerged was almost zero when the degree ofcompaction was larger than 80 %, andii) The settlement of sample A1 and B1 at loosest
state with the degree of compaction of 78 %was significant.

80 A-1:
60

A-2:
B-1:
B-2:

40
20
0

0.01

1
grain size (mm)100

Fig. 7 Grading curves (original grading)

Soil samples were retrieved at points A1, A2, B1
and B2, bearing in mind that the observed grounddeformation was significant at A1, A2 and B1 (refer
to Fig. 3). Table 1 shows physical properties, whereas the grading curves of these four samples areshown in Fig. 7 [3]. All the samples are gravel-richcoarse-grained soil, which is in general suitable forthe fill geomaterials. However, a subtle difference
can be noticed in terms of fines content, F c ; i.e., theF c was the largest in sample B1 as compared to therest.
Figure 8 shows the result of Proctor test for thesefour samples. As can be seen in Fig.6, the maximum
dry density and the optimum water content of the

162

)%

GEOMATE-Nagoya, Nov.13-15, 2013

0

0

1

1

2

2

3
0

50

100

150

200

250

3
0

300

0

0

1

1

2

2

3
0

50

100

150

200

250

3
0

300

50

100

150

200

250

300

50

100

150

200

250

300

Fig. 9 Results of submerge test [3]0Axial strain, ε a (%)

Based on these observations, the soil at B1
having higher fines content could have been
backfilled at loose state with the degree ofcompaction less than 80%, which in turn had
resulted in lower Vs as compared to the other points.
The ground subsidence is concentrated over anarrow area around B1, the cause of which may be
attributed to under-compaction. To avoid groundsettlements, such as above, it seems very important
to compact the gravel-rich soil properly. Similarly,
finer particles should be washed out when using thegravelly soil as a fill material.

0.5

1
: A-1
: A-2
: B-1
: B-2

1.5

TAKA

2
70

80

90

100

Degree of compaction, Dc(%)

Fig. 10 Relationship between axail strain on submergence and the degree of compaction [3]CONCLUSION

comments on the manuscript. Mr. Lee. J-H was
generous in providing his test data in the laboratory.

In this case study, the value of high-resolution
seismic survey was well demonstrated in a mannerthat the deformed ground was properly pin-pointedby showing the low profile of elastic shear wave
velocity. The area, where the ground subsidence wasobserved, was backfilled with the gravelly soil
having higher fines content as compared to the othernon-deformed areas. Based on the results ofcompaction and submerge tests in the laboratory, thesoil could have been backfilled at a degree ofcompaction less than 80%. To avoid groundsettlement as such, it seems quite important toproperly compact even the gravel-rich soil.
Similarly, fine grains should be washed out whenusing the gravelly soil as a fill material.

REFERENCE[1] Hayashi K,"CMP Analysis of Multi-channel
Surface Wave Date", Proceeding of the SEGJ
Conference, 105th, Society of Exploration
Geo-physicists of Japan, 2001, pp. 13-16.
[2] Imai T, Fumoto H, Yokota K,"The Relation of
Mechanical Properties of Soils to P- and Swave Velocities in Japan", Proceedings ofJapan Earthquake Engineering Symposium, 4th,
Japan, 1975, pp. 89-96.
[3] Lee J-H, Shibuya S, Yamamoto T, Okamoto K,
T N Lonani, "Laboratory Investigation on the
One-dimensional Settlement Characteristics ofFill Materials due to Submergence", 4th, JapanKorea Geotechnical Workshop, 2013.

ACKNOWLWDGEMENT
The Authors are grateful to Dr T.N. Lohani for his
163

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

MODIFICATION OF KAOLIN MINERALOGY AND MORPHOLOGYBY HEAT TREATMENT AND POSSIBILITY OF USE IN
GEOTECHNICAL ENGINEERING

Nurmunira Muhammad1, Ideris Zakaria1 and Abdoullah Namdar1
Faculty of Civil Engineering & Earth Resources, University Malaysia Pahang, Malaysia.
aira.munira@gmail.com

1

ABSTRACTThis paper presents an experimental work on the effect of heat treatment on the mineralogy and morphologyof kaolin. Kaolin, which is moderately expansive, was preheated at temperatures ranging from 200°C to 800°C
by increment of 200°C and cooled at room temperature before it was mixed with peat. Peat represents acompressible soil and has low bearing value. The main aim of the work is to study the effect of heat treatment on
shear strength parameters of peat-kaolin mixture. The mixtures are prepared at different proportions, and at each
proportion triaxial samples were prepared and tested in the undrained condition to study the shear strengthparameters. Untreated kaolin-soil mix was also prepared to provide a comparison between the treated anduntreated soil mix in terms of the shear strength behaviour. XRD and FESEM were also carried out to investigate
the change in soil micro-structure due to heat treatment. The tests showed that there was a slight improvement in
the strength of peat-kaolin mixture when kaolin was preheated to a temperature of up to 400°C. Finally results
were discussed and conclusions were made for the preheated kaolin-peat mixture.
Keywords: Kaolin, Peat, Heat treatment, Triaxial, Shear strengthcomposition like the transformation from kaolinite
to metakoalinite when kaolin is heated to between
650°C and 850°C [6].
A number of researchers recently studied thereplacement of the synthetics products for ground
improvement by more natural additive such as fly
ash, coal ash, lime slurry, bentonite, recycled
gypsum and waste plastic trays [7]. In fact, naturally
occurring weak soils are the types of soil that needmore attention to improve their engineering
properties. The term ‘weak soil’ mentioned in thisstudy refers to an organic soil that has highcompressibility but low permeability, bearing
capacity and shear strength.
In engineering projects, weak soils haveunacceptable physical and mechanical properties.
For example peat is a problematic soil. In Malaysia
peat is found mainly in low-lying poorly drained
depressions or basins in the coastal areas thatoccupies over a total of 2.7 million hectares, which
represents about 8% of the total land area of thecountry [8]; hence, the need to find solutions tostrengthen this problematic soil before any projects
is built on it.
In a comparative study by other researchers had
found that the amendment of peat with 10% kaolin
could increase the compressive strength [9]. Ref
Kalantari et al [10] also found a solution forincreasing compressive strength of peat by mixing itwith cement and fibers. However, another study has

INTRODUCTION
Kaolin is a subgroup of the clay family ofmineral which contains polytypes such as kaolinite,dickite, nacrite and halloysite [1]. Mineralcompositions of the tropical residual soils in
Malaysia are mostly dominated by kaolinite which
occurs from weathering or hydrothermal processes.
Kaolinite is the principal mineral element in Kaolin
which is used in various industries and has a natural
moisture content between 16 to 49% [2],[3].
Kaolinite crystals are usually 0.2–2 micrometersin size. Kaolinite (A1 2 Si 2 O 5 (OH) 4 ) is a 1:1 typeclay mineral composed of stacked layers of SiO4
tetrahedral (silica) sheets and AlO 2 (OH) 4 octahedral(alumina) sheets. The ideal chemical composition isAl 2 O 3 39.53%, SiO 2 46.51% and H 2 O 13.96% [4].
The particles tend to agglomerate more strongly at ahigher temperature and produce higher amount ofcoarse particles. Yilmaz [5] had mentioned that thethermal treatment affects the behaviour of clays
through the influence of absorbed water. It may
cause dispersion of flocculation effects dependingon kaolinite mineral and the type of ion exchange.
The disintegration of soil particles is completed
when the water around the particles is removed. Thissituation may lead to particle growing to larger sizes.
The XRD pattern study shows that only a small partof kaolinite mineral remains when kaolin is heated at
500°C. Some changes are observed in mineral
164

GEOMATE-Nagoya, Nov.13-15, 2013

shown that by increasing the amount of kaolinite
may increase shear strength of soil treated but cause
shrinkage of cement grout in grouting method [11].
Construction industries in the United States use
soil mixing technique, a low-cost method in a ratioof one to five compared with other solutions; andthis technique is used to treat contaminated soft soil
[12]. Soil mixing can be used to treat contaminatedsand as well [13]. Deep mixing method is an option
to use for mixing the binding agents such as lime
or/and cement because it may improve thepermeability, strength and deformation properties of
weak soil [14]. But, when the depth of peat layer isless than 4m, the mixing method is not effective
enough.
The present work analyzes the effect of heat
treatment on the shear strength parameters of thepeat-kaolin mixture. We applied the soil mix design
method of peat-kaolin mixtures in laboratory
conditions to assess the improvement of engineering
properties.
MATERIALSAND
CHARACTERIZATIONTECHNIQUE

200°C, 400°C, 600°C and 800°C. The specimens
were prepared by laboratory soil mixing method atmass ratio of peat soil mix at 90:10, 80:20, 70:30.
60:40 and 50:50%.
Table 1 Chemical composition of kaolin
Type of properties

•
•
•
•
•
•

Aluminium (Al 2 O 3 )Silica (SiO 2 )Iron (Fe 2 O 3 )Potassium (K 2 O)
Magnesium (MgO)
Loss on Ignition @1025°C

Kaolin(Manufacturer data)• B32.0 – 38.0 %• 47.0 53,0 %• Below 1.3 %• Below 2.5 %• Below 0.5 %• 11.0 – 14.0 %Laboratory furnace has been used to burn kaolinwith different temperatures for 1 hour. In order toinvestigate the effect of peat and kaolin mix on shear
strength, soil compaction tests were conducted byusing automatic compactor with 1 L mould. These
tests are needed to determine the optimum moisture
content. After mixing thoroughly, the soil samples
again were compacted with the same compactermachine and then they were extruded using an
extruder to a sample cylinder with the size of 38 mm
diameter and 76 mm high. All re-compacted samples
were left to mature in a clear plastic tube container
for at least 24 hours. The unconsolidated-undrained(UU) Triaxial test has been used in order todetermine the shear strength parameters. The valuesof the shear strength parameters reported here were
the average values. The UU tests were performed
according to BS 1377:1990 Part 7. In the second partof this study, the XRD and FESEM were also
carried out to investigate the change in soil microstructure due to heat treatment to gain better
understanding of improvement of soil mixing
properties.

OF

Materials
In the field, the predominant soil types based on
texture are identified by inspection. Generally, theidentification and description methods of soils havealready been clarified in BS 5930 Section 6. Since
the texture and colour of peat soil is different thanother soils it is easier to notice. Peat soil contains
sediments from woody remains such as roots,
branches and tree trunks. Typically the colours ofpeat are from dark brown to black. The samples forthis study were taken at Jalan Kuantan-Pekan,
Pahang, Malaysia in the coordinate of longitude E
103.301239 and latitude N 3.650854. The area has
soils that have organic content.
The commercial kaolin mineral as shown in
Figure 3.4 was imported from Kaolin (Malaysia)
Sdn. Bhd. This is one of the main mineral suppliersin Malaysia that extracts and process kaolin in theirown factory in Tapah, Perak. Type of kaolin
powdered that has been used in this study is C type.
The moisture content of C type is less than 7.0% innatural condition. Average particle size of thispowdered kaolin in between 2.5 µ – 4.5µ and the pHof 30% solid mineral are between 3.0 – 5.0. The
chemical composition of kaolin as provided by the
manufacturer is summarized in Table 1.

RESULT AND DISCUSSION
The weak soil properties have been analyzed
based on BS1377:1990 as shown in Table 2. Before
the untreated soil was tested in laboratory condition,
the observation was done by visual classificationaccording to ASTM D2487. The visualization result
obtained was ML (silt content with low plasticity),
but the laboratory test result refined theclassification as sandy silt with organic matter. The
influence of different proportions of soil mixture
with different levels of temperatures has been
investigated and the results are presented in tables
and figures.

Experimental methods
In order to investigate the changes in engineering
properties of our soil samples mixed with thermallytreated kaolin, tests were conducted for mixtureswith raw kaolin and with kaolin thermally treated at
165

GEOMATE-Nagoya, Nov.13-15, 2013

Table 2 The properties of untreated weak soil
Properties
•
•
•
•
•
•
•
•
•
•

Moisture content (%)
Organic content (%)
Ash Content (%)
Specific gravity, Gs
Liquid Limit (%)
Plastic Limit (%)
Plasticity Index (%)
Bulk Density (kg/m3)
Soil Type (USCS)
Description

rearrange and reorientate themselves into a new
more stable position [15] but when the thermal
treatment took place, the bulk density gradually
decreased with temperature due to particle size
distribution [16]. Eventually, when kaolin issubjected to heating process, particles are found to
agglomerate more strongly and lead to have acoarser fraction. Hence, the treatment tends toreduce the density of the mixture soil samples.

Organic soil
•
•
•
•
•
•
•
•
•
•

23.15
10.5
89.5
2.58
38.93
27.65
11.28
1986.98
SM
Sandy Silt with
Organic Matter

Influence of soil mixing on shear strength
Shear strength was developed from both 50KPa
cell pressure and deviator stress with maximum
values of 182.0KPa for peat and unheated kaolin
mixture at about 10% mix ratio. Figure 2 shows thepattern of the different shear strength values in termof percentage mixture. As we can see, when the
proportion of mixture was increased, the shear
strength value decreases.
At higher temperatures, shear strength of peat
mixed with thermally treated kaolin decreases. The
soil mixture at 400°C shows kaolin has lesser values
in shear strength than the unheated and 200°C ofheated kaolin. The main concern in shear strength
development is related cohesion and the angle offriction.
The correlation coefficient (R square) byregression shows a relationship between cohesion
and internal angle of friction with effects of gradientof temperature. By referring to Fig.3, the cohesion of
mixture soils is found to gradually decreasing with
the increasing of soil mixture temperature with R
square being 0.998. In addition, the internal angle offriction (Fig.4) was increased steadily withincreasing temperature of mixture and the R square
is 0.997. When the soil is mixed with heated kaolin,
the optimum moisture content increased but thecohesion was found to decrease steadily.
Without stabilization the untreated peat specimen
has very low cohesion and internal angle of friction.
This is because organic soil such peat has poor
mechanical properties. Strong correlations were
found between the internal angle of friction andthermal treatment of kaolin as determine by Yilmaz[5]. The internal angle of friction depends on thegrain size distribution of thermal treated kaolin. The
experimental results show gradually decreasing
shear strength values. If we continue the experiment
the results might show lower value of shear strength
as the temperature increases. Hence, theinvestigation was stopped at 400°C.

Influence of soil mixing on optimum moisture
content
Figure 1 shows the graph of optimum moisture
content for soil mixture samples with different ratiosof kaolin-peat mixtures at various temperatures.
When the organic soil has been mixed withincreasing proportions thermally heated kaolin, theoptimum moisture content gradually increased.
Theoretically, when the soils are subjected to heat,
dewatering process will take over after all the
moisture is trapped in voids it evaporated in. Due tothis dewatering process, the natural mineral soil
subjected to thermal high temperatures will go
through this process. Hence, the optimum moisture
content of thermally heated kaolin will be muchhigher than the raw kaolin.

Fig. 1. Graph of optimum moisture content against
soil mixture samples
Moreover, one of the factors that can also be
discussed due to high OMC with low MDD are theparticle rearrangement and orientation. While thepreferred orientation increased as the moisture
content increases, the particles, pores and otherelements tend to become parallel with each other. As
expected, the long platey particles seemed to be
166GEOMATE-Nagoya, Nov.13-15, 2013

soil. It can be observed from this figure that otherelements such as S, K and Ca are present. Table 3
lists the components identified in the 10% natural
mixed soil. It has been observed that, the bonding ofsilica and alumina has shown major distribution
effect among the elements. But the presence of someelements is detrimental to good bonding and formingstrong compound of stabilizing weak soil. In theiranalysis of unconfined compression tests, Wong etal have shown the presence of high peaks of Ca, Si
and O after curing the test specimens. These threeelements would form calcium silicate hydrate as amain cementation product in stabilized soil [9].
Even though this EDAX analysis did not show ahigh percentage of Ca, yet this element plays animportant role as a bonding agent to form an
optimized mixture soil in this study. This can beclearly observed from the particle morphology of
10% mixture in Fig.6. The platy structures areclosely packed together and reducing voids between
the particles. Such association development is likely
because the kaolin particle surface charge iscompensated and hydrogen bonds can dominate
instead of stronger ion-dipole interactions [17].

Fig. 2. Graph of shear strength against percentage ofsoil mixture samples

Fig. 3. Graph of cohesion against kaolin temperatureof soil mixture samples
Fig. 5. The EDAX result for optimum design of
mixed soil sample
Table 3. The component obtained for optimum
design of mixed soil samples
Element
C
Al
Si
S
K
Ca
O
Fig. 4. Graph of internal of friction angle against
kaolin temperature of soil mixture samples
Influence of mineralogy and morphology on
optimal design of mixing soil
Figure 5 shows the energy dispersive X-ray
characterization for optimum design of mixed soil
sample that was 90% peat with 10% unheated kaolin
167

Weight
7.04
11.37
23.66
0.25
0.87
0.31
56.50

FormulaCompound (%)

CO2
Al2O3
SiO2
SO3
K2O
CaO

25.80
21.47
50.62
0.63
1.05
0.43

GEOMATE-Nagoya, Nov.13-15, 2013[3] Nixon IK., Skipp BO, “Airfield construction on
overseas soil: Part 5, Laterite”. Proc. Inst. Civ.
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andEngineering
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additive”, Construction and Building Materials,
40, 2013a, pp. 783–792.
[10] Kalantari B, Prasad A, Huat BBK, “Use of
cement, polypropylene fibers and optimum
moisture content values to strengthen peat”,
International Journal of the Physical Sciences,7(8), 2012, pp. 1276–1285.
[11] Kazemian S, Huat BBK., Barghchi M, “Effectof calcium chloride and kaolinite on shear
strength and shrinkage of cement grout”, 6(4),2011, pp. 707–713.
[12] Christopher RR, Brian HJ, “Deep soil mixing atjackson lake,” ASCE Geotechnical Division
Specialty Conference, vol. 1–14, no. June 25–29,
1989.
[13] Ayotamuno M J, Martin RJ, “Soil mixing ofstratified contaminated sands,” pp. 53–75, 2000.
[14] Larsson S, Rothhamel M, Jacks G, “A
laboratory study on strength loss in kaolin
surrounding lime-cement columns” Appl ClaySci 2009;44:116–26.
[15] Cetin H, Fener M, Söylemez M, Günaydin O,“Soil structure changes during compaction of acohesive soil”, Engineering Geology, 92(1-2),
2007, pp. 38–48.
[16] Chandrasekhar S, Ramaswamy S, “Influence ofmineral impurities on the properties of kaolin
and its thermally treated products”, Applied
Clay Science, 21(3-4), 2002, pp. 133–142.
[17] Kim S, Palomino A M, “Polyacrylamide-treatedkaolin: A fabric study”, Applied Clay Science,45(4), 2009, pp. 270–279.

Fig. 6. The morphology photo of optimum soil
mixing design by FESEM
CONCLUSION
This study was carried out to investigate theeffects on shear strength of peat soil treated withunheated and thermally heated kaolin, added indifferent proportions. It was observed that, whencohesion increases, the internal angle of friction
decreases. This phenomenon can be observed basedon the effect of soil mineralogy on internal angle offriction in soil mass. When kaolin is subjected to
400°C we can see a substantial decrease of soil
cohesion, and in the same time, the internal angle offriction is increased. It can be indicated that bonding
sheets of silica and alumina in clay indirectly
controls the internal angle of friction. The best result
has been observed in the combination of 10% of
unheated kaolin to the peat. This research work was
limited to the specimen in the laboratory. For moreinvestigation the subsoil or earth structure can bemodelled using materials used in this research work
for more application of produced materials.
ACKNOWLEDGEMENTS
The authors wish to express their gratitude to the
Faculty of Civil Engineering & Earth Resources andCentralized Lab at Universiti Malaysia Pahang for
the use of lab facilities.
REFERENCES[1] Brindley GW, “Mineralogical Studies of
Kaolinite-Halloysite Clays: Part I. Identification
Problems,” The American Mineralogist. Vol.,48, 1963, pp. 897-910.
[2] Maail S, Huat BBK, “Index, engineering
properties and classification of tropical residualsoils”, Tropical Residual Soils Engineering,
Taylor & Francis Group, London, 2004, pp. 37–
55.

168

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SIMULATING THE EFFECT OF FLOW VOLUME ON SCOURING
PROCESS AROUND BREAKWATER UNDER TSUNAMI CONDITIONBY SPH METHOD
M.R. Islam1, K. Hayano1 and A.M.K.N. Nadeesha1
School of Urban Innovation, Yokohama National University, Japan

1

ABSTRACTThe study has attempted to simulate scouring process around the breakwater by smoothed particle
hydrodynamics (SPH) method. SPH is a mesh less numerical method with a high capability of simulating large
deformation of geo-material. However, SPH application in geotechnical problem is relatively new. The study has
developed a simplified model arrangement with water and soil particle. Scouring process was simulated forsaturated and dry soil by allowing water to fall continuously. The soil has the properties of elastic-perfectly
plastic model with Mohr-Coulomb failure criteria. The water has the properties of viscous fluid. Scouring
occurred as seepage force tried to drag the soil particles. Scouring process was found to advance with time andwith increase in flow volume for both saturated and dry soil. The outcome of the study will help to predict thescour process around breakwater.
Keywords: SPH, Breakwater, Scour, Flow volume
INTRODUCTION
The Kamaishi seawall of 63 meters depth and
1,950 meters length was collapsed by the Great East
Japan tsunami 2011. It was considered that scouring
by the overtopping water had lowered the stability ofthe seawall foundation and caused to collapse.
Scouring process consists of fluid movement andinteraction with soil. To encounter such a complex
problem Smoothed particle hydrodynamics (SPH) isvery effective. SPH method is a particle method anddoes not require any mesh. A simplified 2D SPH
model of water falling into the landward side of the
breakwater is presented here. The study has
attempted to simulate the behavior of scouring
process by using the simple model. For developing
the SPH code, the study has adopted the SPH theory
written in Liu’s book [1].

influence domain of the smoothing kernel. 𝑊𝑊(𝑥𝑥 −𝑥𝑥 ′ , h) is the kernel or smoothing function, whichmust satisfy the following three properties: the firstone is the normalization condition,∫Ω 𝑊𝑊(𝑥𝑥 − 𝑥𝑥 ′ , ℎ)𝑑𝑑𝑥𝑥 ′ = 1

The second condition is the delta function
property that is observed when smoothing length
approaches zero,limℎ →0 𝑊𝑊(𝑥𝑥 − 𝑥𝑥 ′ , ℎ) = 𝛿𝛿(𝑥𝑥 − 𝑥𝑥 ′ )(3)𝑊𝑊(𝑥𝑥 − 𝑥𝑥 ′ , ℎ) = 0, 𝑤𝑤ℎ𝑒𝑒𝑒𝑒 |𝑥𝑥 − 𝑥𝑥′| > 𝑘𝑘ℎ(4)

Additionally, the third condition is the compact
condition,

Where k is a scalar defines the influence domainof the smoothing function.

FUNDAMENTALS OF SPH
SPH is a particle method where thecomputational domain is discretized into a finite
number of particles (or interpolating points). The
material properties of a particle are evolved from theneighboring particles within support domain byusing interpolation function. The interpolation
process is based on the integral representation of afield function 𝑓𝑓(𝑥𝑥) follows:〈𝑓𝑓(𝑥𝑥)〉 = ∫Ω 𝑓𝑓(𝑥𝑥)𝑊𝑊(𝑥𝑥 − 𝑥𝑥 ′ , h)𝑑𝑑𝑑𝑑 ′(2)

Smoothing function

𝒙𝒙′

x
kh

(1)

Where Ω is the area of the integration that contains x
and 𝑥𝑥 ′ ; and h is the smoothing length defining the

Fig. 1169

Description of influence domain of a field
variable ‘x’.

GEOMATE-Nagoya, Nov.13-15, 2013

There are many kernel functions but the study has
used the cubic spline smoothing function. The cubic
spline function was proposed [2]. The cubic spline
function has the following form:
1.5 − 𝑅𝑅2 + 0.5𝑅𝑅3 0 ≤ 𝑅𝑅 < 1(2−𝑅𝑅)3
𝑊𝑊(𝑅𝑅, ℎ) = 𝛼𝛼𝑑𝑑 �
1 ≤ 𝑅𝑅 < 2
6

0 𝑅𝑅 ≥ 2115𝜀𝜀 𝛼𝛼𝛼𝛼 =(5)3Where,D 𝜌𝜌D 𝑡𝑡

𝑑𝑑𝑠𝑠 αβ𝑑𝑑𝑑𝑑𝑖𝑖

is the time derivative for density, 𝑚𝑚 is

D 𝑡𝑡

𝜎𝜎

𝛼𝛼𝛼𝛼

𝜎𝜎

𝛼𝛼𝛼𝛼

𝜌𝜌 𝑖𝑖

𝜌𝜌 𝑗𝑗

𝜕𝜕𝑊𝑊 𝑖𝑖𝑖𝑖
𝜕𝜕𝑥𝑥 𝛽𝛽+ 𝑔𝑔𝛼𝛼132 ∂𝑥𝑥 β+1 ∂𝑣𝑣 α𝑅𝑅αβ = (
2

(13)

∂𝑥𝑥 β

∂𝑣𝑣 β

∂𝑥𝑥 α

−

)

∂𝑣𝑣 β

∂𝑥𝑥 α

(14)
)

(15)

By combining Eq. (13), (14) and (15) the deviatoric
shear stress components are calculated. According to
the elastic-perfectly plastic soil model, the deviatoricstress components in the plastic region are scaled
back to the maximum shear stress by the MohrCoulomb equation(7)

𝑠𝑠f = 𝑐𝑐 + 𝑝𝑝tan𝜙𝜙(16)

Where, c is the cohesion and p is the mean stress and𝜙𝜙 is the angle of internal friction. Mean stress of soil
has been calculated as the Eq. (17)(8)

Where, p is isotropic pressure, 𝛿𝛿 𝛼𝛼𝛼𝛼 is the
Kronecher’s delta, τ𝛼𝛼𝛼𝛼 is the viscous stress for fluid.
Isotropic pressure for fluid is obtained from equationof state.
𝜌𝜌
𝑝𝑝 = 𝐵𝐵 �( )𝜆𝜆 − 1�(9)𝑝𝑝 = 𝐾𝐾(

𝜌𝜌

𝜌𝜌 𝑜𝑜

− 1)

(17)

Where, K is bulk modulus of soil. The study hastaken the value of the K less than the actual as in
the case of [4].

𝜌𝜌 0Where 𝜆𝜆 is a constant and set equal to 7 for mostcases; 𝜌𝜌𝑜𝑜 is the reference density; B is a problem
dependent parameter, which sets a limit for the
maximum change of the density. B is usually chosen

Soil- Water Interaction
In the preceding sections, SPH formulations for
fuids and soils were described. However, it isneeded how soil-water will interact with each other.
The study has adopted the concept of two-phaseflow for soil and water. When water will passthrough the pores of the soils, it will exert drag force
to the soil. This is called seepage force in soil. The
seepage force acts on the soil particle and will be
introduced into the momentum equation for soil and𝜌𝜌 𝑐𝑐 2

as 𝐵𝐵 = 𝑜𝑜
where, 𝑐𝑐 is the sound speed in
𝜆𝜆water . However, to keep the density variation
within 1% then 𝑐𝑐 = 10𝑣𝑣𝑡𝑡𝑡𝑡𝑡𝑡 is chosen.
For Newtonian fluids, the viscous shear stressshould be proportional to the shear strain rate
denoted by ε through the dynamic viscosity µ .
𝜏𝜏 𝛼𝛼𝛼𝛼 = µ𝜀𝜀 𝛼𝛼𝛼𝛼

(11)

(12)

= 2𝐺𝐺 �𝜀𝜀̇αβ − 𝛿𝛿 αβ 𝜀𝜀̇γγ � + 𝑠𝑠 αβ 𝑅𝑅βγ + 𝑠𝑠 γβ 𝑅𝑅αγ

1 ∂𝑣𝑣 αWhere, σ is the total stress tensor, and g is theexternal force. Total stress σ for fluid is defined as𝜎𝜎 𝛼𝛼𝛼𝛼 = −𝑝𝑝𝛿𝛿 𝛼𝛼𝛼𝛼 + τ𝛼𝛼𝛼𝛼(∇ ∙ 𝑣𝑣)𝛿𝛿 𝛼𝛼𝛼𝛼3𝜀𝜀̇αβ = (

𝜕𝜕𝜕𝜕

𝑗𝑗
𝑖𝑖
= ∑𝑁𝑁
𝑗𝑗 =1 𝑚𝑚𝑗𝑗 � 2 + 2 �

2Where, 𝐺𝐺 is shear modulus, 𝜀𝜀̇ is strain rate tensor, 𝑅𝑅
is rotation rate tensor are defined as in Eq. (14), (15)mass, 𝑣𝑣 is velocity ,is the first derivation of𝜕𝜕𝜕𝜕
kernel, i is the first particle, j is the neighboring
particle, N is the number of total neighboring
particle , α and β are co-ordinate direction.
Moreover, the momentum equation for each particle
becomes
D 𝑣𝑣 𝛼𝛼−where σ is total stress, p is mean stress and s isdeviatoric stress. However, deviatoric stress for thesoil has been calculated from Hook’s law as in theequation (13)

(6)

𝑖𝑖

𝜕𝜕 𝑣𝑣 𝛼𝛼𝜕𝜕𝑥𝑥 𝛽𝛽𝜎𝜎 𝛼𝛼𝛼𝛼 = −𝑝𝑝𝛿𝛿 𝛼𝛼𝛼𝛼 + 𝑠𝑠 𝛼𝛼𝛼𝛼The continuity equation used in the study is asfollows:
D 𝑡𝑡+

SPH formulation for soil is similar with fluidwith some exceptions. For soil the total stress is asfollows:

SPH Formulations for Fluid

𝛽𝛽 𝜕𝜕𝑊𝑊 𝑖𝑖𝑖𝑖𝛼𝛼= ∑𝑁𝑁
𝑗𝑗 =1 𝑚𝑚𝑗𝑗 �𝑣𝑣𝑖𝑖 − 𝑣𝑣𝑗𝑗 � 𝜕𝜕𝑥𝑥 𝛼𝛼𝜕𝜕𝑥𝑥 𝛼𝛼SPH Formulations for Soil

Where, 𝑅𝑅 = |𝑥𝑥 − 𝑥𝑥 ′ |/ℎ ,𝛼𝛼𝑑𝑑 = , 2 ,ℎ 7𝜋𝜋ℎ 2𝜋𝜋ℎ 3respectively in one, two and three dimensions.

D 𝜌𝜌𝜕𝜕𝑣𝑣 𝛽𝛽(10)170GEOMATE-Nagoya, Nov.13-15, 2013

water as in [4], [5] .
𝑣𝑣𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 − 𝑣𝑣𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠

𝑓𝑓𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = 𝛾𝛾𝑤𝑤 𝑛𝑛

In equation (21), p and q represent the first andsecond pair of the water particles. In the applicationsof the artificial compressibility to fluid flows, it isuseful to use the ‘XSPH’ technique proposed by [2].
In the ‘XSPH’ technique fluid particle finally moves
in the following way:

(18)

𝑘𝑘

where 𝛾𝛾w is the unit weight of water, 𝑛𝑛 is theporosity and 𝑘𝑘 is permeability of soil.

𝑑𝑑𝑑𝑑 𝑝𝑝

Artificial Viscosity

𝑑𝑑𝑑𝑑

The artificial viscosity terms are usually added tothe pressure term in the momentum equation todiffuse sharp variations in the flow and to dissipate
the energy of high frequency. The study has used
Monaghan type artificial viscosity ∏𝑖𝑖𝑖𝑖 . The detailformulation is as bellow:∏𝑖𝑖𝑖𝑖
Where,∅𝑖𝑖𝑖𝑖 =

=�−𝛼𝛼 ∏ 𝑐𝑐̅𝑖𝑖𝑖𝑖 ∅𝑖𝑖𝑖𝑖

0ℎ�𝑖𝑖𝑖𝑖 𝑣𝑣𝑖𝑖𝑖𝑖 .𝑥𝑥 𝑖𝑖𝑖𝑖

2
�2
�𝑥𝑥 𝑖𝑖𝑖𝑖 � +0.01ℎ𝑖𝑖𝑖𝑖

1ℎ�𝑖𝑖𝑖𝑖 = (ℎ𝑖𝑖 + ℎ𝑗𝑗 )2

𝑝𝑝̅ 𝑖𝑖𝑖𝑖

𝑣𝑣𝑖𝑖𝑖𝑖 . 𝑥𝑥𝑖𝑖𝑖𝑖 < 021𝜌𝜌̅𝑖𝑖𝑖𝑖 = (𝜌𝜌𝑖𝑖 + 𝜌𝜌𝑗𝑗 )2

In the above equations , 𝛼𝛼∏, 𝛽𝛽∏ are constants, in the study for water the values were taken as
0.01 and 0 respectively. However, for soil the values
for the both were taken as 1.0.
With the inclusion of seepage force and artificial
viscosity the momentum equation for soil is asfollows;
𝛼𝛼𝛼𝛼

𝛼𝛼𝛼𝛼
𝑝𝑝𝑗𝑗
𝜕𝜕𝑊𝑊𝑖𝑖𝑖𝑖𝑝𝑝= − � 𝑚𝑚𝑗𝑗 � 𝑖𝑖 2 + 2 �D𝑡𝑡𝜌𝜌𝑖𝑖
𝜌𝜌𝑗𝑗 𝜕𝜕𝑥𝑥 𝛽𝛽
𝑗𝑗 =1

D𝑣𝑣𝑖𝑖𝛼𝛼

𝑁𝑁

+ 𝑔𝑔

𝛼𝛼

𝛼𝛼𝛼𝛼

𝜎𝜎𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = �

𝛼𝛼𝛼𝛼

𝛼𝛼𝛼𝛼
𝑠𝑠𝑗𝑗
𝜕𝜕𝑊𝑊𝑖𝑖𝑖𝑖
𝑠𝑠
𝑚𝑚𝑗𝑗 � 𝑖𝑖 2 + 2 � 𝛽𝛽𝜌𝜌𝑖𝑖𝜌𝜌𝑗𝑗 𝜕𝜕𝑥𝑥
𝑗𝑗 =1
𝑁𝑁

+�

𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠

𝛼𝛼𝛼𝛼

(24)

𝐷𝐷𝐷𝐷

(25)

𝐷𝐷𝐷𝐷

(26)

𝐷𝐷𝐷𝐷

(27)

𝑣𝑣𝑛𝑛+1/2 = 𝑣𝑣𝑛𝑛−1/2 + ∆𝑡𝑡( )𝑛𝑛
𝐷𝐷𝑡𝑡

𝛼𝛼𝛼𝛼

𝑥𝑥𝑛𝑛+1/2 = 𝑥𝑥𝑛𝑛−1/2 + ∆𝑡𝑡( )𝑛𝑛
𝐷𝐷𝐷𝐷

𝑠𝑠𝑛𝑛+1/2 = 𝑠𝑠𝑛𝑛−1/2 + ∆𝑡𝑡( )𝑛𝑛
𝐷𝐷𝐷𝐷

Where ∆𝑡𝑡 is the time step; n indicates the current
time t; and (n+1) indicates the advanced time (t+∆𝑡𝑡).
The Stability of LF scheme is guaranteed by several
criteria for time step. The first one is the Courant-

𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑓𝑓− � 𝑚𝑚𝑞𝑞 �� 𝑊𝑊𝑖𝑖𝑖𝑖
𝜌𝜌
𝑞𝑞=1
𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝜌𝜌𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠
(21)
𝑁𝑁

(23)

𝐷𝐷𝐷𝐷
𝐷𝐷𝐷𝐷

𝛼𝛼𝛼𝛼
𝛼𝛼𝛼𝛼
𝑁𝑁
𝜏𝜏𝑝𝑝
𝜏𝜏𝑞𝑞 𝜕𝜕𝑊𝑊𝑝𝑝𝑝𝑝+ � 𝑚𝑚𝑞𝑞 � 2 + 2 �𝜏𝜏𝑝𝑝𝜏𝜏𝑞𝑞 𝜕𝜕𝑥𝑥 𝛽𝛽
𝑞𝑞=1
𝛼𝛼

+ 𝑔𝑔

𝛼𝛼𝛼𝛼

−𝜎𝜎𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑖𝑖𝑖𝑖 𝛼𝛼 ≠ 𝛽𝛽

𝜌𝜌𝑛𝑛+1/2 = 𝜌𝜌𝑛𝑛−1/2 + ∆𝑡𝑡( )𝑛𝑛

𝑝𝑝𝑝𝑝
𝑝𝑝𝑞𝑞 𝜕𝜕𝑊𝑊𝑝𝑝𝑝𝑝= − � 𝑚𝑚𝑞𝑞 � 2 + 2 �D𝑡𝑡𝜌𝜌𝑝𝑝
𝜌𝜌𝑞𝑞 𝜕𝜕𝑥𝑥 𝛽𝛽
𝑞𝑞=1
𝑁𝑁

𝛼𝛼𝛼𝛼

𝜎𝜎𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑖𝑖𝑖𝑖 𝛼𝛼 = 𝛽𝛽Equation (6), (20) and (21) are integrated using astandard Leap-Frog (LF) algorithm with thefollowing integration schemes:

However, the momentum equation for water
becomes as follow:
D𝑣𝑣𝑝𝑝𝛼𝛼(22)Time Integration𝑓𝑓+ � 𝑚𝑚𝑗𝑗 �� 𝑊𝑊𝑖𝑖𝑖𝑖
𝜌𝜌
𝑗𝑗 =1
𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝜌𝜌𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠(20)
𝑁𝑁

𝑣𝑣𝑝𝑝𝑝𝑝 𝑊𝑊𝑝𝑝𝑝𝑝

A SPH particle near or on the boundary while
updating physical properties does not getneighboring particles from boundary side. This iscalled particle deficiency problem. The study has
used symmetric image particles proposed by [3].
For each real particle located within kh distancefrom the boundary , an image particle is createdsymmetrically outside of the boundary. The image
particle will have the same physical properties as thereal one except the velocity and stress tensor. The
velocity of an image particle normal to the boundaryis taken as minus of the real one, in order to preventthe real particles from penetrating the boundary.
However, velocity of an image particle tangent tothe boundary is kept equal to the real one in order tosimulate free-slip boundary condition on thesymmetric plane. The stress tensor of an image
particle is set according to the following relations:

1

,

𝜌𝜌 𝑞𝑞

Boundary Treatment𝑐𝑐̅𝑖𝑖𝑖𝑖 = (𝑐𝑐𝑖𝑖 + 𝑐𝑐𝑗𝑗 )

,

𝑚𝑚 𝑞𝑞

Where, 𝜀𝜀𝑥𝑥𝑥𝑥𝑥𝑥 ℎ is a constant usually in the range of 0
to 1.0. The study has used 0.001 and found goodresult.

(19)

𝑣𝑣𝑖𝑖𝑖𝑖 . 𝑥𝑥𝑖𝑖𝑖𝑖 ≥ 0= 𝑣𝑣𝑝𝑝 − 𝜀𝜀𝑥𝑥𝑥𝑥𝑥𝑥 ℎ ∑𝑁𝑁
𝑞𝑞=1

171

GEOMATE-Nagoya, Nov.13-15, 2013Friedrichs-Levy(CFL) condition,

Simulation Results for Saturated Soilℎ∆𝑡𝑡 ≤ 0.25 min⁡
( )
(28)
𝑐𝑐
And constraints due to the magnitude of particle
acceleration f
ℎ

(29)

ℎ2

(30)

∆𝑡𝑡 ≤ 0.25 min⁡(� )And viscous diffusion

𝑓𝑓∆𝑡𝑡 ≤ 0.125 min⁡( )𝑣𝑣

Time step ∆𝑡𝑡 for a simulation should be theminimum of value of Eq. (28)-(30).
DESCRIPTION OF NUMERICAL MODELS
A simplified model with a soil area of 0.095m X
0.25m was developed to simulated scouring process
around the breakwater. Continuous water with
discharges varying from 0.06m3/m/s to 0.11m3/m/s
with falling heights of 0.01m was allowed to fall on
the soil layer. Numerical simulations were done forthe case of both saturated and dry soil. Saturated soil
layer consists of both water and soil particle [4], [5]having the size of 0.005mX 0.005m. However, drysoil layer consists of soil particle only. The soil has
the elastic-perfectly plastic properties with MohrCoulomb failure criteria. The elastic modulus of thesoil was chosen as 20Mpa and Poisson’s ratio was
0.3 with zero cohesion value. The density of soil waschosen as 1800 kg/m3/m .The water was modeled as
viscous fluid having dynamic viscosity of 10-3 Ns/m2
and density 1000kg/m3/m . Figure 2 depicts the initialarrangement of the simulation model.

Fig. 2

Input condition of the simulation model.

Saturated soil was modeled as two-phase layer ofwater and soil [4], [5]. Although the soil and water
stay closer but their physical properties will begoverned by different system. The study has used
two-phase model to allow the seepage force to work
properly between water and soil. From Fig. 3 to Fig.
6 describe the progress of scouring process due tofalling water. The particles in the saturated soil were
found to show a little disturbance with the progressof simulation. This phenomenon may be related withexcessive pore water pressure development. The
study has used almost fifty percent of the saturated
soil mass as the water particles. Figure 7 shows the
progressive scouring depths with different flow
volume with same fall height of 0.01m. It shows thatwith increase of flow volume scour depths increase.

Fig. 3

Scouring progress of saturated soil at 0.005
seconds.

Fig. 4

Scouring progress of saturated soil at 0.01
second.

172

GEOMATE-Nagoya, Nov.13-15, 2013

Simulation Results for Dry Soil

Fig. 5

Dry soil layer was modeled with the soil particles
only. Fig.8, Fig.9, Fig.10 and Fig.11, show the
progress of scouring process. However, it isobserved that soil layer has the tendency of being
compressed. As the soil layer follows the principleof continuum mechanics, and drag force by thewater flow was considered in the momentum
equation for soil, it shows some compressive
behavior after being stressed by the drag force.
Fig.12 shows that with the increase of flow volume
scour depth increase. From Fig.7 and Fig.12, it isfound that saturated soil shows large value of scour
depth comparing with that of dry soil. It is because,in the study saturated soil has porosity filled withwater. However, dry soil was considered morecompacted than that of saturated soil.

Scouring progress of saturated soil at
0.02second.

Fig. 6

Scouring progress of saturated soil at 0.025
second.

Fig. 7

Progressive scouring depths for saturated
soil from 0.01m fall.

173

Fig. 8Scouring progress
0.005second.

of

dry

soil

at

Fig. 9Scouring progress of dry soil at 0.01second.

GEOMATE-Nagoya, Nov.13-15, 2013

CONCLUSION
The study has proved the capability of SPH
method to simulate scouring process aroundbreakwater in tsunami condition. In the simplified
model, adopted here, saturated soil was modeledwith water and soil particle. However, dry soil wasmodeled with only soil particle. It was found thatscouring process progress with time and withincrease of flow volume.

REFERENCES[1] G.R. Liu and M.B. Liu, “Smoothed Particle
Hydrodynamics; a meshfree particle method”, World
Scientific Publishing Co. Pte. Ltd. (2003)

Fig. 10 Scouring progress of dry soil at 0.02second.

Fig. 11 Scouring progress
0.025second.

of

dry

soil

[2] J.J Monaghan, “Simulating free surface flows
with SPH”, Computational Physics, Vol.110,(1994),pp 399-406.
[3] Libersky LD, Petschek AG, Carney TC et al.,“High strain Lagrangian hydrodynamics: a three
dimensional SPH code for dynamic material
response. Journal of Computational Physics
1993; 109: pp.67-75.
[4] Bui Ha H., K. Sako and R. Fukagawa,“Numerical simulation of soil-water interaction
using smoothed particle hydrodynamics (SPH)
method”, Journal of terramechanics 44 (2007)
pp.339-346.
[5] Maeda Kenichi, Hirotaka Sakai and Mamoru
Sakai, “Development of seepage failure analysis
method of ground with smoothed particle
hydrodynamics”, JSCE vol.7, 2004, pp.775-786.

atFig. 12 Progressive scouring depths for dry soil
from 0.01m fall.

174

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DEVELOPING A NUMERICAL MODEL FOR THE STABILITYDESIGN OF TUNNEL HEADING

1

Jim Shiau1 and Ryan Kemp1
Faculty of Engineering and Surveying, University of Southern Queensland, Australia

ABSTRACTThis paper describes the development and verification of a numerical model for tunnel heading using thecommercially available software FLAC. The developed model uses force relaxation techniques to simulate
reductions in tunnel heading pressures. A script file was developed using the built-in program language FISH
that enable automatic mesh generation for each problem analysed and allows that parametric studies to be carriedout efficiently. The model results were verified by comparing stability numbers with those established results
using rigorous limit analysis techniques, and were found to be within their upper and lower limits for all
condition analysed. The overall aim of this paper is to provide the end user with a ‘user friendly’ tool for thedesign of preliminary face pressures to prevent instability from occurring and to control and estimate groundsurface movements to tolerable limits.
Keywords: Numerical Modeling, Tunnel Heading, FLAC, Design(dependent on over consolidated ratio) and (5) poor
construction techniques.
This paper is concerned with volume changes
and stability at the tunnel heading as a result ofchanges in face pressures from the at-rest condition
for soft undrained soils. This paper seeks to developa FLAC model using the built-in program language
FISH for predicting heading pressures and stability
for slurry or Earth pressure balance (EPB) TBM.
This will in turn provide designers with a simple but
effective tool for estimating working headingpressures at the preliminary design stage and during
construction.
Rigorous solutions to the tunnel heading stability
problem have been presented by [2] and [3] using
finite element upper and lower limit analyses forplane strain headings. It was concluded that the true
solution lies within 10%, or less, of their upper andlower bounds. These accurate bounds are used inthis paper to verify the results obtained using thedeveloped FLAC model. Theoretical stability design
charts were then developed. It is expected that sucha development would assist the end users (industry)in their daily design work.

INTRODUCTION
As city’s grow and public infrastructure become
under greater pressures, governments are choosing
to supplement existing infrastructure systems byconstructing an underground network of tunnels.
Transport infrastructure, for vehicles and trains, aswell as services, for water transport, are being built
under urban areas, waterways and throughmountains using tunnel boring techniques.
Tunnel boring machines (TBM) have become thepreferred method of underground construction in
urban areas and are considered a relatively quick andsafe construction technique. TBM technology has
been improved significantly since its beginnings in
the 1960’s to where surface settlement in sensitive
areas can be limited by combining state of the art
TBM’s with suitable construction methodologies.
More research and improvements in soft soil tunnel
construction is needed to better understand andcontrol surface settlement and thus increase theapplicable of tunnel boring.
In today’s urban environment limiting the soils
response to tunnel boring is critical to ensure thattunnel induced movements does not have an adverse
impact on overlying buildings. Indeed, soil stresses
are changed during construction and in turninfluence the soils response [1]. These changes may
be due to: (1) volume change at the heading
resulting from differing heading pressures from theat-rest pressures, (2) volume change at the tail andlining annulus before grouting, (3) consolidation
settlement in soft clay soils from changes in porepressures as the TBM pushed through the soil, (4)consolidation settlement from changes in soil stress

PROBLEM DEFINITION AND FLAC MODEL
While real soil conditions and tunnel/soilinteractions are very complex, the model uses
simplified assumption to predicted theoretical soil
responses to tunnel construction using TBM’s. The
tunnel heading model assumes Mohr-Coulomb
failure criteria, plane strain, and undrained condition
with dimensions shown in Fig. 1. The tunnel lining
is assumed to be rigid and soil conditions
175

GEOMATE-Nagoya, Nov.13-15, 2013homogenous having uniform properties withincreasing depth.
As shown in Fig. 1, σ s is the surface surcharge, γ
is the unit weight, C is the overburden height, σ t is
the tunnel support pressure and S u is the undrained
shear strength of the soil. The tunnel support
pressure, σ t , at the at-rest condition is the state
where no volume change occurs as this internalpressure theoretically matches the in-situ pressures
before construction.

face pressures during construction. Practically thismeans that operators could be provided with a rangeof upper and lower limit face pressure during
construction for different materials and construction
geometries.
The overall heading stability is commonly
presented using the dimensionless quantities γD/S u
and (σ s - σ t )/S u and in conjunction with thegeometry ratio C/D [2]. These dimensionlessquantities, which are also adopted in this paper,
would help to define the point of instability,
providing designers and TBM operators withminimum heading pressures to prevent collapse andto estimate the sensitivity of the soil response to thetunnel boring and changes to face pressures.
A FLAC numerical model using the built-in
FISH language was developed that automaticallygenerates grid dimensions, solution commands andoutputs relevant plots for prescribed condition. The
developed model, using built-in program language
FISH, is user friendly with only limited soil
parameters and dimension inputs required by thedesigner to achieve relatively accurate andmeaningful results for preliminary design andconstruction purposes.
A typical mesh generated by FLAC using thedeveloped script is shown in Fig. 2. The grid was
generated by entering the required parameters in
Heading.fis and then calling the script from thecommand window.

Surcharge (σs)γ : Soil unit weight
Su : Undrained shear strengthC
H

Smooth rigid lining
Internal Pressure(σt)

D

Smooth rigid lining
Fig. 1

Idealized plane strain tunnel heading in 2D
space.

The tunnel heading problem can be approachedby making use of a force relaxation technique
whereby the internal pressure at the at-rest condition
is determined and then relaxed by a percentage ofthe at-rest pressure (equilibrium reached at eachrelaxation step) until σ t is equal to zero. Consideringthat during construction it is the slurry or earthpressures at the tunnel heading that is controlled, it
is generally accepted that the use of force relaxation
technique would provide a more realistic result whencompared to other methods such as the displacement
method. As the relaxation method better reflects theconditions at the cutter head and plenum of a slurryshield or EPM machine. Although there is somecontact between the soil and cutting disk thatprevents displacement at these areas, the heading is
predominantly supported by the pressure balance
generated at the heading during construction [4].
This is also the case when air pressure is used tosupport the face during maintenance.
When the heading pressure is relaxed, theheading stability decreases until yielding occurs at
the point of plastic instability, or where tunnel
collapse is immanent. This point is also where asudden change in tunnel face movement takes place[4]. While reaching this point of collapse is avoided,
it does provide a meaningful bound to designers inprescribing face pressure limits and in understanding
the sensitivity of the soils response to changes in

fix x

(σt)
fix x,yFig. 2A typical mesh generated by FLAC using
Heading.FIS(C/D=2).

It is aimed to develop a design tool that requires
a limited number of input, i.e. soils parameters andtunnel dimensions, as well as achieving a relatively
quick computation time while still providing
accurate and useable results to the designer. Fig. 3
shows a typical screen shot of the FISH input
window with a total of nine soil and geometricparameters required for analysis.
C=2; Height of overburden soil

D=1

;Diameter

SOIL_DEN = 1631

; Soil density

of

SOIL_COH = 80E3 ; Cohesion

176

SOIL_FRI = 0; Frictional angle

SOIL_DIL = 0; Soil Dilationthetunnelfix y

GEOMATE-Nagoya, Nov.13-15, 2013

Set_grav = 2*9.81;more g for stiff clay

Sigma_s = 0; surface surcharge

No_relax = 11

;force relaxation steps

Fig. 3around 50 steps, and this value was selected for themodel in subsequent verification analyses. Thismeans that at each relaxation step the tunnel headingpressure is relaxed (reduced) by 2% of the at-restearth pressure.

A typical FISH input window.

Table 2 Number of relaxation step optimization(C/D = 2 and grid size of 0.1 m).

The built-in program language FISH also allows
efficient parametric and sensitivity analysis to beundertaken by the use of ‘batch’ files.

Relaxation
steps

OPTIMIZATION OF MESH SIZE AND FORCERELAXATION STEPS

10
20
50
100

Table 1 Mesh size optimization (C/D = 2 and 10
relaxation steps).
Grid Size
(m)
0.2
0.1
0.05

Stability Number(σ s - σ t )/S u(This paper)-1.676-2.020-2.155Difference
(%)
N/A
12.58
8.57
0

Stability Number (σs - σt)/Su

One of the goals of optimizing the mesh size wasto ensure accurate test results by having smallenough elements to model soil behavior correctly
while at the same time minimizing computational
speed by limiting element sizes. With the aim ofsimplifying usability, a set mesh size for varying
ratios of C/D needed to be determined.
This convergence between accuracy andcomputational efficiency was achieved by trialingdifferent grid sizes between 0.2 m and 0.05 m.
Table 1 shows a summary of the mesh size
optimization results for different grid sizes
for C/D = 2.

Stability Number(σ s - σ t )/S u(This paper)-2.095-1.833-1.676-1.676

Difference(%)

Number of relaxation step
Fig. 4

N/A
20.6
6.6

Stability number against relaxation steps.

Once a grid size and reduction factor was
selected based on computational efficiencies andaccuracy, model verification was carried out
accordingly.

The difference between using a grid size of 0.2 m
and 0.1 m is over 20% while the difference between
using a grid size of 0.1 m and 0.05 m reduces to lessthan 7%. Considering that the difference in stability
number would be less than 7%, a grid size of 0.1 m
was selected as the optimal grid size for all
verification analyses.
Similarly, the number of relaxation steps
required for the model verification was optimized to
improve computational efficiency. Using a small
number of relaxation steps while reducing
computational time would decrease result accuracy.
On the other hand increasing the number ofrelaxation step increases computational time, andtherefore increases accuracy.
A number of trial runs were performed todetermine the optimal number of relaxation steps forthe validation and future analyses. Table 2 shows asummary of the results for a grid size of 0.1 m of
C/D = 2. The results are also shown graphically in
Fig. 4. It can be seen that convergence is achieved at

MODEL VERIFICATION
To verify the developed model in this paper,stability numbers were compared to the rigorous
upper and lower bounds published in [2] and [3].
The upper and lower bounds provide limits where
the likely ‘true collapse’ would occur. The point ofcollapse is the point where the soil reaches plastic
instability. Using the force relaxation technique, thepoint where the soil reaches plastic instability can be
determined by inspections from the plots of plastic
yields and unbalanced forces at all relaxation steps.
Figs. 5 - 8 show an example of the point where
the soils progress from the stable elastic state toplastic instability. This is for the case of (C/D = 2
and γD/S u = 2). Inspection of the unbalanced forcesin Figs. 5 and 6 shows that there is a relaxation stepat which the soil goes from a steady balanced force
state to a unbalanced force state, , indicating that a177

GEOMATE-Nagoya, Nov.13-15, 2013

has occurred (C/D = 2 and γD/S u =2).

failure mechanism formed. Similarly, inspection of
the plastic yields in Figs. 7 and 8 shows that there isa relaxation step where the soil surrounding thetunnel head and the soil above the head changes
from the elastic state to the plastic state in a single
relaxation step.
The step before plastic instability occurs, shownin Figs. 5 and 7, is considered to be the relaxation
step just before true collapse of the tunnel heading
would occur. The internal pressure, σ t , at thisrelaxation step is the value selected to determine thestability number for the tunnel heading. The internalpressure at this point with an appropriate factor ofsafety would be the pressure prescribed on theconstruction field sheet to provide operators with alower bound face pressure that should not be
exceeded.
The step after plastic instability has occurred,Figs. 6 and 8, results in a sudden increase in soil
displacement at the face and corresponding decreaseof ground settlement at the surface, along with asudden increase of unbalanced forces. At this step
the soil strength with the aid of the internal tunnelpressure can no longer support the overburden
weight and surface pressures, and tunnel collapse
would theoretically occur. The step where plastic
instability has occurred is therefore considered to beunstable and to be avoided during construction.

X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
YYYYYYYYYYYYYYYB
X
X
X
X
X
BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB

Fig. 7

Step before plastic instability has occurredfor C/D = 2 and γD/S u =2.

X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
YYYYYYYYYYYYYYYBXXXXBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB

Fig. 8

Step after plastic instability has occurredfor C/D = 2 and γD/S u =2 (plastic indicators
are shown in orange colour).

Table 3 shows a comparison of stability numbers
between FLAC (this paper) and those in [3] using
rigorous upper and lower bound techniques. This is
for the case of γD/S u = 3. The results are also showngraphically in Fig. 9.
Table 3 Comparison of stability numbers (γD/S u =
3).

C/D

1
2
3
4
5

Stability Number(σ s - σ t )/S u(This paper)
-0.12
-2.02
-4.23
-6.65
-9.26

Upper
Bound
[3]
-0.11
-1.82
-4.00
-6.29
-8.80

Unbalanced force before plastic instability
has occurred (C/D = 2 and γD/S u =2).

(σs - σt)/Su

Fig. 5

Lower
Bound
[3]
-0.74
-2.84
-5.03
-7.49
-10.11An increase inunbalance force

C/D
Fig. 9Fig. 6

Unbalanced force after plastic instability
178

Comparison of stability, this paper, with [3]and [4] (γD/S u = 3).

GEOMATE-Nagoya, Nov.13-15, 2013

to the tunnel heading.
As γD/S u increase (decrease in soil strength)
negative values of stability number are obtained.
From the equation (σ s - σ t )/S u , it is known that for anegative stability number, the value of σ t must be
positive ~ a positive “pushing” pressure is required
to prevent imminent collapse.

It can be seen from Fig. 9 that FLAC results arelocated within the upper and lower bounds. At small
C/D values the stability number is near the upperbounds and with increasing C/D ratios the stability
number moves slightly towards the lower bound.
These results indicate that the current developedmodel produce accurate results and can be used inestimating tunnel stability and provide tunnel design
engineers with suitable internal pressures at the
cutting face.

(σs - σt)/Su

RESULTS AND DISCUSSION
To expand our numerical study for other TBM
geometrical dimensions and for a wider range ofsofter soils, a series of parametric studies were
performed. Nowadays, diameter (D) of TBM’s canrange from less than 1 m, for services such as water
pipelines, to over 19 m for two level, three laneroads such as the 19.25 m TBM for the Orlovski
tunnel in St Petersburg. Overburden heights (C) can
range from several meters to over 50 m (English
Channel). The range of C/D ratios that TBM need tooperate in is therefore relatively large.
The range of strata conditions vary from hardrock to the soft collapsible soils. Practically, thedefinition of the strength of ‘soft’ soil may vary
worldwide however for the purpose of this paper
soft soil refers to soil strength ranging between firm
to very soft with undrained shear strength between 0
kPa and 50 kPa. It is typically these ‘soft’ soils that
require “positive” face support in order to prevent
collapse and limit surface settlement.
The computed numerical results are summarisedin Table 4 and a design chart using the values inTable 4 is shown graphically in Fig. 10.

C/D
Fig. 10 Design chart for the stability of tunnel
heading.
During construction, it is the softer soils that are
particularly problematic and considered the most
unstable, thus requiring tighter control at the face toprevent collapse or to limit surface settlement.
It should be noted that with softer soils (γD/S u >4), some plastic zones may occur before ‘full’ plastic
instability occurs. However, through inspection of
the plastic yield plots at internal pressures greaterthan the instability pressure it can be seen that these
localized plastic zones are generally located near thetunnel heading and do not remain plastic, and also
do not extent all the way to the surface. It indicatesthat if adequate pressure head is maintained thenlocalised failure can be prevented.
Clear differentiation can however be madebetween localized plastic zones with balanced
internal forces and full plastic instability whereinternal forces remain unbalanced. An interestingobservation is the areas of localized instability whenγD/S u > 4. This confirms the general rule by [5] thatbulging may occur at the tunnel heading although
the face at the pressure is considered to be within
acceptable limits.

Table 4 Stability of tunnel heading (σ s - σ t )/S u

γD/Cu

1

2

C/D
3

1
2
3

2.94
1.45

3.05
0.56

2.78
-0.69

2.34
-2.09

1.86
-3.76

-0.12

-2.02

-4.23

-6.65

-9.26

4

-1.66

-4.45

-7.77

-11.08-14.45

5

-3.10

-7.05

-11.26-15.43-19.94

6

-4.61

-9.54

-14.68-20.00-26.25

4

5

Example of Estimation of Internal Pressure

In Table 4, positive values of stability number,such as those with γD/S u = 1 and γD/S u = 2 for C/D= 1 and 2, would require a negative σ t (pullingpressure) to reach the point of imminent collapse.
Therefore they are considered as stable and require
no internal pressure to maintain the stability.
However, in practice elastic settlement may need tobe controlled and so face pressures would be applied

A tunnel with diameter (D) 6.0 m is buried at a
depth of 12 m (C) in an undrained clayey material
with properties S u = 27kPa, φ u = 0° and γ = 18
kN/m3. Given the surface surcharge loading σ s =10 kPa, determine the theoretical tunnel headingpressure σ t required to maintain the tunnel stability.
179

GEOMATE-Nagoya, Nov.13-15, 2013

The following procedures are used to determine
the theoretical internal pressure σ t .
1. Given C = 12 m and D = 6 m, C/D = 2.
2. Given S u = 27kPa and unit weight γ = 18 kN/m3 ,γD/S u = 4.0.
3. For a 2D tunnel heading problem with C/D = 2,
γD/S u = 4.0, Fig. 10 returns a value of(σ s - σ t )/S u = -4.45.
4. σ t can then be computed σ t ≈ 10 - (-4.45* 27) =130.15 kPa. Positive values of σ t indicate aninternal “pushing” pressure.

relevant plots and table for examination and easyinterpretation of results. Proposed future work on themodel is to simulate situation with varying soil
properties with depth and multiple soil layers.

REFERENCES[1] Leca, E, New, B, “Settlements induced bytunneling in soft ground”, Tunnelling andUnderground Space Technology 22, 2007, pp.
119–149[2] Sloan, SW, Assadi, A, “Undrained stability of aplane strain heading”, Canadian Geotechncial
Journal, Vol 31, 1994, pp. 443-450.
[3] Augarde, CE, Lyamin, AV, Sloan, SW,“Stability of an undrained plane strain heading
revisited”, Computer an Geotechnics, Vol 30,
2003, pp. 419-430.
[4] Grant, RJ, Taylor, RN, “Stability of tunnels inclay with overlying layers of coarse grainedsoil”, International Conference on Geotechical& Geological Engineering, 2000.
[5] Kim, SH, Tonon, F, “Face stability and required
support pressure for TBM driven tunnels with
ideal face membrane-drained case”, Journal oftunneling and underground space technology,
Vol 25, 2010, pp. 526-542.

CONCLUSION
The tunnel heading stability model has beendeveloped to provide designers with a simple but
accurate tool for estimating shield or EPB facepressures within soft clay soils during thepreliminary design and construction stage.
Verification of stability numbers with rigorous upperand lower bound solutions in [3] and [4] confirmsthat the model produces accurate results for thestability problem. A simple design chart wasdeveloped to provide the user with internal pressure
for a larger range of geometric situations and soil
condition than typically available.
The developed FISH programme (Heading.fis)
can be used for site specific parametric or sensitivity
analysis. Heading.fis has nine input parameters.
Once called into FLAC, it automatically generates
grid dimensions, solution commands and outputs

180

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INVESTIGATION OF THE OPTIMAL SUPPORT PATTERNS IN
BRACED EXCAVATION USING GROUND ANCHORS

1

H. M. Shahin1, Teruo Nakai2, Okuda Kazuaki3 and Kato Morihiro4
Department of Civil Engineering, Nagoya Institute of Technology, Japan; 2Geo-Research Institute, Nagoya
Branch, Japan; 3Penta-Ocean Construction Co. Ltd., Miyagi, Japan; 4Central Japan Railway, Gifu, Japan

ABSTRACTIn this research, to establish a rational design and construction process in braced excavation using groundanchors, two-dimensional model tests are carried out varying the length, number and inclination of groundanchors. Numerical simulations with finite element method using FEMtij-2D are also carried out for the same
scale of the model tests. Subloading t ij model is used in the analyses to model the ground material. It has been
revealed that installation a longer anchor at the deeper excavation part is the most effective method in the groundanchors of earth retaining wall. Installation angle of ground anchor has significant effect on the backfill grounddisplacement and deformation of the retaining wall as well. The numerical analyses capture well the results ofthe model tests.
Keywords: Braced excavation, Ground anchor, Finite element analysis, Reinforcing

two-dimensional apparatus. The size of the model
ground is 680mm in width and 450mm in height.
Aluminum rods of 5cm in length, having diametersof 1.6mm and 3.0mm and mixed with the ratio of
3:2 in weight, are used as the model ground (unitweight of the mass is 20.4kN/m3). The retaining wallis 300mm in length, 60mm in width and 0.5mm inthickness, which is a plate of aluminum material (EI= 0.88 N*m2/cm, EA = 4.22 kN/cm ). It is set in the
ground before excavation and is located at 200mm
from the right boundary of the ground. In theexperiment the model ground was excavated with alayer of 15mm in thickness up to a possible depth of
excavation. The anchor plate is 50mm in length,
50mm in width and 5mm in thick, and it is made ofaluminum. In the anchor plate, aluminum rods of
1.6mm diameter are glued at both sides at an intervalof 10mm to maintain a certain friction between the
ground and the anchor plate. Pre-stress is applied at
the head of the anchors. The pre-stress of the anchor
is controlled by a fly nut set up at its head, and theanchor can be set up at any arbitrary inclination(θ) from the horizontal line. The anchor is modeledconnecting the head and the anchor plate by piano
wire (thread) at both sides of the ground. The piano
thread is 0.3mm in diameter having EA =1.41*103kN/cm. Biaxial strain gages attached with athin aluminum board (30 mm in length, 60 mm inwidth, and 0.2 mm in thickness) are connected in the
piano thread to measure tensile force. By taking
photographs with a digital camera and using PIVtechnique the ground movements and consequently
the strain of the ground are measured. The wall
deformation is also measured using digitizer fromthe photographs of the ground. A laser type

INTRODUCTION
It is well known that an open excavation causes
problem to the deformation of surrounding ground.
Retaining wall is commonly used to prevent the
ground deformation during excavation. In addition,
struts are used to make a large underground area inopen excavation. However, sometimes the struts
hinder the construction process as the excavated area
is occupied with the struts. It is possible to excavatelarge section and to increase excavation depth using
ground anchor as reinforcement in a retaining wallwithout strut, which accomplishes smooth handlingof construction works. In present design method ofretaining wall with anchor, earth pressure acting on
the retaining wall and its deformation are evaluatedby empirical procedure imitating the construction
procedure of strut. Since it is expected that theconstruction of anchor type retaining wall will be
increasing day by day, it demands a rational design
procedure. Therefore, purpose of this research is toinvestigate the mechanism of anchor type retaining
wall by model tests and numerical analyses. The
analyses are performed using finite element method
based on an elastoplastic constitutive model named
subloading t ij model [2]. This model can describe
typicalstressdeformationandstrengthcharacteristics of soils such as the influence ofintermediate principal stress, the influence of stress
path dependency of plastic flow and the influence ofdensity and/or confining pressure.
LAYOUT OF MODEL TESTS
Figure 1 shows the schematic diagram of the181GEOMATE-Nagoya, Nov.13-15, 2013displacement transducer is used to measure surface
settlement of the ground.
Table 1 shows the experimental pattern. The
anchors are set up either at 2 stages or 3 stages.
Excavation depth during the installation of the 1ststage anchor is 30mm, the 2nd stage anchor is 90mm
and the 3rd stage anchor is 150mm. The anchor depth
for the 1st stage anchor is 15mm, the 2nd stage anchor
is 75mm and the 3rd stage anchor is 135mm from thesurface of the ground. A plane of active earthpressure is assumed considering the final excavation
depth is 210mm and angle of internal friction is 30o.
The anchor plate is set up outside of the assumed
plane of active earth pressure. Case2-A and Case3-A
are considered as the basic patterns, and experiments
are carried out changing the length of the anchor.
The initial pre-stress of the anchor is calculated fromthe active earth pressure using the prescribedexcavation depth of each anchor as mentioned above.
In this paper, only the results of the 2 stages and 3
stages anchor with the inclination of 30o will beillustrated due to the space limitation.
Excavating
Zone

Aluminum bars

LAYOUT OF NUMERICAL SIMULATIONS
An elastoplastic constitutive model for soils,
called the subloading t ij -model [2], is used in finite
element analyses. This model requires only a few
unified material parameters, but can describe
properly the following typical characteristics ofsoils: (1) influence of intermediate principal stresson the deformation and strength of soil; (2) influenceof stress path on the direction of plastic flow is
considered by splitting the plastic strain increment
into two components; (3) influence of density and/or
confining pressure. Model parameters for thealuminum rod mass are shown in Table 2. The
parameters are fundamentally the same as those of
the Cam clay model except for the parameter a,which is responsible for the influence of density andconfining pressure. Where, λ and κ are the slope ofloading and unloading curve of e-lnp graphs at theloosest state. N is the void ratio at mean principal
stresses (p) 98kPa in the above mentioned loading
curve and ν e is the Poisson’s ratio. The parameter β
controls the shape of yield surface. These parameters
can easily be obtained from traditional laboratory
tests. The parameters can be determined throughconventional triaxial tests and consolidation test.
Figure 2 shows the results of biaxial tests for themass of aluminum rods used in the model tests. The
figure shows the positive and negative dilatancy ofaluminum rod mass; and it is clear that the strengthand deformation behavior are very similar to thoseof dense sand.

(Upper Side)

Pianowire

AnchorBlock

Reflect Plate of supersonic wave
Supersonic D.T
Slide Shaft for Laser D.T

AnchorHead

Laser D.T

Straingages

Rod ofMicrometer

Aluminum
board
1

θ

Load
cell

2
3

AnchorBlock
Aluminumbar

Micrometer

4
5

Piano
wire

RetainingWall(300mm)

450mm

200mm
Model Ground(Aluminum bars) Slide Block (13Pieces)
680mm Fixed Block (2Pieces)

6
7
8
9

Table 2 Material parameters for aluminum rods
λ

11
12

N (eNC at p=98kPa& q=0kPa)
RCS=(σ1/σ3)CS(comp.)

13
14
15

Fig.1 Apparatus of the model experiments
Table 1 Pattern of experiments

Case2-B

L 1 =300, L 2 =1252
Case2-C

T 1 =0.31

Case2-DT 2 =0.57

Case3-A

Case3-C

(mm)

Angl
e
θo

L 1 =150, L 2 =125Case2-A

Case3-B

Anchor length L

T 3 =0.84
3

L 1 =150, L 2 =250
L 1 =300, L 2 =250
L 1 =150, L 2 =125,
L 3 =100
L 1 =300, L 2 =125,
L 3 =100
L 1 =150, L 2 =125,
L 3 =300

3.5

Same parameters as
Cam- clay model

0.3

νe

1.80
0.20

β

1.20

a

1300

σa = const

Shape of yield surface (same as original Camclay at β=1)
Influence of density andconfining pressure

observed(σa = 19.6kPa )calculated(σa = 19.6kPa )calculated(σa = 0.2kPa )3.0

εv (%)

Initialtensileforce(N)stress ratio σa/σr

No
.

0.008
0.004

κ

10

2.0

30
1.0
1.0

2.0 3.0 4.0 5.0

6.0 7.0 8.0

9.0

εa (%)

-1.0
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4

Fig. 2 Stress-strain-dilatancy relation for the mass ofaluminum rods
182GEOMATE-Nagoya, Nov.13-15, 2013

Figure 3 shows a mesh used in the finite
element analyses for the simulations of the model
tests. The analyses are carried out using finite
element code FEMtij-2D developed in ourlaboratory. Isoparametric 4-noded elements are used
to represent the soil. The mesh is well refined withelements of finer mesh in most regions. The sheet
pile and anchor plates are modelled using elastic
beam elements. The frictional behavior (friction
angle δ=14o) between the sheet pile and the groundis simulated using elastoplastic joint elements [1].
The frictional angle, δ=14o, was obtained from alaboratory model test. The anchor is modelled using
truss element as it can only resist tensile force. The
stiffness of the truss element considered in theanalyses is the same as the stiffness of the piano
wire used in the model tests. In the analyses, theexcavation is simulated removing elements in themesh corresponding to the excavation area of themodel tests. The analyses are carried out under planestrain conditions, since the aluminium rods do not
deform in the out of plane direction. The analyses
are carried out with the same conditions of themodel tests. Both vertical sides of the mesh are freein the vertical direction, and the bottom face is kept
fixed. The initial stresses of the ground are
calculated by applying the body forces due to selfweight (γ=20.4kN/m3), starting from a negligible
confining pressure (p 0 =9.8×10-6kPa) and an initial
void ratio e=0.35. After self-weight consolidation
the void ratio of the ground was 0.28 at the bottom
and 0.30 at the top. The pre-stress is applied at thehead of each anchor the same as the model tests.

anchor block (beam element). Two tests are
conducted varying the depth of the anchor from thesurface of the ground (D), D = 15 and 30cm. In the
figure the marks represent experimental results andthe lines show computed results. It is seen in the test
results that pullout force of anchor block increases
with the increasing vertical displacement andreaches an ultimate value following a reduction tosome extent. The ultimate pullout load capacity ofthe deeper anchor block is larger than that of theshallower one. Although the numerical analysis
shows the tendency of a flatter initial slope, it canmostly evaluate the ultimate pullout capacity andvariation of the capacities with the soil depths thesame way as the model tests. Therefore, themodeling of the anchor block in the numericalanalysis can be considered as an appropriate one.

10

Pullout Force (N)8D=30cm (Observed)
D=30cm (Computed)
D=15cm (Observed)
D=15cm (Computed)

DT

Anchor
block

6
4
2
0
0

0.5
1
1.5
Displacement (cm)2

Fig.4 Tensile strength of anchor block
RESULTS AND DISCUSSIONS
Figure 5 shows the observed (Fig.5 (a)) andcomputed (Fig.5 (b)) wall displacements for Case2B and Case2-C where anchors are set at two stages
in the ground. Figure 6 represents surface settlement
profiles for the same set of tests. The legend
represents excavation depth (d). The arrows in the
figures indicate the position of the upper and lower
anchors. It is revealed that for the two-stage anchors
it restricts the wall displacement and surface
settlement till the excavation depth of 150mm
irrespective of the anchor length. When excavation
depth exceeds 150mm a large wall displacement isobserved near 150mm depth of the wall, and thesurface subsidence increases significantly as well.
For the excavation depth of 180mm, the influence ofanchor length is seen remarkably. In Case2-C (onlythe lower anchor length is longer) the wall
displacement is smaller than that of Case2-B (onlythe upper anchor length is longer). It (Case2-C) also
restricts the surface subsidence both in magnitude
and in area, i.e. subsidence occur in narrower area.
Therefore, if the lower anchor is longer, it is possible
to make deeper excavation. The results of theFig.3 Mesh for Finite Element Analyses
Pullout Capacity of Anchor Block
The tensile strength of anchor block has been
investigated by a pullout test. Figure 4 shows theobserved and computed results of the tests. The
analyses are performed applying upward verticaldisplacement at the top most nodal point of the183

GEOMATE-Nagoya, Nov.13-15, 2013

100

100

150

150

200

200

250

250

300
0

(a) Observed

Computed
Case2-B

Observed
Case2-B

1020
Displacement (mm)

300
0
30

Computed
Case2-C

d=120mmd=210mm

300
200
100
Distance from Retaining Wall (mm)15

Observed
Case2-C30
1020
Displacement (mm)

150

(

150

300
0

Computed
Case2-B

1020
Displacement (mm)

250
300
0
30

240

15

200

200

210

(a) Observed

Lower Anchor

Displacement (mm)

)

100

180

Excavation Depth (mm)pDepth (mm)50

Lower Anchor

Case2-A
Case2-B
Case2-C
Case2-D

5

Upper Anchor

100

250

10

0
150

0
Upper Anchor

50

0
2
4
6
8
10
12
14
0
0
2
4
6
8
10
12
14
0

(b) Computed
Fig.6 Surface settlement profiles in Case2-B, C

Lower Anchor(a) Observed
0

100

200

300

Displacement (mm)Depth (mm)

50

100

300
200
100
Distance from Retaining Wall (mm)Upper Anchor

Lower Anchor

200

Observed
Case2-Cd : 掘削深度 0

Upper Anchor

50

300

Settlement (mm)d=90mmd=195mmObserved
Case2-B

0
2
4
6
8
10
12
14
0
0
2
4
6
8
10
12
14
0

Settlement (mm)0d=60mmd=180mm

d : 掘削深度

d=120mmd=210mm

Settlement(mm)d=30mmd=150mmd=90mmd=195mm

d=60mmd=180mm

d=30mmd=150mm

Settlement(mm)numerical analyses show the same tendency of themodel tests not only in shape but also in quantity forboth wall displacement and surface settlement
profiles.
Figure 7 represents the maximum horizontal
displacement of the wall for the excavation depth of
150mm and deeper where the wall displacement
remarkably occurs. The figure shows the comparisonof the results among Case2-A, Case2-B, Case2-C
and Case2-D. As mentioned above, Case2-C (onlythe length of the lower anchor is longer) restricts thewall displacement almost the same extent as Case2D where the lengths of both upper and lower anchors
are longer. That is, the longer lower anchor produces
supporting effect efficiently. On the other hand, only
the longer upper anchor, Case2-B, produces almost
the same effect as Case2-A where the lengths ofboth upper and lower anchors are shorter. In both
Case2-A and Case2-B, displacement increases
significantly when excavation depth crosses 180mm
and the ground collapses at shallower excavation
depth compare to other two cases. The numericalsimulation slightly over-predicts the wall
displacement of Case2-A at excavation depth of
180mm as some elements in the ground undergo into
failure state. Until the collapses of the ground theanalyses show good agreement with the model tests.

Computed
Case2-C

Case2-A
Case2-B
Case2-C
Case2-D

10

5
Computed30
1020
Displacement (mm)(b) Computed

0
150

180
210
Excavation Depth (mm)240(b) Computed
Fig.7 Wall horizontal displacement for excavation
depth deeper than 150mm

Fig.5 Horizontal displacement of wall in Case2-B, C
184

GEOMATE-Nagoya, Nov.13-15, 2013

matrix) that is usually used in finite element method
to relate displacements and strains. It is seen that inCase2-A, for the shorter anchor shear band develops
outside the lump of the ground having the anchor
block inside the lump. In the case of longer upperand lower anchors (Case2-D), the anchor blocks arelocated far outside the slip surface which restricts
the development of shear strain significantly. Case2C, where only the lower anchor is longer, shows
almost the same distribution of shear strain as that ofCase2-D. This is because, as the lower anchor is
located outside the slip surface and produces
sufficiently high pullout resistance it increases
tensile force and hence a notable supporting effectcan be speculated. On the other, though the upper
anchor block of Case2-B is located outside the slip
surface, there is not much difference of the
distributions of shear strain between Case2-A andCase2-B. Therefore, it can be said that a longer
anchor at the lower excavation part restricts thedisplacement of retaining wall and can be treated as
an effective supporting method. The shear strain of
the numerical analyses shows good agreement withthe results of the model tests.

2.5

Tension (N)2
1.5

Case2-A (upper)
Case2-A (lower)
Case2-B (upper)
Case2-B (lower)
Case2-C (upper)
Case2-C (lower)
Case2-D (upper)
Case2-D (lower)

Observed

1
T2=0.57N
T1=0.31N

0.5

0

30

60 90 120 150 180 21
Excavation Depth (mm)(a) Observed
2.5

Tension (N)2
1.5

Case2-A (upper)
Case2-A (lower)
Case2-B (upper)
Case2-B (lower)
Case2-C (upper)
Case2-C (lower)
Case2-D (upper)
Case2-D (lower)

Computed

1
T2=0.57N
T1=0.31N

0.5

0

30

60 90 120 150 180 21
Excavation Depth (mm)Case2-A

d=195mm

Case2-B

d=195mm

Case2-C

d=210mm

Case2-D

d=210mm(b) Computed
Fig.8 Variation of tensile force of anchor
Figure 8 shows the observed and computed
variations of tensile force at both upper and lower
anchors for Case2-A to D. It is seen that for all cases,
the change of tensile force at the upper anchor is lesssignificant compare to the lower anchor. In contrast,
the tensile force at the lower anchor increases withthe advance of excavation, especially, when the
excavation depth is deeper than 150mm which is
associated with a significant wall deformation andsurface settlement of the backfill ground. In the thecase of longer lower anchor (Case2-C, D), themaximum tensile force is almost 1.5times the
maximum tensile force of the lower anchor of
Case2-A. The numerical analyses perfectly capture
the observed tensile force of both upper and lower
anchors.
Figure 9 illustrates distribution of shear strainof the model tests and numerical simulations. The
distributions of shear strain of the model tests are
obtained using Particle Image Velocimetry (PIV)
technique. In this paper, two images are divided intoa finite area; the average movement rate of the massof aluminum rods of each area is extracted as nodal
displacements. The strain for one grid is calculated
from these displacements by using the shapefunctions and the B matrix (strain- displacement(a) Observed

Case2-A

d=195mm

Case2-B

d=195mm

Case2-C

d=210mm

Case2-D

d=210mm(b) Computed
Fig.9 Distribution of shear strain: Case2-A to D
Figure 10 represents observed and computed
surface settlement profiles of the backfill ground forCase3-A and Case3-C. The lengths of anchors inboth cases are the same except a longer anchor is
setup at the deeper excavation part in Case3-C. It isseen that when the excavation depth crosses 180mm

185GEOMATE-Nagoya, Nov.13-15, 2013a larger settlement with wider area occurs in Case3A where all the anchors are shorter in length thesame way as the two stages anchor as describe
before. In Case3-C where the 3rd stage (lower)
anchor is longer, excavation up to the depth of
210mm is possible without a significant subsidenceof the backfill ground. Figure 11 illustrates
distribution of shear strain of the model tests and thecorresponding numerical analyses for Case3-A andCase3-C. Case3-A shows the results of the
excavation depth of 210mm as the further
excavation was not possible due to the collapse of
the ground. As described above the longer anchor ofthe deeper excavation depth grasp much pullout
resistance compare to the anchors at the shallower
excavation depth, it restricts the movement of theretaining wall and hence deeper excavation ispossible. The numerical analyses can clearly express
the difference of the surface settlement profiles andthe distribution of shear strain with the variation of
the anchor lengths the same way as the model tests.
d=30mmd=150mm

d=60mmd=180mmd=90mmd=210mmsetup outside the assumed slip surface developed
during excavation. Especially, longer anchor in thelower part of the excavation produces a significant
supporting effect resisting wall displacement andsurface settlement of the backfill ground. As the wall
deformation and surface settlement of the backfill
ground increase with the advance of excavation it isimportant to install an anchor with a sufficient
length in deeper excavation depth. In contrast, there
are not much differences in supporting effectbetween a shorter and a longer anchor in shallower
excavation depth. It is also revealed that the numberof anchors, inclination of anchors and their interval
play an important role in safe and stable braced
excavation. Therefore, it is important to find out an
optimum supporting pattern in anchor type braced
excavation for rational design in the case economical
point of view. It can also be concluded that thecomputed results in which typical stress-strain
behavior of soils is appropriately taken into accountagree well with the experimental results qualitatively
and quantitatively.

d=120mmd=240mm

Settlement (mm)

00
22
2
44
4
66
6
88
8
Case3-A
10 Case3-A
10
12 2D-Computed
12
2D-Observed
14
14
300
200
100
0
300
200
100
0
00
0
22
22
44
4
6
6
8
8
Case3-C
10 Case3-C
10
12 2D-Computed
12
2D-Observed
14
14
300
200
100
0
300
200
100
0
Distance from Retaining Wall (mm)Distance from Retaining Wall (mm)Settlement (mm)0d : 掘削深度

Fig.10 Surface settlement profiles: Case3-A, C

Observed

Computed

Case3-A d=210mm

Observed

Computed

Case3-C d=240mm

Fig.11 Distribution of shear strain: Case3-A,C
CONCLUSION
In this research, two-dimensional model tests
and the corresponding numerical analyses arecarryout out on anchor type braced excavation. It isrevealed that supporting effect of anchor in braced
excavation can be achieved if the anchor block is

186

REFERENCES[1] Nakai, T, “Finite element computations for
active and passive earth pressure problems ofretaining wall”. Soils and Foundations, 25(3),1985, pp. 98-112.
[2] Naka T. and Hinokio T., “A simple elastoplastic
model for normally and over consolidated soils
with unified material parameters”, Soils andFoundations, Vol. 44, No.2, 2004, pp. 53-70.
[3] Nakai, T., Shahin, H. M., Iwata, N., Ninomi M.
and Takei, H., “Influence of deflection process
and mode of wall and existing building load on
retaining wall”, 13th Asian Reg. Conf. on Soil
Mech. and Geotechnical Engineering, Kolkata,
India, December, 2007, pp. 481-484.
[4] Iwata, N., Shahin, H.M., Zhang, F., Nakai, T,
Niinomi, M. and Geraldni, Y.D.S., “Excavation
with stepped-twin retaining wall: model tests
and numerical simulations”, Proc. of the 6th Int.
Sym. on Geotechnical Aspects of UndergroundConstruction in Soft Ground, Shanghai, China,
April, 2008, pp.655-661.
[5] Shahin, H.M., Nakai, T., Kikumoto, M. andUetani, Y, “Influence of existing foundations on
retaining wall in braced excavation”, 14th AsianReg. Conf. on Soil Mech. and GeotechnicalEngineering, Hong Kong, May, 2011, pp. 267.
[6] Shahin, H.M., Nakai, T., Kikumoto, M., Sakai,R., Yoshida, Y., Saito, I., Nagao, N. and Toda,
K., “Investigation of a reliable reinforcing
method for embankment ground”, 1stInternational Conference on Geotechnique,
Construction Materials and Environment, Mie,
Japan, November, 2011, pp. 71-76.

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SHEAR MODULUS REDUCTION CURVES OF GUAYURIBA SANDSBY CYCLIC TRIAXIAL AND BENDER ELEMENT TESTS
J.F. Gaitán-Serrano1, M.P. Ortiz-Pulido1 and J.F. Camacho-Tauta1
Faculty of Engineering, Nueva Granada Military University, Colombia

1

ABSTRACT
A laboratory experimental programme based on cyclic triaxial and bender element tests was performed on
three particle sizes of sands from Guayuriba River (Colombia). The material from the Guayuriba River consists
mostly of quartzite of the group Quetame (Paleozoic shale formation). Tests performed under different
confinements (50, 100, 200 and 400kPa) allow obtaining a general view of the cyclic behavior of this material.
The influence of the grain size on the shear modulus reduction curve was identified. There were good continuity
between the bender element and the cyclic triaxial results. Moreover, it was verified the applicability of a unified
model to predict the shear modulus reduction curves for this sand for normalized shear modulus greater than 0.4.
For the material tested, this model could be used to obtain a reasonable approximation of the shear modulus
reduction curve. Two parameters are required: the initial shear modulus, for example by bender element testing,and the shear strain for a normalized shear modulus equal to 0.7, which is easily recognizable by a cyclic triaxial
test without internal instrumentation. These tests are less expensive than the resonant-column method and otherspecialized techniques.
Keywords: Bender Element Test, Cyclic Triaxial Test, Shear Modulus, Soil Stiffness

INTRODUCTION

THEORETICAL BACKGROUND

Around the world, many authors haveinvestigated the dynamic behavior of granular soils
by laboratory testing. Kokusho [1], Santos andGomes Correia [2], Zhou y Chen [3], Jafarzadeh andSadeghi [4] are examples of that kind ofinvestigations. In Colombia, there are some works
with local materials, providing advances in thissubject, for example Yamin et al [5], Garcia [6],Chaves [7], Rivas [8], who have made similar
investigations about the behavior towards thephenomenon of liquefaction of sands of Tumaco(Chocó, Colombia) or the dynamic behavior inschists of Sabaneta (Antioquia, Colombia).
The shear modulus is one of the parameters
required to estimate the dynamic response of soil
layers. For example, the shear modulus is used in theassessment of seismic behavior of a sand deposit, toassess the risk from cases like the one in the middleof Atrato River (Colombia), where it presented theliquefaction of a dam formed by sandy material
product of an earthquake presented on 17 and 18
October 1992 [9].
This paper aims to study the shear modulus in
fluvial sands of the Guayuriba River (Colombia), by
obtaining the shear modulus reduction curves. These
curves were obtained by cyclic triaxial and benderelement tests with different confining pressures. The
results were analyzed, and a unified shear modulus
reduction curve based on the model of Santos andGomes Correia [2] has been obtained.

In this section, the most relevant concepts related
to the subject of this research are presented, startingby the definition of the initial shear modulus and the
reduction of the modulus along different strain levels.
Special attention is devoted to the unified model
used in this work.
Initial Shear Modulus
The initial shear modulus (G 0 ), is the parameterthat defines the stiffness of a soil subjected to cyclic
stresses in the very small range of deformations. G 0
has been studied by different authors like Kokusho[1], Ishihara [10], Santos and Gomes Correia [2] andRichart et al. [11]. These researchers have found thata number of factors influence G 0 in sandy soils. The
most important factors are the effective confiningpressure (σ’ 0 ) and the void ratio (e), as shown in Eq.
(1).
𝐆𝐆𝟎𝟎 = 𝐀𝐀 �

(𝐁𝐁−𝐞𝐞)𝟐𝟐(𝟏𝟏+𝐞𝐞)� (𝛔𝛔′𝟎𝟎 )𝐧𝐧(1)

Where A, B and n are experimental constants
that depend of the material. A compilation ofdifferent materials presented by some authors, showsthat the most common values of B and n are 2.17
and 0.5, respectively. A fluctuates between 7000 and
14100 for G 0 and σ′0 expressed in kPa [12].
187GEOMATE-Nagoya, Nov.13-15, 2013

Modulus Reduction Curves

Unified Shear Modulus Reduction Curve

The modulus reduction curve is a representationof the secant shear modulus divided by the initialshear modulus (i.e. the shear modulus at very small
strain) as a function of the strain level [12]. The
normalized curve is an advantageous representation
because it can be simply multiplied by anappropriate experimentally determined G 0 to obtainthe shear modulus for any strain level. This curve
synthesizes the nonlinear behavior of soils. Figure 1
shows the modulus reduction curve along the shear
strain [13].
The modulus reduction curve is not unique. In
the case of sands, its shape and location depend
mostly of the confining pressure, number of cycles
and drainage conditions [1, 14].

A first proposal of a unified model was presented
by Ishibashi and Zhang [17]. Based in manycollected data, they proposed a set of formulas forall soil types, taking into account the effect ofplasticity and confinement.
Santos and Gomes Correia [2] proposed a unified
model by the normalization of the strain axis of themodulus reduction curve. The normalized shear
strain (γ*) is computed by:

Fig. 1γ

γ* = r(2)

Fig. 2

Unifiedmodulus
reduction
curvescomputed using data from Vucetic andDobry [18] and Darendeli [19].

γtExperimental data from Vucetic and Dobry [18]and Darendeli [19] was normalized using Eq. (2) andthe results are presented in Fig. 2, showing that themodel works for different soil plasticity andeffective confining pressures.

Modulus reduction curve and zones ofcyclic shear strain. Adapted from [13].

Elastic And Volumetric Threshold Shear Strains

Based on a series of tests [2], it wasdemonstrated that data matches in a narrow zone
delimited by the curves given by Eq. (3) and Eq. (4).

The shear strain level can be classified in verysmall strains, small strains and medium to large
strains [10]. The limit between very small and small
strains was defined arbitrarily as the shear strain
corresponding to G/G 0 ≈0.99 [13]. This strain
receives the name of linear elastic cyclic thresholdstrain (γ t e). The limit between small and medium
strains is defined as the shear strain above which themicrostructure is irreversibly altered by cyclic
shearing [13]. This limit is known as the volumetricthreshold shear strain (γ t v) because from this value
appear irreversible changes in the volume of thesample. Kokusho [15] concludes that γ t v is the shear
strain for which G/G 0 is between 0.6 and 0.85.
Ishihara [10] proposes a mean value of G/G 0 =0.7.
Given the difficult to measure γ t v in practice, Santos[16] proposed to use the reference threshold strain(γ t r), defined as the shear strain causing G/G 0 =0.7.
Relative locations of γ t e and γ t v are shown in Fig. 1.

G

G

G0

G

G0

=

=1

G0

γ∗

1−tanh�0.48 ln�1.9��
G

G0

2

=1

γ∗ −0.1for γ∗ ≤ 10−2∗for γ > 10=

1−tanh�0.46 ln� 3.4 ��
2=

𝟏𝟏+(𝟎𝟎.𝟑𝟑𝟑𝟑𝟑𝟑𝛄𝛄∗ )

(3)

−2

for γ∗ ≤ 10−1

(4)for γ∗ > 10−1

Moreover, experimental data for plastic and nonplastic soils fit with good agreement with Eq. (5)
[20].
𝐆𝐆

𝐆𝐆𝟎𝟎

188

𝟏𝟏

(5)

GEOMATE-Nagoya, Nov.13-15, 2013

MATERIALS, EQUIPMENT AND TESTINGMETHODS
Materials

DigitalOscilloscope

Soil specimen
BE Transmitter
Base CapThe material from the Guayuriba River consists
mostly of quartzite of the group Quetame [21].
Three particle sizes of the same sand were used in
the experiments, in order to analyze the influence ofgrain size on the results. The physicalcharacterization included the determination of
specific gravity of soil solids, particle-size analysis,
maximum index density and minimum index density
according to the ASTM standards [22]. Results ofthese laboratory tests are presented in Table I.
The cylindrical specimens (14 cm in height and 7
cm in diameter) were prepared by the dry pluviation
method. Size and proportions of the specimens are inagreement with suggestions of previously-reported
works [23-25].

Fig. 42

3

Minimum diameter [mm]

0.18

0.43

0.85

Maximum diameter [mm]

0.43

0.85

2.00

Uniformity coefficient [.]

1.58

1.42

1.39

Curvature coefficient [.]

0.93

0.94

1.00

Specific gravity of solids [.]Void ratio [.]Dry unit weight [kN/m3]

2.68 2.65 2.68
0.81 0.91 0.99
14.8 14.1 13.5

Function
Generator

Schematic of the BE system [27].

Each soil specimen was installed in the cyclic
triaxial cell, saturated, and then consolidated under aconfining pressure of 50, 100, 200 or 400 kPa.
Bender element tests (BE)BE tests were conducted by the following
methodology:- The function generator produces a linear sine
sweep signal with frequency band between 1–20
kHz with duration of 40 ms and amplitude of 20
Vpp. This signal is sent to the BE transmitter.
- The digital oscilloscope acquires both input andoutput signals. The Fast Fourier Transform(FFT) computed in real time by the oscilloscope
allows to identify the specific frequency in which
the response of the BE receiver is higher.
- The function generator is turned to single-sine
pulse mode with the frequency previously
determined. The period of the signal is selected
in order to allow enough time for the attenuationof the BE response before the next pulse. The
output signals of a number of pulses are stacked
in order to cancel out random noise, obtaining aclean response from the BE receiver.
- The arrival time is identified by the first
inversion method [28]. The travel time (tt) is thedifference between the arrival time and the timeat the start of the sine pulse.
- The travel distance (L TT ) is the height of thespecimen minus the length of each BE. The
initial shear modulus (G 0 ) is computed by Eq.
(6), where ρ is the mass density.

Material
1

Current
AmplifierTesting Methods

Table I Physical properties of the materials
Property

Conditioner/
Amplifier

Triaxial Cell
Top Cap
BE Receiver

Equipment
The dynamic test program was performed in acyclic triaxial apparatus (Dynatriax, WF-Controls)with automatic control of cell and back pressure,equipped with submersible load cell and external
displacement, volumetric change and pore pressure
sensors, data acquisition unit and driver softwarewith autonomous control of the tests stages.
The triaxial cell was equipped with a set of BE
manufactured by the University of Western
Australia [26]. The transmitter and receiver are
located at the base cap and top cap of the triaxial
device, respectively. The input signal is generated bya function generator (RIGOL, DG1022). A current
amplifier stabilizes the signal and send it to the BE
transmitter. The output signal of the BE receiver isamplified and both input and output signals arecollected by a digital oscilloscope (Tektronics,
3S2012B). The BE system was calibrated usingaluminum rods [27]. A schematic description of the
BE system is presented in in Fig. 4.

L

G0 =ρ � TT�
tt

𝟐𝟐

(6)

Figure 5 shows a typical screen of theoscilloscope in the BE test. Channel 1 exhibits the
single-sine pulse use to excite the BE transmitter andChannel 2 shows the output signal acquired by the
BE receiver. Vertical cursors indicate the initial andarrival times used to compute the travel time.
According to different studies [12, 25, 29, 30],
the shear strain level associated to the BE shear
modulus is assumed to be 5x10-6.
189

GEOMATE-Nagoya, Nov.13-15, 2013

RESULTS AND DISCUSSION
Figure 7 shows the curves obtained for the threesands and the different effective confining pressures.
The results obtained by bender element and cyclic
triaxial tests show the influence of the particle size
and the confining pressure on the shear modulus
reduction curves. The gap between BE and CTX
tests is remarkable, not only regarding to the shear
strain level, but also concerning the magnitude of theshear modulus. The use of internal instrumentationon the CTX test could reduce this difference.

Fig. 5

Typical BE test showing input and output
waveforms.

Cyclic triaxial tests (CTX)
After the bender element tests, cyclic triaxial
tests were carried out according to the Method B(strain controlled) of ASTM D 3999 standard [31],with nine cyclic shear stages, each one with 40
sinusoidal cycles at frequency of 0.5 Hz. The strains
were selected in a range of 0.028 mm (γ≈1.33x10-4)
to 1.4 mm (γ≈6.67x10-3). The shear stress and shear
strain are computed by Eq. (7) and Eq. (8),respectively.
τ=

γ=

𝒒𝒒
𝟐𝟐

a)

(7)
𝜺𝜺

𝟏𝟏+𝝂𝝂

(8)

Where q is the deviator stress, ε is the axial strainand ν is the Poisson’s ratio, assumed to be 0.5 forsaturated sands. Fig. 6 shows an example of thehysteresis loop obtained by the cyclic triaxial test,
where the shear modulus is obtained as the slope ofthe line connecting the two extreme points of the
loop.

b)

c)
Fig. 6

Hysteresis loop of the cyclic triaxial test.
Material 3, σ’ 0 =100 kPa.

Fig. 7

190

Experimental modulus reduction curves: a)Material 1; b) Material 2; c) Material 3.

GEOMATE-Nagoya, Nov.13-15, 2013

could be due that at this strain level, and for theseloose specimens, the soil starts to exhibit cyclicliquefaction.
Results presented here suggest that a practical
approximation of a shear modulus reduction curve
could be obtained by a combination of BE tests andCTX tests.

Shear moduli were normalized by theirrespective maximum shear modulus. These results
are presented in Fig. 8. After a careful analysis of
the figure, it is possible to observe that in general,the higher the confinement, the larger thenormalized modulus for a given shear strain. Thisobservation is in agreement with previous reported
works [1]. However, the dispersion of result does
not allow proposing a clear trend on this issue.
The reference shear strain (γ t r) was estimated byinterpolation of the data and the normalized shear
strain (γ*) was computed by Eq. (2). These doublenormalized curves are presented in Fig. 9, as well as
the limits expressed by Eq. (3) and Eq. (4).
The influence of the assumed shear strain level in
BE tests in results presented in Fig. 8 is insignificant
because the normalized shear strain is computed
using only CTX results and the magnitude of theshear modulus obtained by BE tests.

CONCLUSION
The procedures for the cyclic triaxial and thebender element tests were adequately implemented.
Results on Guayuriba sands were suitable whencompared with the literature and the models
proposed by other authors.
The model presented by Santos and Gomes
Correia, is applicable to the Guayuriba sands. Thismodel has the advantage that only needs the
maximum shear modulus and the shear strain
corresponding to a modulus equal to 70% of the
maximumshear
modulus.
This
simpleapproximation could be useful to obtain initial
estimates of the soil behavior or to check values
obtained by more advanced tests.
ACKNOWLEDGEMENTS
This paper is a result of the Research ProjectING-1187 funded by the Nueva Granada Military
University. Authors acknowledge the financial
support of the Nueva Granada Military University.
REFERENCES

Fig. 8

Shear modulus reduction curves

Fig. 9Unified model for materials tested andcomparison with limits proposed by Santos
and Gomes Correia [2].

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properties for wide strain range”, Soils andFoundations, Vol. 20, no. 2, June, 1980, pp. 4560.
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[3] Zhou Y-G and Chen Y-M, “Influence of seismic
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[4] Jafarzadeh F and Sadeghi H, “Experimental
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[5] Yamin L, Caicedo B and Solano E, “Evaluationof the dynamic response of volcanic deposits
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[8] Rivas D, “Influence of microstructure on the
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dynamic testing methods”, PhD Thesis, Instituto
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[16] Santos JA, “Soil characterization by dynamic
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horizontal loading” (in Portuguese), PhD Thesis,
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[17] Ishibashi I and Zhang X, “Unified dynamic
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[19] Darendeli MB, “Development of a new familyof mormalized modulus reduction and material
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Graduate School, The University of Texas,
Austin, 2001.
[20] Gomes Correia A, Barros JMC, Santos JA and
Sussumu N, "An approach to predict shear
modulus of soils in the range of 10-6 to 10-2
strain levels", in Proc. Proceedings of the FourthInternational Conference on Recent Advancesin Geotechnical Earthquake Engineering andSoil Dynamics, 2001, pp. paper no. 1.22.
[21] Amorocho R, Bayona G and Reyes-Harker A,“Controls on the composition of fluvial sands inthe proximal region of tropical foreland basin(Colombia) (in Spanish)”, Revista Geología
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Standards. West Conshohocken, 2002.
[23] Arroyo M, “Pulse tests in soils samples”, PhD
Thesis, Faculty of Engineering, University ofBristol, Bristol, 2001.
[24] Rio J, Greening P and Medina L, "Influence ofsample geometry on shear wave propagation
using bender elements", in Proc. Deformation
Characteristics of Geomaterials, 2003, pp. 963967.
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using bender elements”, PhD Thesis, University
College London, University of London, London,
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[26] Ismail M, Sharma SS and Fahey M, “A smalltrue triaxial apparatus with wave velocity
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OJ, “A Procedure to Calibrate and Perform
Bender Element Test”, Revista Dyna, Vol. 79,
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[28] Viggiani G and Atkinson JH, “Interpretation of
bender element tests”, Géotechnique, Vol. 45,
no. 1, 1995, pp. 149-154.
[29] Pennington DS, “The anisotropic small strain
stiffness of Cambridge Gault clay”, PhD thesis,
Department of Civil Engineering, University ofBristol, 1999.
[30] Leong EC, Yeo SH and Rahardjo H,“Measuring shear wave velocity using benderelements”, Geotechnical Testing Journal,
ASTM, Vol. 28, no. 5, 2005, pp. 488-498.
[31] ASTM International, "Standard Test Methods
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192

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

WATER DIVERSION AND DRAINAGE IN SHALLOW LAND WASTEREPOSITORY CONSTRUCTED USING CAPILLARY BARRIER OF
SOIL

1Toshihiro Morii1, Kaoru Kobayashi2, Kazunobu Matsumoto2 and Satoru Nakafusa3
Faculty of Agriculture, Niigata University, Japan; 2 Tobishima Corporation, Japan; 3 Japan Atomic Power
Company, Japan

ABSTRACT
Capillary barrier (CB) is tilting soil layer system which is composed of sand layer underlain by gravel layer,
and can well divert water infiltrating from a soil surface. A shallow land waste repository, in which upper CB
and bottom CB were placed to divert infiltration due to rainfall and to drain water percolating through theprotected waste material respectively, was proposed to isolate a hazardous waste material or a very low level
radioactive waste. In this study a test shallow land waste repository was constructed to investigate the CB’s
performance in the field. Firstly a diversion length of the CB was determined based on the laboratory soil box
test to determine the structural dimensions of the shallow land. Then soil moisture contents were measured in thetest shallow land. They showed an excellent and stable water diversion of the CB in the field.
Keywords: Capillary Barrier of Soil, Shallow Land Waste Repository, Diversion Length, Test Construction

interface [7]. Although Ross [6] discussed that thediversion length might be theoretically as much as
50 m in a dryer climate with an order of magnitudeless infiltration, only 1 to 2 meters of the diversion
length has been observed and published [6].
In this paper, a shallow land waste repository
shown in Fig. 2, in which a top CB and a bottom CB
are placed to reduce infiltration due to rainfall and todrain percolating water through the protected wastematerial respectively, is proposed to isolate
effectively a hazardous waste material or a very low
level radioactive waste. As the shallow land waste
repository is constructed on ground surface, there
may be no risk that groundwater enters the waste
and diffuses pollutants into a surrounding
environment. It should be also emphasized that the
CB can maintain its function of water diversion for

INTRODUCTION
Capillary barrier (CB) is a tilting soil layer
system which is composed of a finer soil (usuallysand) layer underlain by a coarser soil (usually
gravel) layer. Water which infiltrates into the soil issuspended just above an interface between the soil
layers and diverted downward along the interface,with the result that a vertical movement of water into
deeper soil layers below the interface stops withinsome length along the interface. Because of thisexcellent diversion of infiltration water, the CB has
been employed in a top cover of waste landfills andmining wastes to reduce water infiltration into theprotected waste materials [1], [2]. The CB has also
been proposed to be used as a soil cover for slope
stabilization purpose against rainfall-induced slope
failure [3], [4]. Water flow downward along theinterface between finer and coarser soil layers
accumulates gradually its mass of flow due tocontinuous infiltration from the soil surface, and, atsome length along the interface, water percolates into the coarser soil layer [5], [6] as shown
schematically in Fig. 1. A horizontal length or
distance from the beginning of water flow to thispercolation into the coarser soil layer (breakthrough)is called a diversion length of the CB, and is one ofimportant parameters in designing structuralconfiguration of the CB system and selecting asuitable combination of the finer and coarser soils. It
is well known that the diversion length cantheoretically be estimated based on the infiltration
flux, saturated and unsaturated hydraulic propertiesof the finer and coarser soils, and the slope of theContinuing supply of water/ rainfall/ irrigation

Top soilacealong interf
Water flow

Sand
GravelWaste

BreakthroughDiversion length

Fig. 1 Schematic layout of a capillary barrier ofsoil and diversion length.
193

GEOMATE-Nagoya, Nov.13-15, 2013
Concrete flume
to collect surface runoff

Cover plant

Upper CBTop soil (usually fumus rich loam forplant growth and water storage)

Hazardous waste/ very low
level radioactive waste

Lower CB

Drainage conduit
for long-term water
quality control

Compacted or improved ground surface

Fig. 2 Proposal of shallow land waste repository covered with upper CB and placed with bottom CB.
an extremely long duration because it consists ofnatural materials such as sand and gravel. In thefollowing section, the diversion length of the CB
which can be applied to structural design of theshallow land waste repository is determined basedon a laboratory soil box test. Then trial construction
is reported to shoe some feasible proposition for
construction of the shallow land waste repository.
Observations of soil water movement in a test
shallow land waste repository are also discussed toshow an effectiveness of the CB.
ESTIMATION OF DIVERSION LENGTH BY
LABORATORY SOIL BOX TEST
a. Soil box (lower set) and water reservoir (upper
set).

Soil Box Test
In order to observe directly the breakthrough ofwater flowing along the interface, and to determine
the diversion length, a series of laboratory soil box
test was carried out. Figure 3a shows an acrylic soilbox, 300 cm in length, 20 cm in width and 50 cm inheight, built in a steel frame. The soil box wasplaced horizontally, and the gravel was compacted
into the layer of 7.5 cm thickness, then the sand into
20 cm thickness as shown in Fig. 3b. A completelypermeable polypropylene net was placed over thecompacted gravel layer so that the sand particles did
not fall into voids formed in the gravel layer. After agauze sheet was spread over the soil surface toprotect soil erosion due to rainfall droplet, one sideof the soil box was jacked up to obtain the tilting
interface of the CB. The infiltration water was
supplied on the surface of the upper sand layer
through emitting needles (syringe needles), 0.3 mm
in an inner diameter, attached to the base plate of thewater reservoir. To keep the acrylic front panel clean,
the emitting needles were placed so that the rainfall
droplet did not fall along the front panel. Intensity ofrainfall was simulated by adjusting the head of
constant water in the water reservoir. Uniformity of
the rainfall intensity over the soil surface was
examined by measuring the water mass collected

50cm

Gravel layer

Partition walls
3 cm highSand layer
0

0

100
200
300
Horizonntal distance along soil box, cm

b. Partition walls attached to the bottom of thesoil box.

Percent finer by mass, %Fig. 3 Test equipment prepared for the soil box test
to measure diversion length of the CB.

100

50

0
0.01

Sand

Gravel

0.1

1

10

100

Soil particle diameter, mm

Fig. 4 Grain size distribution of sand and gravel
used in the soil box test.
into a glass beaker during 10 minutes.

194GEOMATE-Nagoya, Nov.13-15, 2013

D: drainage and W: wetting.

Drainage from partition wall attachedto the bottom of soil box, cm3/10min

Volumetric moisture
contentθ, cm3/cm3

0.6

SWCC
0.4

Sand (D)Sand (W)

0.2
0.0
1

Gravel (W)10
Negative pressure head h, cm

100

Fig. 5 Soil-water characteristic curves (SWCC) of
sand and gravel measured by laboratory soilcolumn tests.

800
Note that drainage were measured
three times, each during 10 min.

600
400

Breakthrough at about 170cm
200
0
0
100
200
300
Distance along the bottom of soil box, cm

Fig. 6 Typical measurement of water volume
collected along the bottom of the soil box.

Figure 4 shows grain size distribution curves ofsand and gravel used in the soil box test. The sandhas less-5% fine and coarse fractions; the gravel,
commercially available, is siliceous with a mean
particle size of 5 to 6mm. Relationships of negative
pore pressure, h, with volumetric moisture content ofsand and gravel were measured by a laboratory soilcolumn test, and are plotted in Fig. 5. Soil-water
characteristic curves are determined by using van
Genuchten equation [8].

to estimate the diversion length of the CB by several
researchers [5], [7], [9]. Among these, the equation
by Steenhuis et al. [7] is effectively adaptable [6],[10]. In the case where an infiltration rate, q, is muchsmaller than a saturated hydraulic conductivity ofsand (the upper finer soil), K s , the equation of thediversion length, L, is given by

Measurement of Diversion Length

L≤

Totally 12 tests were conducted by combining
two interface angles, 5 and 10 degrees, with three
infiltration rate, 5, 10 and 20 mm/h, in two soilboxes. The sand layer in one of two soil boxes wascompacted into 90 % of a maximum dry density,
1.616 Mg/m3, and 85 % in another soil box. Water
which percolated into the lower gravel layer wascollected along a partition wall 3 cm high attachedtransversely every 10 cm intervals onto the bottom
plate of the soil box as shown in Fig. 3b, and led to acollecting beaker through a silicon tube connected to
the lowest position of the side wall of the soil box asshown in Fig. 3a. The diversion length was
determined by observing and measuring a volume ofwater collected into the collecting beaker along thebottom of the soil box. Figure 6 shows a typicalmeasurement of the water volume collected along
the distance of the bottom of the soil box in the caseof 90 % compaction of the sand layer, 10 degrees inslope and 10 mm/h of infiltration rate (rainfall
intensity). As a mean total amount of the water
volume, 1077.4 cm3/10 min., is converted into 10.8mm/h of the infiltration rate, it is found that a massbalance between infiltration and drainage of water is
kept. In this case, the diversion length of 170 cm
was determined from Fig. 6.

in which φ is a slope angle of interface, h a and h w
are an air entry value of sand and a water entry valueof gravel, respectively. α is an exponential constantdescribing the relationship between h andunsaturated hydraulic conductivity, K, of sand nearsaturation:

[

]

Ks
tan φ α -1 + (ha - h w )q

K = Ksh < ha ;K = K s exp[α (h − ha )]h ≥ ha(1)(2)

All the diversion lengths measured in the soil
box test are given in Fig. 7 and compared well withthe estimations calculated by Eqs. (1) and (2). K s of
90 %-compacted sand is 1.31×10-4 m/s, and 85 %compacted sand 1.91×10-4 m/s. The unsaturated
hydraulic properties of the sand, h a , h w and α, aredetermined to be 13 cm, 1 cm and 0.12/cm,
respectively, based on Fig. 5 and Nakafusa, et al.
[11]. Some experiment data published by Walter et
al. [6] and the observed data by Morii et al. [12] arealso plotted in Fig. 7. The measured value of thedata denoted by a small arrow would be larger
because the measurement was restricted to the lengthof the soil box, 300 cm. A fairly good comparison of
the diversion length between the measurements/
observations and the estimations can be found in Fig.
7. It is thought from Fig. 7 that Eqs. (1) and (2)proposed by Steenhuis et al. [7] can be practically

Estimation of Diversion Length
Some theoretical equations have been proposed
195

GEOMATE-Nagoya, Nov.13-15, 2013

6

Diversion length estimated, mTo be larger because measurement was
restricted to horizontal length of the soil box.
5
4
3
2
● Walter, et al. (2000)◎ Morii, et al. (2009)○ Laboratoy soil box test

1
0
0

1

2
3
4
5
Diversion length measured, ma. Gravel layer compacted by the plate-type bucket.

6Fig. 7 Comparison of the diversion length between
measurements and estimations.
employed to estimate the diversion length of the CB.
Based on the results given in Fig. 7, about four
meters of the diversion length can be practically
employed to design the CB in the shallow land waste
repository.

b. Sand layer compacted by the plate-type bucket.

SOIL WATER MOVEMENT IN TESTSHALLOW LAND WASTE REPOSITORY IN
THE FIELD
Construction of Test Shallow Land Waste
Repository
A test shallow land waste repository wasconstructed in order to monitor the soil water
movement in the field and to examine an excellent
water diversion by the CB. The upper CB was notincluded because it was planned only to observe thediversion of infiltration water. The original groundsoil was compacted with the surface inclination of 5
degrees. The gravel was placed over the compacted
ground surface and compacted statically by using theplate-type bucket in 10 cm thickness and in 4 mhorizontal length (Figs. 8a and 8b), then the sandover it in 15 cm thickness. After constructing the CB
layer, sandy soil, polypropylene soil-bags which
simulated containers for waste storage, and sandy
soil were placed and compacted successively higher(Figure 8c). Uniformity in density of the compacted
sand layer is an important property which guarantees
the water diversion in the CB system because thediversion length directly relates to the saturated
hydraulic conductivity of sand as shown in Eq. (1).
After constructing the CB layer, 19 cylindrical sandcores, 100 cm3 in volume and 5 cm in height, were
sampled, and the densities of the sand cores were
measured in laboratory. Figure 9a shows a meanvalue and a standard deviation of the dry density, ρ d ,c. Test shallow land waste repository constructed..
Fig. 8. Construction of the test shallow land waste
repository.
of sand cores on a normal distribution curve,
together with the saturated hydraulic conductivity ofsand measured by laboratory permeability test in Fig.
9b. It is found from Fig. 9 that the saturated
hydraulic conductivity corresponding to a maximum
density expected with 95%-confidence is about 65 %lower than that corresponding to a minimum density
along an average line between K s and ρ d in Fig. 9b,
with the result that the diversion length may varies .
Soil Water Movement
The volumetric moisture contents measured in
the test shallow land waste repository from June to
September are given in Fig. 10b together with thestructural section in Fig. 10a. Two plots were196

GEOMATE-Nagoya, Nov.13-15, 2013

hazardous waste material or a very low level
radioactive waste. The laboratory soil box test andthe test shallow land waste repository constructed in
the field reveal that:
1) The diversion length which determines the
structural dimensions of the shallow land waste
repository can be estimated well based on thehydraulic properties of sand and gravel employed in
the CB, the inclination of the CB interface and theinfiltration rate expected in the field. Equations 1
and 2 proposed by Steenhuis et al. [7] isrecommended to estimate the diversion length of theCB.
2) The test shallow land waste repository showed
the excellent and stable diversion of infiltrationwater provided by the CB. A continuing observationof soil water movement may be required to evaluate
the CB performance for a long duration.

a. Normal distribution of dry density
measured in compacted sand layer
Mean:μ=1.48g/cm3

Standard deviation
σ=0.03g/cm3

Satrated hydraulic conductivity
Ks, cm/s

1.2

1.3 1.4 1.5 1.6 1.7
Dry density of sandρd, g/cm3

1.8

10 -3
μ±1.96σ

ACKNOWLEDGEMENTS
10 -4

The present study was supported by the Grant-inAids for Scientific Research (B), No. 22380127, andChallenging Exploratory Research (C), No.
24658201, made by the Ministry of Education,
Science, Sports and Culture of Japan. Messrs. K.
Taguchi and N. Someya, TNS Co., Ltd., Japan, aresincerely grateful for their help in conducting thelaboratory soil box test and in constructing the test
shallow land waste repository. Their efforts done by
Mr. K. Takahashi and Miss Y. Nakano, theundergraduates of Faculty of Agriculture, Niigata
University, to calculate the volumetric moisture
contents in the test shallow land waste repository are
acknowledged.

b. Laboratory pemeability test
10 -5
1.2

1.3 1.4 1.5 1.6 1.7
Dry density of sandρd, g/cm3

1.8

Fig. 9 Frequency distribution of dry density
measured in the compacted sand layer
and the saturated hydraulic conductivity
measured in laboratory.

prepared in the test construction, a CB layer plot anda reference plot without the CB layer both 2 m inwidth (Fig. 8d). The left and right rows in Fig. 10
show the volumetric moisture contents measured in
the CB layer plot and in the reference plot without
the CB layer, respectively. The upper and lower
lines in Fig. 11 show the volumetric moisture
content measured in the sand layer and in the gravel
layer, respectively. Rainfall intensity measured 5minute intervals is given by an inverse bar with theright vertical axis of each figure. Comparing Figs.
11d with 11b and 11c, it is found that the soil water
which infiltrates from the top surface of the test
repository enters into the sand layer but does not into
the gravel layer underling the sand layer. This isexactly due to the excellent water diversion by the
CB.

REFERENCES[1] Stormont, J.C. & Anderson, C.E. 1999.
Capillary barrier effect from underlying coarser
soil layer. Journal of Geotechnical andGeoenvironmental Engineering 125(8): 641-648.
[2] Yanful, E.K., Simms, P.H., Rowe, R.K. &Stratfoed, G. 1999. Monitoring an experimental
soil waste cover near London, Ontario, Canada.
Geotechnical and Geological Engineering 17:
65-84.
[3] Tami, D., Rahardjo, H., Leong, E.C. & Fredlund,
D.G. 2004. A physical model for sloping
capillary barriers. Geotechnical Testing Journal
27(2): 173-183.
[4] Rahardjo, H., Krisdani, H. & Leong, E.C. 2007.
Application of unsaturated soil mechanics in
capillary barrier system. Proceedings of the 3rd
Asian Conference on Unsaturated Soils: 127137.
[5] Ross, B. 1990. The diversion capacity ofcapillary barriers. Water Resources Research26(10): 2625-2629.

CONCLUSIONS
Shallow land waste repository, in which theupper CB and bottom CB are placed to reduce
infiltration due to rainfall and to drain percolatingwater through the protected waste material
respectively, was proposed to isolate effectively a197

GEOMATE-Nagoya, Nov.13-15, 2013

Height above original
ground surface, m2[a]: Loamy soil with surface inclination of 5 degrees[b]: Gravel constituing CB layer, 10cm thickness[c]: Sand constituting CB layer, 15cm thickness[d]: Sandy soil[e]: Sandy soil packed in polypropylene soilbag● : Soil moisture sensor EC-5, in which
a numeral and a numeral in parentheses
represent sensor number embeded in test
plot with CB and without CB, respectively.

Top surface
69(72)[d]1[e]68(71)[e][e]

10(14)

00[a]3(7) [b]67(70)

9(13)

[e]

[c]

2(5)

[d]

8(11)

1(4)

1
2
3
Distance from center line, m

4

No. 11
No. 13
No. 14

0.2

0.4

10

0.3

0.1
0.0
0

30

60
Time, days

90

120

0.4
0.3

(b)
No. 4
No. 5
No. 7

0.2

0.0
0

30

60
Time, days

90

(c)

10

No. 8
No. 9
No. 10

0.1
0.0
0
0.4

10

0.3

120

0

0.2

0

0.1

Rainfall, mm/5min

(a)

0

30

60
Time, days

90

120

Rainfall, mm/5min

0.3

Rainfall, mm/5min
Volumetric moisture content, cm3/cm3

0.4

Rainfall, mm/5min
Volumetric moisture content, cm3/cm3

Volumetric moisture content, cm3/cm3

Volumetric moisture content, cm3/cm3

a. Structural section of the test shallow land waste repository.

0

(d)

10

No. 1
No. 2*
No. 3

0.2* No data because of sensor trouble

0.1
0.0
0

30

60
Time, days

90

120

b. Volumetric moisture content measured in the test shallow land waste repository.
Fig. 10 Soil water movement measure in the test shallow land waste repository.

[6] Walter, M.T., Kim, J.S., Steenhuis, T.S.,
Parlange, J.Y., Heilig, A., Braddock, R.D.,
Selker, J.S. & Boll, J. 2000. Funneled flowmechanisms in a sloping layered soil:
Laboratory investigation. Water Resources
Research 36(4): 841-849.
[7] Steenhuis, T. S., Parlange, J.Y. & Kung, K.J.
1991. Comment on "The Diversion Capacity of
Capillary Barriers" by Benjamin Ross. Water
Resources Research 27(8): 2155-2156.
[8] Stephens, D.B. 1996. Vadose Zone Hydrology.
Florida: CRC Press.
[9] Kung, K.J.S. 1990. Preferential flow in a sandy
vadose soil, 2, Mechanism and implications.
Geoderma 46: 59-71.

[10] Smesrud, J.K. & Selker, J.S. 2001. Effect ofsoil-particle size contrast on capillary barrier
performance. Journal of Geotechnical andGeoenvironmental Engineering 127(10): 885888.
[11] Nakafusa, S., Kobayashi, K., Morii, T. &Takeshita, Y. 2012. Estimation of water
diversion provided by capillary barrier of soils.
Proceedings of the 5th Asia-Pacific Conference
on Unsaturated Soils, 2: 773-777.
[12] Morii, T., Takeshita, Y., Inoue, M. &Matsumoto, S. 2009. Alternative measures forsoil slope stability using capillary barrier of soil.
Proceedings of the 4th Asia-Pacific Conference
on Unsaturated Soils: 319-324.

198

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

REINFORCING EFFECT OF GEOSYNTHETICS
ON BEARING CAPACITY,
Masuda Saki1, H. M. Shahin2, Nakai Teruo3, Morikawa Yukihiro4 and Mio Susumu5
1,2,3
Department of Civil Engineering, Nagoya Institute of Technology, Japan;
3
Geo-Research Institute, Nagoya Branch, Japan;
5
Nikken Wood Systems, Tokyo, Japan

ABSTRACTIn general, geosynthetics are laid under the foundation for increacing bearing capacity. This method isalready established in the construction of foundation. Until now, the authors examined the reinforcement
mechanism changing the length and the laying depth of reinforcement. However, for getting more clear
information about the reinforcement mechanism to establish a rational design method of reinforced-soilground some model tests have been conducted in addition to the previous research. In this research, wehave investigated the reinforcement effect changing the laying depth, length and fixity conditions of thereinforcement conducting two dimensional laboratory tests referring to the past research. In real field as theload on the foundation is not always vertical, here we have also investigated the effect of loading
conditions. The corresponding numerical analyses are also carried out with finite element programs called
FEMtij-2D using elastoplastic subloading tij model. It is found that a significant increase in bearing capacity
can be achieved if the geosynthetics are placed properly with optimum length having the boundary fixedwith the ground.
Keywords: Geosynthetics, reinforcement, foundation, Bearing capacity

INTRODUCTION
In Japan, a huge area of the ground consists ofsoft soils having insufficient bearing capacity at thesurface layer which makes trouble to engineers indesign and construction process. In such cases, it isnecessary to increase the bearing capacity toconstruct superstructures. To increase the bearing
capacity ground improvement and replacement ofgood quality of soils are commonly used. However,these processes are expensive and also time
consuming. Moreover, these processes sometimes
restrict workability of the construction. In urban
housing it is especially unpleasant to use cement inground improvement which increases construction
cost as well. In the case of replacing the existing soft
soils with good quality soils, it needs installation of
temporary structures, such as sheet pile, retaining
wall, struts, etc. which causes difficulties in
employing this process. Therefore, in this research it
is focused on the use of geosynthetics to reinforce
the ground for reducing ground deformation andincreasing bearing capacity of the ground. The
reinforcement in geosynthetics construction method
consists of fiber materials to withstand against
tensile forces acting upon the soils due to the upper
surcharge. The authors [1] explained some effective
reinforcing method in the previous research. They
investigated the effective methods considering the
optimal length and shape of reinforcement materials.

Here, the reinforcing mechanism is clarified throughtwo-dimensional (2D) model tests of the foundations
using reinforcements under vertical loading
conditions – concentric and eccentric loadings, andthe corresponding numerical analyses.
In practice geosynthetics is laid under a building
foundation. The edges of the reinforcing members
are kept fixed with the ground by hooks to increase
bearing capacity. This construction method has
already been proved effective after the tremor ofGreat East Japan Earthquake on March 11, 2011.
Fig. 1 illustrates an image of tensile force aroundgeosynthetics under a structure. As seen in Fig. 1
tensile force of the reinforcing member determines
the increase of the bearing capacity of the ground.

xFig. 1 Image of tensile force around geosynthetics
However, reinforcing effect with geosynthetics is
199

GEOMATE-Nagoya, Nov.13-15, 2013neither a direct process of ground improvement nor
a process of increasing ground strength. Therefore,at present the evaluation of reinforcing effect is very
difficult. As stated before the reinforcing effect can
only be achieved when tension develops in thereinforcing members depending on the extent oftensile force in the geosynthetics.
OUTLINE OF 2D MODEL TESTS AND
NUMERICAL ANALYSES
500mm

Outline of 2D Model Tests
Fig. 2 shows a schematic diagram of a 2D model
test apparatus for the investigation of bearing
capacity of ground. The size of the model ground is
1000mm in width and 500mm in height. Aluminumrods of 5cm in length, having diameters of 1.6mm
and 3.0mm and mixed with the ratio of 3:2 in weight,
are used as the model ground (unit weight of themass is 20.4kN/m3). An aluminum plate is placed at
the surface of the ground to simulate the bearing
capacity of a strip (flat) foundation. Fig. 3 shows amodel of the foundation. The foundation is 120mm
in width and 35mm in height. Sandpaper is attachedat the bottom of the foundation to attain surface
friction between the foundation and the ground.
Vertical load is applied at the foundation using a
motor. A slider, which permits the movement of theloading rod in the horizontal direction, and a loadcell for measuring the magnitude of load are set in
the loading system. The model test is conducted withthe aspect ratio of 1:100 between the model tests andprototype scale. Vertical displacement and rotationof the foundation are measured setting two
displacement transducers at the two edges of thefoundation. Photographs are taken during theexperiments and they are used later as input data forthe determination of ground movements with aprogram based on the technique of Particle Image
Velocimetry (PIV).
Fig.4 shows a model of reinforcement material.
Tracing paper is used as a geosynthetics which has
almost no bending stiffness. In the tracing paper,
aluminum rods of 1.6mm in diameter are glued withan interval of 10mm to provide frictional behavior in
the reinforcement. The length of reinforcement (L)is 144mm, which is 1.2 times the width of thefoundation (B=120mm). The fixity condition in thegeosynthetics is imposed by setting an aluminum
plate in both edges of the reinforcement. The
dimensions of each aluminum plate for modeling the
fixed boundary condition of the reinforcement are 2mm in thick and 15mm in height having the widthof 50mm. It is projected from the tracing paper(geosynthetics) with an upper part of 5mm and alower part of 10mm. The plate is moved with the
movement of the ground during the application ofload.

Fig. 2 Schematic diagram of apparatus

Fig. 3 Model of foundation

Fig.4 Model of reinforcement material
Outline of Numerical Analyses
Numerical analyses have been conductedconsidering the same scale of the 2D model tests.
Two-dimensional finite element analyses are carriedout with FEMtij-2D program which is developed in
our laboratory. Fig.5 represents a typical mesh usedin the numerical analyses. Isoparametric four-noded
elements are used for soil elements, and elastic beam
elements are used to simulate reinforcements. The
frictional behavior between the reinforcement andaluminum rods, and the foundation and aluminumrods, is modeled employing the elastoplastic joint
element [3]. The friction angle between
reinforcement and aluminum rods, is determined by
the sliding tests (=20° for rough reinforcements).
The friction angle between foundation and soilis=15°. In the numerical analyses the elastoplastic

200

GEOMATE-Nagoya, Nov.13-15, 2013

subloading tij model [4], is used as a constitutive
model for the ground. This model can describe
typicalstressdeformationandstrengthcharacteristics of soils such as the influence ofintermediate principal stress, the influence of stress
path dependency of plastic flow and the influence ofdensity and/or confining pressure. The same
parameters of aluminum rods [1], [2] are used forthe ground materials. The parameters of aluminumrods are listed in Table 1.

which is responsible for the influence of density andconfining pressure. The parameter  represents theshape of yield surface. The parameters can easily beobtained from traditional laboratory tests. Fig.6
shows the results of biaxial test and analysis ofaluminum rod mass. The figure shows the positive
and negative dilatancy of aluminum rod mass; and it
is clear that the strength and deformation behavior
are very similar to those of dense sand.
PETTERNS OF EXPERIMENTS
Table 2 shows the patterns of experiments.
Tracing paper is set underneath the foundation at
different installation depths (D). Five sets ofreinforcement depths are considered: D/B=0.00,
0.05, 0.10, 0.20 and 0.40, where B is the width of
the foundation. In the real field the load of super
structure is not always being acted at the center ofthe foundation. Therefore, the effectiveness of thereinforcement has been investigated for the twodifferent loading positions, load is applied at thecenter (concentric loading) and at an eccentricity of
e=1/4B (eccentric loading).

Fig.5 Finite element mesh for numerical analyses
Table 1 Values of material parameters for the massof aluminum rods

Table 2 Patterns of experiments

RESULTS AND DISCUSSIONS
Concentric Loading Condition
Fig.7 (a) and (b) show the observed andcomputed bearing capacity for different installation
depths in concentric loading condition where thereinforcement length is 144mm (L/B=1.2). The
vertical axes represent vertical load qv, which is
divided byB/2; abscissas show normalized verticaldisplacement that is normalized by the width of thefoundation (B=120mm). The figures also show the
load-displacement curve of the ground without
reinforcement. It is seen in the figures that bearing
capacity increases for the installation depth ofreinforcement at D/B=0.05, 0.10, and 0.20 comparedwith the results of no-reinforcement. In addition,
almost the same reinforcing effect is seen when the
installation depth lies in between D/B=0.05 to 0.20.
On the other hand, the influence of reinforcement
cannot be achieved when the installation depth isdeeper than a certain depth (D/B is greater equal to0.40). Similarly, when the reinforcement is placedon the ground surface just below the foundation,
there is almost no effect of the reinforcements

Fig.6 The results of biaxial test and analysis ofaluminum rod mass
The parameters are fundamentally the same as thoseof the Cam clay model except the parameter a,
201

GEOMATE-Nagoya, Nov.13-15, 2013

except the coefficient of friction of the foundation;
the behavior is similar to the case of noreinforcement. The results agree with the results ofthe previous research [1], where it was found thatwhen the depth of the reinforcement is in between
D/B=1/8 to D/B=1/2, the effect of the reinforcement
is the maximum. Therefore, it can be said that when
the installation of reinforcement is deeper than the
ground surface and is situated in the range of theinfluence of loading on the foundation, the effect ofreinforcement can easily be achieved. When the
installation depth of reinforcement is shallower
tensile force develops in reinforcement due to theload application.
Fig.7(b) shows that the computed bearing
capacity for different installation depths forconcentric loading. As compared with observed
results, the numerical analyses slightly overestimate
the bearing capacity of the model tests. However, if
compared with the results of the no-reinforcement,bearing capacity for the reinforcement at D/B=0.05,
0.10 and 0.20 increases the same way as the model
tests. In addition, in the cases of reinforcement at thesurface and at a depth deeper than D/B=0.40, there isalmost no reinforcement effect. Therefore, it can besaid that the analyses simulate the behavior ofreinforcing effect similar to the observed results.

Figure 8 illustrates observed and computed
deviatoric strain distributions of the ground while
the load approaches the peak strength, it is atv/B=0.06 for the model test, and for the analysis it is
at v/B=0.10 in the case of no-reinforcement and at
0.13 when the reinforcement is setup at D/B=0.10
and 0.40. The distribution of deviatoric strain of themodel tests is obtained from the simulation of the
PIV technique taking two photographs before andafter loading. The upper figure represents the resultsof the no-reinforcement. It is seen that where theeffect of reinforcement occurs, for the reinforcement
at D/B=0.10, a zone of large deviatoric strain
spreads vertically below the foundation and it isdistributed widely compared with no reinforcement.
In the case of installation depth of reinforcement at
D/B=0.4, deviatoric strain develops at narrower zone
and hence bearing capacity of the ground does notincrease. The computed results describe well thedifferences of the deviatoric strain distribution as
observed in the model tests at different installation
depths.

no reinforcement

observed

no reinforcement

computed

D/B=0.10

observed

D/B=0.10

computed

D/B=0.40

observed

D/B=0.40

computed

Fig.8 Deviatoric strain distributions: concentricloading
(a)
24
22
20
18
16
14
12
10
8
6
4
2
0

Observed
Eccentric Loading Condition

0.05

0.1

0.15

0.2

v/B
(b)

ComputedFig.7 Vertical load vs. vertical displacement forconcentric loading

Figure 9(a) shows the observed bearing capacity
for different installation depths in eccentric loading
condition where the reinforcement length is 144mm(L/B=1.2) for the same test patterns as the concentricloading. Here, the load is applied at 2e/B=0.5, i.e., at
1/4th point of the strip foundation. The vertical axes
and the abscissas show the same representation as
described in Fig. 7. The figures also show the resultsof the ground without reinforcement. It is seen thatthe bearing capacity for the eccentric loading issmaller than that of the concentric loading (asillustrated in Fig.7) as a whole. It is seen in Fig.9(a)that bearing capacity increases for the installation
depth of D/B=0.05, 0.10, and 0.20 compared withthe results of no-reinforcement, and the influence of202

GEOMATE-Nagoya, Nov.13-15, 2013

reinforcement cannot be expected when the
installation depth is deeper than a certain depth (D/B
is greater equal to 0.40). These results are similar tothat of concentric loading condition. Consequently,
it can be said that when installation of reinforcement
is deeper than the ground surface and is situated in
the range of the influence of loading on thefoundation, the effect of reinforcement can beachieved even in eccentric loading condition.
Figure 9(b) shows that the computed bearing
capacity for different installation depths for
eccentric loading condition. As compared withobserved results, the numerical analyses slightly
overestimate the bearing capacity of the model tests.
However, if compared with the results of the noreinforcement, bearing capacity in the case ofreinforcements at D/B=0.05, 0.10 and 0.20 increases
the same way as the model tests. In addition, in thecases of reinforcement at the surface and at a depth
deeper than D/B=0.40, there is almost no
reinforcement effect. Therefore, it can be said thatthe analyses simulate the behavior of reinforcing
effect similar to the observed results. The numericalanalyses not only simulate the results of the model
tests for the concentric loading but also simulate theresults of the model tests for the eccentric loading
condition.

Rotation(degree)

Figure 10(a) shows that the observed relation
between the rotations of the strip foundation and thenormalized vertical load in eccentric loading
condition. Since uniform load is not applied to thefoundation during eccentric loading condition, it isvery important to reduce the amount of rotations
which arises at the time of construction. It is seen in
Fig. 10(a) that compared with the result of noreinforcement, the rotation of the foundation starts at
higher load when the reinforcement is installed at
D/B=0.05, 0.10 due to the reinforcing effect. That is,
the foundation can bear a higher load without
rotating if it is reinforced properly underneath thefoundation. However, the amount of load bearing
capacity without any rotation of the foundation isless in the case where the reinforcement is installedat D/B=0.20 as compared with other two cases(D/B=0.05 and 0.10). On the other hand, almost thesame behavior as no-reinforcement is seen when thereinforcement is installed at D/B=0.40. It is revealed
that the rotation angle of the foundation decreases in
the reinforced ground when the reinforcement issetup at D/B=0.05, 0.10 and 0.20. The tendency of
the reinforcing effect in the reduction of rotation
angle of the foundation is similar to that of therelation of bearing capacity and displacement as
described before.

(a)Observed(b)Computed(a)Observed(b)Computed

Fig.10 Rotation angle vs. load for eccentric loading:numerical analyses

Fig.9 Vertical load vs. vertical displacement for
eccentric loading203

GEOMATE-Nagoya, Nov.13-15, 2013

Figure 10(b) represents the results of thenumerical analyses corresponding to model tests
shown in Fig. 10(a). As compared with the observed
results, the numerical analyses slightly overestimate
the amount of rotation at the initial stage. However,
if compared with the results of the no-reinforcement,
rotation of the foundation decreases in the case ofreinforcements at D/B=0.05, 0.10 and 0.20 the same
way as the model tests. In the case of reinforcement
at D/B=0.20, the reinforcing effect on the reductionof the rotation of the foundation is relatively less ascompared with other two cases (D/B=0.05 and 0.10)
the same as the model tests. Similarly, the analyses
do show any reinforcing effect on the rotation of thefoundation in the case when installation depth is
D/B=.40. Therefore, it can be said there is a good
agreement between the computed and observed
results in the rotation of the foundation. So, laying
geosynthetics under the foundation in an appropriate
depth differential settlement can be controlled in
eccentric loading condition.
Figure 11 illustrates observed and computed
deviatoric strain distributions of the ground while
the load approaches the peak strength, it is atv/B=0.03 for the model test, and for the analysis it is
at v/B=0.06 in the case of no-reinforcement and at
0.10 when the reinforcement is setup at D/B=0.10
and 0.40. The upper figure represents the results of
the no-reinforcement. It is seen that even in the caseof eccentric loading where the effect ofreinforcement occurs, for the reinforcement at
D/B=0.10, a zone of large deviatoric strain spreads
vertically below the foundation and deviatoric strain
is distributed widely compared to no reinforcement.
In the installation depth of reinforcement at D/B=0.4,
deviatoric strain develops at narrower zone the same
way as the concentric loading. The computed results
describe well the differences of the deviatoric strain
distribution as observed in the model tests in theeccentric loading as well.

Fig. 11 Deviatoric strain distributions: eccentricloading

CONCLUSIONSThe bearing capacity of soil-reinforcement using
geosynthetics has been investigated with laboratorymodel tests and the corresponding numericalanalyses. The edges of the geosynthetics were kept
fixed with the ground. It is revealed that theeffectiveness of reinforcement mainly depends on
the position of reinforcement and the maximum
reinforcing effect can be achieved when it is set up
in between D/B=0.05 to D/B=0.20 in the fixed
condition. However, in the case of eccentric loading
condition, the reinforcement effect decrease when
the installation depth of reinforcement is D/B=0.20.
Furthermore, if the reinforcement is setup at
D/B=0.40 and deeper, the reinforcement effect is notachieved. If the reinforcement is situated in therange of the influence of loading, the effect ofreinforcement can be achieved even in eccentricloading condition. By laying geosynthetics under thefoundation in an appropriate depth differential
settlement can be controlled in eccentric loading
condition which is very important in real field
construction. The results obtained from thenumerical analyses show very good agreement withthe results of the model tests in all patterns. It can beconcluded that if the mechanical properties ofground material, reinforcing material and skinfriction of reinforcement are appropriately
considered, and the soil-reinforcement is treated as
an interaction problem of the soil and structure (soiland reinforcement), it is possible to explain thereinforcement mechanism properly with such model
tests and numerical simulations.
REFERENCES[1] Nakai T, H. M. Shahin,Watanabe A & Yonaha

S., “Reinforcing mechanism of Geosynthetics
on bearing capacity problems – model tests andnumerical simulations”, Proc. of the 17th
International Conference on Soil Mechanics andGeotechnical Engineering, Alexandria, Egypt,
October, 2009, pp. 917-920[2] Shahin, H. M., Nakai, T., Yoshida, Y. & Mio,M., “Effective reinforcing method forincreasing bearing capacity”, Proc. of the 5th
Sino-Japan Geotechnical Symposium, China,
2012, pp. 457-463.
[3] Nakai, T., “Finite element computations for
active and passive earth pressure problems ofretaining wall”. Soils and Foundations, 25(3),1985, pp. 98-112.
[4] Naka T. & Hinokio T., “A simple elastoplastic
model for normally and over consolidated soils
with unified material parameters”, Soils andFoundations, Vol. 44, No.2, 2004, pp. 53-70.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INFLUENCE OF THE STRESS HISTORY ON THE STIFFNESS OF
SOIL

1,2

Asano Kanako1, H.M. Shahin2, Hiroyuki Kyokawa3, Teruo Nakai4 and Ohashi Ryoki5
Department of Civil Engineering, Nagoya Institute of Technology, Japan; 3The University of Tokyo,
Japan; 4Geo-Research Institute, Nagoya Branch, Japan; 5Nagoya city office, Nagoya, Japan

ABSTRACTThe behavior of soil is influenced by the past stress history. However, it is not only the immediate last stresshistory to have influence on the deformation characteristic of soil, accumulation of all stress histories received in
the past also affects the mechanical characteristic of soil. The number of times, magnitude and the direction of
the past stress are being reflected on the accumulation of stress histories. In this research, several triaxial tests
and true triaxial tests on sand have been conducted employing various stress histories. We have investigated theinfluence of cyclic stress history on the deformation characteristic of soils in details. We have also examined thestationary state of deformation where the change of volume converges to a stationary state by applying cyclicloading on soil. It is revealed that the stiffness of soil increases to certain extent due to the cyclic loading
followed by a constant stiffness after some cycle of loading. The void ratio of soil decreases to certain limit for
cyclic loading and it becomes constant after some cycle of loading the same as the soil stiffness.
Keywords: triaxial test, true triaxial test, stress history, cyclic load, stationary state

which is subjected to drained condition. In order todescribe stress induced anisotropy, till now akinematic hardening law and modified stress areproposed. However, the model cannot explain
completely the development and dissipation
mechanism of a stationary state of soil. Moreover, it
is insufficient to explain only some experimental
values under limited conditions with a constitutive
model. Therefore, verification of a model not only by
the results of a conventional triaxial test but also by
the results of a true axial test is required. For thispurpose, this paper illustrates the results of somecyclic conventional triaxial and cyclic true triaxial
tests under drained condition changing the amplitudeof stress ratio, the direction of loading and the
direction of major principal stress.

INTRODUCTION
In recent years effective use of land including
underground, such as tunnels in urban areas andconstructions of a subway and underground shopping
malls etc., is the demand of modernization. In order
to use the land more effectively, safely andeconomically, exact geotechnical analyses withnumerical simulation are required. For this purpose, aconstitutive model of soil is indispensable which can
express the characteristics of the ground in detailfrom the viewpoints of density, time effect andanisotropy. Even if the conditions of the analysis
conforming to a real problem, if the ability of theconstitutive model used for analysis is insufficient,
the accuracy of the solution will be poor too. In themost cases, the constitutive model used in numericalanalyses of soils is either elastic or elastoplastic
which cannot express the behavior of ground material
fully. Therefore, it is necessary to form a constitutive
model which can clearly express various
characteristics of ground material such as confining
stress and influence of past stress history.
Prediction of soil deformation is difficult because
an internal particle structure changes at every
moment and shows an anisotropic deformation
characteristic according to the past stress history.
This induced anisotropy affects greatly the responseof soil when cyclic loading is applied, and is closely
related to the main problems of geotechnicalengineering, such as liquefaction which is subjected
to undrained condition, compaction of the ground

OUTLINE OF THE TEST AND THE SAMPLEUSED IN THE TESTThe soil used for this research is Toyoura sandhaving a density of 2.65tf/m3. All the test specimens
have been prepared by the water pluviation method tomake a homogeneous sample. In order to maintainalmost the same void ratio, the number of blows
applied in all the test specimens was kept fixed which
was 80. The dimension of the specimen is 12.35 mm
in height, and 50 mm in diameter with saturated
condition. All the experiments were carried out indrained conditions under constant mean effective
stress of 196kPa. The back pressure of 98kPa isapplied to the test specimens for all the tests. In
205

GEOMATE-Nagoya, Nov.13-15, 2013

0.678

1.5

2

Comp.

Comp.

20 cycles10 cycles

e196 = 0.677

1.0

0.677

Initial stateB
End of test

0.5

Void ratio eA

0.0

Stress ratio q/pStress ratio q/p

1.0 1.2

0.0

0.676

-0.5

0.675

-1.0
[A:drained, p=196(kPa) const, e196 = 0.677]

-1.0

Ext.

-1.5

e196 = 0.677

-2

0.0

0.2

Ext.
0.4

0.6

0.8

Deviatoric strain εdMean stress p (kPa)

Ext.
0.0

0.5

1.0

1.5

2.0

Stress ratio q/p(b) εd - q/p relation(a) Stress Path

Comp.

0.674
-1.5 -1.0 -0.5

1.0(c) q/p – e relation

Fig.1 One-way cyclic triaxial compression test
2

0.674

1.5

20
10 cycles
cycles

Comp.
0.672
1.0

A

0.0

B
End of test

Initial state

Void ratio e

0.670

Stress ratio q/pStress ratio q/p

1.0 1.2
0.5

0.0

-0.86

0.668
e196 = 0.672

0.666
0.664

-1.0

-0.5

[A:drained, p=196(kPa) const, e196 = 0.672]

0.662

e196 = 0.672

Comp.
-1.0
-0.4

-2
Mean stress p (kPa)(a) Stress Path

-0.2

0.0

0.2

0.4

0.6

Deviatoric strain εd

0.8

1.0

0.660
-1.5

-1.0 -0.5

0.0

0.5

1.0

1.5

2.0

Stress ratio q/p(b) q/p – εd relation(c) q/p – e relation

Fig.2 Two-way cyclic triaxial compression-extension test
-2

2

Stress ratio q/p

INFLUENCE OF ONE-WAY AND TWO-WAYCYCLIC TESTSIn order to consider the influence of the reverse
way loading in cyclic triaxial test, we have carriedout both one-way cyclic triaxial compression test andtwo-way cyclic triaxial compression-extension test
under constant stress ratio condition. The results of
the one-way cyclic triaxial compression test are
shown in Fig.1, and the results of the two-way cyclic
triaxial compression-extension test are shown in
Fig.2. The stress paths are shown in Fig. 1(a) and Fig.
2(a). Stress ratio q/p – deviatoric strain ε d relations
are shown in figure (b), and void ratio e – stress ratio
q/p relations are shown in figure (c), respectively. It
can be seen from figures (b) and (c) of Figs.1 and 2
that deviatoric strains and void ratio decrease
remarkably in both cyclic triaxial tests. However,with the repeated loading, the amount of deformation
associated with each subsequent cycle gradually
decreases and finally converges to a stationary state.
Comparing the results of the one-way cyclic triaxial

29 cycles

1

Volumetric strain εv [%]addition, all the stresses shown in this paper are
effective stresses. Strain controlled loading is appliedin the tests.

19 cycles
3 cycles2 cycles-1

1 cycleNo history

0
0.0

Comp.

0
0.50

0.25

Deviatoric strain εd [%](a) One-way cyclic triaxial compression test

Stress ratio q/p

29 cycles
19 cycles

3 cycles2 cycles-1

1
No history
1 cycle

0
0.0

Comp.
0.25

0
0.50

Deviatoric strain εd [%](b) Two-way cyclic triaxial compression-

extension test
Fig.3 q/p – εd – εv relations at each cycle
206

Volumetric strain εv [%]-2

2

GEOMATE-Nagoya, Nov.13-15, 2013

compression test (Fig.1(c)) and the two-way cyclic
triaxial compression-extension test (Fig.2(c)), it isfound that more cycles of loading is required to reachthe stationary state in the two-way cyclic triaxial
compression-extension test than that of the one-way
cyclic triaxial compression test.
Figure 3 represents the relation of stress ratio:
q/p – deviatoric strain: ε d for each cycle. The resultsof the one-way cyclic triaxial compression test are
shown in Fig. 3(a), and the results of the two-way
cyclic triaxial compression-extension test are shownin Fig. 3(b). The figures illustrate the behavior due toloading in the compression side in both cases. The
numbers of cycles indicated in the figures represent
the past stress history (in terms of repeated cycle)
which is applied to the specimen. From Fig. 3(a) it isrevealed that for the one-way cyclic triaxial

compression test, when load is applied at the second
time (the first repeated loading), the stiffness
increases sharply, and the stiffness in this state isalmost similar to that of the final stationary state; thestiffness seldom changes even if the number ofrepetition of loading increases after the first cycle ofloading. On the other hand, in Fig. 3(b) for the caseof two-way cyclic triaxial compression-extension test
it is seen that the stiffness increases gradually with
the increase of the number of cycles before reachinga stationary state. It is interesting that though it needs
more cycles to reach the level of the maximum
stiffness (stationary state) the final stiffness in thecase of two-way cyclic test is lower than that of theone-way cyclic test. In the two-way cyclic triaxial
compression-extension test, since the load applied in
the extension side is reverse to the compressive load,

Comp.

2.0

R = 3.0

0.0-1.0

End of test

R = 2.0

Initial stateStress ratio q/p'

1.0

( Drained )( p = 196[kPa] const )( e196 = 0.769 )
-2.0
Ext.

(a) Stress Path(b) q/p - εd relation(c) e – q/p relation

Fig.4 Results of the cyclic test with higher stress ratio(ⅰ) R=3.5(ⅱ) R=2.5(ⅲ) R=1.5(ⅱ) R=2.5(ⅲ) R=1.5(b) q/p - εd relation(a) Stress Path(ⅰ) R=3.5(c) e – q/p relation

Fig.5 Results of the cyclic test reduced stress ratio

207

GEOMATE-Nagoya, Nov.13-15, 2013

stiffness in the compression side is reduced to someextent for every cycle of loading in the extension side.
Therefore, more cycles are required to reach thestationary state in the two-way cyclic test, and thestiffness at the stationary state is comparatively low.

drawn in Fig. 5(a). In Fig.4, the solid marks represent
the results of the first cycle and the open marks show
the results of the last cycle. In Fig.5, black circularmarks represent the results of stress ratio R= 3.5, redsquare marks show the results of R= 3.0, and the blue
diamond marks illustrate the results of R= 3.5. In
every test, the listed stress ratios were applied after
confirmed that soil reached a stationary state.
Figure 4 shows that soil reached to a stationary
state due to the application of repeated stress ratiowith an amplitude of R=2.0 (Stage1). However, whena higher stress ratio R=3.0 is applied on the specimen
the first stationary state is dissipated at the load
application of very first cycle, and gradually soil
reaches to a new stationary state with the increase ofdeviatoric strain and volume contraction due to theapplication of repeated cycles of loading. The
stiffness of the soil increases as well in this case. On
the contrary, it is seen in Fig.5 that when a smaller
stress ratio R=2.5 is applied after applying a higher
stress ratio R=3.5, the stationary state remains as it is
without shifting to a new stationary state.
Consequently, soil stiffness is not affected by thechange of low stress ratio after it has reached thestationary state by applying higher stress ratio.

INFLUENCE OF THE VARIATION OF THE
AMPLITUDE OF STRESS RATIOIn order to investigate the influence of theamplitude of stress ratio on the stress-strain
characteristics of soils in a repeated loading test, thestress ratio is being changed after reaching astationary state by a cyclic triaxial test under constant
amplitude of stress ratio. Figures 4 and 5 show theresults of cyclic triaxial tests on the same specimen as
described before for different amplitudes of stressratio. Figure (b) shows the variation of stress ratio q/pagainst deviatoric strain ε d , and figure (c) represents
the relation of void ratio e and stress ratio q/p. In
Fig.4, stress ratio R changes from 2.0 (Stage1) to 3.0(Stage 2), i.e., stress ratio is being increased. On theother hand, in Fig.5 stress ratio R changes from 3.5 to
2.5 and finally to 1.5, i.e., stress ratio had been
decreased gradually. The stress path of each test is

(A)

Path1

σa

Path1
(3.6,1.2,1.2)(3.6,1.2,1.2)

θ = 12
0 °

(C)
Path1
(3.6,1.2,1.2)

e196 = 0.684

e196 = 0.680

Initial state(2.0,2.0,2.0)

Initial state(2.0,2.0,2.0)

Path2
σl

σa

(B)

θ = 0°

σae196 = 0.674

Initial state(2.0,2.0,2.0)

θ = 180 °(1.2,1.2,3.6)(1.2,3.6,1.2)

σlPath3 σrσl

σr

Conditions common to all tests: drained, p = 196[kPa] const

Path2
σr
(0.858,2.571,2.571)(a) Stress Path
0.686

(A)

0.682

(B)

e196 = 0.684

0.674

(C)

e196 = 0.680

0.684

0.680

0.682

0.678

0.672

0.680

Void ratio e

Void ratio e

Void ratio e

0.670

0.676

0.678

0.674

0.676

0.672

0.668

e196 = 0.672

0.666
0.664

Comp.

0.662

Comp.

Comp.
0.674
-0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

Stress ratio q/p

0.670
-1.5

-1.0 -0.5

0.0

0.5

1.0

Stress ratio q/p

1.5

2.0

0.660
-1.5

-1.0 -0.5

0.0

0.5

1.0

1.5

2.0

Stress ratio q/p(b) q/p – e relation

Fig. 6 Results of cyclic true triaxial test, one-way cyclic conventional triaxial compression test, and two-way
cyclic conventional triaxial compression-extension test
208

GEOMATE-Nagoya, Nov.13-15, 2013

σa(A)
Path1 (3.6,1.2,1.2)(B)drainedp = 196[kPa] const
e196 = 0.761

Initial state(2.0,2.0,2.0)

σaInitial state(2.0,2.0,2.0)

0.762

Path2

(C)

σa

σr

Initial state(2.0,2.0,2.0)
Path3
σl

(1.2,3.6,1.2)
σrσa(D) Path1(3.6,1.2,1.2)

σlθ = 120 °σl (1.2,3.6,1.2)

0.760
0.759
0.758
0.757

Initial state(2.0,2.0,2.0)

0.756

Path3

0.755

Path2
(1.2,1.2,3.6) σre196=0.761

0.761

Void ratio eσlLast cycle of axial cyclic shear
Last cycle of lateral cyclic shear
Last cycle of radial cyclic shear
Last cycle of axial, lateral andradial cyclic shear

σr(1.2,1.2,3.6)(a) Stress Path

0.754
0.0

Comp.
0.5

1.0

Stress ratio q/p

1.5(b) q/p – e relation

Fig.7 Results of cycle test changing the direction of principal stressreaches a stationary state is different in the threedifferent tests. The maximum volume contraction isseen in the two-way conventional triaxial
compression-extension test (C) among the three stresspaths, the minimum one is seen in case (B). The Lodeangles of case (A) is θ =120°, case (B) θ =0° and case(C) θ =120°on the π plane. Therefore, it can be said
that the amount of volume change depends on the
Lode angle too. For the same amplitude of stress ratio
larger volume change is associated with larger Lodeangle.

INFLUENCE OF THE DIRECTION OF MAJOR
PRINCIPAL STRESS (LODE ANGLE)
The variation of the direction of the major
principal stress has been investigated conducting oneway cyclic triaxial compression test. At first,
compressive load with stress ratio of R = 3.0 (q/p =0.0 <=> 1.2) is applied in the direction of a (axial
direction) from an isotropic state of stress having p =196kPa (Path1 – Fig. 6(a)(A) ); in the next step loadin the direction of l (longitudinal direction) (Path2 Fig. 6(a)(B)) is applied; and finally load in the
direction of r (radial direction) (Path3 - Fig. 6(a)(C))
is applied in order. The stress paths 1 to 3 arerepeated until a stationary state is reached. The
results of this test (A) are shown in Fig.6. For
comparison, the results of the one-way cyclic triaxial
compression test (B) and two-way cyclic triaxial
compression-extension tests (C) are also shown in the
figure. The stress path of each test is drawn in figure(a), the relations of void ratio e - stress ratio q/p areshown in figure (b). In figure (a), θ represents theLode angle showing the loading direction on the πplane.
In the case of principal stress path (A), an
expansion of soil is seen after a compaction of soil at
the initial monotonic loading paths and only
compaction is seen at the unloading path the same
way as the conventional triaxial compression test (B).
For the subsequent repeated loading, soil rather
shows compressive behavior even in unloading pathin case (A); the behavior is almost the same as case
(C). After some cycles of loading soil reaches to astationary state the same way as cases (B) and (C).
However, the amount of volume change until it

INFLUENCE OF THE CHANGE OF THE
DIRECTION OF MAJOR PRINCIPAL STRESSIn order to study the influence of the change ofthe direction of major principal stress on the behaviorof re-stationary state in sand, cyclic true triaxial test
kept constant stress ratio in a fixed direction ofprincipal stress have been performed. Here, after
reaching a stationary state, we have changed the Lodeangle and repeated the test by applying the samestress ratio in a fixed direction of principal stress. The
stress path is shown in Fig. 7(a). Firstly, compressive
cyclic load in the direction of a is applied until itreaches a stationary state (Path1 - (A) of Fig.7 (a)), in
the next step the same amount of load is applied in
the direction of l (Path2 - (B) of Fig.7 (a)) until itreaches a stationary state, and the same procedure isapplied in the next step to get a new stationary statein the direction of r (Path3 - (C) of Fig.7 (a)). In thecase of (D) in Fig.7, repeated compressive load isapplied in the directions of a (Path1), l (Path2), and r(Path3) in order until it reaches a stationary state.
Figure 7(b) illustrates stress ratio q/p - void ratio
e relation. Blue circular marks represent the results of209

GEOMATE-Nagoya, Nov.13-15, 2013

the last cyclic of case (A), red square marks show theresults of the last cyclic of case (B), and green
diamond marks illustrate the results of the last cyclicof case (C) and triangle marks show the results of thelast cyclic of case (D). Figure 7(b) shows that after
soil reaches a stationary state in the direction of a, as
a result of changing the loading direction to thedirection of l and then to the direction of r, at every
time soil shifts to a new stationary state with a certain
void ratio breaking the previous one. Therefore, it isrevealed that soil shifts to a new stationary state withthe change of the loading direction even if theamplitude of stress ratio is kept constant.
Nevertheless, if cyclic load is applied in the stress
path shown in (D) after the application of stress pathshown in (C), soil is experienced with the maximum
amount of volume contraction and reaches astationary state with a certain void ratio. This resultshows that the stress path in a cyclic load influences
the amount of volume contraction of soil. The morechange of the direction of principal stress in the stress
path, the larger the volume contraction occurs before
reaching a stationary state.

If the amplitude of stress ratio increases or the
direction of principal stress changes, soil shifts to a
new stationary state from a previously developed
stationary state. The amount of volume change
depends on the Lode angle.
(3) Influence of the direction of major principal
stress The stress path in a cyclic load influences theamount of volume contraction of soil. The morechanges of the direction of principal stress in the
stress path, the larger the volume contraction occurs
before reaching a stationary state.
Therefore, in order to express stress deformation
characteristics, such as the change of stiffness andvolumetric strain which are subjected to the paststress history, it is necessary to consider the past
direction of major principal stress and the amplitudeof stress ratio during the formulation of a constitutive
model.
ACKNOWLEDGEMENTS
The authors are grateful to Mr. A. Ban and Mr.
Ishihara, former student of Nagoya Institute ofTechnology for their contribution in someexperiments.

CONCLUSION
In this paper, several element tests have been
carried out to investigate the factors affecting thevolumetric strain and stiffness of Toyoura sand due tothe stress induced anisotropy. The results can beconcluded as-

REFERENCES[1] Ohashi R, Kyokawa H., Kikumoto M., Nakai. T,
Shahin H.M., and Ban A., “The influences ofstress histories on the deformation characteristics
of sand”, The 23rd conference of JGS Chubu
Shibu, August, 2011 (CD-ROM, in Japanese).
[2] Naka T. and Hinokio T., “A simple elastoplastic
model for normally and over consolidated soils
with unified material parameters”, Soils andFoundations, Vol. 44, No.2, 2004, pp. 53-70.
[3] Ohashi R., Asano K., Shahin H.M, Nakai T,
Kyokawa H., “Experimental Investigation of theDevelopment of Stress Induced Anisotropy andits Dissipation in Sand”, Proc. of the 7th
conference of Japan Society of Materials Science,
Tokai branch, Nagoya, Japan, March, 2013 pp.
71-72 (in Japanese).

(1) Influence of reverse loading In the one-way cyclic test, soil reaches thestiffness due to the first reloading which is almost thesame as the stationary state. In the two-way cyclic
test, stiffness increases gradually with the repeatedloading before reaching a stationary state. Morecycles of loading is required to reach a stationary
state in the case of the two-way cyclic test than thatof the one-way cyclic test because the stiffness is
reduced due to the reverse way loading. Stiffness at
stationary state is less for the two-way cyclic testcompared with the one-way cyclic test as thedevelopment and dissipation of stiffness are being
repeated in the two-way cyclic test.
(2) Influence of the amplitude of stress ratio -210

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECTIVENESS OF CRASHED TILE IN COUNTERMEASURE
AGAINST LIQUEFACTIONMORIKAWA Yukihiro1, MAEDA Kenichi2 and ZHANG Feng3
1
Assistant Professor, Nagoya Institute of Technology, Japan
2,3
Professor, Nagoya Institute of Technology, Japan

ABSTRACT
Liquefaction usually occurs in many sandy grounds during earthquake including Japan. Liquefaction causes
damage of structures by making floatation or subsidence of them, and reduces the necessary performance of thestructures. For example, stability of retaining wall based on skeleton weight of the structure is reduced due tosubsidence and inadequate support which causes the destabilization of the structure. In addition, the light weightunderground structure suffers damage such as floating due to the reduction of shear strength of soils duringliquefaction. The damage occurs not only to the civil engineering structures (roads, bridges, etc.) but also to theresidential buildings which makes the building unusable. On the other hand, Aichi Prefecture (Japan) is a centerof the production of tiles where the crushed tile can be used as recycling materials for a measure of soilliquefaction. In this research, we have investigated the material property of the crushed tile and examined theeffectiveness of countermeasure against liquefaction by shaking table tests. It is found that liquefaction of theground can be reduced using crushed tiles because of its high friction and drainage properties. In the research,
we found that the anti-liquefaction manhole which was backfilled by clashed tile floated only by 1/3 of themagnitude observed in the case of without countermeasure against liquefaction.
Keywords: Countermeasure against liquefaction, recycling materials, clashed tile, disaster mitigation

INTRODUCTION

multiple aftershocks.

In Great East Japan Earthquake happened on
March 11 2011, huge damage was reported [1] and[2]. Especially, the damage caused by tsunami andliquefaction were the largest scale in the history ofobservation. Liquefaction has been intensively dealt
with for a main shock in huge earthquake. In recent
years, however it is found that the bearing capacityof soils may not only decrease in the main shockwith relative short time period but also in multiple
aftershocks with relative a long time seismic motion.
In addition, the multiple aftershocks in short time
period enlarged the damaged area by the liquefaction.
For this reason, it is necessary to predict the damage
and take counter measures, both in software andhardware, against the mixed disasters of huge
earthquake that will happen with very highprobability within thirty years.
Countermeasures against the earthquake forsmall structures such as branch lifelines and personal
houses are urgently needed because they arevulnerable to not only the main shock but also thesecondary disaster that had become serious problems
in the past earthquakes. Therefore, it becomes social
concern and more important for the research on
feasible and effective countermeasures for the
existed small structures against the liquefaction
caused by long-time seismic motion and short-time

IMPORTANCE
OF
THE
COUNTERMEASURES AGAINST LIQUEFACTION FOR
SMALL STRUCTURES
The countermeasures to protect the small
structures from the damage are not so intensively
dealt with compared with huge structures in civilengineering [3]. As observed in Great East Japan
Earthquake, liquefaction causes the floating ofunderground structures such as sewage pipe, water
pipes and gas pipe. Most of which became unusable
for a long period (Fig.1).

Fig. 1

211

Damage as floating ofstructure due to liquefaction

undergroundGEOMATE-Nagoya, Nov.13-15, 2013

In this research, we investigated the material
properties of a crushed tile and examined theeffectiveness of countermeasure against liquefaction
for small structures using the crushed tile. Aichi
Prefecture, Japan, is a major production source oftiles where useless or crushed tile comes out asgarbage. If it can be used as recycling materials foranti-liquefaction, then it will be of great benefit.
RECYCLING
MATERIAL
LIQUEFACTION MATERIAL

AS(Fig.3). The grain size distribution of crashed tile isbetter than Toyoura sand, a clean sand with amaximum grain size is 0.425mm, uniformity
coefficient is 1.6, and coefficient of curvature is 0.9.
As to the density of the crashed tile, because it
has a lot of small voids inside the particles as shown
Fig.4, the density is rather lighter (Gs=2.56) than thegeneral soil (Gs=2.65).
As mentioned before that the grain size
distribution of the crashed tile is better than Toyoura
sand, the distribution of the minimum-maximum
void ratio, however, ranging from e=0.863 to
e=1.457, is much bigger than the other materials,
e.g., Toyoura sand: e=0.614-0.959 (Fig.5).
As the result, the dry density of the crashed tile,
as shown Fig.6, is smaller than other materials
because the void ratio of crashed tile is bigger andthe density of soil particle is lighter.
From the above test results, it is found that thecrashed tile is light soil material that has relatively
good grain size distribution but large void.

ANTI-

About Clashed Tile
The useless or crushed tile, called as abolishedtiles, are produced in a fixed quantity each year,
among which more than 80% of the abolished tiles
are reused as raw materials for the production of
new tile. The other 20%, however, is left unusable.
Besides, the old abolished tile in the process ofreroofing of houses is not recycled at all. The
crushed tile is crushed to small angular particles inorder to make it possible for recycling, as shown in
Fig.2. Physically, the tile is stable that has no bed
influence on environment because it is burnt at avery high temperature of 1150 ºC.

Crushed tile
Toyoura sand
Silica sand No.7
Silica sand No.8

Percentage Passing (%)

120
100
80
60
40
20
0
0.001

Fig. 3

10

Grain Size Distribution

Shape of the particle of material (Left side:crashed tile, Right side: Toyoura sand)

2.8
3

Soil Particle Density(g/cm )Fig. 20.01
0.1
1Particle Size (mm)Physical Properties of Crushed Tile
In this research, some laboratory tests are
conducted in order to investigate the applicability of
the crashed tile as anti-liquefaction material. A redbrown crashed tile made in Mikawa area, hereafter
called as Mikawa crashed tile, is used in thelaboratory tests, including 1G shaking table test.
Figures.3-6 show test results of grain size
distribution curve, density test of soil particle, andminimum-maximum density test of soil (void ratio
and dry unit weight). In addition, the compressive
strength of the particle in crushed tile is 78MPa, andits water absorption is 6-7%.
As for crashed tile that we used in the all tests,
the maximum grain size is 4.75mm, uniformity
coefficient is 6.0, and coefficient of curvature is 0.8

2.7

2.6

2.5

2.4

Fig. 4212

Crushedtile

Silicasand

Toyourasand

Density of Soil Particle

Granitesoil

GEOMATE-Nagoya, Nov.13-15, 2013

Therefore it is reasonable to conclude that theinternal frictional angle of the clashed tile is over40deg from these mechanical tests.

1.50

Void Ratio e

1.25

1.00

0.75

(a) Clashed Tile (41deg) (b) Aluminum ball (41deg)
0.50

Fig. 5

Crushedtile

Toyoura Silica sand Silica sand(No.7)(No.8)
sand

Range of Void Ratio

Fig. 7(d) Silica Sand (31deg)

Repose angle of different materials

15.0

0.004

12.5

10.0

Fig. 6(c) Toyoura Sand (31deg)

17.5

coefficient of permeability (m/s)

3Unit Weight(kN/m )20.0

Crushedtile

Toyoura Silica sand Silica sandsand(No.7)(No.8)

Range of Dry Unit Weight

Mechanical properties of Crushed Tile

0.003

0.002

0.001

0.000
Crushedtile

Figure 7 shows the test results of a repose test, asimplest and easiest way to examine the reposed
angle of a particle material under dry condition. The
reposed angle of the crashed tile is 41deg that ishigher than general sand (around 30deg) from theresult. The reposed angle of aluminum ball whose
shape is completely round, is about 23º, whichmeans that a particle material with angler shape will
possess a high frictional resistance or, a high internal
friction angle.
Figures 8-10 shows the test results ofpermeability test, direct shear test and conventional
triaxial test. The permeability of the crashed tile is
2.76×10-3m/sec, as shown in Fig.8, a higher value
than that of Toyoura sand (5.77×10-4 m/sec)
because the maximum grain size and void ratio of
the crashed tile is bigger than that of Toyoura sand.
The permeability of the crashed tile can be classified
as a coarse sand or gravel.
Figure 9 shows the result from the direct shear
test. The internal frictional angle φ of the clashed tile
is 42deg higher than that of Toyoura sand (around30ddeg). In addition, the test result of triaxial
compression test is shown in Fig.10. The internal
frictional angle of the crashed tile is 41.5deg.

Fig. 8Permeability Test

Shear Strength τ (kN/m2)

400

213

Crushed tile(φ=42.0deg)
Normaly Sand(φ=30.0deg)

300

200

100

0

Fig. 9Toyoura Silica sand Silica sandsand(No.7)(No.8)

0

100
200
300
400
Effective Stress σv'(kN/m2)

Direct Shear Test

GEOMATE-Nagoya, Nov.13-15, 2013

Shear Strength τ (kN/m2)

1000

φ=41.53deg
750

500

250

0

0

250
500
750
1000
Effective Stress σ(kN/m2)

Fig. 11 Shaking Table

Fig. 10 Triaxial Test

The shaking table test device uses air-pressure
actuator that has an advantage of high performanceof maintenance but disadvantage of less accuracy ofwave output. The maximum air pressure is 1.0MPa,
the maximum stroke is 0.05m, the maximum loading
capacity is 18kN, and the maximum vibration
acceleration is 9.80m /s2. A laminate shear box isinstalled on the table whose depth, length and widthis 0.8m, 1.2m and 1.0m respectively. The averagerelative density of Toyoura sand and the crashed tilethat used in the shaking table test, is 24.2% and23.7% respectively.

Table 1 Property of Clashed Tile
Maximum density

ρ d min

g/cm3

1.042

Minimum density

ρ d max3

1.374

Maximum void ratio

e min

1.457

Minimum void ratio

e max

0.863

Soil particle density

ρs

g/cm3

2.56

Maximum grain size

D max

mm

4.75

60% diameter on the grain
size diagram

D 60

mm

1.28

50% diameter on the grain
size diagram

D 50

mm

0.847

30% diameter on the grain
size diagram

D 30

mm

0.456

10% diameter on the grain
size diagram

D 10

mm

0.213

Uniformity coefficient

Uc

6.0

Coefficient of curvature

Uc’

0.8

Coefficient of permeability

k

m/sec

Angle of Internal friction

φ∋

deg

g/cm

Test Conditions
In the shaking table test, we use the crashed tile
as a backfill material against the liquefaction andToyoura sand as the model ground material. In thetest, the apparent gravity of the manhole, anunderground structure, is 1.2, its diameter is 0.10m,
the height is 0.30m, and the manhole is made fromacryl hollow cylinder. Figure.12 shows the planview of the model ground. In the test, one manhole
is backfilled by the crashed tile and another one isbackfilled with the same sand as the model general.
Both the manholes were installed in the samelaminate shear box and were excited with the same
earthquake motion. As shown in Fig.12, the antifloating manhole is on the left side and the manhole
without countermeasure is on the right side of theshear box. In the test, the height of model ground is
0.50m while the depth of the crashed tile ascountermeasure against floating is from GL-0.30m
to the top surface, which is the same depth as the
manhole length. Of course it is much better tobackfill the manhole by the crashed tile from inwhole depth, here we only investigate a minimum
improvement effect of the backfill.

2.76*10-3
42.0

COUNTERMEASURE AGAINST FLOATINGOF UNDERGROUND STRUCTURES
Setup of Experiment
The crashed tile is then regarded as an effective
material for anti-liquefaction because its internal
frictional angle and permeability is higher than thoseof sands. In order to confirm this factor, we
conducted a floating test of manhole which isbackfilled with the clashed tile on liquefiable sandy
ground using 1G shaking table test, as shown in
Fig.11.

214

GEOMATE-Nagoya, Nov.13-15, 2013

1200
50

50

100

400

50

50

200

50
250

100
50

300

4.0

2

Acceleration(m/sec )

180

200

B

70

20 50

C

A

100

300

100

50

1000

300

100

500

200

200

100

100

200

200

100

In addition, the EPWP at Point B (around of thecrashed tile) also dissipated immediately after theexcitation, the same as Point A, meaning that it is aneffective countermeasure against the liquefaction
using the crashed tile as backfilling material.
The EPWP at all the points below GL-0.30m,
however, the effectiveness of the countermeasureagainst liquefaction cannot be confirmed, as shownin Fig.17.

250

600

350
200

100

100

100

300

200

400

100

200

1200

manhole

100

0.0

-2.0

500

100

500

500

300

100

manhole2.0

100

clashed tile
200

-4.0

100
200

100

100

sensor

0

15

100
400

300

100

200

1200

30
t(sec)

45

60

Fig. 13 Input Wave
Excess Pore Water Pressure Ratio

Fig. 12 Plan and x-section of the shaking table test
We installed 12 excessive pore water pressure
sensors within the model ground, Point A, where islocated inside the backfilling area with the crashedtile, Point B where is near the backfilled area, andPoint C where is no-countermeasure area, as shownin Fig.12. In all the measurement points, the sensors
ware installed at 4 different depths (GL-0.10m, GL0.20m, GL-0.30m, GL-0.40m).
Results of Shaking Table Test
Figure 13 shows the input wave which wasmeasured on the table of the test. Its frequency is
4Hz, shaking time is 10sec, and the maximum
acceleration is around 0.2 m/sec2.
Figures 14-17 show the excessive pore waterpressure ratio (EPWPR) at each measurement point.
The results shows that the EPWPR may rise over 1.0,
which we consider as a measuring error, because thereason why this phenomenon occurred is due to thesmall initial value of the confining stress but withrelative large up-down movement happened aroundthe sensors near the surface.
From the measuring results at point A (inside of
the clashed tile), it is known that the excessive porewater pressure (EPWP) decreased substantially
immediately after the excitation at the depth of 30
cm, implying that the crashed tile is a good material
to enhance the dissipation of EPWP and hard to beliquefied.

2.0
A(GL-0.10m)
B(GL-0.10m)
C(GL-0.10m)

1.5
1.0
0.5
0.0
-0.5

0

15

30
t(sec)

45

60

Excess Pore Water Pressure Ratio

Fig. 14 Excess Pore Water Pressure Ratio(GL-0.10m)
2.0
A(GL-0.20m)
B(GL-0.20m)
C(GL-0.20m)

1.5
1.0
0.5
0.0
-0.5

0

15

30
t(sec)

45

Fig. 15 Excess Pore Water Pressure Ratio(GL-0.20m)
215

60

Excess Pore Water Pressure Ratio

GEOMATE-Nagoya, Nov.13-15, 2013

2.0
A(GL-0.30m)
B(GL-0.30m)
C(GL-0.30m)

1.5
1.0

(a)

0.5

Fig. 19 Situation of the Manhole (2nd earthquake):(a) Manhole Without Countermeasure, (b) Manhole
With Countermeasure

0.0
-0.5

0

15

30
t(sec)

45

60

Based on the above results, it is clear that thecrashed tile is very effective backfilling material thecountermeasure against liquefaction. When anunderground structure is backfilled by a material
with high frictional resistance and high permeability
like the crashed tile, it is possible to minimize thedamage related to the floatation due to liquefaction.

Fig. 16 Excess Pore Water Pressure Ratio(GL-0.30m)
Excess Pore Water Pressure Ratio

(b)

2.0
A(GL-0.40m)
B(GL-0.40m)
C(GL-0.40m)

1.5

CONCLUSION
1.0

The Performance of Clashed Tile
0.5

1)
2)

0.0
-0.5

The angle of internal friction is very high.
The coefficient of permeability is very high.

Effectiveness of Countermeasure
0

15

30
t(sec)

45

60

1)Fig. 17 Excess Pore Water Pressure Ratio(GL-0.40m)
Figure 18 shows the situation of the manhole
after the excitation. In the first vibration loading, themanholewithout
countermeasureagainstliquefaction floated by 95mm, shown in Fig.18 (a),while the manhole backfilled with the crashed tile
for anti-liquefaction, floated only by 31mm, shownin Fig.18 (b).
Furthermore, in the second shaking, the manhole
without countermeasure floated and then fell down
completely, shown in Fig.19 (a), but the damage tothe manhole with anti-liquefaction measure islimited, as shown in Fig.19 (b).

(a)

2)

The anti-liquefaction manhole which was
backfilled by clashed tile floated only by
1/3 of the magnitude observed in the case ofwithout
countermeasureagainstliquefaction.
EPWP inside and around the clashed tile
decreases immediately after excitation,
hence clashed tile can be an effective
countermeasure against liquefaction.

REFERENCES[1] Kazam M., " Overview of the damages of The
2011 Off the Pacific Coast of Tohoku
Earthquake and its geotechnical problems"
Japanese Geotechnical Journal, Vol. 7(1), 2012,
pp. 1-11.
[2] Yasuda S., Harada K., Ishikawa K., " Damage
to structures in Chiba Prefecture during the2011 Tohoku-Pacific Ocean Earthquake"Japanese Geotechnical Journal, Vol. 7(1), 2012,
pp. 103-105.
[3] Murakami Y., Goto S., Yoneyama T., "Prevention of liquefaction of shallow backfill
ground and of up-lift of underground facilities
by use of stabilized mud" Japanese
Geotechnical Journal, Vol. 2(2), 2006, pp. 8794.

(b)Fig. 18 Situation of the Manhole (1st earthquake):(a) Manhole Without Countermeasure, (b) Manhole
With Countermeasure216

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PREDICTION OF NATM TUNNEL EXCAVATION UNDER SHALLOWOVERBURDEN IN PAHANG-SELANGOR RAW WATER TRANSFERTUNNEL PROJECT, MALAYSIA
1

Mohd Ashraf Mohamad Ismail, 1Goh Chin Ong, 1Romziah Azit, 2Zulkifli Nordin, 2Norzani Mahmood

1School of Civil Engineering, Universiti Sains Malaysia, 2Pahang-Selangor Raw Water Transfer Tunnel Project,
Ministry of Energy, Green Technology and Water, Cyberjaya, Selangor, Malaysia
ABSTRACTThis study deals with the prediction of NATM tunnel construction with shallow overburden at the Kerau rivercrossing in the Pahang-Selangor Raw Water Transfer Tunnel Project. The subsurface profiles along the shallow
NATM tunnel alignment are developed based on 13 boreholes data and in-situ Lugeon tests using inverse
distance weighting (IDW) interpolation together with electrical resistivity survey result. Based on the subsurface
profiles developed, the tunnel excavation was simulated using filtered tunnel model to assess the rock mass
weathering grade, Rock Quality Designation (RQD) and Lugeon value. From the result analyses, the weathering
grade at the crown along the tunnel alignment is mainly in rock grade III and grade II at the invert with RQDfrom 50-90%. Additionally, the comparison between filtered model for Lugeon value and electrical resistivity
result indicate the zone of potential flow path underneath the Kerau River. The prediction allows the potential
risks along the critical tunnel alignment being evaluated and suggested solutions to be proposed to provide
complete stabilization during the tunnel excavation and advancement.
Keywords: NATM tunnel, inverse distance weighting, Filtered Tunnel, Electrical Resistivity Testfor the tunnel excavation under the Kerau River.
Meanwhile, Japanese Highway (JH) Classification
System is used to classify the rock to determine thetype of tunnel support. Since the geotechnicalparameter and engineering properties cannot be
obtained using borehole method under the Kerau
River before the tunnel construction, only probe
drilling method will be used to investigate thegeological condition ahead of the tunnel during thetunnel excavation [6, 7]. To stabilize the tunnelcrown during the excavation, additional tunnel
support such as pipe roof and forepoling must be
installed during the excavation of the tunnel [8-10].
For this project, forepoling with all ground fastened(AGF) will be used as the additional support system
for the tunnel crown. The construction of forepoling
have been described in details by Kontothanassis,
Koronakis [11] and Leca, Leblais [12]. For thisproject, forepoling was not only acted as support tothe tunnel crown, but also act as a roof support for
further tunnel advancement. In this study thepotential risks along the critical alignment under the
Kerau River crossing will be evaluated based on thegeological and engineering properties that controls
the behaviour of the NATM tunnel excavation.

INTRODUCTION
The construction of shallow tunnel inheterogeneous geological condition is very difficultcompare to other construction projects. The
construction can be more complex if the tunnel is
excavated under a river with shallow overburden as
there are many uncertainties and risk involved.
Before the tunnel is excavated under the Kerau
River, geotechnical investigations has been carriedout to assess the ground condition. Rotary drilling
was carried out to obtain the soil and rock samples.
Meanwhile, single and multiple packers Lugeon
tests were carried out to determine the permeabilityof the rock. According to Spencer [1], the tunnel
can be submerged by the water during theconstruction if there is a water bearing zone
surrounding the tunnel alignment. Thus, it isimportant to identify the water bearing zone
underneath the river bed before the excavation
proceed. However, rotary drilling cannot be done
directly below the river bed of the tunnel alignment
due to the risk presence although the geotechnicalparameter and engineering properties under theriver is essential for the tunnel excavation andadvancement planning.

SPATIAL INTERPOLATION USING IDW
The construction of the tunnels through different
ground conditions needed different methods of
excavation and construction such as using Tunnel
Boring Machine (TBM) or New Austrian
Tunnelling Method (NATM) [3-5]. Due to theshallow tunnel overburden and occurrence ofheterogeneous ground conditions, NATM was used

In this study, subsurface models are developed
using Inverse distance weighting (IDW) techniquewhich is based on spatial interpolation between all
input data points. IDW is an interpolation techniquethat places with a known scattered set of points
nearer to the interpolated location. IDW algorithm217

is a moving average interpolator that is usuallyapplied to highly variable data. This method
assumes the influence of the variable entered on themap decreases with the increase of the distancefrom its sampling site. In the inverse distanceweighted interpolation, the interpolation value ofZ(𝑋𝑋0 ) in the position 𝑋𝑋0 is calculated based on thefollowing expression:𝑛𝑛

𝑍𝑍(𝑋𝑋 ′ ) = � 𝑊𝑊𝑖𝑖 𝑍𝑍(𝑋𝑋𝑖𝑖 )SUBSURFACE MODELINGIn this study the data obtained from the PahangSelangor Raw Water Transfer Project is used tocharacterize the subsurface condition along thetunnel alignment under the Kerau River Crossing.
The data is interpreted and categorized into
geological and engineering parameter for
subsurface characterization together with theelectrical resistivity survey carried out at the site.
The main parameters that important for the study
are rock mass weathering grade, Lugeon value androck quality designation (RQD) which are obtained
from the borehole and rock drilling data at the study
area (Fig.2). The excavation method used for thetunnel alignment under the Kerau River Crossing is
NATM which is very suitable for tunnel excavatedunder mix ground condition.

(1)

𝑖𝑖=1

where n is the number of scatter points (datasamples) in the set, Z( 𝑋𝑋𝑖𝑖 ) are the values at the
sampled points (e.g., the data values set), and 𝑊𝑊𝑖𝑖
are the weights assigned to each sampled point.
This weight is calculated with the following
function:ℎ𝑖𝑖 −𝑝𝑝
𝑊𝑊𝑖𝑖 = 𝑛𝑛(2)∑𝑗𝑗=1 ℎ𝑗𝑗 −𝑝𝑝

where p is a positive real number called the power
parameter (typically, p = 2) and ℎ𝑖𝑖 is the distancefrom the sampled location to the unsampled
location for which an interpolated value is required[13]. For certain data types, it is possible to returnto the collection site and record a new value that is
statistically different from the original reading but
within the general trend for the area. It is notdesirable to honour local high/low values but rather
to look at a moving average of nearby data points
and estimate the local trends.

Fig.2: 3-Dimensional borehole location model
Based on the data collected, the filtered tunnel
model is develop by using Inverse Distance
Weighting Method (IDW) which is one of thedeterministic method for multivariate interpolation
with a known scattered set of data points.
Rockworks 15 software package with the built in
deterministic method for multivariate interpolation
will be used to generate the spatial model andprofile along the tunnel alignment based on the
point wise data obtained from the boreholes and insitu Lugeon tests. The results from the subsurface
models were interpreted and analysed to understandthe ground behaviour that will be subjected to thetunnel excavation. The evaluation is carried out
based on the subsurface and filtered model
developed for the rock mass weathering grade,
Lugeon value and RQD. The ground was filteredalong the tunnel alignment under the Kerau River
Crossing based on rock mass weathering grade,
Lugeon value and RQD to predict the behaviour of
the rock mass that will be excavated during theconstruction of the NATM tunnel. The prediction of
the tunnel behaviour under the Kerau river crossing
will benefit the tunnel excavation project as it will
provide the information of the tunnel behaviour
before and during excavation of the tunnel. Hence,

The IDW technique calculates a value for eachgrid node by examining surrounding data points
that lie within a user-defined search radius. Some or
all of the data points can be used in theinterpolation process. The node value is calculated
by averaging the weighted sum of all the points.
Data points that lie progressively farther from thenode influence the computed value far less thanthose lying closer to the node (Fig.1).

Fig.1: IDW interpolation technique218

safety of the tunnel construction during the
excavation can be ensured by putting additional
supports that are required to stabilize the tunnel.

Table 1: Position of Filtered Ground
Filtered
TunnelLengthA

Simulation of tunnel excavation using Filtered
tunnel model
For the real Pahang-Selangor Raw Water
Transfer Project, the NATM tunnel diameter was
5.5m where there is a semi-circle on the upper partand a rectangular shape at the bottom part. The
dimension of the NATM tunnel was shown in
Fig.3(a). Since it is unable to draw out the realshape of NATM tunnel by using Rockworks 15
software, a circular shape of tunnel with 5.6m
diameter was drawn to simulate the real NATM
tunnel excavation. It is acceptable as the area of a
5.6m diameter circular tunnel was covered thewhole area of the real NATM tunnel. The simulated
NATM tunnel was shown in Fig.3(b). From theanalysis, the excavated ground is filtered tocompute the rock mass weathering grade, Lugeon
value and Rock Quality Designation (RQD) along
the tunnel excavation. The result from the filtered
ground is very important to predict the rockweathering grade, permeability and rock quality
along the tunnel excavation.

Location
Point A 1
Point A 2

Coordinate
EN
444870 373350
444925 373407

Elevation
(m)
80
80

Kerau River
A2

Length A

A1

Fig.4: Location of filtered Tunnel.

Fig. 5: Example of Filtered tunnel excavation forweathering grade(a)

RESULT AND DISCUSSION(b)

Fig.3: a) Real NATM tunnel shape. b) Simulated
NATM tunnel shape

Simulation of tunnel excavation based on Rock
Mass Weathering Grade

Position of Filtered Ground

The result from the analysis was shown in Table
2. Based on the computed result, there are 8.3% ofrock Grade IV, 45.0% of rock Grade III and 46.7%
of rock Grade II existed along the critical tunnelalignment under the Kerau River. Referred to Fig.5,
rock grade IV and rock grade III were existed at the
top part along the tunnel alignment. Thus, top
heading and bottom heading excavation was
proposed in order to reduce the excavation
disturbed or damage zone that might be occurred
during the control blasting. In addition, to preventroof collapse due to the tunnel excavation,
forepoling with AGF was proposed to be used tostrengthen the tunnel roof before the next sequence
excavation. Besides that, rock bolt, shotcrete andsteel rib should be installed once the tunnel
excavation was done.

The ground will be filtered according to two
different lengths based on the real tunnel alignment
data for the Pahang-Selangor Raw Water Transfer
Tunnel Project. The length of filtered ground was
carried out at a specific area under the Kerau rivercrossing. The detailed analyses was carried out
under the Kerau river crossing because there weremany uncertainties at that area, hence prediction ofunfavourable risks and hazards need to be carriedout to provide a reliable information of thegeological condition. The information of thefiltered ground was listed in Table 1. The locationof filtered tunnel is shown in Fig.4 (indicated inyellow) and the example of filtered ground basedon rock mass weathering grade is shown Fig. 5.

219

from 15 to 50 (2x10-4 - 6x10-4 cm/sec) existed under
the Kerau River.

Table 2: Weathering grade during tunnel excavation
Soil Mass
Weathering
Grade
Grade 4
Grade 3
Grade 2
Total Filtered
Volume:Volume (m3)Percentage(%)

156.69850.06881.125

8.3
45.0
46.7

Lugeon Value

Volume (m3)Percentage (%)

<1

0

0

1-5

544

28.36

1887.875

100

5-15

897.875

46.81

15-50

476.25

24.83

Total Volume1918.125

100

Table 3: Lugeon value during tunnel excavationa) Weathering grade III and IV from middle tocrowna) Lugeon value from 1-5b) Lugeon value from 5-15b) Weathering grade II from middle to invert
Fig.6: Filtered tunnel (rock mass weathering grade)
Simulation of tunnel excavation based on
Lugeon value
Lugeon test is necessary for evaluating seepage
potential and for determining whether pre-grouting
is necessary or practical. In this project, the main
purpose to carry out the Lugeon test is to determine
permeability of the rock mass for seepage
evaluation and control. The detailed result from theanalysis carried out on the Lugeon tests data wasshown in Table 3. Based on the computed result,
there are 28.36% of rock having Lugeon value from
1 to 5 (1x10-5- 6x10-5 cm/sec), 46.81% of rockhaving Lugeon value from 5 to 15 (6x10-5-2x104
cm/sec) and 24.83% of rock having Lugeon valuec) Lugeon value from 15-50
Fig.7: Filtered tunnel (Lugeon value)
Fig.7 show the area based on three classified
Lugeon value classes (Lugeon value from 1-5; 5-15

220and 15-50). Higher permeability in rock mass will
induce ingress of water into tunnel when excavated.
Hence, it will affect the working condition during
construction of tunnel. From the result, due to highpercentage of excavated area that will experiencehigh permeability in rock mass, probe drillingshould be done before the tunnel alignment passing
through the high permeable zone in order to obtain
more reliable data regarded to the rock permeability
in front of tunnel face. If the high permeable zone
was confirmed by probe drilling data, pre-grouting
from inside the tunnel was recommended to bedone before excavation in order to reduce the riskof excessive water ingress during tunnel excavation.
Additionally, seepage draining should also be done
so that the ingress water will not affect the working
condition in the tunnel.

Comparison of Electrical Resistivity Test Resultand Lugeon Value
Combining electrical resistivity and Lugeon
tests results are important for comprehensive
prediction of rock permeability which may affectgreatly the progress of the tunnel excavation andadvancement. The electrical resistivity profile was
generated based on the measured data at site and as
shown in Fig.9. Meanwhile Fig.8 shows the Lugeon
value of the subsurface. Under the Kerau river the
resistivity value is in low to moderate resistivity
value zone. This is due to the present of fracture
aquifer existed in the rock mass under Kerau riverwhich indicated that this zone is in critical zone ofhigh water content in the rock mass. When
compared to the Lugeon value profile in Fig.8 andFig.9, both of the subsurface profiles possessed apotential zone of high permeability under the Kerau
river. Both of the results shown that the rock massunder Kerau river were experienced high in watercontent and permeability. Hence, the generated
subsurface profile by using Lugeon value wasreliable to be used as engineering judgement before
and during the tunnel construction.

Evaluation of Filtered Tunnel Based on RockQuality Designation (RQD)
The detailed result from the analysis was shownin Table 4. Based on the computed result, there are
0.41% of rock having RQD from 0 to 25, 33.23%of rock having RQD from 25 to 50, 30.87% of rockhaving RQD from 50 to 75, 32.03% of rock having
RQD from 75 to 90 and 3.46% of rock having
RQD>90 under the Kerau River. Range of RQD
value from 0 to 75 indicated the weak zone thatexisted in rock mass during tunnel excavation.
Based on Table 4 there was high percentage(64.51%) of weak zone of rock mass existed under
Kerau river. Additional investigation should be
carried out to assess the orientation andcharacteristic of the weak zone.

Kerau River`

Table 4: RQD during tunnel excavation
RQD
0-25
25-50
50-75
75-90
>90
Total Volume

Volume (m3)7.75
635.875
590.625
612.875
66.25
1913.375

Fig.8: Lugeon value subsurface profile

Percentage (%)
0.41
33.23
30.87
32.03
3.46
100

Fig.9: Electrical resistivity test result at Kerau river
DISCUSSION AND CONCLUSION
Deterministic analysis was carried out by using
Rockworks software. By using Inverse Distancemethod, the filtered model was generated toestimate the volume of excavated tunnel under
different rock grade.
Fig.7: Filtered tunnel (RQD)
221

Evaluation of filtered model according to rockmass weathering grade allowed the prediction ofrock quality at region under Kerau River. Rockmass weathering grade was the main importantfactor that determine the method of tunnel
excavation and also types of tunnel support used.
From the simulation, Rock Granite II and Rock
Grade III were predicted to exist at the route of
NATM Tunnel alignment. Based on the evaluationof subsurface profile, forepoling was proposed to beinstalled as roof support. Besides, types of tunnel
support such as steel rib, rockbolt and shotcrete
were also proposed.

proposed to provide complete stabilization during
the tunnel excavation and advancement
ACKNOWLEDGEMENT
The authors gratefully acknowledge theassistance and cooperation given by KeTHHA(Ministry of Energy, Green Technology and Water
Malaysia) and Tokyo Electric Power Services Co.,
Ltd. (TEPSCO) to carry out this study successfully.
Finally, the authors greatly appreciate the financial
assistance from USM Short Term Grant that madethis research possible.
REFERENCES

Evaluation of filtered model according to the
Lugeon value allowed the prediction of
permeability of the rock mass under Kerau River.
High permeability of rock mass indicated theoccurrence of discontinuities in rock mass. Thus,
the analysis allow the site engineer to foresee theregion that required more concerns, and able toprepare the countermeasures before the problem
occurred. Based on the analyses, probe drilling wasrecommended to be done in order to obtain morereliable immediately before the tunnel excavation
and advancement. Besides, type of grouting such as
pre-grouting was also recommended to be carriedout to reduce the seal the fractures and reduce theamount of water ingress.

1. Spencer, M. Tunnel Boring Machines. in IMIA
Conference Istanbul. 2009. Instanbul.
2. Ruwanpura, Y.A., M, Allouche, M, Analyticalmethod to reduce uncertainy in tunnel
construction project. Canadian Journal of Civil
Engineering 31 (2), 2003: p. 345-360.
3. Messinella, M., Models for the Analysis of
Tunnelling, 2010, Concordia University: Texas.
4. Rossi, L., Tunnel construction-fact about the
Adelaide-Crafers Highway project, 1999,
Federal Government of Australia.
5. COWI, g., Tunnel Engineering, 2004: Denmark.
6. Almén, K.-E. and L. Stenberg, Characterisation
methods 2005: Sweden.
7. Australia, S.o.W., OPEN PIT MINING
THROUGH UNDERGROUND WORKINGS,
2000: Western Australia.
8. Almeraris, G. and B. Mariucchi, in Rapid
excavation and tunneling conference procedings.
2009, Society of
Mining,Metallurgy, andExplaration,Inc.: USA. p. 736-737.
9. Oskar,S.,
NATM
ApplicationsinSingapore,Ground Condition, 2010, Geoconsult
Asia Singapore Pte. Ltd: Singapore.
10. CHENG, K.H., Construction of Pipe Roof andSupport System, 2010: India.
11. Kontothanassis, P., et al., Design andconstruction of NATM underground station
tunnel by using the forepoling method in
difficult conditions for Athens Metro, 2005,
Taylor & Francis Group: London.
12. Leca, E., Y. Leblais, and K. Kuhnhenn,Underground works in soils and soft rocktunneling, 2005.
13. Mito, Y., M.A.M. Ismail, and T. Yamamoto,Multidimensional scaling and inverse distanceweighting transform for image processing ofhydrogeological structure in rock mass. Journalof Hydrology, 2011. 411(1–2): p. 25-36.

For evaluation of RQD filtered model, thequality of the rock mass are able to be predictedbased on the subsurface model developed.
Condition of rock mass will affect the types oftunnel support and tunnel roof. For the region ofrock mass that had low value of RQD, more support
such as rock bolt with shotcrete and steel rib wasneeded during the excavation of tunnel. Thus, theanalysis displayed a clear image for the engineer todetermine the suitable type of tunnel supports
needed during the construction of NATM Tunnel.
Finally,
comparison
betweenElectrical
Resistivity subsurface profile and Lugeon value
subsurface profile were carried out to determine therelationship between these two profiles. From thegenerated profiles, it had shown that the electricalresistivity subsurface and Lugeon value subsurface
profile were correlated to each other which isthrough the similar zone of high water content.
In conclusion, filtered model based on rockmass weathering grade, Lugeon value and RQD canbe used to determine the main geological andengineering properties that control the behaviour ofshallow tunnel under unfavourable groundcondition. At the same time the analyses allows thepotential risks along the critical tunnel alignment
being evaluated and suggested solutions to be

222

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

FUNDAMENTAL STUDY ON LATERAL RESISTANCE
CHARACTERISTICS OF BALLASTED TRACKS SUBJECTED TO
PSEUDO-STATIC INERTIA FORCE
Ryuta Ogawa1 and Kimitoshi Hayano2
Graduate School of Urban Innovation, Yokohama National University, Japan
2
Institute of Urban Innovation, Yokohama National University, Japan

1

ABSTRACT
Ballasted tracks compose about 90 percent of railroad tracks in Japan. However, there is a concern thatlateral resistance of ballasted tracks may be reduced when they are subjected to earthquakes owing to loosening
or collapse of ballasts. For safety, it is important to evaluate effects of earthquake motions on the lateralresistance. In view of above, discrete element simulations were conducted on model grounds which were 1/5 ofactual size to investigate effects of horizontal seismic inertia force on the lateral resistance. After each model
ground was subjected to quasi-static inertia forces, horizontal loadings were applied on a single sleeper by
displacing it. The resistance forces were measured during the loadings. The analyses results suggested that lateralresistance of sleepers would decrease with the increase of horizontal seismic coefficient. It was also found thatthe significant reduction of lateral resistance appeared when the railway roadbed shoulders collapsed by the
combined effects of the seismic inertia force and horizontal displacement of sleepers.
Keywords: Ballast, Sleeper, Lateral resistance, Earthquake, Quasi-static inertia force, Discrete element
simulations
1. INTRODUCTION
Ballasted tracks compose about 90 percent ofrailroad tracks in Japan. However, there is a concernthat lateral resistance of ballasted tracks may be
reduced when they are subjected to earthquakes
owing to loosening or collapse of railway roadbed as
illustrated in Fig. 1. Then, it is afraid that decrease oflateral resistance induces railway buckling as shownin Fig. 2. Therefore it is important to evaluate effectsof earthquake motions on the lateral resistance forsafety design [1].
In view of above, discrete element simulations(DEM) were conducted on numerical railway
roadbed models which were 1/5 of actual size toinvestigate effects of horizontal seismic inertia force
on the lateral resistance. The numerical roadbed
models were subjected to quasi-static inertia forces
and a constant horizontal displacement was appliedon sleepers. The resistance forces of the sleepers
were measured during the displacements.
External Force

Fig. 2 Schematic image of rail buckling
2. DISCRETE NUMERICAL MODELLING
2.1 Modeling of ballasts and a sleeper
Ballastparticles
weremodeledas spherical particles in this time. Actually, theballast shape is not spherical. However, to reducethe computational cost the spherical shape is adaptedin this study. The effect of the particle shape, forexample, lower resistance of particle rotation, should
be study on the lateral resistance in future research.
The spherical particle sizes were 1/5 of actual
ballasts and the particles size distribution was 1/5 ofactual one which satisfied the Japanese standard
particle size range as shown in Fig. 3.
A single sleeper was modeled as a rectangularparallelepiped solid (0.063m in width, 0.48m in
length and 0.051m in height). The sleeper wasembedded in ballasts as shown in Fig.4. The railway
roadbed slope was set one in 1.8.
The interaction between the spherical particles isdefined by the following equation of motion.

Lateral resistance
Ballastma = ∑ (Fn + Fs ) + Fb

Fig. 1 Decrease in lateral resistance of ballast due tothe collapse of roadbed during and after earthquake
223

(1)

GEOMATE-Nagoya, Nov.13-15, 2013kn =2 E1r1 E2 r2
E1r1 + E2 r2

Percentage passing P (%)

Here, m is the mass of particle, a isthe acceleration of particles, F n is contact normal
force, F s is contact tangential force and F b is bodyforce including gravitational force acting on
the particle. It should be noted that, with regard
to the interaction between the sleeper and particles,
Eq. (1) is also satisfied.
In this study, three dimensional discrete
numerical modeling was adopted with using open
source software called YADE [2]. Table 1 lists
parameters used in the simulations. The details are
as follows.
1) Number of particles n
Number of particles n was determined so that it
satisfied the ballast bed density 1,600 kg/m3. In total
73,210 particles was used in this analysis.
2) Radius of particle r
Radius of particle r was set to follow the particle
size distribution (see Fig. 3).
3) Density of particle ρ s
Density of particle ρ s , 2,700 kg/m3 was used torepresent the actual density of ballasts.
4) Spring constant k n
Spring constant in the normal direction, k n
between particles is defined by the Eq. (2) using
the particles’ Young’s modulus E. In thepresent analyses, although it was significantly lower
than that of actual ballasts, Young’s modulus 50MPa
was adopted to reduce the computational time.
Young's modulus will affect the analysis results.
Lateral resistance of ballast becomes lower than theactual value. But in this study, the emphasis isplaced on understanding the qualitative behavior of
the lateral resistance of ballast.

100
90
80
70
60
50
40
30
20
10
0

Standard range (1/5)
of actual ballasts

Spherical particles

1

20

10

Particle diameter D (mm)Fig. 3 Particle size distribution of spherical particles
0.48
0.063

Sleeper

0.3

Ballast0.68
0.091
Sleeper
Ballast1.0074

0.051[unit : m]

Fig. 4 Railway roadbed model prepared in DEM
Table 1 Input parameters for DEM simulations
Number of particle n
Density of particle ρ s (kg/m3)
Spring constant ratio k s/k n
Inter-particle friction angle φ inter (degrees)
Coefficient of local damping αTime step ∆ t (s)73,210
2,700
0.3
60
0.4
8.72E-06

2.2 Construction of numerical roadbed models
Fig. 5 shows construction steps of a numericalroadbed model. First, sphere particles which
represent ballasts were generated in a box (box size:
0.3m * 0.13m * 0.211m) (Step1). Then, the particles
were set in free fall at 1G. The particles were
deposited in a container which had slopes equivalent
to those of roadbeds. Then a rigid plate was
generated above the sphere particles together withthe parallelepiped box which represented a single
sleeper (Step2). The plate and the sleeper box were
simultaneously settled down at 0.1 m/s and it
statically compressed the deposits of sphere particles
until the thickness of deposits became that ofroadbed shown in Fig. 4(Step 3). The density of theballast beds 1,600 kg/m3 were achieved. Finally, theplate and the container were removed from the scene
and only ballasts and the sleeper remained (Step4).

(2)Here, E 1 and E 2 are Young’s modulus of particle 1
and particle 2 which are in contact to each other. In
the same way, r 1 and r 2 are the radius of the particle
1 and particle 2．
5) Spring constant ratio k s / k n
Ratio of spring constant in the tangential
direction to that in the normal direction k s / k n , 0.3
was used [3].
6) Inter-particle friction angle φ interInter-particle friction angle, φ inter , 60 degrees wasused.
7) Coefficient of local damping α
The local damping is damping forces acting on
the particles with proportion to the resultant forces.
In this analysis, the local damping coefficient 0.4
was used.
8) Time step ∆ tTime step 8.72e-6 seconds was used in this study.

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GEOMATE-Nagoya, Nov.13-15, 2013

Table. 2 Tilting angles and the horizontal seismic
coefficients adopted in DEM simulations

Step 1α (degree)

case
1
2
3
4

Step 2

3. DEM SIMUALTION RESULTS
3.1 Effects of Tilting Angles on the Lateral
ResistanceFig. 7 shows the relationship between thehorizontal displacement of the sleeper and thehorizontal load acting on the sleeper, obtained fromeach DEM simulation. It is seen in the figure that thehorizontal load rapidly increases just after the startof loading and become almost constant after itreaches the maximum. It is also seen in the figurethat the lateral resistance of the sleeper with thetilting angle α of 10 or 15 is significantly lower thanthat with the angle α of 0 or 5.
Fig. 8 shows the relationship between the lateralresistance R and the tilting angle α obtained fromthe results shown in Fig. 7. The lateral resistance R
measured at the horizontal displacements d h of 0.4mm and 10 mm are shown in the figure. It is seen in
the figure that the lateral resistance R measured at 10mm reduces with increase of α more significantly
than that measured at 0.4 mm.

Step 3

Step 4

Fig. 5 Construction steps of a numerical roadbed
model

Horizontal load R (kN)

2.3 Inertia Force and Horizontal Loading
To apply seismic inertia force to the roadbed in
the DEM simulation, pseudo static method
simulating tilt tests as shown in Fig. 6 wasintroduced. The situation was made so that thenumerical model grounds were tilted with the angle
α in the scene. That is, the predetermined horizontal
acceleration G h was given to the railroad while atthe same time the vertical acceleration G v was
reduced from 1G to the 1G * cosθ. Particles weremoved by the application of the inertia force,
however they gradually settled with time. After the
movement became stable, the sleeper was displaced
horizontally at a constant displacement rate 0.7mm/s
until the horizontal displacement reached 10 mm.
The roadbed constructions and the horizontal
loadings were conducted four times with changing
the tilting angles α from 0 to 15 degrees. The
relationships between the tilting angle α andhorizontal seismic coefficient k h are shown in Table.
2.

0.025

α= 0

0.020

α= 5
0.015

α = 100.010

α = 15

0.005
0.000

0

1

2

3

4

5

6

7

8

9

Horizontal displacement dh (mm)10Lateral resistance R (kN)

Fig. 7 Relationships between d h and R

gsinα
Pulling

Kh
0.00000
0.08749
0.17633
0.26795

0
5
10
15

gcosα
g

α (degrees)Fig. 6 Pseudo static method

0.025
0.020
0.015
0.010
0.005
0.000

Horizontal displacement (mm)
0.4
10

0

5

10

Tilting angle α (degree)

15

Fig. 8 Relationships between R and α

225

GEOMATE-Nagoya, Nov.13-15, 2013

0.025

2

3

4

5

6

7

8

9

Horizontal load R (kN)Horizontal load R (kN)

10

Horizontal load R (kN)

Total

0.015
Side

0.005

Bottom
Edge

0.000

0

1

2

3

4

5

6

7

8

9

2

3

4

Edge
5 6

7

8

9

10

α = 15

0.020
Total
0.015
0.010

Side

0.005

Bottom
0

1

2

3

4

Edge
5

6

7

8

9

10

100
90
80
70
60
50
40
30
20
10
0

bottom
side
edge

0

5

10

Tilting Angle α (degree)15

3.3 Particles’ movement
Fig. 11 shows the particles’ trajectory induced bytilting, that is, application of inertia force.
Significant particles’ movement was observed when
the tilting angle α becomes 10 or 15 degrees. In
these cases, several particles in the slope could not
keep their original positions and dropped down theslope. Deposits of fallen particles can be found near
the toe of slope.
Fig. 12 represents the particles’ trajectory
induced by horizontal loading of sleepers. Againsignificant movement can be observed in theparticles along the slope, irrespective of tilting
angles. The slope angles become gentler by theapplication of horizontal loadings. It is also found in
the figures that the slope shoulders cannot keep the

α= 5

0.010

1

Fig. 10 Contribution ratio of each load at the time of
10mm displacement(a) α = 0

0.020

0

(d) α = 15
Fig. 9 Bottom, Side, Edge resistance of sleeper

Horizontal displacement dh (mm)0.025

BottomHorizontal displacement dh (mm)Bottom
1

0.005

0.000

Side

0

Side

0.010

0.025

Edge
0.000

0.015

(c) α = 10

0.015

0.005

Total

Horizontal displacement dh (mm)

0.020

0.010

0.020

0.000

α= 0

Total

α = 100.025

Contribution ratio of each load Rr (%)

Horizontal load R (kN)

3.2 Contributions of Bottom Resistance, Side
Resistance and End Resistance
Lateral resistance of sleeper is usually induced by
the friction resistance at the sleeper bottom and thatat the bilateral sleeper sides as well as earth pressure
acting on the sleeper ends. It is worthwhile to see thecontributions of bottom resistance, side resistanceand end resistance to the total resistance to clarify
the development mechanism of lateral resistance.
Fig. 9 shows the bottom resistance, side
resistance and end resistance of the sleeper for eachtilting angle. In the figure, the total lateral resistanceis also shown based on the results shown in Fig. 7. It
is found in the figures that irrespective of tilting
angles, the bottom and the side resistance rapidly
increase just after the start of loading, while the end
resistance gradually increases. This is because theend resistance is mainly induced by the passive earthpressure of ballasts, which require significant
amounts of displacement to be fully mobilized. It isalso seen in the figures that the maximum end
resistance become lower with the increase of tilting
angle.
Fig. 10 shows the ratios of bottom resistance,side resistance and end resistance to the total
resistance when the horizontal displacement of thesleeper was 10mm. It is found that the contributionof the end resistance becomes significantly lower
when the tilting angle α becomes 10 degrees. In
order to investigate the reasons, discussions will bemade based on particles’ movement in the next
section.

10

Horizontal displacement dh (mm)(b) α = 5

226

GEOMATE-Nagoya, Nov.13-15, 2013

original shapes when α becomes 10 or 15 degrees.
The shoulder width was just 10 cm, therefore thesignificant reduction of end resistance can be causedby the collapse of shoulder.
0.5

0.5

α= 0

α= 0
0.4

0.4

0.3

Z-AxisZ-AxisInertia force
Inertia force

0.3
0.2

Lording

0.2

Sleeper

Sleeper
0.1

0.1
0.0
0.0

0.2

0.4

0.6

0.8

1.0

0.0
0.0

1.2

0.2

0.4

0.6

0.8

Y-AxisY-Axis(a) α = 0(a) α = 0

0.5

1.0

1.2

0.5

α= 5

α= 5
0.4

0.4

Z-AxisZ-AxisInertia force
Inertia force

0.3
0.2

0.3

Lording

0.2

Sleeper

Sleeper

0.1
0.0
0.0

0.1

0.2

0.4

0.6

0.8

1.0

0.0
0.0

1.2

Y-Axis

0.2

0.4

0.6

0.8

1.0

1.2

Y-Axis(b) α = 5(b) α = 5

0.5

0.5

α = 10α = 100.4

0.4

Z-AxisZ-AxisInertia force

Inertia force

0.3
0.2

0.3

Lording

0.2

Sleeper

Sleeper

0.1
0.0
0.0

0.1

0.2

0.4

0.6

0.8

1.0

0.0
0.0

1.2

Y-Axis

0.2

0.4

0.6

0.8

1.0

1.2

Y-Axis(c) α = 10(c) α = 10
0.5

0.5

α = 15

α = 150.4

0.4

Z-AxisZ-AxisInertia force

Inertia force

0.3
0.2

0.3

Lording

0.2

Sleeper

Sleeper
0.1

0.1
0.0
0.0

0.2

0.4

0.6

0.8

1.0

0.0
0.0

1.2

0.2

0.4

0.6

0.8

1.0

1.2

Y-AxisY-Axis(d) α = 15
Fig. 12 Particle’s movements induced by horizontal
loadings(d) α = 15
Fig. 11 Particle’s movements induced by tilting227

GEOMATE-Nagoya, Nov.13-15, 2013

4. CONCLUSIONS
Following conclusions can be derived from thisstudy.
1) Lateral resistance of sleepers would decrease
with the increase of horizontal seismic
coefficient.
2) Reduction of lateral resistance appeared
predominantly when the railway roadbed
shoulders collapsed by combined effects of theseismic inertia force and horizontal displacementof sleepers.
3) Significant reduction of end resistance can becaused by the collapse of shoulder.
REFFERENCES[1] Sekine Etsuo, Nakamura Takahisa and Hirao
Hiroki : The Model Test on the Lateral
Resistance of Ballast in the Ballast Track, Japansociety of Civil Engineers 2010 Annual Meeting,2010, pp.473-474 (in Japanese)[2] Vaclav Smilauer : Cohesive Particle Model using
the Discrete Element Method on the Yade
Platform, PhD thesis, 2010[3] Shimizu Hiroyuki, Murata Sumihiko and Ishida
Tsuyoshi : Influence of particle size distribution
and number of particles on the configuration of
the rock mechanical properties in granular
discrete element method，Material, 59(3), 2010,
pp.219-226 (in Japanese)228

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

USE OF ACOUSTIC EMISSION TECHNOLOGY TO STUDY THE
MECHANICAL BEHAVIOUR OF VARIOUS SANDSTONES:GEOTHERMAL ENERGY
Shao, S.S.1, Ranjith, P.G.2 and Chen, B.K.3
1

Department of Civil Engineering, Monash University, Melbourne, Victoria, Australia;
Deep Earth Energy Lab, Bld 60, Monash University, Melbourne, Victoria, Australia;
3
Department of Mechanical & Aerospace Engineering, Monash University, Melbourne, Victoria, Australia
2

ABSTRACTThe mechanical behavior three types of sandstones: Acrogem (Ac), Wondabyne (Wo) and Barrabool (Ba)sandstones subjected to thermal and compressive loadings was investigated. Prior to testing, samples were either
maintained at ambient temperature or thermally-stressed to a pre-determined temperatures of 200, 400 600 or
800 °C. Thermal-stressing was achieved by heating the sample to the target temperature at a constant rate of 5
°C/min, holding the temperature constant for one hour, and then cooled at two different condition: (a) air/slowcooled and (b) water/rapid-cooled. The results indicate that the axial strains of all sandstones were increasing
temperature increasing. Temperature of 400 is considered critical. In general, the strength changes of rapidlycooled strength testing accordant to the changes performed in slow-cooled strength testing. However, AEs
results indicate the rapidly-cooled specimens produced more energy releases in the beginning of loading (lessthan 5 kN) up to 0.27%, 13.49% and 26.49% of the peak strengths of Ac, Wo and Ba at 400 °C, respectively. AE
results show very direct view of the crack propagation development of the heated and cooled treated sandstones
under axial loading.
Keywords: Acoustic emission, rock mechanics, high temperature, quenching
1. INTRODUCTION

used to detect and measure the transient wave that is
generated from these discrete acoustic waves
produced by each micro-crack, which can produce
appropriate event data to interpret the crack
propagation of the material. Although AE canprovide a qualitative gauge of strain energy release,
it is unable to provide quantitative results.

Geothermal resource is now recognized as
renewable on the time-scales of both technologicaland societal systems, with cost, reliability andenvironmental advantage over conventional energy
resource. In the meantime, there is a new challenge
for rock mechanics to deal with rock engineering
problems at high temperatures. Acoustic emissions(AEs) monitoring has been recently used in various
engineering applications for damage characterization,such as micro-crack nucleation and crack
propagation during rock deformation, evaluation of
the failure process, their mechanisms and fracture
locations.

1.2 Identification of stress crack thresholds
According to Hoek and Bienawski[1], crack
propagation process involves several stages. Basedon the stress strain curve of axial and lateral
deformation measurements in uniaxial compression
test, fracture phases of brittle materials mainly
consist of crack closure, crack initiation followed bystable crack propagation, crack damage followed byunstable crack propagation and ultimate failure.
These phases can be identified using various
methods such as axial stiffness and stress-strain
curve, and volumetric stiffness-strain curve [2]-[3].

1.1 AE technology
AE is a non-destructive technique, which detects
elastic waves generated due to crack initiation, crack
formation and crack coalescene. Based on therecorded waves many parameters are calculated andanalysed in order to characterize the distinct failure
mechanisms. Under certain loads, brittle material
releases sudden strain energy when the crackdevelops which creates an elastic stress wave which
travels from the place of origin to the surface. AE is

1.3 The effect of thermal shock influence rockstrength
Thermal stresses are generated when material
experiences temperature gradients e.g. during
229

GEOMATE-Nagoya, Nov.13-15, 2013quenching, and the transient thermal stresses
generated are normally tensile at the surface andcompressive in the centre of the body [4]. For
instance, the shrinkage of a cooled surface of rock is
constrained by the expanded hotter inner regions. In
general, tensile stress is generated in the cooled
surface and the constraint of the surface thermal
strain is caused by the interior of the specimens. The
tensile stress and the constraint of the surface strain
are counterbalanced by compressive stresses in the
inner part of the specimen [5]. The level of tensilestress is highest at the surface and decreases withcrack depth, and the crack growth occurs in the
downward direction after a certain critical quench[6]. Thermal cracks release the constraint of thethermal strains and the thermal stresses. Thermal
cracks often stop before they separate the specimen
into two or more parts. This paper is aimed to study
the effected of high temperatures and cooling or
quenching treatments on various sandstones throughAEs analysis.

2.2 Experimental procedureSpecimens of size 22.5 mm diameters and 45
mm length (shape factor of 2) were prepared.
Thermal-stressing was achieved by heating thesample to the target temperature at a constant rate of
5 °C/min, holding the temperature constant for one
hour, and then cooled at two different rates: (a)air/slow-cooled and (b) water/rapidly-cooled. In
compressive strength tests, core samples were
loaded at a constant displacement rate of 0.1
mm/min. All unconfined compressive tests were
performed at room temperature (23 °C). Duringexperimentation, AE hits were recorded if signals
exceeded the set threshold of 60 dB. The amplitude
and absolute energy of each AE signal were
provided by the AEwin software.

2. MATERIAL PROPERTIESThe tested sandstones were collected from twosources. Acrogem sandstone (Ac) is from Perthbasin, Wondabyne sandstone (Wo) is from Sydneybasin, Barrabool sandstone (Ba) is from Barraboolbasin. Ac sandstone is buff veined and white incolour, with medium- to fine-grained composing
predominantly of quartz 58%, feldspar 24% and clay
11%. The quartz exhibits a recrystallised character
resulting in fusion between the majority of adjacentgrains. Wo sandstone is in grey-buff colour, withmedium-grained comprising about quartz 60%,
matrix 30%, clay and cement (composed of calcite,
quartz and siderite) 10%. It is grey when quarriedand oxidises to pale buff after extended exposure to
the atmosphere. Ba sandstone is highly weathered
and collected from open surface. It is green-brown incolour, with medium - to fine-grained comprisingquartz, feldspar, calcite, chlorite and a variety ofaccessory minerals. Their mechanical properties atroom temperature without pre-heated thoughunconfined compression test are listed in Table 1.
Ac sandstone has the highest peak strength andelastic modulus, as well as axial failure strain
compared to Wo and Ba sandstones.

(a)Experimental set-up overview(b)

AE sensors

Fig. 1This is the experimental setup

This is AE schematic diagram

Table 1 Mechanical property of sandstones

SpecimenPeakstrength
(MPa)

Axial
strain(%)

Elastic
modulus
(GPa)

Ac

66.85

1.439

7.52

Fig. 2

Wo

39.21

0.970

6.53

Ba

52.40

0.659

3.94

3. EXPERIMENTAL RESULTS ANDDISCUSSION

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GEOMATE-Nagoya, Nov.13-15, 2013

The effects of cooling treatments on themechanical behaviour of various sandstones werestudies by conducting compressive tests on
specimens which had been either slow-cooled (aircooled) or rapidly-cooled (water cooled) at
consistent compressive loading rates. AE eventswere analysed to determine crack formation due tocombination thermo-mechanical loadings.

slowandrapidly-cooledfromdifferent
temperatures. Figure 3 presents the comparison ofpeak strength, elastic modulus and failure strain of
the three types of sandstone.
The images in Table 2 have shown that all three
types of sandstone turned into reddish colour andrapidly-cooled specimens have generally turned
darker. This is due to rock oxidation under highTable 3 Images of specimens after slow- and rapidly-cooled treatment
Slow
Rapid
Ac sandstone

Slow
Rapid
Wo sandstone

Slow
Rapid
Ba sandstone

200 °C

400 °C

600 °C

800 °C

Fig. 3This is the mechanical characteristic changes after various heated and cooled treatment
temperature and direct exposed in atmosphere. Ba
sandstone is relatively highly weather amount the
specimens, therefore it presents the darkest colour
after heat treated. The dark sparkles on some of thespecimens are the burned mark when it contracted

3.1 Effects of pre-heat and cooling on mechanicalcharacteristic of sandstones
Table 3 displays the images of specimens after231

GEOMATE-Nagoya, Nov.13-15, 2013

with pincher.
All three types of granite retain well integrity up
to 800 °C heat treatment followed by both slow- andrapidly-cooled. In general, Ac sandstone showed thehighest rock strength followed by Ba and then Wo,
as shown in Fig. 3. Quenching from temperatures
below 400 °C, the peak strength of Ba sandstonesudden drop from 200 °C while Ac and Wosandstones remain relatively constant. Quenchingfrom temperatures above 400 °C causes the peakstrengths of Ac and Ba sandstones increase while

increase when quenched from temperatures above
400 °C.
In general, the most distinct effect is thatquenching from higher temperatures results inhigher axial failure strain regardless of the speed ofquench. However this result cannot present thedistinct of slow- and rapidly-cooled effect. Therefore
AE result has been used to interpret the thermal
cracks development within the specimen at various
cooling histories.

Fig. 4This is the axial strength and AE event counts of Ac sandstoneFig. 5This is the axial strength and AE event counts of Wo sandstone

Wo sandstone decrease. Both slow- and rapidlycooled results showed similar trends. The elastic
modulus of Ac sandstone behaved quite differently
when quenched from temperature above 400 °C withAc decreasing slightly, Wo decreasing dramaticallyand Ba increasing moderately. A similar pattern was
found with the peak strength when quenched fromtemperature above 400 °C. However, these changes
are in accord with the steep axial failure strain

3.2 Effects of cooling on fracture initiation
Figures 4, 5 and 6 present the different AE event
counts after specimens were quenched from various
temperature changes. Crack propagation can be
identified from the relationship between AE event
count and axial stress. Three stages of crack
propagation are proposed from previous works:
crack closure, crack initiation and crack damage.
232

GEOMATE-Nagoya, Nov.13-15, 2013

Crack closure initially occurs in the pre-existing
crack when sandstone specimens were subjected tothe axial stress. Stress-strain response during crackclosure is non-linear. However, the extent of thisnon-linear region is small and most of the cracks areclosed when a small load is applied, and this nonlinear region is determined by the initial crack
density and the geometrical characteristics of thecrack population. Results in Figs 4, 5 and 6, that
rapidly-cooled specimens released more energy andgenerated numbers of AE event counts were record
simultaneity with larger axial strain development for
all specimens for all quenching temperatures except
Ac sandstone at 800 °C. AE results indicate therapidly-cooled specimens produced more energy

Fig. 6individual minerals decreases, which leads to anincrease in their mutual attraction and the strength of
the bonds increases. Therefore, Ac sandstone
produce less AE event counts after water quenchedfrom 800 °C may due to the volume expansion andcrack closure.
Following crack closure, linear elastic
deformation occurs when the majority of preexisting cracks have closed, which is the stable crack
region. The elastic modulus can be determined in thestable crack region. This region is between crackclosure and crack damage. By increasing thetemperature from which the specimen is quenched,crack initiation region is shortened by the earlier
crack damage occurred. These stable crack regions

This is the axial strength and AE event counts of Ba sandstone

releases in the beginning of loading (less than 5 kN)
up to 0.27%, 13.49% and 26.49% of the peakstrengths of Ac, Wo and Ba at 400 °C, respectively.
Besides the natural micro-cracks, pre-exist
cracks also include cracks caused by tensile stressand thermal cracks which are generated during therock heating process. When temperature increases,
the crystal particles of rock fractures forming new
microscopic cracks (pre-existing grain boundaries)
between mineral grains, as a result of differential
thermal expansion between grains with different
thermo-elastic modulus and thermal conductivities[7]-[9]. Especially it occurs in crystalline rock, since
the amount of quartz has a significant effect onthermally-induced micro-cracks because of thecomplexity of its thermal expansivity.
These thermal cracks were which developed dueto thermal shock during the cooling process, as therock specimens had cooled surface which isconstrained by the expanded hotter centre region.
For Ac sandstone at 800 °C, from the study of
Dmitriyev et al. [7] it is known that due to volume
expansion, the distance between the interfaces of theof rapidly-cooled specimens are generally shorter
than slow-cooled specimens.
As the crack grows, the fracture process involves
unstable crack propagation and as so termed crack
damage. In contrast to crack closure and crack
initiation, rapidly-cooled specimens have greater
region of unstable crack propagation untill failure
occurs.
Overall, AE results showed very direct view of
the crack propagation development of the heated andcooled treated sandstones under axial loading.
Rapid-cooled specimens produced more AE event
signals in each crack propagation stages at all
appointed temperatures. Specimens have beenheated above 400 °C generates dramatically greater
amount of energy release. This result is consistent
with the changes in strength and axial strain.
4. CONCLUSION
The results show increasing axial strains in all
sandstones with increasing temperature from which
the specimen is quenched. However, the changes for233

GEOMATE-Nagoya, Nov.13-15, 2013

peak strength and elastic modulus are inconsistent
with the axial strains and it is difficult to draw firm
conclusions. It was noticed in slow-cooled residual
strength testing, Ac, Wo and Mw sandstones wererapidly strengthened from quench temperature of
200 to 400 °C however the axial strength of Ac
sandstone gently increased up to 800 °C, while Wosandstones decreased. Contrast to these threesandstones, Ba sandstone was sharply weakened
from 200 to 400 °C and followed gentle increasing
up to 800 °C. In general, changes in strength of
rapidly-cooled specimens were consistent with thoseof from slow-cooled specimens. Quenching fromtemperature of 400 °C appears to be a criticaltransition temperature.
AE results show very direct view of the crack
propagation development of the heated and cooled
treated sandstones under axial loading. Rapid-cooled
specimens produce more AE event signals in all
three crack propagation stages (crack closure, crack
initiation and crack damage) at all appointed
temperatures. Specimens have been heated above
critical temperature of 400 °C showed dramaticallygreater amount of energy release. Therefore, bothfrom strength changes and AE results showed thetemperature of 400 °C is the critical transition
temperature for all three types of sandstones.

International Journal of Rock Mechanics andMining Sciences and, 1967. 4(4): p. 407408,IN13-IN14,409-418,IN15-IN18,419-423.
[3] Eberhardt, E., Stead, D., Stimpson, B., Read, R.
S., Identifying crack initiation and propagationthresholds
inbrittlerock.
Canadian
Geotechnical Journal, 1998. 35(2): p. 222-233.
[4] Collin, M. and D. Rowcliffe, The morphologyof thermal cracks in brittle materials. Journal of
the European Ceramic Society, 2002. 22(4): p.
435-445.
[5] M. Fellner, P.S., Thermal shcok failure of brittle
materials. Key Engineering Material, 2002. 223:
p. 97-106.
[6] Collin, M. and D. Rowcliffe, Analysis andprediction of thermal shock in brittle materials.
Acta Materialia, 2000. 48(8): p. 1655-1665.
[7] Dmitriyev A. P., K.L.S., Protasov Y. I. &Yamshchikov V. S, Physical properties of rocks
at high temperatures. National Aearonautics andSpace Administration, NASA TechnicalTranslation, 1972. N 72-26286.
[8] Kranz, R.L., Microcracks in rocks: A review.
Tectonophysics, 1983. 100(1-3): p. 449-480.
[9] Heard, H.C. and L. Page, Elastic Moduli,
Thermal Expansion, and Inferred Permeabilityof Two Granites to 350°C and 55 Megapascals.
J. Geophys. Res., 1982. 87(B11): p. 9340-9348.

REFERENCES[1] Hoek, E. and Z.T. Bieniawski, Brittle fracture
propagation in rock under compression.
International Journal of Fracture, 1965. 1(3): p.
137-155.
[2] Bieniawski, Z.T., Mechanism of brittle fractureof rock. Part II-experimental studies.

234

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

UNCONFINED COMPRESSIVE STRENGTH OF CEMENT TREATED
SOIL/RAP MIXTURE
Jirayut Suebsuk1, Aniroot Suksan2, Suksun Horpibulsuk3 and Apichit Kumpala4
Geomechnics and Geomaterials Research Group, Department of Civil Engineering,
Faculty of Engineering and Architecture, Rajamangala University of Technology Isan, Thailand;2, 3School of Civil Engineering, Institute of Engineering, Suranaree Unversity of Technology, Thailand
1, 4

ABSTRACTThe article attempts to present the influence of reclaimed asphalt pavement (RAP) content on the compaction
behavior and unconfined compressive strength of cement treated soil-RAP mixture. The laboratory compaction
and unconfined compression tests on cement treated soil/RAP mixture were carried out with various RAP andcement contents. The porosity was adopted as a state parameter for assessing the strength of the mixed materials.
The results show that with an increase in RAP content, the OMC tends to decrease, up to the optimum ofsoil/RAP ratio of 50/50. The asphalt fixation point is designated as a transitional point where less change instrength turns to a larger change. An asphalt content of 3.5% (50/50 soil/RAP ratio) is found to be the asphalt
fixation point. The strengths, where the asphalt content is lower than the asphalt fixation point, can be predictedby the proposed generalized form of strength. This proposed equation can assess the laboratory strength ofcement treated soil/RAP mixture under various mixed proportions, cement contents, water contents, and curing
times.
Keywords: Reclaimed asphalt pavement, Lateritic soil, Unconfined compressive strength, Cement stabilization

research efforts aimed at exploring novel
stabilization methods to treat soil/RAP mixture
before their use in pavement base or subbase
construction [6]. The cost-effective method forstabilizing pavement material is a cold in-place
mixed with cement. This method is economical andthe engineering properties of materials can becontrolled. The strength and resistance todeformation increase with curing time. The
fundamental mechanical characteristics and someinfluential factors on the strength behavior (e.g.,water content, cement content, curing conditions andcompaction energy) of cement treated soils havebeen investigated extensively (e.g., [7] to [13], andothers).

INTRODUCTION
Reclaimed asphalt pavement (RAP) is defined aspavement materials containing asphalt andaggregates which have been removed and/or
reprocessed [1]. Rehabilitation of asphalt concrete
pavement includes the milling of asphalt concrete
layer, which produces a great amount of RAP. Those
RAP from the rehabilitation of asphalt road are amajor problem for many countries. Fig. 1 shows theon-site RAP heap from the rehabilitation of asphalt
pavement failure caused by flood in the Lopburi
province, Thailand. RAP can be recycled by thefollowing applications: cold in-place recycling, coldplanning, hot recycling, hot in-place recycling, andfull depth reclamation [2]. Although RAP can berecycled directly as a recycled proportion of new hot
mix asphalt concrete, this is generally limited to25% (or less) of the new material according to thestandard. Some RAP remain and alternative methods
for disposal would need to be developed.
When used as a total substitute for natural
aggregates, most RAP materials do not often meetthe minimum base material requirements set forth by
the standard or local state guidelines [3]. The use of
RAP as a granular base is one solution available forthe disposal of RAP solid waste and provides good
application where no suitable materials are available[4]. RAP can be replaced by natural aggregate inpavement base or subbase if mixed with othernatural aggregates [5]. However, the natural soils
mixed with RAP exhibit low strength and collapse
on wetting. These limitations have led to the new

Fig. 1235

On-site RAP heap in the Lopburi province,
Thailand (photo by Jirayut Suebsuk)

GEOMATE-Nagoya, Nov.13-15, 2013

maximum dry density ( γ d ,max ) of compacted lateritic
soil under the modified Proctor are 8% and 21.2
kN/m3, respectively; while the OMC and γ d ,max of

RAP are becoming increasingly popular as
alternative recycled solid waste materials forpavement base applications over the last decade.
Laboratory and field investigation on the use of RAP
material in pavement base and subbase applications
has been conducted by Rutgers University [14].
Other research works on the use of RAP have beenreported in the most recent literature (e.g., [6], [15]to [17]). However, there are no methodologies basedon rational criteria to assess the target strength forpractical use; the conventional technique to design
the mixed proportions of soil/RAP mixture is basedon a trial batch.
This research therefore aims to study the
influence of RAP content on the compaction
behavior as well as to assess the unconfinedcompressive strength and strength development withcuring time of cement treated lateritic soil/RAP
mixture, using porosity as a state parameter.

compacted 100% of RAP under the modified Proctor
are 6.2% and 17.5 kN/m3, respectively. The
modified Proctor energy was performed on theuntreated mixed materials to assess their OMC and
γ d ,max , which are presented in Table 1.
The unconfined compressive tests were
performed on the cylindrical specimens, which werecompacted on the OMC of untreated materials (videTable 1). The lateritic soil, mixed with RAP, wastreated by various contents of Portland cement typeI. The RAP content used in the mix proportions
varied from 0 to 90% by weight of total material,
while the cement content (C) varied from 0 to 5% byweight of solid. After 24 hours of molding, thespecimens were dismantled from the mold, wrappedin vinyl bags, and stored in a humidity chamber witha constant temperature (25 ± 2 °C). Unconfinedcompression tests were conducted on the samples
after 1, 7, 14, 28, and 60 days of curing. The rate ofvertical displacement was constantly kept at 1
mm/min. After finishing the test, the moisture
content of the samples was measured for evaluating
the porosity.
For all mixtures at each curing time andcombination of moisture content and cement
content, at least five samples were tested under thesame condition to check the consistency of the test.
In the most cases, the results under the same testing
condition were reproducible with a low mean
standard deviation, SD (SD/ x <10%), where x is
the mean strength value).

LABORATORY INVESTIGATION
Lateritic Soil
The natural lateritic soil used in this study is alocal problematic soil from the Nakhon-Ratchsima
province, Thailand. It contains high fine particle
content over the maximum criteria according to the
Department of Highways (DOH) standard. It wascollected from a borrowed pit in the NakhonRatchasima province, Thailand, at a depth 2 to 3 m.
The fine particle accounts for the significant
problems on the base course structure, especially theswelling, consolidation and collapse upon drying
and wetting. The grain size distribution of the soil ispresented in Fig. 2. The natural soil is composed of
2% gravel, 53% sand, 25% silt, and 20% clay. The
specific gravity is 2.68. The liquid and plastic limits
are approximately 23% and 5%, respectively. Basedon the Unified Soil Classification System (USCS),
the soil is classified as clayey sand (SC).

100
Lateritic soil
RAP

Percent passing

80

Reclaimed Asphalt Pavement (RAP)
The only source of RAP material was obtained
from the milling of asphalt pavement for resurfacingin the cold in-place recycling (CIR) process in the
Nakhon-Ratchasima province, Thailand. This RAP
contains primarily crushed limestone with 7% ofasphalt content. The in-situ RAP were air-dried andthen passed through a 3/8" sieve for removal ofparticles larger than 10 mm. The grain size
distribution is also presented in Fig. 2. It indicatedthat approximately 100% of RAP was retained on
the No. 200 sieve. The bulk specific gravity is 2.49.

60

40

20

0
100

10

1

0.1

0.01

0.001

0.00

Particle diameter (mm)Fig. 2

The grain size distribution of lateritic soil
and RAP

Table 1 The OMC and maximum dry density ofsoil/RAP mixtures
Soil/RAP ratio
80/20
60/40
50/50
40/60
20/80

Compaction and Unconfined Compression Tests
The compaction of lateritic soil, RAP and mixedmaterials was carried out using a 100-mm standard
mold under modified Proctor energy (ASTM D
1557). The optimum moisture content (OMC) and236

OMC (%)
7.0
6.8
6.4
7.0
8.8

γ d,max (kN/m3)
21.5
21.6
21.9
21.3
19.9

GEOMATE-Nagoya, Nov.13-15, 2013

porosity increases. The increase in the porosity
could be due to the lower specific gravity of RAP
and the compaction behavior of the mixed material.
Fig. 7 shows the comparison of strength
development in cement treated soil/RAP mixture
under various RAP content but with the same
cement content. As the higher asphalt content
increases, the strength is lowered. The presence ofasphalt binder reduces the bonding between RAP
aggregate and soil. The asphalt binder is detrimental
to cement treated soils. The typical strength
development with curing time for cement treatedsoil/RAP mixtures under 20%, 40% and 50% of
RAP content is shown in Figs. 8-10. The strength
development with curing time (days) in a natural
logarithmic scale can be expressed as a linear
variation. The strength ratio plots after normalization
are also shown in these figures. The normalized
relation is presented in Eq. (2).

RESULTS AND DISCUSSIONS
Fig. 3a shows the compaction curve of thelateritic soil and RAP. The various compaction
curves of mixed materials were presented in Fig. 3b
under various soil/RAP ratios. The OMC tends todecrease as the RAP content increases up to the
optimum RAP content, which is 50/50 of soil/RAP
ratios. At this point, it provides a maximum dry
density of 21.9 kN/m3 associated with a moisture
content of 6.4%. The reduction in the maximum dry
density is associated with an increase in the RAP
content, more than the optimum point. The reductionin the maximum dry density (increase in porosity)
could be due to the larger particle size of RAP,
where the soil/RAP mixture leads to a poorly gradedmaterial.
Fig. 4 shows the typical stress-strain
relationships in the unconfined compression tests of
cement treated soil/RAP mixture for different RAP
content but with the same cement content and curing
time. The RAP content in the mixed materials has
played a significant role in the stress-strain-strength
behavior under unconfined compression tests. The
reduction in strength and stiffness of the mixedmaterials are associated with a decrease in dry
density.
Fig. 5 shows the effect of RAP, as represented by
the asphalt binder content AS (%), on the strength inunconfined compression tests of cement treatedsoil/RAP mixture. AS is calculated as follows:
Was
(1)
AS
=
× 100 ,
Ws
where W as is the weight of asphalt binder, and W s is
the weight of soil solid. As the asphalt content
increases, the unconfined compressive strength
significantly decreases. However, when the asphalt
binder content is greater than 3.5% (50/50 ofsoil/RAP ratio), the change in strength is larger. Theasphalt content of 3.5% can be designated as the"asphalt fixation point". The decrease in strength isdue to a reduction in friction between the solid
particles (soil and RAP aggregate), which is causedby the asphalt binder. The asphalt fixation point is atransitional point where less change in strength turns
to a larger change. The reduction in strength isminimal when the asphalt content is lower than theasphalt fixation point; this zone is called the inert
zone. The zone is also called deterioration when theasphalt content is greater than the asphalt fixation
point.
Fig. 6 shows the porosity η of the cement treatedsoil/RAP mixture. The compacted 100% lateritic soil
inherently exhibits 18.5% of porosity. The increaseof asphalt content in the mixed material reduced theporosity. By adding 3.5% of asphalt content, theporosity is reduced by up to about 14%. However,when the asphalt content is greater than 3.5%, the

23
22

(a)

Base soil
RAP

γd (kN/m3)

21
20

Sr =

19
Sr =

18

100
%,
G

s =

2.6

8

80%

17
16
2

4

6

8

23
22

10

12

16

Soil/RAP ratio

(b)

80/20
60/40

21

γd (kN/m3)

14wn (%)

50/50

20

Sr =

19
Sr =

18

40/60
20/80

10010/90
%,
G

s =

2.6

8

80%

17
16
2

4

6

8

10

12

14

16

wn (%)

Fig. 3Compaction curves of the lateritic soil,
RAP, and mixed materials
8000
wi = 1.0 OMC, C = 5%
28 days of curing

Base soil

6000

Stress (kPa)

Soil/RAP (80/20)
Soil/RAP (60/40)
Soil/RAP (50/50)

4000

Soil/RAP (40/60)
Soil/RAP (20/80)

2000

0
0

1

2

3

4

Strain (%)

Fig. 4

237

Stress-strain relationships in unconfinedcompression test of lateritic soil and mixedmaterials

GEOMATE-Nagoya, Nov.13-15, 2013

Unconfined compressive strength, qu (kPa)8000
wi = 1.0 OMC, 28 days of curing
Cement content
C = 1%
C = 3%
C = 5%6000

qu (kPa)

Inert zone

4000

Deterioration zone

2000
Asphalt fixation point

0
0

6

5

4

3

2

1

AS (%)

Relationship between strength and asphalt
content

Soil/RAP ratio (80/20), w = 7.0%, AS = 1.4%

6000

C = 1%
C = 3%
C = 5%

4000

2000

0
1
1.5

2

4

10

20

40

10

10

20

40

10

qD/q28 = 0.248 + 0.225ln( D)qD/q28Fig. 5

8000

1.0 2

r = 0.951

0.5

24

0
1

wi = 1.0 OMC, 28 days of curing

C = 3%

20

Fig. 8C = 5%

18
16

Asphalt fixation point

12
0

1

2

3

4

5

6

AS (%)

10000
Soil/RAP ratio (80/20), w = 7.0%
AS = 1.4%
C = 1%

8000

Soil/RAP ratio (20/80), w = 8.8%
C = 1%
AS = 5.6%

C = 3%

C = 2%

C = 5%

C = 5%

8000
Soil/RAP ratio (60/40), w = 6.8%, AS = 2.8%

6000

C = 1%
C = 3%
C = 5%

4000

2000

0
1
1.5

2

4

10

20

40

10

10

20

40

10

qD/q28 = 0.297 + 0.197 ln( D)

4000

1.0 2

r = 0.969

0.5
0
1

2000

2

4

Curing time (days)
10

20

30

40

50

60

Fig. 970

Curing time (days)

Fig. 7

Strength development in cement treatedsoil/RAP mixture (80/20) and its
normalization

6000

qD/q28Unconfined compressive strength, qu (kPa)

Relationship between porosity and asphalt
content004

Curing time (days)

14

Fig. 6

2

Cement content
C = 1%

Unconfined compressive strength, qu (kPa)

Porosity, η (%)

22

The comparison of strength development incement treated soil/RAP mixture under
different RAP content

Strength development in cement treatedsoil/RAP mixture (60/40) and its
normalization

content for the range of curing time considered. The
soil water/cement ratio and compaction behavior has
play a significant role on the change in porosity of
cement treated soil/RAP mixture. To account thematerial type and the water/cement ratio, thegeneralized relationship of strength ratio has beentake the porosity into the account by the proposed
generalized equation:qD(3)=η a * +b *ln D
q28
where η is the porosity of treated specimens at each
mixture, a* and b* are constant. Based on the test
result of cement treated mixed materials on the inert
zone, the generalization of strength development canqD(2)= a + b ln D ,q28
where q D is the strength after D days of curing, q 28
is the 28-day strength, a and b are constant. From
this investigation, the values of a and b are 0.248
and 0.225 for 80/20 of soil/RAP ratio, 0.297 and
0.197 for 60/40 of soil/RAP ratio, and 0.444 and0.178 for 50/50 of soil/RAP ratio. The normalized
strength development is comparable to that proposedfor cement treated low plasticity and coarse grainedsoils [10]. It is found that these three sets of values
depend on the variation of porosity and cement
238

8000

1.5

Soil/RAP ratio (50/50), w = 6.5%, AS = 3.5%

6000

1.0

C = 1%
C = 3%

0.5
C = 1%

C = 3%

C = 5%

0

4000

2000

2

4

10

20

40

10

0.5
C = 1%

1.0

C = 1%

C = 3%

C = 5%

Soil/RAP ratio (50/50), w = 6.5%, AS = 3.5%

0.5

0.5

C = 1%

4

10

20

40

qDη/(q28)

0

2

C = 5%

Soil/RAP ratio (60/40), w = 6.8%, AS = 2.8%

0.5

1.0

r = 0.966

C = 3%

0

0

1.0 2

0
1

1.0

Soil/RAP ratio (80/20), w = 7.0%, AS = 1.4%

10

Curing time (days)

C = 5%

0.3 qDη/(q28) = 0.046 + 0.028ln( D)2

0.2

R = 0.927

0.1
01

Fig. 10 Strength development in cement treatedsoil/RAP mixture (50/50) and its
normalization

C = 3%

5

10

50

10

Fig. 11 Generalization of strength development incement treated soil/RAP mixture
8000
Predicted strength, qu,predicted (kPa)be illustrated as in Fig. 11. The linear regression
analysis gives a* = 0.028 and b* = 0.046. This
generalization accounts for the effect of thecompaction behavior of different gradation. It isevident that the asphalt content is lower than theasphalt fixation point (3.5%) and valid for the rangeof curing time between 1 to 60 days. For predicting
the strength via the generalization Eq. (3), one
laboratory test value of strength and porosity
measured on the 28 days of curing at the same
compaction energy, same cement content, and same
soil/RAP ratio is needed. Using this generalization,
the strength of cement treated soil/RAP (70/30 ofsoil/RAP ratio) mixture was predicted and comparedwith those of the laboratory test as shown in Fig. 12.
There is some discrepancy between the predicted
and laboratory strengths. However, the error fromthe prediction is acceptable in common engineering
practice.

ed
ict
ed
pr

Soil/RAP ratio (70/30), w = 7.0%

6000

C = 1%
C = 3%=

01
1.5

qD/q28 = 0.444 + 0.178 ln( D)qD/q28Base Soil, w = 8%

C = 5%
Normalisation of Strength (qD/q28)

Unconfined compressive strength, qu (kPa)GEOMATE-Nagoya, Nov.13-15, 2013

q u,

b
la

q u,

C = 5%

4000

2000

0
0

2000

4000

6000

800

Laboratory strength, qu,la b (kPa)

Fig. 12 Comparison between
laboratory strengths

predictedand2) As the asphalt content increases, theunconfined compressive strength decreases
due to a reduction in friction between thesolid particles (soil and RAP), which is
caused by the asphalt binder. The
unconfined compressive strength of mixedmaterials is associated with the variation inporosity. Asphalt fixation point is definedas the limit point of asphalt content that
separates the inert from the deterioration
zones. An asphalt content of 3.5% (50/50 ofsoil/RAP ratio) has become the asphalt
fixation point of this investigation.
3) The target strength of cement treatedsoil/RAP mixture can be predicted by thegeneralized form of strength if and when
the asphalt content is lower than the asphalt
fixation point. This proposed equation canassess the laboratory strength of cement
treated soil/RAP mixture in which the

CONCLUSION
This article presents the unconfined compressive
strength of a problematic lateritic soil mixed with
RAP. The mixed materials were treated by cement toincrease their strength and engineering properties.
The influence of RAP content on the compaction
and strength development with curing time wasstudied using porosity as a state parameter. The
following conclusions can be drawn:
1) The OMC of mixed material is dependent
directly on the mixed proportions. With anincrease in RAP content, the OMC tends todecrease, up to the optimum gradation witha soil/RAP ratio of 50/50.

239

GEOMATE-Nagoya, Nov.13-15, 2013

mixed proportion, cement content, watercontent, and curing time vary.

[8] Consoli, N.C., Prietto, P.D.M., Carraro, J.A.H.,
and Heineck, K.S. (2001). " Behavior ofCompacted Soil-Fly Ash-Carbide Lime
Mixtures" Journal of Geotechnical andGeoenvironmental Engineering, ASCE, Vol.
127, No. 9, pp.774-782.
[9] Consoli, N.C., Foppa, D., Festugato, L. andHeineck, K.S. (2007). "Key parameters forStrength Control of Articially Cemented Soils",
Journal of Geotechnical and Geoenvironmental
Engineering, ASCE, Vol. 133, No. 2, pp.197205.
[10] Horpibulsuk, S., Katkan, W., Sirilerdwattana,W. & Rachan, R. (2006). "Strength
Development in Cement Stabilized Low
Plasticity and Coarse Grained Soils: Laboratory
and Field Study", Soils and Foundations, Vol.
46, No. 3, pp. 351-366.
[11] Horpibulsuk, S., Rachan, R., Chinkulkijniwat,
A., Raksachon, Y., and Suddeepong, A. (2010).
"Analysis of Strength Development in CementStabilized Silty Clay based on Microstructural
Considerations" Construction and Building
Materials, Vol. 24, pp. 2011-2021.
[12] Horpibulsuk, S., Rachan, R. & Suddeepong, A.
(2011). "Assessment of Strength Development
in Blended Cement Admixed Bangkok Clay",
Construction and Building Materials, Vol. 25,
No. 4, pp.1521-1531.
[13] Horpibulsuk, S., Phojan, W., Suddeepong, A.
and Liu, M.D. (2012). "Strength Development
in Blended Cement Admixed Saline Clay",
Applied Clay Science, Vol. 55, pp. 44-52.
[14] Maher, M.H., and Popp, W.Jr., (1997).
"Recycled Asphalt Pavement as Base andSubbase Material" ASTM STP 1275, ASTM,
West Conshohoken, Pa.
[15] Taha, R., Al-Harthy, A., Al-Shamsi, K., and AlZubeidi, M. (2002). "Cement Stabilization of
Reclaimed Asphalt Pavement Aggregate forRoad Bases and Subbases" Journal of Materials
in Civil Engineering, Vol. 14, No. 3, pp.239245.
[16] Puppala, A.J., Hoyos, L.R., and Potturi, A.K.
(2011). "Resilient Moduli Response ofModerately Cement-Treated Reclaimed Asphalt
Pavement Aggregates", Journal of Materials in
Civil Engineering, Vol. 23, No. 7, pp. 990-998.
[17] Puppala, A.J., Saride, S., and Williammee, R.
(2012). "Sustainable Reuse of Limestone
Quarry Fines and RAP in Pavement
Base/Subbase layers", Journal of Materials in
Civil Engineering, Vol. 24, No. 4, pp. 418-429.

ACKNOWLEDGEMENTS
This research was financially supported by the
Rajamangala University of Technology Isan. The
facilities provided by the Department of Civil
Engineering,
Faculty of Engineering andArchitecture,
Rajamangala
UniversityofTechnology are also very much appreciated.

REFERENCES[1] Cosentino, P.J., Kalajian, E.H., Shieh, C.H.,
Mathurin, W.J.K., Gomez, F.A., Cleary, E.D.,
and Treeratrakoon, A. (2003). "Developing
Specifications for Using Recycled Asphalt
Pavement as Base, Subbase or General Fill
Materials,
Phase
II
(Rep.
No.
FL/DOT/RMC/06650-7754)" Florida Instituteof Technology.
[2] Attia, M.I.E, (2010). "Characterization of theStructural Behavior of Reclaimed Asphalt
Pavement as pavement base layer", Doctoral
dissertations, North Dakota State University ofAgriculture and applied science.
[3] Rana, A.S.M.A. (2004). “Evaluation of recycledmaterial performance in highway applications
and optimization of their use” Ph.D.
dissertation, Texas Tech Univ., Lubbock, TX.
[4] Papp, W.J., Maher, M.H., Bennert, T.A., andGucunski, N. (1998). "Behavior of Construction
and Demolition Debris in Base and Subbase
Applications", ASCE Recycled Materials in
GeotechnicalApplications,GeotechnicalSpeacial Publication No. 79, pp. 122-136.
[5] Taha, R., Ali, A., Basma, A., and Al-Turk, O.
(1999). "Evaluation of reclaimed asphalt
pavement aggregate in road bases and subbases"
Transportation
Research
Record1652,
Washington, DC, pp. 264-269.
[6] Hoyos, L.R., Puppala, A.J., and Ordonez, C.A.
(2011). "Characterization of Cement-FiberTreated
Reclaimed
Asphalt
Pavement
Aggregate: Preliminary Investigation", Journalof Material in Civil Engineering, ASCE, Vol.
23, No.7, pp. 977-989.
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(2000). “The influence of curing under stress on
the triaxial response of cemented soils”
Geotechnique, Vol. 50, No. 1, pp. 99-105.

240

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INVESTIGATION OF STRESS REDUCTION EFFECTON STRUCTURE DUE TO BASEMAT UPLIFTUSING ENERGY CONCEPT
Takafumi Inoue1 and Atsushi Mikami2
Department of Civil & Environmental Engineering, The University of Tokushima, Japan2
Department of Civil & Environmental Engineering, The University of Tokushima, Japan
1

ABSTRACT
In order to verify seismic performance of a structure, it is necessary to evaluate the effect of dynamic soilstructure interaction appropriately. One of the reliable models that can account for basemat uplift as well as soil
yielding is the macro-element model for shallow foundations. This paper studies stress reduction effects induced
in structures (such as bridge piers) due to basemat uplift and soil yielding by the use of a macro-element model
for foundations placed on sands. A superstructure is modeled by a lumped mass and Bernoulli-Euler beam. A
foundation-soil system is modeled as four cases; (1) fixed base, (2) elastic soil, (3) elastic soil with basemat
uplift and (4) elasto-plastic soil with basemat uplift. Time histories that have different frequency characteristics
are considered as input motions to the models. Comparisons of responses of the models show remarkablereduction of section force due to basemat uplift and soil yielding. The degree of base shear reduction differs
depending on the input motions. Therefore, it may be concluded that the degree of base shear reduction depends
on the frequency characteristics of the input motions relative to the system. Regarding the case that degree ofstress reduction effect is the largest, energy balance for the system are estimated. In this case, the input energy
imparted to the structure by an earthquake tends to be smaller by the effect of basemat uplift.
Keywords: Bridge Pier, Stress Reduction Effect, Basemat Uplift, Macro-element, Energy

INTRODUCTION

springs and assumed that the spring doesn’t resist
tensile force to take the effect of uplift into account.
Authors have studied the reduction effect of asection force induced in the structure due tobasemat uplift and soil yielding by the use of amacro-element model and showed that the degreeof base shear reduction depends on the frequency
characteristics of the input motions relative to thesystem [4].
This paper studies the reduction effect of asection force induced in the structure due tobasemat uplift and soil yielding by the use of amacro-element model. In addition, the energybalance for the structure is estimated. A foundationsoil system is modeled as four cases; (1) fixed base,(2) elastic soil, (3) elastic soil with basemat upliftand (4) elasto-plastic soil with basemat uplift. Timehistories which have different frequency
characteristics are considered as input motions in
the model.

As the design method shifts to performancebased design, it becomes more important toaccurately estimate the response of superstructureaccompanied by foundation rotation and basemat
uplift. Basemat uplift is reportedly induced even by
weak to medium ground motions [1], hence, it isnecessary to incorporate the effect of basemat uplift
into a design code.
Hayashi [2] assessed slightly damaged buildings
standing on the most severely damaged area during
the 1995 Hyogoken-Nanbu Earthquake. By using
numerical simulation, he has studied damage
reduction effect due to basemat uplift of buildings
which were subject to strong ground motions, andshowed that the damage reduction effect sometimes
becomes remarkable depending on structuralparameters and input motions. The finite element
model was used in his analysis treating soil as alinear or equivalent linear medium.
Iwashita et al. [3] have examined the effect of
uplift at pile head on structural response. They havediscussed the input energy imparted to the structureby an earthquake. They have treated the ground as

MACRO-ELEMENT MODEL
In this study, a macro-element model developed
by Nakatani et al. [5] is employed to study stress
reduction effect of structures due to basemat uplift
241

GEOMATE-Nagoya, Nov.13-15, 2013uand sand soil yielding. A brief overview is
described in this section. Details can be referred toin Shirato et al. [6].

V

Relationship between displacements and loads ofa macro-element modelx  v u θ TF  V

Fig. 1 Definition of displacements and loads
for the macro-element model
the uplift initiates. Then v up  M relationship isexpressed by(9)v up  0 M  M  (1)v up  M T(2)
where the superscript T stands for transposition.
The
relationshipbetweenincremental
displacements and loads is expressed byHdF  D  D
el

up

up

D


B
4
4



 1 M  M  

2


2
3

M
M


3

M
M






(10)
Plastic compliance
In order to determine plastic compliance,
bearing capacity surface is used. A schematic
diagram of this is shown in Fig. 2. Shirato et al. [6]assumed following expression for bearing capacity
surface.
2
(11)f cr  h 2  m2   2 1     0
where   V / Vm , h  H / Vm  , m  M / BVm  and
V is bearing capacity in terms of centered verticalloading. Parameters  and  are tangents at theorigin on the V  H , V  M planes, respectively. To
describe plastic deformations, a yield function isdefined based on Nova and Montrasio [8] asfollows:2
(12)
f y  h 2  m2   2 1   / c   0

 dx

pl 1

(3)
where D , D and D are elastic compliance,
uplift compliance and plastic compliance,
respectively.
el

θ

H

v

In the macro-element model, the foundation isassumed to be rigid, and foundation-soil model
which is subjected to combined loads is modeled as
one element. Displacements and loads at the centerof the footing are defined as shown in Fig. 1 andthe following equations.

M

plElastic compliancem

In order to determine elastic compliance,
equivalent elastic spring coefficients corresponding
to the vertical, translational, and rocking
component are used based on Gazetas [7]. The
coefficients for a rectangular foundation are
expressed by
4.54GB / 2
1 
9GB / 2
Kh 
2 

Kv 

3.6GB / 2
1 

(4)

where  c is the hidden parameter that specifies
instantaneous size of the yield surface andtranslates instantaneous combined loads into thenorm of an equivalent vertical force. In order torelate size of the yield surface and incremental
displacements, the hardening rule and flow rule are
required. As for the hardening rule, isotropic
hardening, which defines similar bearing capacity
surface and yield surface, is assumed. The
hardening function is expressed by

(5)

3

Kr 

(6)

where G and  are shear modulus andPoisson’s ratio of the underlying soil and B is thefooting length. Frequency dependence of thecoefficients is ignored.
Uplift compliance

H

Uplift compliance is determined based on thefollowing model for uplift.  up  M relationship isexpressed by up  0 M  M  
(7)

4
M 



 0 M  M  2
 3  M M   M   up  

M/B

(8)

V

where M  and  are moments that are
influenced by soil plasticity and rotation at which

Fig. 2 Schematic of bearing capacity surface

0242

GEOMATE-Nagoya, Nov.13-15, 2013

 R0 vc  Vm 

 c  1  exp (13)

ms J swhere R is initial gradient of the V  v pl curve.
vc is expressed by
2
2
2 0.5
(14)
vc  v pl    M u pl    M B pl  
0h EA I η

where  M and  M are non-dimensionalparameters that incorporate the contribution ofhorizontal displacement and rotation into hardening.
As for the flow rule, a non-associated flow rule isadopted. Regarding such a non-associated flow rule,a plastic potential function is defined as follows:2
(15)g  2 h 2   2 m2   2 1   /  g   0

Fig. 3 Schematic of structure-foundation-soil
systemwhere     ，     ,  and  areparameters that specify the shape of the plastic
potential surface.

Table 1 Parameters of structure-foundation-soil
systemg

g

g

B mf J f

Vs Vp ρK v K h K r Cv Ch Cr
Vm μ ψ ζ λ χ R 0 α M γ M

g

STRESS REDUCTION AGAINST A REAL
EARTHQUAKE
Here, stress reduction effects of a structurefoundation-soil system against real earthquakes isreviewed. The system was subjected to different
types of acceleration-time histories. A foundationsoil system is modeled as four cases; (1) fixed base,(2) elastic soil, (3) elastic soil with basemat upliftand (4) elasto-plastic soil with basemat uplift.

Parameter

Unit

Lumped mass mst

Moment of inertia of the structure J stmHeight h

m

Value
500
2

4167
10
2

Young modulus E

kN / mSection area A

m

2

4.423

m

4

1.557

Second moment of area I
Damping coefficient of the structure η

Structure-foundation-soil system
Schematic and parameters of the structurefoundation-soil system is shown in Fig. 3 and Table
1. A superstructure was modeled by a lumped mass
and Bernoulli-Euler beam. The total degrees of
freedom of the system were six; consisting of threedegrees of lumped mass and three degrees of themacro-element. A foundation-soil system ismodeled as four cases; (1) fixed base, (2) elastic
soil, (3) elastic soil with basemat uplift and (4)elasto-plastic soil with basemat uplift. The damping
coefficient of the beam element was assumed to be
proportional to the element stiffness matrix and 5%of the damping coefficient was taken into account.
Frequency dependence of elastic compliances ofthe macro-element was ignored. Damping
coefficients of the macro-element corresponding to
the vertical, translational, and rocking component
were set based on Gazetas [7]. The parameters ofyield function, plastic potential and hardening
function were set based on Nova and Montrasio [8]and Nakatani et al. [5].

24500000

0.05

Footing length B

m

Mass of the foundation m ftMoment of inertia of the foundation J f

tm

2

833

Shear wave velocity Vs

m/ s

230

10
100

Lysmer’s analog wave velocity VLa

m/ s

356

Ground density ρt / m3

1.603

Vertical elastic spring coefficient K v

kN / m2750000

Translational elastic spring coefficient K h

kN / m

2240000

Rocking elastic spring coefficient K r

kN  m / rad 54500000

Vertical damping coefficient Cv

kNs / mTranslational damping coefficient Ch

kNs / m36900

Rocking damping coefficient Cr

kNsm

99800

Bearing capacity of centered Vm
vertical loading

kN

96100

52500

Parameter of yield functon μ

0.9Parameter of yield functon ψ

0.48

Parameter of yield functon 

0.95

Parameter of plastic potential

λParameter of plastic potentialχParameter of hardening function

0.45
0.45

R0

48946

Parameter of hardening function αM

2.8

γM

1.7

Parameter of hardening function

The degree of stress reduction effects of astructure was studied. The aforementioned
structure-foundation-soil system is subjected to
input motions in the time domain. Two kinds ofground motions are considered as the input motions

Stress reduction against a real earthquake243

GEOMATE-Nagoya, Nov.13-15, 2013

200

Acceleration (gal)here; subduction type earthquake (acceleration time
history that was recorded at a port in Hachinohe
during the 1968 Tokachi-Oki Earthquake) andinland type earthquake (acceleration time history
observed at JR Takatori station during the 1995
Hyogoken-Nanbu Earthquake). These time histories
are shown in Fig. 4 and 5. For conducting nonlinear
analysis with the macro-element model, time stepfor seismic response analysis was set at 0.0001
seconds by interpolating the input time histories
which were originally recorded at 0.02 second
intervals. A linear acceleration method was used forthe numerical integration.
The time history of base shear that occurred in the
structure for subduction zone type earthquake isshown in Fig. 6. The thin black dot-line, the thinblue line, the thick red dot-line and the thick green
line correspond to responses for fixed base case,elastic soil case, elastic soil with basemat upliftcase and elasto-plastic soil with basemat uplift case,respectively. The case (1) show different time
responses from other cases (this difference implies
the wave radiation effect). However, linear case andnonlinear cases show similar time responses. Thismeans that significant stress reduction effect due tobasemat uplift and soil yielding are not apparent inthis case.
Secondly, an inland type earthquake isconsidered as input motion into the system.
Calculated responses are shown in Fig. 7. Meaningsof curves are the same as Fig. 6. Responses show
significantly different waveforms. The fixed basecase and elastic soil case show similar time
responses (this difference implies the wave
radiation effect). However, when basemat uplift isconsidered, the base shear becomes significantly
different from linear cases. Nonlinear cases show
drastic reduction of base shear, thus longer period
motions are implied. When soil yielding is
considered, the period of the motion becomes evenlonger.
We can recognize from these results that stress
reduction of structures due to basemat uplift andsoil yielding can occur in some cases depending on
input ground motions. In order to examine factorsthat might bring a differences in the level of stress
reduction, some artificial input motions that havedifferent frequency characteristics are considered in
the next section.

100
0
-100
-200
0

10

20

30

40

50

Time (sec)Fig. 4 Acceleration time history
Acceleration (gal)

600
400
200
0
-200
-400
-600
0

10

20
Time (sec)30

40

Fig. 5 Acceleration time history

Base Shear (kN)

4000

Case (1)Case (3)Case (2)Case (4)

2000
0
-2000
-4000
15

20
Time (sec)25

Fig. 7 Base shear time history
15000

Base Shear (kN)

10000

Case (1)Case (3)Case (2)Case (4)

5000
0
-5000

-10000-1500051015Time (sec)Fig. 7 Base shear time history
The same structure-foundation-soil system isconsidered. As the input motion, harmonic waves
that have different frequency characteristics are
given. An example of the harmonic seismic wave
which has a natural frequency of 1.989Hz is shownin Fig. 8. The amplitude gradually increases until itreaches to the amplitude of 500gal. As the former
section, foundation-soil system is modeled as fourcases; (1) fixed base, (2) elastic soil, (3) elastic soil
with basemat uplift and (4) elasto-plastic soil withbasemat uplift. Three cases of different excitation
frequencies are considered: (a) excitation frequency
fe is lower than the natural frequency of the elastic
soil system fn (fe/fn=0.9) (b) excitation frequency
is the and same as the natural frequency of theelastic soil system (fe/fn=1.0) (c) excitation
frequency is higher than the natural frequency ofthe elastic soil system (fe/fn=1.1). The natural
frequency of the elastic soil system is 1.989(Hz).
Stress reduction for case (a)STRESS REDUCTION OF STRUCTURE FORINPUTMOTIONSOF
DIFFERENTFREQUENCY CHARACTERISTICS

The time history of base shear induced in the
structure is shown in Fig. 9. The meanings of the244

GEOMATE-Nagoya, Nov.13-15, 2013

curves are the same as before. The base shear
responses of fixed base and elastic soil model arelarger than nonlinear cases. When basemat uplifteffect is incorporated in the model, the base shear
reduced significantly. Any clear difference can not
be seen by the soil yielding effect.

reason, base shear of the fixed base model is largest.
Owing to radiation damping effect, base shear of
the elastic soil model reduced significantly.
Furthermore, basemat uplift effect works todrastically reduce the base shear of the structure inthis case.

Stress reduction for case (b)INVESTIGATION OF STRESS REDUCTION
EFFECT USING ENERGY CONCEPT

Calculated responses are shown in Fig. 10. In
this case, the base shear of the elastic soil model
becomes much larger than others. This is because
the elastic soil system reached resonance withexcitation frequency becomes system frequency.
Compared to the elastic soil case, base shear of themodels that incorporated basemat uplift effectreduced significantly.

Regarding case (c) that degree of stress
reduction effect was the largest in the preceding
chapter, energy balance for the system are
estimated. The various energy terms can be definedby integrating the equation of motion of the system.
If a macro-element model developed by Nakatani etal. [5] is employed, the equation of motion of thesystem is expressed byM u Cu K u F  P
(16)
where M  is the mass matrix, C  is thedamping matrix, K  is the stiffnessmatrix for thepier, F  is the soil reaction force matrix frommacro-element, and P is the external force matrix.
Hence, the various energy terms can be expressed
by
t
t
t
t
t
T
T
T
T
T
0 u M udt  0 u C udt  0 u K udt  0 u Fdt  0 u Pdt(17)
The right side of this equation is the energy
input to the system. The first term on the left side ofthis equation is the kinetic energy of the systemassociated with its motion relative to the ground.
The second term on the left side of this equation isthe energy dissipated by viscous damping. The
third term on the left side of this equation is thepotential energy of the structure. The fourth term on
the left side of this equation is the potential energyof the soil. The time histories of energy for thesystems are shown in Fig. 12. In this case, the input
energy imparted to the structure by an earthquake
tends to be smaller by the effect of basemat uplift.

Stress reduction for case (c)Acceleration (gal)The result is shown in Fig. 11. In this case,
excitation frequency is higher than the elastic soil
system and closer to the fixed base model. For this
500

0

-500
0

10

20

30

Time (sec)Fig. 8 Acceleration time history
Base Shear (kN)

20000

Case (1)Case (2)Case (3)Case (4)10000
0-10000-20000051015Time (sec)

20

25

30

Fig. 9 Base shear time history (Case (a))
Base Shear (kN)

50000

Case (1)Case (2)Case (3)Case (4)0CONCLUSIONS-50000051015Time (sec)

20

25

30

This study examined stress reduction effects
induced in a structure due to basemat uplift and soil
yielding by the use of a macro-element model forfoundations placed on sands. The foundation-soil
system is modeled as four cases; (1) fixed base, (2)elastic soil, (3) elastic soil with basemat uplift and(4) elasto-plastic soil with basemat uplift. Timehistories with different frequency characteristics
were considered as input motions to the models.
Comparisons of responses for the models showed

Fig. 10 Base shear time history (Case (b))
50000

Base Shear (kN)

Case (1)Case (2)Case (3)Case (4)0-50000051015Time (sec)

20

25

30

Fig. 11 Base shear time history (Case (c))
245

GEOMATE-Nagoya, Nov.13-15, 2013

REFERENCES

input energy
kinetic energy
potential energy of the structure
potential energy of the soil
damping energy of the structureradiation damping energy
106

fixed base case

105
10

4

103
102
101
100

0

106
10

10

20

30

20

30

20

30

20

30

elastic soil case5104

Energy (tm 2 / s 2 )

103
102

Time (sec)

101
100

0

106
10

10

elastic soil with basemat uplift case

5

104
103
102
101
100

10

6

10

5

Time (sec)010elasto-plastic soil with basemat uplift case

104
103
102

Time (sec)

101
100

0

10

Time (sec)Fig. 12 Energy time history (Case (c))
remarkable reduction of section force due tobasemat uplift and soil yielding. Therefore, it may
be concluded that the degree of base shear
reduction depends on the frequency characteristicsof the input motions relative to the system.
Regarding the case that degree of stress reduction
effect was the largest, energy balance for thesystem are estimated. In this case, the input energy
imparted to the structure by an earthquake tends tobe smaller by the effect of basemat uplift.
ACKNOWLEDGEMENTS
Authors acknowledge the Public Works
Research Institute, Tsukuba, Japan, for providing
the analysis program.

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foundations to large earthquakes”, Technical
Memorandum of PWRI, Public Works
Research Institute, (3627), 1999, (in Japanese).
[2] Hayashi Y, “Damage reduction effect due tobasemat uplift of buildings”, Journal of
Structural and Construction Engineering(Transactions of AIJ), 485:53-62, 1996, (inJapanese).
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Approach to the Earthquake Response of
Building Allowing Uplift at Pile Head”
Journal of Structural and Construction
Engineering (Transactions of AIJ), 564:23-30,
2003, (in Japanese).
[4] Inoue T, and Mikami A, “Stress Reduction
Effect of Structure due to Basemat Uplift andSoil Yielding,” In: Proceedings of the 10th
International Conference on Urban Earthquake
Engineering, Tokyo, JAPAN, 2013.
[5] Nakatani S, Shirato M, and Kouno T,“Development of a numerical model for theseismic nonlinear behavior and irreversible
displacement of a shallow foundations” PWRI
Report, Public Works Research Institute,(4101), 2008, (in Japanese).
[6] Shirato M, Paolucci R, Kouno R, Nakatani S,
Fukui J, Nova R, di Prisco C, “Numericalsimulation of model tests of pier-shallow
foundation systems subjected to earthquake
loads using an elasto-uplift-plastic macro
element” Soils and Foundations, 48(5), 693-71,
2008.
[7] Gazetas
G,“Foundation
vibrations”
Foundation Engineering Handbook, Fang HY(ed.), van Nostrand Reinhold: NY, 1991.
[8] Nova R, and Montrasio L, “Settlement ofshallow foundations on sand,” Géotechnique,41(2), 243-256, 1991

246

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SWELLING DEFORMATION OF BENTONITE MIXED WITH
INORGANIC MATERIALS IN ALKALINE SOLUTION
Yuki YOKOYAMA1 and Kenichiro NAKARAI2
Graduate School of Engineering, Gunma University, Japan
2
Graduate School of Engineering, Hiroshima University, Japan
1

ABSTRACTIn the radioactive waste disposal facility, sodium-type bentonite will be used as an artificial barrier material.
It is expected to delay the infiltration of groundwater and fill the crack with the surrounding ground because it
has high swelling performance. However, during the tens of thousands of years, the bentonite can be deteriorated
and dissolved by the components leached from the surrounding cement-based materials. Then, the swelling
performance of the bentonite may be lowered. In this paper, we propose a method to solve this problem by themixing inorganic materials. From the experimental results, it was found that the mixing of small amount of silica
fume or sodium carbonate to bentonite can reduce the deterioration of the bentonite in alkaline water from theviewpoint of swelling performance. But, in the case of the aged specimens 1 year after mixing, the effect of themixing on the degradation of swelling performance of the bentonite tended to be smaller than in the case of theyoung specimens tested just after mixing regardless of the type of admixtures.
Keywords: artificial barrier, bentonite, silica fume, sodium carbonate, swelling deformation
INTRODUCTION
In radioactive waste disposal facilities, sodium
bentonite having high swelling capacity will be used
as an artificial barrier material. It is expected todelay the infiltration of groundwater and to fillcracks of the surrounding host rock. However,during tens of thousands of years, the bentonite canbe deteriorated by the alkaline water with the ionsleached from the surrounding cement-basedmaterials. It decreases swelling capacity of thebentonite [1]. In order to solve this problem, we
proposed a method to mix inorganic materials suchas silica fume and sodium carbonate, which show
reactivity with the components leached from thecement-based materials, to the bentonite. The
pozzolanic materials such as silica fume and fly ash
are expected to consume the leached calcium ionsfrom the cement-based materials and hence, reducethe deterioration of the bentonite.
In our previous research [2]-[4], one-dimensionalvertical swelling deformation tests proposed by
Komine and Ogata [5], [6] were performed.
Experimental results in the previous researchshowed that the mixing of the pozzolanic materials
could restrain the decrease of the swelling capacity.
Especially, the mix with 10~15 mass% of fly ash or
the mix with 1 mass% of silica fume presented themost effectiveness on reducing the deterioration by
calcium hydroxide solution.
The other proposal is the mixing of sodium
carbonate to the bentonite. Here, calcite precipitationin the interface zone between the bentonite-basedmaterials and cement-based materials was expected.
The previous experimental results conducted by

Nakarai et al. [7] showed that the calcite
precipitation could reduce the deterioration of thebentonite due to calcium leaching from the cement
paste. Here, the immersion tests of the composite
specimens consisting of cement paste and bentonite
were performed. Then, the effect of the sodium
carbonate mixing was investigated from the
distribution of calcium measured by Electron Probe
Micro Analysis (EPMA). In addition, the previous
experimental
resultsstudiedonswelling
characteristics of bentonite showed that the mix with
0.5 mass% of sodium carbonate was the mosteffective in reducing the deterioration by calcium
hydroxide solution.
In the previous research, the swelling-deformation
tests conducted right after mixing. However, in theactual environment, it will take a long time to reachthe leached ions from the surrounding cement-basedmaterials to the bentonite. So, we have to investigate
the aging effect of the mixiting of the admixture in
the bentonite. In this study, we investigated the timedependent effect of mixing by comparing the resultsfrom the specimens tested right after mixing andafter 1 year from the mixing in terms of the swellingcharacteristics of bentonite. Here, we prepared thebentonite specimens mixed with silica fume or
sodium carbonate. Then, we also used the swellingdeformation tests proposed by Komine and Ogata[5], [6] and measured the swelling-deformation of
the bentonite specimens in the saturated aqueous
solution of calcium hydroxide or deionized water.

247

GEOMATE-Nagoya, Nov.13-15, 2013

OUTLINE OF EXPERIMENTS

Table1 Outline of specimens

Materials

Names ofspecimens

Table 1 shows the outline of specimens. In thisstudy, we used silica fume or sodium carbonate as
an admixture. Then, we prepared three kinds ofspecimens; pure bentonite without admixtures,
bentonite mixed with silica fume, and bentonite
mixed with sodium carbonate. This study used thecommercial bentonite, called Kunigel-V1, extracted
from the Tsukinuno Mine in Japan. This study usedsilica fume as an admixture. The 94.9% of silica
fume was SiO 2 . And, its specific surface was 17.5
m2/g. This study also used commercial sodium
carbonate. Its content of sodium carbonate was
99.8%.
In the case of the young specimens tested justafter mixing (experiment in the previous research[3]), the mixing ratios of silica fume to dry bentonite
were 0.5, 1.0, 2.0, 5.0, 8.0 mass% while the mixing
ratios of sodium carbonate were 0.2, 0.5, 1.0, 4.0
mass%. In the case of the aged specimens 1 year
after mixing, the mixing ratios of silica fume to dry
bentonite were 0.5, 1.0, 2.0 mass%, while themixing ratios of sodium carbonate were 0.5, 1.0, 4.0
mass%. The water content of specimen in the bothcases was set to 21 % by considering the planned
value in the design of a subsurface radioactive waste
repository for low level wastes in Japan.
In this paper, the names of specimens indicatedthe composition of the materials, the mixing ratio of
admixture, and the type of solution. (W: distilledwater, CH: saturated calcium hydroxide solution andcalcium hydroxide powder). In the case of the aged
specimens 1 year after the mixing, the asterisk (*)
was attached at the end of the specimen name.

Material composition[mass%]BeSF

Na2CO3

100.0
Be-W
99.5
BeSF-0.5-W
BeSF-2-W
98.0
BeSF-3-W
97.0
BeSF-5-W
95.0
BeSF-8-W
92.0
100.0
Be-CH
BeSF-0.5-CH 99.5
BeSF-1-CH
99.0
BeSF-2-CH
98.0
BeSF-5-CH
95.0
92.0
BeSF-8-CH
BeN2C-0.2-CH 99.8
BeN2C-0.5-CH 99.5
BeN2C-1-CH 99.0
BeN2C-4-CH 96.0
BeSF-0.5-CH* 99.5
BeSF-1-CH* 99.0
BeSF-2-CH* 98.0
BeN2C-0.5-CH* 99.5
BeN2C-1-CH* 99.0
BeN2C-4-CH* 96.0

0.5
2.0
3.0
5.0
8.0
0.5
1.0
2.0
5.0
8.0
0.5
1.0
2.0
-

0.2
0.5
1.0
4.0
0.5
1.0
4.0

Type of Timing ofsolution
test

distilledwater

just after
mixingsaturatedcalciumhydroxide
solution just afterwithmixingcalciumhydroxidepowdersaturatedcalciumhydroxide 1y after
solution mixing
withcalcium

LinearVariable
displacementtransducer
Iron plate
PistonSpecimen
Diameter:60mm
Height:5mm

Acrylic cell
Solution

Pedestal

Mixing of Materials

Porous metal

Fig.1 Schematic drawing of test apparatus

The mixing procedures were as follows. Firstly,
air-dried bentonite and admixture were mixed at low
speed for 30 seconds using an Omni mixer. During
the mixing, water contents of these mixtures were
adjusted during low speed mixing. Here, we sprayeddistilled water. After that, they were mixed at highspeed for 60 seconds. Then, they were kept in apolyethylene bag for 24 hours. In the next day, thesemixtures were mixed at high-speed for 60 seconds
again, and we measured water contents of thesemixtures. Then, the samples were kept again in apolyethylene bag about one year. The temperature of
the storage environment is 20°C. The relative
humidity is 60%.

prepared. The height of the specimens was small tosave time for water absorption because thecompacted bentonite specimens have low
conductivities. The dry density was set to 1.3g/cm3
to easily assess deterioration. The sample wasstatically compacted by vertical pressure for several
hours until the height of specimens became 5mm.
Swelling Deformation Test
Figure 1 shows the test apparatus. Swellingcharacteristics of the bentonite specimens were
evaluated by using the one-dimensional swellingdeformation test under a constant vertical pressure
proposed by Komine and Ogata [5,6]. An iron plate
was fixed to the top of the piston applying theconstant vertical pressure. We used a filter paper(φ60mm × 0.19mm), and a porous metal (φ60mm ×Specimens
In this study, the cylindrical specimens having
diameters of 60mm and heights of 5mm were
248

GEOMATE-Nagoya, Nov.13-15, 20135mm) as filter. The filters were placed below the top
cap and on the pedestal. They were used for
mitigating the outflow of bentonite particles from
specimens. After applying the prescribed verticalpressure (10kPa) to the specimen, aqueous solutions
were supplied to the specimen. Then, therelationship between the axial swelling deformationand the time required from the start of water supply
was then measured.
The solution supplied to the specimens was thesaturated aqueous solutions of calcium hydroxide to
discuss the effects of calcium ions leached from
cement-based materials. And the solution was
included additional calcium hydroxide powders tokeep saturated concentration during the swelling
tests.
In the cases of specimens of the pure bentonite
without admixtures and the bentonite mixed withsilica fume, the temperature during the experiments
was set to 40 °C in order to promote pozzolanic
reaction of silica fume. In the case of specimens of
the bentonite mixed with sodium carbonate, thetemperature was set to 20°C. They were determinedby considering the experimental condition in theprevious studies [2]-[4].) The solution was supplied
from one side of specimens in this study. The
method is same as the previous study [2]-[4].
Measurement period it was decided to be 7 days. It
was longer than the previous study conducted by
Nakarai and Shimakura [2] to improve the accuracyof data.

X-ray Diffraction Analysis
The components of specimen after the swellingdeformation test were examined by X-ray diffraction.
The specimen was mixed with α-Alumina(Corundum), whose volume was 10% of the sample
for the XRD measurement, as a standard substance.
The data was analyzed by using SIROQUANT
Ver.3 to detect the mineral components from themeasured peak.
RESULTS AND DISCUSSIONS
Aging Effect of Mixing of Admixture
Effect of silica fume as an admixture
Fig.2 shows the relationship between thecalculated maximum swelling strain and the mixing
ratio of thesilica fume (included the results of the previous
research [3], [4]). Here, the solid and broken lines in
the figure show the predicted maximum swellingstrain in W and CH, respectively. They werepredicted from the maximum swelling strain of thepure bentonite specimens and the mixing ratio as
references for the discussions. Fig.3 shows theresults of the swelling-deformation tests forinvestigating the aging effect on the swelling
behavior when the saturated calcium hydroxide
solution (CH) was supplied to the specimens whichwere mixed with silica fume about 1 year ago.
According to Fig.3, in the case of the young
specimens, it was found that the maximum swellingstrain of specimens mixed with silica fume (0.5 ~5.0 mass%) became larger than the predictedmaximum swelling strain indicated by the solid line.
It means that the mixing of silica fume can reducethe deterioration of bentonite by alkali. Especially,
the mixing of 1mass% of silica fume was mosteffective to suppress the deterioration. When we
mixed silica fume more than 1mass%, the maximum
swelling strain gently decreased as mixing ratio of
silica fume increase. It was caused by the decreasein the bentonite proportion in the specimen andsolidification associated with the pozzolanic reactionof silica fume in the water.
In the case of the aged specimens 1 year after
mixing, the mixing of 0.5 ~ 2.0 mass% of silica
fume was effective to suppress the deterioration of
bentonite by the calcium hydroxide solution.
However, in these aged specimens, the effect of themixing on the degradation of swelling performanceof the bentonite tended to be smaller than in the caseof the young specimens tested just after mixing.
In the case of the young specimens, the mixing of

Evaluation Method
The swelling strain (%) is defined by𝛆𝛆𝐒𝐒 ＝∆𝐒𝐒
× 𝟏𝟏𝟏𝟏𝟏𝟏
𝐇𝐇𝟎𝟎

(𝟏𝟏)

where ε𝐒𝐒 is swelling strain (%), ∆𝐒𝐒 is swellingdeformation, and 𝐇𝐇𝟎𝟎 is initial specimen height.
It is known that the curves of swelling strain versus
time can be approximated by the hyperbola in Eq.(2)[4], [5]. The maximum swelling strain ε𝐬𝐬𝐬𝐬𝐬𝐬𝐬𝐬 (%) is
obtained from the asymptotic line of the hyperbola,and can be calculated by Eq.(3)ε𝐬𝐬 (𝐭𝐭𝐭𝐭𝐭𝐭𝐭𝐭)＝

𝐭𝐭𝐭𝐭𝐭𝐭𝐭𝐭[%]
𝐚𝐚 + 𝐛𝐛𝐛𝐛𝐛𝐛𝐛𝐛𝐛𝐛

ε𝐬𝐬𝐬𝐬𝐬𝐬𝐬𝐬 = 𝐥𝐥𝐥𝐥𝐥𝐥 𝛆𝛆𝐬𝐬 (𝐭𝐭𝐭𝐭𝐭𝐭𝐭𝐭) =𝐭𝐭𝐭𝐭𝐭𝐭𝐭𝐭→∞

𝟏𝟏
[%]
𝐛𝐛

(𝟐𝟐)
(𝟑𝟑)

where “time” is the duration (in day) from the startof water supply, ε s (time) is swelling strain at “time”, and a and b are constants determined by fitting
procedures.

249

250
200
150
100
50
0

Be1.3-CH
Be1.3SF-CH
Be1.3SF-CH*

Maximum swelling strain εsmax[%]

Maximum swelling strain εsmax[%]

GEOMATE-Nagoya, Nov.13-15, 2013

Be1.3-W
Be1.3SF-W

The relationship content ratio
of bentonite in the specimen
and maximum swelling strain

0

2

4

6

8

10

Mixing ratio of silicafume [mass%]

Be1.3SF-0.5-CH*
Be1.3SF-1-CH*
Be1.3SF-2-CH*

250
200
150
100
50
0

0

2

4

6

Be1.3-W
Be1.3N2C-W

The relationship content ratio
of bentonite in the specimen
and maximum swelling strain

0

2

4

6

8

10

Mixing ratio of sodium carbonate [mass%]

Fig.4 Relationship between maximum swellingstrain and mixing ratio of sodium carbonate

Swelling strain εs[%]

Swelling strain εs[%]Fig.2 Relationship between maximum swellingstrain and mixing ratio of silica fume

250
200
150
100
50
0

Be1.3-CH
Be1.3N2C-CH
Be1.3N2C-CH*

Be1.3N2C-0.5-CH*
Be1.3N2C-1-CH*
Be1.3N2C-4-CH*

250
200
150
100
50
0

0

8

2

4

6

8

Time[day]Time[day]Fig.5 Curves of swelling strain versus time

Fig.3 Curves of swelling strain versus time
1mass% of silica fume was most effective tosuppress the deterioration. But in the case of theaged specimens 1 year after mixing, the effect ofsuppressing the deterioration was all most same
regardless of the mixing ratio of the silica fume.

deterioration. But, it was found that the swellingstrain of Be1.3N2C-1-CH was greater than that of
Be1.3N2C-1-W. It was supposed to be caused by thedecrease in the ionic strength of the pore water in theparticles associated with the precipitation of calcite.
In the case of the aged specimens 1 year after
mixing, the mixing of 0.5mass% of sodium
carbonate was only effective to suppress thedeterioration of bentonite by the calcium hydroxide
solution.
However, in the case of the aged specimens, theeffect of the mixing on the degradation of swelling
performance of the bentonite also tended to besmaller than the young specimens tested just after
mixing.
Finally, we examined the component of thespecimens after the swelling-deformation test using
the X-ray diffraction (XRD) analysis. Figs. 6, 7
show the results of this XRD analysis. Since the dry
densities of the specimens in Figs. 6 and 7 were notsame, the ratio of the components in the specimens
will be discussed here.
According to the results obtained by XRD
analysis, the amount of the montmorillonite in theaged specimen tested 1 year after mixing sodium
carbonate was significantly smaller than in the case

Effect of sodium carbonate as an admixture
Fig.4 shows the relationship between thecalculated maximum swelling strain and the mixing
ratio of sodium carbonate (included the results of theprevious research [3], [4]). Here, the solid andbroken lines in the figure also show the predictedmaximum swelling strain in W and CH, respectively.
Fig.5 shows the results of the swelling-deformation
tests when the saturated calcium hydroxide solution(CH) was supplied to the specimens, which weremixed with sodium carbonate about 1 year ago.
According to Fig.4, in the case of the young
specimens, it was found that the maximum swellingstrain of specimens mixed with sodium carbonate(0.2 ~ 1 mass%) became larger than the predictedmaximum swelling strain indicated by the solid line.
It means that the mixing of sodium carbonate canreduce the deterioration of bentonite by alkali.
Especially, the mixing of 0.5mass% of sodium
carbonate was most effective to suppress the250GEOMATE-Nagoya, Nov.13-15, 2013

Montmorillonite

Montmorillonite

Fig.6 Result of XRD analysis (Be1.6N2C-4-CH)

Fig.7 Result of XRD analysis (Be1.3N2C-4-CH*)of the young specimens tested just after mixing.
Therefore, the decreasing the effect of suppress thedeterioration of the bentonite was thought to becaused by the decreasing of the amount of themontmorillonite as a source of the swelling in thespecimen.

parameter used in groundwater migration
disposal,” 2008. (in Japanese)[2] K. Nakarai., and C. Shimakura: “Swellingdeformation of the bentonite mixed withpozzolanic materials in calcium hydroxide
solution,” Proceedings of 46th Conference of
the Japanese Geotechnical Society, pp.20892090, 2011. (in Japanese)[3] Y. Yokoyama, and K. Nakarai: “Swellingdeformation of the bentonite mixed with silica
fume or sodium carbonate in calcium hydroxide
solution,” Proceedings of 9th Conference of theJapanese Geotechnical Society Branch of Kanto,material3-2, 2012. (in Japanese)[4] Y. Yokoyama, and K. Nakarai: “Swellingdeformation of the bentonite mixed with silica
fume or sodium carbonate in calcium hydroxide
solution,” Second International Conference on
Geotechnique, Construction Materials andEnvironment, pp.172-175, 2012.
[5] H. Komine, and H. Ogata, “Experimental study
on swelling characteristics of compacted
bentonaite,” Canadian Geotechnical Journal,
Vol.31, No.4, pp.478-490, 1994.
[6] H. Komine, and H. Ogata, “Experimental study
on swelling characteristics of sand-bentonite
mixture for nuclear waste disposal,” Soils andFoundations, Vol.39, No.2, pp.83-97, 1999.
[7] K. Nakarai, M. Watanabe, H. Ishii, K.
Koibuchi: “Reducing the deterioration between
cement and bentonite by mixing with Na 2 CO 3 ,”Proceedings of the 66th Annual Conference of
the Japan Society of Civil Engineers, pp.99-100,
2011.

CONCLUSIONSIn this study, we investigated the effect ofadmixtures such as silica fume and sodium
carbonate in order to develop new composite
materials suppressing the deterioration by alkali
solution from the viewpoint of swelling performancein the engineered barrier system for nuclear waste
management. The performance was evaluated basedon the swelling deformation of specimens measured
in the distilled water and the saturated calcium
hydroxide solution. Then, the following conclusions
were drawn from the results of the experiments.
(1) In the case of the young specimens tested justafter mixing, the mixing of small amount of silica
fume or sodium carbonate can reduce thedeterioration of the bentonite in alkaline water.
(2) In the case of the aged specimens 1 year after
mixing, the effect of the mixing on the degradationof swelling performance of the bentonite tended tobe smaller than in the case of the specimens tested
just after mixing regardless of the type of admixtures.
REFERENCES[1] Japan Society of Civil Engineers, “The method
for setting nuclide migration assessment
scenario in safety assessment of sub-surface

251Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

USE OF FULLY SOFTENED VERSUS PEAK STRENGTH TO PREDICT THE
CAPACITY OF FOOTINGS ON GEOSYNTHETIC REINFORCED SOIL
Melia K. Iwamoto1, Phillip S.K. Ooi2, Jennifer E. Nicks3 and Michael T. Adams4
1

Graduate Research Assistant, Department of Civil and Environmental Engineering, University of Hawaii at
Manoa, USA 2Professor, Department of Civil and Environmental Engineering, University of Hawaii at Manoa,
USA 3,4Turner-Fairbank Highway Research Center, Federal Highway Administration, USA
Abstract
A database of load tests performed on geosynthetic reinforced soil (GRS - reinforcement in this study is of
the extensible variety) was developed using results of recent load tests performed on large scale GRS structuresat the Federal Highway Administration’s Turner Fairbank Highway Research Center as well as results from theliterature. The measured capacities were compared to those predicted using the Wu and Pham [1] equation
utilizing both the peak and fully softened soil shear strength parameters. It was found that the fully softenedstrengths yielded capacities that agreed better with the measured capacities. A rationale for this finding is thatthe robust reinforcement in a GRS strengthens the soil considerably causing the GRS to experience large strains
prior to failure. Because the soil peak strengths are mobilized at relatively small displacements/strains even inlarge scale direct shear or triaxial tests compared to the GRS load tests, it is postulated that the fully softenedvalues are more appropriate to estimate the GRS bearing capacity. A follow-on to this is that since large
movements are required to fail say a GRS abutment, the design of GRS abutments will most likely be governedby the serviceability limit state rather than the ultimate limit state.
Keywords: Geosynthetic Reinforced Soil, Bearing Capacity, Fully Softened Strength and Bridge Abutments
INTRODUCTION
Geosynthetic Reinforced Soil (GRS) is defined
as closely-spaced (≤ 0.3 m) layers of geosynthetic
reinforcement and compacted granular fill material[2]. GRS has been used for a variety of geotechnicalapplications but has recently been promoted by theFederal Highway Administration (FHWA) for use as
abutments for single span steel or concrete bridges
in their Everyday Counts Initiative, which is focusedon accelerating implementation of proven, marketready technologies. GRS-IBS, where IBS stands for
Integrated Bridge Systems, consists of a reinforced
soil foundation (RSF), a GRS abutment and a GRS
integrated approach (Fig. 1). The RSF consists of
granular fill compacted and encapsulated in
geotextile. The RSF provides embedment andincreases the bearing width and capacity of the GRS
abutment. The GRS abutment provides load-bearing
support for the bridge, which is placed directly on
the abutment. GRS is also used to construct the
integrated approach adjacent to the superstructure.
GRS-IBS has the following advantages:
1. Fast and cost-effective method of bridge
support. It eliminates the need for cast-in-place
reinforced concrete abutments traditionally
supported on deep foundations.
2. Quality compaction control can be realized
since closely-spaced geosynthetics ensure
backfill is placed in thin lifts.
3. Catastrophic collapse was not observed innumerous load tests carried out to failure; GRS
abutments behave in a ductile fashion.

4.

5.

6.
7.

Can be built in variable weather with common
labor, materials and equipment, and can beeasily modified in the field.
Alleviates the “bump at the end-of-the-bridge”
problem caused by differential settlement
between the bridge abutment and the approachroadway. This is made possible by eliminating
deep foundations, by using GRS to construct the
integrated approach and by limiting its use toshort, single-span integral bridge systems.
Enjoys all the advantages associated with an
integral abutment bridge.
Very flexible system that is amenable todifferential settlement and seismic loading.

Fig. 1 Typical cross-section of a GRS-IBS [2]Because GRS-IBS is load bearing, its capacity is
an important design consideration. Many studies ofthe bearing capacity of strip footings supported on
RSF [3]-[11] consider the RSF to extend
horizontally on both sides of the footing. In the caseof a GRS-IBS, the ground is limited on one side andthe bearing capacity of the bridge footing on a GRS
abutment wall must be known. Work in this area israther limited. One exception is the work by Pham252

GEOMATE-Nagoya, Nov.13-15, 2013[12], who performed plane strain load tests on GRS
and who derived an expression for the bearing
capacity of a footing on a GRS wall.
The
applicability of this expression is examined using
results from an extensive series of load tests
performed at FHWA's Turner-Fairbank Highway
Research Center (TFHRC) as well as those from theliterature.
Motivation for This Study
Christopher et al. [13] proposed that peakstrengths of the backfill should be used when
predicting bearing capacity of footings on
mechanically stabilized earth (MSE) type bridge
abutments reinforced using extensible elements.
However, it was observed that the peak strengthfrom large scale direct shear (LSDS) tests on
granular soils in this study was mobilized at about
13 to 16 mm lateral displacements, whichcorrespond to about 4.5 to 5.4% shear strain for a 0.3
m x 0.3 m x 0.2 m high direct shear sample. Also,
the peak strength from large scale (0.15 m diameterx 0.3 m high) triaxial tests on granular soils wasmobilized at about 2.3 to 5.0% axial strain [12]. As
will be presented later, load tests on GRS withclosely spaced (< 0.3 m) reinforcement having awide width tensile strength of at least 70 kN/m
generally fail at strains greater than 10%, implyingthat the soil shear strength is then past its peak.
𝜎𝜎𝑑𝑑Peak strength
Fully softened strength
Residual strengthε ≈ 2 - 5%

ε ≥ 10%Fig. 2 Typical stress-strain curve
The notion of using fully softened strength is not
new in geotechnical engineering. Duncan andWright [14] recommend the use of fully softenedstrength when analyzing the stability of cuts inheavily overconsolidated soil. The rationale for thisis that swelling and softening was found to haveoccurred along the slip surfaces during forensic
studies of such slides and use of fully softenedstrength, or the strength if the soil was normallyconsolidated, provided better agreement when backcalculating the factors of safety in these failed
slopes. Wu [15] indicated that the fully softenedstrength is typically mobilized at strains on the orderof 10%. In the case of GRS, the reinforcement
strengthens the soil and forces failure to occur very
often at double-digit strains (see TF test series inTable 1). Therefore, in the interest of preserving
strain compatibility, a study was conducted to see
whether fully softened strengths will provide a better
prediction of the bearing capacity of footings on
GRS abutments than peak strengths.
BEARING CAPACITY EQUATION OF A
FOOTING ON A GRS ABUTMENT WALL
Pham [12] derived the bearing capacity of afooting on a GRS abutment wall (q ult ) as follows:𝑇𝑇

𝑞𝑞ult = �𝜎𝜎h + 𝑊𝑊 𝑓𝑓� 𝐾𝐾𝑝𝑝 + 2𝑐𝑐 �𝐾𝐾𝑝𝑝
𝑆𝑆𝑣𝑣

(1)

where σ h is the lateral stress, T f and S v are thereinforcement strength and spacing, respectively, cis the soil cohesion, K p is the Rankine passive earthpressure coefficient, defined as
𝐾𝐾𝑝𝑝 =

1+sin 𝜙𝜙1−sin 𝜙𝜙(2)

φ is the soil friction angle. W is a dimensionlessfactor that amplifies the contribution of S v to the
GRS capacity, and was semi-empirically derived as
𝑆𝑆𝑣𝑣

𝑊𝑊 = 0.76𝑑𝑑𝑚𝑚𝑚𝑚𝑚𝑚(3)

𝜎𝜎ℎ = 𝛾𝛾𝑏𝑏𝑏𝑏 𝐷𝐷 tan 𝛿𝛿

(4)where d max is the maximum particle size of the GRS
backfill. Note that the 0.7 factor was theoreticallyderived using the concept of “average stresses”
proposed by Ketchart and Wu [16] while theexponent was empirically derived. For details on
this derivation, refer to [12].
For a GRS wall with dry stacked modular block
facing, σ h = lateral stress exerted by the facing on
the GRS mass, defined by Pham [12] as

where γ bl = bulk unit weight of facing block =weight of block/volume of block assuming it is nothollow, D = depth of facing block perpendicular to
the wall face and δ = friction angle between
geosynthetic reinforcement and the top and bottom
surface of the facing block.
GRS versus MSE
Mechanically stabilized earth (MSE) differs from
GRS in many respects. The most significant
difference involves the maximum reinforcement
spacing (0.3 m in GRS versus 0.8 m in MSE). The
basic MSE design premise is that each reinforcement
layer is responsible for equilibrium within thereinforcement tributary area; i.e.; σ h = T f /S v .
Implied in this equation is that a GRS withreinforcement strength T f at spacing S v will behave
the same as a GRS with reinforcement strength 2T f
at spacing 2S v , which has been shown to be untrue
253

GEOMATE-Nagoya, Nov.13-15, 2013

APPLICABILITY OF BEARING CAPACITYEQUATION
Considering that most of the load tests in the
database were performed on GRS columns (mostly
square with some circular in plan) while a bridgefooting resting on an abutment more resembles aplane strain (PS) condition, the relationship between
the column tests and that of a strip footing loading
the top of a GRS wall is of interest. Assume that thestrength of a GRS column can be represented by the
Mohr-Coulomb equation as follows:𝜏𝜏 = 𝑐𝑐𝐺𝐺𝐺𝐺𝐺𝐺 + 𝜎𝜎𝜎𝜎𝜎𝜎𝜎𝜎𝜙𝜙𝐺𝐺𝐺𝐺𝐺𝐺(5)𝑞𝑞𝑢𝑢𝑢𝑢𝑢𝑢,𝑃𝑃𝑃𝑃 = 2𝑐𝑐𝐺𝐺𝐺𝐺𝐺𝐺(6)𝑞𝑞𝑢𝑢𝑢𝑢𝑢𝑢,𝑃𝑃𝑃𝑃 = 𝑐𝑐𝐺𝐺𝐺𝐺𝐺𝐺 𝑁𝑁𝑐𝑐𝑐𝑐 + 0.5𝛾𝛾𝐺𝐺𝐺𝐺𝐺𝐺 𝑏𝑏𝑁𝑁𝛾𝛾𝛾𝛾(7)where τ = shear strength, σ = applied normal stress,
c GRS and φ GRS = cohesion and friction angle of the
GRS composite, respectively. In an unconfinedcompression load or Performance Test (PT), where
the facing has been removed, the ultimate capacityof the GRS column (q ult,PT ) can be expressed as

For the PS condition, the bearing capacity of afooting supporting the bridge superstructure can be
estimated using Meyerhof’s [19] solution for a roughstrip bearing on top of a slope

where q ult,PS = ultimate capacity of strip footing
under PS conditions, γ GRS = unit weight of the GRS
backfill, b = footing width, and N cq and N γq =Meyerhof’s [19] bearing capacity factors for a strip
footing with a rough base. N γq approaches zero
when the slope angle is 90° for a GRS abutment
wall; thus Eq. (7) reduces to𝑞𝑞𝑢𝑢𝑢𝑢𝑢𝑢,𝑃𝑃𝑃𝑃 = 𝑐𝑐𝐺𝐺𝐺𝐺𝐺𝐺 𝑁𝑁𝑐𝑐𝑐𝑐(8)

Dividing Eq. (8) by (6), the ratio of the bearing
capacity of a strip footing on top of a GRS abutment
to that of a GRS column can be estimated as
𝑞𝑞𝑢𝑢𝑢𝑢𝑢𝑢,𝑃𝑃𝑃𝑃

𝑞𝑞𝑢𝑢𝑢𝑢𝑢𝑢,𝑃𝑃𝑃𝑃=

𝑁𝑁𝑐𝑐𝑐𝑐2(9)For a surface footing on top of a vertical GRS
abutment, the value of N cq varies with the footing
offset from the edge of the wall face, a, wall height,𝛾𝛾
𝐻𝐻H, footing width, b, and stability factor, 𝑁𝑁𝑠𝑠 = 𝐺𝐺𝑅𝑅𝑆𝑆 ,as shown in Fig. 3. c GRS can be obtained fromlaboratory or numerical experiments.
3
q u l t ,PS/q u l t ,PT

by Adams et al. [17] and Pham [12]. Instead, S v hasa bigger influence on the bearing capacity than T f .
This led Pham to propose the addition of the W termin Eq. 1, without which, the equation is theexpression for the bearing capacity of a footing on a
MSE abutment wall.

Ns = 0Ns = 2

2

1

0
0

1

2 a/H 3

4

5

Variation of N cq with footing geometry andthe stability factor.
For example, Pham [12] conducted a series ofplane strain load tests on 1.94-m-high GRS that canbe used to derive a cohesion value for the GRS.
Two of the tests (GSGC2 and 5 in Table 1) wereidentical in every respect (Tensile strength ofreinforcement = 70 kN/m, Reinforcement spacing =0.2 m, Backfill c = 70 kPa and φ = 50º) except forthe confining stresses (0 in GSGC5 and 34 kPa in
GSGC2). The corresponding failure stresses were2032 and 3396 kPa for the 0 and 34 kPa confining
stresses, respectively. The resulting shear strengthparameters for the GRS are c GRS = 160 kPa and φ GRS= 72°. The corresponding stability factor γH/c ≈0.29. Based on this stability factor, the ratio of planestrain capacity for a typical GRS abutment with atypical set-back a = 0.2 m and H varying from 3 m
to 10 m (i.e. a/H = 0.02 to 0.07) to column (PT)capacity is close to unity. Therefore, the column PT
is fairly representative of an in-service PS condition
for well-graded gravels in this case.
Fig. 3LOAD TESTS
Eleven GRS load tests performed at FHWA's
TFHRC (designated as "TF”) with and without castmasonry unit or CMU facing that was frictionallyconnected to the geosynthetic are reported in Table
1. Each CMU block was 0.194-m-high x 0.397-mlong x 0.194-m-wide (Fig. 4a). A schematic of tests
TF-1, 2, 6, 9 and 12, each 10 blocks high, is shownin Figs. 4b to 4d. Tests TF-4, 7, 10 and 11 have asimilar set-up except the blocks were removed prior
to testing. TF-14 (Fig. 4e) has the same area in plan
but was slightly taller (H = 2.0 m) with 7 pairs offull- and half-height blocks. TF-13 is identical to 14
except the blocks were removed. Details of thegeotextile and soil utilized are summarized in Table
1 along with other tests collected from the literature
giving a total of 28 load tests in this database.

𝑐𝑐𝐺𝐺𝐺𝐺𝐺𝐺

254

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Test parameters of GRS performance tests selected from literature and available studies
Test
USCS
ϕ peakd max
c peak ϕ fs c fs
StrengthTf
S v Facing
Symbol˚
˚ kPa Test Type kN/m
m
kPa
m
Type
4
GSGC22 0.0330 GS-GM
50
70
41 118TX3
70
0.2
4
GSGC32 0.0330 GS-GM
50
70
41 118
TX3
140
0.4
4
GSGC42 0.0330 GS-GM
50
70
41 118
TX3
70
0.4
2
3
GSGC5 0.0330 GS-GM
50
70
41 118
TX
70
0.2
None
Elton10.0127
SP
40
28
41 27
DS5
9
0.15 None
Elton20.0127
SP
40
28
41 27
DS5
9
0.3
None
Elton30.0127
SP
40
28
41 27
DS5
14
0.2
None
Elton40.0127
SP
40
28
41 27
DS5
15
0.2
None
Elton50.0127
SP
40
28
41 27
DS5
19
0.2
None
Elton60.0127
SP
40
28
41 27
DS5
20
0.2
None
Elton70.0127
SP
40
28
41 27
DS5
25
0.2
None
VS-16
0.0127
GP
54
23
51
0
LSDS7
70
0.2
CMU
VS-26
0.0191
GP
46
19
45
0
LSDS7
70
0.2
CMU
6
VS-5
0.0127
GP
51
0
51
0
LSDS7
70
0.2
CMU
MPA8
0.0254 GW-GM
54
75
53
0
LSDS7
70
0.6
None
MPB8
0.0254 GW-GM
54
75
53
0
LSDS7
70
0.4
None
MPC8
0.0254 GW-GM
54
75
53
0
LSDS7
20
0.2
None
TF-1
0.0127
GP
53
69
55
0
LSDS7
35
0.2
CMU
TF-2
0.0254 GW-GM
54
759 53
0
LSDS7
35
0.2
CMU
9
TF-3
0.0254 GW-GM
54
75
53
0
LSDS7
35
0.2
None
TF-6
0.0254 GW-GM
54
759 53
0
LSDS7
70
0.2
CMU
TF-7
0.0254 GW-GM
54
759 53
0
LSDS7
70
0.2
None
9
TF-9
0.0254 GW-GM
54
75
53
0
LSDS7
70
0.4
CMU
TF-10
0.0254 GW-GM
54
759 53
0
LSDS7
70
0.4
None
9
TF-11
0.0254 GW-GM
54
75
53
0
LSDS7
20
0.1
None
TF-12
0.0254 GW-GM
54
759 53
0
LSDS7
20
0.1
CMU
TF-13
0.0254 GW-GM
54
759 53
0
LSDS7
53
0.3
None
9
TF-14
0.0254 GW-GM
54
75
53
0
LSDS7
53
0.3
CMU
Notes:
1. ε f = Strain of GRS load tests at failure

σh
kPa
34
34
34
0
0
0
0
0
0
0
0
1.82
1.82
1.82
0
0
0
1.82
1.82
0
1.82
0
0.91
0
0
1.82
0
2.73

Boundary
Conditions
Plane Strain
Plane Strain
Plane Strain
Plane Strain
Cylindrical Column
Cylindrical Column
Cylindrical Column
Cylindrical Column
Cylindrical Column
Cylindrical Column
Cylindrical Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column
Square Column

q ult,emp
kPa
3396
2038
1783
2032
230
129
306
292
402
397
459
1116
1087
1031
225
170
460
981
1209
837
2095
1271
1068
494
1113
1390
620
1128

εf1
%
6.5
6.1
4.0
6.0
1.7
3.1
3.9
4.5
4.7
7.7
8.5
8.0
7.1
10.4
1.9
2.2
6.4
10.9
11.5
13.8
15.7
12.5
15.6
14.3
12.8
13.4
12.3
12.7

Reference
[12]
[12]
[12]
[12]
[18]
[18]
[18]
[18]
[18]
[18]
[18]
[20]
[20]
[20]
[17]
[17]
[17]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]
[20]

2. GSGC = Generic Soil-Geosynthetic Composite
3. TX = Consolidated drained triaxial compression tests on 0.15-m-diameter and 0.3-m-high samples
4. No facing was used. Instead, a confining pressure = 34 kPa was applied using a rubber membrane wrapped all around the GRS
5. DS = direct shear test. Because soil was SP, direct shear sample was 0.063 m diameter performed in accordance with ASTM D3080
6. VS = Performance tests conducted in Defiance County, OH as part of the FHWA’s Every Day Counts GRS Validation Sessions
7. LSDS = Large Scale Direct Shear tests on 0.3 m by 0.3 m by 0.2 m high specimen
8. MP = Mini pier tests or more widely referred to herein as performance tests
9. Best fit linear Mohr-Coulomb envelopes for soil used in TF-2 through TF-14 yielded values of cohesion of 75 kPa and 6 kPa, respectively for the partially saturated and saturated samples. A
cohesion of 75 kPa was used when estimating the GRS capacity since soil was partially saturated during load testing in FHWA’s TFHRC laboratory.

255

GEOMATE-Nagoya, Nov.13-15, 2013a)c)

0.937m
0.194m

90% confidence that the bias will be within 3
standard deviations of the mean.

Potentiometers
Footing

Table 2
Predicted ultimate bearing capacities offootings on GRS using peak and fully softenedstrengths

0.914mb)

1.384mStrain gauges

0.997md)Fig. 4Test

1.937mFatback Cell

GSGC2
GSGC3
GSGC4
GSGC5
Elton1
Elton2
Elton3
Elton4
Elton5
Elton6
Elton7
VS-1
VS-2
VS-5
MPA
MPB
MPC
TF-1
TF-2
TF-3
TF-6
TF-7
TF-9
TF-10
TF-11
TF-12
TF-13
TF-14

EP Celle)(a) CMU dimensions; (b) and (c) schematicof TF 1, 2, 6, 9, and 12; (d) photo of TF-6;(e) photo of TF-14

Results
The ultimate bearing capacities of the 28 load
tests were predicted using Eq. 1 and both thebackfill’s peak and fully softened shear strengthparameters.
Table 2 contains the predicted
capacities (q ult,peak and q ult,fs ) along with themeasured capacities (q ult,emp ). Also shown in Table
2 are the bias defined as the ratio of the measured to
predicted capacities. The mean, standard deviationand coefficient of variation (COV) of the bias areshown at the bottom of Table 2.
The mean bias using peak strengths was 0.79
with a COV of 36%.
Fig. 5a contains thecorresponding plot of the histogram and normal
distribution of the bias while Fig. 5b shows a plot of
the predicted versus measured capacities. Clearly,
Eq. 1 over-predicts the GRS capacity when using
peak strengths.
In contrast, the mean bias using fully softenedstrengths was 1.00 with a coefficient of variation(COV) of 32%. Fig. 6a contains the corresponding
plot of the histogram and normal distribution of thebias while Fig. 6b shows a plot of the predictedversus measured capacities where the data points are
more centered around the line of equality. Based onthese results, Eq. 1 along with the use of fully
softened strengths yield a bias that is close to unity
with a slightly smaller COV compared to the use ofpeak strengths for this dataset.
Hypothesis testing on the normal distribution of
the bias indicate that using Eq. 1 and fully softenedstrengths will result in a mean bias of 1.0, with aq ult,emp
kPa
3396
2038
1783
2032
230
129
306
292
402
397
459
1116
1087
1031
225
170
460
981
1209
837
2095
1271
1068
494
1113
1390
620
1128

q ult,peakq ult,fs
kPa
kPa
2511
1885
1957
1529
1294
1102
2260
1723
250
252
151
150
325
329
333
337
393
398
416
422
486
494
1587
1159
1329
1155
1159
1159
717
259
1085
620
1070
606
1080
734
1528
1055
1511
1038
2585
2093
2568
2077
1134
668
1126
660
2001
1520
2018
1536
1296
828
1322
852
Mean Bias
Standard Deviation
Coefficient of Variance (%)

Bias
Peak
FS
1.35
1.80
1.04
1.33
1.38
1.62
0.90
1.18
0.92
0.91
0.86
0.86
0.94
0.93
0.88
0.87
1.02
1.01
0.95
0.94
0.94
0.93
0.70
0.96
0.82
0.94
0.89
0.89
0.31
0.87
0.16
0.27
0.43
0.76
0.91
1.34
0.79
1.15
0.55
0.81
0.81
1.00
0.49
0.61
0.94
1.60
0.44
0.75
0.56
0.73
0.69
0.90
0.48
0.75
0.85
1.32
0.79
1.00
0.28
0.32
0.36
0.32

SUMMARY AND CONCLUSIONSThe current state of practice is to use the peakstrength of the backfill material, as suggested by
Christopher et al. [13]. However, the results of thisstudy provide evidence that the fully softenedstrengths are more appropriate for estimating footing
capacities on GRS.
Prediction of GRS bearing capacity improved byusing fully softened versus peak strengths obtained
from large scale direct shear and triaxial tests. Mean
bias between measured and predicted values
increased from 0.79 to 1.00 and the COV improved
from 36% to 32%.
Fully softened strengths are more suitable forbearing capacity predictions because GRS withclosely spaced reinforcement generally fail at large
strains past the backfill’s peak strengths. A followon to this is that since large movements are required
to fail say a GRS abutment, the design of GRS
abutments will most likely be governed by theserviceability limit state rather than the ultimate
limit state.
256

GEOMATE-Nagoya, Nov.13-15, 2013a) 5

REFERENCES

1.5

4

1.2

3

0.9

2

0.6

1

0.3

0

0

0.5
1
1.5
Bias (qult,measured/qult,calculated)
4000
GSGC
Elton
VS
3000
MP
TF
2000

Predicted Capacity Using
Peak Strengths (kPa)b)

2Normal Distribution

Frequency

[1]

0

1000
0
0

Fig. 54000(a) Histogram and normal distribution ofbias using peak strength; (b) predictedversus measured capacities using peakstrength
1.5

4

1.2

3

0.9

2

0.6

1

0.3

0

0

0.5
1
1.5
Bias (qult,emp/qult,calculated)

Predicted Capacity Using
Fully-softened Strength (kPa)b) 40002

Normal Distribution

Frequency

a) 5

1000
2000
3000
Measured Capacity (kPa)

0

GSGC
Elton
VS
MP
TF

3000
2000
1000
0
0

Fig. 6

1000
2000
3000
Measured Capacity (kPa)

4000(a) Histogram and normal distribution ofbias using fully softened strength; (b)predicted versus measured capacities using
fully softened strength

Wu JTH, Pham TQ, “Load-carrying capacity and required
reinforcement strength of closely-spaced soil-geosynthetic
composites”, ASCE J. of Geotech. and GeoEnv. Engrg., Vol.
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[2] Adams M, et al., Geosynthetic Reinforced Soil Integrated
Bridge System Interim Implementation Guide. McLean:
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[3] Binquet J, Lee KL, “Bearing capacity analysis of reinforced
earth slabs”, ASCE J. of Geotech. Engrg. Div., Vol. 101, Dec.
1975, pp. 1257-1276.
[4] Fragaszy RJ, Lawton EC, “Bearing capacity of reinforced
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on Soil Mech. and Found. Engrg., 1985, pp. 1777-1780.
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[8] Huang CC, Tatsuoka F, “Bearing capacity of reinforced
horizontal sandy ground”, Geotextiles and Geomembranes,
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[9] Karim MR, Siddiquee MSA, (2009). “Improvement ofbearing capacity of strip footing on sand by using metal strip
reinforcement”, J. of Civil Engrg., IEB, Vol. 37, Dec. 2009,
pp. 165-177.
[10] Michalowski R, “Limit loads on reinforced foundation soils”
ASCE J. of Geotech. and GeoEnv. Engrg., Vol. 130, Apr.
2009, pp. 381-390.
[11] Sakti JP, Das BM, “Model tests for strip foundation on clay
reinforced with geotextile layers” Trans. Res. Rec. 1153,
Transportation Research Board, 1987, pp. 40-45.
[12] Pham TQ, “Investigating Composite Behavior of
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Mitchell JK, Dunnicliff J, “Reinforced Soil Structures,
Volume 1, Design and Construction Guidelines”, Federal
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FHWA-RD-89-043, Nov. 1990.
[14] Duncan M, Wright S, Soil Strength and Slope Stability.
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257

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

THREE DIMENSIONAL FINITE ELEMENT ANALYSIS OF SOIL
NAILS IN GRANITIC SOILS
G. Ren1 and H. Tokhi1
1School of Civil, Environmental and Chemical Engineering, RMIT University, 376-392 Swanston Street,
Melbourne, Victoria, Australia.

Abstract: Soil nailing techniques have been widely employed in the civil engineering industry to improve thesafety margin of soil slopes and excavations. In this paper, a three dimensional finite element model (FE) isdeveloped to simulate the nail-soil interaction of soil nail during shear-box pull-out test under different
overburden pressures. The behaviour of soil-nail and its interaction play an important role in overall and internal
failure mechanism. The stress strain behaviour of the soil was modelled by the modified Drucker-Prager/Cap
model and the interaction between the nail and soil was simulated using a penalty-type interface. The results
indicate that soil nail capacity is heavily influenced by the soil-nail interaction mechanism and the shear strength
developed at the soil-nail interface.
Key words: Soil nail, pull-out test, slope, surcharge, finite element.
overburden pressures are considered in the present
FE model.

Introduction
Soil nails have been widely used in stabilisingslopes and retention systems as an efficient andeconomical method. Using soil nails for stabilising
purposes is a relative recent development andhence the design guidelines are not fully
understood and are still debated by many
researchers. It is well understood that the pull-out
nail resistance is influenced by factors such as theconstruction method, soil-nail surface interaction,soil dilation and saturation and the nail bending.

Three-dimensional finite element model
The three-dimensional solid model and the finite
element mesh analysed is shown in Fig.1. The
model dimensions were 1mx1mx1.5m. The nailwas modelled to be initially in perfect contact withthe soil and the interaction between them issimulated using a penalty-type interface with afriction factor of 0.3. This type of interface
sufficiently represents the frictional interaction
between the soil and nail. Four nodded continuum
element was used in the analysis. Varying overburden pressure is applied on the top.

Many researchers [1,2,3] have carried out soil-nailpull-out tests. These researchers have tested
physical models of grouted soil nails in typicalHong Kong soil, that is, decomposed granitic soils.
The large scale pull-out tests were conducted to
study the influence of factors such as groutpressure, overburden pressure and soil saturation.
The large-scale pull-out tests of soil nail properly
represent the behaviour of soil nail constructed in afield slope.

The problem was run in three steps. In the first step
the effective self-weight of the soil material wasapplied using the body-force option in Abaqus.
During this step, geostatic command was invoked
to make sure that equilibrium was satisfied within
the soil. In the second step a surcharge load wasapplied and the nail was pulled out in the last step.
In all the steps, the loads were applied at a very
slow rate to ensure effective or drained loading
conditions. Also, the application of slow load will
prevent the generation of excess pore waterpressure anywhere within the finite element mesh.

In this paper, a three dimensional FE model has
been conducted to simulate pull-out tests of a soil
nail. A general purpose FE program, ABAQUS [4]is used in this study. The soil strength and the258Figure 1: Three dimensional finite element model for pull out simulation.
Constitutive models and parameters
Anisotropic elastic-perfectly-plastic model using
the Drucker – Prager failure criterion [13] isadopted. The model is expressed in terms of stressinvariants in ABAQUS as follows:

Where β the soil friction angle and d is is its
cohesion. The yield stress on the 𝑡𝑡 is given by𝑡𝑡 =Mean effective stress,
𝜎𝜎1′ + 𝜎𝜎2′ + 𝜎𝜎3′
𝑝𝑝′ =
3

1

For tri-axial compression conditions, the MohrCoulomb parameters can be converted to DruckerPrager parameters using2

𝑡𝑡𝑡𝑡𝑡𝑡(𝛽𝛽) =Where S = deviatoric stress and is defined as, 𝑠𝑠 =𝜎𝜎 − 𝑝𝑝′ 𝐼𝐼, where I is unit tensor.

𝑑𝑑 =The Drucker-Prager failure surface is given by
𝐹𝐹 = 𝑡𝑡 − 𝑝𝑝′ 𝑡𝑡𝑡𝑡𝑡𝑡(𝛽𝛽) − 𝑑𝑑 = 0

4

K = yield tension and compression stress ratio.

Mises equivalent stress,3
𝑞𝑞 = � (𝑆𝑆: 𝑆𝑆)2

𝑞𝑞
1
1 𝑟𝑟 3
�1 + − �1 − � � � �
2
𝐾𝐾
𝐾𝐾 𝑞𝑞

6𝑠𝑠𝑠𝑠𝑠𝑠(φ)
3 − 𝑠𝑠𝑠𝑠𝑠𝑠(φ)

18𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐(φ)
3 − 𝑠𝑠𝑠𝑠𝑠𝑠(φ)

56Where φ is the internal friction angle and c iseffective cohesion of soil defined in the MohrCoulomb yield criterion.

3

259

Table 1: Nail and soil parameters used in FE analysis
Nail:
Density, ρ (t/mm3)
Young’s modulus, E (MPa)
Poison’s ration, υSoil:
Density, ρ (t/mm3)
Young’s modulus, E (MPa)
Poison’s ration, υEffective cohesion, d (MPa)
Effective angle of friction, β(°)
Angle of dilation, (°)
Void ratio
Coefficient of permeability, k (m/s)
RK
α
Initial yield, 𝜺𝜺𝒊𝒊𝒊𝒊
𝒗𝒗𝒗𝒗𝒗𝒗 �𝟎𝟎

7.85E-9
2100000.2
1.8E-9
30
0.3
0.01
54
2
0.3
1E-5
1
0.8
0.01
0.01
0.0

The soil parameters shown in Table 1 were adopted
for the analysis and these parameters are typical forthe granitic soil.

Results
A three dimension finite element analysis of soilnail pull out was conducted under soil self-weightand surcharge conditions. The soil stress anddisplacements are obtained from the soil-nail pullout model. The theoretical results show that the
deformation and stress around the soil nail isdifferent when compared to the conventional soil
nails. Therefore, it has been shown, at least
theoretically, that this failure mechanism will resultin increased nail pull out capacity.

Figure 2 shown is a plane cut through the midsection of the model. It shows the contours of thezones of high shearing. Furthermore, the relative
displacements of the soil around the nail can clearly
indicate that the soil-nail failure slip line is notalong the soil nail interface. Therefore, it can beconcluded that the nail pull out capacity inferred
must be greater to the conventional soil nailingconstruction.

260

Figure 2: Soil-nail cut view showing displacements and deformations at the interface and around the nail.
Summary
It could be shown that Abaqus can be applied tosolve a wide range of boundary value problems in
the field of soil mechanics. This offers researchersa tool to examine some of the open problems ingeomechanics like the influence of construction
processes for geotechnical constructions, theoptimizationofgeotechnicalconstructions
regarding deformations or the optimization of
construction. It should not be concealed that thepresented simulations have limits caused bymodelling features and hardware resources.

References
[1]

[2]

Simulation of the soil–nail interaction was
conducted with the model. The model that has been
implemented into a finite element analysis will be
used used in a back analysis of a laboratory test
conducted on a scaled model. The soil-nailinteraction can be investigated and therefore overall
and internal failure mechanisms can be analysed.
The information obtained from the threedimensional FE analysis contributes to the deeper
understanding of the behaviour of the reinforcing
and failure mechanisms of nailed soil and can be
helpful for the correct design of nailed soil
structures.

[3]

[4]

261

W.-H. Zhou, J.-H. Yin, and C.-Y. Hong,"Finite element modelling of pullout
testing on a soil nail in a pullout box under
different overburden and grouting
pressures.(Report)," Canadian
Geotechnical Journal, vol. 48, p. 557(11),2011.
L.-J. Su, J.-H. Yin, and W.-H. Zhou,"Influences of overburden pressure andsoil dilation on soil nail pull-out
resistance," Computers and Geotechnics,
vol. 37, pp. 555-564, 2010.
K. Su and Y. Li, "Discussion of Extended
Drucker-Prager Yield Criterion in Slope
Stability Analysis," in Power and Energy
Engineering Conference, 2009. APPEEC
2009. Asia-Pacific, 2009, pp. 1-4.
A. D. S. S, "User Manual," ed, 2011.

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SIMPLIFIED DYNAMIC AXIAL HEAD PILE STIFFNESSIMPROVEMENT ANALYSIS FOR EXISTING PILED VIADUCT WITH
BASE REINFORCEMENTAGLIPAY Mary Roxanne1 and KONAGAI Kazuo2
Graduate Student, University of Tokyo, Japan; 2 Yokohama National University, Japan

1

ABSTRACT
Relatively high vertical accelerations were observed in some viaducts along the Tokaido Shinkansen Linesupported by pile groups embedded at intermediate sandy layers of adequate bearing capacity underlain by soft
soils. New piles in between existing pile groups and beam frame system at the pile head were added as part of
the retrofitting works in the substructure of two viaduct segments (Viaduct “A” and Viaduct “B”) in the intention
to reduce the vertical acceleration by increasing the dynamic stiffness of the foundation. Parametric analyses
using Tajimi and Shimamura’s Thin Layer Element Method (TLEM) were done to determine key parametersthat govern the improvement effect in the axial pile head stiffness of the retrofitted system of the two target
viaducts. Based on a simple assemblage of springs representing the retrofitting elements (existing and new piles,
and beams) and investigation on simple expression of axial stiffness of single pile, there are two importantparameters describing the improvement of axial pile head stiffness: (1) μnewLo,a,new/μexistingLo,a,existing and (2)EIb/μnewLo,a,newLs3. Although rigorous solutions are available, the nomographs developed as a function of thesetwo parameters provide a quick estimate of the improvement effect. With many RC rigid frames supported by
piled foundation similar to the target viaducts A and B, these nomographs will come handy for future retrofitting
works.
Keywords: Soil-Pile Interaction, Dynamic Axial Pile Head Stiffness, Pile Foundations, Viaduct Retrofitting

INTRODUCTION
With the enactment of the three major laws in
1950’s and 1960’s, namely the Industrial Water Act(1951), the Act of Regulation of Pumping-up of
Ground Water for Use in Building (1962) and the
Basic Law for Environmental Pollution Control(1967), followed by implementation of regulations
for practical control of pumping underground waters
in 1970’s, ground subsidence has been largely
stopped allowing JR Central to explore addition ofend bearing piles as part of retrofitting scheme with
the intention to reduce the vertical acceleration byincreasing the dynamic stiffness of the foundation.

Background of the Study
Monitoring and maintenance of the wholerailway system had always been a part of theoperation throughout the 48 years of existence of theTokaido Shinkansen line in the commitment tosafety and sustainability in their service to thecommuters, being one of Japan’s principaltransportation system crossing over the country’s
three largest metropolitan cities: Tokyo, Nagoya andOsaka.
Many of the viaducts carrying the Shinkansen
were supported by piles embedded at shallow depthsof adequate bearing capacity underlain by soft soils.
Supporting the viaducts with floating piles back thenwas a rational and realistic measure to help
minimize the uneven ground subsidence which had
been occurring gradually over the past years
primarily caused by groundwater extraction which
was noticeably worst during the Japan’s post war.
However, in these days during one of the regular
maintenance, vertical accelerations of these viaducts
supported by floating piles under train loads wereobserved to be relatively high. Though there are noserious signs of durability issues, long term effect of
exposure to frequent vibrations is to be mitigated.

Target Viaducts
In response to the problem, retrofitting works inthe substructures of two viaduct segments (Viaducts
A and B) along the Shinkansen Tokaido Linelocated in Aichi and Shiga Prefecture respectively,
had been done. The retrofitting works generally
involved addition of new end bearing piles andlongitudinal and transverse beams connecting theexisting pile group and new piles at their head levels.
This allows the foundation to act as a beam frame
system.
The substructure of Viaduct “A” originallyconsists of 8-3x3 pile groups. In 2008, underpinning262

GEOMATE-Nagoya, Nov.13-15, 2013

works were done which included driving a total of 6
end bearing steel piles. Properties of the new pile areshown in Table 1. The new piles were positioned in
between the existing pile groups along thelongitudinal direction. Longitudinal and transverse
RC beams having a cross section of 0.7m x 1.0m
were added to connect the existing and new piles. A
general layout of the retrofitted viaduct A in planand elevation views is shown in Fig. 1.

interaction between the piles and the surrounding
soil. This soil-pile interaction can be described by
the dynamic stiffness at the pile heads. Considering
the implemented retrofitted scheme, this study aims
to investigate the improvement performance andfurther define the key parameters contributing tosuch effect. Based on the parametric studies, it isimportant to provide simple approach for aneffective retrofitting scheme that may serve as a
useful guide in future retrofitting works given thatsome RC rigid frame viaducts along Tokaido line
similar to the target viaducts are also experiencing
comparatively high vertical accelerations.

On the other hand, Viaduct “B” prior to
retrofitting is supported by 8-5pile groups. This
viaduct was retrofitted in two stages. The first stage
was around late 2010 to March 2011 which included
addition of 6 concrete bored piles in between theexisting pile groups along the longitudinal directionand 2 concrete bored piles, one at each end of thesegment along the transverse direction. New pileparameters are shown in Table 1. The existing pilegroup and new piles were connected by 1.5m x 1.6m
longitudinal and transverse RC beams. The second
stage of retrofitting took place between March 2011
and July 2012 wherein depths of the beams were
thickened to 2.1m and braces were added to theviaduct columns. General layout of the retrofitted
substructure of viaduct B is shown in plan andelevation views in Fig. 2.

SOIL PILE INTERACTION
Simplified Expression for Axial Pile Head
Stiffness of Single Pile
Simple stiffness function of foundations ispreferred for a straightforward superposition withthe superstructure for a dynamic integrated
interaction system. Pile head stiffness can beapproximately expressed by an assembly of spring,
damper and mass as shown in Fig. 3.
Table 1 New pile parameters for the target viaducts

New Pile
Viaduct A
Viaduct B

Fig. 1Outer
radius, ro
(m)
0.300
0.500

Inner
radius, ri
(m)
0.288
0.000

Young’s
ModulusEs (GPa)
210
31

Plan and elevation of viaduct “A”[1]-[4]Objectives of the Study
With about 350 trains operating per day, thestructure experiences vibration constantly due to thepassing trains. The excitation induced by thesevibrations affects the structural response with theFig. 2

263

Plan and elevation of viaduct “B” [1]-[4]GEOMATE-Nagoya, Nov.13-15, 2013

The pile parameters considered were: (1) radius, (2)length, (3) Young’s modulus of elasticity. The soil
parameters: (4) shear modulus, (5) soil density and(6) Poisson’s ratio were varied between the shear
velocity range of 50m/s to 375m/s.
Table 2 Constant values for the parametric analysis

Fig. 3

pile properties
outer radius (ro),m
Young's modulus (Ep), (10)6 tf/m2
length (Lp), m
soil properties
shear modulus (μ), tf/m2
Poisson ratio (ν)
soil density (ρ), tf(s2/m4)

Dynamic pile head stiffness model: (a)rigorous solution of pile-soil system (b)approximate spring-damper-mass system

Konagai [5] introduced an important parameter,Lo,l as a function of pile bending stiffness andsurrounding soil’s shear modulus, that governs theoverall behavior of a rigidly capped flexible pilegroup subjected to lateral loadings. Analogously, thedeformation due to a vertical load for substantiallylong piles is largely noticeable in the upper part andbecomes negligible with increasing depth. This
remarkable deformation at the upper part, called
active length hereafter, is considered to be
dependent on characteristic length,

Lo, a EA

Based on this parametric study, a simple
approximate formula of axial pile head stiffness canbe suggested given by Eq. 2 and Eq. 3. The values ofthe equivalent stiffness, mass and damper are
obtained from the best fit line on various pile andsoil parameters considered. These non-dimensional
constant values are 1.6, 0.001 and 2.1 respectively as
seen in Fig. 4.

where EA is the axial stiffness of the pile and μ is
the shear modulus of the surrounding soil. Thus, theside soil reaction, which contributes largely to theaxial pile head stiffness is dependent on μLo,a. Thisparameter greatly simplifies the dynamic axial pilehead stiffness. It is used to normalize the dynamic
axial
pile
head
stiffness,
kzzrigorous
andcorrespondingly, frequency is normalized by theratio of shear wave velocity to the radius of pile
VT/ro. These non-dimensional parameters describe
the approximate expressions given by the following
equations.

 k zzrigorous   k eq  meq  ro 
Re
V 

 T 
 Lo,a k r 
Im zzrigorous   ceq  o i VT 
 Lo, a 

1098
0.440
0.182

For all piles with axial characteristic length lessthan length of pile, the imaginary and real parts lie ina unique curve. The real part forms a parabolic curve
where kzzrigorous/μLo,a decreases with increasing
frequency. Meanwhile, the imaginary part has alinear relationship, having an increasing trend withincreasing frequency.

(1)



0.250
3.161
50

The parameter, μLo,a,allows simple andstraightforward expression for the axial pile head
stiffness of single piles or equivalent single pile forpile groups. Thus, with a threshold of acceptablevalue of axial pile head stiffness, this simple
approach serves as an easy criteria to which existing
piled foundations can be categorized dependent on
retrofitting priority scale.

2

(2)

(3)

Parametricanalysisusing Tajimi
andShimamura’s Thin Layer Element Method [6] wasdone on end bearing piles of solid cross section
embedded in homogeneous infinite soil deposits. Six
cases of different soil-pile configurations wereconsidered varying one specific soil or pileparameter while keeping other variables constant.

Fig. 4264

Real and imaginary parts of axial pile head
stiffness for Loa/Lp < 1

GEOMATE-Nagoya, Nov.13-15, 2013

Spring Assemblage Analysis for the Retrofitted
Systemcharacteristic lengths of new and existing piles, thus
the ratio is μnewLo,a,new/μexistingLo,a,existing .

Rigorous solution allows derivation of pile head
stiffness for any complicated soil-pile profiles.
However, it is important to highlight the key
parameters that govern the performance of theaddition of new piles and corresponding connecting
beams as a retrofitted scheme on existing pilefoundations. With a simple assemblage of springs as
in Fig.5, the effect of addition of new piles and theconnecting beam can be described.

Shear moduli, μnew and μexisting, may be cancelled
out as long as both the new and existing piles areembedded in the same and homogeneous soils.
However, for non-homogeneous soil deposits, there
is no guarantee that μnew is identical to μexisting,because these representative shear moduli are to be
estimated over the active pile lengths, which candiffer between the new and existing piles. Therefore,
the shear moduli for both new and existing piles areto be left in this stiffness ration.

Fig. 5The vertical stiffness of the longitudinal beam is
proportional to EIb/Ls3 where EIb and Ls is the beamvertical bending stiffness and the space between
existing and new piles respectively. Therefore, theratio between the equivalent spring constants forbeam and existing pile is dependent on
EIb/μnewLo,a,newLs3.

Simple spring model describing the effectof new pile and connecting beam

As summary, the improvement on the axial pilehead stiffness of the existing pile can be described
with
the
two
parameters:(1)
μnewLo,a,new/μexistingLo,a,existing and (2) EIb/μnewLo,a,newLs3.

The improved stiffness can be expressed as theequivalent spring of the system given by Eq. 4.

1

kzz ,improved  kzz ,existing 

1
kbeam



Development of Dynamic Pile Head Stiffness
Nomograph(4)

1kzz , newAnalysis on the effect of the addition of newpiles and beams were done as a function of theabovementioned parameters and are summarized in
nomographs. Two model configurations wereconsidered: (1) two rows of frames connected bytransverse beams and (2) same with case 1 but withaddition of new piles along the transverse direction
at ends of the segments (Fig. 6). Every single line offrame has 7 end bearing piles of uniform
longitudinal spacing, Ls, embedded in a
homogeneous soil deposit. The new piles areembedded in between existing piles. The transverse
spacing is 1.73Ls similar to the configuration of thetwo target viaducts as the standard configuration
throughout the entire stretch of Tokaido Shinkansen
Line. The radius of the existing piles is held
constant while varying the radius of the new piles toobtain different μnewLo,a,new/μexistingLo,a,existing ratios
ranging from 0 to 2.0. Note that the Lo,a,new andLo,a,existing considered were less than the actual lengthof pile Lp. For each EIb/μnewLo,a,newLs3 ratio, there are
4 different cases of beam bending stiffness
considered taken cared by the change in Young’s
modulus (Eb = 26.5, 80, 120, and 200GPa). From therigorous solution, approximate axial pile head
stiffness is derived with the best fit line and isdivided with the simplified axial pile head stiffness
for single piles for Lo,a<Lp.

Simplifying further gives,k zz ,improved  k zz ,existing kbeamk zz ,newkbeam  k zz ,newDividing both sides byk zz ,existing(5)

gives theimprovement effect, kbeam  k zz ,new  k zz ,existing  k zz ,existing k zz ,improved 1 
k zz ,existing kbeam   k zz ,new   k zz ,existing    k zz ,existing 

 


(6)

From Eq. 6, the improvement effect is essentiallya function of the ratio of the stiffness of the new pileto the existing pile (kzz,new/kzz,existing) and the ratio ofthe vertical stiffness of the longitudinal beams to theexisting pile (kbeam/kzz,existing).
It has been established that the axial pile head ofpile is proportional to μLo,a. Therefore, the ratio
between the equivalent spring constants for the
existing and new piles must be dependent on theratio of the product of the shear modulus and265

GEOMATE-Nagoya, Nov.13-15, 2013

Application to Real Viaducts
In application to real viaducts, the two key
parameters were derived for viaduct A and B basedon the pile and beam properties of their foundationand their surrounding soil characteristics. The
existing pile group and new piles of the two target
viaducts were assumed to be embedded in a
homogeneous soil deposit by using representative
shear moduli of the actual non-homogeneous
stratified soil deposits along the active pile lengths.
The representative shear moduli were derived along
this depth by getting the weighted average of theshear moduli of the soil deposits of the viaducts.
Thus, the value of key parameters to describe theimprovement effect of the retrofitting scheme

Fig. 6

implemented in these viaducts can be easily derived
as summarized in Table 3. These are subsequently
plotted in their corresponding nomograph as seen in
Fig. 6.
Table 3 Values of the key parameters.

μnewLo,a,new/μexistingLo,a,existing
EIb/μnewLo,a,newLs3

A
0.54
2.00

B
0.061
0.472

Given a small value for the two key parameters,
little improvement can be seen in Viaduct A.
However, viaduct B exhibits increase in the
improvement by a factor of ~2.0 and ~3.0 for cornerand center piles.

(a.1) corner pile(a.2) center pile(b.1) corner pile(b.2) center pile

Improvement in axial pile head stiffness over frequency in (a.1-a.2) viaduct A and (b.1-b.2) viaduct B

Comparison with Static Locomotive Tests andRigorous Solution
In both viaducts, improvement is higher in center
piles relative to corner piles. Stiffnesses of theimmediate neighboring piles and corresponding
connecting beams have predominant influence on
the improvement of the axial pile head stiffness.

Having stiffer piles installed in viaduct B and thicker
beams, there is a remarkable improvement in the
dynamic axial pile heads stiffness having a factor of~1.7 and ~2.5 for corner and center piles
respectively while very little improvement is seen in
viaduct A based on rigorous solutions. Same generaltrend is observed from results of the static
locomotive loading test, wherein there is a twofold
266

GEOMATE-Nagoya, Nov.13-15, 2013

increase in the average axial pile head stiffness of all
8 pile group in viaduct B while little improvement isseen in viaduct A (Table 4).

works to increase the dynamic axial pile head
stiffness and furthermore categorize based on
retrofitting priority scale.

The general trends of results in the nomograph
are approximately the same with that of the static
locomotive tests and rigorous solutions (Fig. 7).

Upon decision of needed retrofitting works, thenomographs developed in this study provide a quick
estimate of the improvement effect using the two
key parameters: μnewLo,a,new/μexistingLo,a,existingandEIb/μnewLo,a,newLs3. Stiffnesses of neighboring piles
and corresponding beams have predominant
influence on the improvement of the axial pile head
stiffness. For a non-homogeneous soil deposit
present in most cases, the active length is a goodparameter for getting representative shear moduli fora straightforward calculation to derive the key
parameters. Tokaido Shinkansen line has 4000 RC
rigid frames and approximately half of it is
supported by similar foundations of viaducts A andB, having possible the same problems of relatively
high vertical accelerations. The nomographs withreadily available information will come handy for
future retrofitting works.

Table 4 Average settlement of all 8 columns in the
upbound and downbound side before andafter retrofitting from the static locomotive
test
andcorresponding
stiffness
improvement [1]-[4].
Viaduct

Beforeretrofitting

Afterretrofitting

Stiffness
ImprovementA-0.22mm-0.17mm1.29

B-0.33mm-0.18mm1.83

ACKNOWLEDGEMENTS(a)

Thanks to Ms. Chiho Takeguchi, Mr. AtsushiDoi and Mr. Motoyuki Azuma, and the Structural
Design Team of Structural Design Group 1,
Technology Research and Development Department,
JR Central for providing the necessary data and to
Monbukagakusho Scholarship for the financial
support and making this study possible.
REFERENCES(b)

Fig. 7

Improvement in axial pile head stiffness in(a) viaduct A and (b) viaduct B

CONCLUSION
Rigorous solutions using the Thin Layer Element
Method can deal with any complex soil-pileconfigurations, yet simplifications are needed tosave time and effort. Simple expressions of axial pilehead stiffness for single pile or equivalent single pileof pile groups which is largely dependent on μLo,aprovide a simple and straightforward approach for
determining axial pile head stiffness of existing piled
viaducts. With a threshold of acceptable figure forthe axial pile head stiffness, decision can be madewhich existing piled viaducts demands retrofitting[1] Azuma M. et al, “Vertical Vibration Reductionof Existing RC Viaduct with Base
Reinforcement”, Journal of StructuralEngineering , Vol. 156A, 2010.
[2] Azuma M. et al, “Effect of Base Reinforcementof Existing Railway Viaducts with new piles
and underground beams”, Annual Convention ofJapan Concrete Institute, Vol. 32, No. 2, July
2010.
[3] JR Data for target viaducts (Viaduct “A” andViaduct “B”): General Layout, Pile and Soil
Properties, and numerical results.
[4] Imai K., et al., “Maintenance and strengtheningof existing Railway RC Viaducts”, Bridge andFoundation Engineering 2012, No. 10.
[5] Konagai K., Ahsan, R., Maruyama, D. “Simple
Expression of the Dynamic Stiffness of Grouped
Piles in Sway Motion”, Journal of Earthquake
Engineering, 4(3), 2000, pp. 1-22.
[6] Tajimi H., Shimomura Y., “Dynamic Analysis
of Soil-Structure Interaction by Thin Layer
Element Method” (in Japanese), Architectural
Institute of Japan, 1976, pp. 41–51.

267

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PFC3D NUMERICAL EXPERIMENTS OF SELF-BORING IN-SITU
SHEAR PRESSURE-METER MODEL TEST
Yafei Zhang1, Guangli Xu1 and Jidong Teng2
Faculty of Engineering, China University of Geosciences (Wuhan), China; 2 Faculty of Engineering,
Kyushu University, Japan

1

ABSTRACTThe self-boring in-situ shear pressure-meter (SBISP) has little to no disturbance to the surrounding soil. It
can simultaneously determine the deformation and strength parameter of easily disturbed soil at depth. However,the deformation response of surrounding soil under multilevel loading process in SBISP test has seldom beenstudied up to present. At the same time, the determination of the deformation parameter of the soil is closely
related to its deformation mechanism. Based on this, the SBISP model test was simulated by PFC3D (Particle
Flow Code in three Dimensions) program in this study. The results of numerical experiments showed that thedisplacement of particles in central area increased with the shear stress imposed stepwise, and the direction of
displacement vector showed a clearly preferred direction. Additionally, with the increase of the consolidationpressure, the influence area of the numerical sample diminished gradually. The motion trails of particles were
step-like lines; the steps were becoming gentler as the distances from particle to the probing rob center
increasing.
Keywords: Self-boring In-situ Shear Pressure-meter Test; Particle Flow; Deformation Response; Motion Trails;

the practicability of the SBISP was proved [2]. In
another study, the authors confirmed that the shear
strength of soil can be approximately interpreted by
the friction strength of the interface of the roughprobe and surrounding soil, which can be used asstrength parameter of soil directly [3]. The previous
study focused mainly on the introduction of test
methods, the interpretation of test mechanism, andthe comparison and verification with other test
methods, but the deformation process of easily
disturbed soil under multilevel loading condition has
not been discussed. Furthermore, the deformationand destruction of easily disturbed soil is mainly due
to the translation and rotation of each soil particles
and their interaction, which is a macroscopic
phenomenon caused by the change of microstructure. Therefore, it is of great necessary to study
the deformation response of soil particles during the
SBISP test process.
The Particle Flow Code in Three Dimension(PFC3D) was put forward in 1979 to simulate themovement of spherical particles and their interaction[4]. PFC3D program has great advantages insimulating the mechanical response of granular
substance [5]. Based on the laboratory model test,
we establish a numerical model by PFC3D tosimulate the multilevel loading process of SBISP
test in this study, and then comparatively analyze thevariation of displacement fields of the numericalsample under different overlaying consolidationpressures. Moreover, the motion trails of particles ofdifferent positions are monitored to study the

INTRODUCTION
With the development of the geotechnicalengineering test technology, it has been realized thatobtaining undisturbed or less disturbed soil sample
to conduct conventional laboratory testing is very
difficult [1], which impels related researchers todevelop new in-suit testing instruments to exclude
the disturbance while sampling. A new in suit test
instrument, the self-boring in-situ shear pressuremeter (SBISP), has been developed in 2007 [2]based on conventional in suit test methods both athome and abroad. The SBISP test is a combinationof the pressure-meter test (determination of thedeformation modulus) and the direct shear test
(determination of the shear strength). The
deformation and shear strength parameters can bedirectly determined simultaneously compared withprevious traditional test methods. Moreover, it can
reduce the disturbance of surrounding soil as muchas possible by self-boring. Hence, the SBISP test isparticularly suitable for soils that are difficult tosample, easily disturbed and with low strength suchas sandy soil and silty soil.
The experimental studies of SBISP were few.
The apparatus, mechanism and procedure of SBISP
test were first applied in pile foundation engineering
around 2007. And the shear strength obtained by
SBISP test was compared with the test results of theuniaxial compressive test and the undrained tri-axial
compressive test in a project; the comparison
showed that they were almost the same, by which
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GEOMATE-Nagoya, Nov.13-15, 2013

micromechanical characteristic of the surrounding
sand in the process of expansion and shearing of theprobe.

It was shown that the tested data of the tri-axialchamber can be interpreted by theoretical analysis
methods mentioned in paper [3], and the interpreted
results agreed well with other established testing
methods. Therefore, the new test technology may be
put into use in situ. The PFC3D numerical model
established below is based on the verification test
above.

BRIEF INTRODUCTION OF LABORATORYTEST
To verify the feasibility of strength parameter ofsoil obtained by multilevel loading in SBISP test.
The laboratory verification test [6] was conducted ina large tri-axial chamber developed in Kyushu
University of Japan. The sketch of the tri-axialchamber is shown in Fig. 1.

MODEL ESTABLISHMENT OF PFC3D
Boundary and Probe Model of SBISPTo improve the computational efficiency, thesize of the large tri-axial chamber and probe isproperly reduced to decrease the number of particles
generated. As shown in Fig. 2(1), the radius andheight of test chamber are 150 mm and 350 mm
respectively; it consists of one general cylindricalwall (wall 3) and two standard walls (wall 5, 6). The
probe consists of three general cylindrical walls(walls 1, 7, 8; wall 1 is a cylindrical wall, but walls 7
and 8 are truncated cone walls with an inclination
angle of 45°). The original radius of the probe is 15mm, with a height of 180mm; so the probe has alength to diameter ratio (L/D) value of 6. The
diameter of the chamber is 10 times that of the probe.
The radius of the probing rod is 15 mm as well, andis represented by one general cylindrical wall (wall2).

Fig. 1

Sketch of tri-axil chamber with probe of
SBISP

The tri-axial chamber had a diameter of 900mm,
and was 1500mm high. The diameter and height ofthe probe were 86mm and 500mm, respectively. The
Okagaki dry sand employed in the laboratory test
was got from Okagaki town, Fukuoka Prefecture. It
was uniform fine sand of badly graded which mainly
consists of quartz and feldspar. The soil sample was
generated by air pluviating method. The soil sample
during testing had a porosity n value of 0.44. The
mean particle size D50 and the specific density ρ
are 0.26mm and 2.63 g/cm3 respectively.
The tri-axial chamber had the capability to apply
the overburden pressure and up-pull or down-pushstresses independently. The overburden pressure
was executed to the surface of the soil sample
through the high-pressure air bag. And the up-pullstress was applied by the vertical loading cell.
During loading process, the earth pressure wasmonitored by the pressure cells.

Fig. 2

Test chamber model and numerical sample

The functions of each wall are explained asfollows. The initial consolidation load is applied tothe top of the simulated domain by wall 6. The radial
and vertical velocities are specified successively forwalls 1, 7 and 8 which exerting the radial- and shearforce on the domain. To simulate a rigid probe, we
specify a normal- and shear-stiffness of 1×1010N•m-1
for the probe. The mesoparameters of the walls areshown in Table 1.
Table 1 Meso-parameter of model walls
Number of
walls
269

NormalShear
Friction
stiffness
stiffness coefficientk n （N·m-1） k s （N·m-1）
fc

GEOMATE-Nagoya, Nov.13-15, 2013

1
2、3、5、67、8

1×10101×10101×10101×1010
—
—

0.6
—
—

Note: D is the diameter of the probing rod.
The eventual numerical sample of sand particles
is a hollow cylinder and having a total of 89,048
particles. The numerical sample can be seen in Fig.
2(2).

Sand Sample Model of PFC3D
The spherical particles generated can be divided
into two parts from the probe outward. In order toimprove the operation rate in the premise of
ensuring the precision of calculation, we reduce thenumber of particles by generating particles of small
radius in central region and large radius in outerregion. The radius of the central region is 6 times
that of the probing rod.
Based on the particle size in the laboratory
verification test, the particles in central region are
generated. To reduce the number of particles innumerical simulation, the actual grain size isenlarged properly. In this simulation, the average
particle size, D50 of the numerical sample is 5.2 mm
which is 20 times larger than the actual grain size.
The large particles in the outer region are generated
first, followed by the fine particles in the central
region. The mesoparameters of the large particles in
the outer region are deduced based on themesoparameters of the particles in the central region.
When the Young’s modulus of spherical particles isconstant, the relationship of particle stiffness andparticle radius is [7]:

E=

kn
4R

Simulation of Loading Process
According to the loading process of laboratory
verification test of SBISP, the loading procedure ofthis simulation is designed as follows: (1) The
consolidation stress σ v is applied firstly byadjusting the velocity of standard wall 6 using a
servo-control function. When the requested value ofthe consolidation stress is reached, keep it constant.
(2) Then the requested value of the first grade radialstress qV 1 is obtained as the consolidation stress didin procedure (1). The difference is that, at this time,the velocities we adjusting are the cylindrical walls 1,
7 and 8. Keep the requested value of qV 1 constant as
well. (3) The first grade shear-stress qH 1 is applied
to the surrounding soil by specifying a constantvelocity of the probe. When it reaches the peakvalue, terminates the loading. The loading process ofthe shear-stress is automatically controlled bywriting a FISH function. (4) Then the next grade
radial-stress qV 2 is applied. When it reaches therequested value, applies the next grade shear-stressqH 2 . Repeat it five times.
For the purpose of comparing the variation
characteristic of displacement field of the numericalassembly under different consolidation pressures,the pre-consolidation stresses applied are 100kPa
and 200kPa respectively in this simulation. The
corresponding radial-stresses of each grade are
150kPa 、 400kPa 、 600kPa 、 800kPa and 1MPa,
respectively.

(1)

where E is the Young’s modulus; kn is the particle
stiffness; R is the average radius of sphericalparticles.
According to Eq. (1), when the same material issimulated by particles of different radius, the particle
contact stiffness is proportional to the particle radius.
Therefore, the stiffness of large particles in the outerregion can be derived by the stiffness of fineparticles in the central region. The meso-parameterof fine particles in the central region is obtained bycomparison with tri-axial test simulated by PFC.
Partitions and meso-parameters of numerical sample
are listed in Table 2.

Verification of the Results of the Numerical
Simulation
The applicability of the simulation of PFC isconfirmed by comparing the macroscopic curve of
numerical test and the results of the field experimentof SBISP. Fig. 3 is a general test curve of SBISP
which describes the relationship of shear-stress andshear-displacement under the radial-stress of eachlevel. Where qV is radial-stress, qH is shear-stress,

Table 2 Partitions and meso-parameter of numericalsampleand QH is shear-force.
Fig. 4 shows the shear stress-shear displacement
curve obtained by numerical simulation of SBISP by
PFC. It can be seen from Fig.4 that, when applying
the shear-stress of each level at the initial stage,
there is always a sharp peak with steep rise/fallwhich is shown in the circle in Fig. 6. This can beinterpreted by the law of friction [8]: The static

Radius Normal Density Frictionofstiffness ρ (kg·m- coefficient
Region Range particles k (N·m- s 3)
fc
n
1
/mm
)
central
1-4D 2-3.2
3×105
2630
2.5
regionouter
4-10D 4-6.2 5.88×105 2630
2.5
region270

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 4

friction force Ff 0 increases with the external force

F when the object does not slide relative to thehorizontal plane. The object is on the point of sliding
as F reaches a certain value. At this point the static
friction force reaches the maximum value, which is
known as the maximum static friction force Ff 0 m .

Through the comparison of Fig. 3 and Fig. 4, it
can be seen that the stress and deformation response
obtained by numerical experiment of PFC3D is ofgood agreement with that of the field test of the
SBISP. With the increase of radial-stress of each
grade, the peak values of shear-stress of each level
increase as well. However, the growth rate of shearstress decreases with the increase of the shear
displacement under the radial-stress of the samelevel, and approaches the peak value finally. It
demonstrates that the numerical model built canreflect the general law of the sand particles in theloading process of SBISP, and the numerical model
established by PFC3D in this study is reasonable.

Experiments show that the relationship between the
maximum static friction force and the positive
pressure FN is
Ff 0 = µ0 FN(2)where µ0 represents the static friction coefficient.
When the object slides on the plane, the sliding
friction force Ff it subjected isFf = µ FNANALYSIS OF THE RESULTS OF THE
NUMERICAL EXPERIMENT OF PFC3D(3)

Evolution Process of the Displacement Field
under Different Consolidation Pressures

where µ is the sliding friction coefficient. The
sliding friction coefficient is usually less than thestatic friction coefficient when the relative velocityof the object is not too large. Therefore, this canreflects the validity of the PFC3D program in
simulating the actual physical phenomenon.

Fig. 3The variation of the displacement field of theparticles surrounding the probe is monitored under
different consolidation pressures. The distribution of
displacement vectors of particles, after the peakvalue of the shear-stress of each level has beenreached under the different consolidation pressures,is shown in Fig. 5. Fig. 5(1), (2) are the distributionof displacement vectors of particles of each level
under the consolidation pressure of 100kPa, and Fig.
5(3), (4) are that of 200kPa. It can be seen that, nomatter the overlaying consolidation pressure is
100kPa or 200kPa, the influence area mainly lies in
the central region of small particles. At the sametime, the displacement field in the outer region of
the large particles has no significant change.
Moreover, the displacement of particles in thecentral region increases obviously with the peakvalue of shear-stress of each level increases; and thedisplacement vectors have a good directionality
gradually. Under the peak values of the third and thefifth grade shear-stresses, displacement vectors of
the particles surrounding the probe has an upward
directionality obviously. The shape of thedisplacement vectors of particles within the height ofthe probe is a reverse cone.
From the comparison of the two columns of Fig.
5, it can be seen that the displacement of particles
decreases as the consolidation pressure increases.
This is because the bigger the consolidation pressure
applied, the greater the resistance particles sufferedfrom while moving driven by the probe.

The general curve of SBISP tests

Shear stress qH /(kPa)qV5 = 1MPa350
qV4 = 800kPa
300
qV3 = 600kPa
250
qV2 = 400kPa
200
150 qV1 = 150kPa
100
σV = 100kPa
50
Shear stress00
5
10 15 20 25
Shear displacement δH /(mm)(1)

Shear stress qH /(kPa)

400
350
300
250
200
150
100
50

(2)

qV5 = 1MPa
qV4 = 800kPa
qV3 = 600kPa
qV2 = 400kPa
qV1 = 150kPa

Numerical simulation curve of SBISP tests

σV = 200kPa
Shear stress

0 5 10 15 20 25 30
Shear displacement δH /(mm)271

GEOMATE-Nagoya, Nov.13-15, 2013

Meanwhile, the influence area of the probe on thesurrounding particles is increasing as well. But the
influence area mainly locates at the height of theprobe.
It can be found from the comparison of the
figures of both sides that, although the radialstresses of each level applied are the same, theinfluence area of the probe reduces obviously as theconsolidation pressure increases. And the influence
area of the probe is mainly located in the central
region. This is in consistent with the phenomenon
observed in Fig. 5.
Motion Trails of the Particles

Fig. 5The motion trails of particles surrounding theprobe are studied. Under the consolidation pressureof 200kPa, the position of particles with different
distance from the probe center is monitored and the
motion trails of the particles are plotted in the XYZ
space. It should be noted that the initial positions of
the particles monitored mainly located in the XZ
plane. The distances form the particles monitored tothe probing rod center are around 15mm, 20mm,
30mm, 40mm, 50mm, 60mm, 70mm and 80mm,
respectively; and two particles are selected at eachdistance. As space is limited, the motion trails ofparticles illustrated in this paper are only that at the
distances of 15mm, 40mm and 70mm.
It should be noted that “id” represents thenumber of the particle monitored, and “r” represents
the distance from the particle to the probing rod
center in Fig. 8. The projection of the motion trailson the XZ plane is represented by black lines; whilethat on the XY plane are blue lines. It can be seenthat the projection of the motion trails on the XZ
plane is a step-like line. This phenomenon reflectsthat with the expansion and elevation of the probe,
the particles surrounding the probe are moving along
the radial and vertical direction continuously. Whenthe particles contact with the probe, the steps are in a
sharp corner form. However, when the distance tothe probe increase, the steps are in an arc shape.
Moreover, the radian of the arc is increasing as the
distance increase, and becoming much gentler. It
indicates that the closer the distance is, the greater
the degree of the influence suffered from the probe
movement. In addition, the motion trails in the XYZ
space and its projection on the XY plane areirregular, but the motion trails is almost moving
along a unique horizontal direction on the same step
plane. Gibson and Anderson [9] put forward themethod to interpret the self-boring pressure-meter
test for the first time. They assumed that thepressure-meter was infinitely long, so that the
deformation of the surrounding soil takes place
under conditions of axial symmetry and plane strain.
The phenomenon shown in Fig. 8 indirectly provesthat these assumptions are reasonable in someDistribution of displacement vectors ofparticles

In order to observe the impact of inflation of theprobe on the surrounding particles intuitively, theparticles are painted by different colors according to
the magnitude of their displacement. In this study,
the displacement contour map is plotted
automatically by a ‘color function’ written with
FISH language. Fig. 6 is a displacement contour
map of numerical sample.

Fig. 6

Displacement contour map of numericalsample

The two figures on the left are displacement
contour maps generated after the application of theradial-stress of each level under the consolidationpressure of 100kPa, while the three figures on theright are that of the consolidation pressure of 200kPa.
It should be noted that the displacement of particles
monitored in this diagram is that in the XY plane. As
we can see, the diameter of the probe increases withthe radial-stress of each level applied step by step.
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GEOMATE-Nagoya, Nov.13-15, 2013degree.

surrounding the probe is a reversed cone under thefifth grade shear-stress. Moreover, the displacementof particles surrounding the probe reduces as theconsolidation pressure increases, so does theinfluence area.
The motion trails of particles are a step-like line.
Furthermore, as the distance from the particles to the
probing rod increases, the steps are becoming
gentler.
ACKNOWLEDGEMENTS
The authors acknowledge the financial support
provided by the National Natural Science
Foundation of China (Contract No: 41072218).
REFERENCES

Fig. 7[1] Shen Z J, “Soil sampling on site or in-situ
testing—a preliminary research on developmentof soil parameters testing technology”. Chinese
Journal of Geotechnical Engineering, Vol. 18,
Sep. 1996, pp. 90–91.
[2] Zhang X L, Xu G L, Wang C Y, et al.,“Development and application of self-boring insitu shear pressuremeter”, Rock and Soil
Mechanics, Vol. 28(Suup.), Oct. 2007, pp. 909913+918.
[3] Xu G L, Zhang X L, Wang C Y, “Development
and application of self-boring in-situ shear
pressuremeter”,
Chinese
Journalof
Geotechnical Engineering, Vol. 32, Jun. 2010,
pp. 950-955.
[4] Cundall P A, Strack O D L, “A discrete
numerical model for graunlar assemblies”,
Geotechnique, Vol. 29, 1979, pp. 47-65.
[5] Zhou J, Chi Y, “Mesomechanical simulation ofsand mechanical properties”, Rock and Soil
Mechanics, Vol. 24, Dec. 2003, pp. 901-906.
[6] Xu G L, Zhang X L, Wang C Y, et al, The new
self-boring shear pressuremeter and its
application. Wuhan: China University ofGeosciences Press, 2009, ch.4.
[7] Deng Y B, Zhou J, Liu W B, et al., “PFC
numerical simulation of augered piling of soil
displacement screw piles”, Chinese Journal of
Geotechnical Engineering, Vol. 33, Sep. 2011,
pp. 1391-1398.
[8] Ma W W, Physics. Beijin: Higher Education
Press, 1999, ch.2.
[9] Gibson R E, Anderson W F. “In-situ
measurement of soil properties with thepressuremeter”, Civil Engineering Public Works
Review, Vol. 56, 1961, pp. 615-618.

Motion trails of particles

CONCLUSIONS
The results of the numerical experiment suggest
the influence of the probe on the displacement of theparticles has a sectionalized characteristic. The
particles in the central region have been influenced
significantly, but the big particles in the outer region
have seldom been affected. It is found that thedisplacement of the particles in the central region
increases with the shear-stress increases gradually,and has an upward directionality step by step; theshape of the displacement vectors of particles

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DYNAMIC ANALYSIS OF SLOPE FAILURE USING THE MESH-FREE
SPH METHOD
N. Hiraoka1, A. Oya1, Ha H. Bui2, P. Rajeev2 and R. Fukagawa1
Department of Civil Engineering, Ritsumeikan University, Japan;
2
Department of Civil Engineering, Monash University, Australia

1

ABSTRACTIn the past few decades, majority of dynamic behavior of slope have been conducted using the finite element
method (FEM). However, earthquakes often cause large deformation and post-seismic soil deformation which isdifficult to predict using the FEM due to mesh distortion issues. As an alternative numerical method, thesmoothed particle hydrodynamics (SPH) has been recently applied to geotechnical field and showed to be a
promising numerical technique to handle large deformation and post-failure behavior of geomaterials. In thispaper, taking into consideration of this advantage, the SPH method is applied to simulate response of a slope
subject to seismic loading. Reliability of SPH results was assessed by comparing with experimental data
available in the literature. It is shown that the SPH method could qualitatively predict slope failure behavior
observed in the experiment.
Keywords: Dynamic analysis, seismic deformation, SPH, slope failure, elasto-plastic analysis

INTRODUCTIONSIMULATION APPROACH

Seismic induced lateral displacement in a slope
is traditionally determined by Newmark’s sliding
block approach in design and assessment [1].
However, this method has limitations because of its
simplicity. Nowadays, FEM (Finite Element
Method), DEM (Distinct Element Method) [2] andFDM (Finite Difference Method) are used tosimulate the co-seismic
andpost-seismic
deformation of a slope subjected to seismic load.
However, FEM and FDM methods have somedisadvantage such as mesh distortion due to large
deformation induced by soil failure. DEM, which isbased on continuum mechanics, is favorable tosimulate large deformation. However, DEM iscomputationally expensive to simulate the large
problem. Moreover, it is quite difficult to specify
DEM parameters for contact models.
Alternatively, the mesh-free smoothed particle
hydrodynamics (SPH) [3] [4] has been applied to
dynamic analysis of geomaterials [5] and shown thatthe method can be used effectively to predict thelarge deformation due to soil failure such as slope
failure. In this paper, the SPH method is used to
study the seismic behavior of a slope. The coseismic slope displacements and failure surface arecalculated
and compared with laboratory
experimental results. The soil behavior is modeledwith the elasto-plastic Drucker-Prager model. The
artificial time history is used to simulate theearthquake loading. The seismic loading is applied
to the slope by enforcing the motion of the model
boundaries.

Soil constitutive model in SPH
As stated, soil is modeled using the elasticplastic Drucker-Prager constitutive model. The
implementation of this soil model in the SPH
framework was already presented by Bui et al. [6].
The key equation used to represent the advance soil
stresses are summarized here for brevity. The stressstrain relationship of Drucker-Prager’s model with
non-associate flow rule can be written as follow,dσ αβ= 2Geαβ + Kεγγ δ αβdt
G αβ s− λ 9 K sin ψδ αβ +


J2



(1)

with the rate of change of plastic multiplier 𝜆𝜆̇,λ =3αKε γγ + (G / J 2 ) sαβ εαβ
27α φ K sinψ + G(2)

where G is the elastic shear modulus; K is theelastic bulk modulus; 𝑒𝑒̇ is the deviatoric shear strain
tensor; 𝜀𝜀̇ is the elastic strain tensor; ψ the isdilatancy angle; δ is the Kronecker’s delta; s is thedeviatoric shear stress; J 2 is the second invariants ofstress tensor; and α φ is the Drucker-Prager’s
constant. These equations are discretized with SPH
as following,

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GEOMATE-Nagoya, Nov.13-15, 2013

dσ iαβ= σ iαβ ω iβγ + σ iβγ ω iαγ + 2Geiαβ + Kε γγ δ αβdt
G αβ − λ 9 K sinψδ αβ +
s


J2



(

)

(3)

i’

3α Kε γγ + G J 2 siαβ εiαβλ = φ27αφ K sinψ + G

ε

Ghost
particles

Fig.1

)

(

Real SPH
particles

Arrangement and treatment of ghost particles

where σ G and σ R are the stress tensor of ghost
and real SPH particles, respectively. The velocity ofghost particles v G is represented as follows [6-7],∂Wij N m j β β ∂Wij 
1 N m (5)=  ∑ j vαj − viα+∑v j − vi∂xiβ j =1 ρ j∂xiα 
2  j =1 ρ j

(

i

(4)

where i indicates a particle under consideration.
𝜀𝜀̇ , 𝜔𝜔̇ are the strain rate and spin rate tensors,
respectively, which are discretized as below,
αβBoundary planekh)− v + 2vwall
vG =  R
vR


N m
∂W
∂W 
1 N mω αβ =  ∑ j (vαj − viα ) βij − ∑ j (v βj − viβ ) αij  (6)
∂xi
∂xi 
2  j =1 ρ j
j =1 ρ j

if vG is normal velocity
if vG is shear velocity(9)where 𝑗𝑗 = 1,2, … , 𝑁𝑁 are particles in the influence
domain of a certain particle i. W indicates functionof approximation so-called “kernel function”.
The particle position is finally determined asfollows,

where v R is the velocity of real particles and v wallis used to represent moving wall. In this paper, theseismic wave velocity on the roller boundary is
enforced through v wall . In addition, the roller
boundary is also subjected to motion according to
the seismic motion input.

dxiα
= viα
dt

Full-fixity boundary with seismic motion(7)

The second type of boundary condition which isoften used to restraint soil motions at the solidboundary is the full-fixity boundary [8]. In SPH, thefully-fixity boundary condition can be modeledusing “boundary particles” which are placed outside
the wall boundary as shown in Fig. 2. These
particles are normally fixed in the space and carry
the same material properties as soil particles [6-7],
except the velocity. In this paper, the same approachpresented by Bui et al. [6-7] which can be dated
back to the original work proposed by Morris et al.
[9] is applied. Accordingly, velocity of boundary
particles are updated using the following equation,

Further details about SPH framework for soil canbe found in [6] and [7].
Boundary conditions and earthquake loading
Accuracy and stability of computation depend on
the boundary conditions. In this paper, two types ofboundary condition are considered: free-roller andfull-fixity. Details of these boundary conditions andtheir inclusion of seismic motion are discussed in thefollowing section.
Free-roller boundary with seismic motionv AB = v A − vB = β v A

Free-roller boundary condition is usually used torepresent a far field boundary condition. At the freeroller boundary, soil particles are free to move in the
direction which is parallel to the wall boundary. In
SPH, the free-roller boundary can be simulatedusing ghost particles [8] which are placed
symmetrically on the opposite side of the wallboundary as shown in Fig.1. The stress boundary
condition is set as follow [6], σ Rαβ if α = β
− σ Rαβ if α ≠ β

σ Gαβ = d 
β = min β max ,1.0 + B 
dA 


(10)
(11)

where v A and v B are the velocity of real andboundary particles, respectively; d A and d B are thedistance from the real and boundary particles to thewall boundary; and β max is a constant number whichshould be chosen to prevent particles getting closer
to the wall boundary. In this study, β max =1.5 isapplied based on the recommendation by Bui et al
[6].

(8)

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GEOMATE-Nagoya, Nov.13-15, 2013

Real SPH particles

Fig. 3Outline of the experiment (Unit: mm)

Fig. 4

View of the slope model in experimentA
Solid wall

B
Boundary particles

Fig.2 Arrangement and treatment of solid boundary
It is worth noting here that, although boundary
particles are assigned with a virtual velocity (v B ),these particles are fixed in the space. However, forthe case of moving boundary such as due to seismic
motion, equation (10) must be replaced by thefollowing equation,

400

Acceleration (gal)v AB = β (v A − vwall )

600

(12)

200
0
-200
-400

where v wall is again the seismic velocity wave.
As a result, the virtual velocity of boundary particles
on the moving boundary can be estimated asfollows,

vB = (1 − β )v A + β vwall-600

Fig. 5

0

2

4

6
8
Time (sec)

10

12

14

Acceleration - time history used inexperiment(13)

Equation (13) assures that the velocity of realsoil particles right at the solid wall will be exactly
zero which satisfies the full-fixity boundary
condition. However, this boundary condition does
not represent the true natural seismic loading
condition where the motion of boundary should beapplied. In this paper, to simulate the true seismic
loading boundary, the boundary particles are
subjected to seismic motion which can be obtainedby taking integration of the input acceleration.

Sliding surface

Fig. 6

Final slope configuration after loading

NUMERICAL VALIDATION
A small-scale cut slope shaking table experiment
was conducted to verify SPH results. Figure 3 and 4
show the schematic diagram of the experimental
setup and the overview of the soil slope shaking
table setup respectively. A steel box of 100cm long,
60cm wide and 70cm high was mounted on top of
the shaking table. The soil slope model of 90cm
length, 60cm width and 50cm height was set in the
shaking box, and the slope angle was 45°. The soil
used in the experiment was Massa soil which is aweathered granite commonly found at Kansai area inJapan. The particle size over 5mm was eliminatedand the water content of soil is set at 10%. The slope
was constructed in phases using 5cm thickness
compacted layers of 90cm length and 60cm width toachieve the homogeneous soil slope. Finally, the soil
block was shaved to the angle of 45°. The soil

Outline of experiment
Laser displacement sensor
SV1
200

150

Soil box

1000

SV2
300

SV3

SV4

200

Slope model

SH3

45°
900

25

200

500

SH2

75

SH1

200

200

Laser beam

100

276

GEOMATE-Nagoya, Nov.13-15, 2013

parameters are given in Table 1.

dynamic behavior of the slope model. Soilparameters for the constitutive model can be foundin [9] and summarized in Table 1. The effect ofdilatancy angle on the failure mechanism of theslope is investigated. In general, the dilatancy angle
can vary from zero to the friction angle. In the caseof ψ = 0, the plastic volume is constant, and there isno plastic volumetric expansion; however, for thecase of ψ = ϕ, the plastic volumetric expansion is
maximal. Therefore, dilatancy angles of ψ = 0, ϕ/2,
and ϕ are adopted throughout this paper. Results ofthe failure surface and soil displacements are thencompared with those observed in the experiment.
The effect of pore-water pressure was assumed to be
negligible and not considered in this study.

a)b)Fig. 8A total of 3245 SPH particles were used to create
the slope model shown in Fig.3 with an initialsmoothing length of 1.2cm. Boundary conditions are
free-roller at the vertical and full-fixity at the base.
The initial stress condition in the slope was obtainedby applying the gravity loading to soil particles [7].
The slope model was then subjected to the seismic
wave loading shown in Fig.8 which was computedfrom the acceleration time history recoded in the
shaking table test. The load was applied byenforcing the seismic motions of the solid wallboundaries.

Input seismic motions: a) velocity and b)
displacement

Table 1 Soil parameters
Items
Values
Items
Value
ρ
1.68g/cm3
ψ0-φ
φ22.56oE
2.57MPac
0.78 kPaν
0.33
To measure displacement within the slope, sevenlaser displacement sensors were used. Three sensors,
named SH1, SH2, and SH3, were fixed to slope sideon the soil box to measure horizontal displacementof the slope at given height (see Fig.3). Four laser
displacement sensors, named SV1, SV2, SV3, andSV4, were fixed to the top of the soil box to measurevertical displacement at given locations. The shaking
table can generate a maximum acceleration of
323m/s2 with a corresponding displacement of 5cm
in horizontal direction and a frequency of 700Hz.

ψ = 0°The slope model was subjected to the seismic
wave loading shown in Fig.5, which was recorded
from the experiment. Test was run for 14 seconds
until the slope was completely collapsed. Figure 6
shows the deformation pattern of the slope at the endof the testing. The top surface of the slope wassettled down due to the soil compaction. Fourdistinct failure surfaces were identified from the side
wall, suggesting that the slope was collapsed inseveral stages during loading. In addition, because
the soil slope was constructed on the steel box, thefraction at the bottom of the slope is significantly
low. Therefore, the sliding along the steel box could
also be considered as one of the factors triggering
the slope failure.

ψ= φ

ψ=φ

NUMERICAL VALIDATION
A 2D-SPH model was conducted to simulate theFig. 9277

Effects of dilatancy angle on the failureGEOMATE-Nagoya, Nov.13-15, 2013mechanism.

However, the SPH model with (ψ =0) overestimatedthe failure zone. The ends of sliding surface line are
the same in both experiment and simulations. The
shape of the sliding surface in the simulation was foundto be almost circular, while that of experiment was a
curved line having higher curvature angle. It is still not
clear about this failure mechanism observed in theexperiment because there might have some technicalerrors when removing the collapsing soil to specify the
failure surface in the experiments. Further tests should
be conducted to clarify this difference for a future work.
In term of the progressive failure, theexperimental results showed that the slope model
underwent four failure stages which correspond tofour different failure surfaces as shown in Fig.6. The
SPH model was unable to reproduced this failure
mechanism; however, two failure surfaces wereobserved in the SPH simulation with (ψ =0); while
only one failure surface was found in the SPH model(ψ > 0.5ϕ). On the other hand, the SPH method cansimulate well the sliding process of soil after
collapse.
Figure 11 shows a comparison of SPH
simulations for the post-failure behavior of soil
using different dilatancy angles. It can be seen thatthe higher dilatancy angle is utilized in thesimulation, the larger final run-out distance could be
predicted in the simulation. This result isconceptually correct and reflects well the behaviorof the current constitutive model, that is the larger
dilatancy angle is adopted in the constitutive model,
the higher plastic volumetric strain could be
predicted during the post-yielding process. This
result suggests that if a suitable constitutive model isused, the SPH simulation could simulate well postfailure behavior of soil.
Figure 12 shows a comparison between the SPH
simulation and the experiment for the vertical andhorizontal displacements measured at some specificlocations as outlined in Fig.3, i.e. SH1-SH4 andSV1-SV4. In both cases (i.e. ψ =0 and ψ =0.5ϕ), theSPH simulations predicted fairly well the verticaland horizontal displacement profiles measured at
different layer displacement sensors. However,simulation results over predicted the final run-out
distance of soil measured in the experiment. The
SPH model with zero-dilatancy angle seems
providing better prediction of the displacement ascompared to the SPH model utilizing high dilatancy
angle. In addition, it is also noticed that thehorizontal displacement at sensor SH1 in the SPH
simulation of ψ =0.5ϕ went negative, which issignificantly different from that observed in theexperiment. This can be explained due to the fact theslope collapsed and slid downward along the failuresurface. Thus, the measuring location of SH1 in thesimulation was no longer on the sliding soil volume,
but on the failure surface. This mechanism washowever not clear from the experiment. Further

50

Experiment
Simulation (ψ =0)40

Simulation (ψ =0.5φ)

30

20

10

0

0

10

20

30

40

50

60

70

80

90

Fig. 10 Comparison between SPH simulation andexperiment for the failure surface.

ψ = 0°

ψ = φ

ψ=φFig. 11 Effects of dilatancy angle on the post
failure behavior of the slope.
Figure 9 shows a comparison of the failuresurface obtained in the simulations for different
dilatancy angles. The contour plot represents theaccumulated deviatoric strain. In the case of ψ = 0°,
soil underwent shear deformation without plastic
volumetric expansion, which resulted in the thickshear band layer. Contrarily, when the dilatancy
angle was increased, the failure occurred locally due
to the development of plastic volumetric strain. As aresult, the slip surface was found to be localized in anarrow band.
Figure 10 shows a comparison between
experiment and simulation for the failure surface. In
the experiment, the failure surface was obtained byremoving collapsing soil carefully above the failuresurface. It can be seen that the SPH simulation withhigh dilatancy angle (i.e. ψ > 0.5ϕ) predicted fairly
well the failure surface observed in the experiment.
278

GEOMATE-Nagoya, Nov.13-15, 2013

research is required to confirm the mechanism.
Horizontal displacement (cm)15

CONCLUSION

Experimental results

SH3This study presented the application of SPH to
simulate the large deformation and failure behaviorof the slope subjected to dynamic loading. Results
showed that SPH predicted fairly well the failuresurface observed in the experiment, but significantly
overestimated the slope deformation. In order toimprove the accuracy of the SPH simulation,
advanced soil constitutive model and damping
should be taken into consideration. These are thesubjects of future work

10

5

SH2

0

SH1

-5

0

2

4

6

8

10

12

14

Horizontal displacement (cm)

20

ψ=0

SPH results

SH3

15
10

ACKNOWLEDGEMENTS

SH2
5

-5

This research was supported by the JSPS
institution program for young researcher overseas
visits.

SH1

0

0

2

4

6

8

10

12

14

REFERENCES

Horizontal displacement (cm)60
SPH results

ψ = 0.5φ[1] Newmark NM, “Effects of earthquake on dams
and embankments”, Geotechnique, Vol 15,
No.2, 1965, pp 139-160.
[2] Cundall PA, Strack ODL, “A discrete numericalmodel dor granular assemblies”, Geotechnique,Vol 29, Issue.1, 1979, pp 47-65[3] Lucy LB, “A numerical approach to the testingof the fission hypothesis”, Astr. J., 82, 1977,
pp.1013-1024.
[4] Monaghan JJ, Gingold RA, “Smoothing particle
hydrodynamics: theory and application to nonspherical stars”, Mon. Not. R. Astr. Soc, 181,
1977, pp.375-389.
[5] Bui HH, Fukagawa R, Sako K, Okamura Y,“Earthquake induced slope failure simulation by
SPH”, The 5th Int. Conf. Rec. Advanced
Geotech. Earthquake Eng., CD, 2010.
[6] Bui HH, Fukagawa R, Sako K, Ohno S,“Lagrangian meshfree particles method (SPH)
for large deformation and failure flows ofgeomaterial
using
elastic–plastic
soil
constitutive model”, Int. J. Numer. Anal. Meth.
Geomech, 32, 2008, pp.1537–1570.
[7] Bui HH, Fukagawa R, “An improved SPH
method for saturated soils and its application toinvestigate the mechanisms of embankment
failure: Case of hydrostatic pore-waterpressure”, Int. J. Numer. Anal. Meth. Geomech.,
Vol.37, Issue 1, 2011, pp.31-50.
[8] Randles PW, Liversky LD, “Smoothed particle
hydrodynamics: some recent mprovements andapplications”, Com. Meth. Appl. Mech. Eng,
Vol.139, 1996, pp.375-408.
[9] Okamura Y, Sako K, Fukagawa R, “Analysis ofseismic displacements of slopes applied
vibratory conveyance theory”, Journal of JSCE(C), Vol.65, No.1, 2009, pp. 162-173.

SH3

40
20

SH2
0
-20
-40

SH1

0

2

4

6
8
Time (sec)

10

12

14

Vertical displacement (cm)10
SV4Experimental results
5

SV3

0
SV1
-5
-10
-15

SV2

0

2

4

6

8

10

12

14

Vertical displacement (cm)

15

ψ=0

SPH results

SV4

10
5

SV3

0
-5
-10

SV1
SV2
0

2

4

6

8

10

12

14

Vertical displacement (cm)20
SPH results15

ψ = 0.5φ

SV4

10
SV3

5
0

SV1

-5
-10
SV2

-15
-20

0

2

4

6
8
Time (sec)

10

12

14

Fig. 12 Comparison between SPH simulation andexperiment results for the displacements.
279

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ELECTRICAL RESISTIVITY TOMOGRAPHY TO INSPECT BRIDGEFOUNDATIONS

1

Helsin Wang1, Chih-Hsin Hu2, and Chung-Yue Wang1, 3Institute of Bridge Engineering, CECI, Taiwan; 2HCK, Taiwan; 3Department of Civil Engineering, National
Central University, Taiwan

ABSTRACT
Non-destructive testing (NDT) has been verified to efficiently know foundation conditioning. In this paper,
NDT techniques were required to inspect the bridge foundations with high scour potential in Taiwan. The
electrical resistivity tomography was proposed to conduct to the inspection on three commonly-used foundation
types of bridges. This technique displays its unique image outcomes for each foundation type. A high reliability
image can be easy-of-operation to identify both the shape and depth on shallow foundations and caissons.
Keywords: Electrical resistivity tomography, Foundation type, Bridge, Non-destructive testing,a target zone. Two extra potential electrodes are
triggered to measure the ground potential difference(as shown in Fig. 1).

INTRODUCTION
The as-built condition of foundations can affectthe performance of existing bridges supported bythese elements. Foundation conditioning is a crucial
key to evaluate the bridge resistance to flood or
earthquake and its stability for bridge engineers. For
example, lacking foundation dimension could
impede of rating the flood or earthquake resistanceon old bridges. Furthermore, materials deterioration,scour variation, or cracking could undermine thefoundation capacity of bridges as well.
For more than forty years, non-destructive
testing (NDT) or instrumentation inspection has
been developed to know the integrity of foundations[1], [5], [6]. Such inspection technique can provide
quality assurance of construction, maintain originalfunctions after testing, determine in-situ mechanicalproperties, rapidly assess a number of objects, andfind aberration in existing foundations.
At present, both the surface reflection technique,such as the impulse response method or ultraseismic method, and direct transmission technique,such as the sonic logging method or parallel seismic
method, are frequently used to evaluate the integrityof concrete piles, drilled shafts, and caissons in field[1], [3]-[5].
Besides the wave-based inspection techniques,
geophysical inspection methods were introduced tosubsurface and substructure investigation in past few
years [6], [8]. The most useful inspection technique,electrical resistivity tomography (ERT), provided an
outstanding identification on the interface between
foundations and surrounding soils/rocks [2].

Fig. 1A schematic representation for ERT setting.

The typical resistivity values of geomaterials
and waters are shown in Table 1 as reference for
identifying rock type, water content, salt content,
and anomaly, such as embedded pipes, undergroundstructures, or hollows. The measured resistivity
value in field is also highly contingent to mineralcomposition, grain size, mineral formation, watercontent, and ion concentration.
As shown in Fig. 2, the upper part shows the
two RC elements embedded in layered soils; thelower one presents the measured apparent resistivity
image with a display mode of visible-light spectrum,
which corresponds resistivity values varying from
2,000 to less than 1 ohm×m and illustrates theresistivity intensity distributions in space. The
resistivity value for sediments composed of silt andsand is more than 5 ohm×m, corresponding to thepink, red, orange, yellow, or green zones. The
existence of pre-cast or cast-in-place foundations
and protection works, which usually consists of steel,
could increase the electric conductivity value and

ELECTRICAL RESISTIVITY TOMOGRAPHY
The principle of ERT is to develop an artificial
potential field by probing current electrodes around
280

GEOMATE-Nagoya, Nov.13-15, 2013

also form a low resistivity-content zone with a
specific geometrical shape or spatial attribute. The
steel-content structural pieces have a lower
resistivity value, below 1 ohm×m, corresponding tolight blue and grey shades. The possible distributionof underground structures is graphically illustrated
on the resistivity images.

(1).Electrode Spacing: The smaller electrode spacing
is arranged, the higher image resolution and theshallower inspection depth are. Accordingly, thelarger electrode spacing is used, the lower image
resolution and the deeper inspection depth are.
Both inspection depth and site characteristics
determine the possible electrode spacing.
(2).Layout Length: The optimal layout length issuggested to be various from 1.5 to 2 times ofpier foundation depth if possible.
(3).Inspection Type: Two or more inspection types
are suggested to magnify the resolution along
and vertical to the probing array direction.
(4).Layout Deployment: The inspection depth andresolution are in terms of electrode spacing,layout length, and the probing distance to bridgepiers. Furthermore, a trial and error process on
sectional image is used to determine the optimallayout deployment.
(5).In order to enhance inspection accuracy, twomutually-perpendicular inspection directions aresuggested around a target bridge pier if possible.

Table 1 Resistivity range of common rocks, soils,
and waters [6].
Material
Rocks
GraniteSlate
MarbleSandstone
Shale
Limestone
Soils
Clay
Sand (dry)Sand (saturated)
Gravel (dry)Gravel (saturated)
Alluvium
WatersGroundwater (fresh)
Sea Water

Resistivity (ohm×m)
5×103–106
6×102–4×107
102–2.5×108
8–4×103
20–2×103
50–4×102
1–100
5×103–2×104
2×102–103
2×104–8×104
103–5×103
10–800CASE STUDY
The ERT technique was proposed to inspect thefoundation conditioning on four scoured rivercrossing bridges in Taiwan. The following sections
describe the execution and interpretation linking
ERT images and foundation conditions.

10–1000.2

Shallow Foundation
The Guguan Bridge was a 3-span pre-stressedbridge crossing the Da-Jia Stream in middle Taiwan.
The bridge standed at the bending vertex zone, andseverely alternative scour and deposition occured at
the bridge site. Two bridge piers were located at theriver bending zone covered with gravely riverbed
overlaying upon bedrock (Fig. 3). The foundation
type was determined as shallow foundations with adepth of 4 m from the ground surface.

Fig. 2

ERT result of layered soils influenced by 2
embedded RC elements.

There are 4 commonly-used inspection types,
including pole-pole array, pole-dipole array, dipoledipole array, and Wenner-Schlumberger array [6].
Each inspection type has different resolutions alongand perpendicular to the probing array direction andalso expresses various inspection abilities in depth.
In practice, ERT deployment is highly associatedwith subsurface characterization and environment.
Its crucial information is listed as the below:

Fig. 3 ERT inspecting a bridge shallow foundation.

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GEOMATE-Nagoya, Nov.13-15, 2013

A 70-m long ERT layout Line G2 was selected
to set around one of bridge piers with an electrodespacing of 2 m. In order to circumvent embedded
training structures found on the upstream side, Line
G2 had an angle of 45° different from the bridge
direction (Fig. 3). The position of the target bridge
pier was set around at the position of 36~39 m on
Line G2.
Two inspection types, dipole-dipole array andpole-diploe array, were applied to inspect the bridgefoundation type, as shown in Fig. 4 and Fig. 5,
respectively. The black dotted line represented theinterface between gravel and bedrock. The white
dotted line indicated the groundwater table. The
ERT images also significantly revealed a pretty low
resistivity zone, shown as grey-white color, at theposition of 34~40 m, which overlapped the positionof the bridge pier. The resistivity value ranged 1~20
ohm×m which corresponded to the resistivity valueof metal. The foundation type was shaped with ablack thin dotted line. This step-like image was
identified as a shallow foundation. The estimateddepth was around 5 m from the ground with aninspection error of ±1 m.
In addition, the resistivity value of the gravel
layer fell around 300 ohm×m. The resistivity image
on bedrock was distorted by overlaying bridge pierwhich were usually composed of steel for structural
reinforcement.

Fig. 4

Fig. 5at gravely riverbeds overlaying upon sandstone (Fig.
6). The foundation type was determined as a caissonwith a depth of 8.3±0.5 meters obtained from theultra-seismic method. The scour depth around thebridge pier was deepened much more than that of theother river section due to a violent flow of bending
vertex. The exposed height was around 1.5 m above
the river surface. The underwater exposed height
was measured as 2.5 m using a hanging weight scour
measurement. A scour potential has been reported tothe bridge agency for re-building a new bridge inorder to replace the current old bridge.

Fig. 6

ERT inspecting a bridge caisson.

Fig. 7

ERT image crossing a bridge caisson.

ERT image crossing a shallow foundation
with dipole-diploe array.
The inspection type of pole-diploe array was
executed to inspect the foundation type. The ERT
probing Line L-1 was set perpendicularly to thebridge direction and parallel to the flow direction. Its
total length was around 102 m by using an electrodespacing of 3 m. The position of the piercorresponded to around the position of 48~51 m on
the ERT image (Fig. 7). A light blue zone was
identified as the bridge pier. Its embedment depth
was evaluated as 4.5±1.5 m. The estimated height ofthe caisson was totally 8.5±1.5 m consistent with therecorded value.
In addition, the black dotted line represented theinterface of gravels and bedrock. An unknown
embedded object, RC armed blocks possibly, which
was marked with a low resistivity value, severelyinterfered with the ERT image on the downstreamside.

ERT image crossing a shallow foundation
with pole-diploe array.

CaissonThe Tienmei Bridge was a 2-span pre-stressed
RC bridge crossing the Chung-Guan Stream in
northern Taiwan. The single bridge pier was located282

GEOMATE-Nagoya, Nov.13-15, 2013

two bridges. Repeatedly scour and deposition aroundpile foundations were induced by storms or typhoons.
A 220-m ERT inspection line R-2 was aligned
along the traffic direction with a distance of 1 m
outside to bridge piers P11~P16. Electrode spacing
as 5 m was selected to detect foundations and soils
above the depth of 40 m. The corresponding
positions of bridge piers P11~P16 were at thepositions of 10~16 m, 45~51 m, 80~86 m, 115~121m, 150~156 m, and 185~191 m along the inspection
line, respectively. These six zones with pretty low
resistivity values positively confirmed the existenceof six pile groups (as shown in Fig. 9(a)).

Deep Foundation
The Sibin Bridge
The Sibin Bridge on joint Highway No.17 andExpressway No.61 provided the most downstream
crossing point over the longest Chuo-Shuei Stream,around few kilometers from the Taiwan Strait inwestern Taiwan (Fig. 8). This 78-span bridge was
2,730 m in length and consisted of three parallel Itype pre-stressed bridges with widths of 8 m, 18 m,
and 8 m supported by 35-m-long pile group eachpier. The distance was around 2 m between adjacentFig. 8

Panorama of the Sibin Bridge.

Depth(m)P11-P16
10
5
0
-5
-10
-15
-20
-25
-30
-35
-40
0

P11

P12

P13

P15

P14

P16

(a) Line R-2

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

180

190

200

210

220

Depth(m)Distance(m)
P21
10
5
0
-5
-10
-15
-20
-25
-30
-35

P21

(b) Line R-3

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102 108 114 120 126 132 138 144 150 156 162 168 174 180 186 192 198 204

Distance(m)1 4 7 10 13 16 22 28 34 40 46 52 58 64 70 76 85 100130

Fig. 9ERT images (a) along the bridge direction and (b) across pier P21 on the Sibin Bridge.

A low resistivity isolines image was assumed asa rectangular shape on each pile group herein. Sinceboth the length of pile groups and shallow embedded

protection works, RC armed blocks, or training
structures, the most countermeasures used tomitigate bridge scour in Taiwan, played a key role in283

GEOMATE-Nagoya, Nov.13-15, 2013

ERT inspection results, these two effects severelyinterfered with ERT inspection ability and sheltered
the electrical potential response at deeper zones.
This caused a distorted water-drop-like shape, not arectangular shape, extended from the pile cap
downward into the elevations various -25~-29 m±2.5 m, much less than designate depth, -35 m, onpiers P13~P15 (seen in Fig. 9(a)).
A 207-m-long ERT inspection Line R-3 wasaligned perpendicularly to the bridge direction witha distance of 1 m to all piers on the P21 position.
Electrode spacing as 3 m was selected to detect
foundations and soils below the depth of 37 m. Pier
P21 was marked at the position of 100~138 m on the
ERT image (Fig. 9(b)). The ERT image also
exhibited that a low resistivity zone with less than 22
ohm×m could be identified at the position of
100~108 m. Its water-drop-like shape geometricallyindicated that the length of pile groups was aroundthe 28±1.5 m less than the construction length, 35 m.
Unfortunately, the caps on the rest pile groups
severely interfered with ERT inspection results andblocked the electrical potential response below 10 m
at the position of 110~138 m. No reliable
information could be provided to estimate theirdepth. In addition, two low resistivity zones, whichranged around the horizontal positions of 0~90 m
and 141~207 m, represented unknown RC armed
blocks existing at the depth of 20~25 m.

layer. The distance was 2 m between these twobridges. An increasing scour were found on the
upstream right embankment. Therefore, inspection
Lines L-1 and L-2 were set across and along thistarget zone as shown in Fig. 10.
Inspection Line L-1 had a length of 200 m andtransversely crossed through around four piers at P6
position with a distance of 1 m to all piers. Electrodespacing as 5 m was selected to detect foundations
and soils below the depth of 45 m. These four RC
piers were located at the positions of 96~103 m,
107~116 m, 124~133 m, and 137~144 m,
respectively, on its ERT image (seen in Fig. 11).
These corresponding positions displayed four low
resistivity-content zones (less than 26 ohm×m).
Their pile caps and an unknown aberration material
severely interfered with the ERT inspection result.
Therefore, the lengths of pile groups have great
variations from 10 m to 28 m ±2.5 m, less than theconstruction length, 30 m, marked on Fig. 11.

P6
P5

P6

P5

P5

L-1

Upstream

The Wanda Bridge
The Wanda Bridge on Expressway No.88 played
an important transportation role over the Kaoping
Stream in southern Taiwan (Fig. 10). This bridge
was consisted of two parallel I-type pre-stressedbridges with a width of 24.5 m each. Each bridge
was supported by two RC piers overlaying 30-mlong pile groups which were embedded in sandy

L-2

Fig. 10 ERT inspecting the pile foundations of the
Wanda Bridge.

Upstream

Expected pile group

Unknown material

Fig. 11 ERT image across pier P6 on the Wanda Bridge.

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GEOMATE-Nagoya, Nov.13-15, 2013

Protection works

Main channel

Expected pile group

Fig. 12 ERT image along the traffic direction on the Wanda Bridge.
Line L-2 was aligned along the bridge direction
and crossed five piers from P4 to P8 with a distanceof 1 m to these 5 piers. Fig. 12 indicated that theircorresponding positions were situated at thepositions of 8~15 m, 44~51 m, 79~86 m, 115~122m, and 150~157 m, respectively, along theinspection line. An extreme low resistivity zone (lessthan 10 ohm×m) was found at the positions of
105~168 m. This condition could be identified toexperience embedded protection works due tocontinuously lateral erosion on the upstream side.
Therefore, the depth of pile groups could not berecognized from this ERT deployment.

REFERENCES[1] Baker CN, Parikh G, Briaud JL, Drumright EE,
and Mensah DF, Drilled Shafts for Bridge
Foundations, FHWA Report No. FHWA-RD-92004,
McLean,VA:
FederalHighway
Administration, 1993.
[2] Non-Destructive Testing Committee of theChinese Institute of Civil and HydraulicEngineering, Inspection Method and Applicationof Bridge Inspection, Taipei, Taiwan: Scientificand Technical Publishing Co., Ltd., 2010, pp. 527~5-32.
[3] Davis AG and Dunn CS, “From theory to field
experience with non-destructive vibration testingof piles”, Proceedings of the Institution of Civil
Engineers, Part 2: Research and Theory, Vol. 57,
1974, pp. 571-593.
[4] Geo-Institute Deep Foundation Committee,“Nondestructive evaluation of drilled shafts”,
Journal of Geotechnical and Geoenvironmental
Engineering, ASCE, Vol. 126, No. 1, 2000, pp.
92-95.
[5] Hertlein BH and Davis AG, Nondestructive
Testing of Deep Foundations, Chichester, U.K.:
John Wiley & Sons Ltd., 2006.
[6] Loke MH, Electric Imaging Surveys forEnvironmental and Engineering Studies— A
Practical Guide for 2-D and 3-D Surveys,
Sunbyberg, Sweden: ABEM Instrument AB,
2000.
[7] Olson LD, Jalinoos F, and Aouad MF,
Determination of Unknown Subsurface Bridge
Foundations, NCHRP Project No. E21-5,
Transportation Research Board, Washington,
D.C.: National Research Council, 1998
[8] Wightman WE, Jalinoos F, Sirles P, and Hanna
K, Application of Geophysical Methods to
Highway Related Problems, FHWA Report No.
DTFH68-02-P-00083, Lakewood, CO: FHWA,
Central Federal Lands Highway Division, 2003.

CONCLUSIONThe ERT inspection technique was applied toinvestigate the foundations of four scoured rivercrossing bridges in Taiwan. The foundation depths,
as well as foundation type, could be significantly
identified from the measured resistivity images onshallow foundations or caissons of bridges. However,a droplet-like resistivity shape represented theexistence of deep foundations, for the shelter effectof pile groups obviously limited the cognoscible
range of the electrical field on the upper part of pilegroups. Therefore, their exact depth also could not
be recognized on the detective ERT images. In
future, according to these ERT image characteristics,
bridge engineers have a chance to rapidly determine
the foundation type, even its depth, of unknown
foundation bridges, and their flood or earthquake
resistance can be preliminarily assessed.
ACKNOWLEDGEMENTS
The paper is partially granted by the Harbor andMarineTechnology
Center,InstituteofTransportation, the Ministry of Transportation andCommunications (MOTC) in Taiwan. Authors
greatly appreciate the financial support andassistances of the MOTC.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ULTIMATE BEARING CAPACITY ANALYSIS OF GROUND AGAINSTINCLINED LOAD BY TAKING ACCOUNT OF NONLINEAR
PROPERTY OF SHEAR STRENGTHDu N L1, Ohtsuka S1, Hoshina T1, Isobe K1, and Kaneda K2
Department of Civil and Environmental Engineering, Nagaoka University of Technology, Japan
2
Takenaka corporation, Japan

1

ABSTRACTIn the assessment of bearing capacity of footing, the bearing capacity formula proposed by The Architectural
Institute of Japan (AIJ) has been widely used in Japan for the design of building foundation. However, thisformula is limited to simple conditions like simple footing shape, flat ground and uniform material property.
Although the rigid plastic finite element method (RPFEM) can solve this complex problem, it has not taken into
account the size effect in assessment of bearing capacity. This study newly develops the RPFEM by introducing
the nonlinear shear strength property against the confining stress and proposes the rigid plastic constitutive
equation of parabolic yield function, basing on the change in the angle of shear resistance of Toyoura sand. The
developed method and the bearing capacity formula (established by empirical approach) provided identicalresults for various footing sizes showing good estimation for wider range of footing size.
Keywords: Rigid plastic finite element method, Bearing capacity, Inclined load effect, Size effectOn the other hand, rigid plastic finite element
method uses only strength parameters of the ground.
RPFEM is an analysis method which has beendeveloped in the field of plastic working of metal. It
is the effective analysis method to calculate theultimate bearing capacity of the ground. Initially,
RPFEM was established on the basic of the upperbound limit analysis, then it developed the rigid
plastic constitutive equation to provide the similar
result as in limit analysis. RPFEM with several
constitutive equations is quite often utilized to
predict the critical behavior. However, RPFEM does
not take into account the size effect in assessment ofbearing capacity. This study newly develops the
RPFEM by introducing the nonlinear shear strength
property against the confining stress and proposes
the rigid plastic constitutive equation of parabolicyield function against the confining stress.
This paper describes a simple method of
calculating bearing capacity by using rigid plastic
finite element method which is derived from therigid plastic constitutive equation, and thencompares the result which those of other methods(limit equilibrium method (Meyerhof, AIJ) and, Slipline method (Hansen) with the width range offoundations from 1m to 100m.
Results obtained from this study shows that
although Meyerhof, Hansen or AIJ methods arewidely used in design, they are not sufficiently
clarified. As we have known, although many
experiments have been carried out with model tests,
a conclusion for the size effect of model scale isdifficult to obtain. Moreover, these formulas use the

INTRODUCTION
Assessment of bearing capacity is necessary toensure the stability of a building. However, thebearing capacity of footing could be considerably
influenced by many factors, including inclinationload, eccentric load, shape, depth, size effect, etc.
Many researches have investigated these effects
on bearing capacity. Terzaghi & Peck (1948)
developed the classical bearing capacity equation as
follow:
qu = γ .D f .N q + c.N c + 0.5γ .B.N γ and definedbearing capacity factors Νc , Νq , N γ in terms of alinear strength envelope τ max = σ tan φ + c .
Meyerhof (1951, 1963), and Brich Hansen (1970)
based on the limit equilibrium method and the slip
line method which were extended by the original
proposal of Terzaghi (1948) to apply that fomurlawith more general factors and also derived
expressions for the inclination factors. In Japan,
bearing capacity formula proposed by Architectural
Institute of Japan (AIJ) has been also widely used.
This formula uses bearing capacity factors Νc , Νqgiven by Prandtl, Νγ and inclination load factors i c , i γ , i q
described by Meyerhof, and other extended factors: shapecoefficient α,β defined on the basic of footing shape andsize effect factor. In recent years, finite element
method has envolved as a well known method in
structural analysis, a revival of interest in finite
element, mainly focusing on soil mechanics
problems and exploiting the kinematic.

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GEOMATE-Nagoya, Nov.13-15, 2013

simple linear strength model. This study develops
RPFEM to solve the boundary problem withkinematical properties and provide a summary ofgood estimation for wider range of footing size.
RIGID
PLASTICMETHOD (RPFEM)FINITE

Rigid Plastic constitutive equation
Tamura (1991) developed the rigid plastic
constitutive equation for frictional material. The
Drucker-Prager’s type yield function is expressed asfollow:(2)f (σ ) = aI1 + J 2 − b = 0

ELEMENT

where I1 is the first invariant value of stress, J 2 isthe second invariant value of shear stress, theconstants of a and b express the angles of shear
resistance and dilatancy.
(3)
I1 = trσ

Limit analysis and its application to FEM
Hill (1951) and Drucker (1951, 1952) publishedtheir ground breaking lower and upper boundtheorems of plasticity theory, on which limit
analysis is based. It is apparent that limit analysis
would be an effective tool to provide important
insights into the bearing capacity problem.

1J2 = s : s
2(4)

Following the non-associated flow rule, the strain

The upper bound theorem of classicalplasticity theory which assumption of a perfectplastic soil model with an associated flow rule, isan useful tool to predict the stability of problems
in soil mechanics. It states that the power
dissipated by any kinematically admissible
velocity field could be equated to the power
dissipated by the external loads, and so enables astrict upper bound on the true limit load to be
deduced. A kinematically admissible velocity
field satisfies the conditions of compatibility, flow
rule and velocity boundary. In order to provide
practical solutions, the upper bound theorem isoften used in parallel with the lower boundtheorem.

rate ε = εpε = λcould be written as follow:

s 
∂g
= λ  αδ ij +∂σ
2 J 2 

(5)where λ is an indeterminate multiplier and δ ij is
the Kronecker’s delta symbol, e = ε : ε is the normof strain rate and I is a unit tensor. However, thestrain rate ε should satisfy the volumetric constraint
condition as follow:
3α(6)h(ε) = εv −e = 02
3α + 1 2
in which εv and e indicate the volumetric strain

The formula of the Rigid Plastic finite element
method is built on the basic of the upper boundtheorem. The arbitrary general strain rate elementεij is not always allowed for the strain

rate and norm of the strain rate, respectively. The
rigid plastic constitutive equation was expressed byrate D (εij ) since some kind of constraint is more

Tamura (1991) as follow:

specific. It is assumed that no volumetric plasticstrain rate occurs under the limit state. This isnaturally accepted for the soil structure. Define
further the subset K 0 (⊂ K p )σ = σ (1) + σ ( 2 ) = γ

The variable of γ is determined by inserting Eq. (4)The upper bound theorem previously proved isfound to be valid when we restrict ui , εij tohand, the indeterminate stress parameter β still(∫ D(ε )dVij(7)

into the plastic potential of Eq. (2). On the other)remains unknown until the whole problem with theK 0 since (ui∗ , εij∗ ) at the limit state also stays in K 0 .

Minimize

∂f
∂h
+β
∂σ
∂ε

kinematical constraint conditions of Eq. (6) is solved.
The stress-strain rate relation for the Drucker-(1)εij ∈K 0

Prager’s type by means of the nonassociated flow

It should be noted that this problem falls into thecategory of the convex programming problem, i.e.,
the functional to be minimum is always identical to
the global one.
whereε : Vector of strain rates of all elements

rule is finally expressed in the following form:σ=ψ − 3αβ ε
+ βI
1 e
2
3α + e2(8)Where the coefficient ψ is a variable, which isdetermined by stress σ located on the yield function,
α as cohesion.

u : Vector of all nodal velocitiesv : Vector of rates of volume change of all elements
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GEOMATE-Nagoya, Nov.13-15, 2013

confining stress .

BEARING CAPACITY OF FOOTING UNDER
PLANE STRAIN CONDITION

15000

Bearing capacity formulas

RPFEM

Meyerhof (1951, 1953, 1963, 1965 and 1976)
developed the bearing capacity equations byextending the Terzaghi’s mechanism to the soil
above the base of the footing, The bearing capacity
factors Νc and Νq are given by Prandtl (1921).
Meyerhof extended the proposal of Terzaghi (1948)
and incorporated those factors as follow:(9)q = ic cN c + 0.5iγ γ 1 BN γ + iqγ 2 D f N q

Bearing capacity q[kPa]

Meyerhof
Hansen

5000

0

In 1953, Meyerhof extended his theory for ultimate
bearing capacity under vertical load to the case withinclined load. The assumed failure mechanism isconfined to one side of the footing for all values of
the inclination angle, and composed of three zones
whose geometry is changed to account for the load
inclination. Furthermore, two slightly different
mechanisms were considered, one for small
inclinations and another for large inclinations.
Brich Hansen (1957, 1970) used the slip – line
method and provided a new expression for the semi empirical Νγ factor, with other bearing capacity
factors kept unchanged. Hansen also derived
expressions for the empirical inclination factors.
This expression has assumption on one sided
mechanism and accounts for the adhesion between
the soil and the footing base.
Bearing capacity formula of AIJ using bearing
capacity factors Νc , Νq given by Prandtl and Νγ andinclination load factors i c , i γ , i q described by Meyerhof(12)
q = icαcN c + iγ γ 1βBηN γ + iqγ 2 D f N q

1

100

Fig. 1 Effect of footing width on bearing capacity
for concentric vertical load application (φ = 30 deg)
Bearing capacity of footing for inclined load
We calculate the bearing capacity regardless of size
effect. The bearing capacity under vertical load is
calculated for the case with inclined load and, angleof shear resistance φ = 30 deg. Load inclination
angleθis inclination of load with respect to vertical.
The load inclination angle changes from 10 deg to
30 deg.
As presented above, inclination load only effectwhen inclined load angle θ < 30 deg with the
Meyerhof’s formula.
The empirical results shows that the values ofbearing capacity of footing decrease as the load
inclination angle increase, even for small inclination
angles.
4500
RPFEM

n

Meyerhof(10)Bearing capacity q[kPa]η = 

10
Width of foundation B[m]and some extended factors: shape coefficient defined
based on the shape of foundations. α,β with the strip
foundations are 1 and 0.5 respectively; Size effectfactor (B is a width of footing and B 0 is a reference
width): B
 Bo 

10000

Bearing capacity of footing for vertical load
For under concentrated vertical load, the numericalsolution is used with a rigid plastic constitutive
equation under plain strain condition. This is thelinear shear strength properties.
This study uses the angle of shear resistance ϕ=30
deg. The result presented from fig.1 shows that thebearing capacity of footing increases with theincrease of size footing. As can be seen the value
obtained from RPFEM and other methods have large
difference. This difference is due to the significant
effect of confining stress when calculating thebearing capacity of footing. This would be improvedin the next section when using RPFEM consider

3000
Hansen

1500

0
1

10

100

Width of foundation B[m]Fig. 2 Bearing capacity with angle of Inclined load
θ = 20 deg
Fig. 2 describes the relationship between bearing
capacity and width of footing. The different values
also consistently confirmed the effect of confining
stress dual on bearing capacity of footing.
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GEOMATE-Nagoya, Nov.13-15, 2013

Furthermore, results presented in the Fig. 2 indicate
the influence of size effect. The larger width offooting the larger difference between RPFEM withother methods.

shear strength is needed. Higher yield function andparameters of the yield function are proposed on thebasic of experimental results of Tatsuoka. The
ultimate bearing capacity results gained through theapplication of high yield function in RPFEM in thisstudy shows more consistent with the actual groundthan the values obtained in the Drucker-Prager yieldfunction. The study’s results shown that it is possible
to evaluate the ultimate bearing capacity values,
taking into account the nonlinearity’s influence ofthe soil strength due to confining pressure of theground.
Based on the layout of Toyoura sand from Fig. 3, theresults show that the confining stress effect on the
behavior of ground in Fig. 4. So we can establish therelationship between the value of the first stressinvariant I1 and the second invariant value of shear
stress J 2 . This allows us to design parameters whenreferring to nonlinear shear strength properties ofsoil for different types of soil.

RIGID PLASTIC CONSTITUTIVE EQUATIONOF TOYOURA SAND

Angle of shear resistance ϕ (deg)Strength tests of Toyoura sand by Tatsuoka

Fig. 3 Experimental result of Toyoura sand
(Tatsuoka, 1986)

The first invariant of the stress I1 (kPa)

Fig. 4 Effect of confining stress to soil behavior
Non – linear rigid plastic constitutive equation
for confining stress

Applying Drucker-Prager criteria and MohrCoulomb criterion are based on the frictional
characteristics to represent the strength of the ground.
When angle of shear resistance is increased, theeffect of the ultimate bearing capacity of the groundchanges constantly on the extremely large ultimate
bearing capacity of the ground. Therefore, when
determining the angle of shear resistance andadhesion by soil test, in the compression zone, lowpressure area always overestimates the strength. It is
pointed out that the development of yield function
by the non linear shear strength is needed to improve
the accuracy when calculating the bearing capacityof footing.
As mentioned above confining stress and size effecthave significant effects on the shear strength using
shear strength linear properties. It is more thanevident through experiments of Tatsuoka. Tatsuoka
surveyed the shear strength of Toyoura sand andclarified that the angle of shear resistance variedwith the confining stress as Fig. 3 above. So, thedevelopment of yield function by the non-linear

From yield function:f (σ ) = aI1 + ( J 2 ) n − b = 0(11)
The first invariant of the stress is decided bymodifying the yield function formula, the firstinvariant of the stress using the second invariant of
the deviatoric stress is updated by the following
equation:

I1 =

1
n
b - (J 2 )
a

(

)

(12)

The strain rate for nonlinear case:ε = λaI + nJ 2n−1s∂f (σ)=∂σ

3a + 2n (b − aI1 )
2

2

2− 1

e

(13)

n

and the volumetric strain rate εv :εv = trε =289

3a3a + 2n (b − aI1 )2

2

2− 1 ne

(14)

GEOMATE-Nagoya, Nov.13-15, 2013

The first invariant and stress is expressed by strain
rate so this relationship can be obtained as follows:
1− n


2
2 n −1 ε 1  9a 2  e  3a 2 
σ =  2   − 2 3a  − aI  



 εv

 n  2n  ε v  2n 
(15)


n


2
2
2  2 n −11  b 1 9a  e  3a
+  −  2   − 2  I
3  a a  2n  εv  2n  respect to the horizontal ground and the comparision
with theoretical solution of Meyerhof.

Bearing capacity q[kPa]3500

In this study, we develope a rigid plastic constitutive
equation incorporating a confining pressure
dependence of the ground strength which isevaluated with highly accurate the ultimate bearing
capacity. The first term of the above equation isdetermined by the stress constitutive relation and thesecond term is the stress component along the yieldsurface. So the stress σ can be shown as follows:( aI1 + 2n ( b − aI1 ) ) εσ=
( 2 −1 n ) e
3a 2 + 2n 2 ( b − aI1 )
(16)


3a
ε 

+ κ ( εv − β e )  I −( 2−1 n )  e
3a 2 + 2n 2 ( b − aI1 )



3000

RPFEM

2500

Meyerhof
Hansen

2000
1500
1000
500
0
1

10

100

Width of foundation B[m]Fig.4 Bearing capacity with higher order yieldfunctionFig. 4 shows the development of Rigid Plastic Finite
Element Method. RPFEM results coincide with theresults of Meyerhof, which mean that the results
obtained from non-linear shear strength properties ismuch better than the linear function described earlier.

where κ : is the variable determined by inserting Eq.
(8) into the plastic potential of Eq. (3).
Through analysis of the explicitly dilatancy
characteristics, computation of stable displacement
velocity field can be implemented by using above
nonlinear equation. Further, the advantage of thenumerical analysis on the rigidity matrix issymmetrical.

Bearing capacity of footing for inclined load
Results from Fig. 5 indicats that the differences
between RPFEM and other methods are significantly
improved when comparing with the results
calculated from linear shear strength properties.
1500

APPLICABILITYOFPROPOSEDCONSTITUTIVE EQUATION TO BEARING
CAPACITY ASSESSMENT

RPFEM

Bearing capacity q[kPa]

Meyerhof

Bearing capacity of footing for vertical load
As mentioned above, high pressure and low pressurearea of the confining pressure of the ground is aproblem which leads to the overestimate of DruckerPrager’s yield function. This is primarily due to theintensity nonlinear characteristic of confiningpressure by soil. Therefore, it is reasonable toevaluate the strength by applying the intensity
equation linear shear strength of the soil. In practice,
non-linear strength of the ground may dominate thestability, hence it is important to incorporate thestability evaluation of the nonlinearity strength inengineering. The rigid-plastic constitutive equation,that is non-linear, should be used for higher-orderyield function. In this case, the effect of compression
stress on estimated values is smaller than thoseobtained from the linear intensity formula. In thissection, we perform a numerical analysis with

1000
Hansen

500

0
1

10

100

Width of foundation B[m]Fig.5 Bearing capacity with angle of Inclined load
θ = 20 deg
As can be seen from Fig. 6, with width of footing
B=30m when considering the influence of inclined
load, the effect of confining stress is very significant
and the use of nonlinear properties of shear stress tocalculate the bearing capacity of footing is perfectly
reasonable.
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GEOMATE-Nagoya, Nov.13-15, 2013

REFERENCES

5000
RPFEM (Nonlinear)
4000[1] Aysen A, “chapter 10”, Soil Mechanics – Basicconcepts and engineering applications, Balkema
A A publisher, 2002, pp. 413 – 419.
[2] Drucker D C, Greenberg H J, Lee E H, Prager
W, “On plastic rigid solutions and limit design
theorems for elastic plastic bodies”, 1st US
NCAM, 1951, pp. 533 – 538[3] Hill R, “On the limits set by plastic yielding to
the intensities of singularities of stress”, J. Mech.
Phys. Solids, Vol. 2, 1954, pp. 278-285.
[4] Okamura M, Takemura J, Kimura T,“Centrifuge model tests on bearing capacity anddeformation of sand layer overlying clay”, Soiland Foundations, Vol. 37, No.1, 1997, pp.73–
87.
[5] Fumio Tatstuoka et al, “Model tests and FEM
simulation of some factors affecting the bearing
capacityof footing on sand”, Soil andFoundations, Vol. 41, No.2, 2001, pp. 53 – 74.
[6] Tatsuoka F, Sakamoto M, Kawamura T and
Fukushima S, “Strength and deformation
characteristics of sand in plane strain
compression at extremely low pressures”, Soiland Foundations, Vol.26, No.1, 1986, pp.65– 84[7] Takeshi Hoshina, Satoru Ohtsuka and Koichi
Isobe, “Ultimate bearing capacity of ground by
Rigid plastic finite element method taking
account of stress dependent non-linear strength
property”, Journal of Applied Mechanics, Vol.6,
2011, pp.191 – 200[8] Takeshi Tamura, “Rigid-Plastic Finite Element
Method in Geotechnical Engineering”, The
Society of Materials Science, Japan, Vol.7, pp.
135–164.
[9] Mohammed Hijaj, Andrei V. Lyamin, Scott W.
Sloan, “Bearing capacity of cohension-frictionalsoil under non-eccentric inclined loading”, Vol
31, 2004, pp. 491 – 516.
[10] Hjiaj M, Lyamin A V, Sloan S W, “Numericallimit analysis solutions for the bearing capacity
factor N γ ”, International Journal of Solids andStructures, Vol. 42, 2005, pp. 1681 – 1704.
[11] Lyamin A V and Sloan S W, “Upper boundlimit analysis using linear finite elements andnon-linear programming”, International Journal
for numerical and analytical methods ingeomechanics, Vol. 26, 2002, pp. 181 – 216.
[12] Bolton M D and Lau C K, “Vertical bearing
capacity factors for circular and strip footings
on Mohr – Coulomb soil”, Canada Geotechnical
Journal, Vol 30, 1993, pp. 1024 – 1033.
[13] Siddiquee M S A, Fumio Tatsuoka, Tadatsugu
Tanaka, Kazuo Tani, Kenji Yoshida andTsutomu Morimoto, “Model tests and fem
simulation of some factors affecting the bearing
capacity of a footing on sand”, Soil andFoundations, Vol. 41, No.2, 2001, pp. 53 – 76.

Meyerhof

Bearing capacity q[kPa]

HansenRPFEM (Linear)

3000

2000

1000

0
0

10

20

30

Angle of inclination(Deg)

Fig. 6 Bearing capacity with Inclined load effect incase width of footing B = 30m
In this case, the value of bearing capacity decrease
quickly under effect of inclination load. Impact ofsize footing is considerable. The value of bearing
capacity reduces from 3 to 4 times when considering
size effect. This finding is very important to insurestability of building.
The use of rigid-plastic constitutive equation withhigher-order yield function proposed, which can be
expressed nonlinearity strength by confining stressof the ground and checked the applicability ofDruker-Prager method to the ultimate bearing
capacity problems.
CONCLUSION
This study has developed the ultimate bearing
capacity analysis method using a rigid-plastic
constitutive equation with higher-order yieldfunction by confining pressure. The empirical results
indicated that, ultimate bearing capacity value
decreases in accordance with the increase of the load
inclination angle in both cases linear and nonlinear
shear strength properties. However, the values ofultimate bearing capacity from developed RPFEM isless than those values obtained from DruckerPrager’s yield function.
In addition, be evaluated properly to yield function
from the change in values of the first invariant I1 ofthe stress and, the effects of confining pressure of
the ground can be evaluated reasonably.
However, the results from empirical investigation
are still limited by the experimental method in caseof size of footing. RPFEM coincided with thecalculated results from the experimental method.
This persuasively demonstrates the accuracy of thismethod. We proposed to use numerical method withlarge width of footing. The applicability of RPFEM
is to solve more complicated problems in case oflayered ground and improved ground. The
developed Rigid plastic finite element method canprovide the good estimation for wider range offooting size.
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PREDICTION OF SLOPE DEFORMATIONS BY ELASTIC WAVEVELOCITIES IN RELATION TO LANDSLIDE FAILURES

1,2

Muhammad Irfan1 and Taro Uchimura2
Department of Civil Engineering, University of Tokyo, Japan

ABSTRACTThe authors propose a method for the prediction of landslide movement by using elastic wave velocity insoil. A series of triaxial tests was conducted on unsaturated sand specimens to study the variation of shear andcompression wave velocities with soil yielding. Several specimens with different initial saturation ratio wereprepared. To simulate the field stress path followed by soil during landslides, total radial stress (σ 3 ) was reduced
at a constant rate while keeping the total axial stress (σ 1 ) constant. Shear and compression wave velocities were
determined at regular intervals till failure of specimens. Soil yielding due to reduction of radial stress (σ 3 ) was
observed to be dependent on saturation state. Shear and compression wave velocities were observed to decreaseby about 40% and 15% respectively with soil yielding. An idea to predict landslides by monitoring changes inwave velocities in slope ground is schematically presented and explained.
Keywords: Landslide Monitoring; Elastic Wave Velocity; Triaxial Tests; Unsaturated Soil.

shallow depths is generally in unsaturated state,hence possessing negative pore water pressure(matric suction) which adds to the stability of slope.
The infiltration of rain water in slope surface causes
decrease in matric suction which in turn reduces
effective normal stress acting on the potential failure
plane. As a consequence of decreasing effective
normal stress (σ n ), available shear strength (τ) also
reduces, and this reduction continues to a point at
which equilibrium can no longer be sustained in theslope. He further suggested that the field stress pathcan be simulated in laboratory element tests by oneof the following tests methods;
i. Application of constant total stress (σ 1 , σ 3 :constant) and increasing pore waterpressure from initial negative value until
the failure occurs.
ii. Decreasing the radial stress (σ 3 ) while
maintaining the axial stress (σ 1 ) constant.
Although both the methods yield the same stress
path but the latter method is unable to simulate
actual failure mechanism [7, 8]. But as water
saturation distinctly reduces elastic wave velocities[9], therefore to study the effects of soil yielding on
wave velocity in isolation, the latter method was
adopted for this study. Hence, to achieve failure, aconstant axial stress (σ 1 ) was maintained while
decreasing the radial stress (σ 3 ) at a constant rate
and recording wave velocities at regular intervals.

INTRODUCTION
Landslides are among the most devastating
natural disasters. Every year numerous lives are lostand infrastructure is destroyed around the globe due
to landslides. According to GLIDE number record of
134 landslides between 1999 and 2012, around 63%
are triggered by rainfall (www.glidenumber.net).
Majority of landslide early warning systems aroundthe world are based solely on the monitoring of
rainfall intensity or duration and issuing warningwhen precipitation exceeds a certain critical value.
However, for efficient prediction of landslides,
consideration of soil characteristics and monitoringof actual slope displacements is integral. A variety
of sensors are currently being used around the world
to monitor physical movements of slope surfaces.
These include draw wire displacement sensors [1],inclinometers [2-4], extensometers [5, 6], etc. A new
idea to watch slope movements by monitoringelastic wave (shear wave and compression wave)
velocities in soil is presented in this paper.
Experimental results and relevant discussions from aseries of triaxial tests, performed to explore theeffect of soil yielding on elastic wave velocities, arepresented in the following passages.
FIELD STRESS PATH
In conventional triaxial tests, a soil element issubjected to increasing axial stress (σ 1 ) while
maintaining the radial stress (σ 3 ) constant. However,such tests do not correctly depict the in-situ stress
path followed by soil during rainfall induced failure.
Brand [7] postulated that the slope surface at

TEST PROGRAM
Experimental Setup
A stress controlled triaxial testing apparatus was
292

GEOMATE-Nagoya, Nov.13-15, 2013(a) P-wave(b) S-wave

Fig. 1: Typical elastic wave propagation signals in Edosaki sand, and definition of wave travel time (a) P-wave, and(b) S-wave
employed for this study. Independent control ofaxial and radial stress was made possible by meansof electro-pneumatic transducers.
Volumetric strains of unsaturated specimens
were recorded by continuously monitoring axial andradial strains. A pair of local deformationtransducers (LDTs) [10, 11] attached to the surfaceof specimen by means of pseudo-hinges was used tomeasure axial strains. However, LDTs could
measure axial strains only up to 2-3 %, therefore
axial strains beyond this level were recorded by an
externally mounted linear variable differential
transducer (LVDT). Radial strains in the specimens
were measured by three clip gauges mounted at
different heights of the specimen.
Top cap and base pedestal of the apparatus weremodified to enable measurement of shear wave (Swave) and compression wave (P-wave) velocities inunsaturated triaxial specimens. A novel disk typepiezoelectric transducer (referred as disk transducer
hereinafter) was fabricated and sealed to the pedestal
and top cap for generation and measurement ofelastic wave velocities (construction details in [12]).
The use of disk transducers instead of the morecommonly used bender elements, not only enabled
the measurement of both P-wave and S-wave
velocities but also reduced sample disturbance due
to its non-intrusive nature.
Transmitter disk transducer, sealed to thepedestal, was excited by a single cycle of 10 kHz or
15 kHz sinusoidal wave for generation of P-wave orfor S-wave respectively. An excitation voltage of 4.5
Vpp (Vpp = peak-to-peak voltage) generated by afunction generator was amplified to 90 Vpp and fed
to the transmitter disk transducer. The wave
travelled through the soil specimen and was received
at the top cap by receiver disk transducer whichtransferred the signals to oscilloscope to be digitallydisplayed. Time of flight of each wave through soil
specimen was then computed by analyzing received

signals as shown in Fig. 1. As compression waves
are the fastest propagating waves through soil, thus
were identified by the first deflection of receiversignal (Fig. 1a). However, the first arrival of S-wave
may not correspond to the actual arrival of shear
wave but rather to the arrival of the so called “nearfield” component, which travel with the velocity ofP-wave [13]. Shear wave travel time was thus
calculated as the difference between the start oftransmitted signal and the start of first major
positively polarized up rise; i.e. “first-zero crossover” method [14]. By knowing the wave travel time‘t’ from received signal, and travel distance ‘H’(equivalent to specimen height), wave velocity canbe computed by using a simple expression;
Vp or Vs = H/t(1)

where, Vp and Vs represents compression andshear wave velocity respectively and t is thecorresponding travel time for compression or shear
wave.

Fig. 2: Particle size distribution of Edosaki sand.

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GEOMATE-Nagoya, Nov.13-15, 2013

Materials & Methodology
Edosaki sand procured from a pit trench in
Tsukuba, Japan was used for this study. Fig 2 shows
typical particle size distribution of material used.
Particles larger than 2 mm were removed throughsieving. Table 1 summarizes physical properties of
Edosaki sand employed for this study.
Cylindrical triaxial specimens (75 mm indiameter and 150 mm in height) were prepared by
wet tamping Edosaki sand to a predefined density of
1.56 g/cm3 (Dr=88%) in ten equal layers. Placement
moisture content was controlled to prepare
specimens with initial saturation ratio of 10%, 20%,
45% and 75%. A saturated specimen with
Skempton’s B-value of 0.80 (Sr ≈ 90%) was also
prepared. All the specimens were prepared at initial
all around confining pressure of 15 kPa. Then as partof a separate study (not covered in this paper),isotropic confining pressure was first increased to
300 kPa and then gradually brought down to 150
kPa. From 150 kPa initial isotropic confiningpressure, radial stress (σ 3 ) was gradually decreased
at a rate of 0.016 kPa/s so that the specimen reachedfailure. The magnitude of axial load was adjusted
accordingly to maintain a constant axial stress (σ 1 )throughout the test. Elastic wave velocities wererecorded at various points along this stress path.
Stress path employed in these tests is schematicallyshown in Fig. 3.

Fig. 3: Stress path adopted for this study.
continuous straining of the specimen without any
appreciable change in stress. Moreover, the strains
beyond yield point are irrecoverable. Hence, theyield point can be said to represent failure initiationof the specimen as indicated by “Δ” in Fig. 4.
A systematic approach adopted for the definitionof Δ is explained in Fig. 5. Using the radial stress(σ 3 ) ~ axial strain (ε 1 ) plot, a tangent corresponding
to 0.2% axial strain (point A) was drawn. Anotherline, tangent to the final part of the curve, wasextended backwards to intersect the first tangent.
The intersection point of these two tangents (pointB) represented the yield point of soil specimen andthe corresponding magnitude of radial stressindicated the yield strength. Thus, the failure wasinitiated when the specimen reached its yieldstrength, and yield point of each specimen isindicated by Δ in Fig. 4.

Table 1: Physical properties of Edosaki sand.
Property
Specific gravity, Gs
Minimum void ratio, emin
Maximum void ratio, emax
Fines (%)
Maximum dry density (g/cm3)
Optimum moisture content (%)

Value
2.639
0.647
1.160
9
1.762
14.6

TEST RESULTS
Effect of Initial Saturation on Landslide Failure
Field stress path tests were carried out on
specimens with different initial saturation ratio, by
maintaining the axial stress constant and gradually
reducing the radial stress to the point of failure. Fig.
4 shows the response of various specimens whensubjected to field stress path. On reducing the radialstress (σ 3 ) from an initial isotropic stress of 150 kPa,
extremely small strain was observed during the earlyphase of tests. However, after sufficient reduction inradial confinement, axial strain started to increase
first slowly and then at a rapid rate. Such transitionin strain rate can be defined as yield point ofspecimen. Once the yield point is reached, there isFig. 4: Deformation time history of specimens
subjected to field stress path.
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GEOMATE-Nagoya, Nov.13-15, 2013

slopes. Post-yielding strain rate decreases withincreasing saturation. For instance, 20% saturated
specimen developed very large strains in a very
short time after yielding. However, it took a very
long time after yielding for 90% saturated specimen
to reach the failure strain. Dry slopes undergoing
failure process are therefore expected to fail at a
rapid pace (brittle in nature) as compared to wet
slopes which are rather expected to fail in a moreductile manner. Large post-yielding strain in wet
slopes can hence be used as a warning before
complete failure.
Fig. 5: Definition of failure initiation adopted for thisstudy.

Effect of Yielding on Wave Velocity

From Fig. 4, yielding of soil specimen subjected
to field stress path is a function of initial saturation
state. Although the rate of radial stress decrement
was same for all test cases, yet specimens withhigher saturation initiated failure much earlier thanrelatively drier specimens. Therefore, it can besurmised that wetter slopes are closer to failure stage
than relatively drier slope surfaces.
Test results presented in Fig. 4 also help
understand the post failure behavior of unsaturated

As the specimens were subjected to field stress
path, elastic wave velocities (Vs: shear wave
velocity, and Vp: compression wave velocity) were
determined at various intervals. Fig. 6 summarizes
the effects of soil yielding on shear and compression
wave velocities. With the reduction of radial stress(σ 3 ), shear wave velocity start decreasing slowly.
This decrease in Vs can be attributed to the gradualloss of inter-particular contact force with the
reduction of radial stress. As the radial stress

(b)

(a)

Fig. 6: Effect of radial confinement on wave velocities (a) S-wave; (b) P-wave

(a)

(b)

Fig. 7: Effect of radial confinement on normalized wave velocities (a) S-wave; (b) P-wave
295

GEOMATE-Nagoya, Nov.13-15, 2013

approaches yield strength of specimen (representedby Δ), a sharp increase in rate of Vs decrement isobserved. Compression wave velocity (Vp) however,nearly remains constant before failure initiation, but
drops at an accelerated speed once the failure isinitiated (Fig. 6b). Difference in the pre-yielding
behavior of Vs and Vp is because of the difference instress dependency of two waves i.e. Vs is a functionof both axial (σ 1 ) and lateral stress (σ 3 ), whereas Vp
is solely dependent on axial stress (σ 1 ) [15].
Therefore, decrease of radial stress (σ 3 ) in the preyielding phase only causes reduction in Vs, while Vp
remains unaffected. However, once failure isinitiated, the specimen starts to dilate at anaccelerated pace and the structural rearrangement ofparticles causes rapid reduction of both Vp and Vs.
Shear strength of unsaturated specimens
subjected to field stress path is function radial stress(σ 3 ) and soil matric suction (negative pore waterpressure). Higher the saturation ratio, lower would
be matric suction, and shear strength would be moresensitive to radial stress (σ 3 ) only. This phenomenon
can be observed from Fig. 7, a plot of radial stressversus wave velocities normalized with respect tothe respective maximum wave velocity. The rate ofpre-yielding Vs decrement is higher for 90%
saturated specimen as compared to the relatively
drier specimens. Moreover, while undergoing thefield stress path shear and compression wave
velocities were observed to decrease by about 40%
and 15% respectively. This decrease in wave
velocities due to soil yielding can be used as anindicator of landslide initiation in actual field
conditions.
APPLICATION
PREDICTION

FOR

percolates the slope surface, matric suction is
gradually lost resulting in reduction of shear strength.
With the loss of available shear strength slope
surface starts to become more and more unstable andthis destabilization continues to a point at which
equilibrium can no longer be sustained and the slope
ultimately fails.
Elastic wave velocities in soil decrease withincreasing saturation [9]. Discussions in previous
sections based on Fig. 6-7 also highlight thesensitivity of elastic wave velocities to soil yielding.
These phenomena can therefore be utilized for theprediction of landslides. A conceptual idea oflandslide prediction by using elastic wave velocities
is presented in Fig. 8. A pair of exciter/receiver
assembly placed on the slope surface can be used toobtain wave velocities in slope at regular intervals.
Start of a rainfall event would increase soil
saturation hence reducing wave velocity. Meanwhile,slope failures may occur when the slope ground isalready nearly saturated and water contents areconstant at a high level. Some failures happen evenafter the rainfall has stopped. Wave velocity should
start decreasing sharply once failure is initiated andsoil has started to yield. Shear wave velocity is
expected to drop by about 40% due to soil yielding(Fig. 7a). This decrease in wave velocity is large
enough to be used for early warning of landslides.
CONCLUSIONSA series of triaxial tests, following the field
stress path during landslides, was conducted to
explore the effects of soil yielding on elastic wave
velocities. The main conclusions drawn from thisstudy are summarized below.
• Failure initiation (yielding) due to reduction ofradial stress was found to be a function of
initial saturation ratio. Wet specimens were
found to yield earlier than dry specimens
reflecting the wet slopes to be much closer tofailure stage.

LANDSLIDE

Slope surfaces, at shallow depths, are generally
in unsaturated state with soil matric suction(negative pore water pressure) playing an importantrole in their stability. During rainfall events, as water

Fig. 8: Conceptual schematic of landslide prediction by monitoring wave velocities.
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GEOMATE-Nagoya, Nov.13-15, 2013

• Post-yielding behavior was also found to be
dependent on saturation state. Time lapse
between failure initiation and complete failure
can be considerably large in nearly saturated
slopes. However, dry slopes may tend to fail ina brittle manner i.e. very small time between
failure initiation and complete failure.
• Both shear and compression wave velocities
were found to decrease rapidly once failure isinitiated in soil specimens. A decrease of about
40% was observed in shear wave velocity
whereas the corresponding decrease incompression wave velocity was about 15%.
• An idea for the prediction of landslides byusing elastic wave velocities is presented.
Sensitivity of wave velocities to soil moistureand slope deformations can effectively beutilized to warn against landslide failures.

[5]Angeli, M.-G., A. Pasuto, and S. Silvano, A
critical review of landslide monitoring
experiences. Engineering Geology, 2000.
55(3): p. 133-147.
[6] Uchimura, T., D. Suzuki, and S. Hongkwan.
Combined monitoring of water content anddisplacement for slope instability. in Proc. of
4th Japan-Korea Geotechnical Workshop.
2011. Kobe, Japan.
[7] Brand, E.W., Some Thoughts on Rain-Induced
Slope Failures. Proc. of 10th International
Conference on Soil Mechanics and Foundation
Engineering, 1981. 3: p. 373-376.
[8] Brenner, R.P., H.K. Tam, and E.W. Brand,
Field stress path simulation of rain-induced
slope failure. Proc. of 11th International
Conference on Soil Mechanics and Foundation
Engineering, 1985. 2: p. 991-996.
[9] Irfan, M. and T. Uchimura. Effects of soil
moisture on shear and dilatational wave
velocities measured in laboratory triaxial tests.
in Fifth International Young GeotechnicalEngineering Conference - 5iYGEC’13. 2013.
Paris, France (to appear).
[10] Goto, S., et al., A simple gauge for local small
strain measurements in the laboratory. Soils
and Foundations, 1991. 31(1): p. 169-180.
[11] Hoque, E., T. Sato, and F. Tatsuoka,
Performance evaluation of LDTs for use intriaxial tests. ASTM geotechnical testing
journal, 1997. 20(2): p. 149-167.
[12] Irfan, M. and T. Uchimura, Criteria for
determining Gmax in laboratory element tests
using disk type piezoelectric transducers., in10th International Conference on Urban
Earthquake Engineering 2013: Tokyo, Japan.
p. 555-560.
[13] Sanchez-Salinero, I., et al., Analytical studies
of body wave propagation and attenuation,
1986, DTIC Document: Texas Univ at Austin
Geotechnical Eengineering Center Report GR
86-15.
[14] Lee, J. and J. Santamarina, Bender Elements:
Performance and Signal Interpretation.
Journal of Geotechnical and Geoenvironmental
Engineering, 2005. 131(9): p. 1063-1070.
[15] Hardin, B.O. and F.E. Richart, Elastic wave
velocities in granular soils. J. Soil Mech. andFound. Div., ASCE, 1963. 89(1): p. 33-65.

ACKNOWLEDGEMENTS
Ministry of Education, Culture, Sports, Science& Technology (MEXT) is gratefully acknowledged
for their financial assistance.
REFERENCES
[1]

[2]

[3]

[4]

Arnhardt, C., et al., Sensor based Landslide
Early Warning System-SLEWS. Developmentof a geoservice infrastructure as basis forearly warning systems for landslides byintegrationofreal-time
sensors.
Geotechnologien science report, 2007. 10: p.
75-88.
Lollino, G., M. Arattano, and M. Cuccureddu,
The use of the automatic inclinometric system
for landslide early warning: the case ofCabella Ligure (North-Western Italy). Physics
and Chemistry of the Earth, Parts A/B/C, 2002.
27(36): p. 1545-1550.
Uchimura, T., et al., Simple monitoring method
for precaution of landslides watching tilting
and water contents on slopes surface.
Landslides, 2010. 7(3): p. 351-357.
Uchimura, T., et al. Miniature ground
inclinometer for slope monitoring. in Proc. of
The 14th Asian Regional Conference on Soil
Mechanics and Geotechnical Engineering,
ATC3 session. 2011. Hong Kong, China.

297

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

BOX-SHAPE RETAINING WALL SYSTEM: EXPERIMENT AND
NUMERICAL PREDICTION
C.T. Nguyen2,3, Ha H. Bui1, N. Hiraoka2, A. Oya2, and R. Fukagawa2
1
Department of Civil Engineering, Monash University, Australia
2
Department of Civil Engineering, Ritsumeikan University, Japan
3
Institute of Mechanics, Vietnam Academy of Science and Technology, Vietnam

ABSTRACT
Box-shape retaining wall system has been extensively used to stabilize natural and cut-slope. Despite this fact,
numerical development for prediction of the large deformation and flexible behavior of retaining wall bocks isstill not advanced. To overcome this limitation, this paper presents a new numerical approach which can be used
to simulate large deformation and flexible behavior of the box-shape retaining wall system. Herein, soil ismodelled using an elasto-plastic constitutive model, while wall blocks are assumed rigidity with full degree of
motion. A linear contact model is proposed to simulate interaction between soil and wall block. Experiments
were also conducted to validate the proposed numerical framework. It is showed that the proposed numericalframework can simulate well behavior of the box-shape retaining wall system. The proposed method can bereadily extended to analyze dynamic response of a general segmental retaining wall.
Keywords: Box-shape retaining wall, large deformation, elasto-plastic, SPH

INTRODUCTION
Box-type retaining walls (BRW) have been used
as an effective method to stabilize cuts and fills
adjacent to highways, driver-ways, embankment,
etc. Because they are flexible structures, box-type
retaining walls can tolerate movement andsettlement without causing crack and damage,
particularly under seismic loading conditions.
Despite of its advantage, very few numerical studiesof large deformation of the BRW systems were
found in the literature. This is because it is very
difficult to simulate large deformation and flexible
behaviour of wall blocks (i.e. full rotational andtranslational motions) in the BRWs system using
traditional continuum based numerical methods suchas finite element method (FEM) which is sufferedfrom grid distortions. The Discrete Element Method(DEM) proposed by Cundall & Strack [1] which isanother popular numerical method in geotechnicalapplications may be applied to simulate dynamic
behaviour of the box-type retaining wall blocks in
the BRW system. However, the DEM suffers from
low accuracy in predicting soil behaviour due to thedifficulty in selecting parameters for contact laws. In
addition, the DEM cannot make use of advanced soil
constitutive models which have been extensively
developed in the literature. The discontinuous
deformation analysis (DDA) method proposed by
Shi et al. [2] has also been applied to geotechnicalapplications, but is mainly used for rock engineering,etc. In order to overcome the above limitations of
traditional numerical methods, continuum based

mesh-free methods such as the mesh-free Galerkinelement method (EFG) [3], material point method(MPM) [4], particle in cell method (PIC) [5], etc.,
could be also applied to simulate large deformationof soil. However, these methods are quite time
consuming and complicated to implement into a
computer code as they consist of both interpolation
points and the background mesh. On the other hand,the smoothed particle hydrodynamics (SPH) method,originally proposed by Gingold & Monaghan [6],has been recently developed for solving large
deformation and post-failure behaviour of
geomaterials [7-12] and represents a powerful way
to understand and quantify the failure mechanismsof soil in such challenging problems.
In this paper, taking into consideration theunique advantage of the SPH method, the SPH
method is further extended to simulate large
deformation and post-failure of the BRW systems.
Herein, soil is modelled using the elasto-plastic
Drucker-Prager constitutive model [8] and wall
blocks are assumed rigidity with complete degree ofrotation. A linear contact model which is similar tothe penalty contact law is proposed and is
implemented in the SPH code to simulate interaction
between soil and wall blocks, and between wall
blocks in the BWR systems. The developed model isthen applied to simulate large deformation of the
BRW system and comparing to a two-dimensional
experiment. Results showed good agreement withthe experiment, suggesting that the proposed method
is a promising approach for further design ofretaining walls subject to earthquake.
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GEOMATE-Nagoya, Nov.13-15, 2013

SIMULATION APPROACHES
Simulation of Soil in SPH Framework
In the SPH method, motion of a continuum ismodeled using a set of moving particles(interpolation points); each assigned a constant massand “carries” field variables at the corresponding
location. The continuous fields and their spatial
derivatives are taken to be interpolated from thesurrounding particles by a weighted summation, in
which the weights diminish with distance according
to an assumed kernel function. Details of theinterpolation procedure and its application to soil
can be found in Bui et al. [8]. The motion of acontinuum can be described through the following
equation,ρdv= ∇ ⋅ σ + ρg + f ext
dt(1)

where v is the vecolity; ρ is the density; σ is thetotal stress tensor, where negative is assumed forcompression; g is the acceleration due to gravity;and fext is the additional external force(s). The total
stress tensor of soil is normally composed of theeffective stress (σσ´) and the pore-water pressure (pw),and follows Terzaghi’s concept of effective stress.
Because the pore-water pressure is not considered,
the total stress tensor and the effective stress are
identical throughout this paper, and can be computed
using a constitutive model.
In the SPH framework, Equation (1) is often
discretized using the following form [8, 11],α

 σ αβ σ αβdva
αβ  β∇ a Wab= ∑ mb  a2 + b2 + Cab
dt
ρ
ρ
b =1
b
 a

α
α
+ g a + f ext→aN(2)

where α and β denote Cartesian components x, y,z with the Einstein convention applied to repeatedindices; a indicates the particle under consideration;
ρa and ρb are the densities of particles a and b
respectively; N is the number of “neighbouring
particles”, i.e. those in the support domain of particle
a; mb is the mass of particle b; C is the stabilization
term employed to remove the stress fluctuation andtensile instability [10]; W is the smoothing kernel
function which is taken to be the cubic Spline
function [13]; and fext→ a is the unit external force
acting on particle a.
The stress tensor of soil particles in Equation (2)can be computed using any soil constitutive model
developed in the literature. For the purpose of soilstructure interaction, the Drucker-Prager model has
been chosen with non-associated flow rule, which

was implemented in the SPH framework by Bui et al.
[8] and shown to be a useful soil model for
simulating large deformation and post-failure
behaviour of aluminum rods used in the current
paper as model ground. The stress-strain relation ofthis soil model is driven from the assumption of
additive decomposition of the total strain rate tensor,

ε& = ε& e + ε& p(3)

where a raised dot denotes the time derivative; ε&is the total strain rate tensor; ε& e is its elastic
component; and ε& p is its plastic component. The
elastic component is computed using the wellknown Hooke’s law; while the plastic component
can be calculated using the plastic flow rule [8],σ& = Dε& e∂g p
ε& p = λ&
∂σ

(4)
(5)

where D is the elastic stiffness matrix, λ& is therate of change of plastic multiplier, and gp is theplastic potential function.
According to the plasticity theory, the plastic
deformation occurs only if the stress state reaches
the yield surface. Therefore, the plastic deformation
will occur only if the following yield criterion issatisfied,

f = α φ I1 +J 2 − kc = 0(6)where I1 and J2 are the first and second invariantsof the stress tensor; and αφ and kc are DruckerPrager constants that are calculated from the
Coulomb material constants c (cohesion) and φ(internal friction). In the plane strain, the DruckerPrager constants are computed by,

αφ =
kc =

tan φ
9 + 12 tan2 φ
3c
9 + 12 tan 2 φ

(7)

(8)

The non-associated plastic flow rule specifies theplastic potential function by [9-10],g p = αψ I 1 + J 2 − constant(9)

where αψ is a dilatancy factor that can be related
to the dilatancy angle ψ in a fashion similar to thatbetween αφ and friction angle φ.
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GEOMATE-Nagoya, Nov.13-15, 2013

Substituting Equation (9) into Equation (5) inassociation with the consistency condition, that is
the stress state must be always located on the yieldsurface f during the plastic loading, the stress-strain
relation of the current soil model at particle a can be
written as [10],Motion of Rigid Wall Blocks
An arbitrary motion of a rigid body can be
represented as a superposition of translationalmotion in which all points of the body, including thecentre of mass, move with the same speed along
parallel trajectories, and rotation around the centreof mass. Accordingly, the motion of a rigid wall
block in the BRW system can be determined by
specifying the translational motion of the centre ofmass and the rotational motion about its mass central.
The equation of motion of the central mass is given
as follows,dσ aαβ= 2Ga e&aαβ + K a ε&aγγ δ aαβ
dt
(10)
αβ
αβ
&
− λ a 3 K a α ψ a δ + ( Ga / J 2 a ) s a[]

where eαβ is the deviatoric strain-rate tensor; sαβ
is the deviatoric shear stress tensor; and λ& is the rateof change of plastic multiplier of particle a, which in
SPH is specified by [10],λ&a =3α φ a K a ε&aγγ + (Ga / J 2 a )s aαβ ε&aαβ
9α φ a K aαψ a + Ga

M

(

)

1 β α
∇ u& + ∇ α u& β a
2

(11)

I
(12)

(13)

where ω& is the spin-rate tensor computed by

ω& aαβ =

(

)

1 β α
∇ u& − ∇ α u& β a2dV= ∑ fidtidΩI= ∑ (ri − R ) × f i
dt
k

M
(14)

As a result, the final form of the stress-strain
relationship for the current soil model is modified todσ aαβ= σ aαγ ω& aβγ + σ aγβ ω& aαγ + 2Ga e&aαβdt+ K a ε&aγγ δ aαβ − λ&a 3K aαψ aδ αβ

dΩ
=T
dt

(17)

where I is the inertial moment, Ω is the angularvelocity which is perpendicular to the plane of the
motion, and T is the total torque about the centralmass.
In the computation, the rectangular block isrepresented by the set of boundary particles that are
equi-spaced around the boundary. Denoting theforce vector acting on each boundary particle ilocated on the moving block is fi, Equations (16) and(17) can be rewritten, respectively, as follows,

When considering a large deformation problem,a stress rate that is invariant with respect to rigidbody rotation must be employed for the constitutive
relations. In the current study, the Jaumann stressrate is adopted:

σˆ& aαβ = σ& aαβ − σ aαγ ω& aβγ − σ aγβ ω& aαγ(16)where M is the central mass, V is the velocity
vector of the central mass, F is total force vector
acting on the body.
The equation of rotation about the central mass is,where the strain-rate tensor is computed by

ε&aαβ =

dV
=F
dt

(18)
(19)

where ri and R are vector coordinates ofboundary particle and central mass, respectively.
The rigid body boundary particles move as a part of
the rigid body, thus the change on position ofboundary particle i is given by,

(15)

dri
= V + Ω × (ri − R )dt+ λ&a (G / J 2 ) a s aαβ
Validation of the elasto-plastic Drucker-Prager
soil model with SPH has been extensively
documented in the literature [8-10], and readers canrefer to these references for further details on thevalidation process.

(20)

The force fi acting on a boundary particle on therigid body is due to the surrounding soil particles orboundary particles that belong to different rigid
bodies. This force can be calculated using any
suitable contact model.
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GEOMATE-Nagoya, Nov.13-15, 2013

where µ is the friction coefficient. Finally, theseforces are converted to the conventional coordinate
system and added to Equations (2), (18) and (19) toprogress the motion of soil and wall block.

Contact Force ModelIn this paper, a linear soft contact model basedon a concept of the spring and dash-pot system is
proposed to model the interaction between soil andretaining wall blocks and between blocks.
Accordingly, the radial force acting between two
particles can be calculated using the following
equation,

f

n
a→i

− K ai δ n − c n v nak=0

hai > 2 d ai
hai ≤ 2 d ai

TWO-DIMENSIONAL EXPERIMENTS
A serial of two-dimensional box-shape retaining
wall system collapses were conducted to investigate
the failure mechanism of the BRW system and toverify the proposed numerical framework. Fig.1
outlined the initial setting condition of the BRW
system which consists of six rectangular wall blocks.
The size of the model ground is 15cm in height and50cm in width at the base. Soil was modelled usingaluminum rods of 1.6mm and 3mm in diameters,
50mm in length, and mixed with the ratio of 3:2 inweights. The wall block is 3.2cm in width, 2.5cm inheight, and 5cm in length, which is also
manufactured from aluminum. In the experiment,
the BRW system was constructed by successively
placing one wall block on the top of the other withan overlapping of 1.2cm, followed by filling themodel ground at each layer. The BRW system wasstabilized by a stopper stand as shown in Fig. 1. To
visualize the failure pattern of the model groundafter collapse, square grids (2.5×2.5cm) were drawn
on the soil specimen. The experiments were initiatedby quickly removing the stopper stand and digital
photos were taken to record the failure process aswell as the final configuration of the BRW systemafter collapse. A series of experiments wereconducted starting from one block and thengradually increasing the number of blocks in the
BRW system until the retaining wall is collapsed.
The experimental evidences consistently showedthat the BRW system will collapse when reaching 6
blocks height. Accordingly, a numerical model
consisting of six retaining wall blocks will be
conducted in the next section to verify the proposed
numerical framework. A total of six experiments
were conducted to verify the failure mechanism of
the BRW system and the final run-out distance ofeach block in the BRW system. In all experiments,
the failure mechanism of the BRW systems wasmore and less the same as shown in Fig.2.

(21)

where K is the radial stiffness; δn is the allowable
overlapping distance between two particles; cn is theradial damping coefficient; vn is the relative radial
velocity vector between particle a and particle i; haand hai are the sum of the initial separation between
soil particles and between boundary particles,
respectively; and dai is the distance between two
particles. The overlapping distance and radial
damping coefficient can be calculated using thefollowing relationships,

δ n = d ai − hai / 2(22)c n = 2 mai K ai

(23)

The contact force in the shear direction which isperpendicular to the radial direction can becalculated in the same manner,

f

s
a →i

− k ai δ s − c s v ais=0

hai > 2d ai
hai ≤ 2d ai(24)where kai is the shear stiffness which is taken
similar to K; δs is the relative shear displacement
between the two particles; cs is the shear damping
coefficient; vs is the relative shear velocity vector
between particle a and particle i. The relative shear
displacement and shear damping coefficient arecalculated by,δ s = ∫ v ais dt(24)

c s = 2 m ai k ai

(26)

The current shear force must satisfy Coulomb’s
friction law which implies that the maximum shear
force must not exceed the maximum resisting force,f as→i ≤ µδs n
f a →iδs(25)

Fig. 1

301

Initial setup of model ground and theretaining wall blocks in the BRW system.

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 2

Typical final configurations of the BRW
system observed in the experiment after
collapse for two different tests.

Fig. 3Outline of sliding test to measure friction
between model ground and wall block.

those measured by Umezaki et al. [15]. The unit
weight of the ground model is γs = 20.4kN/m3. In
addition to the ground parameters, parameters forthe linear contact model needed to be specified. In
this paper, the radial and shear stiffness wereassumed to be K = k = 1×109N/m. The friction
coefficients between the ground model and the block,between the rigid blocks, and between the block andthe bases of the wall boundary were taken similar to
those measured in the sliding tests as explained in
the experimental section. The boundary conditions
for the model ground are restrained with a free-slip
boundary at the lateral boundaries and fixed in both
directions at the base [8].
Fig. 4 shows the comparison between theexperiment and the computation for the final
configuration of the BRW system after collapse. It
can be seen that the computed result could predict
fairly well the behavior of all rigid blocks observedin the experiment after the BRW system wascollapsed. The good agreement between experimentand simulation can be attributed to the fact that thecomplete degrees-of-freedom of the rigid wall was
taken into consideration in the simulation and large
deformation and post-failure behavior of soil could
be simulated well in the current SPH framework.
Comparing the final run-out distance of eachblock, for instance Block No.1, it can be seen thatthe final position (right edge) of Block No.1 in thesimulation is approximately ∼68.3cm from the leftmost solid boundary. This result is in fairly good
agreement with that observed in experiment which
was approximately ∼66.2cm. This suggests that the
proposed numerical framework could be applied tosimulate the soil-structure interaction in the BRW
system. However, further refinement of the contact
model should be considered to provide a moretheoretical sound framework to specify theparameters for the contact model.

In addition to the retaining wall collapse
experiments, sliding tests were also conducted tomeasure friction coefficients between the wall
blocks, between the soil model and the wall block,and between the block and the bottom solid wall.
Outline of these tests are shown in Fig. 2. Based onthese experiment, it was found that the friction (µ)
between retaining wall blocks is µ ∼ 0.31, between
the retaining wall block and model ground is µ ∼0.38, and between wall block and the bottom wallboundary is µ ∼ 0.49.

SPH simulationt = 0.742s
5cm

6SIMULATION OF BOX-SHAPE RETAINING
WALL COLLAPSE USING SPH

5

4 3 2

1

Experiment

The model test shown in Figure 1 was simulatedusing 11,304 SPH particles arranged in a rectangularlattice with an initial separation of 0.25cm. Rigid
blocks were created by placing boundary particles
uniformly around the boundary at a constantdistance. In order to simulate the smooth surface,half of particle spacing was chosen for the rigid
body boundary particles. Model ground parameters
including elastic modulus E = 5.84MPa, Poisson’s
ratio ν = 0.3, friction angle φ = 21.9o, dilatant angle
ψ = 0o, and cohesion c = 0kPa were taken similar to

5cm

Fig. 4302

Comparison between the SPH simulations
and the experiment for the final
configuration of the BRW system.

GEOMATE-Nagoya, Nov.13-15, 2013

to non-spherical stars”, Mon. Not. Roy. Astron.
Soc., Vol.181, 1977, pp.375-389.
[7] Bui HH, Sako K, and Fukagawa R, “Numericalsimulation of soil-water interaction usingsmoothed particle hydrodynamics (SPH)
method”, Journal of Terramechanics, Vol.44,
2007, pp.339-346.
[8] Bui HH, Fukagawa R, Sako K. and Ohno S.
“Lagrangian mesh-free particle method (SPH)
for large deformation and post-failure ofgeomaterials
usingelastic-plastic
soil
constitutive model, International Journal for
Numerical and Analytical Methods inGeomechanics”, Vol. 32, 2008, pp.1537-1570.
[9] Bui HH, Fukagawa R, and Sako K, “Slopestability analysis and discontinuous slope failure
simulation by elasto-plastic smoothed particle
hydrodynamics (SPH)” Géotechnique, Vol.61,
2011, pp. 565-574.
[10] Bui HH and Fukagawa R, “An improvement of
SPH for saturated soils and its application toinvestigate the mechanisms of embankment
failure: Case of hydrostatic pore-waterpressure”, International Journal for Numericaland Analytical Methods in Geomechanics, Vol.
37, 2013, pp.31-50.
[11] Blanc T, and Pastor M, “A stabilized smoothed
particlehydrodynamics,
Taylor-Galerkinalgorithm for soil dynamics problems”,
International Journal for Numerical andAnalytical Methods in Geomechanics, Vol.37,
2013, pp.1-30.
[12] Pastor M, Haddad B, Sorbino G, Cuomo S, andDrempetic V, “A depth-integrated, coupled SPH
model for flow-like landslides and related
phenomena”
International
Journalfor
Numerical and Analytical Methods inGeomechanics, Vol.33, 2009, pp.143-172.
[13] Monaghan JJ, “SPH elastic dynamics”.
Computer Methods in Applied Mechanics andEngineering, Vol.190, 2003, pp.6641-6662.
[14] Monaghan JJ and Lattanzio JC, “A refinedparticle method for astrophysical problems”,
Astronomic & Astrophysics, Vol.149, 1985,
pp.135-143.
[15] Umezaki T, Kawamura T, and Ochiai H,“Increment of Confining Pressure Due To Pullout of Reinforcement Anh Modelling ofReinforcing
Mechanics”,
Geosynthetics
Engineering Journal, Vol.20, 2005, pp.241-248.
(in Japanese).

CONCLUSION
This paper presented a new numerical approachfor simulation of large deformation and post-failureof box-shape retaining wall system. It was shownthat the proposed method provides good agreementwith the experimental results. One of the key
advantages of the proposed method is that thecomplete degrees-of-freedom of the retaining wall
blocks, which could not be simulated using
traditional numerical approaches such as finite
element method, can now be simulated in the
proposed numerical framework. Large deformationand post-failure behaviour of geomaterials can also
be readily simulated. In order to broaden theapplication of the proposed numerical approach ingeotechnical engineering, generalized contact modelis necessary. This work is in progress and will bereported in the near future.
ACKNOWLEDGEMENTS
The first author would like to thank the Japan
Society for the Promotion of Science (JSPS) for
providing doctoral scholarship through the
RONPAKU Program.
REFERENCES[1] Cundall PA and Struck ODL, “A discrete
numerical model for granular assemblies”,
Géotechnique, Vol.29, 1979, pp.47-65.
[2] Shi GH, “Discontinuous deformation analysis: a
new numerical model for the static anddynamics of block systems” Ph.D. Thesis, 1988,
University of California, Berkeley.
[3] Belytschko T, Lu YY, and Gu L, “Element-free
Galerkin methods”, International Journal for
Numerical Methethods in Engineering, Vol.37,
1994, pp.229–256.
[4] Sulsky D, Chen Z, and Schreyer HL. "A particle
method for history-dependent materials".
Computer Methods in Applied Mechanics andEngineering, Vol.118, 1994, pp.179-196.
[5] Harlow FH, Ellison MA, and Reid JH, "Theparticle-in-cell computing method for fluid
dynamics". MethodsinComputational
Physics. Vol.3, 1964, pp.319–343[6] Gingold RA and Monaghan JJ, “Smoothed
particle hydrodynamics: Theory and application

303

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PERMEABILITY AND CONSOLIDATION BEHAVIOR OFCOMPOSITE GROUND REINFORCED WITH SAND COLUMNS
B. A. Mir1 and Ashish Juneja2
Faculty, Deptt. of Civil Engg., National Institute of Technology Srinagar-006, J&K,, India
2
Faculty, Deptt. of Civil Engg., Indian Institute of Technology Bombay-076, Mumbai,, India
1

ABSTRACTIn this paper, the behavior of the composite ground reinforced with sand columns with and without smear
effect installed in 200mm long and 100mm diameter cylindrical clay specimens was investigated using
conventional triaxial consolidation tests under different confining pressures ranging from 50kPa to 575kPa.
Change in volume of the specimen was measured using automatic volume change apparatus. This typicallyrequired a consolidation time of about 100minutes compared to more than 6-7days required to consolidate thespecimen without the sand columns. However, specimens prepared with smear effect took slightly more time toconsolidate thereby lending further confidence to the method used to create the smear zone. The test results
showed that the dissipation of excess pore water pressure occur faster in the radial direction due to the greater
coefficient of soil permeability in the horizontal direction and the reduced drainage path.
.
Keywords: Composite ground, Sand column, Smear, Soil improvement, Consolidation, Permeability

considered as cost-effective method as well as
alternative solution to the problem of stability andsettlement posed by construction on soft ground. In
particular, the insertion of stone or sand columns
into soft clay has been shown to have a positiveeffect on the load carrying capacity of the clay,
resulting in a composite soil mass that has greater
shear strength and improved stiffness compared tothe unreinforced clay. In addition, sand columns
generally act as vertical drains in the clay thus
accelerating the dissipation of excess pore waterpressures that are generated during preloading. As
such, sand columns currently stand as one of themost viable and practical techniques for improving
the mechanical properties of soft clays. The
consolidation time can be reduced to achieve a
required degree of consolidation by selecting
suitable drain spacing and an appropriate installation
pattern [1]. This method of ground improvement has
been widely used for rapid improvement of soft
ground, and also in near-shore regions for land
reclamation works e.g. [2]-[4]. In India, the sandcolumns have been used to improve ground forcontainer freight station at Navi Mumbai and theconstruction of dry dock at Pipavav shipyard Gujarat[5]. But, installation of the sand columns is known tocause disturbance due to smear in a limited zone of
the soil surrounding the sand column [6]. Thicknessof the disturbed zone depends upon the roughness ofthe casing used during the installation and, isassociated with reduced permeability and high porepressures. Laboratory and field tests previously
conducted to determine the extent of the disturbancecaused by pile driving into soft clay deposits have

INTRODUCTION
Soft clay deposits usually have a low bearing
capacity and undergo excessive settlement over along period of time. One of the important problems
geotechnical engineers are often to deal with is theaccurateandreliablemeasurementofcompressibility and permeability characteristics ofsoft soils. The coefficient of consolidation is an
essential soil parameter required for seepage,
settlement, stability calculations and for predicting
the rate of settlement of soft soils. The importanceof compressibility characteristics are further
increased in case of environmental problems, such aswaste disposal and detrimental effects on thesurrounding ground due to contamination.
In the recent years, improvement of soft soils has
been extensively implemented for the various
development projects all over the world due toextremely limited stable construction sites. But oneof the major problems associated with soft soils is
the presence of thick deposits of soft clayey ground.
Thus, soft clay foundations present considerable
construction problems. Therefore, where poor
ground conditions make traditional forms of
construction expensive, it may be economically
viable to attempt to improve the engineering
properties of the ground before building on it. Thiscan be done by reducing the pore water pressure, byreducing the volume of voids in the soil, or byadding stronger materials. Although there are avariety of ground improvement techniques under
different categories, granular piles such as sandcolumns or sand compaction piles (SCPs) are304

GEOMATE-Nagoya, Nov.13-15, 2013

demonstrated that the natural structure of the clayaround the pile is excessively disturbed [7]-[9].
Recently, Weber TM et al. [10] compared the smear
zone around model SCPs installed on the centrifuge
to that observed around driven piles. The smear zone
around the SCP was observed to extend up to 1.2 to
1.4 times the SCP diameter. It was perhaps not acoincidence that the thickness of the smear zone wascomparable to the thickness of the disturbance,
which is usually observed around piles driven in soft
clays [7]. Similarly, Bond and Jardine [11] observedthat the thickness of the smear zone was narrow
when the piles were driven in overconsolidated
clays. If the extent of the disturbance around SCPs istaken analogous to that observed around driven
piles, then any change in the clay fabric during the
SCP installation will also affect the permeability andpore pressure dissipation, and consequently the loadcarrying capacity of the composite ground [12]-[13].
Laboratory tests on model sand drains haveshown significant reduction in the horizontal
permeability in the vicinity of the drain, and theextent of the smear zone caused by mandrel driven
vertical drains, which otherwise was estimated basedon the pore pressure generated [14]-[16]. The extent
of the smear zone was also confirmed from thechange in permeability of the clay layer in the smear
zone obtained from oedometer tests [17].
In this paper, the behavior of the composite
ground reinforced with sand columns is analyzed.
The consolidation of model sand columns installed in
100mm diameter and 200mm long clay specimens
was investigated using conventional triaxial
consolidation tests. The composite specimens wereprepared by driving a small diameter PVC casing
into the specimen and then backfilling the cavity
with sand column after removing the casing. The
casing was painted using sand glued with araldite
prior to the insertion to create smear zone. Diameterof the sand particles glued to the casing was taken asa measure of the smear zone. The composite
specimens were first saturated and then consolidated
isotropically under different confining pressures
ranging from 50kPa to 575kPa. Change in volumeof the specimen during consolidation was measured
using automatic volume change apparatus. Thistypically required a consolidation time of about
100minutes compared to more than 6-7days required
to consolidate the specimen without sand columns.
However, specimens prepared with smear effect tookslightly more time to consolidate thereby lending
further confidence to the method used to create thedisturbed zone. The results show that the dissipationof excess pore water pressure occurs faster in theradial direction due to the greater coefficient of soil
permeability in the horizontal direction and the
reduced drainage path. Thus, the main function ofsand column application is to accelerate soil
consolidation by shortening the drainage path andactivating radial drainage, thereby reducing postconstruction settlement [18].
EXPERIMENTAL WORK
Materials and methods of sample preparation
Isotropic consolidated triaxial tests were performedon 100mm diameter and 200mm long specimens[19] prepared from commercially available kaolin
clay. The experimental program consisted of 18
triaxial consolidation tests on composite specimen.
The triaxial samples were prepared in 250mm
diameter and 450mm long stainless steel cylindricalmould. Up to 3 specimens could together be
prepared using this mould. De-aired clay slurry was
consolidated on the laboratory floor, first under its
own self-weight and later under surcharge of 211- to
404kN/m2 applied in stages on top of the clay
surface using a custom designed pneumatic load
frame. Upon completion of the 1-D consolidation,
the block of clay was extruded and trimmed into
three 100mm diameter specimens using soil lathe(Fig. 1). Three additional steps were undertaken to
prepare the composite samples. In the first step, acylindrical hole was cored through the centre of thesample using a thin, smooth casing. The diameter ofthe hole varied between 25 and 45 mm in different
tests. In the second step, air-dry sand (d 50 = 0.3 mm)
was poured into the hole in layers and each layercompacted at 90% relative density using apneumatic compactor. The final diameter of the SCP
was equal to the diameter of the hole (Fig. 2).

100m

200
mm

Fig.1 Consolidation set-up on the laboratory floor
and specimen trimming

PVC casing
pushed into
the sample

Pneumatic
compactor

Soil sample

Sand

Fig. 2 Preparation of composite specimen
In some tests, the outer surface of the casing was
made gritty by painting a paste of coarse sand mixed
with araldite. This helped to create a smear zone
around the compacted sand column. In the third step,305

GEOMATE-Nagoya, Nov.13-15, 2013

two circular rubber sheets with a hole at the centre
were placed at the ends of the sample. The diameterof the hole was slightly less than that of the sandcolumn so as to only permit radial drainage duringconsolidation. Table 1 shows the properties of theclay and Table 2 shows experimental program usedin this study.

were placed at the two ends of the sample so as toonly permit radial drainage during consolidation.
Change in volume of the sample duringconsolidation was automatically measured using thevolume change apparatus. The effect of smear zone
was investigated by observing the change in porepressure during consolidation of the composite
specimen. Fig. 3a-c shows the average degree ofconsolidation, U avg plotted against time duringisotropic consolidation.

Table 1 Properties of kaolin clay
Silt
(%)

75

25

Liquid
limit
(%)
49

Plastic
limit
(%)
23

Shrinkage
limit (%)

Gs

16

2.64

0

Table 2 Experimental program for composite
samples
Smear
zone

p′ c
$
(kP
a)

p′** (kPa)

σ'c = 300kN/m2
σ'c = 150kN/m2
σ'c = 100kN/m2

0.4
0.6
0.8

OCR =
p′ c/ p′ds#
Test σ′ v *No (kPa) (mm)Without smear
With smear

0.2
U avg

Clay
(%)

1
0

S1
404
25 (no)
285
100
3

S2
404
25
285
150
2

S3
404
25
285
300
1
S4
264
29 (yes)
187
100
2

S5
264
29
187
150
1.2

S6
264
29
187
300
1

S7
211
32
149
450
1

S8
211
32
149
200
1

S9
211
32
149
50
3

S10 211
36
149
450
1

S11 211
36
149
200
1

S12 211
36
149
50
3

S13 211
40
149
375
1

S14 211
40
149
575
1

S15 211
40
149
75
2

S16 211
45
149
575
1

S17 211
45
149
375
1

S18 211
45
149
75
2
*:
σ′ v =Vertical stress at end of 1D loading,#:d s = Equivalent diameter of sand column,$:
p′ c =Preconsolidation pressure= σ′ v /3 (1+2k o )**:P′ = mean effective stress at end of consolidation

20

40

60

80

100

Elapsed time (min)(a)

0Without smear
With smear

Uavg

0.2

σ'c = 450kN/m2
σ'c = 200kN/m2
σ'c = 50kN/m2

0.4
0.6
0.8
1
0

20
40
60
80
Elapsed time (min)

100

(b)

0

Without smear
With smear

Uavg

0.2

In this table, σ v is the 1-D vertical stress used forconsolidating slurry in cylindrical mould on the laboratory
floor. Mean effective stress (p′) towards the end of 1-D
loading was estimated using K o (0.56) obtained fromundrained shear test results.

σ'c = 375kN/m2

0.4

σ'c = 75kN/m2
σ'c = 575kN/m2

0.6
0.8
1
0

RESULTS AND DISCUSSIONS

20
40
60
80
Elapsed time (min)

100

(c)

Variation of consolidation
Fig.3a-c

Triaxial consolidation tests were performed on
200mm long and 100mm diameter cylindrical
specimens
preparedfrom
remoldedandreconsolidated commercially available kaolin clay.
Two circular rubber sheets with a hole at the centre
306

Variation of average degree ofconsolidation with time using sandcolumns of: (a) 25mm diameter; (b)32mm diameter; and (c) 40mm diameter.

GEOMATE-Nagoya, Nov.13-15, 2013

As can be seen, the figures show that the time to
90% consolidation reduced from about 400 min toless than 60 min with the use of sand column.
However, specimens prepared with smear effecttook slightly more time to consolidate thereby
lending further confidence to the method used tocreate the disturbed zone. The figure also shows that
not all specimens with smear effect wereconsolidated up to U avg of 1. Similar results havebeen reported under radial drainage by many
researchers [20]-[22].

Variation of water content
Figure 5 shows water content variation at different
locations measured after the completion of few
selected tests with and without smear effect. The
figures show that water content was not uniform
throughout the sample length, and the water content
was higher in the samples with the smear zone which
supports the above supposition that the smear zone
does not permit the complete dissipation of the porepressure. The results seem to suggest that radial
drainage can give rise to significant non-uniformities
during consolidation of soil specimens. Similar
results have also been reported by [20].

Variation of coefficient of permeability andcoefficient of consolidation

35

Without smear
With smear

σ'c =150kN/m2 Height above base (mm)34

Without smear
With smear
142.5
142.5
125
125
105
105
85
85
65
65
45
45
25
25
7.5
7.5

33
32
31
30
29
28

Edge of sand column

Water content (%)

4
3.5
3
2.5
2
1.5
1
0.5
0

27
12.5

25

37.5

35

100

200

300

400

500

600

700

Mean effective stress, p' (kPa)(a)
60

σ'c =450kN/m2 SCP dia. =32mm without smear

34
33
32
31
30
29
28

SCP dia. =36mm with smear

Height above base (mm)Edge of sand column

0With smear
Without smear
142.5
142.5
125
125
105
105
85
85
65
65
45
45
25
25
7.5
7.5

27
15

25

35

45 50

Radial distance (mm)

40
32

20

Without smear
With smear

10
0
0

100

200

300

400

500

600

700

Mean effective stress, p' (kPa)

σ'c =575kN/m2
SCP dia. =40mm without smear; SCP dia. =45mm with smear

31

Height above base (mm)

30
29
28
27

Without smear
142.5
125
105
85
65
45
25
7.5

Edge of sand column

30

Water content (%)

2

Ch, (m /year)

50

With smear
142.5
125
105
85
65
45
25
7.5

26

(b)
Fig.

50

Radial distance (mm)Water content (%)-9

k*10 , m/sec

Figure 4a shows the variation of coefficient of
permeability, k for selected soil specimens deduced
from consolidation data against p' using theprocedure suggested by [23].

20

30

40

50

Radial distance (mm)4a-b Variation of: (a) coefficient of
permeability;(b)coefficientofconsolidation with mean effective stress forcomposite samples.

Fig. 5 Variation of water content at different
locations measured after the completion of
the tests for composite samples under
different confining pressures with andwithout smear effect.

The results seem to suggest that there was a marginal
reduction of permeability by about 20% when
specimens were prepared using the smear effectcompared to the k of the composite samples preparedwithout the smear zone. The variation of coefficientof horizontal consolidation with mean effective stressis shown in Fig. 4b above.

This is also evident from Scanning Electron
Microscope (SEM) images (Fig. 6a-d) taken on postcompression tests of specimens with and without
smear. 7.5mm x 7.5mm x 7.5mm air dried samples
were prepared at room temperature for SEM images.
307

GEOMATE-Nagoya, Nov.13-15, 2013

The images of samples with and without the smear
zone show differences in the microstructure. The
clay minerals in the smear zone appear to be closely
packed with reduced pore space. As such,permeability of the composite samples with thesmear zone is reduced with reduced pore space inthis zone. The properties within the smear zone arealso shown to vary with the overburden pressure[24]. Notwithstanding the above, the focus of thisstudy is to note the difference in the soil behavior
when a well defined smear zone is formed
surrounding the sand column.

Pores(a). Mean eff. stress at end of consolidation (50kPa)

CONCLUSIONSPores

The permeability and consolidation behavior of
the composite ground reinforced with sand columns
with and without smear effect was studied using 18
triaxial consolidation tests on composite specimens.
It is seen that specimens with sand column (inward
radial consolidation) is more effective to improve
permeability and consolidation characteristics thancompared to conventional clay specimen, which
require more than 6-7days to consolidate without
the sand columns. The test results showed that thedissipation of excess pore water pressure occur
faster in the radial direction due to the greater
coefficient of soil permeability in the horizontal
direction and the reduced drainage path. But the
installation of the sand columns by means of a roughcasing cause remolding of the subsoil in a limitedzone of the soil surrounding the sand columns. The
presence of smear zone was shown to affect theconsolidation and permeability characteristics of thecomposite sample. Effect of smear zone surrounding
the sand column was evident from the additionaltime taken to consolidate the composite triaxial
specimen and because of reduced soil permeability.
The soil permeability was reduced by about 20%
which was also manifested by the water content
variation and pore pressure dissipation in thecomposite specimen. Also, in present study, ahollow open ended casing was used to remove thesoil and form a cavity for installing sand columns,
which may not yields realistic pore pressures in theclay during installation. Hence, the effective stressmanifested due to the all-round uniform cell pressure
is not uniform throughout the specimen. The nonuniformity of consolidated ground and its
consequence on subsequent construction of
structures needs further study. In order to simulate
the better field conditions, installation of driving-inof closed ended casing may be used. Further,amongst the various techniques for improving in-situ
ground conditions, columnar inclusions such as sandcolumns/sandcompaction
piles,
stone
columns/granular piles etc., are considered as one of
the most cost effective ground improvement
techniques as well as good drainage systems.

(b). Mean eff. stress at end of consolidation (450kPa)(c). Mean eff. stress at end of consolidation (50kPa)(d). Mean eff. stress at end of consolidation (450kPa)
Fig. 6 SEM images: (a-b) Composite samples
without smear zone, (c-d) Composite
samples with smear zone.

308

GEOMATE-Nagoya, Nov.13-15, 2013[11] Bond AJ and Jardine RJ, “Effects of installing
displacement piles in high OCR clay”,
Geotechnique 41(3), 1991, pp. 341–363.
[12] Madhav MR, Park YM and Miura N,“Modelling and study of smear zones aroundband shaped drains”, Soils and Foundations
33(4), 1993, pp. 137–149.
[13] Sharma JS and Xiao D, “Characterization of asmear zone around vertical drains by large-scalelaboratory tests”, Canadian Geotechnical
Journal 37(6), 2000, ppp. 1265–1271.
[14] Indraratna B and Redana IW, “Laboratory
determination of smear zone due to verticaldrain installation”, Jl. Geotech. Engg., ASCE,
Vol. 124, No. 2, 1998, pp. 180-184.
[15] Sathananthan I and Indraratna B, “Laboratory
evaluation of smear zone and correlation
between permeability and moisture content”,
Journal of Geotechnical and Geoenvironmental
Engineering, ASCE, Vol. 132, No. 7, 2006, pp.
942-945.
[16] Sathananthan I, Indraratna B
andRujikiatkamjorn C, “Evaluation of smear zone
extent surrounding mandrel driven verticaldrains using the cavity expansion theory”,
International Journal of Geomechanics, Vol. 8,
No. 6, 2008, pp. 355-365.
[17] Andreou P, Frikha W, Frank R, Canou J,
Papadopoulos V And Dupla JC, “Experimental
study on sand and gravel columns in clay”,
Proceedings of the ICE - Ground Improvement161(4), 2008, pp. 189-198.
[18] Holtz RD, Jamiolkowski M, Lancellotta R andPedroni S, “Prefabricated vertical drains: design
and performance, CIRIA Ground Engineering
Report: Ground Improvement”, ButterworthHeinemann Ltd, UK, 1991.
[19] BS 1377-1, “Methods of test for soils forgeneral requirements and sample preparation’,
British Standards Institute, 1990, London.
[20] Atkinson JH, Evans JS and Ho EWL, “Nonuniformity of triaxial samples due toconsolidation
withradialdrainage”,
Geotechnique 35(3), 1985, pp. 353-355.
[21] Robinson RG and Shilpa D, “Equal strain
consolidation of clays under radial drainage”,
Indian Geotechnical Journal, 38(2), 2008, pp.
204-220.
[22] Mir BA, “Study of the influence of smear zone
around sand compaction pile on properties ofcomposite ground”, Ph.D. Thesis, Deptt. of
Civil Engineering, IIT Bombay, 2010.
[23] Barron RA, “Consolidation of fine-grained soils
by drain wells”, Transactions ASCE, 113,
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[24] Bergado DT, Alfaro MC and Balasubramaniam
AS, “Improvement of soft Bangkok clay using
vertical drains”, Journal of Geotextiles andGeomembranes 12, 1993, pp. 615-663.

ACKNOWLEDGEMENT
The first author would like to acknowledge thefinancial support from the Indian Institute ofTechnology Bombay (IITB) in the form of researchscholarships.
REFERENCES[1] Jamiolkowski M, Lancellotta, R and Wolski W,“Precompression and speeding up consolidation”,
Proc. 8th European Conference on Soil
Mechanics and Foundation Engrg., Helsinki, vol.
3, 1983. pp. 1201-1206.
[2] Aboshi H, Ichimoto E, Enoki M and Harada K,“Composer: method to improve characteristics
of soft clays by inclusions of large diametersand column”, Proceedings of the International
Conference on Soil Reinforcement: Reinforced
Earth and other Technique, Paris, Vol. 1, 1979,
pp. 211-216.
[3] Aboshi H and Suematsu N, “Sand compaction
pile
method:State-of-theartpaper”,
International
Proceedings
of
the
3rd
Geotechnical Seminar on Soil Improvement
Methods, Narryang Technological Institute,Singapore, 1985, pp. 38-44.
[4] Bergado DT and Balasubramniam AS,“Laboratory testing of prefabricated verticaldrains (PVD)”,
Geotechnical Engineering
Journal, Vol. 25, No. 1, 1994, pp.1.
[5] Raj D and Dikshith CV, “Vibro replacement
columns for shipyard infrastructure at Pipavav,
Gujarat, India”,
Proceedings of theInternational
SymposiumonGroundImprovement Technologies and Case Histories,
GeoSS, Singapore, 2009, pp. 763-769.
[6] Juneja A and Mir BA, “Behavior of clay
reinforced by sand compaction pile with smear”,
Proceedings of the ICE-Ground Improvement,
165 (2), 2012, pp. 111-124.
[7]
Randolph MF, Carter JP and Wroth CP,“Driven piles in clay-the effects of installationand subsequent consolidation”, Geotechnique
29(4), 1979, pp. 361-393.
[8] Singh G and Hattab TN, “A laboratory study ofefficiency of sand drains in relation to methodsof installation and spacing”, Geotechnique
29(4), 1979, pp. 395-422.
[9] Xu XT, Liu HL and Lehane BM, “Pipe pile
installation effects in soft clay”, Proceedings ofthe Institution of Civil Engineers, GeotechnicalEngineering 159, Issue GE4, 2006, pp. 285-296.
[10] Weber TM, Plotze M, Laue J, Peschke G and
Springman SM, “Smear zone identification andsoil properties around stone columns
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Geotechnique 60(3), 2010, pp.197–206.

309

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

LABORATORY EVALUATION OF PHYSICO-CHEMICALVARIATIONS IN BENTONITE UNDER ELECTROKINETIC
ENHANCEMENT
Nasim Mosavat1, Erwin Oh1 and Gary chai3
Griffith School of Engineering, Griffith University, Australia
2
Centre for Infrastructure Engineering & Management, Griffith University, Australia
1

ABSTRACT
When the traditional ground improvement techniques are not practical for a particular situation, alternativetechnology, such as electrokinetic (EK) soil treatment can be considered. EK treatment method involves
applying a low direct current (DC) or a low potential gradient to arrays of electrodes inserted in the low
permeable soils simulating migration of electricity, pore water, ions and charged particles across the soil, hence
modifying the physicochemical, mechanical and engineering properties of the soil. This study investigates theeffects of EK treatment on conductance phenomena and physico-chemical changes of bentonite at different
intervals under total applied voltage of 10V subjected to specific types of anode enhancement solutions. The
cumulative electroosmotic flow and electric current through the sample was measured for 15 days of treatment.
The specimens were also tested for moisture content, pH and undrained shear strength variations over different
time periods of 3, 6, 9, 12 and 15 days showing good correlations between the soil parameters.
Keywords: Electrokinetic, Enhancement solutions, Bentonite, Physico-chemical
1.

beneficial to decrease the extreme acidity at theanode; manage/neutralise anode pH; facilitate theelectro-osmotic flow, and enhance the EK processacross the soil. The combined effects of theseprocesses together with various geochemical
reactions alter the chemical composition of the soil
porous medium and hence modify thephysicochemical properties of the soil during the EK
treatment.

INTRODUCTION

The use of EK treatment, which is a comparatively
new methodology, is being investigated in someparts of the world as a viable in situ soil stabilisationand treatment method [1-10]. EK soil treatment
method also termed as electro-chemical soil
processing, uses low intensity direct current (DC) ora low electric potential, to remove pore water andmodify fine-grained soils, mud, sludge, slurries andsediments by electric potential. The transportation of
charged chemical species across the soil involves
several complex mechanisms such as electrolysis,electro-osmosis,
electromigration
andelectrophoresis. In this regard, application of directelectric current (EC) has various effects such as:

Although the EK technology has been proven to be
useful in many laboratory and field tests, theapplication of the technology is still limited. Thismay be due to the complicated and unknown
features such as conductance phenomena andelectrochemical reactions during this treatment.
Field electro-osmotic mechanism is different fromlaboratory experiment and moreover, the EK
treatment with the injection of lime and salineenhancement solutions (chemical stabilisers) has
rarely been discussed. In this regard, there a need for
a comprehensive experimental program to be carriedout for a better fundamental understanding thechanges in soil during and after the treatment. Suchinformation would be of particular interest in the
improvement of marine soils possessing highmoisture content (Mc) and low baring capacity on
existing infrastructure. The aim of this study is toevaluate the conductance phenomena and several
physico-chemical modifications of bentonite clay
subjected to hydrated lime and saline enhancement
under the total applied voltage of 10 V (0.3 V/cm
voltage gradient) during 15 days of treatment.

i. It results in electrolysis of water which brings
about oxidation at the anode, generating an acidfront, and reduction at the cathode, producing abase front [11]ii. It generates two migrations: an ionic migration(electromigration) and electrophoresis ofcolloidal particles.
iii. It establishes an electric potential difference
which will lead to generation of electro-osmosis
through the sample [12].
This technique can also be enhanced by introducing
desirable chemical compounds (enhancement
solutions) such as lime, calcium chloride or even tap
water to the soil by injecting them at the appropriate
electrode, preferably anode. The introduction of an
appropriate chemical enhancement solution can be

310Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

2.

EXPERIMENTAL SOIL

3.

Some studies have shown that bentonite exhibits
much higher buffering capacity (resistance tochange in pH) because of higher CEC comparedwith other clay minerals, compared to kaolinite [13].
Despite several industrial and engineering
applications of bentonite, such deposits exhibit largeof swell/shrink behaviour upon moisturefluctuations and being sensitive to the changes inchemical environment. Therefore, it is known as oneof the dangerous types of clay and can lead toserious engineering problems such as slope or wall
failures, high swell/shrink behaviour leading todifferential settlements and large cracks. Therefore,
Na-bentonite was selected in this study toinvestigate the potential of EK treatment techniqueincorporated with chemical stabilisation to
improve/stabilise soft soils. The original propertiesof the bentonite are summarized in Table 1.
Table 1. Original properties of the bentonite
Soil characteristics

ValuesReferences

Clay mineralogy

Bentonite-

Liquid limit (%)

650

AS 1289.3.1.1-1995

Plasticity index,
(%)

450

Linear shrinkage,
(%)

27.2

Activity

4.9

PI/ Percentage
clay

Specific gravity, Gs

2.8

AS 1289.3.5.1-1995

Unified soil
Classification

CH

Texturalclassification

Heavy
clay

AS 1289.3.1.1-1995
AS 1289.3.1.1-1995
AS 1289.3.1.1-1995
ofASTM D 2487-83

Soil textural triangle
by USDA1

ColourLight grey-

Clay (%)

92

AS 1289.3.6.2-1995

Silt (%)

6

AS 1289.3.6.2-1995

Sand (%)

2

AS 1289.3.6.2-1995

Electricalconductivity, (μS)

397

pH

10

AS 1289.4.3.1-1997

EXPERIMENTAL MODEL AND SET UP

The laboratory experiments of EK treatment ofsoil samples are carried out using the test model
developed at the Griffith University. The EK tests
are performed in clear glass rectangular tanks of 38
cm in length and 20 cm in width, under highly
controlled laboratory conditions. A compacted layerof the soil with a thickness of about 17 cm wasplaced in the tank to known moisture content value.
Tap water having a conductivity of 187 µS at 25°C
was used for the slurry preparation to resemble
actual field application. Then, two hollow stainlesssteel tubes, possessing some drilled holes throughtheir walls, to allow the enhancement liquids tomove freely into the sample, were placed 32 cm
apart at the ends of the tank to be served aselectrodes. An outlet from cathode chambers isconnected to the vacuum pump to facilitatecollecting cathode effluent and measuring the
cumulative electro-osmotic flow volume. The power
distribution cables were attached to the electrodes
and connected to the DC power supply, providing
total voltage of 10 V. The soils at various
normalised distances of 0, 0.25, 0.5, 0.75 and 1 fromthe anode, were tested for variations in moisture
content (Mc), pH and undrained shear strength (Su)
as a result of EK process for 3, 6, 9, 12 and 15 day
periods. The normalised distance is defined as the
distance of the testing point from anode, over the
total distance between the electrodes. The schematic
view of the experimental model has been shown in
Fig. 1. In order to aid the EK process, soil samples
were subjected to a slow continuous flow of anodeenhancement solutions (hydrated lime and saline
solution). The saturated hydrated lime in distilledwater, had pH value of 12.4 and electro-conductivityof 8.9 mS. Similarly, 0.1 N calcium chloride was
mixed with 1:100 sodium silicate solutions (by thevolume of distilled water) and this saline solution
was selected as second enhancement liquid during
the EK treatment. The pH of this solution was foundto be 9.5 and electro-conductivity value of 15 mS.
The physico-chemical properties of the hydrated
lime (slaked lime), calcium chloride and sodium
silicate used in this study are shown in Table 2. The
enhancement liquids were permitted through the soil
via anode by use of a thin flexible PVC tube
connected to an external plastic reservoir, at a small
external hydraulic head (with very low discharge ofsolution, almost dripping). For testing, the upper 20mm was first removed to ensure that any surface
drying/wetting or disturbance effects were avoided.

AS 1289.4.3.1-1997

311

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

4. METHODOLOGY

Reservoircontaining
enhancement
solution

Vacuumpump

power supplyDC

Measuringcylinder

Glass
tank

Hollow stainlesssteel electrodes
Anode
(+)

25 cm

22.5 cm

17.5 cm

Cathode(-)

60 cm

Clay soil specimen

35cm

5. RESULTS AND DISCUSSIONS
5.1. Conductance Phenomena During
Process

90 cm

20 cm

Plan View

Cathode
(-)

Anode
(+)

Clay soil speciman

38 cm

Fig. 1 (a) Schematic view and (b) plan view of thelaboratory set up for the EK treatment of the clay
soil (not to scale)

Table 2. Properties of the enhancement agents usedin this study

Molecular
formulaMolar mass
(g/mol)Exact mass
Appearance
Odour

Solubility

EK

Upon the application of DC electric potential
through the soil sample across the electrodes, thesoil-liquid medium undergoes several complex
electrochemical processes that take place within thesoil porous media. Some of these processes are
initiated immediately after the DC electric potential
was applied (e.g. electrolysis of water, electroosmotic flow, current flow, etc), while several otherprogressions develop with time (e.g. variations in
Mc, pH, Su, etc). With the increase of treatment
durations, some of these modifications (e.g. electroosmotic flow and electric current flow) appear tocontinue but with a gradually decreasing rate, whichis due to the several other system complications
developing within the porous media. The mostprominent observation of these experiments was thedevelopment of wet and drier areas between theelectrodes due to positive electro-osmotic flow fromanode to cathode.

Testing points
during and after
the treatment

32 cm

Properties

The cathode effluent (liquid) was extracted
mechanically via a vacuum pump from the cathodewell to measure the accumulated electro-osmotic
flow volume for period of 15 days. The electric
current between the electrodes was manuallymonitored using a digital multimeter for everyday.
The moisture content (Mc) and pH variations of thesoil samples were evaluated by using the method
described in Australian standard AS 1289.2.1.12005 and AS 1289.4.3.1-1997 respectively. The
undrained shear strength (Su) of the soil wasmeasured directly using a hand vane shear apparatus
in accordance with AS 1289.6.2.1-1997.

Hydratedlime

Calciumchloride

Sodiumsilicate

Ca(OH)2

CaCl2

Na2 SiO3

5.1.2.

74.093111122.0673.968071
Soft white
powderOdourless
Soluble inglyceroland acids.
Insoluble
in alcohol.

110.9848

When a electric potential is employed to a claywater structure, electro-osmosis flow occurs fromanode to cathode and the mobile DDL moves anddrags the solution with it [14]. The variation of totalliquid volumes cumulated in the cathode well for
bentonite due to electro-osmotic flow subjected tohydrated lime and saline enhancement is presented
in Fig. 2. As it can be seen with hydrated lime
enhancement higher cumulative electro-osmotic
flow volume has been recorded in comparing withsaline solution. This can be described by theHelmholtz–Smoluchowsky’s (H-S) theory which is
the most common theoretical electro-osmotic
description and is widely accepted by geotechnicalresearchers [13, 15]. According to this model the

Toxicity

Low

Acidity

12.4

Basicity

2.37

White powder
Odourless
Soluble inacetone, acetic
acid
Low tomedium8-9(anhydrous)
6.5-8.0(hexahydrate)-ThickliquidOdourless
Insoluble
in alcohol

Corrosive

11.5
-

312

Cumulative electro-osmotic flow

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

D

ke

(1)

n

400

400
Hydrated lime, ER
Saline, ER
Hydrated lime, EC
Saline, EC

350

1600

Electrical resistance, ER (Ohm)

Cumulative electro-osmotic flow (mL)

Where ζ is the zeta potential (V), n is the porosity, η
is the viscosity (FT/L2) and D is the dielectric
constant. Saline solution has higher viscosity (η)
compared to hydrated lime due to existence ofwater-soluble thick liquid; sodium silicate.
Therefore, with saline enhancement the viscosity ofthe pore fluid increases and electro-osmotic flowrate decrease. This led to delaying of electroosmotic flow through bentonite and reduction of
cumulated cathode effluent.

concentration and electro-conductivity of the saline
solution, which will increase electrochemical effects(e.g. increase of cation exchange and precipitationon the surface of clay particles) leading to higher
initial current through the sample. By dividing theapplied voltage by the electric current, the electricalresistance (ER) of bentonite was obtained. The ER
of the soil decreased initially and then increased
with processing time. This is due to the fact that
injection of enhancement solutions would increase
the electric current in the sample, which in turn
reduces the initial electrical resistance of soil. With
increasing treatment time, the electrical resistanceincreased due to the decline of the electric current
through the soil sample.

1400
1200
1000

Hydrated lime

800

Saline

600
400

300

350
300

250

250

200

200

150

150

100

100

50

50

200

0

0
0

0
0

3

6

9

12

15

3

6

9

12

15

Time (days)

Time (days)

Fig. 2 Variation of cumulative electro-osmotic flow
volume with time for bentonite under applied
voltage of 10 V subjected to hydrated lime andsaline enhancement solution

Fig. 3 Variation of electric current flow (EC) andelectrical resistance (ER) across bentonite over time
under applied voltage of 10 with hydrated lime andsaline enhancement

Electric current (EC) flow and electricalresistance(ER)5.2. EK
Effecton
Physico-chemical
Characteristics of Bentonite Soil

Fig. 3 represents the variation of electric current
flow (EC) and electrical resistance (ER) acrossbentonite with respect to hydrated lime and salineenhancement solutions. It can be seen that both tests
begin with relatively high EC values, while with
passing processing time, the current reduces
reaching almost constant values. The injection ofenhancement solutions through the soil sample
would increase the number of cations in the soil
pore solution leading to more hydration of cations
migrating towards the cathode [16]. According to
the Fig 3 higher rate of EC flow was observed withsaline enhancement compared to hydrated lime
enhancement. This can be due to greater ionic

EK processes can modify the system chemistry of
the porous media, hence modifies several physicochemical and engineering properties of the soils.

5.1.3.

5.2.1.

EK effect on moisture content (Mc) andundrained shear strength (Su) variations

The undrained shear strength (Su) and moisture
content (Mc) variations of bentonite with time atdifferent normalised distances from anode under 10
V applied voltage with hydrated lime and salineenhancement are presented in Figs. 4 and 5
respectively. It is noticed that under both EK
processing conditions employed, a considerable Mc
gradient was built up in the bentonite between theelectrodes, forming wet and dry regions. The
313

Electric curent, EC (mA)electro-osmosis permeability (ke) under an electrical
gradient is indirectly proportional to the viscosity(η) of the pore fluid via the following formula:Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

positive electro-osmotic flow from anode to cathodeformed dry regions at the vicinity of the anode andwet areas at the vicinity of the cathode. In thisregard, the exact location of wet and dry regions
depends on the mineralogical properties of the soil
such as permeability characteristics, clay type andcontent, DDL characteristics, etc [17].
From the Figs. 4 and 5 it can also be observed that
there is a considerable Su gradient in soil sample
between the electrodes showing very goodcorrelations with the changes in Mc of the soil

500

across the sample. In general, with increasing
processing time, the strength appears to increase
possessing the highest strength values after 15 daysof treatment at 0.25 normalised distance from theanode subjected to both enhancement solutions.
Moreover, with saline enhancement, higher degreeof shear strength was observed in soil sample
compared with hydrated lime enhancement. Fromthese results it can be concluded that the EK
treatment with enhancement solutions, hassignificantly improved soil strength especially at thevicinity of the anode and in the middle of the tank.

12

Hydrated lime

450

Moisture content, Mc (%)

350

8

300
250

6

200
4

150
100

2

Undrained shear strength, Su (kPa)

10

400

3 days, Mc
6 days, Mc
9 days, Mc
12 days, Mc
15 days, Mc
3 days, Su
6 days, Su
9 days, Su
12 days, Su
15 days, Su

50
0
-0.25

0

0.25

0.5

0.75

1

0
1.25

Normalised distance from anodeFig. 4 Shear strength (Su) and moisture content (Mc) variation of bentonite over time at regular normalised
distances from the anode under applied voltage of 10V with hydrated lime enhancement
600

20SalineMoisture content, Mc (%)

16
14

400

12
300

10
8

200

6
4

100

2
0
-0.25

0

0.25

0.5

0.75

1

Undrained shear strength, Su (kPa)18
500

3 days, Mc
6 days, Mc
9 days, Mc
12 days, Mc
15 days, Mc
3 days, Su
6 days, Su
9 days, Su
12 days, Su
15 days, Su

0
1.25

Normalised distance from anodeFig. 5 Shear strength (Su) and moisture content (Mc) variation of bentonite over time at regular normalised
distances from the anode under applied voltage of 10V with saline enhancement314

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

5.2.2.

Fig. 7 Variation of pH of bentonite over time atregular normalised distances from the anode underapplied voltage of 10V with saline enhancement

EK effect on pH variations

The development of the pH gradient across theelectrodes, for bentonite versus time at regularnormalised distances from the anode with hydrated
lime and saline enhancement is presented in Figs 6
and 7, respectively. It can be noticed that under theboth EK processing conditions, a clear pH gradient
was being developed within the bentonite soil
between the electrodes, forming an acid front at theanode and a base front at the cathode. However, thepassage of enhancement solutions through the soil
reduced the extreme acidity near the anode. As it
can be observed form Figs. 6 and 7, during the earlystages of EK treatment, the pH of the soil remained
unchanged. This is due to the high buffering
capacity of bentonite. However with the passage ofprocessing time, the pH at the vicinity of the anodeseems to drop reaching almost lowest pH value at 15
days of treatment.

6.

This paper has presented some laboratory resultsof a study undertaken to investigate the EK
treatment effects in bentonite soil subjected to twoenhancement solutions under a predetermined
applied voltage gradient of 10 V. From the analysisof the test results the following conclusions can be
made:
i.

14
Hydrated lime
12

ii.
10

pH

8
0 day
3 days6 days9 days12 days
15 days

6
4
2
0
-0.25

0

0.25

0.5

0.75

1

iii.
1.25

Normalised distance from anodeiv.
Fig. 6 Variation of pH of bentonite over time atregular normalised distances from the anode underapplied voltage of 10V with hydrated lime
enhancement
14
Saline

v.

12
10

pH

8
0 day
3 days6 days9 days12 days
15 days

6
4
2
0
-0.25

0

0.25

0.5

0.75

1

CONCLUSIONSWith the application of DC electric potential
through the sample, the soil-liquid medium
undergoes several physico-chemical andelectrical changes due to several complex
electrochemical processes which take place
within the soil porous media. The mostprominent observation of these experiments
was the development of wet and dry areas
between the electrodes due to positive electroosmotic flow from anode to cathodeHigher rate of electro-osmotic flow is observed
during the early stage of the EK process underboth processing conditions while withprocessing time, a gradual decrease in the rateof electro-osmotic flow was noted. Withhydrated lime enhancement higher cumulativeelectro-osmotic flow volume was recorded incomparing with saline enhancement.
The tests began with relatively high currents,
however with processing time, the current
declined gradually, leading to higher ER
values. The electric current through the sample
found to be higher with saline enhancement.
Under both EK processing conditions
employed in this study, a clear Mc gradient insoil increasing from anode to cathode was built
up exhibiting very good correlations with thechanges in Su of the soil. With salineenhancement, higher degree of shear strength
was observed in soil sample (at 0.25
normalised distance form the anode) comparedwith hydrated lime enhancement.
Under both EK processing conditions
employed, a clear pH gradient was being
developed in the bentonite between theelectrodes, creating an acid front at the anodeand a base front at the cathode, although thepassage of anode enhancement solutions
through the soil reduced the extreme acidity
near the anode.

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Vol. 27.(13): pp. 2638-2647.

[14]

[15]

[16]

[17]

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Ahmad, K., K.N. Kassim, and M.R. Taha,
Electroosmotic flows and electromigrations
during electrokinetic processing of tropicalresidual soil Malaysian Journal of Civil
Engineering, 2006. Vol. 18.(2): pp. 74-88.
Mitchell, J.K., Fundamentals of Soil
Behaviour. 2nd ed1993, New York: John
Wiley & Sons Inc.
Ou, C.Y., S.C. Chien, and Y.G. Wang, Soil
improvement using electroosmotic with theinjection of chemical solutions: field tests.
Canadian Geotechnical Journal, 200946): pp.
727-733.
Jayasekera, S. and S. Hall, Modification of
the properties of salt affected soils using
electrochemical treatments. Geotechnical andGeological Engineering, 2007. Vol. 25.(1):
pp. 1-10.

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

FLOW PATTERN FOR MULTI-SIZE SILOSYi Yang1, Na Li2, PengYin3 and YM Cheng4
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong.
ABSTRACTSilo container is a very important storage structure for coal, sand and other granular materials.
Nonhomogeneous granular flow is sometimes found in ore discharging in mining engineering, but so far there
are only limited studies to this topic, particularly for double opening silo. In views of that, it is necessary tofigure out the details about the flow pattern behavior. In the present paper, four physical models are designed toinvestigate the flow patterns for silos discharge behavior with double openings. The opening spacing, heightratio, sand properties and automatic separated manners are considered in these laboratory tests. Meanwhile, twodimensional discrete element method is used to reproduce the flow behavior as well as to evaluate the dynamic
wall stresses distribution on the silo hopper from bottom to top. It is found that the flow pattern is very sensitive
to the spacing between openings under close opening silos. For the wide opening silos, the discharge efficiency
would change nearly 30%. The arch effect in the dead zone and ore recovery are significantly influenced by theheight /spacing ratio. The results from discrete element analysis can match well with the experimental study ifsuitable micro-parameters are used in the analysis.
Keywords: Silos; Flow Pattern; Discharging; Laboratory Tests; Discrete Element

where S means the opening distance, H_layer is theheight of each soil layer, and H_total is the height ofeach silo. The heights of the two shorter silos (silo A
and silo B) are 650mm, and it is 1000mm for silos C
and D. The laneway in the physical model is 30mm
wide with an angle of 30 degree to the horizontal
direction. The laneway can be removed to induce theinitial sand drawing. The surrounding sides of thesilos were made of transparent PVC sheet with scalelines for easy monitoring and capturing discharge
process. The flow pattern of this test is also
recorded by a high speed camera. In thisexperimental study, red sand and green sand, whichwere deposited and compacted in layers, were usedfor visualizing the flow behavior. The particle size
distributions of the sands are nearly uniform. Cheng
and co-workers [2] have used these two sands forcomparing the single and double opening effects inflow patterns, where the opening distance is close
and the height ratio is small.

INTRODUCTION
Many engineers still use the classical Janssen
formula [1] to analyze the stress distribution on thewall of silo, where only homogeneous material isconsidered and the end effect is ignored. The
limitations of this formula come from theassumption of uniform flow required in the classicalcontinuum mechanism for analyzing discontinuous
problem. Cheng et al. [2] discovered thatcolumniform channel flow can be observed when
two layers of materials with different sizes are
introduced into short silos, where maximum stresscan be found at the top of dead region. Cheng et al.
[3] had found that the double opening silo canincrease the recovery of the bottom material. The
material deposition from the nature is complicated,as the columniform channel and funnel flow arerequired to be considered for granular discharge
flow. In this paper, four physical models aredesigned to carry out 16 groups of tests with double
openings for the silos. The effect of opening distance,height/spacing ratio and layering are investigated forthe flow pattern, arching effect and ore recovery.
The discrete element method [4]-[7] is also used forcomparing the analysis and monitoring the stressfield for the whole processing.

EXPERIMENTAL TESTSFour different double openings silos are designed,
where the opening spacing and height ratio arevaried. The schematic diagram is shown in Fig. 1,
317

GEOMATE-Nagoya, Nov.13-15, 2013

obvious.
Table 1 Detail information of experimental tests (Tmeans the time required for complete
discharge)
GroupsSilo A

Silo B
Fig. 1

2D and 3D double-opening schematic.

The number and types of layers are limited inthis study. In this paper, multiple experiments havebeen carried out to capture the sensitivities of theabove three factors for granular flowing pattern andore recovery. Detailed information about these tests
can be seen in Table 1, where the height of eachlayer is associated with layers order. For silo A
model, the reverse deposition manner may directly
influence the flow pattern. In test 1, the coarse redsand is at the bottom layer, where the global flow isbasically a uniform discharge. In test 2, the finegreen sand at the bottom will induce two twin funnel
flows, and a steady dead zone with sharp geometryat the interface between the two layers were foundduring the flow. The speed of the red sand (coarsersand) is much greater than the fine sand, and thegreen dead zone will support the upper layer togenerate two fast flow side zones. Red sand will
firstly deposit in the deposition tank. The flow
pattern of these two tests can be seen in Fig. 2.

Silo C

Silo D

Fig. 2

Layer
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red
Red
Green
Green
Red

Num

S
(mm)

H_layer
(mm)

155

155
155

1
2
3
240
4
5

140
280

6
7
140
8
9

11

270
270

12
13
270

15
16

140
420

140
560

10

14

240
240

270
405

270
540

T
(s)
5.8
5.9
10
14.2
6.8
7.2
9.5
9.7
9.8
10.1
10.8
13.2
11.1
14.6
12.6
16

However, for the wide opening silo B and D, thevariations are nearly 30% which can directly
influence the discharge behavior. This may be
induced by the couple effect of the geometry and thematerial properties. The frictional coefficient of finegreen sand is larger than the coarse red sand, andthis may impact the flow ability. Meanwhile, higher
height can accelerate the whole flow velocity toincrease the discharge efficiency. The dead zones atthe bottom layer can be found in each test for silo C
and silo D, especially at a larger height value. The
dead zones are unstable in higher top layer, which
will gradually decrease in the global processing

The flow patterns in test 1(left) and 2.

The discharge time in Table 1 can be influenced by
the material property at each layer, which has beenfound by Cheng et al. [2]. In these experimental tests,
it can be found that the opening spacing cansignificantly affect the discharge efficiency. The
difference in the discharge time for reversing thelayerings in the close opening silo A and C are not

318

GEOMATE-Nagoya, Nov.13-15, 2013

behavior. This interesting phenomenon can be seenin Fig 3. In this figure, since the opening spacing isclose, the depression cone will also appear in thebottom layer. Ore recovery will be better when theheight ratio is higher, where the height of bottom
layer is coincident with the opening spacing. The
authors here choose test 5 and test 9 for acomparison which is shown in Fig 4. Thesefoundings can be important for non-homogeneousore mineral discharge behavior.

given by：

 Fi n = K nU n
 s∆Fi =−ks ∆U s
 F s ≤ µF n
i
i


(1)

Where Kn and ks denote the normal and shear
stiffness coefficients, ∆Un is the normal overlap,∆Us is the incremental tangential displacement, µ is
the inter-frictional coefficient.
The calibration of the input micro parameters
has been discussed by many researchers [2], [7].
The material physical and micro numericalparameters are given in Table 2. Particles are
generated by the deposition method, which cangenerate a similar initial stress filed as theexperimental specimen initial condition. The
dimensions in the numerical model are same as thephysical model. The vertical and horizontal stresses
can be monitored at every step in the computing
procedure, which can qualitatively analyze the stress
distribution on the boundary. The stress field on theboundary is another important index for optimizing
the design of the silo and ore discharge.

Fig. 3 The variation of dead zone in bottom layer.

Table 2 Physical and micro parameters
Sand
Red
Green

Size
(mm)
2-2.2
0.15-0.60

φ2731

Density(kg/m3)
1415
1379

Kn
(N/m)
4e6
1e6

Fig. 4 The deposition veiw of test 5(top) and 9.

NUMERICAL COMPARISON
Two dimensional program PFC2D [4] using rigid“Disk” with soft contact is used for the present study.
The governing principle in the modeling includes
three models: 1) contact model; 2) bonding model; 3)slip model. For cohessionless materials such as sandin the present study, the bonding model can beignored. The authors have chosen the linear elastic
model and Coulomb slip model in the present study
which is also adopted in many previous studies [2][7]. The micro parameters of linear contact model
include the normal and shear stiffnesses and theinternal frictional coefficient. Furthermore, thevelocity vectors of each “Disk” consist of two planetranslational components and a rotational component.
The skeleton of the linear contact model in thispaper is given in Fig 4. Meanwhile, the mechanicalgoverning equations of the bond/slip model area) Initial numerical and laboratory test.

b) 400,000 numerical steps

319

ks
(N/m)
4e6
1e6

GEOMATE-Nagoya, Nov.13-15, 2013

The monitored normal and shear stress data canbe easily analyzed to capture the qualitative trend ofboundary circumstance, which is shown in Fig.6.
The normal stresses in the initial stage are
fluctuating dramatically and stress concentration isfound at the corner of the side and bottom plates.
This is induced by the instantaneous opening
behavior and geometry effect. Normal stress drops
very significantly in the initial stage, meanwhile, thepeak stress location has also changed, which isinduced by the short funnel flow pattern after 100
million numerical steps in Fig.5. Accompanied thewhereabouts of red coarse sand, the normal stressvariation and stress concentration location graduallychange steadily. The flow pattern can’t lead to a
sharply variation for the shear stress, as the shortfunnel would just produce extra lateral compression
for the boundaries dead zone, where the dynamic
force is on the horizontal direction. The discreteelement simulations just give some qualitative
assessments for stress or other physical quantities.
The flow pattern behaviors can similar be
reproduced by discrete element method, which cangive some visualization not possible from the model
test even in the internal of each layer.

c) 1,000,000 numerical stepsd) 5,500,000 numerical steps
Fig. 5 Numerical and experimental comparion.
In this paper, the authors choose test 1 to carryout a numerical simulation. It was observed that thesand is drawn uniformly beginning, but it gradually
becomes twin short funnel channel. The flow
patterns of test 1 at different numerical time steps
are shown in Fig.5, which is simultaneously
compared with experimental test from the highspeed cameral. These results can totally match wellwith the trend of the laboratory results.

(a) Initial stage(b) 1,000,000 steps (c) 2,600,000 steps

Fig. 7 Contact force distribution of test 1.

In Fig.7, from the contact force of test 1,
different contact force chains within these two sandlayers can be noticed. Red sand which owns larger
size generates much stronger force chainsconcentrated at the silo bottom and is shown in Fig.
7 (a), and its gravity transfers to the four hopper
walls forming strong connections between sands andwalls. On the other hand, Green sand creates much
weaker force chains on the silo top, which represent
more intense and sufficient contact and friction
inside this layer. It can also be noted from thesequence of contact force diagram that theinteraction of particles becomes stronger during thedischarging process.
The circular shaped arch of distribution zone canbe noticed above the caving arch near the silo
openings in Fig. 7 (b). The falling velocity of sandsis large within the distribution zone, while the sanddraws slowly outside the arch. In the beginning of
the silo flow, particles from the two sides travel theFig. 6 Normal and shear stresses on the side wall.
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GEOMATE-Nagoya, Nov.13-15, 2013

same distance with those flow at the middle, which
explains why the mass flow is formed during
discharging. As sands are continuously drawn out,
less contact force induces smaller stress on the silos
hopper walls. Hence, the distribution zone startdeveloping upward, so funnel flow may possibly beformed at the later stage till the end of flow.

microproperties are used in the analysis. It is
recommended that for the further study, more indepth numerical study needs to be carried out tocapture the fundamental behavior for theseinteresting experimental results. Three dimensional
simulations are also suggested.

CONCLUSIONS AND RECOMMENDATIONSACKNOWLEDGEMENTS
The present study in this paper has focused on
nonhomogeneous granular flow behavior from both
macroscopic and microscopic view points, and has
revealed some interesting phenomenon for a silo
flow problem with granular material. The resultsfrom the present study are particular useful formining engineering in ore discharging.

The authors acknowledge the support of the
postgraduate funding of the Hong Kong Polytechnic
University.
REFERENCES[1] Janssen HA, “Getreidedruk in Silozellen”, Z.
Ver, Dtsch. Ing, Vol. 39, pp. 1045-1049.
[2] Cheng YM et al,“ Laboratory test and Particle
Flow Simulation of Silos problem with nonhomogeneous materials”, J. of Geotechnical andGeoenviornmental Engineering, ASCE, Vol.
135, Nov. 2009, pp. 1754-1761[3] Cheng YM et al, “Flow pattern for silo with twolayers of materials with single and double
openings”, J. of Geotechnical and Geoenviornmental Engineering, ASCE, Vol. 136,
Oct. 2010, pp. 1278-1286.
[4] Itasca Consulting Group, Inc, “Theory andBackground of PFC2D”. 1999
[5] Parisi DR et al, “Partitioned distinct element
method simulation of granular flow within
industrial silos”, J. of Eng. Mech., ASCE, Vol.
130, July. 2004, pp. 771-779.
[6] Masson S and Martinez J, “Partitioned distinct
element method simulation of granular flow
within industrial silos”, Powder Technology,
Vol. 109, Apr. 2000, pp. 164-178.
[7] Coetzee CJ and Els DNJ, “Calibration of
discrete element parameters and the modeling ofsilo discharge and bucket filling”, Computers
Electronics in Agriculture, Vol. 66, Mar. 2009,
pp. 198-212.

Four sets of silos are investigated in this research.
It is found that the opening spacing can significantly
influence the discharge efficiency. The flow patternand efficiency can also be influenced by the soil
layerings. For close opening silos, the flow pattern isslightly changed while the efficiency of flow is notsensitive to the layerings. However, for the wide
opening silos, the discharge efficiency can changeby nearly 30%. Larger height ratio is also beneficial
for ore recover. Depression cone can be seen in theclose opening silos. Meanwhile, the dead zone in thebottom layer is unstable for relative higher top layer.
Numerical analysis can match well with the flow
pattern and give some qualitative results. The
porosity of the dead zone in funnel flow is larger
than the mass flow. The size of opening affects thecontact force in the middle of the silo, which leads tothe formation of a depression cone. The nature of theinternal force network is of great importance in theunderstanding of various properties of granularassemblies.
A good agreement between the laboratory andnumerical results can be observed if suitable

321

GEOMATE-Nagoya, Nov.13-15, 2013

Construction Materials

322

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

IMPROVING ENGINEERING PROPERTIES OF FINE-GRAINED SOIL
WITH STEEL SLAG FOR USING IN EMBANKMENT EARTHFILL
Je-Min Baek1, Satoru Shibuya1, Jin-Suk Hur2 and Tara Nidhi Lohani3
1
Graduate school of Civil Engineering, Kobe University, Japan;
2
ESCO C&E Co., Ltd., Korea; 3RCUSS, Kobe University, Japan

ABSTRACTAs part of the promotion and effective utilization of steel slag as an embankment fill material, its
applicability was studied through a series of laboratory test. It was found that the steel slag, which has higher
internal friction angle as compared to the normal embankment earthfill materials, has sufficient strength to be
used as a fill material. When mixed with a poor natural soil containing high percentage of fines, grain-size
characteristics, permeability values, compaction properties and strength properties were also significantly
improved, exhibiting an excellent soil-improvement effect. The soil-slag mixture showed transitional values ofphysical and mechanical properties in between the steel slag and natural soil. The environmental concern ismostly alleviated by the low permeability characteristics of the soil-slag mixture. This shows that steel slag is
expected to be a promising fill material for its low-cost and strong soil strength feature to be used inembankments, if proper grain-size and compaction control are done at the site.
Keywords: Soil-improvement, Steel slag, Fill material, Embankment, L-shaped geosynthetic drain

improving its reinforcement function. This method
differs from the conventional drainage system set
inside the embankment in such a way that the water
seeped into the reinforced wall from its back or top
is smoothly lowered to the base level through Lshaped vertical geosynthetics layer inserted inside
the wall. The drained water further finds its escapeout of the embankment through the drainage layer
installed at its base. This makes an embankment acompletely a waterproof area [5].
In this research, study is done on the steel slag
for its effective utilization as a fill material forembankments. The slag, although considered to haveexcellent strength characteristics, has a criticalalkalinity concern in using as an embankment
backfill material. The soil improvement effect of theslag has been examined by using a poor soil, having
a lot of fines content and considered to be unsuitablefor earthfill purpose, and also a soil-slag mixture.
Laboratory tests were performed on the fine-grained
soil, steel slag and soil-slag mixture to evaluate their
physical properties, permeability, pH, compactionand shear-strength characteristics.

INTRODUCTION
In recent years, the disasters related to reinforced
earth wall due to rainwater infiltration have been
increasing. In 2004, reinforced earth wall underconstruction in Hyogo prefecture was collapsed due
to a rapid increase in water level at its back causedby the heavy rainfall from Typhoon No.23. The
prime factor behind the failure was an increase in the
degree of saturation of fill material by the infiltrationof stagnant water at its back and directly from therainfall, which decreased suction value and hence,lowered the strength and stiffness of the reinforced
earth embankment below the critical [1].
The significance of using locally available soil inan earthfill is quite explicable from economic reason
as well as the assurance of speedy construction.
However, shear strength and permeability
requirement may not always be met, especially,
when the local soil is a fine-grained one. In general,the cement stabilization technique is usually appliedin such cases. The resulting soil acquires better
strength parameters however, the low permeability
might result in the water stagnation at the rear sideof reinforced earth wall and therefore, becomes thecandidate for failure as mentioned earlier.
In order to alleviate the damage on the reinforced
embankment, it is therefore important to prevent thepenetration of the rainwater inside the earthfill andalso avoid the water stagnation at the rear side.
References [2]-[4] suggested that the combination of
the water proofing and the drainage systems inside
the reinforced earth wall is quite effective for

CHARACTERISTICS
OF
THE
FILL
MATERIAL USED FOR THE EXPERIMENT
Table 1 shows the fundamental physical propertiesof the steel slag, the soil used and its mixture. The
slag has relatively low water absorption rate of about
2.7% and its unit weight, ρ s = 3.480g/cm3, is quite
heavy as compared to commonly available soils(2.6~2.8g/cm3).
323

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Basic physical properties of the tested soilsw (%)ρ s (g/cm3)(%)ℯ
S r (%)n a (%)≧75mm
2~7mm
0.075~2mm≦0.07mm
D 50 (mm)

8
3.480
2.7
0.468
67.8
10.3
0
69.0
27.8
3.2
8.7

Soil-slag
mixture*1)
15
2.908
－
0.474
92.7
2.4
0
47.9
43.8
8.3
1.61

D max (mm)

37.5

37.5

26.5

Uc

54.0

43.9

126.7

Uc'

0.939

0.361

2.46

Name

Steel slag

Grain-size
characteristics

Water content
Particle density
Water absorption coefficient
Void ratio*2)
Degree of saturation *3)
Air porosity *4)
RockGravel
(%)
Sand
Fines
Mean particle size
Maximum particle
size
Uniformity
coefficient
Coefficient ofcurvature

Natural soil
23
2.609
－
0.655
88.0
4.8
0
25.2
42.2
32.6
0.23

∗ 1) Steel slag : Natural soil = 4：6 (volume ratio)∗ 2) e =

ρs
ρd

−1

∗ 3) Sr =wρseρw∗ 4) na = 100 − ρd/ρw(100/ρs + w)

In addition, soil-slag mixture was also preparedat the volume ratio of respectively, 6:4 (5:5 in termsof weight ratio) and had unit weight, ρ s =2.908g/cm3. Figure 1 shows the grain-size
distribution curves for all materials. As observed
from the uniformity coefficient and coefficient ofcurvature values from the plot, the grain-size
characteristics of the fine-grained soil is improvedby steel slag addition.

The fine-grained soil used for the test is a byproduct generated at a construction site and has
particle density of 2.609g/cm3. With the fines
content (Fc) as high as=32.6% and containing gravel
faction as well, it can be classified as SFG from thestandard soil classification system. According to thedesign standard of the reinforced earth [6], this typeof soil is not allowed as a fill material without
proper countermeasures.

TEST PERFORMED AND THEIR RESULTS
Soil pH Measurement
Being alkaline in nature, there is wide concern
from the environmental impact point of view that thesteel slag can affect the surrounding soil when it isused as an embankment earthfill. A Japanese
effluent standard (water pollution prevention act ofJapan) has set the allowable pH limit as 5.8~8.6(5.0~9.0 at the sea area) [7]. However, as shown inthe measured pH values for steel slag, soil-slag
mixture and the soil in Table 2, strong alkalinity is

Figure 1 Grain-size distribution curves324

GEOMATE-Nagoya, Nov.13-15, 2013

shown by the steel slag (pH = 12.9). The soil usedalso had a weak alkalinity (pH=10). The pH of soilslag mixture dropped only slightly (pH = 12.7) ascompared to the pure slag, probably because of thissoil alkalinity. Therefore, in order to use the steelslag in the real field, some countermeasure against
alkali pollution is anticipated.

form of L-shaped drains [2]-[4] are adopted,
infiltrating water never pass into the fill body andenvironmental concern is completely alleviated.
Soil Compaction
Figure 2 shows the compaction curve of each soil
type performed according to JIS A1210. The
compaction of steel slag and soil-slag mixture wasdone according to the B-c method (mold diameter
15cm, height 12.50cm, no soil reuse). On the other
hand, the fine-grained soil was compacted by A-c
method (mold diameter 10cm, height 12.73cm, nosoil reuse). As apparently observed by comparing
with the result of fine-grained soil, the increase inmaximum dry density and lowering of the optimum
moisture content was quite conspicuous by steel slag
addition. This result is similar to the compaction
characteristics of the ordinary soil when mixed withthe sandy soil or gravely soil. In other words, there
is an improvement in compaction characteristics by
mixing the heavy particle weight steel slag mass.

Table 2 pH Measurements
Item

Volume ratio (%)
Steel slag: Natural soil

Soil-slag
mixturepH

100 ： 012.9

40 : 60

12.7

0

10.0

: 100

Water Permeability
The best option considered to prevent the alkali
pollution of steel slag is to avoid water infiltration
into the embankment. The effluent volume reduction
is obviously expected. Focus was therefore, put on
permeability characteristics of geomaterial.
Table 3 Permeability coefficient
Items

Material

Constant Steel slag
–headpermeability
Slag-soil
test
mixtureFalling-head
Naturalpermeability
soil
test

Dc

85%

90%

4.0×10-6－-6
k 15 2.4×10
(m/s)

－

－

6.84×10-8
Figure 2 Compaction curve for three different soil
types used in the test

Table 3 shows the result of the constant-head
permeability test on slag and soil-slag mixture, andfalling head permeability test on soil by using a
10cm x 12.73cm mold. In case of steel slag and soilslag mixture, particle size above 19mm wasscreened out by considering mold size used in thetest. The fine-grained soil used in the experimentyielded a very low permeability (10-8m/s). On theother hand, the permeability figure was also low (106m/s) for the slag and its mixture. This assures a verysmall quantity of infiltration into the earthfill andcorrespondingly, the effluent quantity as well. In
addition, when additional safety measures in theStrength Characteristics
Table 4 Test conditions for triaxial compression test

Item

Degree Confinin Shear
Volumeofgstrainratio (%)
compaction pressure
rate
Slag : Soil
D c (%)
σ'(kPa) (%/min)

100 :
Soil
0
CD
-slag
Test
mixture 40 :
60

325

85

50
100
200

0.1

GEOMATE-Nagoya, Nov.13-15, 2013

0:100

Summarizing the above outcomes, steel slag is
expected to be a promising embankment fill material
because of its low-cost and strong soil strengthfeatures by preparing its composite with the locallyavailable soils. The environmental concern is mostly
alleviated by the low permeability characteristics ofthe soil-slag mixture. In addition, the impervious
surface layers, such as asphaltic layers in roadembankments and improved drainage system, suchas L-shaped drainage system as discussed inprevious sections, can keep the water out of the fill
and any environmental impact to the surrounding
soil could be reduced to almost zero level.

90

The shear strength characteristics were examinedby the triaxial compression test. Specimens of 10cm
diameter and 20cm height were prepared byconsidering the maximum grain size of steel slag.
Table 4 shows the test condition.
Mohr’s circle of stress at failure is plotted in
Figure 3. The angle of internal friction, φ d of thesoil-slag mixture (φ d =37.4°) lies nearly at midway
between steel slag (φ d =44.1°) and the fine-grained
soil (φ d =29.7°). It is thus well understood that slag
mixing has improved the shear strength properties ofthe fine-grained soil and resulted mix has enoughstrength to satisfy the criteria of an embankment fillmaterial [8].

REFERENCES[1] Shibuya S, Kawaguchi T, Chae J-G, “Failure of
Reinforced Earth wall as attacked by Typhoon
No. 23 in 2004”, Soils and Foundations, 2007,
Vol.46, No.2, pp. 153-160[2] Shibuya S, Saito M, Hara K, Mitsui J, “Proposalof L-shaped geodrain for preventing seepage
flow into embankment using Geosynthetics”,
43th
Japan
National
Conferenceon
Geotechnical Engineering, July 2008, pp. 15391540.
[3] Hara K, Saito M, Mitsui J, Shibuya S, “Model
test and numerical simulation for L-shaped
geodrain for preventing seepage flow into
embankment using Geosynthetics”, 43th Japan
National
Conferenceon
GeotechnicalEngineering, July 2008, pp. 1541-1542.
[4] Hara K, Shibuya S, Saito M, Torii N, Chae J-G,
Masuo T, “Watertight embankment using lshaped geosynthetic drain - Full-scale test andnumerical
simulation”,
Geosynthetics
Engineering Journal, Vol. 23, Japan Chapter ofInternational Geosynthetics Society, 2008, pp.
147-154.
[5] Shibuya S, “Embankment failure: mechanicalprocess & remedy”, Geosynthetics Engineering
Journal, Vol. 23, Japan Chapter of International
Geosynthetics Society, 2008, pp. 1-14.
[6] Public Works Research Center, “Design andConstruction Manual of Reinforced Soil (Terre
Armee) Wall Construction Method (inJapanese) [3rd Edition]”, Nov. 2003.
[7] Ministry of Land, Infrastructure, Transport andTourism,
MLIT:
http://www.mlit.go.jp/,
Considerations about pH and bad smells,
Reference 1-6-9 (in Japanese).
[8] East, Central, West Nippon Expressway
Company Limited, “Primary collection ofdesign guidelines”, July 2009.

Figure 3 Results of triaxial compression test
CONCLUSION
The applicability of steel slag as a fill material
for embankments was examined through a series oflaboratory test. It was found that the steel slag,
which is quite heavy and has higher internal friction
angle as compared to the normal embankment
earthfill materials, has sufficient strength to be used
as a fill material.
When mixed with natural soil, grain-size
characteristics, permeability values, compaction
properties and strength properties were significantly
improved, exhibiting excellent soil-improvement
effects. The soil-slag mixture showed intermediate
values of physical and mechanical properties
between the steel slag and natural soil. Although, theexact values obtained in the tests could be associatedto its soil-slag weight ratio of 5:5, there is a quite
clear tendency that the physical properties of thecomposite material can be easily controlled.
326

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EVALUATION EQUATION OF DIFFUSION COEFFICIENT OFCHLORIDE ION FOR CRACKED CONCRETE
Junpei SAITO1 and Satoru SHIMOBE2
College of Science and Technology, Nihon University, Japan

1,2

ABSTRACTThe first author has built a evaluation equation (proposed equation) of diffusion coefficient of chloride ionin which the limit on the range of application has been expanded to include various crack conditions and various
reinforced concrete members, by using crack area ratio (the ratio of crack area to concrete area) in the equation
as the JSCE STANDARD "design" and by decreasing the constant which represents the effect of cracks
according to the depth of cracks.
However, the concrete area should be appropriately defined in the equation, in order for chloride ion
penetration properties calculated by the equation proposed based on the experiment results, to be assessed withappropriate accuracy on existing reinforced concrete structures with cracks.
Therefore, this study investigates appropriate concrete area set value in the proposed equation, based on therate of chloride ion penetration from cracks into the core in a vertical direction which was obtained through theback analysis of the results of electrical migration test conducted by the first author.
Keywords: Cracked Concrete, Chloride Ion Penetration, Evaluation Equation, Diffusion Coefficient, Concrete Area

built to evaluate equation (proposed equation) ofdiffusion coefficient of chloride ion. In the proposed
equation, the limit on the range of application has
been expanded to include various crack conditionsand various reinforced concrete members. For the
expansion of limit of JSCE Equation, the first author
has used the crack area ratio (the ratio of crack area
to concrete area) and the decreasing of the constantwhich represents the effect of cracks according to
the depth of cracks for the proposed equation [3][4].
However, the concrete area should beappropriately defined in the equation, in order forchloride ion penetration properties calculated by theequation proposed based on the experiment results,
to be assessed with appropriate accuracy on existing
reinforced concrete structures with cracks.
Therefore, this study investigates appropriate
concrete area set value in the proposed equation,
based on the rate of chloride ion penetration fromcracks into the core in a vertical direction which was
obtained through the back analysis of the results ofelectrical migration test conducted by the first author.

INTRODUCTION
In order to plan for the proper extension of thelife of deteriorated reinforced concrete structures,
appropriate diagnosis and repair is required. Out ofthe various factors that influence the deterioration of
concrete in Japan, the effect of the airborne salt in
the coastal areas, as well as the chloride ions present
in snow melting agents in the mountainous and thecolder regions create an environment where
reinforced concrete structures are susceptible todeterioration due to salt attack. In addition, once
cracks appear in reinforced concrete structures insuch environments, the penetration of salt is
encouraged, resulting in the structures becoming
more susceptible to early deterioration. In thissituation, it is therefore especially necessary to haveappropriate maintenance plans, as well as future
predictions based on the deterioration and diagnosis
in place.
The first author has investigated the Evaluation
Equation (JSCE Equation) of diffusion coefficientfor chloride concentration at the location ofreinforcement which is used in the examination ofchloride attack. The JSCE Equation is indicated in
STANDARD
SPECIFICATIONSFORCONCRETE STRUCTURES "Design" by Japan
Society of Civil Engineers[1]. The author's electricalmigration tests were carried out using specimens
modelized concrete cover with various types ofcracks in order to evaluate chloride ion penetration
on reinforced concrete structures with diversified
types of cracks[2]. In the results, the first author has

EXPANSIONOFAPPLICABILITY
CONDITIONS IN JSCE EQUATION
Test Method
Using a cracked concrete model as a specimen,
effective diffusion coefficients were calculated withexperimental equipment complied with the electricalmigration test method (JSCE-G571) [5] (Fig.1).

327

GEOMATE-Nagoya, Nov.13-15, 2013

The specimens were modeled as a cube with aconcrete cover set at 40mm. Crack conditions usedwere crack width, crack depth, and crack number;the specimens were cracked according to theconditions set (Table 1). Figure 2(a) shows astandard specimen. Figure 2(b) shows a specimen
modeled to examine a condition of irregularity
cracks spreading over concrete.
Three types of crack widths were set, 0.1, 0.2,
and 0.4mm, considered the limit value of crack
width(0.2mm) and set the near values. For crack
depths, they were set at 40mm when cracks wereassumed to pass through reinforcing steel (passthrough crack); depths were set 1/4(10mm),
1/2(20mm), or 3/4(30mm) of the concrete coverwhen cracks were assumed not to pass throughreinforcing steel (not pass through crack). Anotherspecimen without cracks was prepared at the same
time.

There were two types of specimen concretemix, with a water-cement ratio (W/C) of 45% and55%, and the volume ratio of fine aggregate andcement (S/C) was 400vol%. As for material
characteristics,
compressive
strengthwas
39.5N/mm2 at W/C 45% and 36.3N/mm2 at W/C
55%. Ordinary Portland cement was used and pit
sand (passed through a 2.5 mm sieve) was used as afine aggregate.
Experimental Results and Proposed Equation
Figure 3 shows the relationship between
effective diffusion coefficient considering a cracking
effect (D cr ) and crack area ratio (A/A cr ). Regression
coefficient of linear approximation was put down
together. Regression coefficients were 200270cm2/year for pass through cracks, and 100150cm2/year for not pass through cracks, with

Direct Electric
Current (15V)

Cathode

NaCl
Solution(0.5mol/l)(740ml)Titanium
Electrode

Holes for sampling ,stirring, discharging
and pouring solution
Crack

Acrylic
Block

Crack

Specimen

Cl-

Cl-

Cl-

Cl-

Front
Face

40mm

Anode

Acrylic
Block

Side
Face

NaOH
Solution(0.3mol/l)(740ml)

Side
Face

Crack
Width

40mm
Crack Depth

Titanium
Electrode

40mm
Crack Length（30mm）

Fig.1. Schematic view of migration cell andexperimental set-up

Front Face
（Crack Face）(a) Specimen

Crack
Crack
Depth

10
mm
20
mm

Crack
Width

10
mm
Crack Length（30mm）

Floor SlabModelized Specimen

Situation of Multiple Cracks
Appearing Randomly(b) Modelized specimen of multiple cracks appearing randomly
Fig.2

Shape of specimens

328

GEOMATE-Nagoya, Nov.13-15, 2013

Value

W/C (%)

45，55

Crack Width (mm)0.1，0.2，0.4

Crack Depth (mm)10，20，30，40

Crack Length (mm)30

Crack Number

1，2

2Regression Coefficient (Unit:cm /y ear)

2.5

Pass through Crack
W/C=45%：212
W/C=55%：265
Not Pass through Crack

2.0
1.5

（Crack Depth 20mm）
W/C=45%：97
W/C=55%：144

1.0
0.5

0.0
0.000

0.002

0.004

0.006

0.008

Crack Aria Ratio （Acr/A）

A cr
D0
A

(1)

Problem of Proposed Equation
For applying the proposed equation toexisting concrete structures, the issue wasaccompanied with the difference in concrete areasof specimens and existing concrete structures. As
shown in Fig.5, concrete areas of existing
concrete structures are larger than that of thespecimens, and there may be a difference inchloride ions in areas near and apart from cracks
into the core in a vertical direction. However, ion
distribution in crack spacing is averaged in the
proposed equation; chloride ion penetration
characteristics are evaluated as in danger on highchloride ion areas near cracks, and as safe on low
chloride ion areas apart from cracks. It may
mislead the evaluation of chloride ions as it is.

(a) W/C=45%,55%

Effective Diffusion
Coefficient Considering
Cracking Effect （cm 2 /year）

In this equation, D cr is the diffusion
coefficient considering cracking effect, A cr is the
Crack Area, A is the Concrete Area （A cr /A is
the Crack Area Ratio） and D 0 is the constant torepresent the effect of cracks on transport ofchloride ion（＝200cm2/year）.

INVESTIGATIONTOPROPOSED EQUATIONSTRUCTURES

Specimens Condition

Regression Coefficient (Unit:cm 2 /y ear)
Pass through Crack(s)4.0Crack Number=1：230
Crack Number=2：234

3.0
2.0

Not Pass through Crack(s)（Crack Depth 20mm）
Crack Number=1：106
Crack Number=2：71

1.0
0.0
0.000

0.005

0.010

0.015

0.020

Crack Aria Ratio（Acr/A）(b) Crack Number=1,2
Fig.3 Relationship between Dcr and crack area ratio

Mean Value of The
Regression Coefficient（cm 2 /year）

D cr =

Table 1 Specimens condition

Effective Diffusion
Coefficient Considering
Cracking Effect （cm 2 /year）

approximately a half of it for pass through cracks.
Figure 4 shows the relationship between themean of the regression coefficient (same meaning
as a constant D 0 which represents a cracking
effect on transport of chloride ions in concrete)and crack depth in crack area ratio where there
was a large number of data items. It shows a line
shape; regression coefficients for not pass throughcracks became a value that regression coefficientfor pass through cracks was proportionallyreduced depending on crack depth.
From the above, in the calculation ofeffective diffusion coefficient considering thecracking effect, pass through cracks can beconsidered as a product of crack area ratio andregression coefficient. For effective diffusion
coefficient for not pass through cracks, theregression coefficient for pass through cracks
should be reduced depending on crack depth. In
addition, D 0 in JSCE Equation (=200cm2/year)
seems to be able to be used for the regression
coefficient for pass through cracks. Equation (1)is a proposed equation where limits of crack
conditions and members of the JSCE Equation
were expanded.

300
250
200

Crack Aria Ratio=0.00375

150
100
50

Crack Aria Ratio=0.0075

0
0

APPLY
THE
TO EXISTING

10

20

30

Crack Depth (mm)Fig.4 Relationship between D0 and crack depth329

40GEOMATE-Nagoya, Nov.13-15, 2013

ClConcrete Area
（A=Large） Cl-

ClCrack

ClAverage（A=Small）
Low （A=Large）

High
Low

Diffusion Coefficient
Considering Cracking EffectConcrete Area
（A=Small）

Experimental Study（A =small ~ middle）
Existing RC
Structure（A=Large）

Concrete Area (A)Width of the Floor SlabFig.5

The mean value of the chloride ion in cracked concrete

Chloride Ion Penetration
Area from Crack (A1)

塩分浸透影響範囲外（APenetration Area
fromNon penetration2）Area
Crack (A1)from Crack (A2)Crack

塩分浸透影響範囲（A1）

Cl-

Cl-

Cl-

Cl-

Rainforcing
Steel
鋼
-

ClCl-

Crack

Cl-

Cl-

Cl-

Cl
Cl- Cl(b) Plan view(a) Cross section view（in the crack area）
Fig.6 Penetration area from crack
Contents for Investigation

Back Analysis Outline

For applying the proposed equation to existing
concrete structures, this study suggests a method
determining minimum and maximum areas affectedby chloride ion penetration from the cracks(penetration area) and using the value of theconcrete area to the equation depending on thepenetration area to solve the issue coming from thedifference in concrete areas. Penetration areas fromthe cracks were classified as shown in Fig.6; the area
where chloride ions penetrate from cracks into thecore in a vertical direction in the period chloride ionspenetrating from concrete surface to a reinforcing
steel in concrete (A 1 ), and the area out of A 1 areas(A 2 ). Appropriate setting of the area is important;the area was examined with a back analysis based on
experimental results.

Values for the back analysis were the values
obtained in this experiment. Experimental result D cr ,various crack conditions (converted to crack area
ratio) and D 0 were used to calculate penetration area
A via the back analysis. Two kinds of constant D 0
which represents the crack effect on transport ofchloride ions in concrete were used for calculation;
200cm2/year used in the JSCE Equation and400cm2/year (the diffusion coefficient for chloride
ions in water) used in the Kagaku Binran by theJapan Chemical Society (JCS) [6]. For not passthrough cracks, D 0 is adjusted by crack depth (Table
2).
The amount of chloride ion supplied to cracks
can be considered correlating to crack area A cr .
When the constant D 0 which represents the crack
effect on transport of chloride ions in concrete is
assumed to be fixed, supplied chloride ions are330

GEOMATE-Nagoya, Nov.13-15, 2013

correlated to a product of A cr and D 0 . In contrast,
chloride ions supplied to cracks penetrate fromcracks into concrete, as shown in Eq.(1), it becomes
equivalent to a product of penetration speed(effective diffusion coefficient considering thecracking effect D cr ) and penetration area A. That canbe said, when the relationship holds, the diffusion
coefficient considering the cracking effect D cr
becomes larger correlating to the amount of supplied
chloride ions because D cr in this experiment wascalculated with the constant penetration area
(specimen area A). Using Eq.(2) with diffusion
coefficient considering the cracking effect D cr , thecalculated penetration area A is considered that ittheoretically becomes almost the same on specimens
with different cracking conditions. The calculated
value represents the penetration area.

D・A
A = o cr
Dcr

Table 2

Constant to Represent the Effect of Cracks
on T ransport of Chloride Ion in ConcretePass
T hrowghCrack

D0 =400 cm 2 /yearStandard
Specifications forConcrete Structures2007, Design by
JSCE [5]Kagaku Binran by
JCS [6]

Cover

200（＝D0 ）

400（＝D0 ）

Cover ×3/4

150（＝D0 × 3/4）

300（＝D0 × 3/4）

100（＝D0 × 1/2）

200（＝D0 × 1/2）

50（＝D0 × 1/4）

100（＝D0 × 1/4）

0

0

Not Pass
Cover ×T hrowgh
1/2
Crack
Cover ×1/4

(2)

No Crack

In the case of D 0 set at 200cm2/year, L Cl- was
40mm. This is the same length as the penetration
area from the concrete surface (concrete cover).
Moreover, when the crack area ratios in thisexperiment and the existing experiment were thesame, the mean of the results in this experimentwere a comparable level to the existing experimentsuch as Ismail et al. [7] and Iwanami et al. [8]. By
contrast, in the case of D 0 set at 400cm2/year, L Clwas approximately twice the length between thesurface and the reinforcing steel, and showed a close
value to that in Pa et al. [9].
From the examination above, the concrete area
should be used at a smaller set value to take acomputationally safe value; it is consideredappropriate that a product of concrete cover andcrack length obtained in back analysis (in the case of

Back Analysis Results-

ClLCl-

Crack

ClCl-

Schematic View of LCl-

Length of Chloride Ion Penetration from
Cracks into the Concrete in a Vertical
Direction LCl－ （mm）

Figure 7 shows the relationship between
penetration lengths of chloride ion from cracks in a
vertical direction L Cl- and the ratio of penetration
area when chloride ions penetrate from the concretesurface to the reinforcing steel. Results from existingstudies in Fig.7, the relationship between thechloride ions in cracked concrete and that in noncracked concrete, and appropriate crack width, wereconverted values to make them comparable to thevalues from this experiment using the size of thespecimens in this experiment.

40mm

D0 =200 cm 2 /year
Crack Depth

In this equation, A is the Penetration Area, A cr
is the Crack Area, D 0 is the constant to represent theeffect of cracks on transport of chloride ion and D cr
is the diffusion coefficient considering cracking
effect.

Cl

D0 for back analysis

200
160

Saito（in this study ）D0 =200 cm 2 /year

Saito（in this study）
D0 =400 cm 2 /year

120
80
40
0
0.000

0.002

0.004

0.006

Crack Aria Ratio （Acr/A）

Fig.7 Relationship between LCl- and crack area ratio
331

0.008

GEOMATE-Nagoya, Nov.13-15, 2013

D 0 set at 200cm2/year is equal to the penetration
area. The proposed equation becomes more suitable
for the application to existing concrete structures by
setting an appropriate concrete area to Eq.(1)according to the classification of the area.

Nihon University, No.127, 2012, pp.1-10 (inJapanese).
[3] Saito J., "Experimental Study on Evaluation of
Chloride Permeability of Plate Concrete with
Multiple Cracks", Proceedings of the Japan
Concrete Institute, Vol.34, No.1, 2012, pp.790795 (in Japanese).
[4] Saito J . and Simobe S.,” Experimental Study on
Chloride lon Penetration in Damaged Concrete
under External Force Using Electrical
Migration Test Method”, Proceedings of theJapan Concrete Institute, Vol.35, No.1, 2013,
pp.823-828 (in Japanese).
[5] JSCE Concrete Committee., "STANDARD
SPECIFICATIONSforCONCRETESTRUCTURES -2007 Test Methods andSpecifications -JSCE STANDARD-, JAPANSOCIETY of CIVIL ENGINEERS(JSCE),
2007, pp.277-284 (in Japanese).
[6] TheJapan Chemical
Society (JCS).,"kagakubinran kisohen Part2, 2004 (inJapanese).
[7] Ismail M., Toumi A., Francois R and Gagne R.,"Effect of Crack Opening on the Local
Diffusion of Chloride in Cracked Mortar
Samples", Cement and Concrete Research,
Vol.38, 2008, pp.1106-1111.
[8] Iwanami M., Yokota H. and Nick R B.,"Experimental Study on Chloride Transport in
Cracked Concrete", Proceedings of the Japan
Concrete Institute, Vol.28, No.1, 2006, pp.917922 (in Japanese).
[9] Pa P W., Watanabe M. and Machida A.,"Penetration Profile of Chloride Ion in Cracked
Reinforced Concrete", Cement and Concrete
Research, Vol.34, 2004, pp.1073-1079.

CONCLUSIONS
Obtained results in this study are summarized
as follows.
1) Using a crack area ratio and considering
proportionally reduced D 0 for pass throughcracks depending on crack depth expand theapplication conditions for the JSCE Equation.
2) It is reasonable to set penetration area as a
product of concrete cover and crack length. The
proposed equation becomes more suitable byapplying appropriate concrete area to the JSCE
Equation according to the classification of thearea.
ACKNOWLEDGEMENT
This work was supported by JSPS KAKENHI
Grant Number 23760430.
REFERENCES[1] JSCE Concrete Committee., "STANDARD
SPECIFICATIONSforCONCRETESTRUCTURES -2007 "design", JAPANSOCIETY of CIVIL ENGINEERS(JSCE),
2007, pp.119-122 (in Japanese)[2] Saito J., "Experimental Study on the Chloride
Permeability of Plate Concrete with Cracks",
Journal of Research Institute of Science andTechnology College of Science and Technology

332

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

OPTIMIZATION OF EFFECTIVE DEPTH OF COMPACTION FOR
FINE-GRAINED SOILS

1,2

Girum Y. Yesuf1, Inge Hoff2 and Jan Vaslestad3
Faculty of Engineering Science and Technology, Norwegian University of Science and Technology,
Norway; 3 Norwegian Public Roads Administration, Norway

ABSTRACT
Soil compaction is an important phase during construction of roads. Its primary aim is to reduce the void
ratio, in order to improve the strength of the soil. In this way, a good bearing capacity of pavement foundation is
obtained. Consequently, long term deformation in the pavement layers can be substantially reduced. In this paper,a finite element method is used to study the rolling compaction of fine-grained soils. Since compaction isassociated with volumetric plastic deformations, the modified Drucker-Prager Cap model, available in Abaqus
FEA is used for numerical simulation. The soil-structure interaction of a rolling rigid body over a compressible
soil mass is defined using Abaqus/Explicit. The weight of the roller, or the contact pressure, is directly related tothe effective compaction depth and density of the soil. The evaluation of these factors has been optimized using
the strength characteristics of soils, namely the cohesion and friction angle.

Keywords: Cap model, Compaction, Density, Optimization

friction angle. These parameters are not the inherent
properties of soil; rather they describe the“condition” of the soil. For soils, the highest strengthis frequently obtained by using greater compactive
efforts with water contents somewhat below the
optimum moisture content. Large scale tests [2] haveshown that the confined compressive strength ofclayey sand could be doubled by compaction, within
the range of practical field compaction procedures.
Rollers with static load drums use the effective
dead weight of the machine to apply pressure on thesurface. Adequate compaction with static rollers isnormally achieved only in the upper layers of thematerial because the effective depth of staticcompaction is limited [3]. In some cases,
considerable compaction can also be obtained byproper routing of hauling equipment during
construction [2]. Although the specifications of thesecompacting machines are different, the degree ofcompaction is highly dependent on the static weightof the roller. Road agencies provide regulations on
the static load that must be used during compaction
and the number of roller passes [4]. In this way, thequality of compaction is ensured or field tests are
conducted to evaluate the degree of compaction.
With the advent of high computer speed andavailability of advanced finite element modelingtools, the science of terra-mechanics is gaining
popularity in the recent years for optimization ofsoil-structure problems [5]-[7]. Besides, appropriate
soil models should be chosen for the specificpractical problems. In this paper, the theoretical

INTRODUCTION
Pavement layers are compacted during road
construction to maintain the long-term performanceof roads. Insufficient compaction leads to distress inpavements such as premature pavement rutting,longitudinal unevenness and cracking. Hence,compaction of bound and unbound materials inroads is highly desired. The increase of vehicles withheavier axle loads demands a good subgrade support.
A good bearing capacity of subgrade soils is often
obtained by increasing the strength by means ofcompaction. Compaction increases also the stiffnessof the pavement layers so that future settlements dueto the traffic loads can be greatly reduced. To alesser extent, the reduced permeability of soils may
prevent undesirable frost heave problems. The
common factors that control the extent ofcompaction are the compaction effort, the type ofsoil and its gradation, and the water content [1].
In the study presented in this paper, we mainly
discuss on the effect of the compaction energy andthe strength characteristics of soils for possible
optimization techniques by using a Finite Element
Method (FEM). The scope of modeling is limited tostatic roller compaction which is often applied to thefine-grained soils. Since the compaction process ishighly dependent on the moisture content, thenumerical modeling is more suitable for studying thesoil-roller interaction. Moreover, the influence ofmoisture content in subgrade soils can be related togeotechnical soil parameters such as cohesion and333

GEOMATE-Nagoya, Nov.13-15, 2013

formulations of the model used in our analysis ispresented from literature [8],[9]. In the conventionalelastoplastic soil models, such as the standard
Drucker-Prager and Mohr-Coulomb models, theapplication of compressive hydrostatic pressurealone does not cause plastic flow. Plastic flow undercompressive hydrostatic pressure may only be
triggered with the superposition of shear stresses.
When plastic compaction is relevant the standard
Drucker-Prager or Mohr-Coulomb plasticity models
are not able to capture the actual material behavior[10]. Instead, the Drucker-Prager Cap model is used
for soil compaction.
The analysis presented in this paper is based on
the assumption of monotonic loading conditions ofstatic rollers during soil compaction. If the dynamic
effect of the roller(i.e. rolling speed, vibration
frequency) is to be evaluated, advanced ratedependent models such as the hypoplastic model
formulation must be considered for realistic
simulation of the compaction process [11],[12].
Another important aspect of numerical simulation ofsoil compaction is the geometric and boundarymodeling techniques. Such issues are addressed inthis paper mainly based on the user manual of the
FEM tool used for the numerical simulation [8].

Fig. 1

Geometric model of the soil and roller.

Because of symmetry, only one-half of thegeometry is modeled. To ensure the dynamic
analysis with a very small inertial effect, a small
mass (i.e. 100kg) is assigned for the roller. A point
load, equivalent to the weight of the roller) is
applied at the center of mass at the reference point.
In the numerical model, the motion of the rigid bodyis controlled by the boundary and loading conditions
applied at the reference point.

FEM MODELLING
Finite element analysis has been widely used formodeling non-linear soil-structure interaction
problems in recent years. The numerical simulationof soil-structure interaction needs the contact
boundary conditions to be properly defined. In thisstudy, the finite element program Abaqus FEA has
been used for modeling of the roller compaction.
The numerical simulations presented in this paper
are carried out using Abaqus/Explicit. The explicit
scheme provides stable solutions for contact
problems, in contrast to the implicit scheme. In thelongitudinal direction (direction of rolling), small
elements are used to ensure a smooth interaction
between the roller surface and the soil.
The objective of the FEM, in this study, is toobtain a relationship between the weight of the roller
and the volumetric plastic strains (change indensity). It is assumed that the change in density is
due to the plastic deformations which do not reach alarge deformation limit. The principle is moresuitable for surface compaction of wet fine-grainedsoils in thin layer applications. When large
deformation is encountered during compaction,
objective stress rates must be considered in the
numerical scheme [8]. This is not the scope of thispaper.
The three-dimensional model that is used in thisstudy is shown in Fig. 1. It consists of two distinct
bodies: a soil bed and a rigid rotating roller.

The Soil Model
The soil is modeled using the modified DruckerPrager Cap model incorporated in Abaqus FEA. The
Drucker-Prager constitutive model for pressure
sensitive geo-materials was formulated in the
1950ies [9]. Though the original model is able tosimulate a varying yield surface depending on thelevel of the mean stress, it cannot predict plastic
volumetric strain or compaction of soil materials
during hydrostatic loading. To alleviate thisproblem, the model was later modified with aconvex end cap [13]. The Cap model provides aplastic hardening mechanism to account for plastic
compaction and helps to control volume dilatancy
when the material yields in shear. The generalized
Drucker-Prager yield criterion is shown in Eq. (1)
[8].
Fs =
t − p tan β − d(1)Where β and d represent the angle of friction andthe cohesion of the soil respectively. The deviatoricstress measure t is defined in Eq. (2).
3
1 
1 
1  r  (2)=tq 1 + −  1 −    
2  K 
K   q  

334

GEOMATE-Nagoya, Nov.13-15, 2013

Where

friction angle ( φ ) as shown in Eqs. (4) and (5) forthe points where the Drucker-Prager yield surface
coincides with the Mohr-Coulomb in triaxial
compression.

1
p = − trace σ33q =  σ dev : σ dev 
2



1/ 2

6 * sin φ
3 − sin φ(4)

6 * c* cos φ
3 − sin φ

(5)

1/ 3

9

r =  σ dev : σ dev .σ dev 2
dev
are the stress and its deviatoricσ and σcomponent. K is the ratio of the yield stress intriaxial tension to the yield stress in triaxial
compression. It can be understood from Eq. (2) thatthe value of K controls the shape of the yieldsurface.

Fig. 2tan β =
d=Fig. 3

Density dependent Drucker-Prager Cap
model(2D representation) [5].

Table 1 Input parameters for the Cap model.

The cap yield surface includes dependence on thethird stress invariant. The cap surface hardens orsoftens as a function of the volumetric plastic strain.
The detail description of the shear failure surface( Fs ) and transition surface ( Ft ) and the Cap surface( Fc ) shown in Fig. 2 is available in [8]. The
hardening or softening law is a user definedpiecewise linear function relating the hydrostatic
compression yield stress ( pb ) and the correspondingpvolumetric plastic strain ( ε vol) . The current density( ρ ) in reference to initial density ( ρ0 ) can bepobtained from the relation with ε vol, as shown in
Eqn. (3) and the cap surface as a function of density
is presented in Fig. 3.
p
ε vol= ln  ρ 
 ρ0 

Density dependent Drucker-Prager Cap
model (3D view) [14].

Parameters

Unit

Value

Cap eccentricity
parameter, R
Initial Cap yield surface
plposition, ε vol,0
Transition surface radiusparameter, αFlow stress ratio, K

[-]

0.2

[-]

0

[-]

0.01

[-]

1.0

Density(initial), ρ0[kg / m3 ]1600

The Cap hardening parameters are determined,
based on the ratio of compression index ( λ ) toswelling index ( κ ) ( λ κ = 10 ) , where λ = 0.2 isconsidered. For the initial yield stress level, 60kPa is
assumed. The elements selected for the soil were
“C3D8R”, a 3-dimensional, 8-node with reduced
integration, solid elements. This element supports
the three translation degrees of freedom in the x , yand z directions.

(3)pl
The value of d , β , R, ε vol,0 ,α and K are used todefine the shape of the yield surface. The elastic
behavior of the soil is defined by its Young’s
modulus and the Poisson’s ratio, and is combinedwith the Modified Drucker-Prager Cap model tomodel the overall soil behavior during compaction.
For triaxial loading condition, the material cohesion( d ) and friction angle ( β ) are obtained from theMohr-Coulomb parameters, cohesion ( c ) andRoller
A roller with a diameter of 1.2m is used. For low
rolling speed, the rotary inertia of the roller is not
335

GEOMATE-Nagoya, Nov.13-15, 2013

considered in the model. The roller is simulatedusing analytical rigid shell. Analytical rigid surface
is chosen for both accuracy and computational
performance since analytical surfaces are notdiscretized in to finite elements [8]. A cylindricalshell with edge fillet of radius 0.07m is used to avoid
numerical problems arising in the algorithm used tomodel contact surface between the roller and thesoil.

affects compaction cost and machine performance.
In addition, the interaction between the soil and theroller affects the compaction efficiency.

Roller-Soil Interaction
The analytical surface of the roller is constrained
to the reference point. An angular velocity of 1.85
rad/sec is applied on the reference point. Since thesoil model used in this study is rate-independent, therolling speed has not influence on the compaction
process. The roller is modeled as an analytical rigid
body and it is non-deformable in the analysis. A
surface-to-surface contact is chosen and a penalty
contact method is used in Abaqus/Explicit.
Two surfaces are defined to connect the roller
surface. The friction coefficient between the roller
and the soil surface is roughly approximated fromthe friction angle of the soil, i.e. f = tan (φ ) . To be

Fig. 4

View of the compaction profile.

Fig. 5Compaction density profile for different
weight of roller.

more realistic, a slightly lower value of friction
coefficient than the one computed from the friction
angle is used. This is to account the fact that rolling
friction is lower than sliding or static friction.
For φ < 150 , a friction coefficient of 0.3 isconsidered to ensure rolling of the roller on the soil
surface.
FEM RESULTS AND DISCUSSIONS
Figure 4 shows the result from a single roller
pass. The density at the instance of roller loading iscomputed from the total volume change i.e. both theelastic and plastic volume change in the soil. Afterthe roller is passed, the density is computed only
from the plastic volume change. The elastic
volumetric change recovers during unloading. The
density profile for different weight of rollers ispresented in Fig. 5. The relative density (RD) in thiscontext is the density normalized by the maximum
density. The stiffness of the soil in the analysis is
50MPa and the Mohr-Coulomb parameters arec = 40kPa and φ = 200 . It is evident that the effective
compaction depth increases as the weight of theroller increases.

Different road agencies have their own
specification for the lift height. When different
compacting equipment is available in the field,
economical compacting effort can be carried out by
proper planning. Figure 6 shows the principle of
optimization techniques of the lift height for theminimum allowable relative density.The effect offriction angle on effective compaction depth for aroller weight of 10tonn is shown in Figs. 7 and 8. In
the model, the cohesion value of the soil is 15kPa
and the value of friction angle is varied.

Lift Height
During compaction of fine grained soils, thenumber of passes needed to achieve the desired
compaction depends on the lift thickness, the contactpressure and soil moisture content. So, the depth of
the soil layer (lift height) is an important factor that336

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 6

Principle of an approximate method for
determining lift height to achieve aminimum compacted relative density [2].

A critical height is noted at a depth of 0.3m
above which soils with low friction angle arecompacted to a lesser extent. The highest density is
obtained for moderate friction angle and the density
closer to the surface of compaction reduces forhigher friction angle, possibly due to the effect ofdilation. Dilation in soils is associated with increasein volume which consequently reduces the density.

Fig. 7

Fig. 8

Effective compaction depth at different
relative densities based on friction angle.

The relationship between the relative density andcohesion for specific depths in the soil is presented
in Figs. 9 and 10. In this case, the value of friction
angle is kept constant ( φ = 20 o ) and the cohesion isvaried. The compacted density appears to be
independent of the cohesion of the soil in the top
0,1m for high cohesion values. As the depth
increases, the effect of cohesion is clearly shown.
For the same load, the effective depth of compaction
for highly cohesive soils is very limited and it
increases as the cohesion decreases.

The effect of friction angle on soil
compaction

When the depth of compaction increases, there isno significant change for low friction angle since thecompaction depth is controlled by cohesion. At
higher values of friction angle, the change in
effective compaction depth is small as the soil
becomes strong enough and additional compaction
effort is required.

Fig. 9337

The effect of cohesion on compaction.

GEOMATE-Nagoya, Nov.13-15, 2013

REFERENCES[1] Proctor, RR, Fundamental principles of soil
compaction.
Engineering
News-Record,
Vol.111, No.9, 1933, pp. 286-289.
[2] Holtz RD, and Kovacs WD, “Compaction”, An
introduction to geotechnical engineering,
Prentice-Hall, Inc.,1981, pp.109-165.
[3] Briaud JL, Seo J, Intelligent Compaction:
Overview and Research needs, Texas A&M
University, 2003, pp. 1-84.
[4] NPRA, Handbook 018: Road Design andConstruction Guidelines(in Norwegian ),Norwegian Public Roads Administration, 2011.
[5] Xia K., Masud A, You Z, A large deformation
finite element formulation for subgrade soil
compaction, Pavements and Materials, 2008,
pp. 122-130.
[6] Chiroux RC, et al., Three-dimensional finite
element analysis of soil interaction with a rigid
wheel. Applied Mathematics and Computation,
Vol. 162 ,No.2, 2005. pp. 707-722.
[7] Hambleton JP, Drescher A, Development of
improved test rolling methods for roadway
embankment construction. 2008, Minnesota
Department of Transportation.
[8] Abaqus FEA, Simulia, Dassault Systèmes, 2011[9] Drucker DC, Prager W, Soil mechanics andplastic analysis for limit design. Quarterly of
Applied Mathematics, Vol.10,No.2,1952. pp.
157-165.
[10] Neto EDS, Peric D, Own DRJ, “Advanced
Plasticity Models”, Computational Methods for
Plasticity: Theory and Applications,John Wiley& Sons Ltd,2008, pp. 403-433.
[11] Hügel, H.M., S. Henke, and S. Kinzler, Highperformance Abaqus simulations in soil
mechanics, in Abaqus Users’ Conference. 2008.
[12] Kelm M. and Grabe J, Numerical simulation of
the compaction of granular soils with vibratoryrollers, in Cyclic Behavior of Soils andLiquefaction Phenomena, Taylor & Francis
Group, 2004, pp. 661-664.
[13] Chen WF and Mizuno E, Nonlinear Analysis in
Soil Mechanics - Theory and Implementation.
Elsevier. 1990.
[14] Han LH, et al., A modified Drucker-Prager Cap
model for die compaction simulation ofpharmaceutical powders. International Journalof Solids and Structures, Vol.45, No.10, 2008,
pp. 3088-3106.

Fig. 10 Effective compaction depth at different
relative densities based on cohesion.
CONCLUSION
The study presented in this paper is mainly forsmooth wheel rollers. These types of rollers arecommonly used when adequate compaction is
obtained under relatively low pressure. The effect ofsoil strength parameters during the compaction
process can be used as an input to optimize thecompaction depth. The rule of thumb in practice isto use a specified lift height (the same thickness fora range of fine grained soils). Though the general
understanding of soil parameters on the response ofsoil is well known, the quantitative understanding is
yet to be investigated.
The numerical investigation shows that soil
cohesion highly affects the effective compaction
depth. Depending on the amount of stress induced
from the roller and the relative density required, thelift height can be chosen as a function of the strengthparameters. Based on the knowledge of the friction
angle and cohesion of fine grained soils, the rolling
strategy can be adjusted and the compaction practice
can be improved.
ACKNOWLEDGEMENTS
This research is conducted at the Norwegian
University of Science and Technology with theresearch fund support from the Norwegian Public
Roads Administration.

338

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

COMPRESSIVE STRENGTH OF CEMENT PASTES EXPOSED TO
ELEVATED TEMPERATURE AND DETERIORATION MITIGATION
Abdoullah Namdar1, Ideris Bin Zakaria1 and Gurumurthy Hegde2
1. Faculty of Civil Engineering & Earth Resources, Universiti Malaysia Pahang, Malaysia
2. Faculty of Industrial Science & Technology, Universiti Malaysia Pahang, Malaysia
ab_namdar@yahoo.com
ABSTRACT
Kaolin-bentonite mixture [1] is mixed with cement paste for introducing a green and fire sustainableconcrete. The effects of Kaolin-bentonite (additive is grounded particles sized of <75µm) as mineral admixtureson the hydration behaviour and mechanical properties of ordinary Portland cement (OPC) have been
investigated. The crystalline modification, changes in microstructure and minerals mixtures in hydration of
cement by using X-ray diffraction (XRD) and also the compressive strength of specimens have been
investigated. The specimen exposed to elevated temperature of 500 and 1000 ºC for 3 h in ceramic furnace andcooled down to the room temperature. The compressive strength test made after specimens are cooled down toroom temperature. It observed if OPC-Kaolin-bentonite imposed by 500 ºC heat for 3 hours resulted in improve
25% of compressive strength compare to OPC. Increasing heat to 1000 ºC almost resulted in failure of all type of
specimens and one day after cooling down specimen exposed to 1000 ºC heat the compressive strength reach toabsolute zero. The certain level of heat in limited time will improve OPC-Kaolin-bentonite, it is revealedpossibility of using this method for improving cement paste in construction industry.
Keywords: Kaolin-bentonite mixture, compressive strength, hydration, XRD.

is exposed to temperatures of 400 ºC extend crack
compare to not used polypropylene fibers inconcrete. When the fibers dissolve with water, theconcrete expands, creating a tensile strength within
its matrix, and hence generating cracks [7-8]. The
quartz powder (QP) as mineral admixture used in
Portland cement (PC) from 0 to 20 wt % inincrement of 5% and subsequently exposed toelevated temperatures up to 1000 ºC for 2 h, whichstarted from 200 ºC and in each stage 200 ºC is
increased. The result indicated that the QP improves
both elevated temperature and thermal shock
resistance of the cement pastes [9]. It has been
indicated that compressive strengths of mortars
containing pozzolan were less affected hightemperature than that of control mortars [10]. Not
any studies have been performed on OPC-Kaolinbentonite mixture properties after elevatedtemperatures. It is very promising method, in
understanding mechanical properties of thiscomposite material after elevated temperatures. In
this paper a comparative study on OPC and OPCKaolin-bentonite exposed to elevated temperature
has been investigated. The mechanical properties,
ccompressive strength and hydration of pastes havebeen analysed, to find appropriate effect of heatlevel and room temperature during curing as well as
exposed high level temperature deterioration
mitigation of cement paste.

INTRODUCTION
The effect of elevated temperature on cement pateand concrete are two enormous topics in civilengineering research work. There are several reasons
available these two parts of investigation integrated
each other. This reconnaissance takes concentration
on effect of elevated temperature on cement pate andcomparing with previous work was on concrete.
The effect of CaO rehydration in reducing strengthof OPC after 800 ºC has been reported. It was findthat the rate of water absorption is a factor governs
the extent of deterioration caused by CaO
rehydration, and also water absorption quantity it isa reason in accelerating rehydration of CaO into
CaOH2. This phenomenon is impossible to observein concrete [2]. The maximum of water reduction
occurs between 300 and 500 ºC is due to thedehydration-dissociation of CaOH2. And OPC
produce is calcium hydroxide (CaOH2) during
hydration [3]. In an investigation on micro-level andmacro-level properties of cement pastes mixed withdifferent fiber contents to study role of PP fiber atelevated temperature in self-compacting cement
paste samples, is observed in higher temperatures
micro cracks is influences the gas permeability [4].
Reducing amount of concrete spalling and enhance
the fire-resistance has mitigate by using fire-resistantspray materials for ensure an effective level of fireresistance [5-6]. The polypropylene fiber in concrete339

GEOMATE-Nagoya, Nov.13-15, 2013

2. Experimental program
Materials
The produced additive is made from Kaolinbentonite mixture exposed to 800 ºC has ability toenhance compressive strength of concrete [1]. These
are natural commercial minerals. The produced
additive from Kaolin-bentonite mixture exposed to
800 ºC (12%) for one hour has been used as mineraladmixtures along with OPC (43 G) as a binding
material. The produced additive created from
Kaolin-bentonite mixture under 800 ºC have been
blended with OPC, Subsequently the compressive
strength is measured after exposed to temperature of
500 ºC and 1000 ºC for 3 hours in ceramic furnace(figure 1) and cooling down. The mix designs of theadditive and water to cement ratio are indicated inTable 1.

Cement paste mix design
The Kaolin-bentonite mixture [1] admixture has
been used for studying mineralogical reform andchemical reaction of cement paste. It is notdiscovering any specific methods for cement pastmix design used Kaolin-bentonite, this research
work is established by trial mixes. The ACI methods
could not be applied to the cement past mix design
with this new material for micro properties
investigation and analyzing their effect on macrocharacteristics of concrete. In this research work forthe identification of appropriate natural additive andestablish optimization of materials mix ratio theadditives are mixed based on weight of cement
paste.
Compressive strength
To obtain the effect of Kaolin-bentonite mixture(12%) on the compressive strength of OPC, cubicalmolds (5 cm × 5 cm × 5 cm) were preparedaccording water to cement ratio indicated in Table 1.
After initial curing of 1 day, the specimens were
kept at water 30 ± 5 ̊C for 28 days. The compressive
strength has been done as per ACI and the averagevalue of three specimens has been selected forinterpretation.
XRD
X-ray diffractometry (XRD) has been used toinvestigate in hydration process of OPC and OPCproduced additive [1] (figure. 2.1-2), mixture after
28 days of curing. The samples were grounded to aparticle size of <75 µm for application of XRD, toreconnaissance on hydration and morphologicalcharacteristic of cement pastes.

Figure.1. Paste cube exposed to temperature of 1000
ºC after 3 hours in ceramic furnace.

Fig. 2.1 XRD pattern of cement, and cement- kaolin-bentonite mixture, the kaolin-bentonite was submitted to
800 ºC heat for 1 hour [1].

340

GEOMATE-Nagoya, Nov.13-15, 2013

compressive strength. But in recent investigation has
not agreement with previous work, it is enoughreason for investigate effect of elevated temperature
on both cement paste and concrete. From other hand
the room temperature has specific effect on cement
paste hydration. The room temperature was 30 ± 5 ̊Cfor curing concrete and the room temperature was 20± 3 ̊C and more humidity for curing cement paste.
Test results showed [14] that the compressive
strength of concrete cooled in water cooling ishigher than that cooled in natural and furnace. It canbe understand humidity and room temperature areimportant factors in mitigating elevated temperatureof paste fire resistance. The finding in [1] and recent
research work has good agreement with which
reported in [14]. Pozzolanas are defining as siliceousand aluminous materials they react with lime to form
calcium silicate and calcium aluminate silicate
hydrates in moist environments [15]. The room
temperature also play important role in hydration
process and time. The compressive strength ofcement paste is exposed to high temperature can bepartially recovered by providing appropriate
environment contents sufficient humidity andtemperature. Figure 3 indicated OPC after elevatedtemperatures of 500 ºC for 3 hours and cooling inopen area for 2 hours in this case 70% of specimens
separated due to self-weight of specimen in furnace
but in same condition if Kaolin-bentonite mixed to
OPC this deterioration reduced (Figures 3-4). In
condition eliminating surcharge it is possible toincrease temperature up to 1000 ºC without thisdeterioration (figures 5-6). Figure 7 is shown OPC
after elevated temperatures of 500 ºC for 3 hours andcooling in open area for 2 days, it is faced severdeterioration. Figure 8 indicated that OPC-Kaolinbentonite after elevated temperatures of 500 ºC for 3
hours and cooling in water immediately in this casethe paste change color to black but not faced any
deterioration even after long term and its
compressive strength is improved. From other hand
if temperature increased to 1000 ºC cooling down of
specimen immediately in water resulted in fully
collapse (figure 8) and even after cooling down inopen area after 1 hour when the specimen cantransport by naked hand keeping in water it shown
collapse (figure 9). From above indications find thatcooling down of specimens can be done only in
specific environments which depend on specimen
temperature.

Figure. 2.2 Paste cube exposed to temperature of1000 ºC after 3 hours in ceramic furnace.
Table. 1. Mix designs of the solidified wastes.
Identity
W/C
Produced
ratio
Additive
OPC only - C 0
0.34
OPC + Kaolin
0.34
12-bentonite (12%)

RESULT AND DISCUSSION
A large amount of heat was released from thehydration process evaporating water inside thespecimens during curing due to minerals-cement
reaction. The method is suitable in cold region basedon mentioned phenomenon. The specimen subjected
to high level of heat is faced accelerating
rehydration due to high level of water absorption
and resulted in extending crack in specimen (figure3-7) and drastically reducing compressive strength.
According to Petzold and Rohrs [11], the reason forthis cracking is the expansive, and hence disruptive,
rehydration (due to reaction with airborne water
vapour) of previously dissociated CaOH2. It has
been reported [12-13] using pozzolanic materials
due to consume calcium hydroxide in cement pasteby pozzolanic reaction between calcium hydroxidein hydrated cement and reactive SiO 2 in mineraladmixtures help to reduce cracking due to postcooling. It has good agreement with figures 6-7 in
Ordinary Portland cement subjected to 1000 ºC for 3
hours bigger crack is appear, based on table 2
strength of Ordinary Portland cement paste-Kaolinbentonite mixture subjected to 1000 ºC for 3 hours
has lower compressive strength compare to Ordinary
Portland cement subjected to 1000 ºC for 3 hours.
And one day after fully cooling down both
specimens exhibited with zero compressive strength.
The pozzolanic materials in high temperature havemore negative effect on material due to fast reachingto end of hydration process. According to reported
mentioned in [1], the quantity of 12% Kaolinbentonite additive produced by 800 ºC heats has
shown best result in improving concrete341

GEOMATE-Nagoya, Nov.13-15, 2013

Sl
No
1
2
3
4
5
6

Table. 2. Cement paste-additive mixture ratio
Compressive
Type ofTime of Heat in
Heat level(%)
strength after 28
hours
additivedays (MPa)Roomtemperature
500 ºC
1000 ºC
Roomtemperature
500 ºC
1000 ºC

-

-

3
3
3
3

Additive
produced by
800 ºC (%) [1]

0

30.1

0
0

33.8
4.57

12

27.71

12
12

42.29
3.55

Fig. 5. OPC after elevated temperatures of 1000 ºC
for 3 hours and cooling in open area for 2 hours.

Fig. 6. OPC-Kaolin-bentonite mixture after exposed
to elevated temperatures of 1000 ºC for 3 hours andcooling in open area for 2 hours.

Fig. 3. OPC after exposed to elevated temperaturesof 500 ºC for 3 hours and cooling in open area for 2
hours.

Fig. 7. OPC after exposed to elevated temperaturesof 500 ºC for 3 hours and cooling in open area for 2
days.

Fig 4. OPC-Kaolin-bentonite after exposed toelevated temperatures of 500 ºC for 3 hours andcooling in open area for 2 hours.

Fig. 8. OPC-Kaolin-bentonite after exposed toelevated temperatures of 500 ºC for 3 hours andcooling in water immediately.

342

GEOMATE-Nagoya, Nov.13-15, 2013

REFERENCES[1] Namdar A, “Natural minerals mixture forenhancing concrete compressive strength”,
Frattura ed Integrità Strutturale, 22, 2012,
pp.26-30; DOI: 10.3221/IGF-ESIS.22.04.
[2] Mendes A, Sanjayan J. G, Gates W.P, Collins F,“The influence of water absorption and porosity
on the deterioration of cement paste andconcrete exposed to elevated temperatures, as ina fire event”, Cement & Concrete Composites,
34, 2012, pp. 1067-1074.
[3] Y. Lea FC, Stradling RE, “The resistance to fireof concrete and reinforced concrete”,
Engineering, 144, 1922, pp.341-4.
[4] Liu X, Ye G, Schutter G. De, Yuan Y, Taerwe
L, “On the mechanism of polypropylene fibres
in preventing fire spalling in self-compacting
and high-performance cement past”, Cement
and Concrete Research , 38, 2008, pp.487- 499.
[5] International research institute of cooperation
between industry and academia. Exfoliation of
the concrete tunnel of shinkansen and spallingof concrete structures, University of Tokyo,
Tokyo, Japan; 2002.
[6] ITA Working group No. 6. maintenance andrepair, Guidelines for structural fire resistancefor road tunnels; 2004.
[7] Kalifa P, Menneteau FD, Quenard D, “Spallingand pore pressure in HPC at high temperatures”,
Cem Concr Res 30, 2000, pp.1-13.
[8] Pierre K, Grégoire C, Christophe G, “Hightemperature
behaviour
of
HPC
with
polypropylene fiber from spalling tomicrostructure”, Cem Concr Res 31, 2001,
pp.1487-99.
[9] Rashad A. M, Zeedan S.R, “A preliminary
study of blended pastes of cement and quartz
powder under the effect of elevatedtemperature”, Construction and Building
Materials, 29, 2012, pp. 672-681.
[10] Yazıcı S, Sezer G.I, Sengül H, “The effect ofhigh temperature on the compressive strength ofmortars”, Construction and Building Materials,
35, 2012, pp.97-100.
[11] Petzold A, Rohrs M, “Concrete for hightemperatures”, Second ed, London, 1970,
Maclaren and Sons Ltd.
[12] Aydın S, Baradan B, “Effect of pumice and fly
ash incorporation on high temperature
resistance of cement based mortars”, Cem Conr
Res, 37(6), 2007, pp.988-95.
[13] Xu Y, Wong YL, Poon CS, Anson M,“Influence of PFA on cracking of concrete andcement paste after exposure to hightemperatures”, Cem Conr Res, 33(12), 2003, pp.
2009-16.
[14] Karakoç M.B, “Effect of cooling regimes oncompressive strength of concrete with

Fig. 9. OPC-Kaolin-bentonite after exposed toelevated temperatures of 1000 ºC for 3 hours andcooling in water immediately.

Fig. 9. OPC-Kaolin-bentonite after exposed toelevated temperatures of 1000 ºC for 3 hours andcooling in water after 2 hours.

CONCLUSION
This is well known that the elevated temperaturechanges engineering properties of construction
materials. In this investigation has been observedthat the certain level of heat in limited time will
improve OPC properties if appropriate additive has
been used. Both cement paste and concrete has to beinvestigated for accurate design construction
materials. The humidity, room temperature andelevated temperature are important factors in fire
resistance mitigation of concrete and concrete curing
time. The compressive strength of cement paste
exposed to 1000 ºC for 3 hours is reduced
continuously and is reached to absolute zero evenafter cooling down, and stopping exposing hightemperature not stopping reducing compressive
strength of specimen and deterioration process of
micro properties of cement paste destroy wholecompressive strength gradually. The compressive
strength of cement paste is exposed to hightemperature can be partially recovered or reduce
deterioration of concrete structure by providing
appropriate
environment
contents
sufficienthumidity and temperature. There is possibility for
improve paste characteristics using appropriate
temperature, method and additive.

343

GEOMATE-Nagoya, Nov.13-15, 2013

lightweight aggregate exposed to hightemperature”, Construction and Building
Materials, 41, 2013, pp.21-25.
[15] Heikal M, El-Didamony H, Sokkary T.M,
Ahmed I.A, “Behavior of composite cement
pastes containing microsilica and fly ash atelevated temperature”, Construction and
Building Materials, 38, 2013, pp.1180-1190.

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PARTICLE SIZE AND OTHER FACTORS AFFECTING THE
PULLOUT BEHAVIOR OF GEOCELLS EMBEDDED IN GRAVELLY
SOIL BACKFILL
1, 2

Xinye Han 1, Takashi Kiyota2, Michiyuki Harata3 and Fumio Tatsuoka4
Institute of Industrial Science, University of Tokyo, Japan; 3 Plastic Products, Technical& Engineering
Plastic Products Sales Division, Tokyo Printing Ink MFG.CO.LTD, Japan; 4 Department of Civil
Engineering, Tokyo University of Science, Japan

ABSTRACT
In order to study whether geocell can be worked as tensile reinforcement in retaining walls, pullout tests were
performed on two types of geocell which have diamond-shaped cells and square-shaped cells embedded in two
different compacted gravelly soils under the surcharge of 1 kPa at constant pullout rate. Different pullout
behaviors were found due to the effect of in-plane geometry which can be explained by different interaction
mechanisms. In particular, the dilatancy effects on the pullout strength of geocell were also discussed. Moreover,a preloading method was applied to reduce the slackness of transverse members of square-shaped geocell, andtherefore enhance the initial stiffness.
Keywords: Pullout test, Diamond-shaped geocell, Square-shaped geocell, Preloading method

INTRODUCTION
Geocells,
as athree-dimensionalsoil
confinement system, have been widely applied inconstruction roads over soft soils, stabilization soils
on embankments, protection steep slopes.
The common type of geocell has a diamondpattern, on which many studies were carried out
mainly to check the function as base reinforcements
subjected to vertical loads, such as roads,
embankments and light houses. The influencing
factors for the performance of geocell-reinforced
bases, such as geometric structures and dimensions,
properties of geocell material and properties of
infilled soil, loading methods, etc., were investigatedby previous works [1]-[4], etc. However, theapplication of geocell as tensile reinforcement to soil
structures, such as retaining walls, is relatively new
due to the lack of related research. Ling et al. (2009)[5] investigated the seismic performance of several
soil retaining walls having a geocell facing byshaking table tests. The results showed that walls
having a geocells facing are flexible exhibiting muchbetter seismic performance than conventional typeretaining walls. In addition, the performance of aretaining wall with the backfill reinforced with
geocell layers is better than with geogrid layers.
In order to check whether geocell can be worked
as tensile reinforcement, two types of geocell whichhave diamond-shaped cells (traditional type geocell)and square-shaped cells (new developed geocell)were evaluated by pull-out tests embedded in two
different compacted gravelly soils.

TEST APPARATUS,
MATERIALS

PROCEDURES

AND

Pullout Test Apparatus
Figure 1 shows the schematic diagram of pullout
test apparatus that was developed at IIS, theUniversity of Tokyo. The tests are carried out onplane-strain condition. The soil box is rectangular inshape and made of steel. The dimensions of innersoil box are 700mm (length) ×400mm (width)
×500mm (height). The opening size of the front wall
could be changed for pulling out the model geocellsof different heights. Leads shots are applied on the
crest of the backfill to provide a surcharge of 1 kPa
as a flexible top boundary, which is preferred for the
purpose of measuring vertical deformation of
backfill, which caused by the dilatancy of soil
around the geocell reinforcements in the pullout
process.

Fig. 1

345

Schematic diagram of pullout test apparatus

GEOMATE-Nagoya, Nov.13-15, 2013

Pullout Test Procedures
Gravels were poured into the soil box andcompacted in 25 cm-thick sub-layers arranging
geocell model at the prescribed level in the backfill.
The target density of the backfill was 1.76g/cm3. As
indicated in Fig. 1, the front displacement (d0) wasmonitored by laser deformation transducer. The
displacements along the geocell, for example, thelocations at distances of 60 mm (d60), 180 mm (d180),
300 mm (d300), and 540 mm (d540) from the face offront wall were measured with linear variable
differential transformers (LVDTs). Monitoring thedisplacements along the geocell reinforcement
allows proper interpretation of the interface force
transfer mechanism and provides appropriate
evaluation of the pullout resistance as well.
Inextensible stainless wires were connected to thedesignated locations of geocell reinforcement tomeasure the displacements along the geocell
reinforcement. The wires were protected by stiff
tubes and connected to the LVDTs, which were
mounted on the rear wall of soil box. In addition, thevertical deformation of the backfill surface at
distances of 60 mm (V60), 300 mm (V300), and 540
mm (V540) from the face of the front wall were alsomeasured with three LVDTs. The tests wereconducted by pulling out the geocell at a constantdisplacement rate of 2.5 mm/min using a precision
jack driven by a motor. The pullout force wasmeasured with a load cell. All instrumentations werelinked to an electronic data logger which can scan
the measurements at desired time intervals.

Fig. 3 Schematic diagram of: (a) square-shaped
geocell and (b) diamond-shaped geocell
RESULTS AND DISCUSSION
Effects of Geometry of Geocell
Typical pullout behavior
Typical pullout test results on square-shaped
geocell and diamond-shaped geocell embedded in
Gravel No.1 and Gravel No.3 are presented in Fig. 4.
The pullout resistance (P) versus horizontal
displacement (d60) of geocells is plotted in Figs. 4aand 4c, while the vertical displacement (V60) of thebackfill surface and horizontal displacement (d60) of
geocells is plotted in Figs. 4b and 4d. It is found thatsquare-shaped geocell shows both higher peakpullout resistance and higher initial stiffness thandiamond-shaped geocell in both soil materials. It isinteresting to note that, for square-shaped geocell
embedded in Gravel No.1, with increasing pullout
horizontal displacement (d60) there is a high peakpullout resistance indicating a contribution fromdilatancy of soil (Fig. 4b), and then as pullout
continues the resistance decreases to a residual state.
The peak pullout resistance at 16mm horizontal
displacement coincides with the steepest slope of thevertical displacement line (Fig. 4b). This behavior isquite similar to the typical behavior of granulardense soils which indicates that the dilatant
contribution equals the work done against thenormal stress as pullout progresses, thereby
increasing the pullout resistance, as pullout
continues, the shear zone around the geocell
reinforcement eventually achieves to a stable state-

Soil Materials and Tested Geocell Models
The backfill soils used in this study were poorly
graded sub-round gravelly soils, Gravel No.1 andGravel No.3 (Fig. 2). Their particle sizes are 3~5mm and 7~10 mm, respectively. As shown in Fig. 3,
two types of geocell reinforcements were prepared:
diamond-shaped geocell (conventional type geocell)and square-shaped geocell (new developed typegeocell), both of which were made of polyethylene
terephthalate (PET) covered with PVC for protection,
having a thickness of 1 mm. The ultimate tensile
strength of the material is 56 kN/m at a strain of
20%.

Fig. 2
No.3

Soil materials: (a) Gravel No.1; (b) Gravel

346

GEOMATE-Nagoya, Nov.13-15, 2013a 16

Fig. 4 Typical pullout behaviors of square-shaped
geocell and diamond-shaped geocell: (a) and (c),pullout resistance against horizontal displacements(d60); (b) and (d), relationships between verticaldisplacement (V60) and horizontal displacement (d60)

Pullout resistance (kN/m)

14
12

Square-shaped Geocell(H=25mm)

t1'

10
8

Diamond-shaped Geocell(H=25mm)

6
4

t3

t2

2

t1

0

0

t4

Backfill: Gravel No.1
Vertical pressure:4.95/5.20kPa

t0'/t0-2-10sliding state, in which the pullout resistance reaches
residual state. While for diamond-shaped geocell,the dilatant contribution is lower than square-shaped
geocell (Fig. 4b), which is associated with the valueof the pullout resistance is lower than square-shaped
geocell in both peak state and residual state (Fig. 4a).
From Figs. 4c and 4d, similar pullout behavior ofsquare-shaped geocell and diamond-shaped geocell
embedded in Gravel No.3 are also investigated. In
both cases, as shown in Fig. 5, square-shaped
geocell exhibits not only higher peak pullout
resistance but also higher residual pullout resistancethan diamond-shaped geocell. These differences are
due likely to the different geometries of the geocell,in particular the shape of aperture (Fig. 3). Moreover,as particle size increases from Gravel No.1 to Gravel
No.3, the peak pullout resistance increases
associated with an increase of dilatancy for bothdiamond-shaped geocell and square-shaped geocell.

10

20

30

40

50

60

70

80

Horizontal Disp. (d60, mm)

Vertical Disp. (V 60, mm)b 24

Backfill: Gravel No.1
Vertical pressure:4.95/5.20

20
16

Square-shaped geocell(H=25mm)12
8
4

Diamond-shaped geocell(H=25mm)

0
-10

0

10

20

30

40

50

60

70

18

80
Pullout resistance (kN/m)

Horizontal Dsip. (d60, mm)

c 16
Pullout resistance (kN/m)

14

Square-shaped geocell(H=25mm)

12
10
8
6
4

-2
-10

0

10

20

30

40

50

60

70

Vertical Disp. (V 60, mm)

Square-shaped geocell(H=25mm)128
Diamond-shaped geocell(H=25mm)

0
-10

0

10

20

Peak strength=Residual strength

642Gravel No.3

Gravel No.1
0

2

4

6

8

10

12

14

16

Figure 6 represents the distribution of local
horizontal
displacementsofthegeocell
reinforcements for different values of the applied
pullout forces, and the slope of the curve represents
local strain. It is found that, for square-shaped
geocell (Fig. 6a), two different phases are observed
to characterize the pullout behavior of thereinforcement: (1) In Phase 1 (force-transfer phase),
the local strain increases as the pullout force
increases, which indicates that the tensile force isprogressively transferred to the geocells and the eachcell provides its passive anchorage resistance or
shear resistance consecutively from the front cells

Vertical pressure:4.86/5.2kPa

4

Residual strength

8

Stress-deformation mechanism

d 24 Backfill: Gravel No.3
16

10

Fig. 5 Peak and residual pullout resistances for
geocell reinforcement in different backfill soils

80

Horizontal Disp. (d60, mm)

20

12Mean particle size (D50, mm)

Backfill: Gravel No.3
Vertical pressure:4.86/5.2kPa

0Peak strength

140

Diamond-shaped geocell(H=25mm)2

Square-shaped geocell (H=25mm)
Diamond-shaped geocell (H=25mm)

16

30

40

50

60

70

80

Horizontal Dsip. (d60, mm)

347

GEOMATE-Nagoya, Nov.13-15, 2013near the point of pullout load application to the end
cells until the peak pullout state (P=12.59kN/m) of
geocell reinforcement after which no increment ofstrain along the geocell reinforcement occurs. Noteagain, at peak state, the steepest slope of verticalhorizontal displacements curve (V60-d60) is reached(Fig. 4b); (2) In Phase 2 (sliding phase), two
adjacent curves are parallel each other, indicatingthat the geocell reinforcement move as a whole andthe shear bands form where the residual shear force
determines the residual pullout resistance.

Backfill: Gravel No.1
50 Vertical pressure:4.95kPa

40
30

9.50 kN/m
10.59 kN/m
11.50 kN/m
Pullout force 12.59 kN/m
11.99 kN/m
10.06 kN/m
8.84 kN/m
2.49 kN/m

100

Phase 220
100Peak statePhase 1

0

100

200

300

400

500

Horizontal Disp. (mm)Local disp. of geocell (mm)a 60 Square-shaped Geocell (H=25mm)

Fig. 7 Schematic stress-deformation characteristics
of diamond-shaped geocell: (a) horizontal
displacement versus time history; (b) schematic
diagram of stress-deformation mechanism

600

Local disp. of geocell (mm)

b

60
40

60 Diamond-shaped Geocell (H=25mm)
Backfill: Gravel No.1
50 Vertical pressure:5.20kPa

20Phase 1
Phase 230
Phase 1

20

0
200

300

400

500

600

Distance from wall (mm)Fig. 6 Local horizontal displacements at different
pullout force levels: (a) square-shaped geocell and(b) diamond-shaped geocell

a 100 Diamond-shaped Geocell (H=25mm); Gravel No.1
80
60

d60

40

d180
Phase 1

20
0

t0

0

t1

t2

500

d300
t4

t3

1000
Time (s)

1500

500

1000

Fig. 8Stress-deformationsquare-shaped geocell

10

100

t1'

t0'

1500

2000

Time (s)Pullout force
4.70 kN/m
4.56 kN/m
4.94 kN/m
5.03 kN/m
4.03 kN/m
2.07 kN/m

40

d60
d180
d300
d540

Peak state0

0

Horizontal Disp. (mm)800Distance from wall (mm)Square-shaped Geocell (H=25mm); Gravel No.1

d540
2000

characteristicsofIn the case of diamond-shaped geocell (Fig. 6b),
only Phase 1 (force-transfer phase) occurs. It isnoteworthy to highlight that, due to large
deformation of diamond-shaped cell itself, the last
node of geocell does not move at large displacementof the first node, which restricts the development ofshear band along the geocell resulting in a lower
peak resistance.
Figures 7 and 8 show the stress-deformation
characteristics of diamond-shaped geocell andsquare-shaped geocell varying with time whensubjected to a pullout force. The schematic diagramsof deformation status varying with time are given in
the inset of the figures. In particular, the stressdeformation mechanism of diamond-shaped geocell
is shown in Fig. 7b. For diamond-shaped geocell(Figs. 4a and 7), from t0 (initial state) to t1 (the firststate), the first diamond cell starts to deform andprovide corresponding pullout resistance (Fig. 4aand 7b) until other cells reach the residual resistancestate of the first cell. Afterwards from t1 to t2, thesecond and the third cells deform and provide theirpullout resistances until the rest cells reach theresidual state of them. This procedure repeats from t2
to t3 until all cells work in the pullout Phase 1 (forcetransfer phase). This deformation characteristics of
diamond-shaped geocell can be characterized as
348

GEOMATE-Nagoya, Nov.13-15, 2013

progressive deformation in Phase 1 (force-transfer
phase), which would induce the soil surrounding the
diamond-shaped geocell not fully mobilized, andtherefore cause a lower peak pullout resistance andinitial stiffness compared with the square-shaped
geocell. However, as shown from Figs. 4a and 8, thesquare-shaped geocell only shows a slightly
progressive deformation in Phase 1 (force-transfer
phase) from t0 (initial state) to t1 (peak state). After
that, all square cells work immediately which could
provide larger peak pullout resistance and higher
initial stiffness than diamond-shaped geocell. It is
possible to observe the final deformation states of
diamond-shaped geocell (Fig. 9a) and squaredshaped geocell (Fig. 9b), showing shrink
deformation
characteristics
andnon-shrink
deformation characteristics close to the position ofclamp, respectively.

Fig. 10, a preloading was applied at the value ofresidual strength in order to decrease the slacknessof transverse members as presented in Fig. 11. From
Fig. 12a, with Gravel No.1, the initial pullout
stiffness of square-shaped geocell increases
significantly by preloading method, while from Fig.
12b, with Gravel No.3, the initial pullout stiffness
increases slightly. However, the preloading method
has little influence on the peak resistance andresidual resistance in both cases.
16

Square-shaped geocell (H=25mm)

Pullout resistance (kN/m)

14

a

12
10
8

Ppre=65.7% of Ppeak=Presidual

642

Backfill: Gravel No.1
Vertical pressure:4.95kPa

0
-2
-10

0

10

20

30

40

50

60

70

Horizontal Disp. (d60, mm)

Fig. 10
geocell

Preloading method for square-shapedbFig. 11
Arrangements
members before test

a 16

Fig. 9 Final deformation states of: (a) diamondshaped geocell and (b) square-shaped geocell

Pullout resistance (kN/m)With square-shaped geocell, the peak pullout
resistance and initial stiffness are mainly determinedby the anchorage resistance provided by transverse
members or shear resistance around geocell
reinforcements in Phase 1 (force-transfer phase). In
particular, initial stiffness would increase as anincrease in the stiffness of transverse members andbetter initial arrangements of transverse members
would also be of prime importance. As shown intransverse

12
10
8

Non-preloading

6
4
2
0
-2
-10

Square-shaped geocell H=25mm, Gravel No.1
0

10

20

30

40

50

Horizontal Disp. (d60, mm)

349

cell

Vertical pressure:4.95kPa

14 Preloading

Enhancement of Initial Stiffness

of

60

70

GEOMATE-Nagoya, Nov.13-15, 2013b 16 Preloading
Pullout resistance (kN/m)

resistanceprovided by transverse
members or shear resistance of the shear
band determines the total pullout resistance
until the peak state, after that, in Phase 2(sliding phase), the geocell reinforcement
moves as a whole and the shear bands form
where the residual shear force determines
the residual pullout resistance.
c) A preloading method was applied to reduce
the slackness of transverse members ofsquare-shaped geocell, and therefore
enhance the initial stiffness.
d) In Phase 1 (force-transfer phase), thedimension of geocell, such as height ofgeocell and spacing between transverse
members determines the mobilization ofinteraction mechanism and therefore thepeak pullout resistance, which should be
investigated in the future.

Vertical pressure:4.95kPa

14
12
10

Non-preloading

8
6
4
2
0
-2
-10

Square-shaped geocell H=25mm, Gravel No.3
0

10

20

30

40

50

60

70

Horizontal Disp. (d60, mm)

Fig. 12
Enhancement of square-shaped geocell
by preloading method with: (a) Gravel No.1 and (b)Gravel No.3
CONCLUSIONREFERENCES
The pullout tests were conducted using
diamond-shaped geocell and square-shaped geocell
embedded in compacted granular soils under thesurcharge of 1 kPa at constant pullout rate. The main
conclusions could be summarized as follows;[1] Mhaiskar, S.Y. and Mandal, J.N. (1994). “Three
dimensional geocell structure: performance
under repetitive loads”, 5th International
Conference on Geotextile, Geomembranes andRelated products, Singapore, 155-158.
[2] Dash, S.K., Krishnaswamy, N.R., andRajagopal, K. (2001). “Bearing capacity of strip
footings supported on geocell-reinforced sand.”
Geotextiles and Geomembranes, 19(4), 235-256.
[3] 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(4), 197-219.
[4] Dash, S.K., Rajagopal, K. and Krishnaswamy,
N.R. (2004). “Performance of different
geosynthetic reinforcement materials in sandfoundations.” Geosynthetics International, 11(1),35-42.
[5] Ling, H.I., Leshchinsky, D.,Wang, J.P., Mohri,
and Y., Rosen, A. (2009). Seismic response of
geocell retaining walls: experimental studies.
ASCE
Journalof
GeotechnicalandGeoenvironmental Engineering 135, 515-524.

a)

The square-shaped geocell exhibits muchhigher peak pullout resistance and higher
initial stiffness than the diamond-shaped
geocell, and with an increase in particle
size from Gravel No.1 to Gravel No.3, thepeak pullout resistance increases for bothtypes geocell, associated with an increaseof soil dilatancy.
b) These differences are related to the effectof geometry of geocell on the mobilizationof interface mechanisms. With diamondshaped geocell, a large progressive
mobilization of the interface interaction
mechanism develops indicated as Phase1(force-transfer phase), which determine
the total pullout resistance; on the other
hand, square-shaped geocell firstly
experiences
slightly
progressive
deformation indicated as Phase 1 (forcetransfer phase) in which passive anchorage

350

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECT OF LOADING RATE ON STRENGTH CHARACTERISTICS
OF GRANULAR BASE COURSE MATERIAL
Yuan Zhang1, Tatsuya Ishikawa2 and Tetsuya Tokoro3
Graduate School of Engineering, Hokkaido University, Japan; 2Faculty of Engineering, Hokkaido
University, Japan; 3Tomakomai National College of Technology, Japan

1

ABSTRACTThis paper examines the effect of loading rate on the shear behavior of granular base course material under aseries of degrees of saturation through monotonic triaxial compression tests. In this study, monotonic triaxial
compression tests under consolidated drained condition (CD test) were carried out. The experimental results
show that peak strength of base course material increases with the increase of loading rate, especially in air-dried
condition. Besides, it is appeared as the loading rate plays a remarkable part in the shear strength parameters
obtained for granular base course material. Under air-dried and saturated condition the internal friction angle
increases with the increase of loading rate, while the cohesion decreased with the increase of loading rate.
Loading rate effects under unsaturated condition do not appear to be the same regularity as under air-dried andsaturated conditions.
Keywords: Unsaturated soil, Monotonic triaxial compression test, Suction, Shear strengthwith a medium-size specimen, which were highly
useful in water retention tests and triaxial
compression tests in terms of the reduction of total
testing time as in [2].
In this paper, in order to examine the effects ofloading rate on the shear behavior of a granular basecourse material (C-40), a series of monotonic triaxial
compression tests for C-40 with different degree ofsaturation were conducted under different loading
rates with the medium-size triaxial compression
apparatus. Here, the monotonic triaxial compression
tests were carried out under fully drained condition(CD test) during shearing process.

INTRODUCTION
The pavements have to transfer traffic loadings
with different loading speeds from the asphaltmixture layer to subgrade course layer, which causes
deterioration on the pavement structures. However,throughout a year, the water content of pavement
will be affected by the infiltration of water throughvarious means. Especially, in snowy cold regions,such as Hokkaido, Japan, the water content of thepavement rises due to the inflow of thaw water or
thawing of ice lenses. As a result, the bearing
capacity of the subgrade and base course temporarily
degrades. Therefore, it is of great significance tounderstand the influence of loading rate on themechanical characteristics of unsaturated basecourse material under different degree of saturation.
Many different types of unsaturated soil havebeen studied by various researchers, however, there
is limited available information in existing literature
on mechanical behavior of unsaturated base course
material which has maximum particle size of almost
40mm. This is because laboratory element tests forunsaturated soils with large-size specimens are quite
time-consuming due to the ceramic disk with very
low permeability usually used in the test apparatus
for unsaturated soils. Recently, Nishimura et al. [1]performed some kinds of laboratory element tests forunsaturated soils using a cellulose filter, and wereable to confirm the validity of using this filter as a
substitute for a ceramic disk and thus shorten thetesting time. On the other hand, based on theusefulness of membrane filters, we proposed testing
methods adopting the pressure membrane method

TEST MATERIAL
The base course material (C-40) was employed
as a test material in this study, which is a natural
crusher-run made from angular, crush, hard andesitewith maximum particle size of 40mm. C-40 is
encountered in subbase course layer of Japanese
pavement structures. Physical properties and grainsize distribution curves for test specimen are shownin Table 1 and Fig. 1, respectively. Note that
according to the results of sieve analysis before andafter the test as shown in Fig. 1, the particle
breakage of C-40 under air-dried condition at
effective confining pressure of 34.5kPa was notlargely caused during the monotonic triaxial
compression test with loading rate of 0.05%/min.
When we performed the monotonic triaxial
compression test under unsaturated condition, theprescribed degree of saturation can be obtained byapplying corresponding suction based on the soil
351

GEOMATE-Nagoya, Nov.13-15, 2013

water characteristic curve (SWCC). Figure 2 shows
the relationship between matric suction (s=u a -u w )and degree of saturation (S r ) obtained from the water
retention test on C-40 with the degree of compactionof 95% in the previous study [2]. The residual
degree of saturation of C-40, which was 23.94%, canbe determined through the fitting curve by LGmodel [3]. On the basis of Fig. 2, in order to get theapproximate degree of saturation as the same value
as regular degree of saturation (about 35%) in thereal long-time field measurement [4], the suction of
10kPa was selected.

Fig. 3. In the cap and pedestal, the pore waterpressure is applied to a specimen through a versapor
membrane filter attached to the water plumbing
path, while the pore air pressure is applied through ahydrophobic polyflon filter attached to the air supply
path in the cap and pedestal. Physical properties ofthe filters are shown in Table 2.
HybridActuator
Air supply path
Dial
gauge

Table 1 Physical properties of base course material.
Load cell
LVDT

Percent finer (%)

w opt
Fc
PI
ρ dmax *2 ρ dmin *2
ρ dmax *1
3(g/cm ) (%)(%)(g/cm3) (g/cm3)
2.070
8.2
5.20
NP
2.270
1.680
Note: *1 is compaction E-b method (JIS A 1210,
2009). *2 is test method for minimum and maximum
densities of gravels (JGS 0162, 2009).

100
90 σc'=34.5kPa, ε.a=0.05/min
80 Air-dried, D =95%c
70
60
Before test
50
After test
40
30
20
10
0
0.01
0.1
1
10
Grain size (mm)Suction, s (kPa)

Fig. 1

Fig. 2

Gap sensor

LVDT
Cap
Gap sensor

Water plumbing path
Screw
Hydrophobic
polyflon filter

Pedestal
Lower
plate

Porous metal
Versapor membranefilterFig. 3Medium-size triaxial apparatus
structure of cap and pedestal.

andTable 2 Physical properties of filters.
Thickness Pore size AEV/WEV*1
(μm)
(μm)
Versapor
94.0
0.8
60
Polyflon
540.0
14.3
Note: *1 AEV is the air entry value of versapor
membrane filter, while WEV is the water entry valueof hydrophobic polyflon filter.
Name

100

Grain size distributions of C-40 before andafter test.

18
16
14
12
10
8
6
4
2
0

Loadingrod

The measurements of stress and strain of a
specimen were performed as follows. Axial stress(σ a ) was measured by a load cell installed inside thetriaxial cell. Axial strain (ε a ) was obtained bymeasuring the displacement of loading piston withan external displacement transducer (dial gauge) andtwo linear variable differential transducers (LVDTs).
Volumetric strain (ε v ) was measured by two sets of
two proximity transducers (Gap sensors). As shownin Fig. 3, the gap sensors were fastened on two
pillars diagonally opposite to each other around thespecimen diameter. To ensure the accuracy for ε v
including unsaturated condition, the ε v wascalculated by taking the average value between two
methods. One approach was that specimen wasdeemed to maintain a cylinder in the ideal caseduring shearing. And then diameter change of
specimen during shearing could be measured by gap
sensors, while vertical displacement change can bemeasured by dial gauge. Hence, the volume change
can be calculated in accordance with the diameterC-40 SWCC(Dc=95%)
Fitting curve by LG model

30 40 50 60 70 80 90 100
Degree of saturation, Sr (%)

Soil-water characteristic curve of C-40.

TEST APPARATUS
A schematic diagram of the medium-size triaxial
apparatus for unsaturated coarse granular materials
and the structure of cap and pedestal are shown in352

GEOMATE-Nagoya, Nov.13-15, 2013change and axial displacement change. The anothermethod was as below: The initial positions of gap
sensors were at the point of ¼ and ¾ of thespecimen, therefore, with the increase of shearing,the measuring positions on specimens by gap
sensors were also changed. During shearing thespecimen was postulated to have a vertical crosssection of a “beer barrel shape”, and the curve partsof which were represented approximately byparabolas. The parabolas can be drawn by themeasurement data of gap sensors and the axial
displacement change. Then the volume change of
specimen can be calculated by the parabola, which
was assumed to be equal to the rotator of theparabola [5]. Finally, ε v of the specimen was
obtained by the mean value of volumetric strain
calculated from the two above mentioned methods.
In case of saturated specimens, the volume ofdrainage during testing was also measured with adouble tube burette.

GAMES with coefficients of slip interface of 0.0 and
0.5 are 33.4kPa and 67.6kPa, respectively, which areclose to the confining pressure of 34.5kPa and68.9kPa in AASHTO standard. Therefore, the σ c ' inthis paper were selected as 34.5kPa and 68.9kPa.
For the air-dried specimen, the S r was 8.2%. All
saturated specimens (S r =100%) were saturated by
CO 2 method and the B-value of each saturated
specimen was insured as 0.96 or more. For theunsaturated specimen, the S r of specimen was about
35% by applying an intended suction of 10kPa.
Reference [2] presents detailed operation approachesof consolidation for specimens with different S r .
Upon attaining an equilibrium condition in the
consolidation
process,
thespecimenwascontinuously sheared by applying an axial deviator
stress (q=σ a -σ c ) at a designated loading rate of
0.05%/min or 0.5%/min under fully drained
condition (CD test) regardless of the water content,
while all other testing parameters were held constant.
Here, σ a is the axial stress. Note that the loading rateof 0.05%/min in drained test was selected based on
the standard of Japanese Geotechnical Society (JGS
0527, 2000), while the loading rate of 0.5%/min was
designed by referring to the axial strain rate of
1.0%/min in quick shear test of MR test [7].

TESTING METHOD
Monotonic triaxial compression tests were
performed with different loading rates of 0.05%/min
and 0.5%/min under three different degrees ofsaturation, namely “air-dried”, “unsaturated”, and“saturated” in conformance with the standards ofJapanese Geotechnical Society (JGS 0524 & JGS
0527, 2000).
A cylindrical specimen for C-40 with initially
300mm in height and 150mm in diameter was
prepared with air-dried sample by tamping with awoody rammer and compacting with a vibrator infive layers. And more detail about the specimen
preparation method was described in previous study[2]. Note that after finishing all the tests underunsaturated condition, the air entry value (AEV) of
versapor membrane filters would be checked byapplied suction increasingly until air passed throughthe filters. Measurements of versapor membranefilters attached to the cap and the pedestal showedthat the AEV after the test were nearly equal as
before. This indicates that the versapor membranefilter suffers little degradation from the wear andtear during monotonic triaxial compression tests oncoarse granular material.
Next, a consolidation process was conducted.
Note that there are two effective confining pressure(σ c '): 68.9kPa and 34.5kPa. The loading condition of
σ c ' loaded on roadbed middle were estimated basedon stress analysis of Japanese paved road model by
GAMES (General Analysis Multi-layered Elastic
Systems) [6]. Fig. 4 is the result of stress state inside
typical Japanese pavement structure with different
coefficients of slip interface calculated by GAMES,
and AASHTO is the testing sequence forbase/subbase of MR test [7]. Here, the maximum
confining pressures of roadbed middle calculated by

Deviator stress, q (kPa)

300

Fig. 4

250
200
150
100

AASHTO
Slip 0.0
Slip 0.5

33.4
34.5
67.6
68.9

50
0
0

30
60
90 120 150
Confining pressure, σc (kPa)Stress state inside
pavement structures.

typicalJapanese

TEST RESULTS AND DISCUSSION
Stress-strain Behavior
Fig. 5 and Fig. 6 show typical relationships for
air-dried, unsaturated and saturated specimens
among the q, ε v and ε a obtained from CD tests under
different loading rates at σ c ' of 68.9kPa and 34.5kPa,
respectively. It should be noted that in Fig. 5(c) and
Fig. 6(c), the results of volumetric strain were
measured by gap sensors and burette under saturated
condition. The dash dot lines denote the volumetricstrains obtained by burette. As what to be confirmed
previously, the two methods of gap sensors andburette were in reasonable agreement with each353

GEOMATE-Nagoya, Nov.13-15, 2013

When comparing two curves obtained from tests
under air-dried condition with different loading rates
at the σ c ' of 68.9kPa and 34.5kPa as shown in Fig.
5(a) and Fig. 6(a), the results clearly show thatbehavior of C-40 was affected by loading rate. Theq-ε a relationship with higher loading rate locates
above of that with lower loading rate and peakstrength is increasing with increase of loading rate as
shown in Fig. 7. The reason for the increase in peakstrength would be related with corresponding
volume changes during shearing as discussed inreference [8], which analyses from the view ofparticle crushing and rearranging during shearing.
Since there is not obvious particle breakage on thebasis of sieve analysis, the particle rearranging could
be considered to play an important role in peakstrength during shearing. As shown on ε v -ε a curves,300

εv - εa200

C-40, σc'=34.5kPa

100

Air-dried, Dc=95%

0
0

3
6
9
12
Axial strain, εa (%)

Deviator stress, q (kPa)

Volumetric strain, εv (%)

500

(b)

q - εa15

0.5%/min
0.05%/min

400
300

εv - εa

200

3
6
9
12
Axial strain, εa (%)

Volumetric strain, εv (%)

Deviator stress, q (kPa)

Relationships among q, ε v and ε a underσ c '=68.9kPa.

Fig. 6q - εa300
Burette200
100
0εv - εa02150.5%/min
0.05%/min

(c)

400

-2

Unsaturated, Dc=95% 0

0
0

500

-4
C-40, σc'=34.5kPa

100

600

354

-6
-4
-2
0
2

Volumetric strain, εv (%)

400

600

900
0.5%/min
800 (c)
0.05%/minq - εa
700
-8
600
-6
500
Burette400-4300
εv - εa-2
C-40, σc'=68.9kPa
200
100
Saturated, Dc=95% 0
2
0
0
3
6
9
12
15
Axial strain, εa (%)

Fig. 5500

0.5%/min
0.05%/minq - εa(a)Volumetric strain, εv (%)

Volumetric strain, εv (%)

Deviator stress, q (kPa)

600

Volumetric strain, εv (%)

Deviator stress, q (kPa)

900
0.5%/min
0.05%/min
800 (b)q - εa
700
600
500
400
-4
εv - εa300-2C-40, σc'=68.9kPa
200
0Unsaturated,
D
=95%
100
c
2
0
0
3
6
9
12
15
Axial strain, εa (%)

Deviator stress, q (kPa)

900
0.5%/minq - εa800 (a)0.05%/min
700
600
500
400
εv - εa-4300-2C-40, σc'=68.9kPa
200
100
Air-dried, Dc=95% 0
2
0
0
3
6
9
12
15
Axial strain, εa (%)

Deviator stress, q (kPa)other in the change of ε v during shear up to the ε a of
6 % approximately until the q reached peak.
Accordingly, we do not adopt the ε v calculated withthe lateral displacements of the specimens measured
by gap sensors as an experimental data in the rangeof ε a of 6% or more from the viewpoint of themeasurement precision.
According to set of curves in Fig. 5 and Fig. 6,
the dense compacted C-40 exhibits strain softening
behavior irrespective of loading rates during
shearing process. With increasing ε a , q sharply
increases to the peak strength at ε a of about 4% to
6%, and then it gradually decreases to the residual
strength at ε a =12% or over. Further, the volumes of
all the specimens initially decrease, and then thespecimens dilate with the increment of ε a during
shearing, irrespective of loading rates and S r .

-8
-6
-4
-2
C-40, σc'=34.5kPa
Saturated, Dc=95% 0
2

3
6
9
12
Axial strain, εa (%)

15

Relationships among q, ε v and ε a underσ c '=34.5kPa.

Maximum deviator stress, qmax (kPa)GEOMATE-Nagoya, Nov.13-15, 2013

1000
900
800
700
600
500
400
300
200
0.0

Fig. 7

shear resistance between grain contact points. It is
supposed that the suction here is capillary force
which acts perpendicularly on grain contact points
and attracts soil particles together. Then this force
restrains relative sliding between soil particles [11].
For this reason the peak strength is correspondingly
increasing with decrease of S r .

Hollow symbols represent σc'=34.5kPa
Solid symbols represent σc'=68.9kPa

Air-dried
Unsaturated

Saturated

Air-dried
Unsaturated

Influence on Strength Parameters
Saturated

0.1 0.2 0.3 0.4 0.5.
Loading rate, εa (%/min)In order to show how to calculate strengthparameters under different loading rates, the typicalrelationships between maximum deviator stress(q max ) and mean effective principal stress (p') are
shown in Fig. 8. Here, Eq. (1) was employed to
calculate mean effective principal stress (p') insaturated and air-dried soils, where the effective
stress plays a main role for saturated condition andthe pore water pressure (u w ) is equal to zero in airdried condition [12].

0.6Maximum deviator stresses related todifferent loading rate of all the tests.

specimens with higher loading rate are prone todilation instead of compression. That is because thetime for rearranging soil particle reduces, and thenamount of particle compression decreases due toshort of time. Therefore, the specimens are
inclinable to expand. The same result is shown inreference [8] that higher strain rates induce volume
change that are slightly less compressive than that inlower tests. These small amounts of volumetriccompression changes make the specimens appear
more dilation.
In case of unsaturated condition of σ c ' of 34.5kPa
as shown in the Fig. 6(b), the trend is consistent withthose of the air-dried specimens, and specimen withhigher loading rate exhibits more dilation thanspecimen with lower loading. However, opposite
regulation obtained under σ c ' of 68.9kPa that thelarger loading rate is, the smaller the peak strength isas shown in Fig.7. Since the two different trends
discussed above are not satisfactory for each other, it
would be desirable to redo unsaturated tests withloading rate of 0.5%/min under σ c ' of 68.9kPa in thenear future.
Saturated condition of σ c ' of 68.9kPa are shownin Fig. 5(c), which shows specimen with higher
loading rate has related higher peak strength. The
reason for such phenomenon is associated with thevolume change. The volume change with higher
loading rate appears to be slightly less compressive
while more dilated than that of slower loading rate.
As for Fig. 6(c), it expresses that peak strength ofhigher loading rate is smaller than that of lower one.
That is because the specimen with higher loading
rate shows more compression during shearing.
Except loading rate, S r related with suction also
has a deep effect on strength characteristic of C-40.
As shown in Fig.7, with increase in S r , the peakstrength is decreasing, except the unsaturated testwith loading rate of 0.5%/min under σ c ' of 68.9kPa.
The same result was obtained for rockfills by Kohgo[9]. Based on the reference [10], the resistance ofsoil to plastic deformation is strongly influenced by1
p ' = (σ a + 2σ c ) − u w
3(1)

Based on Fig. 8, the failure envelope can beplotted by linear fitting curve. Then friction
coefficient, internal friction angle, and cohesion are
expressed as Eq. (2), and Eq. (3) as in [12].
M =

qmax
6 sin φ=P
3 − sin φ

(2)

c=b

3 − sin φ
6 cos φ(3)

qmax (kPa)

Where, M represents friction coefficient, φ isinternal friction angle, c signifies cohesion, and b isintersection of fitting curve on the vertical axis.

Fig. 8

900
800
700
600
500
400
300
200
100
0
0

.

εa=0.05%/min.

εa=0.5%/min

C-40, Air-dried, Dc=95%

100

200
P' (kPa)

300

400

Failure envelopes under air-dried conditionof loading rate of 0.05%/min and 0.5%/min.

The calculated internal friction angles φ andcohesion c under different loading rates are shown in
Table 3. Note, the φ and c in Table 3 were calculated
by adding results under σ c ' of 49kPa. The values of φ355

GEOMATE-Nagoya, Nov.13-15, 2013

under different loading rates are not the same. In airdried and saturated condition, the corresponding φincreases slightly with the increase of loading rates,
which agrees the result obtained by Yamauro and
Lade [8]. While under unsaturated condition theφ reduces with decrease in loading rate, which isdifferent regulation from above mentioned
conditions, and it should be affected by the test
result of unsaturated condition as mentioned
previously. On the other hand, the loading rate is
influential in the c. In air-dried and saturated
conditions, with the increase of loading rate, the cdecreases. While under unsaturated condition, whenincreasing the loading rate, the viscosity resistanceincreases. In conclusion, considering the different
trends of c obtained from various degrees ofsaturation, more tests will be performed in near
future.

apparatus for unsaturated granular base course
materials, in Proc. 2nd In. Conf. on ICTG, 2012,
pp. 534-540.
[3] Mori T, Kamiya K, Chiba T, Uzuoka R andKazama M, The functional model of the soilwater characteristic curve used the logistic
function during cyclic shearing, in Proc. 44th
Japan national Conf. geotechnical engineering,
2009, pp. 1519-1520(in Japanese).
[4] Ishikawa T, Kawabata S, Kameyama S, Abe R
and Ono T, Effects of freeze-thawing on
mechanical behavior of granular base in cold
regions, in Proc. 2nd In. Conf. on ICTG, 2012,
pp. 118-124.
[5] Kato S and Kawai K, Deformation
characteristics of a compacted clay in collapse
under isotropic and triaxial stress state, Soils
and foundations, Vol. 40, No. 5, 2000, pp. 7590.
[6] Maina JW, and Matsui K, Developing softwarefor elastic analysis of pavement structure
responses to vertical and horizontal surface
loading, Transportation Research Record, No.
1896, 2004, pp. 107-118.
[7] American Association of State Highway andTransportation Officials, Standard method oftest for determining the resilient modulus ofsoils and aggregate materials (T 307-99), 2007,
pp. T 307-1-T 307-42.
[8] Yamamuro JA and Lade PV, Effects of strain
rate on instability of granular soils,
Geotechnical testing journal, 1993, Vol. 16, No.
3, pp. 304-313.
[9] Kohgo Y, Asano I and Hayashida Y,
Mechanical properties of unsaturated low
quality rockfills, Soils and Foundations, 2007,
Vol. 47, No. 5, pp. 947-959.
[10] Kohgo Y, Nakano M and Miyazaki T,
Theoretical aspects of constitutive modellingfor unsaturated soils, Soils and Foundations,
1993, Vol. 33, No. 4, pp. 49-63.
[11] Kohgo Y, Asano I and Hayashida Y, An
elastoplastic model for unsaturated rockfills andits simulations of laboratory tests, Soils andFoundations, 2007, Vol. 47, No. 5, pp. 919-929.
[12] Nishimura T, Toyota H and Waguri M,
Influence of high soil on angle of internal
friction and cohesion for a statically compacted
non plastic silty soil, Japanese Geotechnical
Journal, 2008, Vol. 3, No. 4, pp. 321-329(inJapanese).

Table 3 The strength parameters.

Air-dried
UnsatuatedSaturatedεa(%/min)
0.05
0.5
0.05
0.5
0.05
0.5

M

φ

2.07
2.15
2.15
1.80
2.21
2.30

(o)
50.21
52.23
52.42
43.71
53.73
56.10

c
(kPa)
23.50
19.88
6.95
27.90
2.36
1.25

CONCLUSION
The following findings were obtained from thepresent study:(1) Loading rate has strongly impact on shear
behavior of granular base course material.
Especially in air-dried condition, the shear
strength of base course material increases with
the increase in loading rate, and also specimens
with higher loading rate are prone to dilation
instead of compression.
(2) Under air-dried and saturated conditions,internal friction angle slightly increases withincrease in loading rate, while the cohesion
decreases with the increase of loading rate.
REFERENCES[1] Nishimura T, Koseki J, Fredlund DG and
RahardjoH,
Microporous
membranetechnology for measurement of soil-water
characteristic curve, Geotechnical Testing
Journal, Vol. 35, No. 1, 2012, pp. 61-77.
[2] Ishikawa T, Zhang Y, Segawa H, Miura S andTokoro T, Development of medium-size triaxial
356

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EXPERIMENTAL STUDY OF PLYWOOD COMPARING TO FOAMFILLED HONEYCOMB STRUCTURE
Phacharaporn Bunyawanichakul, Chattarin Sunsin, and Thammakorn Sasanawin
Department of Aerospace Engineering, Faculty of Engineering, Kasetsart University, Thailand

ABSTRACTIn the current study, results of an experimental analysis of plywood panel used in Thailand for construction
purposes are presented comparing to sandwich panel composed of two plywood sheets separated by a kraft paper
core whose cells were filled with two different types of foam. The honeycomb core was initially formed inhexagonal shape. Flexural properties were determined according to the guidelines specified by the Thai
Industrial Standard No.876-2547 for flat pressed particleboards (TIS No. 876-2547). The plywood samples were25.4 mm x 350 mm, two-ply and five-ply, 6 mm and 15 mm thick. They were fabricated both face grain paralleland perpendicular to span direction to test in order to indentify flexural stiffness, flexural strength, shear
stiffness, and shear strength. The sandwich beam samples were fabricated by filling PU and PVC foam into eachcells of the core. The failure mechanism of each sample was observed and it was found that the sample failures
were identical for the same type of specimen. The experimental result in this study will be implemented in amodel that can be used to observe the correlation between the flexural strength and stiffness of plywood andfoam filled honeycomb structure.
Keywords: Plywood, Honeycomb, Flexural properties, Shear properties, FailureThis paper focuses on commercial plywood typewhich uses tropical wood for fabrication and has low
price as shown in Table 1. In the market, plywood
panel has standard size about 1.22 m x 2.44 m withavailable thickness range from 3 mm to 20 mm. Not
all thicknesses are readily available. Plywood panel
having thickness of 3 mm is selected in this study.
The panel is constructed of small pieces of wood
united under pressure and temperature by a bonding
agent. The face and back plies are also covered bytropical wood sheet and have the grain direction
oriented parallel to the long dimension of the panel.
It is usually found in indoor application and canmake more benefits in case of knowing structurallimitation.
Additionally, in recognition of required
mechanical properties for each plywood panel, it isvery interesting to compare their strength when thepanel is separated by other lightweight materials,
called sandwich structure. This type of structure
consists of two thin but stiff face sheets attached to alightweight thick core as shown in Fig.1. The core
supports shear load and increases flexural stiffness
and strength to the overall structure.

INTRODUCTION
In Thailand, plywood panels are widely used inconstruction, furniture, interior decoration, andflooring purpose. Market survey shows several
plywood products in common trade name, such as
black coated plywood, natural teak plywood,
engineered teak plywood, commercial plywood,
Medium-Density Fiberboard (MDF), Particleboard
or chipboard, Oriented Strand Board (OSB), andothers. All plywood panels as mentioned use
different type of wood species to fabricate. It is hard
to classify following any standard as shown in [1]because we use tropical wood to be basic sheet to
manufacture. From the list of common trade name of
plywood in Thailand, the plywood type covered bythis paper is classified by type of cover sheet and by
price without specific structural meaning as follows:
Table 1 List of plywood in Thailand
Plywood typeBlack coated
Natural teakEngineered teakCommercial
MDF/ Particleboard
or Chipboard
OSB/others

Cover sheet
synthetic
teak
synthetic
tropical wood

Price
high*
mediummediumlow

synthetic

vary

Importedwood

mediumFig. 1*reusable 5-8 times.
357

Schematic of honeycomb structure. [2]GEOMATE-Nagoya, Nov.13-15, 2013

The flexural stiffness and strength efficiency of
sandwich panel are illustratively compared to solid
plate in Fig.2. Solid plate is split at the middle of its
thickness then inserted by a typical core material
having the same thickness as solid plate and double.
The result is two more sandwich panel with 2 and 4
times of the total thickness. Two new panels presentvery good flexural stiffness and strength. By
doubling the thickness of the core material, theflexural strength is increased by 3.5 with only 3
percent of additional weight while 9.2 is the flexuralstrength number for tripling the thickness of the corematerial. The maximum core thickness panel gives
sandwich structure having 37 times of flexural
stiffness while only 6 percent of weight increasing isobserved.

RELATED THEORY
The typical sandwich beam theory is used in thispaper to calculate the deflection of sandwich beam.
Consider a simply supported sandwich beam of spanl and width b loaded in three-point bending with acentral load P as illustrated in Fig.3.

Fig. 3

Beam with central load and simple supportcondition. [3]The beam deflection or vertical displacement of
the beam is induced by bending and shear withassumption of perfect bonding of the whole panel,and it can be obtained from the equation:
Fig. 2Comparison of solid and sandwich beam interms of weight, flexural stiffness, andstrength. [3]

δ=

2Pl3
2

+

48Ests h b

In this study, commercial plywood is used as
face sheets. Porous materials, e.g., foam, paper ormetallic formed in different shape, are commonlyused for core material. More details on the various
core materials are demonstrated in [4-7]. Basically,foam is the most famous to be selected as corematerial in general application because of its variety
and continuity in macroscopic scale. However, inhigh performance application, Nomex core or
Rohacell or honeycomb as shown in Fig.1 arewidely used due to high strength to weight ratio.
This paper will investigate the combination of foam
and honeycomb as core material. Sandwich panels
which the cell were filled by foam are studied inorder to expanded requirements for construction andindustrial uses.
Survey on the selection of the core material is in
this paragraph. Many core materials were listed frommarket place in Thailand. Kraft paper in hexagonal
shape, polyurethane (PU), and Polyvinyl chloride
foam (PVC) have light weight and suit to be selected
for sandwich panel construction due to ease of
fabrication and cost. The benefits of PU foam areused to prevent heat, cold, acid, and alkali. PU foam
has usually lightweight and strong. The benefits of
the PVC foam are lightweight, weather-resistant,heat and sound insulation, and excellent protection
against chemicals substances.

Pl

(1)

4bhGc

where δ = Mean deflection of the beam
Es = In-plane Young’s moduli of the skints = Skin thickness
h = Beam thickness
Gc = Out-of-plane shear modulus of the core
The beam deflection depends on someparameters of sandwich beam material properties in
Eq. (1), for example, Es and Gc. The first unknown
properties can be obtained by a variety of reports
conducted by three-point bending test of plywood
panel with a simply supported beam of span l loadedwith a central load P. The beam will be deformed
under the effect of bending moment and shear force
controlled by support distance. The longer support
distance gives lower effect of shear force. Therefore,
the deflection of beam in classical beam theory canbe calculated as;
3

Pl
Pl
∆=
+
48EI AG
where ∆ = Mean deflection of the beam
E = Young’s moduli of beam material
I = Moment of Inertia
A = Cross-sectional area of the beam
G = Shear modulus of beam material
358

(2)

GEOMATE-Nagoya, Nov.13-15, 2013

From Eq. (2), the longer number of support spanmakes more effects on the beam deflection by the
first term. In contrast, if the beam is short, thesecond term in Eq. (2) will play more important role.

The following study is focused on comparing theflexural stiffness of sandwich beam. The dimensionof all specimens is 25.4 mm x 350 mm. Four typesof sample were fabricated based on the same
effective thickness of 15 mm. The 15 mm thickspecimens are:

PLYWOOD PROPERTIES INVESTIGATION
Many of the questions that arise with plywood
application have to do with mechanical properties of
plywood, especially properties of plywood in
Thailand compare with those of plywood in othercountry. The mechanical property data
waspresented in many reports show a wide range of theproperties [8] occurred in the manufacturing of
plywood and correspondingly changes in design
information. There are several standard test methods
for evaluation of the basic properties of plywood, forexample, Young’s modulus, modulus of rigidity, andstrength properties. The procedure to determine
Young’s modulus is described in TIS No. 876-2547
which the flexural stiffness of the board can becalculated from test (Fig.4).

1)
2)

3)

4)

LO: 5-ply of plywood with [L/T/L/T/L]
orientation (see in Fig. 6)
4SLOT: Sandwich beam consists of a
Nomex honeycomb core with a cell sizeof 12.5 mm and a density of 270 kg/m3.
The skin is 3-mm thick plywood panel
with outer face orientation parallel tobeam axis (see in Fig. 7)
PU: 4SLOT sandwich beam filled thehoneycomb cells with PU foam (see in
Fig. 7)
PVC: 4SLOT sandwich beam filled thehoneycomb cells with PVC foam (see in
Fig. 7)
Load

Fabrication: L300, T300
Upper plateLO

3-point bending test
slope × l ;long beam
48 I
3

E=

Lower plate

Results: E
Fig. 6
Fig. 4Fabrication of the LO specimen.

Diagram for plywood testing procedure.

Specimen manufacturing
One test piece was cut from 3-mm thick plywood
panel in two different directions of the grain of outerlayer: parallel and perpendicular to the longitudinal
axis of the specimen. Both layers were bonded
together under pressure forming specimen with total
thickness of 6 mm indicated by L300 and T300 (Fig.
5). ‘L’ and ‘T’ denote the outer face ply of specimen
in longitudinal and transverse direction respectively.
The test specimens measured 350-mm in length,25.4-mm in width, and the distance between the
supports was 300-mm as indicated by following
number ‘300’. Three specimens of each type are
manufactured to investigate flexural stiffness by
experiment.

4SLOT
Fig. 7

Typical photograph of 4SLOT, PU, and
PVC specimen before attaching upper skin.

The modulus of rigidity, load at yield, and load
at peak of these specimen configurations are to beinvestigated. The bending tests were conducted on a
Testometric MICRO 500 50 kN universal testingmachine. Samples were installed in the compression
zone of test unit between the support base of 300
mm and the thrust punch at its central point.
Regardless of dynamic response of the beam, only
one cross-head speed was done. The test is
performed under quasi-static condition with crosshead speed of 0.5 mm/min. The data acquisition
system which was linked with the Testometricmachine was used to record all the necessary results

T300

Lower plate
Fig. 5

PVC

Testing procedures of the 15-mm thick specimen

Load
Upper plate L300

PU

Fabrication of L300 and T300 specimen.
359

GEOMATE-Nagoya, Nov.13-15, 2013

including the maximum load or load at peak,average load, vertical displacement or deflection,andusefulrelatedmechanicalproperties.
Photograph of PU and PVC specimen are illustrated
in Fig. 8. During the test, sample failure behaviors
were observed and recorded to identify the loss of
linear proportion of the load-deflection curve.

Fig. 8PU and PVC specimen.

RESULTS AND DISCUSSIONS

head moves down as shown in Fig. 10 while thedeflection of the L300 specimen is limited at 15-25
mm by a total rupture at static peak load.
As observed in Fig. 9, a slight drop of the load
level applied to the L300 specimen is appeared
about 150-160 N, then the upper and lower skin start
to crack until reaching the maximum load-carrying
capacity of the sample in bending at about 35-45
percent of peak load as shown in Table 2. To
investigate failure behavior from the first to final
damage for both specimens, the glue-bonding
between plies was in good condition. Fig. 10 shows
the L300 specimen at break and T300 one at stopthat no slipping between the layers is found. Onlysome noises were observed after the first damage
indicated by a slight loss of slope was reached asshown Fig. 9. The total failure of L300 specimen canbe seen by a sudden drop caused by the outer facegrain’s fiber breaking of its upper and lower faceskin which the highest flexural stress is basicallyoccurred.

Two-ply Specimen
Load-deflection curves of representative 2-ply
specimens in the bending test are illustrated in Fig. 9,
showing the flexural stiffness of the L300 and T300
specimens in different value with a high level of
reproducibility for each sample type. The flexural
stiffness is higher for the samples having face grain
parallel to span direction with 5.77-6.29 GPa,
compared to 1.3-1.88 GPa of T300 (see in Table 2).
Compared to few studies in [9] and information
about a variation of these properties, the Modulus ofelasticity of plywood is 6.96-8.55 GPa. The results
obtained by tropical wood-based plywood in
Thailand as shown by L300 bending test are slightly
less than international product which is probably
caused by temperature and moisture content.

(a) L300 test(b) T300 test

Fig. 10 Photographs of (a) L300 specimen at breakand (b) T300 specimen at stop.
Comparison of the first damage of both
specimens, it is found that L300 can carry higher
load at yield at approximately 2 times. So thestrength shall be about 2 times as well by using thesame rectangular size in cross section. The same
effect is occurred in case of the ultimate load asshown by load at peak in Table 2.
Table 2 Elastic modulus, load at yield, and peakload of the L300 and T300 specimens.

Fig. 9Load-deflection curve of 2-ply specimen.

The failure scenario is also investigated during
the test. It is obvious that the T300 specimen is very
flexible and can be deflected as much as the cross-

Sampletype
L300-1
L300-2
L300-3

E
(GPa)
6.21
5.77
6.29

T300-1
T300-2
T300-3

1.72
1.30
1.88

Load (N)@yield
@peak
150
250
160
250
160
210
60
55
80

150
125
115

There is more information about failure scenario
for 2-ply sample of two different orientation angles.
The load-deflection curves of L300 sample isobviously illustrated into two main parts: the elastic
360

GEOMATE-Nagoya, Nov.13-15, 2013and plastic zone. The first zone represents thelinearity of the curve, whereby the sample deformed
as a part of circle regardless of shearing effects. The
second zone show plastic behavior of the sample,
whereby the sample is still intact until the lowest
point touched the machine base about 70 mm so thetest was stopped. No catastrophic failure appears to
T300 sample after removing the load. This would be
advantage of T300 to be good performance inenergy absorption.
Fifteen-mm thick Specimen
As previous mentioned, four types of specimens
under flexural test are performed as follows:
LO samples
The load-deflection response of three LO
samples is shown in Fig. 11. At the start, all the LO
specimens were pressed at the mid-point of the
supports. The load increased with displacement
linearly up to the first damage at a variation of loadfrom 400 to 520 N (see in Table 3). The flexural
stiffness of all the specimens was found by thislinearity to be the same, which is not surprisingsince it is determined by the intrinsic material
properties. After the first damage, a slight increasingof load was applied till the first drop was occurred.
Three tested specimens had different response after
the drop. Two-third could be recovered as seen in
additional exerted load. However, an increasing load
after the first drop was less than the first peak andsamples were broken. The maximum load is 620760 N. With respect to the sheared surface A, thisresults in a shear strength of 1.63-1.99 MPa:

τ =

620 N
Pmax
= 1.63 MPa=
A
25.4 mm ⋅15 mm(3)

The shear strength properties vary because ofdifferent failure modes corresponding to crack
between layers and outer skin fiber breaking.

Fig. 11 Load-deflection curve of the LO specimen.

Table 3 Weight, shear modulus, load at yield, andpeak load of the 15-mm thick specimens.
Weight*
(g)

G
(MPa)

LO-1
158.5
LO-2
LO-3
4SLOT-1
87
4SLOT-2
4SLOT-3
PU-1
95
PU-2
PU-3
PVC-1
100
PVC-2
PVC-3
*average value

24.24
27.44
17.18
11.59
28.28
21.97
8.72
8.68
5.45
7.78
5.56
5.17

Sampletype

Load (N)@yield @peak
400
520
440
97
153
157
99
93
55
55
60
80

620
760
700
161
187
174
154
190
150
125
150
115

4SLOT samples
Three load-deflection curves of 15-mm thick
4SLOT samples are almost congruent for the elastic
regime until the first failure occurs as illustrated inFig. 12. From experimental results, two specimensshow the load has two peaks. The second peak ishigher than the first peak. Load level is gradually
increased after the first drop except one specimen.
However, the second slope seems to coincide for all
specimens testing results. It corresponds to failure of
the bonding between skin and core as observed
during the test. The separation started from the end
and grew to the centre of the sample. At this point,skins and core individually work to resist thebending. Sudden and dramatic drop occurs
indicating an outer face rupture which visuallyappears during the test. Shear strength which is
calculated by Eq. (3) yields 0.44-0.46 MPa. The
deflection reaches a large amount at breaking point.

Fig. 12 Load-deflection
samples.

361

curve

of

the

4SLOT

GEOMATE-Nagoya, Nov.13-15, 2013

4SLOT, PU, and PVC samples
Fig. 13 shows three curves obtained from one ofeach type of sandwich beam specimen. The trend of
PU and PVC specimen was found to be similar to
the 4SLOT sample. There were crack growth fromthe edge to the center of sample during a constantforce level from the deflection of 3-35 mm.
Photograph of PU specimen when the maximum
load was reached are illustrated in Fig. 14. The
flexural stiffness of all three types are close eachother. Shear strength which is calculated by Eq. (3)yields 0.3-0.4 MPa. The filled foam specimen has
shear strength less than the sample without foam
filling. This drop is observed by many defects frommanufacturing processes. The slipping is occurredby imperfect bonding between skin and core.

From a summary bar chart in Fig. 15, the height ofthe bar shows comparison of load at yield, load atpeak, shear modulus, and weight based on LO
specimen. For sandwich sample, the two first terms
is relatively low with the imperfect bonding during
manufacturing processes.
CONCLUSION
The modulus of elasticity of tropical wood-based
plywood in Thailand is identified with slightly lessvalue than international standard plywood. These
properties can be useful for Thailand constructionindustry. The development of a finite element
modeling will be validated by implementation of theflexural properties obtained from testing results.
Manufacturing processes and environmental control
is needed for specimen fabrication. The bonding
plays very important role to increase strength of thesample.
REFERENCES

Fig. 13 Comparison of load-deflection curve inexperiment for 4SLOT, PU, and PVC
samples.

Fig. 14 Load at peak of PU specimen testing.

Fig. 15 Bar chart of the 15-mm thick samples test.

[1] ASM Handbook: Composites Vol. 21. Ohio:
ASM International, 2001.
[2]
Voluntary
Product
Standard:
PS1-95Construction
andIndustrial
Plywood.
Washington: APA-The Engineered Wood
Association, 2002, sec. 4.
[3] Hexcel composites, “HexWebTM Honeycomb
sandwich design technology”, 2000.
[4] Bitzer T, “Honeycomb Technology: Materials,
Design, Manufacturing, Applications andTesting”, Chapman & Hall, 1997.
[5] Zenkert D, “The Handbook of Sandwich
Construction”, EMAS/Engineering Materials
Advisory Services Ltd., 1997.
[6] Strong AB, “Fundamentals of Composites
Manufacturing: Materials, Methods andApplications”, 2nd ed., SME/Society of
Manufacturing Engineers, 2008.
[7] Marshall AC, “Lightweight Structural Cores,
ASM
Handbook:
Composites”,
ASM
International, 2001. Composite Basics, Marshall
Consulting Publishing, 7th ed., Vol. 21, 2005,
pp. 180-183.
[8] Biblis EJ, “Effect of weathering on surface
quality and structural properties of six
species of untreated commercial plywood siding
after 6 years of exposure in Alabama”, Forest
Products Journal, Vol. 50, 2000, pp. 47–50.
[9] Cai Z and RJ Ross, “Wood Handbook, Chapter
12: Mechanical Properties of Wood-BasedComposite Materials”, General Technical
Report FPL-GTR-190, Madison, WI: U.S.
Department of Agriculture, Forest Service,
Forest Products Laboratory, 2010, pp. 12-1-1212.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

X-RAY IMAGE ANALYSIS OF POROSITY OF POROUS CONCRETES
Jaehun Ahn1, Jinwoo Jung2 and Seungbae Kim3
Faculty, Pusan National University, Korea; 2,3Student, Pusan National University, Korea

1

ABSTRACTThe use of permeable pavement is one of most promising tools to control runoff and water quality, therefore
enabling low impact development, along with several other benefits. The porosity of the permeable pavement is
the most important property of the pavement in current state of the practice. In this article, the porosity of aporous concrete sample made in laboratory was evaluated by two approaches: measuring weights and X-ray
image analysis. Two different X-ray equipment, 2D and 3D, were used to construct cross-sectional planar
images of a cylindrical porous concrete sample. It was found that the porosity estimate from 2D X-ray was close
to the results with measuring weights, but that of 3D X-ray was rather larger. The difference in porosity (notratio) from 2D X-ray and weight measurement was about 2%, but the differences from 3D X-ray and weightabout 9%. The observed trend corresponds to the authors past experience with field core sample.
Keywords: Porosity, Porous Concrete, Permeable Pavement, Green Infrastructure, Low Impact Development

A porous concrete sample with 4.8-cm diameterand 8.5-cm length was made in laboratory as shownin Fig. 1. The crushed stone was used for aggregatesof the concrete sample. Before mixing, the crashedstone was screened to be in 1.18 ~ 2 mm range, andwashed 3 times with water. Portaland cement wasused as a binding material; the mixture proportion isshown in Table 1.

INTRODUCTION
In urban area, many traffic infrastructures suchas highways, parking lots, sidewalks, and smallroads (say, for bike) are paved, and therefore
impervious, which adversely affect the stormwater
management as these infrastructures generally
replace natural permeable greens or at least soils
with impervious paved surface. In addition to theeffective control of runoff, the pervious pavement
are told to have more benefits such as skid
resistance, water quality control, noise control, andsurface temperature decrease.
The concept of pervious pavement is, though, notvery new but some of early pervious pavements
have been a couple of decades, and there are some
but no unified design guides available (NRMCA,
2004; Paul et al., 2004; John et al., 2009; ACI, 2008;
ACI, 2010). In current state of the practice, the mostimportant property of pavement material is theporosity, the ratio of the volume of internal pore andthe gross (total) volume of the pavement.
Montes et al. (2005) used the submerged weightof the pervious concrete for porosity estimation, andNeithalath et al. (2006) the difference of saturated
and drained weights of the concrete. There are alsostudies that utilize the X-ray image to identify thepore in porous materials: concrete, asphalt, andgeotechnical materials (Jung et al., 2011; Kim et al.,2012; Kang et al., 2012).
This paper presents the preliminary results on theestimation of the porosity of a laboratory porous
concrete sample using X-ray images.

Fig. 1 Porous concrete sample
Table 1 Mixture proportion
Weight per volume
Material(kg/m3)Aggregate
1,590
Cement
477
Water
183
Total
2,250

Content (%)
70.7
21.2
8.13
100.0

Montes et al. (2005) used the submerged weightof the pervious concrete for the porosity estimation.
In this paper, the porosity estimation was made

POROUS CONCRETE

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GEOMATE-Nagoya, Nov.13-15, 2013

following the work of Montes et al. (2005). The
porosity P of porous concrete can be estimatedbased on the following equation.
𝑷𝑷 = 𝟏𝟏 −�𝑾𝑾𝑫𝑫 −𝑾𝑾𝑺𝑺 �
𝜸𝜸𝒘𝒘

𝑽𝑽𝑻𝑻

Table 3 Specifications of 3D X-ray equipment
Item
Description
Manufacturer
X-Tek
Model number
HMK CT – 225
X-ray tube voltage
225Kv
X-ray tube current
1.0mA

(1)

where 𝑾𝑾𝑫𝑫 and 𝑾𝑾𝑺𝑺 are the dry and submerged
weights of the sample, 𝑽𝑽𝑻𝑻 is the total volume andand 𝜸𝜸𝒘𝒘 is the unit weight water.
The submerged weight of the pervious concrete
sample was measured by using the electronic scale
and a wired mesh basket attached shown in Fig. 2.

Fig. 3 presents the planar images from 2D and
3D X-ray equipment. It was found that the image
from 3D X-ray was not clear with more noise thanthat of 2D X-ray. (Noise may be observed better in
Fig. 4.)

Fig. 2 Equipment to measure the submerged weight(a) 2D X-ray

The sample was saturated more than 3 hours
under water to measure 𝑊𝑊𝑆𝑆 . For the measurement of
𝑊𝑊𝐷𝐷 , the saturated sample was drained in the air for
24 hours and assumed that the sample is insaturated-surface-dry condition. The 3-hr saturated
and 24-hr air-drained weights were 147.47g and247.69g, respectively. Given the volume of thesample 153.81 cm3, the porosity was calculated to be
34.8%.
X-RAY IMAGE ANALYSIS
X-ray CT is a powerful tool to look inside thesample of a porous material and analyze the porecharacteristics. Pusan National University has three
X-ray machines with different specifications. In thisstudy, two X-ray equipment (one 2D and one 3D)
with the specifications in Tables 2 and 3 were used
to get the images of the pervious concrete sample.

(b) 3D X-ray
Fig. 3 Planar images from X-ray equipment
For image processing and estimation of theporosity, the image inside the sample was first
cropped. Given cross-sectional images were 16-bit
grayscale, which means that 216 = 65536 gray levels
can be used to represent different shades of grayfrom black (gray level = 0) to white (gray level =65535). To distinguish the pore (dark) from the solid(bright), the cropped images were converted toTable 2 Specifications of 2D X-ray equipment
Item
Description
Manufacturer
X-Tek
Model number
VENLO450-ACTIS
X-ray tube voltage
450 kV
X-ray tube current
4.8𝐦𝐦𝐦𝐦364

GEOMATE-Nagoya, Nov.13-15, 2013

purely black and white image by taking the limit ofblack and white based on the Otsu’s method (Otsu,
1979) implemented in MATLAB Image Processing
Toolbox (MathWorks, 2011). Based on black andwhite images in Fig. 4, the numbers of black andwhite pixels were counted; the number of black
pixels over the total pixels makes the porosity.
The results of porosity estimates are presented inFig. 5 with respect to the depth of the sample. The
averages of the porosities from 2D and 3D X-ray
equipment are 37.9% and 44.2%, respectively. It isnoted that the result of 2D equipment is closer to theporosity measured using submerged weight 34.8%.
This trend corresponds to authors’ experience withanother sample (field core). In case of field core, theporosity from weights was 29.9%; the results from
2D and 3D X-rays were 30.9 and 35.2, respectively.

(a) 2D X-ray(b) 3D X-ray
Fig. 5 Porosity with depth
DISCUSSION
There are several sources to make scatters in theporosity values based on both weight measurement
and X-ray image analysis. In evaluating the porosity
from Eq. (1), the sample should be completely
saturated when the submerged weight is measured.
The weight of drained or dried solid sample can also
differ corresponding to how it was drained or dried.
As of X-ray image analysis, first concern is to takeX-ray image of the sample under proper setup, thatis tube voltage and current, which may determine thequality of the image. Then, proper image processing
should be done to filter out noise and scatters, which
was conducted by commercial software VGStudio(2004) in this paper. The limit of black and white,which is void and solid, should be properly made,and in fact there is no real proof that the limit value
based on Ostu’s method (Otsu, 1979) is correct. The
fact that the results of Eq. (1) and 2D X-ray image
are close may sooth this argument, but does not clear
out. But still the X-ray image analysis will be auseful tool inspecting pore spaces of the pervious
pavement; for example, Kayhanian et al. (2012) wasable to successfully inspect the degradation of theporosity of the permeable concrete pavement due toclogging.

(a) 2D X-ray(b) 3D X-ray
Fig. 4 Black and white images

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GEOMATE-Nagoya, Nov.13-15, 2013

in Portland cement pervious concrete, Journal of
ASTM International, 6(9)[4] Jung, Y.J. and Yun, T.S. (2011) Quantificationof 3D pore structure in glass bend using micro
X-Ray CT, KGS collection of dissertations,27(11), 83-92.
[5] Kang, D.H., Yun, T.S., and Kim, K.Y. (2012)
Image processing techniques relevant togeomaterials, Advances in civil, environmental,
and Materials research, ACEM’12(August 2630)[6] Kayhanian, M., Anderson, D., Harvey, J.T.,
Jones, D. and Muhunthan, Balasingam. (2012)
Permeability measurement and scan imaging toassess clogging of pervious concrete pavementsin parking lots. Journal of Environmental
management, 95(2012), 114-123[7] MathWorks. (2011) MATLAB R2011b,
http://www.mathworks.co.kr.
[8] Montes, F., Valavala, S. and Haselbach, M.L.
(2005) A New test method for porosity
measurements of portland cement pervious
concrete, Journal of ASTM International,
January 2005, 2(1).
[9] Neithalath, N., Weiss, J. and Olek, J. (2006)
Characterizing enhanced porosity concrete
using electrical impedance to predict acoustic
and hydraulic performance, Elsevier cement andconcrete research, 36 (2006), 2074-2085.
[10] Otsu, N., "A Threshold Selection Method from
Gray-Level Histograms," IEEE Transactions on
Systems, Man, and Cybernetics, 9(1), 1979, 6266.
[11] Paul, D.T., Michael, L.L. and David, J.A.
(2004) Pervious concrete pavements, Portland
Cement Association, Illinois.
[12] VGStudio MAX (2004) User's Manual Version
1.2

CONCLUSION
The porosity of the porous concrete material was
evaluated by measuring weights and analyzing
images from two different X-ray machines in thispaper. The result from 2D X-ray was close to that ofweight measurement; not the case for 3D X-ray. The
averages of the porosities from 2D and 3D X-ray
equipment are 37.9% and 44.2%, respectively. This
trend corresponds to authors’ experience with a fieldcore sample.
In near future, authors plan to investigate theeffect of gradation of aggregate in porous concreteon the pore shape and hydrologic performance ofporous concrete. The saturated and unsaturated
permeability of porous concrete will also be
investigated.
ACKNOWLEDGEMENTS
This work was supported by the National
Research Foundation of Korea (NRF) grant fundedby the Korea government (MEST) through the MidCareer Researcher Program (2012-047702) and the
Human Resource Training Project for Regional
Innovation (2011-07-Univ-04-034).
REFERENCES[1] ACI Committee 522.1-08 (2008) Specification
for pervious concrete pavement an ACI standard,
American concrete institute.
[2] ACI Committee 522R-10 (2010) Report on
pervious concrete, American concrete institute.
[3] John, T.K., Wang, K. and Vernon, R.S. (2009)
Test methods for characterizing air void systems

366

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3252

STRESS - STRAIN BEHAVIOUR OF SLAG CEMENT CONCRETE
Mustapha BOUKENDAKDJI
College of Engineering, University of Hail, Saudi Arabia

ABSTRACTThe paper describes the results of test carried out on OPC concrete and slag cement concretes. Ten blendedslag-cement concretes, made with typical slags from four countries (United Kingdom, Belgium, South Africa
and Japan), are compared with a control OPC concrete. The slags replaced 30 to 70% of cement by mass. The
bobbin shaped specimens were used in the direct tension test and 300x150 mm dia. cylindrical specimens wereused in the axial and lateral strain tests. Poisson's ratio in compression was determined as the ratio of the lateral
to axial strain at the ages of 14 and 84 days. Concretes at the age 84 days exhibits more linearity than at the ageof 14 days and slag concrete becomes more brittle when stored in the dry environment. There was no difference
between the Poisson's ratio of slag and OPC concretes.
Keywords: Slags, Stress-strain, Compression, Tension, Poisson's ratio

aggregate. Slags were obtained from the U.K.,
Belgium, Japan and South Africa. Chemical analysis
and physical properties are given in Table 1.

INTRODUCTION
The main objective of this investigation was tostudy the stress-strain of concrete containing
different slags as a cement replacement incompression and tension.
From typical stress-strain curves for aggregates,
hydrated cement paste, and concrete loaded inuniaxial compression, relative to aggregate andcement paste, concrete is really not a linear elastic
material. The deformation of concrete under a shortterm loading has been shown to be directly related toprogressive internal microcracking at both thecement paste-aggregate interface and through themortar itself [1], [2]. The non-linearity of the stressstrain relation is related to the cumulative effects ofthis cracking. Such microcracking occurs as a resultof differential volume changes between the cement
paste and the aggregate, i.e. due to differences instress-strain behaviour, and in thermal and moisture
movements.
The rate of strength development at early ages isgenerally inversely proportional to the amount ofslag used in the blend because the initial rate ofreaction of slag and water is slower than that of OPC
and water [3]. Brooks and Neville [4] found that the
secant modulus in tension is greater than that incompression and Stutterheim [5] found that forwater-stored specimens Poisson's ratio wassubstantially the same irrespective of the cement
type and ranged between 0.23 and 0.3.

Table 1 Chemical analysis of OPC and slags ('%)

SiO2
Al2O3
Fe2O3
CaO
MgO
MnO
TiO2
Sulphur
Sulphide
SO3
Na2O
K2O
L.O.I
Fineness(m2/kg)

OPC

U.K.
slag

B.
slag

S.A.
slag

J.
slag

20.5
5.79
2.50
65.8
1.25
0.08
0.25
0.97
0.04
2.33
0.28
0.62
1.27
391

36.11
10.84
0.38
40.45
9.46
0.57
0.70
1.22
1.13
0.28
0.32
0.51
1.78
412

33.08
12.93
1.17
39.80
9.79
0.50
0.57
1.13
1.07
0.15
0.40
0.60
0.98
402

38.59
12.94
0.56
35.02
9.40
1.07
0.64
0.89
0.82
0.18
0.22
0.78
0.05
407

32.99
15.20
0.37
42.49
6.22
0.49
0.98
0.83
0.78
0.13
0.24
0.36
0.53
465

Potential compound composition
C3S
C2S
C3A
C4AF
chemicalmodulus

EXPERIMENTAL DETAILSThe materials used to make eleven concretes
were ordinary Portland cement (OPC), groundgranulated blastfurnace slag and quartzitic

62.73
11.59
11.12
7.6
1.68

1.89

1.48

chemical modulus = CaO + MgO + Al 2 O 3
SiO 2
367

1.96

GEOMATE-Nagoya, Nov.13-15, 2013

The first concrete was an OPC control mix
having mass proportions of 1:1.62:2.49 with awater/cement ratio of 0.43 and the cement content
was 437 kg/m3. The ten slag concretes had 30 to
70% of the mass of OPC replaced by equal massesof slags, with the same aggregated proportions andwater/cementitious ratio as the control concrete.
All moulded specimens were cured for 24 hours
under wet hessian, then demoulded and cured inwater for 13 days. Thereafter, the specimens werestored in two storage environments: in water at 20±
2o C;, and in air at 65±5% RH and 20±2o C.
The bobbin shaped specimens were used in the
direct tension test and 300 x 150 mm dia. cylindrical
specimens were used in the axial and lateral strain
tests. The strain gauges used were 60 mm and 30
mm foil electrical resistance and were embedded inboth the bobbin and the cylindrical specimens; the30 mm gauges were used for lateral strain, and the
60 mm gauges for axial strain. The ages of testing
were 14 and 84 days and the average curve of two
specimens was obtained.
Secant modulus of elasticity in compression andtension were obtained at a stress equal to 0.3 of thestrength. Poisson's ratio in compression wasdetermined as the ratio of the lateral to axial strain at
the ages of 14 and 84 days. In addition, for each
mixture, 100 mm cubes were made to determine thecompressive strength

strength, but later-age strengths are similar to, orslightly greater than, the strength of OPC concrete.
For concrete stored dry from the age of 14 days, thestrength was greater than for wet storage. The 300 x
150 mm dia. cylinder strength followed the same
pattern, and the relationship between the twostrengths was similar for both the wet and dry
storage conditions. The mean and standard
deviations of the cylinder to cube strength ratio was
0.82 ± 0.042, which is close to the generally
accepted ratio of 0.80.
Stress-Strain in Compression
Figures 2 to 4 show the stress-strength ratio
plotted against axial and lateral strain as measured
on 150 x 300 mm. cylindrical specimens for OPC,
50% U.K.slag and 50% S.A.slag cement concrete,respectively. It can be seen that the shape of thecurves are similar for OPC and slag concretes. The
maximum variability was ± 6 and ± 25% for the
stress-strain test in axial and lateral, respectively.

TEST RESULTS AND DISCUSSION
Compressive Strength
Figure 1 shows the average influence of
replacement of cement by slag on strength of waterstored concrete.

Fig. 1

Fig. 2Stress-strain curves for OPC concrete incompression.

Fig. 3Stress-strain curves for 50% U.K.slag
concrete in compression.

Average influence of cement replacement
by slag on compressive strength.

The behaviour follows the expected trend in thatan increase of slag content reduces the early-age
368

GEOMATE-Nagoya, Nov.13-15, 2013

because it leads to a higher bond-strength between
aggregate and cement paste, and the curve also
becomes more linear when the stiffness of the matrix
approaches the aggregate stiffness and it is known
that stiffness of the matrix increases with age.
Table 3 Axial strain in compression at limit ofproportionality (L.O.P.) of OPC and slag concretes(Microstrain).
Age (days)
Control Mix
U.K.slagFig. 4

14
84
84 *
440
550
555
30%
785
625
952
50%
672
555
1375
70%
745
932
1350
B.slag
30%
490
602
905
50%
640
930
860
70%
420
560
750
S.A.slag
50%
600
945
917
70%
350
864
1400
J.slag
50%
410
575
950
70%
420
920
1010
* specimens were stored in dry environment after
14-days of water curing and tested dry.

Stress-strain curves for 50% S.A.slag
concrete in compression.

The secant modulus of elasticity, as measured at
a stress-strength ratio of 0.3 is shown in Table 2.
Compared with OPC concrete, the 14-day values ofslag-cement concrete are similar, but the 84-day
strengths are greater. The 84-day modulus of drystored slag-cement concrete was less than for wetstorage by approximately 12%. However, for OPC
dry-stored concrete, the 84-day modulus was 14%
greater than for wet storage.

It seems that while the effect of storing slag
concrete specimens in the dry environment is toincrease the strain at L.O.P., compared with thosestored wet, there was no effect on OPC concrete.
Therefore, it can be concluded that the slag concrete
becomes more brittle when stored in the dry
environment. It is difficult to notice any differences
between the effect of slag types or slag content inview of the scatter.
As the stress-strength ratio versus axial strain
curve becomes asymptotic at failure, it is difficult toassess any value for limiting axial strain. However,comparison can be made on the basis of 95% of
failure stress, i.e. the stress at a stress-strength ratioof 0.95. These values are tabulated in Table 4.

Table 2 Secant modulus of elasticity of water-cured
OPC and slag concretes obtained from 150 x 300
mm cylinders (GPa)Age (days)
Control Mix
U.K.slag

14
84
84 *
31.5
33.9
38.6
30%
27.8
37.1
33.8
50%
29.9
37.3
31.9
70%
27.4
38.6
33.2
B.slag
30%
30.4
35.1
30.9
50%
28.4
39.5
34.5
70%
27.6
35.5
32.3
S.A.slag
50%
30.6
41.6
36.8
70%
32.1
38.4
34.5
J.slag
50%
28.1
41.6
32.6
70%
26.1
35.9
33.7
* specimens were stored in dry environment after
14-days of water curing and tested dry.

Table 4 Axial strain at a stress:strength ratio of 0.95
of OPC and slag concretes (Microstrain).
Age (days)
Control Mix
U.K.slag

14
84
84 *
1750 1930
1850
30% 1950 1510
1780
50% 1900 1680
2065
70% 1745 1642
1915
B.slag30% 1875 1650
2110
50% 1725 1600
1860
70% 1585 1595
1865
S.A.slag
50% 1735 1535
1920
70% 1585 1735
1852
J.slag
50% 1820 1784
2426
70% 1640 18602313
* specimens were stored in dry environment after
14-days of water curing and tested dry.

A comparison of the strain at which the initialsecant modulus decreased by 5% is made. A similar
approach has been adopted previously by Kaplan[6]. The strain measured at this particular point isdefined as the strain at the limit of proportionality(L.O.P.) and the values obtained are tabulated inTable 3. It appears that generally, the strain
increases with age which implies concrete at the age
84 days exhibits more linearity than at the age of 14days. This difference is probably due to the fact thatthe concrete tested at 84 days is stronger; Mindessand Young [7] have stated that stronger concrete
exhibits a more linear stress-strain behaviour
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GEOMATE-Nagoya, Nov.13-15, 2013

The development of direct tensile strength of
OPC and slag-cement concretes is similar to that ofcompressive strength. The results of direct tensile
strength of concrete are listed in Table 6. Unlike thecompressive strength which was about 8% stronger
for dry storage than for wet storage, tensile strength
was stronger for wet storage.

It can be seen that for concrete stored wet andtested at 84 days, the slag concrete has a lower
limiting axial strain than OPC concrete. On the other
hand, for concrete stored dry, the limiting axial
strain was similar or higher in the case of slag
concrete. Also, for any slag concrete mix, the effectof storing concrete dry after 14 days of water-curing
was to increase the limiting axial strain which
implies that dry specimens can withstand higher
axial strain at failure compared with those wet stored
in the case of slag concrete.
A comparison of the limiting lateral strain at astress-strength ratio of 0.95 is given in Table 5 andthere are no apparent differences between OPC andslag concretes at the age of 14 days, the averagevalue being about 560 microstrain. On the other
hand, generally at 84 days, the OPC concrete
exhibited higher limiting lateral strain for both wet
and dry storage conditions which implies moreductile behaviour and the capacity to sustain ahigher stress. This may explain the higher indirect
tensile strength of slag concrete compared to OPC
concrete [8].

Fig. 5 Stress-strain curves for OPC concrete in
tension.

Table 5 Lateral strain at a stress:strength ratio of
0.95 of OPC and slag concretes (Microstrain).
Age (days)
Control Mix
U.K.slagB.slagS.A.slagJ.slag

30%
50%
70%
30%
50%
70%
50%
70%
50%
70%

14
550
540
500
595
462
445
610
505
525
775
650

84
775
372
445
300
500
560
460
497
640
700
670

84 *
887
702
405
510
610
475
475
465
415
750
700

Fig. 6 Stress-strain curves for 50% U.K.slag
concrete in tension.

* specimens were stored in dry environment after
14-days of water curing and tested dry.
Stress-Strain in Tension:
Figures 5 to 7 show the average stress-strain
curves for OPC, 50%UK slag and SA slag concretes
in tension and the maximum variability between two
specimens obtained was ± 14%. It can be seen thatin tension most failures were sudden. This behaviour
could have been due to the fact that failure did notoccur at the centre of the specimens (within thegauge length) and, therefore, strength and strain at
failure may not considered to be representative. For
the case of elastic-pseudo plastic behaviour (Fig. 7),
the tensile strain at failure, for concrete tested at 84
days, was up to about 125 microstrain.

Fig. 7 Stress-strain curves for 50% S.A.slag
concrete in tension.
370

GEOMATE-Nagoya, Nov.13-15, 2013

ratio due to the scatter of the results. Also, there
does not seem to be difference between Poisson's
ratio of slag concrete and OPC concrete, apart fromthe effect of storage environment. Stutterheim [5]found that for water-stored specimens Poisson's ratio
was substantially the same irrespective of the cement
type and ranged between 0.23 to 0.30 at the age of
28 days.

Table 6 Direct tensile strength of OPC and slagcement concrete (MPa).
Age(days)
14
84
84

storageenviro
nment
water
air
water

OPC
mix
2.30
3.13
3.74

50%
U.K.slagconcrete
2.35
3.13
3.72

50%
S.A.slagconcrete
1.54
3.52
3.74

The secant modulus calculated from these curves
are tabulated in Table 7. It can be seen that themodulus increases with age following a similar trend
to that of modulus in compression. The secant
modulus in tension is greater than that incompression because the modulus decreases with anincrease in stress [9] and the modulus in tension ismeasured at a lower stress than that in compression.
This confirms the finding of Brooks and Neville [4]whose explanation for this trend was that, at low
stresses, the stress-strain curve is concave to thestress axis owing to the closing of microcracks and,at high stresses, the stress curve is convex owing tothe opening of microcracks and to creep.

Fig. 8 Poisson's ratio at a stress:strength ratio of 0.3
of water-cured OPC and slag concretes.

Table 7: Secant modulus of water-cured OPC andslag-cement concretes in tension (GPa)Age(days)
14
84
84

storageenviron
ment
water
air
water

OPC
mix
41.3
44.8
46.9

50%
U.K.slagconcrete
37.8
44.1
52.2

CONCLUSION

50%
S.A.slagconcrete
34.8
35.0
42.1

For the range of typical international slags andreplacement levels used in this investigation, acomparison with OPC concrete had led to thefollowing conclusions:
1) An increase of slag content reduces the early-age
strength, but later-age strengths are similar to, orslightly greater than, the strength of OPC concrete
which confirms the conclusion of Boukendakdji[10].
2) The secant modulus of elasticity in compressionof water-stored slag-cement concretes was similar atearly ages, and greater at later ages. However, theopposite trend occurred for mature dry-storedconcrete.
3) Concretes at the age 84 days exhibits more
linearity than at the age of 14 days and slag concrete
becomes more brittle when stored in the dry
environment.
4) The secant modulus in tension is greater than thatin compression5) There was no difference between the Poisson's
ratio of slag and OPC concretes which confirms theconclusion of Stutterheim [5]. However, the values
for specimens stored dry was slightly higher thanthose stored wet for slag concretes.

Poisson's Ratio:
Poisson's ratio at a stress-strength ratio of 0.3
represents the elastic portion of the stress-strain
curve, and is generally used for practical design; thevalues are shown in Fig. 8. For OPC and slag
concretes tested at 14 days, Poisson's ratio ranged
between 0.139 and 0.22 and for slag concretes stored
dry, and at 84 days the range was between 0.122 and0.209. These values for slag concrete are lower thanthose of the same concrete stored in water; the latter
varied between 0.161 and 0.24. This difference ismainly due to the fact that the wet-stored slag
concrete exhibited a higher axial strain than that
stored dry, whilst the lateral strains remained fairly
constant. This confirms the conclusion of Mindessand Young [7] that Poisson's ratio of saturated
concretes lies in the range 0.2 to 0.3, but decreases
to about 0.18 on drying. However, the Poisson's
ratio of OPC concrete stored either in water or dry
are similar (Fig. 8) because the axial strains ofspecimens stored dry or in water are similar. From
the results shown in Fig. 8 it is not easy to see any
effect of slag content or slag type on the Poisson's

ACKNOWLEDGEMENTS
The author wishes to acknowledge the facilities andassistance provided by the University of Hail. The
371

GEOMATE-Nagoya, Nov.13-15, 2013

support of this research program by The Saudi
Binladin Group is gratefully acknowledged as well.

Concrete Institute Journal, Vol.56, April, 1960,
pp.1027-45.
[6] Kaplan, M.F. "Strains at stresses of concrete at
initiation of cracking and near failure" ACI journal,
July 1963, pp.853-78.
[7] Mindess, S. and Young, J.F. Concrete, New
Jersey, Prentice-hall, Inc, Englewood Cliffs, 1981.
[8] Boukendakdji, M , Brooks, J.J. and Waiwright,
P.J. "Strength Development of Concrete with andwithout slag" ConChem International Exhibition and
Conference, Brussels, Belgium, 28-30 Nov. 1995.
[9] Neville, A.M. Properties of concrete, London,
Pitman third edition, 1981.
[10] Boukendakdji O., Kadri E., and Kenai S.
“Effects of granulated blast furnace slag andsuperplasticizer type on the fresh properties andcompressive strength of self-compacting concrete”
Cement and concrete composites, Vol 34, 2012, pp
583-590.

REFERENCES[1] Hsu, T.C. et al. "Microcracking of plain concreteand the shape of the stress-strain curve", American
Concrete Institute Journal, Vol.60 No.2, 1963,
pp.209-223.
[2] Shah, S.P. and Winter, G. "Inelastic behaviourand fracture of concrete", American Concrete
Institute Journal, Vol.63, No.9, 1966, pp.925-930.
[3] Boukendakdji, M. "Mechanical properties andlong-term deformation of slag cement concrete",
PhD thesis, Dept. of Civil Engineering, Universityof Leeds, 1989, 290 pp.
[4] Brooks, J.J. and Neville, A.M. "A comparison of
creep, elasticity and strength of concrete in tension
and in compression" Magazine of Concrete
Research, Vol.29, No.100, 1977, pp.131-41.
[5]. Stutterheim, N. "Properties and uses of high magnesia Portland slag cement concretes" American372

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ESTIMATION AND EXPERIMENTAL STUDYON DIVERSION LENGTH OF CAPILLARY BARRIER
USING CRUSHED SHELL PARTICLES

1,2

Kazunobu Matsumoto1, Kaoru Kobayashi2 , Satoru Nakafusa3 and Toshihiro Morii4
Tobishima Corporation, Japan; 3 Japan Atomic Power Company, Japan; 4 Niigata University, Japan

ABSTRACT
A simple soil layer system which is composed of a finer soil layer underlain by a coarser soil layer provides
an excellent property of capillary barrier. In order to realize the best performance of the capillary barrier function,
it is necessary to make a sharp contrast of soil particle diameter between sand and gravel. The authors found thatan employment of crushed shells instead of gravel in the lower layer greatly reduces transport of the finerparticles in the upper layer into the lower layer, and provides an effective function of capillary barriers. In thisstudy, the diversion lengths are measured in the laboratory soil box tests using crushed shells instead of gravel,and compared those with the estimations calculated by the theoretical equation proposed by Steenhuis et al. In
addition, we compared it with the diversion lengths which were measured in the laboratory soil box tests using asand layer underlain by a gravel layer. As the result, the authors make clearly the applicability of the theoreticalequation proposed by Steenhuis et al. in estimating the diversion length of the capillary barrier.
Keywords: Capillary barrier , Soil water characteristic curve, Diversion length, Crushed shell particles

first, some fundamental properties (grain size and its
distribution) and soil water characteristic curve(SWCC) of crushed shell particles are measured toshow a practical effectiveness of crushed shellparticles in the CB system. Then the diversion
lengths [7] are measured by the laboratory soil box
test, and compared with ones estimated by Steenhuis
et al. [8]. The applicability of the theoreticalequation proposed by Steenhuis et al. [8] inestimating the diversion length of the CB employing
the crushed shell particles instead of gravel.

INTRODUCTION
Capillary barrier (CB) is simply composed of afiner soil (usually sand) layer underlain by a coarser
soil (usually gravel) layer [1]. The CB has been
employed in a top cover of waste landfills to reducewater infiltration into the protected waste materials[2]. The length along which water infiltration isdiverted is limited to some value, because waterflow downward along the interface of CB
accumulates gradually its mass of flow due tocontinuous infiltration from the soil surface, and, atsome length along the interface, water percolates
into the coarser soil layer.
As the CB effect is brought by a sharp contrast inwater retention capacity between the finer andcoarser soils, it is necessary to select a large
difference in the grain size of two soils. But asignificant performance deterioration is concerned
because sand particles may move down into voids ofgravel layer by earthquake or water infiltration foran extremely long duration [3]. To solve thisproblem, Nakafusa et al. [4], [5] and Matsumoto etal. [6] focused on the water retention characteristics
of crushed shell particles, and selected as analternative material for the lower layer soil (gravel)of the CB. They have shown that the movement of
the upper sand into the lower crushed shell particles
can be well prevented because the crushed shellparticles have flat and finer grain size distribution
while maintaining the CB function.
In this study, the performance of CB using thecrushed shells instead of gravel is investigated. At

DIVERSION LENGTH OF THE CB AND
ESTIMATED EQUATIONIn the CB system, water which infiltrates into
soil is suspended just above the interface between
soil layers due to a physical difference in the water
retention characteristics of the finer and coarser soils(Fig. 1). When the interface between soil layers has
an slope as shown schematically in Fig. 1, thesuspended water flows downward along theinterface. This water flow downward along theinterface between soil layers gradually accumulates
its mass of flow due to continuous infiltration fromthe soil surface, and, at some length along theinterface, water percolates vertically into the coarser
soil layer. A horizontal length from the beginning ofwater flow to this percolation (breakthrough) into
the coarser soil layer is called a diversion length [7].
Some theoretical equations have been proposed
to estimate the diversion length of the CB by several
researchers [8]-[10]. Among these, the equation
373

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Result of laboratory soil tests
Terms
densityρsnatural water content
gravel (2～75mm)
sand (0.075～2mm)
silut (0.005～0.075mm)
cray (under 0.005mm)
maximum grain sizeWnuniformity coefficicent

Uc

coefficient of curvature

Uc'

50% grain size

D 50

mm

20% grain size
minimum void ratio

D 20

mm

maxmum void ratio

e max

dry density

ρdsaturated hydraulic conductivity K s

grain size

Fig. 1

Schematic layout of water flow
downward along an interface between
soil layers in the CB system.
proposed by Steenhus et al. [8] is effectively
adaptable [11], [12]. In the case where an infiltration
rate, q, is much smaller than a saturated hydraulicconductivity of sand, K s , the equation of thediversion length, L, is given by

[

]

Ks
tan φ α -1＋(ha－hw )q

100

Percent finer by mass, %

L≤

(1)

where φ is the slope angle of the interface, h a andh w are the air entry value of sand and the water entry
value of gravel, respectively. α is an exponential
constant describing
the relationship between
negative pressure head, h, and unsaturated hydraulicconductivity, K, of sand near saturation:

K = Ksh < ha

；

unit
－
g/cm3
％
％
％
％
％
mm

samples
cruhed shell silica sand no.6

g/cm3

2.671
0.3
55
39
6
0
19.00
14.00
1.48
2.340
0.564
0.763
1.463
1.321

2.701
0.8
53
41
6
0
0.45
1.74
0.938
0.194
0.499
0.672
1.055
1.334

cm/s

1.82×10 -1

1.31×10 -2

0.1
1
10
Soil particle diameter, mm

100

D max

e min

Crusheledshell
Silica sand
no.6

80
60
40
20
0
0.01

Fig. 2Grain size distribution of crushed shellparticles and silica sand employed in the
CB.

(2)

K = K s × exp[− α (h − ha )]h ≥ haIn Eq. (1), q may depend on a thickness of the top
soil layer above the sand as well as rainfall intensityand duration.

Matric suction h, cmH2O

100

PHYSICAL PROPERTIES AND SWCC OF
THE CRUSHED SHELL PARTICLES AND
SAND

Crushed shell(drying process)
Crushed shell(wetting process)gravel (wetting process 1st)
gravel (wetting process 2nd)

80
60
40

hw = nearly equal to 0 cm

20
0
0.0

Materials

0.1
0.2
0.3
0.4
Volumetric moisture content θ, cm3/cm3

0.5(a) Crushed shell

Scallop shell and silica sand no.6, which areavailable widely and easily, were used in the study.
The shell was crushed by a small crusher machine
after washing and being dried for 24 hours in thedrying oven (80 degree Celsius).Table 1 shows theresult of soil test of crushed shell and silica sand.
Grain size distribution curves are given in Fig. 2.
The crushed shell particles have the effective
distribution curves which can prevent the movementof the upper sand into lower crushed shell particles[6].

Matric suction h, cmH2O

100

60

Measured(drying process)Measured(wetting process)Estimated(drying process)Estimated(wetting process)40

ha=13cm80

20
hw=8cm0
0

Fig. 3

Test Method

0.1
0.2
0.3
0.4
Volumetric moisture content θ, cm3／cm30.5(b) Silica sand no.6
SWCC measured by soil column tests
and estimated by using van Genuchten
equation.

crushed shell particles and sand were 1.321 Mg/m3(relative density D r =60 %) and 1.334 Mg/m3(compacted D c =90%), respectively.

The crushed shell particles and the sand werecompacted into a cylindrical specimen, 10 cm indiameter, by using a compact plate. Dry densities of374

GEOMATE-Nagoya, Nov.13-15, 2013

Test Results
Relationships of , h with the volumetric moisture
content, θ, of crushed shell and silica sand no.6 were
measured by a laboratory soil column test, and areplotted in Figs. 3(a) and (b). SWCC are determinedby using van Genuchten equation [13], [14]. For
comparison, in Fig. 3(a), data of gravel (silica sand,
6-8mm in typical diameter) [3] is also plotted.
As shown in Fig. 3(a), the SWCC of crushed
shell during the drying and wetting processes show
only very small air entry value (h a ) and water entry
value (h w ). They are similar to the water entry value(h w is nearly equal 0) of gravel. From this, it may
think from the point of view of soil-water
characteristic that the crushed shells can be well
employed in CB instead of gravel.
As shown in Fig. 3(b), the SWCC of silica sandno.6 during the wetting process locate lower thanthat during the drying process, the SWCC has clear
hysteresis. It is found in Fig. 3(b) that h a is about 13
cm and h w is about 8 cm. Saturated volumetricmoisture content of sand is 0.42 to 0.43.

Fig. 4

Partition walls attached on the bottom of thesoil box. Painted circles show sensors, EC-5, tomeasure soil moisture in the CB.

The infiltration water was supplied on thesurface of upper sand layer by a rainfall simulator(300 cm in length, 20 cm in width and 70 cm inheight) with constant head of water. Emitting
needles (syringe needles), 0.3 mm in an innerdiameter were attached to the base plate of water
reservoir by 50 mm intervals.

Method of Soil Box Test
The crushed shells (D r =60%) were compacted
into the layer of 7.5 cm thickness, then the silica
sand no.6 (D c =90%) were compacted into 20cm
thickness as shown in Fig. 4. After constructing thesoil layers, a gauze sheet was spread over the sandsurface to protect sand erosion due to rainfall droplet.
Soil moisture was measured by the moisture sensor,
EC-5. Fig. 4 shows position and number of the
moisture sensors embedded in the sand layer and thecrushed shell layer. The volumetric moisture content
was measured 1-minute interval.

MEASUREMENT OF DIVERSION LENGTHBY LABORATORY SOIL BOX TEST
Experimental Apparatus of Soil Box Test
Picture 1 shows an acrylic soil box, 300 cm inlength, 20 cm in width and 50 cm in height, with
rainfall simulator built in a steel frame. Water whichpercolated into the lower gravel layer was collectedalong a partition wall 3 cm high attachedtransversely every 10 cm intervals onto the bottom
plate of the soil box as shown in Fig. 4, and led to acollecting beaker through a silicon tube connected to
the lowest position of the side wall of soil box. The
diversion length was determined by observing andmeasuring a volume of water collected into thebeaker along the bottom of soil box.

Test Cases and Conditions
A series of laboratory soil box test shown in
Table 2 was carried out successively by changing
the infiltration rate (rainfall intensity) and by jacking
up the one side of the soil box to obtain the tilting
interface of the CB. In order to examine thereproductiveness of experimental results, test was
repeated under the same conditions.

Rainfall simulator

Table 2 Test cases and conditions
Soil box
Cases of test
Case A
Case B
Case C
Case D
Case E
Case F
Case G
Case H
Case I
Case J
Case K

Beaker to collect percolation into crushed shell layer

Picture 1

Soil box (lower set) and rainfall
simulator (upper set).

375

Finer soil

SilicaSand
no.6

Coaser soil

Crushedshell

Angle ofslope
(Degree)
5.0
5.0
5.0
10.0
10.0
10.0
2.5
10.0
10.0
10.0
10.0

Raifallintensity(mm/h)

Duration
(min)

5
10
20
5
10
20
5
10
20
10
5

1660
1795
1280
534
1501
2356
9975
1957
1098
1330
1430

Volumetric moisture content θ, cm 3 /cm 3(5 days)

0.5(10 days)

1st (Established amount of water volume 500cm3, measured volume 490.2cm3）2nd (Established amount of water volume 500cm3, measured volume 498.1cm3）3rd (Established amount of water volume 500cm3, measured volume 491.2cm3)

500
400

Distance along the slope is about 140cm

300
200
100

0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100100-110110-120120-130130-140140-150
150-160
160-170
170-180
180-190
190-200
200-210210-220220-230230-240240-250250-260
260-270270-280280-290290-300

downstream

0

Distance along the bottom of soil box, cm(a) Slope5 °, rainfall intensity 5 mm/h (Case A)
600
1st (Established amount of water volume 1000cm3, measured volume 977.2cm3）2nd (Established amount of water volume 1000cm3, measured volume 988.2cm3）3rd (Established amount of water volume 1000cm3, measured volume 976.9cm3）

500
400

Distance along the slope is about 80cm

300
200
100

downstream

0

0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100100-110110-120120-130130-140140-150
150-160
160-170
170-180
180-190
190-200
200-210210-220220-230230-240240-250250-260
260-270270-280280-290290-300

Distance from partition wall attachedto the bottom of soil box, cm3/ 10 min

Distance along the bottom of soil box, cm(b) Slope5 °, rainfall intensity 10 mm/h (Case B)
600

1st (Established amount of water volume 1000cm3, measured volume 937.5cm3）2nd (Established amount of water volume 1000cm3, measured volume 951.6cm3）3nd (Established amount of water volume 1000cm3, measured volume 942.2cm3）

500
400

Distance along the slope is about 180cm

300
200

0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100100-110110-120120-130130-140140-150
150-160
160-170
170-180
180-190
190-200
200-210210-220220-230230-240240-250250-260
260-270270-280280-290290-300

0

Distance along the bottom of soil box, cm

downstream

100(c) Slope10 °, rainfall intensity 10 mm/h (Case E)
600
500
400
300

1st (Established amount of water volume 1000cm3, measured volume 1000.6cm3）
2nd (Established amount of water volume 1000cm3, measured volume 1013.3cm3）3rd (Established amount of water volume 1000cm3, measured volume 1011.6cm3）

Distance along the slope is about 180cm

200

0Distance along the bottom of soil box, cm

downstream

100
0-10
10-20
20-30
30-40
40-50
50-60
60-70
70-80
80-90
90-100100-110110-120120-130130-140140-150
150-160
160-170
170-180
180-190
190-200
200-210210-220220-230230-240240-250250-260
260-270270-280280-290290-300

The volumetric moisture contents measured
along the line C given in Fig.4 during the soil box
test are given in Fig.5.
Comparing θ measured at S3, S8 and S13, it isfound that the moisture content becomes larger
along the depth in the sand layer. As the sand layer
was compacted uniformly, the larger value ofmoisture content means higher degree of saturation
above the interface. In addition, the volumetricmoisture contents become higher with the increaseof rainfall intensity. Conversely, the volumetricmoisture contents become lower with the decrease of
rainfall intensity.
In case G with 2.5 degrees in slope and 5 mm/hof infiltration rate (rainfall intensity), rainfall was
supplied steadily during about 7 days. As the result,the volumetric moisture contents are constant both insand and crushed shell layers as shown in the Z
section devoted in Fig.5. The condition of moisturein CB remains stable for a long duration of rainfall.
A series of laboratory soil box tests was carried out
continuously by changing the rainfall intensity andby jacking up the one side of soil box to obtain thetilting interface of the CB. The volumetric moisture
contents show the same values under the conditionof the same slope and rainfall intensity during theperiod from the start of rainfall to the end of a seriesof tests (about 21 days). Tests were carried out 2times, 3 times, and 2 times under the same condition
to recognize the reproductiveness, 10 degrees inslope and 5 mm/h of rainfall intensity, 10 degrees
and 10 mm/h, 10 degrees and 20 mm/h, respectively.
As shown for sensor number S13 in Fig.5, thevolumetric moisture contents in steady state, is about
0.20 (in 2 times), about 0.23 (in 3 times), and about
0.26
(in
2
times),
respectively.
Thus,
reproductiveness is verified.

Distance from partition wall attachedto the bottom of soil box, cm3/ 10 min

Change of volumetric moisture content (θ)

600Distance from partition wall attachedto the bottom of soil box, cm3/ 10 min

Results of Soil Box Test

Distance from partition wall attachedto the bottom of soil box, cm3/ 10 min

GEOMATE-Nagoya, Nov.13-15, 2013(d) Slope10 °, rainfall intensity 10 mm/h(2) (Case H)
Fig. 6

Time, days

Typical measurement of water volume collectedalong the bottom of the soil box to determine thediversion length .
(15 days)(20 days)

0.4

S3

0.3

S8

0.2

S13

0.1

G3

0.0
0

CaseA
7200
14400
Stopping
Stopping
5°5mmCaseB
CaseE
rainfallrainfall10°10mm
5°10mm
CaseC
CaseF
5°20mmCaseD 10°20mm
wetting
processFig. 5

Time, min

21600

CaseG
2.5°5mm
Z section( about7 days)

10°5mmwetting

wetting
process

drying process process drying process

CaseH
28800
10°10mm CaseJ
2nd times 10°10mm
3rd times
CaseK
CaseI
10°20mm 10°5mm
2nd times 2nd times
drying process

Volumetric moisture content measured in CB constructed in the soil box. S3, S8, S13 and G3 are sensor
numbers and given in Fig. 4.
376

GEOMATE-Nagoya, Nov.13-15, 2013

350

Table 3 Diversion lengths measured in the soil box
test. Note that the upper asterisk “*” shows
the diversion length measured during drying
processes.

Diversion length estimated, cm(Unit: cm)

Established rainfall intensity, mm/h
Slope angle, degree
5
10
20
2.5
90
5.0
139
80
30
1st time
246
177
89
10.0
2nd time
177
89
246*
3rd time
187*

As a result, in the case where a certain rainfall
intensity is given for a long duration, soil moisture
contents remain constant and the condition ofmoisture is in a steady state. The volumetricmoisture contents of CB fluctuate according to therepetition of wet and dry conditions for about 21
days. The volumetric moisture contents have thesame values and reproductiveness is found under thesame condition for aouut 21 days. The performanceof CB using crushed shells is stable for a long
duration of rainfall and in the case of repetition of
wet and dry conditions.

○ :Morii, et al. [15](lower layer is gravel)■ :Laboratory soil box test
(lower layer is crushed shell)

300
250
200
150
100
50
0
0

50

100

150

200

250

300

350

Diversion length measured, cm

Fig. 7Comparison of the diversion lengths
measured in the soil box test with ones
estimated by Steenhuis et al [8]. The
diversion length of the CB composed of sandand gravel are also given for comparison.

The diversion lengths of CB were estimated by
Eq. (1) considering the test conditions. As shown in
Fig. 3(b), the air entry value (h a ) of silica sand was
13 cm, and the water entry value (h w ) was set to 1
cm because there was no definite value as shown in
Fig. 3(a). Saturated hydraulic conductivity of sand,K s =1.31×10-2 cm/s, was measured as given in Table
1. α near saturation of silica sand can be estimatedto be 0.118 cm-1.
The diversion lengths which were measured incases A to K are compared with ones estimated by
Eq. (1) in Fig. 7 by using gray squares. Laboratory
results using gravel instead of crushed shells
published by Morii et al. [15] are also plotted bywhite circles. As the diversion lengths in the case of
crushed shells are almost same as values in the caseof gravel, it may be found that Eq. (1) can be well
employed to estimate the diversion length of the CB.
According to the results as mentioned above, it isconcluded that the crushed shell particles areapplicable to the CB system. This alternative of thecrushed shell particles will keep good performancefor a long duration because of small deteriorationof shell material.

Diversion length of the CB
Figs. 6(a)-(d) show the volume of water collectedalong the bottom of the soil box. Horizontal axis
shows the distance along the interface from the most
upstream of the soil box. In Fig. 6, the distance fromthe upstream of the soil box to a point where thewater volume collected firstly gives the diversion
length of the CB. Table 3 summarizes the diversion
lengths measured in all cases, in which the diversion
lengths are converted into the horizontal lengths bytaking the angles of slope of the soil box into
account. The diversion length measured by the soil
box test is affected by the rainfall intensity and slope.
The lower the rainfall intensity is and the larger theslope angle is, the longer the diversion length
becomes.
To examine whether the CB can reproduce thesame diversion length, the test of 10 degrees in slope
angle and 5 mm/h of rainfall intensity were repeated
twice (Cases D and K), the test of 10 degrees and 10
mm/h 3 times (Cases E, H and J), and the test of 10
degrees and 20 mm/h twice (Cases F and I). As
shown in the lowest line of Table 3, almost the same
diversion lengths were measured. This means the
CB can provide a stable diversion of infiltrationwater.
According to the results as mentioned above, it
was clarified that the CB using crushed shellparticles instead of gravel provides an excellent andstable performance of water diversion.

CONCLUSION
In order to determine the diversion length of the
CB composed of sand and crushed shell particles,
the laboratory soil column test and the soil box test
were carried out. The diversion lengths measured by
the soil box test were compared with ones estimatedby Steenhuis et al.[8]. In addition, the applicabilityof the equation proposed by Steenhuis et al. [8] in

APPLICABILITYOF
ESTIMATIONEQUATION INTO THE CB COMPOSED OF
SAND AND CRUSHED SHELL PARTICLES
377

GEOMATE-Nagoya, Nov.13-15, 2013

estimating the diversion length of the CB was
discussed.
The following are obtained:(1) The SWCC of crushed shell particles during
the drying and wetting processes show only verysmall air entry value (h a ) and water entry value (h w ).
They are similar to the air entry value and the water
entry value of gravel. From the point of view of soilwater characteristic, crushed shell particles can bewell employed in CB instead of gravel.
(2) The volumetric moisture contents have thesame values under the condition with the same
slope and rainfall intensity in the soil box test during
a period from the start of rainfall to the end of aseries of tests (about 21 days) and reproductivenessis found. So, the CB using the crushed shells
displayed the stable function during a long-term
rainfall and under repetitive dry and wet condition.
(3) It was confirmed experimentally that the lower
the rainfall intensity is and the larger the slope angle
is, the longer the diversion length becomes. The
diversion length measured several times under thesame condition had almost the same value andreproductiveness of diversion length was verified.
(4) As the diversion lengths in the case of crushed
shells are almost same as values in the case of gravel,
Eq. (1) can be well employed to estimate thediversion length of CB.
According to the results as mentioned above, it
is concluded that the crushed shell particles insteadof gravel are applicable to the CB system. The reuseof fishery by-product (shell) may contributes toconstruct a recycling society in Japan with scarcenatural resources.

Autumn lecture and symposium, 2011, pp. 138141.
[4] Nakafusa S., Kobayashi K., Morii T. andMatsumoto K., “Study on capillary barrier ofusing fishery byproducts to reduce theinfiltration of sand particles into the low layer “,Journal of JSCE (B3) , Vol. 68, No. 2, 2012,
pp.I_462-I_467.
[5] Nakafusa S., Kobayashi K., Morii T. andNishimura T., “Alternative employment ofcrushed shell particles in capillary barrier ofsoil”, Int. J. of GEOMATE, Vol.1, No.1, 2011,
pp.50-55.
[6] Matsumoto K., Kobayashi K. and Morii T., “Anexamination of crushed shells by constructive
heavy machinery for the alternative to gravel
constituting the capillary barrier”, Proceedingsof the 57th Japan Geotechnical symposium,
2012, pp. 235-238.
[7] Miyazaki T, “The diversion capacity of an
inclined capillary barrier”, Journal of JSIDRE,
No. 179, 1995, pp. 49-56.
[8] Steenhuis T. S., Parlange J. -Y. and Kung K –J.,
“Comment on ‘The diversion capacity ofcapillary barriers’ by Benjamin Ross”, Water
Resources Research, Vol. 27, No. 8, 1991, pp.
2155-2156.
[9] Ross B, “The diversion capacity of capillarybarriers“, Water Resources Research, 26(10),1990, pp. 2625-2629.
[10] Kung K. -J. S., “Preferential flow in a sandy
vadose soil 2, Mechanism and implications”,
Geoderma, 46, 1990, pp. 59-71.
[11] Walter M. T., Kim J. –S., Steenhuis T. S.,
Parlange J. –Y., Heilig A., Braddock R. D.,
Selker J. S. and Boll J., “Funneled flowmechanisms in a sloping layered soil:
Laboratory investigation”, Water Resources
Research, 36(4), 2000, pp. 841-849.
[12] Smesrud J. K. and Selker J. S., “Effect of soilparticle size contrast on capillary barrier
performance”, Journal of Geotechnical andGeoenvironmental Engineering, 127(10), 2001,
pp. 885-888.
[13] van Genuchten M. Th., “A closed-form
equation for pre-dicting the hydraulicconductivity of unsaturated soils”, Soil Science
Society of American Journal, Vol. 44, pp. 892898, 1980.
[14] Stephens D. B., “Vadose Zone Hydrology”,
CRC Press, pp. 183-187, 1996.
[15] Morii T., Kobayashi K., Matsumoto K., SuzukiT., Kawai T. and Nakafusa S., “Practicalapplication of capillary barrier of soil into ashallow land waste repository”, Pro-ceedings ofthe Fifth China-Japan Geotechnical symposium,
2012.

ACKNOWLEDGEMENTS
The present study was supported by JSPC
KAKENHI Grant Number 22560507. Messrs. K.
Taguchi and N. Someya, TNS Co., Ltd., Japan, aresincerely grateful for their help in conducting thelaboratory soil box test.
REFERENCES[1] Morii T, “Capillary barrier of soil”, Geotechnical Engineering Magazine, Vol.59, No.2,
2011, pp. 50-51.
[2] Rahardjo H., Krisdani H. and Leong E-C.,“Application of unsaturated soil mechanics in
capillary barrier system”, Proceedings of the 3rd
Asian Conference on Unsaturated Soils edited
by Yuan, J. and Chiu, A. C. F., 2007, pp. 127137.
[3] Nakafusa S., Nishimura T., Kobayashi K. andMorii T., “Soil water characteristic curve ofsoil mixed by sand and gravel”, the 2011 JAGH

378

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EXPERIMENTAL STUDY OF CONCRETE AND MORTAR MIXINGWASTE TIRE RUBBER
Man-Kwon Choi 1, Yuki Hasegawa 2, Shushi Sato 3, Shinsuke Matsumoto 3 and Hyeon-Tae Kim 4
1
Institute of Agriculture & Life Science, Gyeongsang University, Korea
2
The United Graduate School of Agricultural Science, Ehime University, Japan
3
Faculty of Agriculture, Kochi University, Japan
4
Department of Bio-Industrial Machinery Engineering, Gyeongsang National University (Institute of Agriculture& Life Science), Korea
ABSTRACT
Waste tire disposal is one of the most important issues in all over the world. The use of waste tire as amaterial to concrete is a possible disposal solution. In this study, the fundamental properties in harden state ofconcrete and mortar mixed waste tire rubber were examined. The volume percentage of aggregate and sand was
replaced by waste tire rubber. Focusing on the mechanical properties, the use of waste tire rubber of replaced
volume was shown compressive and flexural strength concerning both rubberized concrete and mortar. As aresult, the reduction rate of flexural strength was smaller than that of the compressive strength. In addition,
ultrasonic pulse velocity showed the same tendency that rubberized mortar decrease more than rubberized
concrete.
Keywords: Waste Tire Rubber, Mechanical Properties, Mixture Proportions, Concrete, Mortar

reduced when crumb rubber and tire chips inPortland cement concrete [6]. But, the main variablein the mixtures was the toughness of the material
greatly increases. Moreover, workability was not
significantly affected. Li et al. investigated theperformance of the waste tire chip and waste tirefiber modified concrete [7]. They observed thatfibers performed better than chips did. Atahan andSevim produced concrete mixed shredded waste tirechips and measured compressive strength, modulus
of elasticity and dynamic impact using the identicalmix design [8]. They found that specimens with 20
to 40% aggregate replacement gave the best impact
performance without significant reduction in
concrete strength. Yuksel et al. investigated how theusage of bottom ash, granulated blast furnace slags[9]. They observed that compressive strength loss
due to freezing-thawing effect for low replacement
ratio (10-30%) and abrasion resistance of concrete
incorporation non-ground blast furnace slag did notdecrease when replacement of non-ground blast
furnace slag with fine aggregate up to 50%.
Although numerous investigations have been
performed for rubberized concrete with waste tireparticles, there are a limited number of studies
related to the mechanical properties rubberizedmortar. In this study compressive strength, flexuralstrength and ultrasonic pulse velocity were
investigated for both rubberized concrete and mortar
at each mixed design.
The objective of this study was to evaluate thefeasibility and performance of waste tire rubberized
concrete using larger sized chips, rubberized mortar

INTRODUCTION
Japan is generating millions of waste tires every
year. All over the world, waste tire disposal havebeen occurred many environmental problems. As aresult, several studies have been carried out to findsubstitution and application for this rubber waste.
Waste rubbers disposal have two main uses; the firstone is the reuse of rubber tires left over retreading
process, and the second one is incorporating it into
cement-based material [1]. As for the latter use,
many authors have studied the use of water tirerubber in applications to such as aggregate ofconcrete, asphalt pavement and shock absorberstructures. In the last utilization method, they called
it as the rubber concrete [2-4]. Experimental
investigations of rubber concrete indicated thatchipped or crumbed tire rubber particles results thesignificant change in mechanical properties. Almost
all investigators reported a substantial decrease (1080%) in compressive and tensile strengths ofrubberized concrete with increasing waste tirerubber content [5-12]. The level of strength
reduction was related to the waste tire rubber content
and low bond strength between the cement based
matrix and the waste tire rubber particles. Eldin andSenouci reported that the concrete mixtures
exhibited lower compressive and splitting tensile
strength than those of normal concrete [5]. Also, amathematical model is used to describe the effects ofrubber aggregate on the compressive and tensile
strength reduction of concrete. Papakonstantinou
and Tobolshi reported that compressive strength379

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Mix proportion of rubberized concrete and mortar

Specimen

Cement(kg/m3)Water(kg/m3)Fine
aggregate(kg/m3)Coarseaggregate(kg/m3)

Rubberadded(kg/m3)Admixture(g/m3)RC0 (control)

373

212

732

849

0

75

RC10

373

212

732

810

39

75

RC20

373

212

732

771

78

75

RC30

373

212

732

733

116

75

Specimen

Cement
(g)

Water
(g)

Fine aggregate(g)

Coarse aggregate(g)Rubber added(g)

Admixture(g)

RM0 (control)

450

225

1350

-

0

-

RM10

450

225

1215

-

53.7

-

RM20

450

225

1080

-

107.4

-

RM30

450

225

945

-

161.1

-

RM50

450

225

675

-

268.5

-

using waste tire powder.

Specimen Preparation and Testing

EXPERIMENTAL DESIGNAll specimens were placed and unmolded after
24 hours of casting, and cured with standard water
curing under a constant temperature 20 ± 1 ℃. A
total of 72 concrete specimens were made and cured
according to JIS A 1132 [14]; of these, 36
cylindrical specimens (10cm×20cm) were tested forcompressive strength and 36 rectangular specimens(10cm×10cm×40cm) were tested for flexuralstrength. On the other hand, total of 40 mortar
specimens were made and cured for this experiment.
The size of all mortar specimens were controlled inheight, width, and length of 4cm×4cm×10cm,
respectively. All mortar specimens were tested atage 7, 28 and 91 days for compressive, flexural andultrasonic pulse velocity tests. The flexural andcompressive strength tests were conducted at age 7,
28, 91 days using Hi-ACTIS 200 (MARUI CO.
LTD).
For the flexural strength test of concrete, three
specimens in each mixture were prepared and testedby three point loading configuration. Compressive
strength test of concrete were performed threecylindrical specimens in each mixture. Compressive
strength test of mortar specimens were used six
broken pieces of test prisms left after testing theflexural strength. Ultrasonic pulse velocity wasmeasured against each test age.

Materials and Mix Design
In this study, the concrete specimen was
designed with a constant water cement ratio of 56 %.
Ordinary Portland cement, crushed stone (as coarse
aggregate), crushed sand (as fine aggregate) and tap
water were basic components for the fundamental
materials of all concrete specimens. The densities ofcoarse and fine aggregate were 2.58 g/cm3 and2.54g/cm3, respectively.
The mortar specimen was designed with samewater cement ratio of 50 %. Ordinary Portland
cement, standard sand and tap water were used as
the fundamental materials of mortar specimen. The
mix proportions of rubberized concrete and mortar
were given in Table 1.
The waste tire rubber chips were collected from atire recycling company in Kochi prefecture. These
chips were shredded and thieved into maximum sizeof 25 mm for concrete specimens, and gathered lessthan 5 mm of diameter for mortar specimens. The
density of waste tire rubber was 1.18 g/cm3. The
waste tire rubber was mixed into concrete against
the volume of coarse aggregate at ratio of 0%, 20%
and 30%. In addition, the waste tire rubbers weremixed into mortar against the volume of fineaggregate at ratio of 0%, 20%, 30% and 50%.

RESULTS AND DISCUSSIONSThe test results of the compressive strength,
flexural strength and ultrasonic velocity of each380

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 1 Compressive strenght variations of theconcretes

Fig. 3 Flexural strength variations of concretes

Fig. 2 Compressive strength variations of themortars
specimen were shown in Fig.1 to Fig.6. These
results were analyzed and described as follows.

Fig. 4 Flexural strength variations of mortars
and 59.69MPa at 7, 28, 91 days respectively.
Comparing these values above, the reduction ofcompressive strength at age 28day was 33.6%(RM10), 55.2% (RM20), 70.6% (RM30) and 86.2%(RM50).
It was concluded that the large amount of rubber
mixing led to huge losses of compressive strengthand the reduction ratio of compressive strength ofmortar was higher than that of concrete due toincrement of replacement ratio.

Effect on Waste Tire Rubbers to the Compressive
Strength of the Rubberized Concrete and Mortar
The compressive strength of rubberized concreteand mortar was determined at 7, 28 and 91 days
respectively. It was calculated based on the averagein each specimen. The test results were given in Fig.
1and Fig.2.
From these test results, the compressive strengthof all rubberized concrete and mortar were lower
than that of the control regardless the replacement
ratio. It was natural results because waste tirerubbers were softer than the concrete and mortar
matrix such as aggregate or cement hydrates. In
general, soft part acts as the concentration of stressin the composite [7]. The compressive strength ofthe control mix for concrete specimens wasevaluated as 25.87MPa, 34.47Mpa and 43.03MPa atage 7, 28, 91 days, respectively. Comparing thesevalues above, the reduction of compressive strength
at age 28 day were 24.0% (RC10), 33.5% (RC20)
and 51.6% (RC30). On the other hand, thecompressive strength of the control mix for mortar
specimens was evaluated as 41.15MPa, 58.22MPa

Effect on Waste Tire Rubbers to the Flexural
Strength of the Rubberized Concrete and Mortar
The flexural strength of rubberized concrete andmortar was determined at age 7, 28 and 91 days. The
test results were presented in Fig. 3 and Fig.4.
Flexural strength of control mixed for concrete was
evaluated as 4.31MPa, 5.49MPa and 5.92MPa at age
7, 28 and 91 days, respectively. The result of
flexural strength test also indicated the similartendency of the result of compressive strength.
Comparing with the control mixture of concrete(RC0), the reduction of flexural strength at age 28
days were 15.7% (RC10), 18.4% (RC20) and 31.1%(RC30). The flexural strength of the control mixture
for mortar specimens was evaluated as 8.72MPa,
381

GEOMATE-Nagoya, Nov.13-15, 2013

was observed that the change of UPV had tendency
of increment with the advance of age at threerubberized concrete mixture.
According to the previous study by Malhotra(1976), the specimens are classified in “good”
condition as their UPV values ranged in 3.66km/s4.58km/s [13]. Rubberized concrete in this researchwere evidently in “good” conditions.
From the Fig. 6, the UPV values of mortar
specimen showed the same tendency withrubberized concrete. However, UPV value at age 28
days of mortar mixture tended to decrease more thanthat of concrete mixture.

9.65MPa and 11.23MPa at age 7, 28 and 91 days,
respectively. Comparing with these values above,
the reduction of flexural strength at age 28day was
22.4% (RM10), 44.7% (RM20), 58.3% (RM30) and
73.3% (RM50).
These results indicated that the reduction rate offlexural strength was lower than that of thecompressive strength. Thus, there was possibility
that the rubber particles in concrete affect to a goodbonding than rubberized mortar.
Effect on Waste Tire Rubbers to the Ultrasonic
Pulse Velocity (UPV) of the Rubberized Concreteand Mortar

CONCLUSION
Ultrasonic pulse velocity (called UPV, here
after) method is one of the non-destructive tests andutilized for the evaluation of strength development.
The effect on mixed waste tire rubber to themechanical property of various specimens wasinvestigated. Fig. 5 and Fig.6 showed the change of
UPV with the age of rubberized concretes andmortars. The UPV reduced significantly withincrement of the replacement ratio concerning to theboth concrete and mortar specimen. From the Fig. 5,
the UPV values of age 28 days were 4.21km/s(RC10), 4.19 km/s (RC20) and 4.02km/s (RC30),
respectively. All of these values were lower than thevalue of control mixture (4.4km/s). Additionally, it

Rubberized concrete and mortar was preparedand tested. The compressive and flexural strengthand ultrasonic pulse velocity tests of rubberized
concrete and mortar were conducted. The effect ofvarious deigns variables on the compressive andflexural strength decrease while the amount ofrubber replacement increases, respectively. At age
28 days, compressive and flexural strength of mortar
tended to decrease more than that of concrete withsame replacement ratio due to the advance of curing
time. Also, ultrasonic pulse velocity showed thesame tendency that rubberized mortar decrease morethan rubberized concrete.
ACKNOWLEDGEMENT
A part of this study was supported by JSPS
KAKENHI Grant Number 24580356. Authors arethanks to Ms. Uchida Mika, Mr. Matsuura Satoru,
Ms. Aoki Anna, Mr. Kagawa Haruhiko, Mr.
Kanaoka Hiroki, Ms. Hara Shizuka and othermembers of water use and environmental
engineering laboratory in Kochi University, for theirkindly cooperation on experiment.

Fig. 5 Ultrasonic Pulse Velocity variations ofconcretes

REFERENCES[1] Ozbay E, Lachemi M, Sevim UK, “Compressive
strength, abrasion resistance and energy absorption
capacity of rubberized concretes with and withoutslag”, Materials and Structures, Vol. 44, Dec. 2011,
pp. 1297-1307.
[2] Yilmaz A, Degirmenci N, “Possibility of using
waste tire rubber and fly ash with Portland cement asconstruction materials”, Waste Management, Vol.
29, Dec. 2009, pp.1541-1546.

Fig. 6 Ultrasonic Pulse Velocity variations ofconcretes
382

GEOMATE-Nagoya, Nov.13-15, 2013

Vol. 35, Jan. 2004, pp. 305-312.
[9] Yuksel I, Bilir T, Ozkan O, “Durability ofconcrete incorporating non-ground blast furnace slag
and bottom ash as fin aggregate”, Building andEnvironment, Vol. 42 (7), Jul. 2007, pp. 2651-2659.
[10] Atahan AO, Sevim UK, “Testing andcomparison of concrete barriers shredded waste tirechips”, Materials Letters, Vol. 62, Aug. 2008, pp.
3754-3757.
[11] Khatib ZK, Bayomy FM, “Rubberized Portland
cement concrete, J. of Materials in Civil Engineering,Vol. 11(3), Aug. 1999, pp. 206-213.
[12] Toutanji, HA, “The use of rubber tire particles
in concrete to replace mineral aggregates”, Cement
and Concrete Composite, Vol. 18(2), Jan. 1996, pp.
135-139.
[13] Malhotra VM, “Testing hardened concrete:nondestructive methods”, American Concrete
Institute, Monograph, NO. 9, 1976
[14] Japanese society of civil engineers, Guideline
for Experiment on Materials of Civil works, JSCE,
2009 Edition.

[3] Son KS, Hajirasouliha I, Pilakoutas F, “Strengthand deformability of waste of waste tyre rubberfilled reinforced concrete columns”, Construction
and Building Materials, Vol. 25, Jan. 2011, pp. 218226.
[4] Cao W, “Study on properties of recycled tirerubber modified and asphalt mixtures using dry
process”, Construction and Building Materials, Vol.
21(5), May 2007, pp. 1011-1015.
[5] Eldin NN, Senouci AB, “Rubber-tire particles asconcrete aggregate”, J. of Materials in Civil
Engineering, Vol. 5(4), Nov.1993, pp. 478-496.
[6] Papalonstantinou CG, Tabolski MJ, “Use ofwaste tire steel beads in Portland cement concrete”,
Cement and Concrete Research, Vol. 36, Sept. 2006,
pp. 1686-1691.
[7] Li G, Stubblefield MA, Garrick G, Eggers J,
Abadie C, Huang B, “Development of waste tire
modified concrete”, Cement and Concrete Research,
Vol. 34(12), Dec. 2004, pp. 2283-2289.
[8] Li G, Garrick G, Eggers J, Abadie C,
Stubblefield MA, Pang SS, “Waste tire fiber
modified concrete”, Composites Part B: Engineering,383

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PILE DRIVING EFFECTS ON NEARBY BUILDING
Adhilla Ainun Musir1 and Abdul Naser Abdul Ghani2
Faculty of Civil Engineering, UiTM Penang, Malaysia; 2School of Housing Building and Planning, Universiti
Sains Malaysia, Malaysia

1

ABSTRACT
Piles are used to support many major structures such as buildings and bridges. It is known that pile driving
activity creates vibrations in the ground and may affect nearby building and structure. However, the different pile
size and shape as well as installation distances factors remain as interesting subjects for studies. The effect ofhammer driven piles installation were studied using laboratory scale model. Three main effects were studied inwhich they are the response on top and bottom of a building, the vibration creates by three different distances ofdriven pile and the vibration produced by two different pile sizes. It can be concluded that the effect of vibrations
are higher at the bottom of the building. The result also indicates that the nearest distance of piling activity
produced higher vibration. However, it is interesting to note that the smaller pile creates larger vibrations.
Keywords: Pile, Piling Vibration, Building, Laboratory Model.

spread into the ground travels from the pile tostructures within. The amplitude of this vibration
depends on many factors. The energy propagating
away from driven pile depends on pile driver and thepile type itself [2]. Massarsch and Fellenius [3]described three types of ground waves created by piledriving namely surface wave, spherical wave fromthe pile toe and cylindrical wave from the pile shaft.
The main thrust of this study is to identify thevarious physical parameters involve in the
propagation of vibration energy that affectsurrounding building or structure by means oflaboratory model. Over the years, several researchers([2], [4], [5], [6] and [7]) have used scale model tocarry out experiments related to piling. In this study,
it is expected that relationship of the various
parameters such as pile size, pile type, distance,
trench depth and driving methods can be established.
The empirical relationships can then be used in theactual operational condition as preliminary strategy to
reduce or eliminate pile driving effects on nearbybuilding or structure.

INTRODUCTION
It is known that pile driving activity createsvibrations in the ground and may affect nearbybuilding or structure. Propagation of vibrations to thesurroundings depends on the weight of the ramming
equipment, impact velocity, impact duration, shape of
the pile, surrounding and underlying soil, crosssectional area of the pile, straightness of the pile andeccentric or oblique strokes. Piling and sheet pilingwork on construction sites affects the environment indifferent ways depending on geological conditions.
Usually, piling cause noise, vibration, settlement or
heaving close to the site. The effects are dominatedby the energy introduced into the subsoil, the distancefrom the source and because of subsoil condition.
Settlement quickly occurs in non-cohesive soil.
It is expected that vibration level associated withpile driving may vary with distance from the piledriving site. This is because the resulting wave is ofperiodic nature which is highly attenuated after shortdistance and harmonic frequencies are low vibrationlevel.
Ground vibration generated by construction
sources consists of transient vibration and steady statevibration. Transient vibration is the single event orsequence vibrations. Each transient pulse of varying
duration decaying before the next impact occurs. For
example air, diesel or steam impact pile drivers bydynamic compaction of loose sand and granular fills
by highway and quarry blast. Abdel-Rahman [1]surveyed and concludes that the force vibration
caused by pile driver, double acting impact hammers
operating at high speed and heavy machineries affectsurrounding buildings. It causes or propagates crack
and failure.
Energy that is produced by pile driving and

MATERIAL AND METHODS
Laboratory scale model was used to carry out
experiments. A suitable sand container was fabricatedto be used as a testing ground. The laboratory testing
container was scaled from real construction site with
1:20 scale. This box was filled with river sand as soil.
The size of container is 1.35 meter for the length, 1.0
meter for the width and 0.6 meter from the depth.
Figure 1 shows the testing container used in this study.
The size of the container is designed to accommodate
dimensional similitude of a model building structure.
Similar container size has been used before by otherresearchers as described in previous paragraph.
384

GEOMATE-Nagoya, Nov.13-15, 2013

building.

Figure 1: Sand container
Building/Structural Model

Figure 3: Equivalent 200mm square Pile of
10mm x 10mm

Model of building was built by using stainlesssteel bar. This model was scaled as 1:20 from 3 storey
building and the height of the model building is 0.9
meter. The width and the length of the building is 0.3
meter. Stainless steel were cut into pieces and weldedto the shape of skeleton building structure. The
foundation of this building is raft foundation. The
model of the building is shown in Figure 2.

Figure 4: Pile arrangement at various distance frombuilding
Pile driving hammer
On site hammer weight considered for this study
is 1 ton and it was scale down to the ratio 1:20. The
model hammer weight now becomes 120 gram. The
dimension of container is 50 mm x 50 mm x 50 mm
and filled with sand to the required weight. Hammer
weight will be released at 150 mm height to the top of
pile. Vibration at nearby model building wererecorded when the hammer reach the pile. Hammer
weight and hammer drop distance are constantthroughout this experiment.

Figure 2: Building Model
Pile
Piles used for this study are squared piles with
150mm x 150 mm and 200mm x 200 mm dimension.
The size of pile was scaled down to 7.5mm x 7.5mm
for the size of 150mm x150mm and 200mm x 200mm
was scaled to 10mm x 10mm. The pile shoe scaled to
20 mm for both types of pile.
The assumed length of piles is 6m on site and it
was scaled to 300 mm for the model. There are threepiles for each size and will be allocated at different
distance. The two sizes of piles chosen was thecommon pile sizes used for low rise building
construction. The difference of pile size is expected
to produce different level of vibration to the nearby

Figure 5: Hammer system

385

GEOMATE-Nagoya, Nov.13-15, 2013

RESULTS AND DISCUSSION
Laboratory testing model result is based onvibrations occurs during pile driving. These results
were divided into three parts. The first is the result ofcomparison between vibration impact on top andbottom of the nearby building. It involved both sizesof piles which is 7.5 mm x 7.5 mm (150 mm x 150mm) on site and 10 mm x 10 mm (200mm x 200 mm)
on site. The scale ratio of sizes of pile is (1:20).
The next part involves the analysis and discussionof comparison of vibration impact on nearby building
based on three different distances which are 900 mm,
600 mm and 300 mm from the building. The scale
used is 1:20 and it means the real distance frombuildings is 18 m, 12 m and 6 m on site.
The last part of analysis for this study iscomparison of vibration impact on existing building
with different sizes of piles. The comparison valuesof vibration impact based on two sizes of piles thatwere driven on same distance from the building.

Figure 6: Use of special casing to make surehammer drop on top of pile.
Testing Procedure

Effect based on pile size

The steps conducting this experiment wereexplained further as below:

Table 1(a): The comparison between sizes of pile on
top of building (vibration level in mV/g)

1) Two vibration transducers (accelerometer)
were connected to the top and bottom of building andalso connected to a dynamic data-logger as it willrecord the vibration data in computer.

TOP

7.5 X 7.5

10.0 X 10.0

Point 1

1810

1392

Point 2

1560

1884

2) Pile with the size 7.5 mm x 7.5 mm waspositioned at point three. Pile was aligned at thecentre of building as measured before. Pile wasbraced by formwork to make sure pile still standing
correctly during driven activity.

Point 3

4394

5061

Table 1(b): The comparison between sizes of pile onbottom of building (vibration level in mV/g)

3) When pile is ready, the hammer will be alignedwith the pile. A casing with 150 mm height was
installed to make sure hammer drop distance isconstant and the hammer will be drop just over the
pile. It also to make sure there is no disturbance fromothers such as wind or any movement.

BOTTOM

7.5 X 7.5

10.0 X 10.0

Point 1

2037

1602

Point 2

3119

2690

Point 3

5656

6241

4) The vibration data will be recorded for every
10 mm penetration of pile to the sand.
At the top of building, it shows that the resulting
vibration was higher from point 1 (farthest) for thesmaller 7.5 mm pile. As piling work moved closer tothe building the bigger pile produce higher vibration
at the top as indicated by point 2 and point 3 (nearest).
This is possibly because heavier pile reduces thevibration amplitude. It was similarly reported before
that when the pile is small, the vibration amplitude
can be inadequate at the pile base. This can also result
in too much transverse vibration and sometime leadto a broken pile [9].
Similarly, the bottom transducers produce higher

5) Formwork was divided into parts. After 50 mm
penetration, part of formwork will be dismantling tohammer pile again.
6) The process will be continued until pilepenetrated up to 250 mm. The steps will be repeatedto the other pile for point 2 and point 1.
7) The process continuously repeated for otherpile installation.

386

GEOMATE-Nagoya, Nov.13-15, 2013

Point 3

vibration record as a result of 7.5mm pile fromposition 1 and 2. Only when it is very close to themodel building at position 3 that the bigger 10mm
pile cause higher impact.

5061

6241

The tables above show that the effect of driven
pile activity was higher at the bottom for both sizes ofpile. This is mainly because the ground vibrations isnearer to the bottom part of the building and the effectis diminishing towards the top.

Effect based on driving distance
Table 2 (a): The comparison on the effect based on of
7.5 x 7.5 mm piles (vibration level in mV/g)

CONCLUSION
7.5 x 7.5

POINT 1

POINT 2

POINT 3

Top

1810

1560

4394

Bottom

2037

3119

5656

It is known that pile driving activities createsvibrations in the ground. Those vibrations may affectthe nearby structures or disturbed people in theneighborhood of pile driving activity.
In this study, the result naturally shows thatvibrations effect were higher at the bottom of building
compared to the effect on the top of building. Also,
the nearer distance cause higher vibrations comparedto the one further from the building. However, thesmaller pile creates more vibrations towards the
nearby building. This could be due to pile density
reaction towards resisting forces from soil. Further
study is required to identify a matrix of pile type, sizes
and suitable distance for use in practical selection ofpile size in works associated with pile installationnear existing building or structure.

Table 2 (b): The comparison on the effect based on of
7.5 x 7.5 mm piles (vibration level in mV/g)
10.0
10.0

x

POINT 1

POINT 2

POINT 3

Top

1392

1884

5061

Bottom

1602

2690

6241

Table 2 clearly indicates that the vibration levelfrom various pile sizes increases as it moves closer tothe model building.
The risk of driving piles next to a building mayvary according to the types of structure and methodof piling but in general vibration will be higher nearer
to the building.

REFERENCES[1] Abdel-Rahman, S.M (2002), “Vibration
associated with pile driving and its effects on
nearby historical structure”. In: ProceedingsSpie the International Society for OpticalEngineering, 2002, USA. 1251-1258[2] Woods, R. C. and Sharma V. M. (2004),“Dynamic Effect of Pile Installation on Adjacent
Structures”, A. A. Balkema, India.
[3] Massarsch, K.R. and Fellenius, B.H. (2008).
“Ground Vibrations Induced by Impact Pile
Driving.”, In Proceedings of 6th International
Conference on Case Histories in GeotechnicalEngineering. 2008. VA USA.
[4] Dowding, C.H. (1996) Construction Vibrations,
New Jersey: Prentice-Hall[5] Pak, R. Y. S. and Guzina, B. B. (1995), Dynamic
CharacterizationofVertically
LoadedFoundation on Granular Soils, J. Geotech.
Engrg., 121(3),274-286.
[6] Ali, H., J. Castellanos, Hart, D. and B. Nukunya(2003), Real Time Measurement of the Impact ofPile Driving Vibrations on Adjacent Property
during Construction, TRB Annual Meeting.
[7] Teh, M. (2010), Flac 2D Analysis of a Single Pile
under Lateral Loading, Unpublished Master
Thesis, UiTM.
[8] Selamat, M. R., Ramli, N. A. and Abdul Aziz, H.
M. (2004), “Pile Driving Tests for Mitigating

Effect to the top and bottom of building
Table 3(a): The comparison between top and bottom
vibrations on 7.5 x 7.5 mm piles (vibration level inmV/g)
7.5 x 7.5

TOP

BOTTOM

Point 1

1810

2037

Point 2

1560

3119

Point 3

4394

5656

Table 3(b): The comparison between top and bottom
vibrations on 7.5 x 7.5 mm piles (vibration level in
mV/g)
10.0 x
10.0
Point 1TOP

BOTTOM

1392

1602

Point 2

1884

2690

387

GEOMATE-Nagoya, Nov.13-15, 2013

Structural Damage due to Ground Vibrations”,
Proceeding 3rd National Conference in Civil
Engineering, Copthorne Orchid, Tanjung
Bungah, Malaysia.
[9] Huybrechts, N., Legrand, C. and Holeyman, A.
(2002), “Drivability Prediction of Vibrated SteelPile”, International Conference on Vibratory
Pile Driving and Deep Soil Compaction, Swets& Zeitlinger, Lisse

388

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

LABORATORY STUDY ON THE PERFORMANCE OF RECYCLED
CONCRETE AGGREGATES BLENDED WITH RECLAIMEDASPHALT PAVEMENT AS A PAVEMENT GRANULAR MATERIAL
S. Jayakody, C. Gallage, J. Ramanujam, A.Kumar
School of Earth, Environment and Biological Sciences, Science and Engineering Faculty, Queensland
University of Technology, Brisbane, Australia

ABSTRACT
Production of recycled concrete aggregates (RCA) from construction and demolition (C&D) waste has become
popular all over the world since the availability of land spaces are limited to dispose. Therefore it is important toseek alternative applications for RCA. The use of RCA in base and sub-base layers in granular pavement is a
viable solution. In mechanistic pavement design, rutting (permanent deformation) is considered as the major
failure mechanisms of the pavement. The rutting is the accumulation of permanent deformation of pavement
layers caused by the repetitive vehicle load. In Queensland, Australia, it is accepted to have the maximum of
20% of reclaimed asphalt pavement (RAP) in RCA and therefore, it is important to investigate the effect of RAP
on the permanent deformation properties of RCA. In this study, a series of repeated load triaxial (RLT) tests
were conducted on RCA blended with different percentage of RAP to investigate the permanent deformation andresilient modulus properties of RCA. The vertical deformation and resilient modulus values were used todetermine the response of RCA for the cyclic loading under standard pressure and loading conditions.

Keywords: Recycled concrete aggregates, Granular pavements, RLT testing, Permanent deformation, Resilient
modulusof load repetitions [2]. Rutting failure of thepavements is due to the increment of these gradualaccumulation plastic deformations of the granularlayers.
The conventional classification test procedure forthe pavement materials typically describe propertiesof the aggregates and then compared to those of anadequately performing material. But this is not
appropriate for an alternative aggregate like crushedconcrete because the material constituents are differ
substantially from those of traditional materials.
Therefore the most appropriate method of material
assessment is to simulate the insitu loading anddetermine the performance. The materials can be
performed in Repeated Load Triaxial test (RLT) in
laboratories to observe the permanent deformation
and resilient responses. The RLT test is significanceto predict the performance and to determine theresponses of the materials under different confiningpressures and loading stresses.
This paper presents the results of RLT tests on RCA
mixed with different percentages of RAP. The
effects of RAP on RCA are determined through thepermanent deformation and resilient modulus
values. RAP is the major constituent that could bemixed with RCA at the crushing process. Theasphalt is being mixed with crushed concrete
aggregates when the rigid pavement concrete

INTRODUCTION
Road constructions are typically demanded a hugevolume of crushed aggregates which causes for the
depletion of natural resources. Therefore,
investigations on the alternatives are becoming more
popular to replace the crushed aggregates.
Utilization of recycled materials in pavement
construction leads the sustainability in thedevelopment of infrastructures. Reuse the crushedconcrete as an unbound pavement material is apromising concept from both environmental andeconomic standpoints.
The subsurface layers (e.g: base and sub base) of
flexible pavement usually made up from compacted
aggregates. The absolute strength of these layermaterials is very important to have a good stiffnessin spreading traffic loading efficiently to theunderlying subgrade soil. Thus these aggregatesshould be high quality and stringent materials. These
granular layers exhibit two types of deformation
when subjected to repeated loading; resilient
deformation and permanent deformation. The
resilient deformation provides an indication ofelastic response and causes for fatigue cracking on
bound layers (e.g asphalt, concrete layers) [1]. The
permanent deformation is due to the accumulation ofsmall increments of plastic strain over large number

389

GEOMATE-Nagoya, Nov.13-15, 2013

structures are crushing. The possible mixing
percentage of RAP with RCA is usually around 20%
at the crusher plant [3]. Therefore it is important toinvestigate the influence of RAP in RCA on its
performance under repetitive loading in order toassess RCA as unbound pavement materials. Further
RLT tests on RCA will be conducted to investigate
the effects of number of load repetitions, stresslevels, and moisture content on plastic deformation
and resilient modulus and the results will be
published in subsequent journal/conference papers.

Material name
RM1-100/RAP0
RM1-90/RAP10
RM1-85/RAP15
RM1-80/RAP20

with

blending

RM1-90/RAP10

12.7

1.785

RM1-85/RAP15

12.3

1.789

RM1-80/RAP20

12.9

1.789

Mixing percentage by mass
RM001
100
90
85
80

Repeated Load Triaxial test

RAP
0
10
15
20

Repeated Load Triaxial test was performed on thecompacted specimens to simulate the repeatedpassage of loaded vehicle wheels over the materials.
The standard test method of Department ofTransport and Main Roads Q137 for permanent
deformation and resilient modulus of granular
unbound materials was followed for the permanent
deformation and resilient modulus test [6]. The
UTM-4 digital servo control testing machine wasused with the UTM-14 Resilient modulus test
application software to determine the performance
characteristics. The RLT equipment is shown in theFig. 1.
Stresses were decided according to the Q137;
125kPa confining pressure was applied and held
over the test. The total vertical pressure 750kPa wasapplied to represent the tire pressure of a standard
axle. Therefore constant stress ratio of 750/125 was
kept for 50000 loading cycles.

EXPERIMENTAL METHODStandard proctor compaction test in accordance with
the Australian standard [4] was performed on eachsample to determine the optimum moisture content(OMC) and maximum dry densities (MDD). Results
are shown in Table 2. The RLT tests were performed
at OMC to determine the permanent deformations attheir maximum compactions.
Table 2. Optimum Moisture Content and Maximum
Dry Density for four Samples

Material name

1.748

Each sample was compacted at corresponding MDD
with OMC. Prior to the compaction the water mixed
samples were cured in sealed containers for 3 hours
as it is the sufficient time period for moisturehomogenization for crushed concrete aggregates [5].
Sample compaction was done using standard
compaction method within 25 blows in 3 layers instandard triaxial mould, 100 mm in diameter and
200 mm in height. Since cement fines are presented
in crushed concrete samples, it is required a specifictime period for strength gaining in the specimens.
Thus, the compacted samples were again cured insealed containers for 4 days to steady their strength.
Curing the RCA samples in hermetic boxes for 3
hours prior to the compaction and 4 days after thecompaction were found to be adequate to guarantee
the completion of strength gaining due to the cement
fines as well as other organic constituents [5]. In thecase of determining the performance characteristics,
the curing period is significance to expose theprecise responses of RCA specimens under cyclicloading.

The crushed concrete which is commerciallynamed ‘RM 001’ is the main material and obtained
from a leading concrete recycling plant in
Queensland, Australia. RM001 is produced as a purecrushed concrete aggregates by avoiding thepossible constituents such as asphalt, bricks, glass
and wood. In order to evaluate the performance of
RCA with and without the RAP, another threesamples were prepared by mixing 10%, 15% and
20% of RAP with RCA. The maximum percentage
of RAP was kept as 20% because it is the maximum
possible amount of RAP content that could be mixed
at the production process of RCA [3]. Table 1 shows
the names of the tested samples and percentage ofmaterial mixed by mass.
samples

13.2

Sample Preparation

MATERIAL USED

Table 1 New RCA
percentages

RM1-100/RAP0

Optimum
Moisture
Content %MaximumDry density(g/cm3)390

GEOMATE-Nagoya, Nov.13-15, 2013

samples are seen at the beginning of the cyclic loads.
It is noted that the capability to lower the
deformation by increasing the compaction effort at
the sample preparation on the four specimens. It issignificant that RM1-100/RAP0 and RM190/RAP10 exhibit almost similar values but on theother hand RM1-90/RAP10 has slightly lower valueof deformation than 100% pure crushed concrete.
The deformation curves of these two specimens in
Fig. 3 shows that the rapid deformation of RM190/RAP0 is slightly lower than RM1-100/RAP0 at
the initial loading cycles. This indicates that RM190/RAP10 sample is well compacted than RM1100/RAP0 specimen. The 10% RAP particles arecaused for appropriate gradation of the particles forbetter compaction and higher stiffness by soundinterlocking of the particles. Therefore the
combination of RM001, 90% and RAP 10% has
shown higher resistance for the repetitive load.

Fig. 1 Repeated load triaxial apparatus
RESULTS AND DISCUSSIONRLT test results aimed to characterize the resistanceof the specimens to the incremental plastic strain
responses and the resilient modulus (Mr) of the RCA
samples. Figure 2 shows a typical vertical stress vs.
axial strain behavior of a granular material after acertain number of load cycles at fixed loading andpressure condition [7].

Other two specimens had comparatively higher
deformation and the values have been increased withthe portion of RAP percentage. Further theincreasing rate of deformation also higher than the
RM1-100/RAP0 and RM1-90/RAP0. Increase of
RAP portion as 15% and 20% caused for the lack ofcoarser particles and led for lower stiffness of thecompacted specimens. In addition, the bitumen coataround the asphalt particles could be facilitated forfurther compression of the specimens withincreasing cyclic loading. The rapid deformations ofthese two samples also indicate higher values for the
initial load cycles. This specifies that the mixing
RAP more than 15% do not sustain for better
compaction with particles size distribution of thespecimens. However, having a higher deformation at
the beginning of load cycles is a common feature forthe four samples. Therefore this rapid deformation
could be minimized by applying a higher
compactive effort at the sample preparation.
Limitation of the rut depth in pavement constructionis the key aspect in pavement designing. The
prediction of rutting in flexible pavement isextremely complex since it is basically depend on
the quality of the base and sub base aggregates aswell as the environmental conditions. Therefore,
appreciate the nature of permanent deformation of apavement material is the foremost thing tounderstand and assess the behavior of materials inpavement rutting [8]. The overall results ofpermanent deformation of the four samples are lessthan 7mm for the 750 kPa loading pressure with 125
kPa confining pressure after 50000 loading cycles.
This is a satisfactory result and more tests arecontinuing to investigate the behavior of axial
deformation of RCA under different stressconditions.

Fig. 2 strains and resilient behavior of granularmaterials
Usually it can be observed a rapid accumulation ofplastic strain at the beginning of load cycles and theplastic response of the material becomes gradually
decreased and then stabilized. The elastic response
also gradually decreased as seen in the Fig. 2 and it
shows non linear behavior for the load repetitions.
However a stable resilient behavior can be observed
after a large number of load cycles [2]. The resultsof the RLT tests of this study have been discussed inaccordance with the above behavior of RCA
specimens.
Effect of RAP in RCA on Its Permanent
Deformation
Figure 3 shows the values of permanent deformationof the four samples. Rapid deformations of the four391

GEOMATE-Nagoya, Nov.13-15, 20137

Permanent deformation-mm

65
43
RM1-100/RAP0
2

RM1-90/RAP10
RM1-85/RAP15

1

RM1-80/RAP20

0
0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Loading cycles
Fig. 3 Permanent deformation values for 50000 cycles

Resilient Modulus- MPa

0
200
190
180
170
160
150
140
130
120
110
100

5

Reclaimed Asphalt Pavement %
10
15

20

180
182

182.9

175

Resilient Modulus values

100

95

90

85

80

Recycled Concrete Aggregates %Fig. 4 Resilient Modulus values after 50000 cycles

highly stress dependent and for the pavement
designing a representative Mr value should beselected according to the stress state for the selectedpavement structure and loading [9]. Figure 4 shows
the Mr values of four samples with the variation of

Effect of RAP in RCA on Its Resilient Modulus
The resilient modulus is a key property of granularmaterial characterization which indicates thestiffness and elastic response of aggregates. Mr is392

GEOMATE-Nagoya, Nov.13-15, 2013

RCA and RAP content after 50000 load cycles. They
have almost similar Mr values at the end of 50000
load cycles. But RM1-80/RAP20 shows slightly low
value of Mr and this makes a sign that the elastic
response of the RCA samples could be higher with
the increasing of RAP over 15%. Four samples also
show considerably high Mr values for 750kPa cyclicpressure. It can be noted that the compacted
materials perform higher stiffness and the elasticstrain becomes lower after 50000 cycles on thespecimens. This is a good sign for a pavement
material since higher resilient modulus values
indicate lower elastic responses of the materials for
cyclic loads.

International Journal of Geomechanics,
2006, pp. 279-289.
[3] Department of transpotr and main roads Q,
Australia,"Recycledmaterials
forpavements",
State of Queensland,
Department of Transport and Main Roads,
2011.
[4] Australia CoS, "Method 5.1.1: soil
compaction
anddensity
tests—
determination of the dry density/moisture
content relation of a soil using standard
compactive effort",
Standards Australia
International Ltd, Sydney, NSW 2001,
Australia, 2003.
[5] Jayakody S, Gallage C, A.Kumar,"Assessment
of
recycled
concreteaggregates for road base and sub-base",
Second international conference on
Geotechnique, Construction Materials andEnvironment - GEOMATE 2012, pp. 575579.

CONCLUSIONRLT tests were aimed to evaluate the RCA as it isused as unbound pavement material. On the basis of
the test results of this study following conclusions
are made.
• Modified RCA sample by mixing 10% RAP
shows the best performance with lowest
permanent deformation• High percentage of RAP as 15%, 20% lead forlower stiffness of the RCA and show higher
permanent deformations• After 50000 loading cycles the deformation is
not resilient in four samples and permanent
deformation is acceptable for more load
repetitions. These materials could reach the
failure for a great number of load repetitions• It is seen that resilient modulus is not
significantly affected by the RAP content if theamount of RAP in RCA is equal or less than
15%. However, further increase in RAP
content (e.g: 20%) cause to decrease in resilient
modulus of RCA samples. Therefore the elastic
response could be higher when increasing the
RAP content over 15%[6] Department of transpotr and main roads Q,
Australia, "Permanent deformation andresilient modulus of granular unboundmaterials",
The state of Queensland,
Department of transport and main roads,
2012.
[7] United State Department of Transportation
FHA, "Geotechnical Engineering ", 2011.
[8] Lekarp F, Dawson A, "State of the art. II:
Permanent strain response of unboundaggregates", Journal of transportationengineering, Vol. 126, 2000, pp. 76-83.
[9] Jameson G, Vuong B, Moffatt M et al.,"Assessment of rut-resistance of granularbases using the repeated load triaxial test",
Austroads Limited, Sydney, New South
Walse, Australia, 2010.

Further studies are continuing to investigate theresilient behavior and permanent deformation of
RCA with respect to the number of load repetitions,stress levels, and moisture content and the results
will be published in future.
REFERENCES[1] Lekarp F, Dawson A, "Modelling
permanent deformation behavior ofunbound granular materials", Construction
and Building Materials, Vol. 12, 1998, pp.
9-18.
[2] Chazallon C, Hornych P, Mouhoubi S,"Elastoplastic model for the long-term
behavior modeling of unbound granularmaterials
inflexible
pavements",

393

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

BEHAVIOR OF PENETRATION AND LEACHING OF CESIUM
IN MORTAR HAVING VARIOUS FINE AGGREGATES AND
MOISTURE CONTENT
Masashi ITO1, Kenichiro NAKARAI1 Akihiko HAYASHI1 and Kenji KAWAI1
1
Graduate School of Engineering, Hiroshima University, Japan

ABSTRACTThe accident at the Fukushima Daiichi Nuclear Power Plant resulted in spreading a huge amount of theradioactive cesium (cesium-137) widely. It is important to decontaminate the radioactive cesium and dispose theradioactive waste safely as soon as possible. This study aims to investigate the basic behaviors of the cesium-133
in mortar such as adsorption, penetration and leaching. From the experimental results, it was observed that thecesium was hardly adsorbed on the cement hydrates as well as lime sand and silica sand prepared as aggregate inthis study. In the penetration test, in the water-saturated mortar specimens, around 80% of the penetrated cesiumin the whole area of specimens was soluble. On the other hand, in the dried specimens, 80% of the penetrated
cesium was soluble only in the inner area of the specimen. In the surface, 60% of the cesium was soluble. It wasthought that the surface of the dried specimens were carbonated during the drying process before the penetration
tests, and then fixed more cesium.
Keywords: Cesium, Adsorption, Penetration, Leaching, Zeolite

the experimental installation, the non-radioactive
cesium (cesium-133) was used in this study.

INTRODUCTION
The accident at the Fukushima Daiichi Nuclear
Power Plant caused by the Great East Japan
Earthquake resulted in spreading a huge amount ofradioactive cesium widely [1]. The cesium-137 has a
half-life of thirty years and remains longer thanother main radioactive substances released by theaccident. We need to decontaminate the radioactive
cesium appropriately.
Disposing a huge amount of radioactive wastethat resulted from decontamination has been also
problems. It is necessary to prevent radioactive
waste from scattering and diffusion to theenvironment again during transportation and storage.
From the above, it is demanded to investigate thebehavior of the cesium in concrete. To discuss the
behavior of the cesium in concrete, the sorption
properties for cement materials have already been
investigated by several researchers [2]. However, thestudies on the mass transfer considering the time
histories of moisture contents in the concrete undercyclic drying and wetting conditions are very few.
Therefore, this study aims to investigate thecesium behaviors such as adsorption, penetration in
the cyclic dying and wetting conditions, andleaching from mortar. Because of the limitation of

EXPERIMENT METHODS
Materials
The materials used in this experiment wereordinary Portland cement (the density was 3.16
g/cm3 and the chemical composition is shown in
Table. 1), unwashed lime sand (the density insaturated surface-dry condition was 2.68 g/cm3 andthe water absorption was 1.46 %), washed lime sandand zeolite. The zeolite prepared in this study was
the synthetic mordenite, which was reported toadsorb a large quantity of the radioactive cesium [3],[4]. In the adsorption test, silica sand (the density insaturated surface-dry condition was 2.64 g/cm3 andthe water absorption was 0.18 %) was also used. The
commercially available cesium-133 chloride wasused.
Specimens
The mortar specimens with different fineaggregates were used in the penetration and leaching
tests. The fine aggregates were the unwashed lime

Table. 1 Chemical composition of cement394

GEOMATE-Nagoya, Nov.13-15, 2013

Table. 2 Mixture proportion of mortar specimens(a) Penetration test

W/C
0.60

Water
430

Unit content kg/m3
Cement
Sand
872
717
918

Zeolite06.8(b) Leaching test
W/C

Water

0.45

386

0.60

430

Unit content kg/m3
CementSand
Zeolite
918
0
858
872
6.8
918
0
717
872
6.8

CsCl
6.5
7.2

Table. 3 Ponding and drying condition

sand, the washed lime sand, and the unwashed lime
sand partially replaced by zeolite (5 % in volume).
For the penetration test, the above materials andwater were mixed mechanically at the water-cement
ratio of 0.60, and then the mortar was casted inmolds of 40×40×160 mm. After 24 hours, specimens
were demolded and cured in the high humid
condition for 28 days. The mix proportions of mortar
specimens were shown in Table. 2 (a).
The specimens for the leaching test, wereprepared in the similar manner to that for the
penetration test, but we used 0.1 mol/L of cesium
chloride solutions as the mixing water of the mortar
specimens. The water-cement ratios were 0.45 and0.60 and the mortar was casted in molds of
40×40×40 mm. The mix proportions of mortar
specimens were shown in Table. 2 (b).

One gram of samples including cement paste
powder was added in 20 mL of deionized water, andthen they were stirred for 10 hours to stabilize pH.
After that, 1mL of the cesium chloride solution wasadded, and then stirred for 6 more hours again. In
this test, 5, 10 and 15 g/L of cesium chloride
solutions were added (the initial cesium
concentration were 0.0018, 0.0036, and 0.0054
mol/L, respectively). After stirring, the solution was
filtrated with a membrane-filter and the equilibrium
concentration of cesium in the solution wasmeasuredbyanatomicadsorption
spectrophotometer.
Measurement of pore size distribution
In the measurements, the total porosity and thepore size distribution were measured by mercury
intrusion
porosimetry(MIP).
Beforethemeasurements, the mortar specimens with W/C=0.45
and 0.60 at the age of about 64 days (cured in highhumid condition) were cut by an oil cutter andcrushed with a hammer to become less than 1 cm ingrain size. The crushed specimens were ponded in
acetone and dried by the vacuum deaeration. The
measurement range of pressure was 0.01~413 MPaand the diameter was 0.003~121 µm.

Adsorption test
The samples used in the adsorption test were
cement paste powder with a water-cement ratio(W/C) of 0.40 (hand mixed, and cured for 28 days)
and fine aggregates such as unwashed lime sand,washed lime sand, silica sand and zeolite. Those
samples were pulverized to smaller than 75 μm. In
addition, the mixed samples that consist ofequivalent amount of cement paste powder and fineaggregates were prepared.
395

GEOMATE-Nagoya, Nov.13-15, 2013

Penetration test
In the penetration tests, two types of specimens
with different moisture contents, saturated and dried
specimens, were prepared. The saturated specimens
were prepared with vacuum saturation technique [5],while the dried specimens were dried to be constantweight in the conditions of 20 °C and 60 % RH. Fivesurfaces of each specimen were coated with epoxy
resin before the test in order to discuss onedimensional penetration behavior.
The ponding and drying condition during thepenetration test is shown in Table. 3. The specimens
were ponded in 0.1 mol/L of the cesium chloride
solutions or the deionized water. After that, thespecimens were cut into slices of 2.5 mm inthickness from the exposure surface by an oil cutter,and pulverized in order to measure the distributionof total and soluble cesium. The measurement of thequantity of cesium in every sample was conductedbased on “Methods of test for chloride ion content inhardened concrete” (JIS A 1154). The total cesium
was derived by nitric acid and the soluble cesium
was derived by hot water of 50 °C. The
concentration of cesium in the solution wasdeterminedwithanatomicadsorption
spectrophotometer.

Fig. 1 The results of adsorption test

The mortar specimens were placed in a tankfilled with the deionized water. The deionized water
volume was 480 mL, which was equated to 5 mL per
100 mm2 of the surface area of the specimen. The
tank was capped to avoid the evaporation of thewater and the carbonation of the specimen. The
deionized water was renewed at the periods of 0.25,
1, 2.25, 4, 9, 16, 25, 36, 49 and 64 days. After that,the solution was filtrated with a membrane-filter andthe concentration of cesium was measured by anatomic adsorption spectrophotometer.

The distribution ratio is the ratio of theconcentration in the solid-phase to the concentrationin the liquid-phase. For example, the highdistribution ratio at the same initial concentration of
the solution means that cesium was adsorbed by thematerials easily. From Fig. 1, it was found that the
distribution ratios were around 1 mL/g for cement
paste powder and 2~4 mL/g for fine aggregates,
respectively. On the other hand, the distribution ratioof zeolite was approximately 1×105 mL/g, and it wassignificantly higher than those of cement paste
powder and fine aggregates.
The distribution ratios for unwashed and washedlime sand were almost same although the decrease in
the distribution ration by the washing was expected.
It was thought that pulverizing might relatively
decrease the influence of the fine grains in theunwashed lime sand on the adsorption.
The equilibrium concentrations in the liquidphase of the samples including zeolite were too low
to be measured accurately. Although the values ofthe distribution ratios should be used as a guide, it
can be said that a large amount of cesium could be
adsorbed on zeolite.

RESULTS AND DISCUSSION

Measurement of pore size distribution

Adsorption test

The results of measurement of the total porevolume, and pore size distribution of the mortar
specimens with W/C=0.45 and 0.60 are shown in
Figs. 2, 3, and 4. From Fig. 2, it was observed thatthe specimens with W/C=0.60 had larger total porevolume than the specimen with W/C=0.45 regardlessof the kinds of the fine aggregates. Figs. 3 and 4
indicate that the specimens containing zeolite had
the largest total pore volume with the increase in the
cumulative pore volume in the range of pore size of
0.01~0.1 μm. Especially, the increase in the porevolume was significant in the specimen with
W/C=0.60.
Regarding to the effect of the washing of thesand, the clear differences in the pore size

Leaching test

The results of the adsorption test are shown in
Fig. 1. The distribution ratio K d calculated by Eq (1)was used to discuss the cesium adsorptivity of thesamples [6].

Kd =V C0 − C
×
M
C

(1)

where V: volume of liquid (mL)
M: mass of samples (g)C 0 : initial concentration (mol/L)
C: equilibrium concentration (mol/L)

396

GEOMATE-Nagoya, Nov.13-15, 2013

Fig 2 The cumulative pore volumes

Fig. 3 The distribution of pore volume (W/C=0.45)

Fig. 4 The distribution of pore volume (W/C=0.60)

distributions and the cumulative pore volumes were
not observed between the specimens containing
unwashed and washed lime sands.

surface.
As for the dried specimens [D (P)], in the innerarea of the specimen, 80 % of the penetrated cesium
was soluble. On the other hand, large amounts of thecesium were fixed as insoluble at the surface, where
60 % of the total cesium was soluble. It was reported
that the distribution ratio of cesium in carbonatedpart was 1.5 times as much as non-carbonated part[7]. From the above, it was thought that the surfaceof the dried specimens were carbonated during thedrying process before the penetration tests, and thenfixed more cesium.
For the transportation of cesium during ponding
and drying processes, the total quantity of cesium
increased at the surface of specimen, and decreased
at 6~12 mm from the surface for the specimen [D(P-D)] compared with the specimen [D (P)] during
the drying process. It was thought that solublecesium in the inner area were transported to thesurface with dissipating of water, and adsorbed
during the drying process. The quantity of cesium
increased at near 8 mm from surface of the specimen
for the specimen [D (P-D-P)] again. It was also
thought that a part of insoluble cesium which was
fixed at the surface became soluble, and wastransported to the inner area with water penetration
when the specimen was ponded in the deionizedwater.

Penetration test
First, as the results of the penetration test of thespecimen containing the unwashed lime sand, thedistributions of the measured total and solublecesium from the exposure surface of the specimens
are shown in Fig. 5. The distribution of the total
cesium showed that the cesium penetrated to thedeeper area in the saturated specimen than in thedried specimen. It was because the ponding periods
were 28 days, which was longer than that of thedried specimens. The apparent diffusion coefficientsof the saturated specimens were about 1×10-7 cm2/s
and those of the dried specimens [D (P)] were about
1×10-6 cm2/s. Since they were calculated based on
Fick’s laws of diffusion, the apparent diffusion
coefficients of the dried specimens [D (P)]significantly increased by the effect of advection. Itmeans that the cesium penetrates to the dried
specimens deeper than the saturated specimens when
the ponding periods were same.
Regarding the solubility of the penetrated cesium,
80 % of the penetrated cesium was soluble not onlyin the inner area of the specimen but also at the397

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 5 The distribution of total andsoluble Cesium (UL)

Fig. 6 The distribution of total andsoluble Cesium (WL)

Fig. 7 The distribution of total andsoluble Cesium (Zeolite)

Fig. 8 The result of leaching test

Next, the results of the specimen containing thewashed lime sand were shown in Fig. 6. The trend of
penetration for the specimen containing washed lime
sand were similar to the specimen containing
unwashed lime sand, while the total quantity ofcesium increased.
Finally, the results of the specimen containing
zeolite were shown in Fig. 7. The profiles of thepenetrated cesium were almost similar with the otherspecimens. However, the quantity of cesium did notincrease at near 8 mm from surface of the specimen
for the specimen [D (P-D-P)]. It was caused by thezeolite’s high adsorption reducing the transportationof cesium to the inner area associated with theadvection.

specimens with W/C=0.45 regardless of fineaggregates because the specimen with W/C=0.60
had larger total pore volume as seen in Fig. 2, andthe internal structure was porous.
About the differences in the fine aggregates, theleaching ratio of the specimen containing washedlime sand was higher than that of the unwashed lime
sand because of the high specific surface area of thesmall particle lime sand. In addition, the leachingratio of the specimen containing zeolite was equal or
lower than that of unwashed lime sand in spite of theresult that the specimen has the largest total porevolume. It is considered that adsorption performanceof the zeolite reduced the leaching ratio for the
specimen containing zeolite.

Leaching test

CONCLUSIONSAs results of the leaching test, the leaching ratio
are shown in Fig. 8. The leaching ratio was thepercentage of the cumulative amount of cesium
leached from a specimen to the amount of total
cesium. The amount of total cesium was the amountof cesium contained in a specimen at the time of test
start, calculated by mixture proportion. The leachingratios of specimens with W/C=0.60 were higher thanIn this study, we investigated the cesium
behaviors in the mortar such as adsorption,
penetration in the cyclic dying and wetting
conditions, and leaching by using cesium-133. As aresult, it was found that the cesium was hardly
adsorbed on the cement paste powder and fineaggregates, while significantly adsorbed on zeolite.

398

GEOMATE-Nagoya, Nov.13-15, 2013

In the penetration test, around 80% of
penetrated cesium was soluble in the surface andinner area of saturated specimens. On the other hand,in the dried specimens, 60% of the penetrated
cesium was soluble in the surface. We thought thatlarge amounts of the cesium were fixed as insolubleat the surface, and it was caused by carbonation of
the specimen. In the inner area of the dried
specimens, 60% of the penetrated cesium was
soluble.
The leaching ratios of the specimens with
W/C=0.45 and 0.60 were 30~40 % and 50~60%,
respectively, and the leaching ratio of cesium was
high.
From the study, it was found that the cesium
was transported with the water penetration or
dissipating in the cyclic dying and wetting
conditions.

Reactor and Nuclear Fuel Development
Corporation, PNC TN8410 97-258, 1997, p.40
[3] National Environmental Research Institute,“Proper waste disposal behavior of radioactive
materialfromtechnical
documentation
version3”, December, 2012, pp.43-44
http://www.nies.go.jp/shinsai/techrepo_r3_1212
20.pdf[4] Ogawa M., “Zeolite”, Journal of the Japan
Research Association for Textile End-Uses,
Vol.24, No.7, 1983, pp.293-302[5] Watanabe H., et al, “Effect of vacuum
saturation method for concrete specimen on
results of rapid chloride permeability test”,
Proceedings of annual meeting of Japan Societyof Civil Engineers, Vol.57, No.5, 2002,
pp.1057-1058[6] Sugiyama D., “Experimental measurements andintegrated modeling studies of actinide sorption
onto cement”, CRIEPI report T02025, April,
2003, p.3
[7] Mochizuki M., et al, “Effect of Carbonation ofConcrete on the Distribution Coefficient of Cs
and Co”, Atomic Energy Society of Japan,
Autumn convention proceedings 1991, p.569

REFERENCES[1] Digital Japan, “Extension site of distribution
map of radiation dose, etc.”
http://ramap.jmc.or.jp/map/eng/[2] Mine T., et al, “Adsorption tests of Iodine andCesium in various cementitious material” Power

399

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECTS OF COARSE AGGREGATE CONTENT ON THE EROSIONRATE OF CONCRETE DUE TO SULFURIC ACID ATTACK
Yuji Hatano1, Yutaka Okame1 and Kenji Kawai1
1
Hiroshima University, Japan

ABSTRACTThe deterioration of concrete structures caused by sulfuric acid attacks has been serious. However, aprediction method for concrete deterioration due to sulfuric acid attack has not been established yet. In thisstudy, the effects of the coarse aggregate content on sulfuric acid deterioration of concrete were
investigated. In the experiment, the coarse aggregate content and water cement ratio of concrete werevaried and concrete specimens were immersed in two different concentrations of sulfuric acid solution (1mol/L, and 2 mol/L). The erosion depth, mass loss and neutralization depth were measured at fixed periods.
The results showed that the increase in the coarse aggregate content led to the decrease in the rate ofsulfuric acid deterioration of concrete. Coarse aggregate was found to contribute to preventing the removalof gypsum produced by the reaction of sulfuric acid with calcium compounds.
Keywords: Sulfuric acid attack, Coarse aggregate, Erosion depth, Mass loss, Neutralization depth

concrete specimens were used, the effect of coarse
aggregate on the deterioration was barely
considered. For this reason, it is hard to apply the
results of previous studies to the prediction of thedeterioration of existing concrete structures. It isnecessary to consider the effect of coarse
aggregate on the deterioration in order to apply
the results of previous studies using mortar toexisting concrete. In this study, using two
different concentrations of sulfuric acid solutions,the effect of coarse aggregate on the erosion of
concrete and the sulfuric acid penetration into theconcrete was investigated.

INTRODUCTION
There are various acid solutions that cause
chemical deterioration of concrete, and aparticular attention has been paid to sulfuric acid.
Recently, the deterioration of concrete caused bysulfuric acid attacks in sewage and waste water
treatment plants has been reported. In sewage andwaste water treatment plants, sulfuric acid isgenerated by microorganisms, and this causes
sulfuric acid deterioration of concrete. However, aprediction formula of sulfuric acid deterioration of
concrete is not yet established. In the previous
studies1,2,3), it was reported that the deteriorationof concrete due to sulfuric acid is affected by theconcentration of sulfuric acid and the water
cement ratio of concrete. However, most of theexperiments were carried out using cement paste
and mortar specimens. Even in the case where

Names
G0
G17
G35
G50
G0
G18
G37
G50

W/C

0.40

0.55

EXPERIMENTAL OVERVIEW
Materials
Normal Portland cement (density: 3.16 g/cm3;

Table 1 Mix proportion of concrete specimens.
Unit Content(kg/m3)
W
C
S
G
AE
266
664
1146
0
3.3
220
549
949
452
2.8
174
435
751
905
2.1
132
332
573
1310
1.7
274
498
1253
0
2.5
224
407
795
479
2.0
174
316
795
958
1.6
137

249

626
400

1310

1.3

Thickener
0.3
0.2
-

G/V
0
17
35
50
0
18
37
50

GEOMATE-Nagoya, Nov.13-15, 2013

100mm

Initial surface
Eroded area

100mm

The cutting
surface was
exposed tothe sulfuric
acid
solution.

400mm
Cured in water for 27 daysac

Uncolored area byphenolphthaleinbColored area byphenolphthaleina:Erosion depth
b:Neutrallization
thickness
c:Neutrallizaion
depth

Coated withacidresistantPhenolphthalein

Fig. 1 Schematic diagram of the specimen

Fig. 2 Schematic diagram of deterioration depth

specific surface area: 3360 cm2/g), crushed sand(saturated and surface-dry density: 2.60 g/cm3;
absorption 1.06 %), crushed stone (saturated andsurface-dry density: 2.62 g/cm3; absorption
0.69 %) were used as cement, fine aggregate, andcoarse aggregate, respectively. In addition, athickener (methyl cellulose type) was used todisperse coarse aggregate homogeneously inconcrete when the volume ratios of coarse
aggregate in concrete were 17 % and 18 %.

water for 1 day in advance to prevent rapid
penetration of sulfuric acid due to water
absorption.
Immersion test
Specimens were immersed in sulfuric acidsolution at concentrations of 1 mol/L and 2 mol/L.
The concentration of the solution was measured
periodically, and the concentration was adjusted
by adding sulfuric acid every week.

Mix proportion of specimens

Measurement

The mix proportion of concrete used in thisstudy is shown in Table 1. The water cement
ratios of concrete are 0.55 and 0.40, and thevolume ratios of the coarse aggregate in concrete
are 0 %, 18 % (17 %, in the case of W/C=0.40),
37 % (35 %, in the case of W/C=0.40), 50%.
Based on the mix proportions for G35(W/C=0.40) and G37 (W/C=0.55) concretes, thevolume ratios of water, cement, and fineaggregate in concrete were kept constant so as not
to change the properties of mortar.

Mass loss
The mass loss of a specimen was measured atfixed periods. The mass loss was defined positive
when the mass of the specimen became smaller
than the initial mass.
Erosion depth
The erosion depth is the difference between theinitial length and measured length of the specimen.
The length of each specimen was measured atgiven 4 points at fixed periods. The erosion depth
was defined negative when the specimen was
expanded because of reaction products.

Outline of specimens
Figure 1 shows the outline of specimens.
Prismatic
concrete
specimens
measuring
100×100×400 mm in size (W/C=0.55, 0.40) wereprepared and demolded after 24 hours, and cured
in water for 27 days. At the age of 28 days, thespecimens were cut into three pieces. These
pieces were then coated with acid resistant acrylic
epoxy, except for one cutting surface exposed tothe sulfuric acid solution. Before the following
immersion test, the specimens were immersed in

Neutralization depth
After being immersed for a fixed period,
specimens were split into two pieces andphenolphthalein solution was sprayed on the
cross-section. The length of the uncoloured area
was measured and the sum of that length and the401

GEOMATE-Nagoya, Nov.13-15, 2013

1000

1400

G0

G0
G17

G37
600

Mass loss(ｇ)Mass loss(ｇ)

G18

G50

200

1000

G35
G50

600

200
0

50

100

150

0

Immersion duration(days)-200(a) 1.0mol/L W/C=0.55
1400

1400

150

G0
G17

G18
G37

Mass loss(ｇ)Mass loss(ｇ)100(b) 1.0mol/L W/C=0.40

G0

1000

50

Immersion duration(days)

-200

G50
600

200

1000

G35
G50

600

200
0

-200

50

100

Immersion duration(days)

150

0

50

(c) 2.0mol/L W/C=0.55

100

Immersion duration(days)

-200

150

(d) 2.0mol/L W/C=0.40

Fig. 3 Relationship between immersion duration and mass loss
different in the water cement ratio ofconcrete and the concentration of sulfuric
acid solution.

erosion depth of the same specimen was definedas neutralization depth.
EXPERIMENTAL RESULTS

Erosion depth
Mass Loss
Figure 4 indicates the relationship between
immersion duration and erosion depth. In all cases,
the specimen for G0 began to be eroded earlier
compared with the other specimens. For specimens
other than G0, the time when the specimen began tobe eroded was different. The larger the coarse
aggregate content, the later the erosion starts. The
Erosion depth for G0 increased almost linearly withtime, while the erosion depth for others seems toincrease in a stepwise manner. Although the value
shown in Figure 4 is the average of three different
specimens, the raw data measured at given four
points of the specimen for G0 with W/C=0.40
immersed in 1.0 mol/L and for G35 with W/C=0.55
immersed in 1.0 mol/L are shown in Figure 5 Fromeach data in this figure, a linear increase for G0 anda stepwise increase for G35 can be also confirmed.
When a space between coarse aggregates is small, it
is thought that the aggregates keep gypsum produced

Figure 3 indicates the relationshipbetween the immersion duration and mass
loss. From this figure, the mass loss for G0
is the largest in all cases. The mass loss forG50 having the highest coarse aggregate
content is becoming gradually larger thanthat for G37 in the case of W/C=0.55. It issuggested that coarse aggregate could
control the mass loss of concrete due to thesulfuric acid attack. However, little
difference can be seen in the mass losses
for G35 and G50 (W/C=0.40) immersed in
1.0mol/L of sulfuric acid solution and forG37 and G50 (W/C=0.55) in 2.0mol/L. The
effect of the coarse aggregate content on
the sulfuric acid deterioration could be402

GEOMATE-Nagoya, Nov.13-15, 2013

60

40

G0
G17
G35
G50

50

Erosion depth(mm)50Erosion depth(mm)

60

G0
G18
G37
G50

30
20
10

40
30
20
10
0

0
0

50

100

50

0

150

(a) 1.0mol/L W/C=0.55
60

30
20
10
0
0

G0
G17
G35
G50

50

Erosion depth(mm)Erosion depth(mm)

40

50

100

150

(b) 1.0mol/L W/C=0.40
60

G0
G18
G37
G50

50

100

Immersion duration(days)

Immersion duration(days)

40
30
20
10
0

150

0

50

100

150

Immersion duration(days)

Immersion duration(days)(c) 2.0mol/L W/C=0.55(d) 2.0mol/L W/C=0.40

Fig. 4 Relationship between immersion duration and erosion depth

35

45Erosion depth(㎜)Erosion depth(㎜)

45

G0-1
G0-2
G0-3
G0-4

25
15
5
-5 0

50

100

35
25
15
5
-5 0

150

Immersion duration(days)(a)1.0mol/L W/C=0.40 G0

G35-1
G35-2
G35-3
G35-4

50
100
Immersion duration(days)

150(b)1.0mol/L W/C=0.55 G35

Fig. 5 Erosion depth at every measuring point of specimen
by sulfuric acid and retard the erosion of concrete.
This could be the reason why the time when thespecimen began to be eroded is different anddelayed for the specimen having larger coarse
aggregate content, and the erosion depth increases ina stepwise manner instead of linear.

defined as an increment of the erosion depth after
the specimen began to be eroded. The regression
line for each specimen is shown in Figure 6 andthe value in this figure represents the erosion rate
(mm/day). Figure 7 shows the relationshipbetween the coarse aggregate content and erosion
rate. The larger the coarse aggregate content, thesmaller the erosion rate, although the erosion rates
for G50 with W/C=0.40 immersed in 1.0 mol/Land with W/C=0.55 immersed in 2.0 mol/L arelarger than those for G35 with W/C=0.40

Erosion rate

Based on the results of the erosion depth, theerosion rate was calculated. The erosion rate is403

GEOMATE-Nagoya, Nov.13-15, 2013

G0
G18
G37
G50

Erosion depth(mm)

50
40

60

30
20

0.133

10

0.129
0.126
0.034

0
0

G0
G17
G35
G50

50

50

100

Erosion depth(mm)

60

40
30
20

0.150

10

0.093
0.138

0
0

150

50

(a) 1.0mol/L W/C=0.55
60

0.343

30

0.211
0.184
0.159

20
10
0
0

50

100

G0
G17
G35
G50

50

Erosion depth(mm)Erosion depth(mm)

40

150

(b) 1.0mol/L W/C=0.40

G0
G18
G37
G50

50

100

Immersion duration(days)

Immersion duration(days)

60

0.236

40

0.435
0.384

30

0.334

20

0.272

10
0

150

0

50

100

150

Immersion duration(days)

Immersion duration(days)(c) 2.0mol/L W/C=0.55(d) 2.0mol/L W/C=0.40

Fig. 6 Regression line for Erosion depth
0.6

Neutralization depth

2.0mol/L (W/C=0.40)

Erosion rate (mm/day)

2.0mol/L (W/C=0.55)
1.0mpl/L (W/C=0.40)

Figure 8 indicates the results of neutralization
depth. The larger the coarse aggregate content, thesmaller the neutralization depth. This result alsosuggests that the existence of coarse aggregate
contributes to controlling neutralization.

1.0mol/L (W/C=0.55)

0.4

0.2

CONCLUSIONS
0
0

10

20

30

40

(1) The coarse aggregate content affects thedeterioration of concrete due to sulfuric acidattack.
(2) The increase in the coarse aggregate content
leads to the decrease in the sulfuric aciddeterioration of concrete.
(3) The increase in the coarse aggregate content
also reduces the erosion rate in the sulfuric aciddeterioration of concrete.
(4) The effect of the coarse aggregate content on
the deterioration differs in the water cement rationof concrete and the concentration of sulfuric acidsolution50

Coarse aggregate content(vol.%)

Fig. 7 Relation between coarse aggregate
content and erosion rate
immersed in 1.0 mol/L and G37 with W/C=0.55
immersed in 2.0 mol/L, respectively. There is apossibility that the optimum coarse aggregate
content can exist to control the erosion of concrete.
effect and the control effect was became constantor degraded over define coarse aggregate content.

404

GEOMATE-Nagoya, Nov.13-15, 201330

Neutralization
thickness
Erosion depth

168days

84day

50
Neutralization depth（㎜）Neutralization depth（㎜）

40

20
10
0

G0
-10

G18

G37

G50

G0

G17

G35

G50

168days
40
30
20
10
0

G0

W/C=0.55

Neutralization
thickness
Erosion depth

84daysG18

W/C=0.4

G37

G50

G0

W/C=0.55(b) 2.0mol/L(a) 1.0mol/L

G17

G35

G50

W/C=0.4

Fig. 8 Neutralization depthof The Japan Concrete Institute. Vol. 23, No. 2,
2001, pp. 469-474.
[3] Kurashige I, “Mechanisms of Scaling-off ofHardened cement paste due to sulfuric acidattack”, Cement Science and Concrete
Technology, No. 55, 2001, pp. 458-464[4] Hisada M, “Progression of Deterioration ofHardened Cement under Sulfuric Acid
Environment”, Journal of Materials, Concrete
Structures and Pavements, Vol. 64, No. 3, Aug.
2008, pp. 449-459.REFERENCES[1] Terabayashi A, “A study about the influencewhich sulfuric acid density gives to thedeterioration of concrete”, Progression of The
Japan Concrete Institute, Vol. 29, 2007, pp. 921926.
[2] Kurashige I, “Effect of Cement Hydration
Products and Microstructure of Concrete on theResistance to Sulfuric Acid attack”, Progression

405

Third International Conference on Geotechnique, Construction Materials and

GEOMATE-Nagoya,Nov.13-15,
2013
Environment, Nagoya,Japan, Nov.
13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STUDY ON PHYSICAL PROPERTIES AND USABILITY OF SOMESELECTED RECYCLED FINE AGGREGATESMohammad Raihanul ISLAM1, Satoru ISHIGURO2
Doctoral Student, 2Faculty, Graduate School of Bioresources, Mie University, Japan.

1

ABSTRACTThe study was accomplished to know the usability of the experimental recycled aggregates through physicalproperties, lightness, skid resistance and light irradiation behavior. The saturated and dry density of the slag
aggregates (2.64 g/cm3 & 2.6 g/cm3) was highest and the roof tiles (2.27 g/cm3 & 2.13 g/cm3) was the lowest
among the experimental recycled aggregates. Roof tiles aggregates absorbed highest percentage of water(6.61%) and the lowest absorption showed the glass aggregates (0.02%). The highest increased inside andsurface temperature showed the slag aggregate made sample block and the lowest showed the ceramic aggregate
block during the light irradiation test. The skid resistance test value was in between 75 to 83 for the all test
aggregate block. According to the color test result ceramic block will reflect most of the light and holdminimum; slag block will hold the maximum. The test results of the recycled aggregates were satisfactory andsometimes better in compare with the standard aggregate sand test results.
Key Words: Recycled Aggregates, Physical Properties, Lightness, Skid Resistance and Light irradiation.
aggregate. The main objective of this study was toinvestigate the physical properties of the selected
recycled aggregates, making mortar to test theirlightness, light irradiation motive and skid resistancefor understanding the usability of the selected
recycled aggregates.

INTRODUCTION
In the recent years, industrial and constructionwastes become a big problem because of their risky
and expensive management system. On the other
hand the demands of the construction materials are
increasing day by day. This increasing demand iscreating pressure on environmental sustainability. To
save the environment and to continue the present
construction activities in the world, use of recycle
construction aggregates can play a vital role.
In Japan, the treatment and disposal of municipal
solid waste (MSW) come under the jurisdiction of themunicipality where it is generated, and it is thecommon practice to incinerate the waste and landfill
the subsequent residue (bottom and fly ash, etc.) [1].
Japan produced glass and ceramic wastes of 10947
thousand ton in 2005, 11004 thousand ton in 2006,
11461 thousand ton in 2007 and 8776 thousand ton in2008. There also produced slag wastes of 4555
thousand ton in 2005, 4922 thousand ton in 2006,
5183 thousand ton in 2007 and 6174 thousand ton in2008 [2].
Fukushima, Miyagi and Iwate prefecture generated
320 and 11 times larger amount of wastes in comparewith their usual waste generating amount due to thegreat east Japan earthquake in 2011 [3].
Recycling of ceramic and glass wastes is achallenge for the electric power generationcompanies worldwide. In the year 2009, The Kansai
Electric Power Co. Inc. generated 3,100 ton of glass
and Ceramic wastes those they use as insulator andother purposes [4].
A number of research studies have completed andcontinuing in the field of recycled construction

MATERIALS AND METHODS
The investigation was accomplished with four
recycled fine aggregates; ceramic, roof tiles, glassand slag aggregate and a traditional standard fineaggregate sand.
Sand: River bed sand with size 0-5 mm was usedin this study.
Ceramic Aggregates: The ceramic tiles aggregateswere collected from Yamamura Co. Matsusaka City,
Japan. Size of the recycled ceramic aggregates in thisstudy was 0-3mm.
Roof Tiles Aggregates: The roof tiles aggregateswere collected from Manen Co. Tsu City, Japan. This
recycle center producing roof tiles aggregates bycrushing used roof tiles. Size of the recycled roof tiles
aggregates in this study was 0-3mm.
Glass Aggregates: The used glass aggregates werecollected from Yamamura Co. Matsusaka City, Japan.
Size of the recycled glass aggregates in this study
was 0-2.5mm.
Slag Aggregates: The used Slag aggregates werecollected from Yokkaichi City, Mie, Japan. Size ofthe recycled slag aggregates in this study was 0-5mm.
To achieve the objectives of the investigation thebasic physical parameters of the above mentioned
recycled aggregates were determined with standard
methods.

406

GEOMATE-Nagoya, Nov.13-15, 2013

the temperature adjustment with the room
temperature. The beam lamp Irradiation was
continued on the sample block for four hours. The
data logger was received data for 24 hours and stored.

Sieve Analysis
Sieve analysis was accomplished according to the“JIS A 1102: Method of test for sieve analysis
of aggregates” [5].

Skid Resistance Test
The test was performed by using British Pendulum
Tester. The experiment was accomplished byfollowing the “ASTM E 303: Standard Test Method
for Measuring Surface Frictional Properties Using the
British Pendulum Tester” [9].
RESULTS AND DISCUSSIONS
Sieve analysis
The results of sieve analysis were expressed asfineness modulus (FM) and as graphical presentation
by gradation curve. The fineness modulus of sand,roof tiles, ceramic, slag and glass were 3.1, 2.9, 3.0,
4.0 and 3.4 respectively. The limit of the finenessmodulus of fine aggregates is 2 to 3.5[10].

Passing by mass in (%)

100
Fig.1 Shape of the standard gradation curve [6]Dense and well-graded aggregates are desirable formaking concrete, gap-graded aggregates can makegood concrete, for the uniform grading, only a few
sizes dominate the bulk material, The open graded
contains too much small particles and easy to be
disturbed by a hole [6].

60
40
20
0

Test of Density and Absorption
The aim of the experiment was to determine thesaturated density (d s ), oven dry density (d d ) andabsorption of the fine aggregates. The experimentfollowed the instructions of “JIS A 1109: Method of
test
for density and water
absorption offine aggregates” [7].

Sieve opening size (mm)Fig.2: Gradation
aggregates

curve

of

the

experimental

According to the above gradation curve sand canbe defined as uniformly graded when ceramic tiles
and glass aggregates can be defined as well graded,slag was dense graded and the roof tiles aggregate
was gap-graded[6]. The recycle slag, ceramic tiles
and glass aggregates were desirable for making
concrete. As gap-grading aggregates have lacks of
one or more intermediate size, roof tiles could be use
to prepare concrete with relatively low workability
and with high workability, segregation might beoccurred and that could make problem.

Color Test
This test was performed with Digital Color Reader(CR -13, Konica Minolta Optics Inc.) by the
instructions of the instrument manufacturer which
was followed by JIS Z8721 [8].
Light Irradiation Test
The concrete-mortar samples were prepared andstored for the test in a controlled room at 25℃ andwith R.H. 50%. Every sample placed in cork sheet
frame (30cm x 30cm x 5cm) and was kept in the lightirradiation test room for 24 hours before the test for

80

Sand
Slag
Ceramic
Glass
Roof Tiles

Density of the fine aggregates407

GEOMATE-Nagoya, Nov.13-15, 2013

2.61
2.58

Density g/cm3

2.6

2.64
2.6

2.49
2.49

Saturated
Density(g/cm³)Dry density(g/cm³)More light holding property indicates the hotter
surface and less indicates the cooler block surface.
Lightness Parameter Value

2.8

2.35
2.28 2.27

2.4
2.2

2.13

2

Sand

Slag

80
70
60
50
40
30
20
10
0

Glass ceramic Roof
Tiles
Fig.5 Lightness Status of the Sample Blocks surface.

Fig.3 Saturated and dry density of the experimental
aggregates

Lamp Irradiation
16
14
12
10
8
6
4
2
0

Temperature increased in ℃

The saturated and dry density of the slag
aggregates (2.64 g/cm3 & 2.6 g/cm3) was the highest
and the roof tiles (2.27 g/cm3 & 2.13 g/cm3) was thelowest among the experimental recycled aggregateswhen the value was 2.61 g/cm3 & 2.58 g/cm3 for the
standard reference aggregate sand.

Water absorption in %

7
6

6.61

5
4
3

2.98

2
1
0

1.1

1.51

Fig.6 Sample block increased inside temperature
0.02

The highest increased inside and surface
temperature showed the slag aggregate made sample
block and the lowest showed the ceramic aggregate
block during the light irradiation test.
Temperature increased in ℃

15

Fig.4 Water absorption of the study aggregates

14

Roof tiles aggregates absorbed highest (6.61%)
and slag absorbed the lowest (1.51) percentage ofwater within the recycled aggregates. The absorptionof the glass aggregates (0.02%) was very negligible
and could be count as zero absorbent.

13
12
11

Color Test
The value of the lightness parameter indicates thelightness as well as the reflection and heat control
property of the sample block. According to the color
test result ceramic block will reflect most of the lightand hold minimum; slag block hold the maximum.

10

Fig.7 Sample block increased surface temperature

408

GEOMATE-Nagoya, Nov.13-15, 2013

aggregates.
➣ The same type of experiments could be set for theaggregates collecting from new sources.

Skid Resistance83

Skid Resistance Value

84
82

80

80

82

REFERENCES[1] Masahide
Nishigaki.
Producingpermeable blocks and pavement bricks
from molten slag. Waste Management,
Volume 20, Issues 2-3, April 2000, Pages
185-192.
[2] Waste Report, Environmental Statics
2012 (Chapter: 3.6, 2.37, 3.19), Ministryof Environment, Government of Japan.
http://www.env.go.jp/en/statistics/conten
ts/index_e.html#haikibutu[3] Report on the: Tohoku Area PacificOffshore Earthquake, Department of
Urban Engineering, The University ofTokyo, Japan.
http://www.recwet.t.u-tokyo.ac.jp/kurisu/
gs11s/report2.html[4] The Kansai Electric Power Co. Inc.,Japan
http://www1.kepco.co.jp/corporate/csr/data/data02.html[5] JapaneseIndustrial
Standards
Committee.
JIS A 1102: Method of test forsieve analysis of aggregates.
[6] http://teaching.ust.hk/~civl111/CHAPTE
R3.pdf[7] JapaneseIndustrial
Standards
Committee. JIS A 1109: Methods of testfor density and water
absorption offine aggregates.

79

78
76

75

74
72
70

Fig.8 Skid Resistance Test Result
The highest skid resistance test value showed theceramic tiles aggregate block surface and the lowest
value showed the sand made mortar block surface.
Skid resistance value should be ≥ 65 for round,bend, gradient and unrestricted roads. It should be ≥55 for motorways and ≥ 45 for all other sites [11]. So,
all of the recycled aggregates could be used safely tomake walkways and pavements including bend andslop condition.
CONCLUSION AND RECOMMENDATIONS
The outcomes of the experiment can be concluded
as follows:
The experimental aggregates can be used inconstruction industry as the replacement of sand andother traditional fine aggregates to reduce the costand save the environment for green and sustainable
construction. Ceramic aggregates would be the good
choice where normal surface temperature is needed
and slag could be used where hot surface temperatureis needed. Other aggregates also could be used withsatisfactory light irradiation motive. Ceramic
aggregates would be the best choice where high skid
resistance is needed and other aggregates also could
be used in all conditions (walk-ways, motor-ways,
with bend or slop condition) to make road andpavement surface.

[8] http://www.konicaminolta.jp/instruments/knowledge/color/part1/09.html[9] American Society for Testing andMaterials (ASTM). ASTM E
303:
Standard Test Method for Measuring
Surface Frictional Properties Using the
British Pendulum Tester[10]
The
Constructor. http://theconstructor.org/pr
actical-guide/grain-size-analysis/2261/[11]
MUNRO, Skid Tester.
http://munroinstruments.co.uk/pdf/PSR
T_Manual.pdf

The following Recommendations were preparedfrom the experiment:➣ These types of experiment could be set for new
recycled aggregates to increase the re-use ofaggregates for sustainable environment.
➣ More and more new experiment should be set forthe safe use and finding new ways of use of the409

GEOMATE-Nagoya, Nov.13-15, 2013

Environment

410

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

COMPUTER MODELING AND ANALYSIS OF THREE PHASE
INDUCTION MOTOR UNDER TEMPORARY SHORT CIRCUIT
FAULT IN STATOR USING WAVELET TRANSFORM
Dicky Nova Wardana1,2, Dimas Anton Asfani1, Ardyono Priyadi1, and Mauridhi Hery Purnomo1
1
Electrical Engineering Department, Institut Teknologi Sepuluh Nopember (ITS), Indonesia
2
PT PLN Persero, Indonesia

ABSTRACTThe stator winding deterioration at the early stage does not affect to the motor performance i.e. torque, vibration,etc. Therefore, in most cases the deterioration is not detected until short circuit fault is occurred. This circumstancecan produce a worse short circuit fault, overheating and end up with catastrophic failure as long as motor operation.
The early warning system is necessary for detecting this condition to avoid the operation motor failure. This paper
proposes mathematical model and simulations of temporary short circuit in induction motor winding. Moreover,the detection method is proposed to detect the symptoms of fault while motor operate normally. This method uses
wavelet transform that able providing both of frequency and time information. Low current short circuit with shortduration represents the symptoms of winding and insulation deterioration. Simulation analysis shows that the
proposed method can detect very low short circuit current and short time duration as a spike fault. Moreover, theinformation of fault occurring can be provided
Keywords: Induction Motor, Temporary Fault, Short Circuit, Wavelet Transformmodeling is also widely developed in order toinvestigate the characteristic of the induction motor
under faulty condition. Asymmetrical stator windingof induction motor is developed and simulated under
Matlab-Simulink environment [7-8]. However, mostmodels simulate permanent fault and only few models
simulate temporary fault in stator winding that use
negative sequence current as fault identifier of thistype of fault [9].
This paper presents theoretical analysis andsimulation of temporary and non-periodic stator
faults in phase-A of induction motors. A three-phaseinduction motor is simulated under normal operationand faulty condition: non-periodic and temporaryinter-turn short circuit windings to represent earlystage of faults on the stator induction motor. The fault
severity can be changed by varying number of shorted
turn. By simulating this model, current characteristic
when fault occur can be investigated and wavelet
transform is proposed as identifier of temporary shortcircuit.

INTRODUCTION
Stator and bearing faults are the most common
fault that occurred on the induction motors. 30% 40% from all faults on the induction motors related tostator fault. Stator fault initiated with inter-turn shortcircuit caused by degradation of stator winding
insulation. Early stage of inter-turn short circuit
virtually no effect on the motor performance, but it
will develop phase-to-phase or phase-to-ground shortcircuit if it is not detected immediately. Phase-tophase or phase-to-ground short circuit cause
catastrophic damage on the stator core and motor
winding due to high current flows [1].
Several detection methods with varied parametersand variables have been proposed. Non-invasive
method is more attractive due to its ability to detect
fault without disassembly the machine. Motor current
signature analysis (MCSA) is a common method thatused to detect motor fault because different type of
fault yields different harmonics current [2]. MCSA
has very low accuracy in detecting temporary andnonperiodic faults. Harmonic frequency is unable torepresent nonperiodic faults since the current of thistype of fault doesn’t periodic. Therefore, wavelet
transform was used as alternative method to handle
this problem. Several experiments on the laboratory
have been conducted to acquire temporary shortcircuit current characteristic from real motor andclassified them using wavelet transform. The results
show that this method very effective and can be usedas faults identifier [3-6].
Beside laboratory experiment, induction motor

ASYMETRICAL INDUCTION MOTOR
MODEL
Symmetrical three-phase induction motor’smodel is well described in [10-11]. In this paper, themathematical model of the mathematical model of an
induction machine consisting of inter-turn stator
winding short circuit [7] is used to simulate
asymmetrical induction motor due to non permanentand nonperiodic short circuit as shown in Fig. 1. Inorder to derive equations for this type of induction
411

GEOMATE-Nagoya, Nov.13-15, 2013

motor, the following assumptions have been made:(1) Stator phase-A of the motor has a different
number of turns (N a ) caused by inter-turn shortcircuit and N b =N c =N s .
(2) Magnetic saturation, friction and windage
losses are neglected.
(3) Mutual and self-inductance on the rotor are
constant.
(4) Rotor resistances are same each phase r ar = r br
= r cr = r r .
The voltage equation of induction motor consistsof current and magnetic flux can be expressed asfollows:
s
s s
s
=
Vabc
rabc
iabc + dtd λabc

(1)

r r
r
=
0 rabciabc + dtd λabc

 rasscwhere r s =  0
abc

 0

(2)

0
rbs
0

Figure 1. Wiring Diagram0
 rar 0 0 r0  ; rabc
=  0 rbr 0 
 0 0 rcr 
rcs 
.

In the symmetrical stator condition, stator mutual
inductance will be Lasbs=Lbsas, Lascs=Lcsas,
Lbscs=Lcsbs. Similar to stator, rotor mutual
inductance and self-inductance have Larbr = Larcr =Lbrcr = Lbrar = Lcrar = Lcrbr and Larar =Lbrbr =Lcrcr, respectively.

and rassc is stator resistance due to short circuit.
Applying
stationaryreferenceframe
transformation to this equation yields thecorresponding qd0 equations and (1,2) becomes:ssd=Vqds 0 rqds 0iqd
0 + dt λqd 0

0= r irr
qd 0 qd 0(3)

 0 1 0− ωr  −1 0 0  λqdr 0 + dtd λqdr 0 (4) 0 0 0 

where,sqd 0r

 kr1rs=  0 kr 3 rs0
rs0

kr 2 rs 
1 0 0 
r
0  rqd 0 = rr 0 1 0 
0 0 1 
kr 3 rs ,

Based on machine’s parameters, the stator selfinductances for phase as, bs and cs can be calculated
as follows:
N a2
2
(6)
( Lls + Lm )
=
Lasas
3
N s2
2
(7)
Lbsbs
= Lcscs= Lls + Lm
3
The stator mutual inductances can be calculated asfollows:

1
Lasbs = Lbsas = Lascs = Lcsas = − N a Lm
3
1
Lbscs = Lcsbs = − Lm3and kr is constant of resistance due to short circuit.
The flux linkages of the stator and rotor windings
are written as follows:λ   L=λ   L
s
abc
r
abc

ss
abc
rs
abc

L  i  L  i 
sr
abc
rr
abc

s
abc
r
abc

Lrrarbr
Lrrbrbr
Lrrcrbr(9)

Assuming rotor has symmetrical parameters, therotor self and mutual inductances can be calculated asfollows:

(5)

L=
L=
L=
asar
asbr
ascr

where stator and rotor mutual inductances are:
 Lssasas Lssasbs Lssascs 
ssLabc =  Lssbsas Lssbsbs Lssbscs  Lsscsas Lsscsbs Lsscsc s  Lrrarar
Lrrabc =  Lrrbrar
 Lrrcrar(8)2
N a Lm
3

L=
L=
L=
L=
L=
L=
bsar
bsbr
bscr
csar
csbr
cscr

Lrrarcr Lrrbrcr 
Lrrcrcr 

(10)

2
Lm
3
(11)

Mutual inductance of stator to rotor and rotor tostator are dependent on the rotor position (angle),
therefore:

412

GEOMATE-Nagoya, Nov.13-15, 2013

 Lsrasar cos θ rLsrabc =  Lsrbsar cos θ r 2
 Lsrcsar cos θ r1
Lsrasbr cos θ r1
Lsrbsbr cos θ r
Lsrcsbr cos θ r 2

Lsrascr cos θ r 2 
Lsrbscr cos θ r1 
Lsrcsc r cos θ r 

where,ss L11

Lssqd 0 =  Lss21
 Lss31(12)2πand θ r 2= θ − 2π .
where θ r1= θ +3
3
The inductance matrix Lrsabc = Lsrabc' where (’)
means transpose of the matrix. The coefficients ofmatrix Lsrabc are peak values of stator-to-rotor mutual
inductance. Because of rotor symmetry Lasar=
Lasbr=Lascr, Lbsar=Lbsbr=Lbscr and Lcsar =Lcsbr =Lcscr.
The stator and rotor qd0 flux linkages are obtainedby applying transformation to the stator and rotor abc
flux linkages in (5), can be written as follows:(13)=
λqds 0 Lssqd 0iqds 0 + Lsrqd 0iqdr 0=
λqdr 0 Lrsqd 0iqds 0 + Lrrqd 0iqdr 0

Lss22
Lss32

rs
 L11

Lrsqdo =  Lrs21
0


rs
L12
rs
22

L

0

rr
rs
 L11

L13


Lrs23  Lrr =  0
0
0 


0
Lrr22
0

sr

L13
sr 
L23 
Lsr33 ,00
Lrr33 Normally, induction machine is supplied withthree wire connection without neutral wire. Hence,stator, rotor and inductance of the asymmetrical canbe written compactly as:k r
rqds =  r1 s
 0

(14)

ss
 L11
 ss
L
Lqd =  rs21
 L11
 rs
 L21700
500

Ampere

sr
sr
ss
 L11

L12
L13


Lss23  Lsrqd 0 =  Lsr21 Lsr22
 Lsr31 Lsr32
Lss33 


ss
L12

0
 rr
r
and rqd = 

rs 
0
ss
L12
Lss22

sr
L11
Lsr21

rs
L12
Lrs22

rr
L11
0

100
0
-100
1.4

0

sr

L12
sr 
L22 
0 

Lrr22 

1.5

1.45

0
rr 

1.55

(15)

(16)

1.6

-500
-700
0

1

Ampere

700
500

100
0
-100
1.4

0

3

2

Phase-A Stator Current

1.5

1.45

1.55

1.6

-500
-700
0

3

2

1

Phase-B Stator Current

Ampere

700
500

100
0
-100
1.4

1.45

1.5

1.55

1.6

0
-500
-700
0

2

1
time(s)Phase-C Stator Current

Figure 2. Phase current of the motor
Table 1. Machine’s parameters

413

3

GEOMATE-Nagoya, Nov.13-15, 2013

Value
50 hp
460 V
1705 rpm
0.087 Ω
0.302 Ω
13.08 Ω
0.302 Ω

|Detail Coef.| |Detail Coef.| |Detail Coef.|

Parameter
Horse powerLine voltage
Rated speed at 60 Hz
Stator winding resistance
Stator leakage inductance
Magnetizing inductance
Stator leakage inductance(stator refereed)
Rotor winding resistance (stator
refereed)
Inertia
Number of poles

Flux linkages in qd axis can be obtained byrearranging voltage equation in Eq. 3 and 4, theresults are expressed as follow:



λqs =
∫ Vqs +r
λqr = ∫ ωr λdr + r (λmq 2 − λqr ) dt
Lls




r
λds =
∫ Vds + Lsls (λmd − λds ) dt

0.228 Ω
1.662 kg.m2
4

20



λdr =
∫ −ωr λqr +

10
0
0

1

Phase-Ars(λmq1 − λqs ) dt
aLls


2



3


rr
(λmd − λdr ) dt
Llr


(19)

(20)

(21)

(22)

20

where

10

 b ( λqs − λmq1 ) c ( λqr − λmq 2 ) 
λmq1 Lm 
=
+

3
aLls
Llr



0
0

1

Phase-B

2

20
10

and

0
0

1

time (s)Phase-C

2

Figure 3. Detail coefficient each phase c ( λqs − λmq1 ) ( λqr − λmq 2 ) 3
λmq 2 Lm 
=
+

aLls
Llr



Table 2. Detail coefficient with different number ofshorted turn
SC Severity
10% Total Winding
25% Total Winding
50% Total Winding
75% Total Winding

Absolute Detail Coefficients
Phase A
Phase B
Phase C
23.68
12.25
11.43
73.31
37.07
36.25
215.8
108.3
107.5
484
242.4
241.6

Torque and speed of motor is expressed asfollows:

P(Tem + Tmech )dt
2J ∫
3P ss
=
Tem
(λd iq − λqs ids )22

ωr (t )=SIMULATION AND ANALYSIS OFTEMPORARY SHORT CIRCUIT IN STATOR
WINDING

(17)

vds =

(18)

1
3

[−vbs + vcs ](24)

SIMULATION RESULT
Initially, motor is operated in normal condition.
After starting transient has finished and motor
running in nominal speed, microcontroller send asignal to activate temporary short circuit at 1.5 second
with 0.01 second duration (half cycle) and loadchange begins at 2 second. The current characteristics
during free acceleration from stand still to full speed
consist of 10% short circuit of total winding areshown in Fig. 2. As it can be seen from this figure,only slight different between normal and faulted
current during motor operation, this problem makes
identification system less accurate. Fig. 3 shows
absolute detail coefficients obtained using wavelet
transform. The significant difference between normal
and faulty condition is shown in this figure. This
result is makes detection of fault is easier. Moreover,
it is founded that magnitude of detail coefficient islinear with the number of shorted turn as shown in
Table 2.

Machine parameters used in this paper are shownin Table 1. Temporary and non periodic short circuit
is simulated using model based on the mathematicalequation derived above. Short circuit causes
resistances and inductances parameter of the motorchanged. At that period of time, the parameters arecalculated using Eq. 15 and 16.
The qd voltages can be obtained by applying qd
transformation from stator phase voltage as follows:

vqs = 23 [vas − 12 (vcs + vbs )]

(23)

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GEOMATE-Nagoya, Nov.13-15, 2013

Temporary Short Circuit Detection in Induction
Motor Winding”, Presented at the 5thInternational Student Conf. on Advanced
Science and Technology (ICAST), Kumamoto,Japan, 2010.
[5] Dimas A. Asfani, Syafaruddin, Dicky N.
Wardana, M. H. Purnomo, and T. Hiyama,“Characterization of Temporary Short Circuit inInduction Motor Winding using Wavelet
Analysis”, Proceedings of the 2010 International
Conference on Modelling, Identification andControl (ICMIC), Okayama, Japan, July 17-19,
2010.
[6] D. A. Asfani, Syafaruddin , M. H. Purnomo, T.
Hiyama, “Temporary Short Circuit Detection in
Induction Motors Winding using Second Level
Haar-Wavelet Transform”, IEEJ Transactions on
Industry applications, Vol. 131 No. 9, pp. 1-10,
2011.
[7] M. Arkan, D. Kostic-Perovic, and P. J. Unsworth,“Modelling and Simulation of Induction Motors
with Inter-Turn Faults for Diagnostics”, ElectricPower System Research, vol. 75, pp. 57-66, 2005.
[8] S. Sivakotaiah, Mini V.P., Shajialal A. S., “Fault
Detection of Induction Motor by Fuzzy Logic
Algorithm”, 10th National Conference On
Technological Trends (NCTT09), pp. 85-90.
Nov 2009.
[9] D. A. Asfani, Syafaruddin , M. H. Purnomo, T.
Hiyama, “Simulation and Detection of
Temporary Short Circuit in Induction Motor
Windings Using Negative Sequence Current”,
The International Conference on Advanced
Power System Automation and Protection(APAP), pp. 2304-2308. 2011.
[10] P. Krause, O. Wasynczuk, S.D. Sudhoff,“Analysis of Electric Machinery”, IEEE Inc,
1995.
[11] C. M. Ong, “Dynamic Simulation of Electric
Machinery”, Prentice Hall PTR, 1998.

CONCLUSION
Mathematical model of asymmetrical induction
motor has been presented in this paper. This model isused to simulate temporary and non-periodic interturn short circuit on the phase-a of induction motor
winding. Simulation results show that wavelet
transform is an effective tool to identify temporary
short circuit in induction motor winding. Wavelet
transform is used to provide detail coefficient of thestator current which is used as variable detection.
Analysis of some fault cases varied by different
number of shorted turn is resulting that the magnitudeof detail coefficient is linear with the number ofshorted turn.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge to the
Directorate General for Higher Education (DGHE),
Ministry of national Education, the Republic ofIndonesia and JICA PREDICT-2 for supporting thisresearch under program of “Joint – Research Predict
Batch-2”.
REFERENCES[1] Rasool Sharifi and M. Ebrahimi, “Detection of
Stator Winding Faults in Induction Motor Using
Three-Phase
Current
Monitoring”,
ISA
Transactions 50(2011) 14-20.
[2] Neelam Mehla and Ratna Dahiya, “An Approachof Condition Monitoring of Induction Motors
Using MCSA”, International Journal of System
Application, Engineering & Development, Vol.
1, Issue 1, 2007.
[3] D. A. Asfani, Syafaruddin, D. N. Wardana, M. H.
Purnomo, and T. Hiyama, “Temporary Short
Circuit Identification in Induction Motor
Winding Using Wavelet Transform”, Presented
at the 3rd International Student Conf. on
Advanced Science and Technology (ICAST),
Seoul, Korea, 2009.
[4] D. A. Asfani, Syafaruddin, M. H. Purnomo, and
T. Hiyama, “Wavelet Level Evaluation for415

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ANALYTICAL SOLUTION TO CONTAMINANT EXTRACTIONCONSIDERING SMEAR EFFECT

1

H.Y Wang1 , X.W Tang1 and B. Bai1
Research Center of Coastal and Urban Geotechnical Engineering, Zhejiang University, China

ABSTRACTThe smear zones are usually caused by the installation of vertical drains in fine-grained soil. An analyticalsolution to contaminant extraction utilizing well injection depth extraction (WIDE) system is developed. The
effect of the smear zone around the vertical drains is considered. The injection rate is assumed to be equal to theretrieval rate to maintain full saturation and a steady-state seepage flow. The results obtained by the proposed
analytical solution agree well with those obtained from the finite element method. An illustrative example ispresented to show the influence of the smear zones and results revealed that the smear zone can have a great
influence on the contaminant extraction from contaminated soils. The 500-hour base concentration of acetone in
the middle of the contaminated soil increases by a factor of approximately 1.9 when the effect of the smear zone
is considered in the model. The proposed analytical model is relatively simple to verify complicated numericalmethods, and evaluate experimental data.
Keywords: Contaminant Extraction; Smear Effect; Analytical Solution; Well Injection Depth Extraction (WIDE);

characteristics of the smear zone investigated using alarge-scale consolidometer are found with reduced
permeability, decreased water content and increased
compressibility (Indraratna and Redana, 1998;
Sathananthan and Indraratna, 2006). Porter et al.
(1960), Barraclough and Tinker (1981), So and Nye(1989) observed that the solute diffusion coefficientin soil decreased with increasing bulk density anddecreasing water content. Therefore, it is of great
importance to research the smear effect on
contaminant transfer in soils.
In this paper, an analytical solution of 1D
contaminant extraction using WIDE system
considering the smearing effect is obtained underconditions of steady-state flow. In order to simplify
the sophisticated problem and emphasize the smear
effect on contaminant transfer, the PVWs aresubstituted by sand-wall (Fig. 1). Similarly to theclassical model of consolidation (Hansbo, 1981), thepresented model is described as an idealized threezone model, where the smear zone is the disturbed
region in the immediate vicinity of the sand-wall,and the middle zone is the intact region. In theremainder of the paper, the results obtained by the
proposed method are compared with those obtainedby the finite element method (FEM) provided by
GeoStudio 2007. An illustrative example isperformed to investigate the smear effect based on
the proposed analytical solutions.

INTRODUCTION
Remediation of contaminated low-permeability
soils utilizing conventional technologies, such as
pump-and-treat and vapor extraction systems istypically ineffective. Well injection depth extraction(WIDE) is an improved pump-and-tread system
which is demonstrated to be effective for depthspecific removal of contaminants in fine-grainedsoils, because the use of prefabricated vertical wells(PVW) installed in a relatively close spacing shorts
the flow path (Gabr et al., 1996; Quaranta et al.,
1997; Welker and Gilbert, 2003; Kunberger et al.,
2003; Warren et al., 2006; Sharmin et al., 2008).
The models for contaminant extraction using
WIDE technology in the literature are usuallycompleted by numerical models. For instance,
Welker and Gilbert (2003) developed MODFLOW
with MT3D method to numerically model the benchscale PVD remediation system. Sharmin et al.
(2008) analyzed the impact of the extraction processof WIDE technology on the groundwater head
distribution and contaminant transport using thefinite element model. Although many sophisticatedmust be solved numerically, simplified analyticalsolutions are still an economical and efficient
alternative to the numerical models. Gabr et al.
(1996) have given the analytical solution forcontaminant extraction through an axisymmetricmodel with semi-infinite boundary.
The installation of vertical drains by means of amandrel causes significant remolding of the subsoil,
especially in the immediate vicinity of the mandrel(Hansbo, 1981; Indraratna and Redana, 1998, 2000;
Sathananthan andIndraratna, 2006). The

MATHEMATICAL MODELAs shown in Fig. 1, the flushing solutions are
injected through a row of sand-wall, and retrieved
through another row of sand-wall that runs parallel
416

GEOMATE-Nagoya, Nov.13-15, 2013

∂Csi ( x, t )∂ 2Csi ( x, t ) 1 qx ∂Csi ( x, t )
R=
D
−
ds
s
∂t
∂x 2
ns
∂x

to the injection sand-wall, and the rate of theinjection which remains constant is equal to the rateof the extraction. The model mainly includes the
sand-walls, the smear zones, and the undisturbed
contaminated soil which are considered to behomogeneous and fully saturated. The co-ordinate x
has its origin at the border of the injection sand-wall,and its direction is parallel to the ground surface. It
is assumed that the piezometric heads in theinjection sand-wall and extraction sand-wall are
steady, and the piezometric head varies linearly
between the injection sand-wall and extraction sandwall. Based on Darcy’s law, the flow of the flushingsolution can be occurred only in the x direction andif the piezometric heads in the injection sand-walland extraction sand-wall are fixed, the seepage
velocity must be invariable.

(i=1, 2)∂C ( x, t )∂ C ( x, t ) 1 qx ∂C ( x, t )
(2)
−
R=
D
d
∂t
∂x 2
∂x
n
where Rds , Rd are the retardation factor of thesmear zone and the undisturbed soil, respectively;
Cs1 is the contaminant concentration in the smear
zone near the injection sand-wall; Cs 2 is thecontaminant concentration in the smear zone near
the extraction sand-wall; C is the contaminantconcentration in the undisturbed soil; Ds , D are thecoefficient of the hydrodynamic dispersion of thesmear zone and the undisturbed soil; and ns , n are
the porosity of the smear zone and the undisturbed
soil, respectively. qx is the seepage velocity andbased on the Darcy’s law it is determined by

S urfa ce seal

E xtra ction sand-wall

Injection sand-wall

C onta m ina ted soil

l1 + l2 + l3
∆h
∆h
(3)
=
qx K=
H
L l1 / K s + l2 / K + l3 / K s L

S eepa g e direction

Trench

S mear zone(a)Spatial pattern
Injection
sand-wall

TrenchExtraction
sand-wall

Surface seal

Smear zone
ax,Kd,n,p,K,D*

H

l3

L

Fig. 1(b)Analysis scheme
Schematic
diagram ofextraction with smear zones.

l3 are the width of the smear zone; l2 is the widthof the undisturbed soil; and L is the span between
the injection sand-wall and the extraction sand-wall.
Using the Henry’s law, Rds , Rd can be
represented as follows:(4)(5)

where ρ ds , ρ d are the dry bulk density of thesmear zone and the undisturbed soil, respectively;
and K d is the equilibrium distribution coefficient,which is usually obtained by the Batch test, as thesoil type of the smear zone and the undisturbed zone
are same, K d in the both regions are assumed to beequal.
On the basis of the Eq. (3), Ds , D can beobtained:xl2

where K H is the horizontal equivalentpermeability coefficient; K s , K are the permeability
coefficient of the smear zone and the undisturbed
soil; ∆h is the water head difference between theinjection sand-wall and the extraction sand-wall; l1 ,Rds = 1 + ρ ds K d n s
Rd = 1 + ρ d K d n

Contaminated soil
ax,Kd,ns,pds,Ks,Ds*

l1

(1)

2

contaminant

The governing equations for solute transport
through the smear zones and the undisturbed
contaminated soil at a particular distance x and time
t are expressed respectively:D=
Ds* + α x K H
s

417

∆h
ns L

(6)

GEOMATE-Nagoya, Nov.13-15, 2013

D D* + α x K H
=

∆h
nL

can be expressed as follows:
(7)

qx x
qx 2t
−
Csi ( x, t ) = exp(
)×
2ns Ds 4ns 2 Rds Ds

where Ds* , D* are the effective diffusion
coefficient of the smear zone and the undisturbed
soil; and α x is the dispersivity of the x direction,∞∑ ξ h ( x) e

likewise, α x in the both regions are assumed to beequal.
The initial condition is

Csi ( x, 0) = C ( x, 0) = C0 (i = 1, 2)
where

C0

is

the

initialm =1

C ( x, t ) = exp(

contaminantconcentration which is a constant.
For the left boundary, the contaminantconcentration of the flushing solution is zero:Cs1 (0, t ) = 0

thecoordinate

x = l1

as i=1,

(14)

D
β mt
Rd

m mi

(15)

β m =λm2

(16)

DRds
q2
q2
R
βm + ( 2 x − 2 x
) ds
Ds Rd
4n Rd D 4ns Rds Ds Ds(17)

hsmi ( x)=A smi sin λsm x+Bsmi cos λsm x

(10)

(18)

(i=1,2)hm ( x)=A m sin λm x+Bm cos λm x

The contaminant concentration at the interface ofthe smear zone and the undisturbed zone are thesame, and the continuity of the contaminant flux
must be obeyed as well:

where

−

2
β sm =λsm

β sm =The Neumann boundary condition is consideredat the right boundary:∂C ( x, t )−ns Ds si+ qx Csi ( x, t )∂x∂C ( x, t )=−nD+ qx C ( x, t ) (i = 1, 2)∂x
Csi ( x, t ) = C ( x, t )(i = 1, 2)

where

(9)

∂Cs 2 ( x, t )x=L = 0
∂x

(13)

qx x
q 2t
− 2x
)×
2nD 4n Rd D

∑ ξ h ( x) em =1Ds
β sm t
Rds

m smi

∞

(8)

−

ξm =

C0 [ns Ds e

qx x1 qx x2+
ns Ds nD

ns Ds e
+

(11)

(12)
and

qx x1 qx x2+
ns Ds nD

x1

dx
...

∫ h ( x)dx
0

2
sm1

q x

− x
x2
Ds Rd
2 nD
nDe
h
x
e
dx
(
)
m
∫
x
1
DRds
...
qx x1 qx x2
+
x2
Ds Rd
2
nD nD
+
nDe
∫x1 hm ( x)dx
DRds
qx x2 qx x1+
ns Ds nDL

∫ h ( x )e−qx x
2 ns Dsx2 sm 2
qx x2 qx x1+
L
ns Ds nD
2
s
sm 2
x

dx]

∫ h ( x)dx

+ ns D e

ANALYTICAL SOLUTION

sm1

0

qx x1 qx x2+
nD nD+ ns Ds e

x= l1 + l2 as i=2.

x1

∫ h ( x )e

(19)

q x
− x
2 ns Ds

2(20)

The process of the contaminant extraction is
analogous to the process of the small-strain
consolidation because their governing equations areboth the same form of a second-order partial
differential equation. Similarly to the problem of
one-dimensional consolidation of layered systems,
the method of separation of variables mentioned by
Lee et al. (1992) is applied. The solution to thegoverning Eqs. (1) and (2) satisfying the boundary
conditions given by Eqs. (9) and (10) and thecontinuity conditions given by Eqs. (11) and (12)The coefficients A smi , Bsmi , A m and Bm in
Eqs. (18) and (19) can be obtained as follows:[ Asm1 Bsm1 ] = [1 0]TT[ A m Bm ] = T1−1S1 [ Asm1 Bsm1 ]T
T[ Asm2 Bsm 2 ] = S2−1T2 [ A m Bm ]
T

418

T

(21)
(22)
(23)

GEOMATE-Nagoya, Nov.13-15, 2013

based on large-scale consolidation studies, as
described by Sathananthan and Indraratna (2006).
The porosity and permeability in the undisturbed
contaminated soil and the smear zone are extracted
from Indraratna and Redana (1998, 2000). Toluene
is chosen to represent the contaminant in the soil,
and the initial constant concentration of toluene isassumed to be 1mg/L. The material and chemical
properties of the soil are taken directly from Foose etal. (2002) for the similar property of the compacted
clay liner from Foose et al. (2002) and the clay usedin Indraratna and Redana (1998). The effective
diffusion coefficient D* in the smear zone isassumed to be decreased by 10% than D* in theundisturbed zone. The properties of the undisturbed
zone and smear zone are shown in Table 1.
In this case, the Neumann boundary condition,i.e., ∂Cs2 ( L, t ) ∂x =0 , is adopted at the extraction
sand-wall. The comparisons of contaminantconcentration profiles in the contaminated soil
consisting of two smear zones and an undisturbed
zone obtained by the presented analytical solution
and GeoStudio 2007 are shown in Fig.2. The
presented analytical solutions are agreed with theresults obtained by the finite element method
excellently. This result further validates the
proposed analytical solutions.

where

E
Si =  si
Gsi

Fsi 
H si 

(i = 1, 2) ,(24)

in which:

Esi = sin λsm xi e

qx xi
2 ns Ds

Fsi = cos λsm xi e

,

qx xi
2 ns Ds

,

q x

x i
qx
2 ns Ds
Gsi =(−ns Ds λsm cos λsm xi − sin λsm xi )e
2
qx xi
qx
2 ns Ds.
=
H si (ns Ds λsm sin λsm xi − cos λsm xi )e2
 E Fi 
Ti =  i(25)
 (i = 1, 2) ,
Gi H i 

in which:

Ei = sin λm xi e

qx xi
2 nD

Fi = cos λm xi e,(−nDλm cos λm xi −Gsi ==H i (nDλm sin λm xi −qx
sin λm xi )e2qx
cos λm xi )e
2

qx xi
2 nD

qx xi
2 nD

qx xi
2 nD

,
,

Table 1 Parameters of the model for comparison
with GeoStudio 2007.
Propertynsnρ d (g/cm3)
ρ ds (g/cm3)∆hK(cm/s)K s (cm/s)
K d (ml/g)
α x (m)*D ( cm2/h)
D s *( cm2/h)
l 1 (cm)
l 2 (cm)
l 3 (cm)

The determinant of the following which is equal
to zero yields the values of λm :U ⋅ S 2−1 ⋅ T2 ⋅ T1−1 ⋅ S1 ⋅ [1 0] =
0
T

(26)

where

qx


 λsm cos λsm L + 2n D sin λsm L 
s s

U =


qx
 −λsm sin λsm L + 2n D cos λsm L 
s s



T

COMPARISONS
WITH
ELEMENT METHODFINITE

THE(27)

Toluene
0.52
0.55
1.25
1.30
12m
3.36×10-7
2.7×10-8
1.0
2.0
7.34×10 -3
6.6×10-3
1080
10RESULTS AND DISCUSSION

To demonstrate the method is reasonable andverify the analytical solution gives the correct results,
the proposed analytical solutions are compared withthe finite element method (FEM) provided by
GeoStudio 2007. The width of the sand-wall isassumed to be 4cm and smear zone is taken to be
0.1m, which is 2.5 times the width of the mandrel

An illustrative example is presented to show theinfluence of the smear zones. Acetone is selected torepresent the contaminant in the soil, and the initialconstant concentration of acetone is assumed to be
1mg/L. The diffusion and distribution coefficients ofthe clay are from Kalbe et al. (2002). The effective419

GEOMATE-Nagoya, Nov.13-15, 2013

from 0.88 for the case considering the smear zone to
0.46 for that assuming no smear zone. Meanwhile,the contaminant concentration at the distance of
0.5m decreases from 0.996 to 0.66 when the smear
zone is not considered in the model. The results
suggest that the smear zone has a great effect on thecontaminant extraction from contaminated soils.
Another case considering the smear zone is
performed that the seepage velocity of the case ispromoted to be equal to that assuming no smear
zone. The 500-hour base contaminant concentrationof this case is slightly less than that assuming nosmear zone for the actual flow velocity in the pore of
the smear zone is a little more than that of the poreof the undisturbed zone, correspondingly, the actionof advection and dispersion can be greater. It is
indicated that the smear zone has a slight influenceeven though the effect of smear zone on the flow
velocity is not considered.

diffusion coefficient D* in the smear zone isassumed to be 90% of D* in the undisturbed zone.
The properties of the smear zone and theundisturbed zone are extracted from Indraratna andRedana (1998, 2000).
The material and thechemical properties of the undisturbed zone andsmear zone are summarized in Table 2.
1.0

Concentration(mg/L)

0.8

0.6

0.4

Analytical solution (t=1000h)
Finite element method(t=1000h)
Analytical solution (t=5000h)
Finite element method(t=5000h)

0.2

0.0
0.0

0.2

0.4

0.6

0.8

1.4

1.0

Distance,x(m)1.2Table 2 Parameters of the model for analysis
Propertynsnρ d (g/cm3)
ρ ds (g/cm3)∆hK(cm/s)K s (cm/s)
K d (ml/g)
α x (m)D*( cm2/h)
D s *( cm2/h)
l 1 (cm)
l 2 (cm)
l 3 (cm)

No smear zone(qx=3.37x10-5m/h,t=500h)
With smear zone(qx=3.37x10-5m/h,t=500h)

Comparisons of the analytical solution withthe finite element method.

Concentration(mg/L)

Fig. 2

With smear zone(qx=6.49x10-6m/h,t=500h)

Acetone
0.52
0.55
1.25
1.30
12m
3.9×10-8
3.4×10-90
2.0
1.22×10 -2
1.09×10-2
10
30
10

1.0
0.8
0.6
0.4
0.2
0.0
0.0

0.1

0.2

0.3

0.4

0.5

Distance,x(m)Fig. 3

Effect of smear zone on contaminantconcentration profiles.

CONCLUSION
An analytical solution for one-dimensional
contaminant extraction considering the effect of thesmear zone is presented in this paper. The results
obtained by the proposed analytical solution agree
well with those obtained by the finite element
method. The results suggested that the smear zone
can have a great influence on the contaminant
extraction from contaminated soils. The 500-hourbase concentration of acetone at the distance of
0.25m increases by a factor of approximately 1.9
when the effect of the smear zone is considered in
the model. Even though the flow velocities of thesmear zone and undisturbed zone are identical, thesmear zone still has a slight effect.

Three different conditions are considered for this
discussion. The comparison of the concentration
profile for the case considering the effect of thesmear zone and that assuming no smear zone isshown in Fig. 3. Both concentration profiles of thetwo cases are obtained on the basis that the waterhead difference is maintained at 12m, andcorrespondingly the seepage velocities of the twocases are 6.49×10-6m/h and 3.37×10-5m/h
respectively. The 500-hour base contaminantconcentration at the distance of 0.25m decreases

ACKNOWLEDGEMENTS
The authors would like to express their sincere
gratitude to National Natural Science Foundation of420

GEOMATE-Nagoya, Nov.13-15, 2013

China (Grant 51179168) and the National Basic
Research Program of China (Grant 2012CB719800)
for the financial support to this study.

(WIDE)”, in Proc. 12th Pan-American Conf. on
Soil Mechanics and Geotechnical Engineering,
2003, pp. 1575–1581.
[10] Lee PKK, Xie KH and Cheung YK, “A study
on one-dimensional consolidation of layered
systems”, International Journal for Numericaland Analytical Methods in Geomechanics, Vol.
16, November. 1992, pp. 815–831.
[11] Porter LK, Kemper WD, Jackson RD and
Stewart BA, “Chloride diffusion in soils as
influenced by moisture content”, Soil Science
Society of America Journal, Vol.24, November.
1960, pp. 460-463.
[12] Quaranta JD, Gabr MA, Cook EE and Szabo D,“Developments in prefabricated vertical drainenhanced soil flushing”, in Proc. 7th Int. Conf.
on Offshore and Polar Engineering, 1997, pp.
703–706.
[13] Sathananthan I and Indraratna B, “Laboratory
evaluation of smear zone and correlation
between permeability and moisture content”,
Journal of Geotechnical and Geoenvironmental
Engineering, Vol. 132, July. 2006, pp. 942-945.
[14] Sharmin N, Kunberger T, Gabr MA, Quaranta
JD and Bowders JJ, “Performance modeling andoptimization of contaminant extraction using
prefabricatedverticalwells(PVWs)”,
Geosynthetics International, Vol. 15, March.
2008, pp. 205–215.
[15] So HB and Nye PH, “The effect of bulk density,
water content and soil type on the diffusion ofchloride in soil”, Journal of Soil Science, Vol.
40, December. 1989, pp. 743-749.
[16] Warren KA, Gabr MA and Quaranta JD, “Field
study to investigate WIDE technology for TCE
extraction”, Journal of Geotechnical andGeoenvironmental Engineering, Vol. 132,
September. 2006, pp.1111–1120.
[17] Welker AL and Gilbert RB, “Calibration offlow and transport model with a bench-scale
prefabricated vertical drain remediation system”,
Journal of Geotechnical and Geoenvironmental
Engineering, Vol. 129, January. 2003, pp. 81-90.

REFERENCES[1] Barraclough PB and Tinker PB, “Thedetermination of ionic diffusion coefficients infield soils. i. diffusion coefficients in sieved
soils in relation to water content and bulk
density”, Journal of Soil Science, Vol. 32, June.
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[2] Foose G, Benson C and Edil T, “Comparison of
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[3] Gabr MA, Wang J and Bowders JJ, “Model for
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system”, Journal of Geotechnical Engineering,Vol. 122, November. 1996, pp. 914-919.
[4] Gabr MA, Bowders JJ, Wang J and Quaranta JD,“In situ soil flushing using prefabricated verticaldrains”, Canadian Geotechnical Journal, Vol. 33,
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[5] Hansbo S, “Consolidation of fine-grained soils
by prefabricated drains”, in Proc. 10th Int. Conf.
SMFE, 1981, pp. 677-682.
[6] Indraratna B and Redana IW, “Laboratory
determination of smear zone due to verticaldrain installation”, Journal of Geotechnical andGeoenvironmental Engineering, Vol. 124,
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[7] Indraratna B and Redana IW, “Numericalmodeling of vertical drains with smearand wellresistance installed in soft clay”, Canadian
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[8] Kalbe U, Müller WW, Berger W and Eckardt J,“Transport of organic contaminants withincomposite liner systems”, Applied Clay Science,Vol. 21, April. 2002, pp. 67-76.
[9] Kunberger T, Quaranta J and Gabr MA,“Remediation of Former Lockbourne Air Force
Base using well injection depth extraction421

Third International Conference on Geotechnique, Construction Materials and
GEOMATE-Nagoya,2013
Environment,
Nagoya,Nov.13-15,
Japan, Nov.
13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

MECHANISM OF C 6H6 OXIDATION IN THE THREE-WAY CATALYTICCONVERTER EQUIPPED A GASOLINE ENGINE
1

Akio Takigawa 1 , Akihiro Mieda 1 and Yongzhen Peng 2
Department of Civil and Environmental Engineering, Mebashi Institute of Technology, 460-1,Kamisatorycho, Maebashi, Gunma 371-0816, Japan,
2
Key Laboratory of Beijing for Water Quality Science and Water Environment Recovery Engineering,Beijing University of Technology, 100Pingleyuan, Chaoyang District, China
ABSTRACTThe mechanism C 6 H 6 oxidation was investigated in a tubular-flow reactor containing a three-way catalyst athree-way catalyst. Experiments were performed to investigate the effects of coexistence gas components,
temperature, gas flow rate and operating age of catalytic converter. The components of C 6 H 6 , H 2 , CO, H 2 O, HC,O 2 and N 2 were selected from the gasoline engine exhaust gas. The experimental results show that the oxidationof C 6 H 6 was effect by the presence of coexistence gas component, and C 6 H 6 oxidation was enhanced by thepresence of O 2 and CO, while the presences of H 2 , HC and H 2 O have suppressive effect on the oxidation of
C 6 H 6 than O 2 and CO. The results reveal that catalyst has lower catalytic oxidation activity for C 6 H 6 oxidation
at lower temperature, and has higher catalytic oxidation activity for C 6 H 6 than CH 4 , C 2 H 6 and C 3 H 8 , anddecomposition of C 6 H 6 via catalytic was similar to the decompositions of C 2 H 4 and C 3 H 6 . The operating age
of catalytic converter has lower effect on the oxidation of C 6 H 6 with an increase in the operating time of catalytic
converter from 0 to 80,000km at lower temperature range.
Keywords: C 6 H 6 , Catalytic Converter, Coexistence Gas, Temperature, Operating Ageage of catalytic converter has been pointed out topotentially result in higher pollutant emissions.
The experiments reported here were designed toinvestigate the emission of C 6 H 6 from a gasoline
engine equipped with a three-way catalytic converter
under different operating conditions. The effect ofdegradation of the catalytic converter on the C 6 H 6emission is also discussed.

INTRODUCTION
Volatile chlorinated hydrocarbons such as
chloroform, trichloroethylene, aromatic compounds,
such as benzene, xylene etc. 18 substance are in thesubstance on the hazardous air pollutants list defined
as atmospheric pollutants with long term toxicity. 18
substances is also a substance in hazardous air
pollutants list, high detection rates in our living
environments, especially in the indoor air.
Carcinogenic substance has been demonstrated to 18
types of being measured in benzene only. Benzene
was also given priority initiatives substance of
atmospheric organic harmful substances inEnvironment Agency, a revision of the Clean Air Act
air quality guideline value less than 3μg/m 3[1] .
Automobile exhaust gas, petroleum industry andvarious combustion systems etc. are the major C 6 H 6emission sources. C 6 H 6 is estimated to about 83% in
automotive-related source of C 6 H 6 [2] . For building
measures to prevent air pollution caused by C 6 H 6 ,there is a need to clarify the discharge mechanism
from the Automobile. Most modern gasoline engines
equipped with three-way catalytic converters thatsimultaneously convert NOx, CO and HC into nonpolluting forms by means of precious metal-based
heterogeneous catalyst. However, gasoline engine
exhaust contains up 150 different hydrocarbons,
except for NOx and CO [3] . Among these, the reactivityof C 6 H 6 on the three-way catalytic converter isdifferent with the other components. The three-way
catalytic converter varies extremely with the changeof driving mode of the automobile, and the operating

EXPERIMENTS
The experimental apparatus is shown in Fig.1, andthe reaction tube is shown in Fig.2. The reaction tube
consisted of a preheating zone and a reaction zone. To
achieve as near isothermal conditions as possible, thetemperature of reaction tube was controlled by anelectric furnace. The reaction tube was 18mm ofinside diameter and 1300mm long. The preheatingzone occupied 850 mm of the length and main reaction
zone was 150mm in length. The reaction tube housed
a commercial catalyst of 17mm outside diameter and
150mm in length used in an automobile. A rapid
cooling zone, 10mm inside diameter and 300mm long,
below the main reaction zone, was used to halt thereaction at the outlet of the reactor as rapidly as
possible. The gas mixture was made up from sevenstreams (C 6 H 6 , CO, H 2 , HC, H 2 O, O 2 and N 2 )supplied by calibrated mass controllers. The
experiments were carried out for various flow rates ofindividual stream, using individual control valves so
as to keep the concentration at the inlet of the reactor
at the stated level. Measurement of C 6 H 6 , CO, H 2 ,HC and O 2 concentration was then performed after
422

GEOMATE-Nagoya, Nov.13-15, 2013

the temperature of the reaction zone stabilized. The
experiments were carried out for the various gas
compositions, flow rate and reaction temperature.
C 6 H 6 and HC were measured using aflame ionization
detector (FID) gas chromatographEffects of O 2 , H 2 , CO, H 2 O and HC on the
Oxidation of C 6 H 6Initial experiments were carried out with the C 6 H 6 /O 2 /N 2 gas system in the absence and presences of H 2 ,CO and H 2 O. The reactions were investigated as thefunction of gas flow rate (Fig.3). The decompositionof C 6 H 6 is 100% in the range

Electric furnace
Reaction tube

Cooler

O2,CO,H2(%)

temperature:300℃,gas flow rate:10〜24ℓ/min
No.4:xNo.1:◊
No.2 :□
No.3: ∆
2
Catalyst
C6H6,N2,O2,HC,CO,H2,H2O
To gas chromatographFig.1 Experimental apparatus
φ10

φ18

φ4

1
0

10
30

12

14

16

18

20

22

24

26

25
C6H6(ppm)

20

750

100

150

15

1300

10

Fig.2 Details of reaction tube

0

Table 1 Experimental conditions

10 12 14 16 18 20 22 24 26
Gas flow rate (ℓ/min)Fig.3 Effcts of O2,CO, H2 and H2O on
the oxidation of C6H6
from 10ℓ/min to 16ℓ/min and the concentration of
C6H6 increases from 0ppm to 7ppm as the gas flowrate is increased from 16ℓ/min to 24ℓ/min in the
C 6 H 6 /O 2 /N 2 gas system. The variation of C 6 H 6concentration in the presence of CO is similar to thatshown in C 6 H 6 /O 2 /N 2 gas system, however, theemission of C 6 H 6 is observed at 22ℓ/min andmaximum concentration of C 6 H 6 of 4ppm is much
lower than that for the C 6 H 6 /O 2 /N 2 gas system. In
the gas system of H 2 O presence, the concentration of
C 6 H 6 increases from 0ppm to 3ppm with theincrease in the gas flow rate from 10ℓ/min to 18ℓ/min,
while the concentration of C 6 H 6 increase sharply
from 3ppm to 13ppm in the range of gas flow rate of
18ℓ/min 〜 24ℓ/min. For the C 6 H 6 /H 2 /O 2 /N 2 gas
system, as the gas flow rate is increased from 10ℓ/min
to 14ℓ/min, the concentration of C 6 H 6 increases from
15ppm to 24ppm. Above 14ℓ/min, the concentrationof C 6 H 6 maintains nearly a same valve. In theseexperimentations CO was decomposed completely
and the concentration of H 2 O was not measured.
Fig.4 shows the variation in Paraffin (CH 4 , C 2 H 6 ,C 3 H 8 ), olefin (C 2 H 4 , C 3 H 6 ) hydrocarbon
concentrations and benzene (C 6 H 6 ) concentration
No.5, gas flow rate:10〜24ℓ/min

Gas component and concentration
C 6 H 6 : 30ppm, O 2 : 0.5%, HC: 1800ppm,
CO: 0..2%, H 2: : 2.0%
No. N 2 C 6 H O 2 CO H 2 H 2 O HC
6

1
2
3
4
5
6

O
O
O
O
O
O

O
O
O
O
O
O

O
O
O
O
O
O

O
O
O
O

O

O

5

O
O

gas flow rate: 10-24(ℓ/min), reaction
temperature: 300-700℃, catalyst: 0km,
40000km, 80000km(G2500, Hitachi). The concentrations of CO, H 2 were
measured using a thermal conductivity detector (TCD)
gas chromatograph (G5000, Hitachi). The activity of
the catalytic converter is expected to be greatly
dependent on the operating age. In order to elucidate
the operating age with respect to C 6 H 6 emission,
three three-way catalytic converters were employed inthese experiments. The catalytic converters tested are
the same type in the composition and model water was
injected in a manner to pass gas into the distilled waterin the reaction tube inlet.
RESULTS AND DISCUSSION

temperature:300℃
423

GEOMATE-Nagoya, Nov.13-15, 2013

500

CH4

C2H4

C3H6

temperature:300℃

C3H8

2
1.6
1.2
0.8
0.4
0

300

H2,CO(%)

HC (ppm)

400

C2H6

200
100
0

10

12

14

16

18

20

22

24

26

30
20
15
10
5
0

H2
10

12

14

CH4

C2H6

C2H4

10

12

14

16

10

12

14

800
700
600
500
400
300
200
100
0

16

18

20

22

24

26

C3H6

C3H8

20

22

24

26

16 18 20 22
Gas flow rate(ℓ/min)24

26

HC (ppm)

C6H6(ppm)

25

CO

10

12

14

16

18

20

22

24

30

26

25
C6H6(ppm)

Gas flow rate (ℓ/min)Fig.4 Effect of HC on the oxidation of C6H6
at the outlet of converter with respect to gas flow rate.
The variation in concentrations of CH 4 , C 2 H 6 andC 3 H 8 show the similar tendency for the change of thegas flow rate, and show the lower decomposition
rate at any gas flow rate. The variation inconcentrations of C 2 H 4 , C 3 H 6 and C 6 H 6 also show
the similar tendency for the change of the gas flow rate,
however, the concentrations of C 2 H 4 , C 3 H 6 andC 6 H 6 show higher decrease in the range of lower gas
flow rate.
Comparison of the effects of O 2 , CO, H 2 O, H 2 andHC on the decomposition of C 6 H 6 shows that at
300℃, addition O 2 , CO, H 2 O, H 2 or HC to C 6 H 6 /N 2
gas system can strongly influence the C 6 H 6decomposition. These also evident that by contrast
H 2 O, H 2 and HC, O 2 and CO have significant
accelerating effect respectively on the decompositionof C 6 H 6.
Fig.5 shows effect of coexistence of CO, H 2 O, H 2
and HC with C 6 H 6 /O 2 /N 2 gas system on thedecomposition of C 6 H 6 . When increasing the gas
flow rate from 10ℓ/min to 18ℓ/min, the concentrationof C 6 H 6 increases from 15ppm to 25ppm. Above
18ℓ/min, the concentration of C 6 H 6 maintains nearlya same valve. These results resemble with theconcentration in thevariation of C 6 H 6C 6 H 6 /H 2 /O 2 /N 2 gas system, show that the inhibitionof H 2 for C 6 H 6 degradation is greater than thecoexistence of other gas.

18

20
15
10
5
0

Fig.5 Effect of coexistent gas on the C6H6
oxidation
Fig.6 shows effect of temperature on the C 6 H 6oxdation in the C 6 H 6 /CO/H 2 /H 2 O/HC/N 2 gas
system. Car exhaust gas temperature will vary withchanges in the running speed of the car. Usually, undernormal pressure, gasoline catalyst performs oxidation
and reduction reactions in a range of 300℃〜600℃ [4] .
As shown in Fig.6, C 6 H 6 is about 20ppm at thetemperature less than 500 ℃ , and maintained aconstant concentration substantially, as the catalyst
temperature rises from 500 ℃ to 700 ℃ , C 6 H 6concentration is reduced to about 11ppm.
Comparing the results in Figure 5, these results
indicate that the decomposition of C 6 H 6 in the
catalyst is influenced by temperature, and there is atemperature range, in which the C 6 H 6 decompositionis enhanced. When increasing the temperature from
500℃ to 700℃, the concentrations of CH 4 , C 2 H 6
and C 3 H 8 were impaired, while the concentrations of
C 3 H 6 , C 2 H 4 were increased conversely. Theseexperimental results differ from the experimental
results shown in Fig.5. These results indicate that thetemperature direct influence the decomposition
process of each component in the catalyst, and also

Effect of Temperature on the Oxidation of C 6 H 6
No.6, gas flow rate:10〜24ℓ/min
424

GEOMATE-Nagoya, Nov.13-15, 2013

30
25
20
15
10
5
0

300

400

500
600
700
Temperature (℃)

800

H2 (%)

2
1.6
1.2
0.8
0.4
0

It is believed that the performance of the gasoline
catalyst to decline with an increase in the mileage ofthe car. Besides mechanical destruction, wear,
alteration, catalyst degradation is also advanced by thealteration and dissipation of the active substance, andadsorption of toxic substance.
Fig.7 is the results of the experiment with threecatalyst taken from used gasoline car. The mileage ofthe car is 0km, 40000km and 80000km respectively.
As shown in Fig.7, C 6 H 6 concentrations are hardly
affected by the increase in the mileage from 0km to
80000km. There is no significant difference on theconcentrations of H 2 , and CO concentration was notdetected. However,
the effect of mileage on the CH 4 , C 2 H 6 , C 3 H 8
concentration is small in the range of the mileage, andconcentrations of C 2 H 4 , C 3 H 6 significantly

0km
10

800
700
600
500
400
300
200
100
0

40000km

12

14

16

CH4

C2H6

80000km

18
C2H4

20

22

C3H6

24
C3H8

10

12

14

CH4

C2H6

16

18
C2H4

20

22

C3H6

24

40000 km

C6H6 (ppm)

0km
1240000km26

26

80000km14 16 18 20 22 24 26
Gas flow rate (ℓ/min)Fig.7 Effect of catalytic degradation on the
C6H6 oxidation
increase with the increasing in the mileage from 0km
to 80000km. These results indicate that the effect ofdegradation of the catalyst with increasing mileage of
425

10

26

C3H8

10 12 14 16 18 20 22 24
800
700 CH4 C2H6 C2H4 C3H6 C3H8
600
500
400
300
200
80000 km100
0
10 12 14 16 18 20 22 24

30
25
20
15
10
5
0

26

O km

800
700
600
500
400
300
200
100
0

HC (ppm)

Fig.6 Effect of temperature on the C6H6
oxidation
Effect of Catalyst Degradation on the Oxidationof C 6 H 6

No.6, gas flow rate:24ℓ/min
temperature:300℃, mileage:0 ~80000km

HC (ppm)

No.6, gas flow rate:24ℓ/min
temperature:300℃~700℃
2
1.6
1.2
CO
0.8
H2
0.4
0
300
400
500
600
700
800
800
CH4 C2H6 C2H4 C3H6 C3H8
700
600
500
400
300
200
100
0
300
400
500
600
700
800

HC(ppm)C6H6(ppm)

HC (ppm)

CO, H2 (%)

influence to that by the shortening of the reaction time
due to temperature rise.

GEOMATE-Nagoya, Nov.13-15, 2013

the car on the decomposition of the gas components
depend on the components.
CONCLUSION
The effects of the engine operating conditions on
the C 6 H 6 emission have been investigated withrespect to gas flow rate, coexistence gas components
and temperature in a tubular-flow reactor containing athree-way catalyst. The comparisons of the effects ofcoexistence gas components and gas flow rate on the
C 6 H 6 decomposition have clarified that the oxidationof C 6 H 6 is effected by the presence of coexistence gas
component, and C 6 H 6 oxidation is enhanced by thepresences of O 2 and CO, while the presences of H 2 ,HC and H 2 O have suppressive effect on the oxidationof C 6 H 6 than O 2 and CO. The results also reveal that
there is a certain range of the temperature, at which thecatalysts have higher catalytic activity for C 6 H 6oxidation. The effect of catalyst degradation on theoxidation of C 6 H 6 has also investigated. It was foundthat in the range of the mileage from 0km to 80000km,
the degradation of catalyst has lower effect on thedecomposition of C 6 H 6 .
REFERENCES[1] Environmental preservation measures technicalcommittee, Basic knowledge of air pollution,
Japan, Japan environmental management
association for industry, 2003, ch1.
[2] NITE, Initial risk assessment of chemicals, japan,
2007, No.104[3] John E. S, Silvestre T, William R, et al,“Volatileorganic compound emissions from 46 in use
passenger cars”, J. of Environ. Sci. Technol.,Vol.21, No.5, 1987, pp.466-475.
[4] Abe E, Present and future of automobile exhaustgas catalyst, Science and technology
developments, Vol.117, 2010, pp. 8-6

426

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ROLE OF CURBSIDE CRACK OF ROAD IN URBAN BIODIVERSITY
Taizo Uchida1, Xue J. Huan1, Daisuke Hayasaka2, Teruo Arase3, William T. Haller4 and Lyn A. Gettys4
1
Faculty of Engineering, Kyushu Sangyo University, Japan; 2Faculty of Agriculture, Kinki University,
Japan; 3Faculty of Agriculture, Shinshu University, Japan; 4Center for Aquatic and Invasive Plants,
University of Florida, USA

ABSTRACTThe objective of this study is to collect basic information on flora along roadside, especially in curbside
cracks of road, for evaluating biodiversity in urban landscape. A curbside crack in this study was defined as alinear space (under 20 mm in width) between the asphalt pavement and curbstone. The species composition ofplants invading curbside cracks was surveyed in 38 plots along the serial National Route, over a total length of
36.5 km, in Fukuoka City in southern Japan. In total, 113 species including native plants (83 species, 73.5%),
perennial herbs (57 species, 50.4%) and woody plants (13 species, 11.5%) were recorded in curbside cracks.
Buried seeds were also obtained from soil in curbside cracks, which means the cracks would possess a potential
as seed bank. Incidentally, no significant differences were found in the vegetation characteristics of curbside
cracks among land-use types (Kolmogorov-Smirnov Test, P > 0.05). From these results, curbside cracks would
be likely to play an important part in offering habitat for plants in urban area.
Keywords: Biodiversity, Curbside Crack, Roadside Vegetation, Seed Bank, Urban Area

INTRODUCTION

MATERIALS AND METHODS

Roads are important infrastructure componentsthat provide critical corridors for transporting goods
and humans. Expansion and integration of asphalted
road networks would symbolize urban landscape.
Some plants, however, become established incurbside cracks of road and cause deterioration ofasphalt and curbs, reducing road surface longevity
and safety. Therefore, road managers spend aconsiderable amount of time and money on roadsidevegetation management [4]. In this context, several
ecological traits of plants in curbside cracks of roadhave been also shown for effective road management [4], [5], [18].
On the other hand, there has been growinginterest in the effect of urbanization on thebiodiversity and ecosystems [12], [19], [20]. And, toevaluate the urban biodiversity and ecosystems, thesites where could be habitats for plant, such as
wetland, riverside, garden, park or shrine in thecities, have been surveying [12].
In this study, we hypothesize that roadsides,
especially curbside cracks of road, can be site wheresome plants establish including ecologicallyvaluable species, and be evaluated as useful habitatfor plant. To investigate above hypothesis, wesurveyed plant that invades curbside cracks of road;we compared species composition and characteristics in the curbside cracks among land-use types inurban area. The objective of this study is to collectbasic information on flora along roadside, especiallyin curbside cracks of road, for evaluating biodiversity in urban area.

Study Area
Surveying of vegetation in curbside cracks was
conducted in Fukuoka City, southern Japan, in
September 2012 along National Route 3, 202 and263, over a total distance of 36.5 km (Fig. 1).
Fukuoka City is one of the biggest cities inJapan besides Tokyo, Osaka and Nagoya, and the
population is around one and a half million, thedensity is 4,392 km-2, as of May 1, 2013 (Fukuoka
City Environmental Date System). According to
AMEDAS (Automated Meteorological Data AcCxxxxity

Route 3
Route 202
Route 263

0 2 4 kmFig. 1427

Location of study sites.

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1Vegetation characteristics of curbside cracks amongland-use types.
ｘｘ
Vegetation characteristics
Average number ofSannon-Wiener's
species
diversity index (H ')Number of survey
plots

Total number of
species

ForestBusiness area
Residential districts
Developed land
Dry fields
Paddy fields

8
12
14
1
3
0

63
45
41
20
23
-

13.3
10.6
18.7
20.0
10.0
-

1.670
1.952
1.785
2.987
1.675
-

19.0
35.6
39.0
40.0
30.4
-

P -value-

0.200ns0.194ns

0.053ns0.200ns

Land-use types

Percentage of nonnative species

P > 0.05: ns indicates not significant using Kolmogorov-Smirnov test.

quisition System) from 2003 to 2012, Fukuoka City
lies in the warm-temperature zone, with values of
Kira’s Warmth Index [9] ranging from 143.4 to155.5 °C and with annual precipitation of 1,020 to
2,018 mm.

pared pots were put under the constant temperatureof 25 °C with 12 hours light of 3,300-3,600 lux a
day for 3 months, and plant emerged from the soil
was regularly identified.
Data Analysis

Species Composition and Characteristics
Braun-Blanquet cover-abundance scale (r, +, I, II,
III, IV and V) was transformed as follows: r and +,0.1%; I, 5.0%; II, 17.5%; III, 37.5%; IV, 62.5%; andV, 87.5%.
To test whether characteristics of vegetation incurbside cracks were different among land-use types,
we conducted a Kolmogorov-Smirnov test, under thenull hypothesis that vegetation characteristics of
curbside cracks were equivalent across land-use
types [3], [21]. The vegetation characteristics
employed were the following: the total number of
species, average number of species, SannonWiener’s diversity index (H’) and the percentage of
non-native species.
Horn’s measurement of overlap [6] was donewith mean cover data of species in each land-use
type in order to examine the similarity of species
composition among land-use types. According to theEq. (1), Summed Dominance Ratio (SDR) of species[14] in each land-use type was also calculated;

The species composition of vegetation incurbside cracks was recorded according to themethodology of Braun-Blanquet cover-abundancescale [2]. A curbside crack was defined as a linear
space (under 20 mm in width) between the asphalt
pavement and curbstone [4]. We located 38 survey
plots along the route at intervals of approximately 1
km. The size of the plots was 50 m (length) × 20 mm(maximum width of the crack).
Plant nomenclature used in this paper followed
Miyawaki et al. (1994), Baba (1999) and Shimizu(2003). All the recorded species were categorized bylife form (dormancy form, disseminule from,radicoid form and growth form) and invasive status(native or non-native), in order to characterize thevegetation surveyed. Life form was based on thedescription by Raunkiaer (1934) and Numata (1990),
and we distinguished non-native from native species
based on published literature [1], [11], [17]. Using
aerial photographs and field observation, dominantland-use types within a radius of 100 m from eachsurvey plot were classified as residential districts,
dry fields, developed land, paddy fields, forest, andbusiness area.

SDR = (F’ + C’) / 2(1)

Where F’ and C’ is the ratio of frequency andcover of each species to the numbers of the mostabundant species, respectively.
To find out whether the proportion of each life
form was different among land-use types, we
conducted a two-way ANOVA. The differences in
pH and EC of curbside crack soil among land-use
types were also analyzed using an ANOVA. All of
the date for the ANOVAs were used after transforming to ln(x + 0.5) value.

Soil Property
The soil was collected from curbside crack ineach survey plot, using stainless spatula, for measurement of pH and EC.
And then, in order to estimate the potential flora
in curbside crack, the soil obtained from the crack
was spread over 20 cm2 with thickness of 1.5 cm onthe vinyl pot filled with expanded vermiculite. Pre428

GEOMATE-Nagoya, Nov.13-15, 2013

Table 2

Number of species emerged from soil of curbside wee.
crack obtained in each vegetation type.
Number of survey
plots

Total number of
species

Study parameter
Average number of
species

Maximum numberof species

Minimum numberof species

V1

26

17

3.4

7

1

V2

a9

14

3.1

6

1

V3

q3

10

4.3

8

1

Total

38

20

3.4

8

1

Vegetation types

See Fig. 2 and Appendix 1. Eight unknown species were excluded. Of the 20 species identified, 2 plants, Juncus tenuis Willden. and Aira caryohyllea L., were not recorded at the field survey.
Horn's overlap index (Ro )RESULTS

1.0

0.8

0.6

0.4

Species Composition and Characteristics
n = 26

V1

In total, 113 species including 83 (73.5%)
natives were observed in curbside cracks along thesurveyed routes (Appendix 1), of which 100 (88.5%)
species were herbaceous and 13 (11.5%) species
were woody plants. In the former, 57 perennials(50.4%) were recorded．Of the 36 families obtainedin this survey (Appendix 1), Poaceae and Asteraceae
accounted for the majority of herbaceous plants(47/100 species), and Ulmaceae was dominant inwoody plants recorded (4/13 species).
No significant differences were found in thevegetation characteristics of curbside cracks acrossland-use types (P > 0.05) (Table 1).
Using Horn’s measurement of overlap threevegetation types could be distinguished (Fig. 2).
Type V1 contained business area and residential
districts (n = 26), and Type V2 included forest anddeveloped land (n = 9). Type V3 consisted of dry
fields (n = 3). Common species to all vegetation
types (12/113 species) were Artemisia princeps
Pamp., Digitaria ciliaris (Retz.) Koel., Eleusine
indica (L.) Gaertn., Euphorbia supina Rafin.,
Lactuca indica L., Oxalis corniculata L., Paspalum
dilatetum Poir., Sagina japonica (Sw.) Ohwi,
Setaria viridis (L.) Beauv., Solidago altissima L.,
Taraxacum officinale Weber and Youngia japonica(L.) DC. (Appendix 1). On the other hand, species
that emerged just in some specific type or other werealso observed. The species occurred only in Type V1
were 35 plants, e.g. Cynodon dactylon (L.) Pers.,
Gnaphalium japonicum Thunb. and Trifolium
dubium Sibth., and those in Type V2 were 39 plants
including Bidens frondosa L., Carex lenta D. Don,
Clinopodium micranthum (Regel) Hara, Festuca
arundinacea Schreb., etc. Four species of Euphorbia
muculata L., Lespedeza cuneata (Dum. Cours.) G.
Don, Ulmus davidiana Planch. var. japonica(Rehder) Nakai and Viola mandshurica W. Becker

V2

n =9

V3
n =3

Fig. 2 Classification among 5 land-use types basedon mean cover of component species, using Horn's
measurement of overlap. See Appendix 1.

were found only in Type V3.
In the top 10 species of SDR in each type (Fig. 3),lots of perennials (H and Ch) were found as well as
ephemeral plants (Th(w) and Th), and barachory(D4) or anemochory (D1) was the dominantdispersal modes. Definite tendency was not shown
in radicoid and growth forms. Incidentally, theproportion of life forms of vegetation in curbside
cracks was not statistically different among the types(P > 0.05).
Soil Property
There was no significant difference in pH and
EC of curbside crack soil across the types (P > 0.05)(Appendix 1).
Seedlings from curbside crack soil which spreadover the pot were shown in every pot (max., 8 species; and min., 1 species) (Table 2 and Appendix 1).
In total, 20 species emerged from the pot, of which 2
species had not been observed at the field survey.
DISCUSSION
Investigating the vegetation in curbside cracks ofroad, 36 families with 113 species were observed(Appendix 1). Our results are not surprising because
429

GEOMATE-Nagoya, Nov.13-15, 2013

Poaceae and Asteraceae dominated the plants
observed in this survey (Fig. 3 and Appendix 1). Incidentally, correlation between these dispersal
modes and families is definite.
A common species among vegetation types
would be defined as a typical species in curbside
crack vegetation (Fig. 2 and Appendix 1); to name afew, Artemisia princeps Pamp., Digitaria ciliaris(Retz.) Koel., Taraxacum officinale Weber, etc.
Conversely, a unique species in each vegetation type
could be a peculiar species which affected by thesurrounding land-use, e.g. Phyllanthus urinaria L.,
Talinum crassifolium Willd., Impatiens textori Miq.
and Viola mandshurica W. Becker. To obtain
biodiversity more from curbside cracks of road inurban landscape, therefore, securing various landuse types in the city would be also needed.
Recognizing road is one of the serious problems
today in natural ecosystems would be required- forinstance, expansion and integration of road networks,
which accompany urbanization, can cause fragmentation and extinction of plant populations andcommunities [7], [16]. And furthermore, roads
become dispersal corridors for plants, including nonnative species [8], [10]. However, to appreciate therole of curbside cracks of road in offering habitatand seed bank place for plants, including much
native species, might be also very important in urban
biodiversity.

road has also become an important corridor for
dispersal and expansion of plants as well as transporting humans and all the goods we need [8], [10].
Ephemeral (annual and biennial) and non-nativeplants are species having the highest advantages incurbside cracks [5]. Of 113 species recorded in thissurvey (Fig. 3 and Appendix 1), however, plenty ofperennial (61.9%), native (73.5%) and woody(11.5%) species were confirmed. The characteristics including diversity index (H’) were not also
affected by land-use types (Table 1). Furthermore,
20 species including 2 species not recorded at thefield survey were obtained from the soil in curbside
cracks of road (Table 2 and Appendix 1). Therefore,
we suggest that curbside cracks would be likely toplay an important part in offering habitat and seedbank for plants regardless of surrounding land-use
types in urban area although there is the problem ofdeteriorations of road [4], [5].
Hayasaka et al. (2011, 2012) mentioned that themain ecological types of curbside crack vegetation
were species with gravity dispersal (barochory) or
wind dispersal (anemochory) mechanisms. Suto et al.
(2006) reported the similar opinion of view too.
Additionally, both of them were also referred that
Poaceae and Asteraceae were dominant families incurbside crack environments [4], [5], [18]. Theseprevious studies support our results that species withbarachory or anemochory mechanisms and those inxx

Proportion of life forms (%)

100%
100

(I)
P = 0.757 ns

100
100%

175
75%

175
75%

150
50%

50%
150
Th(w)
Th
H
Ch

125
25%
100
0%
V1
群A

V2
群B

R5
R4
R3
R2

125
25%
100
0%

V3
群C

100
100%

( III )
P = 0.908 ns

V1
群A

V2
群B

V3
群C

100%
100

( IV )
P = 0.830 ns

175
75%

75%
175

150
50%

150
50%

t-p
t,t-p
t
r
ps
pr
p-b
e
b-p

( II )
P = 0.645 ns

125
25%

125
25%

D4
D3
D1

100
0%
V1
群A

V2
群B

0%
100

V3
群C

V1
群A

V2
群B

V3
群C

Vegetation types

Fig. 3 Proportion of life forms of the top 10 species in SDR in each vegetation type. Life forms are as follows:(I), dormancy form; (II), disseminule from; (III), radicoid form; and (IV), growth form. P > 0.05: ns indicates
not significant using a two-way ANOVA. See Fig. 2.
430

GEOMATE-Nagoya, Nov.13-15, 2013

Appendix 1 Species recorded in this survey and they were listed, according as component species in eachvegetation type.
Vegetation types
V1(n = 26)

V2(n = 9)V3(n = 3)Occurrence
frequency
(%)

Ⅴ
Ⅱ
Ⅱ
Ⅰ
Ⅱ
Ⅱ
+
+
Ⅱ
Ⅳ
Ⅲ
+

Ⅴ
Ⅰ
Ⅱ
Ⅰ
Ⅱ
Ⅲ
Ⅰ
Ⅰ
Ⅱ
Ⅰ
Ⅲ
Ⅱ

81.60
84.20
47.40
55.30
36.80
63.20
7.9
10.50
76.30
23.70
78.90
13.20

Species

FamilyCommon name

Artemisia princeps Pamp. #Digitaria ciliaris (Retz.) Koel. † #Eleusine indica (L.) Gaertn. †Euphorbia supina Rafin. * †Lactuca indica L. † #Oxalis corniculata L. #Paspalum dilatatum Poir. *Sagina japonica (Sw.) Ohwi † #Setaria viridis (L.) Beauv. † #Solidago altissima L. *Taraxacum officinale Weber *Youngia japonica (L.) DC. †Asteraceae
Poaceae
PoaceaeEuphorbiaceae
Asteraceae
Oxalidaceae
Poaceae
Caryophyllaceae
Poaceae
Asteraceae
Asteraceae
Asteraceae

Japanese mugwort
Southern crabgrass
Indian goosegrass
Milk purslane
Indian lettuce
SorrelDallis grass
Pearlwort
Green bristlegrass
Canada goldenrod
Dandelion
Oriental false hawksbeard

Ⅱ
Ⅲ
Ⅲ
Ⅲ
Ⅱ
Ⅲ
+
+
Ⅴ
Ⅰ
Ⅲ
r

Amaranthus spinosus L. * †Ambrina ambrosioides (L.) Spach * †Ambrosia artemisiaefolia L. var. elatior (L.) Descurtilz * †A virginicus L. *Aphananthe aspera (Thunb.) Planch.
Calystegia hederacea Wall.
Capsella bursa-pastoris Medicus † #Cayratia japonica (Thund.) Gagn.
Celtis sinensis Pers. var. japonica (Planch.) Nakai
Cynodon dactylon (L.) Pers.
Cyperus iria L. †Cyperus rotundus L.
Digitaria violascens Link †Eragrostis multicaulis Steud. †Stenactis annuus (L.) Cass. * †Glechoma hederacea L.subsp.grandis (A.Gray) Hara #Gnaphalium japonicum Thunb. #Isachne globosa (Thunb.) O. Kuntze
Kalimeris yomena Kitam.
Melia azedarach L. var. subtripinnata Miq.
Muhlenbergia japonica Steud.
Ophiopogon japonicus (L. fil.) Ker Gawl.
Panicum dichotomiflorum Michx. * †Phyllanthus urinaria L. † #Phytolacca americana L. *Polygonum lapathifolia (L.) S. F. Gary †Portulaca oleracea Cvs. * †Portulaca oleracea L. †Rorippa indica (L.) Hiern †Sedum bulbiferum Makino †Talinum crassifolium Willd. * #Trifolium dubium Sibth. * † #Zanthoxylum schinifolium Sieb. et Zucc.
Zephyranthes candida (Lindl.) Herbert *Zoysia japonica Steud.

Amaranthaceae
Chenopodiaceae
Asteraceae
Poaceae
Ulmaceae
Convolvulaceae
Brassicaceae
Vitaceae
Ulmaceae
Poaceae
Cyperaceae
Cyperaceae
Poaceae
Poaceae
Asteraceae
Lamiaceae
Asteraceae
Poaceae
Asteraceae
Meliaceae
Poaceae
Liliaceae
Poaceae
Pyllanthaceae
Phytolaccaceae
Polygonaceae
Portulacaceae
Portulacaceae
Cruciferae
Crassulaceae
Portulacaceae
Fabaceae
Rutaceae
Amaryllidaceae
PoaceaeSpiny amaranth
Mexican tea
RagweedBroomsadge bluestem
Aphananthe
Japanese false bindweed
Shepherd's purse
Bushkiller
Chinese hackberry
Bermuda grass
Rice galingale
Nut grass
Violet crabgrass-----Annual fleabane
AlehoofJapanese cudweed
Dwarf white-striped banboo-----Chinaberry-----Mondo grass
Fall panicum
Chamberbitter
Pokeweed
Curlytop knotweed
Purslane pusley
Common purslane
Variableleaf yellowcress-----Coral flower
Suckling clover-----Fairy lily
Lawnglass

r
r
r
r
Ⅱ
r
r
r
+
Ⅲ
r
r
Ⅰ
r
Ⅰ
r
Ⅰ
r
r
+
+
+
r
r
r
r
r
+
+
r
r
r
r
r
Ⅱ

Acalypha australis L. † #Achyranthes bidentata Blume var. Tomentosa (Honda) Hara
Amorpha fruitcosa L. *forma citrulloides (Lebas) Rehd.
Aster ageratoides Turcz. subsp.
Kalimeris incisa (fisch) DC.
Bidens frondosa L. * †Urtica thunbergiana Sieb. et Zucc.
Boehmeria tricuspis (Hance) Makino
Boehmeria spicata (Thunb.) Thunb.
Boenninghausenia japonica Nakai
Carex lenta D. Don
Chenopodium centrorubrum (Makino) Nakai † #Cirsium dipsacolepis (Maxim.) Matsum.
Clerodendron trichotomum Thunb.
Clinopodium micranthum (Regel) Hara
Dactyloctenium aegyptium (L.) Beauv. *Dioscorea japonica Thunb.
Duchesnea indica (Andr.) Focke
Echinochloa crus-galli (L.) Beauv. var. caudata (Roshev.) Kitag. † #Festuca arundinacea Schreb. *Ficus erecta Thunb.
Geranium nepalense Sweet subsp. Thunbergii (Sieb. et Zucc) Hara
Impatiens textori Miq. †Justicia procumbens L. †Oplismenus undulatifolius (Arduino) Roemer et Schultes
Oplismenus compositus (L.) Beauv.
Paspalum thunbergii Kunth
Petasites japonicus (Sieb. et Zucc.) Maxim.
Picris hieracioides L. subsp. japonica (Thunb.) Krylov †Plantago lanceolata L. *Polygonum caespitosum Bl. var. laxiflorum Meisn. †Reynoutria japonica Houtt.
Persicaria Longiseta (De Bruyn) Kitag. †Persicaria thunbergii (Sieb. et Zucc.) H. Gross † #Rubus buergeri Miq.
Rumex japonicus Houtt.
Trifolium repens L.
Viola verecunda A. Gray

Euphorbiaceae
Amaranthaceae
Fabaceae
Vitaceae
Asteraceae
Asteraceae
Asteraceae
Urticaceae
Urticaceae
Urticaceae
Rutaceae
Cyperaceae
Chenopodiaceae
Asteraceae
Verbenaceae
Lamiaceae
Poaceae
Dioscoreaceae
Rosaceae
Poaceae
Poaceae
Moraceae
Geraniaceae
Balsaminaceae
Acanthaceae
Poaceae
Poaceae
Poaceae
Asteraceae
Asteraceae
Plantaginaceae
Polygonaceae
Polygonaceae
Polygonaceae
Polygonaceae
Rosaceae
Polygonaceae
Leguminosae
Violaceae

Australian acalypha-----Desert false indigo-----Wild chrysanthemum-----Devil's beggartickRamie---------------Flat sedge
Fat hen-----Harlequin glory bower-----Crowfoot grass
Japanese yam
Mock strawberry
Barnyardgrass
Tall fescue-----Oriental geranium
Touch-me-not
Common asystasia
Wavyleaf basketgrass-----Japanese paspalum
Fuki
Hawkweed oxtongue
Ribwort plantain
Asiatic smartweed
Japanese knotweed
Tufted knotweed
Water pepper----------White clover
Japanese violet

Euphorbia muculata L. * †Lespedeza cuneata (Dum. Cours.) G. Don
Ulmus davidiana Planch. var. japonica (Rehder) Nakai
Viola mandshurica W. Becker

Euphorbiaceae
Fabaceae
Ulmaceae
Violaceae

EyebaneSericea lespedeza
Japanese elm
VioletArtemisia capillaris Thunb.
Conyza bonariensis (L.) Cronq. * †Cyperus microiria Steud. † #Dactylis glomerata L. *Digitaria timorensis (Kunth) Balansa †Eragrostis poaeoides Beauv. * †Gnaphalium spicatum Lam. *Leptochloa chinensis (L.) Nees †Paspalm urvillei Steud. *Persicaria capitata (Buch. -Ham. ex D.Don) H. Gross * #Plantago asiatica L.
Oenothera Laciniata Hill * †Sambucus chinensis Lindley
Setaria glauca (L.) Beauv. †Asteraceae
Asteraceae
Cyperaceae
Poaceae
Poaceae
Poaceae
Asteraceae
Poaceae
Poaceae
Polygonaceae
Plantaginaceae
Onagraceae
Caprifoliaceae
Poaceae

Capillary artemisia
Flax-leaf fleabane
Asian flatsedge
Orchard grass----------Spiked cudweed
Asian sprangletop
Knot grass
Pink-head knotweed
Chinese plantain
Cutleaf eveningprimrose
Chinese elderberry
Yellow foxtail

431

2.6
2.6
2.6
2.6
5.3
2.6
2.6
2.6
2.6
23.70
5.3
2.6
5.3
2.6
18.40
2.6
2.6
2.6
2.6
2.6
2.6
10.50
2.6
5.3
2.6
2.6
2.6
7.9
2.6
2.6
5.3
2.6
2.6
2.6
18.40
+
+
+
+
+
Ⅰ
+
Ⅱ
+
+
+
+
+
+
+
+
+
+
+
+
+
+
Ⅰ
+
Ⅱ
+
+
+
+
+
+
Ⅰ
+
Ⅰ
+
+
Ⅰ
+
Ⅰ

2.6
2.6
2.6
2.6
2.6
5.3
2.6
10.50
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
2.6
5.3
2.6
10.50
2.6
2.6
2.6
2.6
2.6
2.6
5.3
2.6
5.3
2.6
2.6
5.3
2.6
5.3
Ⅰ
Ⅰ
Ⅰ
Ⅱ

+
Ⅱ
+
r
Ⅱ
Ⅲ
r
r
+
r
+
Ⅰ
r
Ⅰ

+
+
Ⅰ
+
Ⅱ
Ⅱ
Ⅰ
+
+
+
Ⅱ
Ⅲ
Ⅰ
Ⅱ

2.6
2.6
2.6
2.6
5.3
23.70
10.50
5.3
26.30
21.10
7.9
5.3
10.50
5.3
15.80
10.50
7.9
13.20

GEOMATE-Nagoya, Nov.13-15, 2013

Appendix 1

Continued.
Vegetation types

Species

FamilyCommon name

Solanum nigrum L. †Zelkova serrata (Thunb.) Makino
Cleistogenes hackelii (Honda) Honda
Erigeron canadensis L. * †Oxalis corymbosa DC. *Zanthoxylum ailanthoides Sieb. et Zucc.
Eragrostis ferruginea (Thund.) Beauv.
Miscanthus sinensis Anderss.
Sporobolus fertilis (Steud.) W. Clayton

Solanaceae
Ulmaceae
Poaceae
Asteraceae
Oxalidaceae
Rutaceae
Poaceae
Poaceae
PoaceaeBlack nightshadeJapanese zelkova-----Canadian horseweed
Violet wood-sorrel
Japanese prickly-ash
Korean lovegrass
Eulalia
Giant paramatta grass

V1(n = 26)

V2(n = 9)

r
r
Ⅰ
Ⅰ
+
+

Ⅰ
+

+
Ⅰ
+

V3
(n = 3)Occurrence
frequency
(%)

Ⅰ
Ⅰ
Ⅰ
Ⅰ
Ⅰ
Ⅱ
Ⅳ

7.9
5.3
13.20
13.20
10.50
5.3
5.3
7.9
5.3

pH of soil in curbside cracks; mean ± S.D.

P = 0.053ns

007.5 ± 00.4

007.2 ± 00.6

007.2 ± 00.4

EC (µS cm-1 ) of soil in curbside cracks; mean ± S.D.

P = 0.924

ns

162.1 ± 53.6

157.3 ± 65.0

173.0 ± 22.3

Roman numerals and other symbols for each species indicate SDR classes, defined as follows: r, under 5%; +,under 10%; I, under 20%; II, under 40%, III, under 60%; IV, under 80%; and V, above 80%. P > 0.05: ns
indicates not significant using an ANOVA. *, non-native species; †, ephemeral species (annual and biennial
plants); and #, species emerged from soil [See Table 2]. Highlight; woody species. ------; unknown.

[10] Kowarik, I., 2003. Human agency in biologicalinvasions: secondary releases foster naturalisation and population expansion of alien plant
species. Biol. Invasions 5, 293-312.
[11] Miyawaki, A., Okuda, S. and Fujiwra, R., 1994.
Handbook of Japanese vegetation. Shibundo Co.,
Ltd., Tokyo. 646 pp. In Japanese.
[12] Niemelä, J., 2011. Urban ecology. Oxford
University Press Inc., New York. 374 pp.
[13] Numata, M., 1990. The ecological encyclopediaof wild plants in Japan. Zenkoku Noson Kyoiku
Kyokai, Tokyo. 664 pp. In Japanese.
[14] Numata, M. and Yoda, K., 1957. The
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grasslands (1). J. Jap. Soc. Herb. Crops Grassl.
Farm. 3, 4-11. In Japanese.
[15] Raunkiaer, C., 1934. Life forms of plants andplant geography. Oxford University Press,
London. 632 pp.
[16] Rentch, J.S., Fortney, R.H., Stephenson, S.L.,
Adams, H.S., Grafton, W.N. and Anderson, J.T.,
2005. Vegetation-site relationships of roadsideplant communities in West Virginia, USA. J.
Appl. Ecol. 42, 129-138.
[17] Shimizu, T., 2003. Naturalized plants of Japan.
Heibonsha Ltd., Publishers, Tokyo. 337 pp. In
Japanese.
[18] Suto, Y., Takahashi, Y. and Ogasawara, M.,
2006. Summer weed vegetation of roadpavement seams in Route 4. J. Weed Sci. Tech.
51, 1-9. In Japanese.
[19] Tiébré, M.-S., Saad, L. and Mahy, G., 2008.
Landscape dynamics and habitat selection by
the alien invasive Fallopia (Polygonaceae) in
Belgium. Biodivers. Conserv. 17, 2357-2370.
[20] Tyser, R.W. and Worley, C.A., 1992. Alien
flora in grasslands adjacent to road and trail
corridors in Glacier National Park, Montana(USA). Conserv. Biol. 6, 253-262.
[21] Zar, J.H., 1984. Biostatistical analysis, 2nd ed.
Prentice Hall, Englewood Cliffs. 718 pp.

ACKNOWLEDGEMENTS
We sincerely thank Atsuhiro Tanaka, Masaaki
Furuno and Hisae Yonao, Ecol. Lab., Kyushu
Sangyo Univ., for assistance with the field work.
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their leaf appearances. Shinano Mainichi
Shinbunsha, Nagano. 396 pp. In Japanese.
[2] Braun-Blanquet, J., 1964. Pflanzensoziologie.
Grundzüge der Vegetationskunde, 3rd ed.
Springer-Verlag, Vienna. 865 pp.
[3] Davis, J.C., 1986. Statistics and data analysis ingeology, 2nd ed. John Wiley & Sons, New York.
656 pp.
[4] Hayasaka, D., Asasaka, M., Miyauchi, D. andUchida, T., 2011. Classification of roadsideweeds along two highways in different climatic
zones according to ecomorphological traits.
Weed Technol. 25, 411-421.
[5] Hayasaka, D., Asasaka, M., Miyauchi, D.,
Elgene, O.B. and Uchida, T., 2012. Qualitative
variation in roadside weed vegetation along anurban–rural road gradient. Flora 207, 126-132.
[6] Horn, H.S., 1966. Measurement of "Overlap" incomparative ecological studies. Am. Nat. 100,
419-424[7] Jantunen, J., Saarinen, K., Valtonen, A., Saarnio,S., 2006. Grassland vegetation along roads
differing in size and traffic density. Ann. Bot.
Fenn. 43, 107-117.
[8] Kalwij, J.M., Milton, S.J., McGeoch, M.A.,
2008. Road verge as invasion corridors? A
spatial hierarchical test in an arid ecosystem.
Landscape Ecol. 23, 439-451.
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432

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DYE TRACER EXPERIMENTS FOR IDENTIFYING SOLUTEDISPERSIVITY IN UNSATURATED POROUS MEDIA
Kazuya Inoue1, Takayuki Fujiwara1 and Tsutomu Tanaka1
Graduate School of Agricultural Science, Kobe University, Japan

1

ABSTRACTA methodology using spatial moment analysis linked with image processing of a dye tracer behavior in
porous media was applied to identify time-series variation of dispersivities not only in longitudinal but intransverse directions under saturated and unsaturated conditions. Dye tracer experiments were carried out in a
two-dimensional and vertically placed water tank with the dimensions of 100 cm width, 100 cm height and 3 cm
thickness under saturated and unsaturated flow conditions. An image processing technique based on digitalized
spatial distributions of dye tracer allowed to link with a spatial moment approach to identify the temporal changeof the longitudinal and transverse dispersivities. Dispersivities exhibited an increasing and decreasing tendency
associated with infiltration rates and showed a marked difference between estimates under saturated andunsaturated conditions. Transverse dispersivities under unsaturated conditions were approximately one orderlarger than those under saturated conditions. This attributed to the effect of air distributions in porous media on
the temporal and spatial change of solute dispersion phenomena.
Keywords: Dispersivity, Dye tracer, Unsaturated porous media, Spatial moment, Image analysis

measurements while the spatial resolution istherefore limited.
In a nondestructive manner, laboratory scale
experiments at different spatial scales have shownthat techniques based on image analysis of dye
tracer movements could be successfully used to
study solute mass transport processes in porous
media [8]-[11]. The objectives of this study are to
determine the both longitudinal and transverse
dispersivities in unsaturated porous media using
image analysis linked with spatial moment analysis
and to elucidate the nature of dispersion phenomena
in unsaturated porous media compared to saturated
porous media. A new laboratory flow-tank
experiment designed to study this issue is also
described in this paper.

INTRODUCTION
Fertilizers and pesticides have ensured highproductivity of agriculture and a quality supply offood in past decades. However, use of fertilizers andpesticides can raise concerns about health risks fromresidues in food and drinking water such as
methemoglobinemia
andneurodegenerative
disorders like Parkinson [1], [2]. Fast transport offertilizers and other agrochemicals into subsurface
or groundwater systems has been recognized as aserious threat due to high concentration of solutes.
Thus, an understanding of solute transportmechanism through not only saturated but
unsaturated zones under various hydraulicconditions is important in environmental protection
and agricultural activity.
In order to understand and express the transport
behavior of contaminants in a subsurface, thetransport parameters such as longitudinal andtransverse dispersivities are some of the key factorsthat play an important role in spreading thecontaminants. Several studies have been conducted
through column experiments with well definedboundary conditions [3]-[5]. In such studies, solute
breakthrough curves typically are measured in thecolumn’s effluent. They provide integrated and fluxaveraged information on the processes governing
solute transport in the column. Time domainreflectometry has been also used to determine
resident solute concentrations in a nondestructive
manner both in the laboratory and in the field [6],[7].
However, this method is restricted to local

DYE TRACER EXPERIMENTS
Materials and Methods
In the experiments, Brilliant Blue FCF is used asa dye tracer which differentiates the tracer evolution
visually from the ambient pore water. The initialconcentration of the Brilliant Blue FCF dye tracer
was set to 1.0 mg/cm3. Although the specific gravity
of dye tracer is 1.0001 measured using the specificgravity meter and the initial concentration of tracer
is determined to be low enough to avoid densityinduced flow effects, there is no denying that theeffect of gravity on solute transport. This dye ischosen based on good contrast with soil for433

GEOMATE-Nagoya, Nov.13-15, 2013

visualizing transport patterns of tracer plume andlow toxicity implied by its food dye designation[12].
In this study, as a soil material, silica sand with alow uniformity coefficient of 1.80 was selected inorder to reflect a relatively high hydraulicconductivity fields. Silica sand of concern had
0.085cm, 2.68 g/cm3 and 0.751 cm/s of physicalproperties such as the mean particle size, the particle
density and the hydraulic conductivity, respectively.
Silica sand was washed and dried at 110 °C before
the use to remove organic chemicals attached to theparticle surface.
Experimental
Conditions

Procedure

under

Distributor
3
65

U

z
x
100
10
S

Water table
5

Glass plate
S
U

Saturated

Dye tracer experiments were carried out in a
two-dimensional and vertically placed water flowtank with the dimensions of 100 cm width, 100 cm
height and 3 cm thickness. The water flow tankallowed to contain soils in order to form transparent
quasi two-dimensional solute transport phenomena
and consisted of two glass plates with 2 cm
thickness. Schematic diagram of experimental
apparatus is shown in Fig.1.
Soils were completely washed and saturated
before packing to avoid entering air and to conduct
experiments under the saturated condition. In theprocess of creation of flow field, water flow tank
was filled with water and silica sand from bottom to
top in 5 cm layers to achieve uniform packing. In
this process, soil was funneled using an extended
funnel. Each layer of interest was compacted prior tofilling the next layer, resulting in 0.42 of the porosity.
The porosity of each flow field was able to be
estimated indirectly from measurements of theparticle density and the dry soil bulk density.
After packing, water was applied to the flow tankunder a specific hydraulic gradient controlled byconstant head water reservoirs at the upstream anddownstream sides, while maintaining saturated
condition of porous media. A steady saturated flow
field was established when fluctuations in theobserved drainage rate, which was effluent from theconstant head water reservoir, and piezometerreadings could become negligible. After reachingsteady state flow conditions, dye tracer with thevolume of 25 cm3, which made flow paths visible,
was uniformly injected along the whole thickness ofthe flow tank. During the experiment, the profiles oftracer migration were periodically recorded using a
digital camera, which located about 100 cm away

Fig. 1

Unit: cm

Injection port in saturated flow experiments
Injection port in unsaturated flow experiments
Constant head water reservoir
Water pressure measurement port

Schematic drawing of the experimental
apparatus used in this study.

from the front face of the water flow tank.
Experimental
Conditions

Procedure

under

Unsaturated

Dye tracer experiments under unsaturated
conditions were conducted in a similar manner.
Internal drainage using constant head reservoirs
allowed for approximately one day to create an
unsaturated flow field after the flow tank was filledwith water and silica sand. Water table wasmaintained at the 10 cm from the bottom of thewater tank. After steady state condition wasestablished, dye tracer with the volume of 25 cm3
was injected in the same manner as saturated
experiments. Following that, water was applied
using a distributor placed 10 cm above the top of theexperimental apparatus, or the ground surface, as
shown in Fig.1. Three rainfall rates of 125, 190 and
290 mm/day, were set with no rainfall case. In theseexperiments, geomembrane was placed on the
ground surface to avoid the erosion due towaterdrops.
Spatial Moment Analysis Linked with Image
Processing
Each of the pixels representing an image has apixel intensity which describes how bright that pixel
is. In order to establish the relationship between the
pixel intensity of a pixel and dye tracer
concentration, a calibration was conducted in thesame manner reported by Inoue et al. [11]. Under
identical experimental conditions, a known
434

GEOMATE-Nagoya, Nov.13-15, 2013

concentration of dye tracer was injected into a
corresponding porous formation without a hydraulicgradient. The spread of dye was captured by thedigital camera. The same procedure was repeatedusing different concentrations of dye tracer.
Consequently, the concentration of the dye tracer asa function of the pixel intensity varied over the rangeof 0 mg/cm3 to 1.0 mg/cm3.
A commonly used measure of dilution is thespatial moments of aqueous concentrations, which
are calculated from snapshots of tracer plume atgiven times as follows [13].
M ij (t ) = ∫∞∞∫ c( x, z, t ) x z dxdz, i, j = 1, 2
i

j

−∞ −∞

10

1

0.1
0

M ij (t ) = ∫

∫

∞

(1)

Fig. 2−∞ −∞where H(x,z) is the area per unit pixel and B(x,z,t) is
the intensity at a corresponding pixel. The centroidof plume concentration distribution is calculated as
the normalized first order spatial moment by thefollowing equation.
MM(3)
xc = 10 , zc = 01
M 00
M 00
where x c and z c are the centroid locations of plumeconcentration distribution in the x and z coordinates,
respectively. The second order spatial moments arealso computed as follows.
σ
σ ij =  xx
 σ zxM 11
− xc z c 
M 00

M 02

− z c2 M 00


1 σ zz1 σ xx, αT =
2 ξc
2 ξc
1 σ xx1 σ zzαL =, αT =
2 ξc
2 ξc

5 cm

Fig. 3

40

50

60

70

80

z

Seepage line

290 mm/day
t = 30 min

Tracer plume

290 mm/day
t = 40 minx

Representative images of the change of dye
tracer distribution.

where α L is the longitudinal dispersivity, α T is thetransverse dispersivity and ξ c is the travel distanceof the center of tracer plume in the mean flow
direction at a given time t.
RESULTS AND DISCUSSION
Longitudinal Dispersivity(4)

The results of longitudinal dispersivity α L as afunction of the displacement distance undersaturated and unsaturated conditions are shown in
Fig.2. Longitudinal dispersivity estimates underunsaturated conditions are two to four times larger
than those under saturated conditions. The increaseof the longitudinal dispersivity may be induced fromdiversity of solute movement due to the effect of air
distribution. Several studies have pointed out thesame tendency in unsaturated soils [14].
Except for the case without the rainfall intensity
and under the saturated flow condition, longitudinal
dispersivity estimates also exhibit a rapid decreasing
and gradual increasing tendency and show a lessdependency on infiltration rates. Water applied to
the ground surface infiltrates and reaches an upper

where σ ij is the second order spatial moments.
Longitudinal and transverse dispersivities fromspatial moments of the distributed tracer plume arecalculated as the following Eqs. (5) and (6) undersaturated and unsaturated conditions, respectively
[11].

αL =

30

Results of the longitudinal dispersivity
estimates.

290 mm/day
t = 20 minj0 M 20− xc2
σ xz   M 00
=σ zz   M 11 − z x
c c
M
 00

20

Injection port

H ( x, z ) B ( x, z , t ) x z dxdz, i, j = 1, 2 (2)i10Displacement distance (cm)where x and z are the Cartesian coordinates, c is thesolute concentration, t is the time, M ij is the spatial
moments associated with the distribution of tracer
plume at a certain time, and i and j are the spatial
order in the x and z coordinates, respectively.
The pixel intensity distribution can be converted
to a concentration distribution by the calibration,
providing an analogy between Eq.(1) and Eq.(2).
∞Saturated
Case 1 (0mm/d)
Case 2 (125mm/d)
Case 3 (190mm/d)
Case 4 (290mm/d)

(5)
(6)

435

GEOMATE-Nagoya, Nov.13-15, 2013

Transverse Dispersivity
10

The results of transverse dispersivity α T as afunction of the displacement distance undersaturated and unsaturated conditions are shown in
Fig.4. Transverse dispersivity estimates underunsaturated conditions are also larger than thoseunder saturated conditions. Unlike the results of thelongitudinal dispersivity, the values of the transverse
dispersivity under unsaturated conditions more thanten times larger than those under saturated
conditions. Except for the case without the rainfall
intensity, transverse dispersivity estimates show aslight increase and a gradual decreasing tendency. It
is inferred that transverse solute displacement
depends largely on mixing of water and air whose
distribution
varieswiththedepth.
As
aforementioned above, the mobility of part of dye
tracer may be extremely low due to the effect of air
entrapped within pores. This point leads to larger
values of the transverse dispersivity underunsaturated conditions.
On the contrary to the case in longitudinal
dispersion phenomena under the unsaturated
condition, when water applied to the ground surface
reaches an upper part of dye tracer and affects thechange of dye tracer distribution, a shape of dye
tracer distribution extends horizontally, or laterally.
This implies the increase of the transverse
dispersivity as well as the decrease of thelongitudinal dispersivity.
As a whole, both the longitudinal and transverse
dispersivities exhibit a less dependency on
infiltration rates. Although the degree of increase ofwater content induced from rainfall application
decreases as rainfall intensity is lower, silica sandemployed in this study has a relatively highhydraulic conductivity. Thus, it is inferred that theinitial water distribution in the entire domain rather
than the rainfall intensity influences the subsequent
solute transport pathways.

Saturated
Case 1 (0mm/d)
Case 2 (125mm/d)
Case 3 (190mm/d)
Case 4 (290mm/d)

1

0.1

0.01
0

10

20

30

40

50

60

70

80

Displacement distance (cm)Fig. 4

Results of
estimates.

thetransverse

dispersivity

30

Saturated
Case 1 (0mm/d)
Case 2 (125mm/d)
Case 3 (190mm/d)
Case 4 (290mm/d)
40
50
60
70

100

10

1
0

10

20

80

Displacement distance (cm)Fig. 5Results of the ratio of longitudinal totransverse dispersivities.

part of dye tracer. Because flow velocity is larger
than solute velocity in unsaturated zone and affects
the change of tracer migration patterns, shape of dye
tracer distribution is shrunk longitudinally. In Fig.3,
representative images of the change of dye tracer
distribution are shown with seepage lines, whichwere visually observed through the experiments.
This duration may correspond to the decreasing
process of the longitudinal dispersivity due totemporarily shrunk shape of dye distribution. Afterinfiltrating water reaches a front of dye tracer, dyetracer migrates mainly with interstitial water.
However, part of dye tracer has relatively low
velocities due to the effect of air entrapped withinpores. Therefore, shape of dye tracer extends
longitudinally, leading to the increase of longitudinal
dispersivity estimates. Basically, as solutes movewith interstitial water, the intensity of infiltration
rates has little effect on the magnitude of thelongitudinal dispersivity under the experimental
conditions adopted in this study.

Ratio of Dispersivity
The results of the ratio of the longitudinal
dispersivity α L to the transverse dispersivity α T as afunction of the displacement distance undersaturated and unsaturated conditions are shown in
Fig.5. For all cases, the ratio increases with theincrease of the displacement distance. This indicatesthe shape of dye tracer distribution extends
longitudinally. Under saturated condition, initial
shape of dye tracer and its geometric shape strongly
affect the initial value of the transverse dispersivity[11], which is relatively larger value than an inherent
transverse dispersivity, or microdispersivity.
According to the dye migration, the transverse
dispersivity approaches to an asymptotic value.
Therefore, the transverse dispersivity in Fig.4 shows
436

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Comparison of dispersivities with other experimental results.
Longitudinal
dispersivity (cm)Transverse
dispersivity (cm)Displacement
distance (cm)Condition of watercontent

Reference

0.78 – 0.82

0.020 – 0.060

5 – 50Saturated

This study

0.025 – 0.10

0.005 – 0.018

35 – 60

Saturated

Inoue et al. [15]0.522 – 0.756

–

30.2

Saturated

Maraqa et al. [16]–0.000039 – 0.013

30

Saturated

Robbins

1.0 – 2.6

0.25 – 0.60

5 – 50Unsaturated

This study–

0.002930

Unsaturated

Massabò et al. [18]1.02 – 1.67

0.320 – 0.577

5 – 25

Unsaturated

Inoue et al. [19]2.6 – 18.3

0.03 – 2.20

6 - 14

Unsaturated

Abbasi et al. [20]0.966 – 1.631

–

30.2

Unsaturated

Maraqa et al. [16][17]an increasing tendency. On the other hand, theresults under unsaturated conditions reflect thechange of the degree of solute dispersion both inlongitudinal and lateral directions.

under saturated conditions. These estimation values
agree with experimental results in the literature,indicating that employed methodology is useful toidentify these transport parameters.

Comparison with Other Studies

ACKNOWLEDGEMENTS

In order to confirm the accuracy of identified
parameters, Table 1 compares the longitudinal andtransverse dispersivities identified in this study withflow tank results reported in the literature that wereconducted in a similar displacement distance. The
results obtained in this study are in good agreementwith other experimental results, although it seems
that the maximum value of the longitudinal
dispersivity is a slight larger value. This is probably
because pulse input of dye tracer effects on thetemporal change of the magnitude of the flow
velocity during the short time period at the
beginning of the experiments, leading to an
overestimate of the longitudinal dispersivity.

The work reported here was supported by JSPS
Grant-in-Aid for Young Scientists (B).
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Anderson H, “Blue babies and nitratecontaminated well water”, Environmental
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CONCLUSION
In the present study, dye tracer experiments
under saturated and unsaturated flow conditions
have been conducted for homogeneous flow field
filled with silica sand in order to investigatetransport characteristics. Spatial moment approach
linked with image analysis has applied to theestimation of not only the longitudinal dispersivity
but also the transverse dispersivity in porous media.
Experimental results revealed that transportparameters depend strongly on the water content
where solute passes through, leading to the larger
estimates under unsaturated conditions than those437

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Vanclooster M, “Three-dimensional modelingof the scale- and flow rate-dependency ofdispersion in a heterogeneous unsaturated sandy
monolith”, Vadose Zone Journal, Vol.5, 2006,
pp.515–528.
[6] Vanclooster M, Mallants D, Vanderborght J,
Diels J, Van Orshoven J, Feyen, J, “Monitoring
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lysimeter using time domain reflectometry”,
Soil Science Society of America Journal, Vol.59,
1995, pp. 337–344.
[7] Weihermuller L, Kasteel R, Vanderborght J,
Putz T, Vereecken H, “Soil water extraction
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pp.899–907.
[8] Jia C, Shing K, Yortsos YC, “Visualization andsimulation of non-aqueous phase liquids
solubilization in pore networks”, Journal ofContaminant Hydrology, Vol.35(4), 1999,
pp.363–387.
[9] Huang W, Smith CC, Lerner DN, Thornton SF,
Oram A, “Physical modeling of solute transportin porous media: evaluation of an imaging
technique using UV excited fluorescent dye”,
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[10] Jones EH, Smith CC, “Non-equilibrium
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[11] Inoue K, Takenouti R, Kobayashi A, Suzuki K,
Tanaka T, “Assessment of a UV excited
fluorescent dye technique for estimating solute
dispersion in porous media”, Journal ofRainwater Catchment Systems, Vol.17(1), 2011,
pp.1–9.
[12] Flury M. and Flühler H., “Tracer characteristics
of Brilliant Blue FCF”, Soil Science Society ofAmerica Journal, Vol.59(1), 1995, pp.22-27.

[13] Freyberg DL, “A natural gradient experiment on
solute transport in a sand aquifer 2. Spatial
moments and the advection and dispersion of
nonreactive tracers”, Water Resources Research,
Vol.22(13), 1986, pp.2031–2046.
[14] Vanderborght J, Vereecken H, “Review ofdispersivities for transport modeling in soils”,
Vadose Zone Journal, Vol.6, 2007, pp.29-52.
[15] Inoue K, Kobayashi A, Matsunaga N, Tanaka T,“Application of particle tracking method todispersivity identification and its experimental
verification”, Journal of Rainwater Catchment
Systems, Vol.13(2), 2008, pp.7-16.
[16] Maraqa MA, Wallce RB, Voice TC, “Effects ofdegree of water saturation on dispersivity andimmobile water in sandy soil columns”, Journalof Contaminant Hydrology, Vol.25, 1997,
pp.199-218.
[17] Robbins GA, “Methods for determining
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media in laboratory column experiments”,
Water Resources Research, Vol.25(6), 1989,
pp.1249-1258.
[18] Massabò M, Catania F, Paladino O, “A new
method for laboratory estimation of thetransverse dispersion coefficient”, Ground
Water, Vol.45(3), 2007, pp.339-347.
[19] Inoue K, Setsune N, Suzuki, F, Tanaka T,“Determining
transport
parametersforunsaturated porous media in flow-tank
experiments using image analysis”, Water
PollutionVIII Modelling, Monitoring andManagement, WIT Press, 2006, pp.309–319.
[20] Abbasi F, Simunek J, Feyen J, van Genuchten
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438

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

REUSE OF AGRICULTURAL AND FOOD RESIDUES FORRETARDING AND ATTENUATING NITRATE IN POROUS MEDIA
Kazuya Inoue1, Saki Matsuyama1 and Tsutomu Tanaka1
1

Graduate School of Agricultural Science, Kobe University, Japan

ABSTRACT
Nitrate pollution in groundwater is related to surplus nitrate fertilizers and animal waste disposal. As highnitrate concentration leads to health concern, mass reduction of nitrate in a contaminated site is important. Fromthe perspective of recent reuse streams, this paper assessed the potential of agricultural and food residues such as
rice husk, rice straw and used coffee as a nitrate attenuation material in porous media. Under saturated flow
conditions, column experiments were carried out in silica sand with a mixture of residues. KNO 3 or NaClsolutions were injected into columns and were analyzed using temporal moment approaches to characterize themobility of nitrate and chloride ions. The results showed that the mixture of rice straw leads to the increase of theretardation factor. The results also revealed that the use of rice husk and used coffee decreases the mass of bothanions, whereas the rice straw has little effect on attenuation of these anions.
Keywords: Nitrate, Agricultural and food residues, Reuse, Column experiments, Attenuation

almost 7 million from the previous year [5] and large
amount of spent coffee grounds are discharged.
Although part of them as well as rice husk and ricestraw is reused as compost or biodiesel [6], most ofthese are burned as a waste, which results in
production of carbon dioxide, the green house gas.
Thus, it is necessary to develop new technologies
enabling to reuse agricultural residues for useful
purposes.
This paper assessed the potential application ofagricultural residues including rice husk, rice straw
and spent coffee grounds for retarding andattenuating nitrate in porous media. Some quantity
factors such as the dispersivity, the retardation
factor, the mass recovery fraction and thedegradation rate constant were identified using
temporal moment approaches based on a time seriesof leachate concentration of nitrate or chloride ions.
Additionally, quantity parameters for assessing thepotential use of agricultural residues were also
discussed.

INTRODUCTION
Man-made nitrogen fertilizers became widelyused not only in Japan and the United States but also
around the world, providing an inexpensive sourceof nitrogen and other plant nutrients that resulted inhuge increases in agricultural productivity. In thepast century, the global nitrogen cycle has been
increasingly affected by nitrogen fixation for
agricultural activities, which now exceeds theamount that occurs naturally. Both groundwater andsurface water can be contaminated by excess nitrate
as a result of agricultural activities. Human exposure
to nitrate and nitrite is mainly from the ingestion offood and drinking water [1]. Therefore, public water
utilities are required to maintain nitrate levels below
a Maximum Contaminant Level of 10 mg/L nitratenitrogen that was instituted to protect against
methemoglobinemia, to which infants are especiallysusceptible. In addition to methemoglobinemia, a
range of other health effects have been associatedwith ingesting nitrate-contaminated drinking water,
including various cancers, neural tube defects andthyroid conditions [2],[3].
In associated with agricultural activities, large
amounts of agricultural wastes are discharged, forexample, from the harvesting of rice, instant coffee
manufacture and field preparation [4]. Rice husk andrice straw are the main agro-industrial residues fromthe rice milling industry. Coffee is also one of thelargest agricultural products that are mainly used forbeverages. According to the U.S. department ofAgriculture, the world’s coffee production in
2012/13 is forecast at a record 151 million bags, up

MATERIALS AND METHODS
Materials
In this study, as a soil material, silica sand with alow uniformity coefficient of 1.25 was selected inorder to reflect a relatively high hydraulicconductivity fields. Silica sand of interest had
0.050cm, 2.68 g/cm3 and 0.11 cm/s of physicalproperties such as the mean particle size, the particle
density and the hydraulic conductivity, respectively.
Since silica sand was washed and dried at 110 °C
439

GEOMATE-Nagoya, Nov.13-15, 2013(a) Rice husk(b) Rice straw(c) Used coffee grounds

Fig. 1 Images of agricultural residues and food residue used in column experiments: (a) rice husk, (b)rice straw and (c) used coffee grounds.

Table 1 Physical properties of agricultural and food residues mixed with silica sand.

Residues

Weight ratio (%)

Porosity (-)

Hydraulicconductivity(cm/s)

Rice husk

0.95 – 2.6

0.44 – 0.47

0.10 – 0.11

Rice straw

1.0 – 2.2

0.45 – 0.46

0.053 – 0.11

Used coffee

2.3 – 8.9

0.46 – 0.56

0.070 – 0.10

repeatedly, there were no microbes onto the soil
surface.
In this study, two types of agricultural residues
such as rice husk and rice straw were employed,
which were taken from the paddy field after the
harvest. In addition, Lion Coffee’s “Hawaii coffee”
used coffee grounds were used throughout as one
food residue in order to compare the degree ofnitrate attenuation among agricultural residues.
Images of these residues are shown in Fig.1. As
shown Fig.1, the length of artificially chopped ricestraw was adjusted in approximately 5 mm length.
All residues were dried at 110 °C before column
experiments.

of 1.5 cm, 2.1 cm and 3.4 cm was replaced withresidues of concern. These soils with one of theresidues were completely saturated with deionizedwater before packing to avoid the entrance of air andwere filled into the column in increments of 2.5 cm,
homogeneously. Each layer was compacted with arammer to adjust the porosity prior to packing thenext layer. In Table 1, physical properties of eachresidue mixed with silica sand are listed. The
porosity was estimated in each experiment indirectlyfrom the measurements of the total weight of residue
and silica sand filled in the column. The hydraulicconductivity was measured using the discharge rateof water from the column under a hydraulic gradientand the sectional area of the column.
After packing, deionized water was applied tothe column up to a specific level controlled byconstant head reservoirs at the top and bottom of thesaturated media, while maintaining the saturated
condition of porous media. Steady saturated flow
field was established in the column whenfluctuations in the observed drainage rate from thebottom reservoir became negligible. A volume of
40cm3 of KNO 3 solution or NaCl solution wasapplied to produce a pulse input with an initialconcentration of 1.5×10-4 g/cm3 of NO 3 -N or NaCl.
Despite of the condition of the weight ratio of
residues, pore water velocities were set toapproximately 0.012 cm/s under the control of theColumn Experiments
Column experiments under the saturated
condition were carried out at room temperature (18±2 °C ) under an air atmosphere. The soil columns
were constructed of acrylic cylinders having 5 cm of
inner diameter and 30 cm length and also had filter
meshes attached to the top and bottom.
In column experiments, the weight ratios of rice
husk, rice straw and used coffee to the total weightof silica sand were varied in order to examine theeffect of the amount of residues on the degree ofnitrate transfer. From the practical viewpoint, theweight of silica sand equivalent to the column height440

GEOMATE-Nagoya, Nov.13-15, 2013

1

0%
2.3%
5.7%
8.9%

used coffee
0.8

In this study, the dispersivity, the degradation
rate, the mass recovery fraction and the retardation
factor were identified using temporal moment
approaches based on a BTCs of nitrate or chloride
ions as quantity factors reflecting the effect ofagricultural and food residues. Representative BTCs
as a function of the elapsed time for nitrate ion under
different weight ratios of mixed used coffee areshown in Fig.2.
The dispersivity from temporal moments wascalculated as [8] :

0.6
0.4
0.2
0
0

500 1000 1500 2000 2500 3000 3500 4000 4500

Elapsed time (s)Fig.2 Representative BTCs for nitrate ion in usedcoffee columns

αL =hydraulic gradient. Pore water samples at the end of
the column were taken at specific intervals using afraction collector to measure experimental
breakthrough curves (BTCs). Nitrate ion in the porewater samples was analyzed by capillaryelectrophoresis (G1600A, Agilent technologies,
USA). The basic anion buffer and a fused silica
capillary with 104 cm in length and 5 cm internal
diameter were obtained from Agilent technologies.
The temperature-controlled cartridge for fused silica
was set at 15 °C. On the other hand, electricalsensors were used to measure the voltage readings ofelectrical sensors using a calibrated relationshipbetween the specific concentration of NaCl solution
and the corresponding voltage via a data logger.

(3)

where ξ p is the distance between the source and theobservation location. The retardation factor was
expressed as [9] :R=( µ1 − 0.5t0 ) v 2p + 4α Lv p λx(4)where t 0 is the pulse duration. In all experiments, t 0
was set to 30 seconds to reflect the injection
situation of solute.
The mass fraction of solute was used to estimate
the mass recovery fraction (MRF) [7] :∞∫ Q( L, t )c( L, t )dt
MRF = 0∞∫0 Q(0, t )c(0, t )dt

PARAMETER ESTIMATION
Consider a sorbing and degradable chemical
moving through a homogeneous medium at a steady,uniform, flow rate. Assuming linear, equibrium
sorption and first-order kinetic degradation for thesolute, the governing transport equation can be
written as :

∂c
∂c
∂ 2c
R = αv 2 − v − λ c
∂x
∂t
∂x

ξ p µ22 µ12(5)where Q is the volumetric flow rate and H is thelength of the soil column. The degradation rate
constant was also calculated by [6] :

λ=

(1)

where c is the concentration of solute, x is thecoordinate, t is the time, R is the retardation factor
estimate, v is the average pore water velocity, α isthe dispersivity, and λ is the degradation rate
constant [7].
Temporal moment analysis is a useful approach
to characterize experimental BTCs without solving
solute transport model [8]. The normalized temporal
moment µ n at a location x, is defined as :

 1 
ln

µ1  MRF 
1(6)

Prescribed solute source conditions in column
experiments was designed to clarify the transientconcentrations of nitrate and chloride ions and toeffectively provide the parameter identification
relevant to solute transport using temporal moment
approaches.
RESULTS AND DISCUSSION
Solute Dispersivity∞ n∫ t c( x, t )dt∫0 c( x, t )dtµn = 0 ∞From the practical viewpoint, larger dispersionof solute is the consequence of significant mixing or
dilution in field. The dispersivity is one of the solute

(2)

441

GEOMATE-Nagoya, Nov.13-15, 2013

1.6

1
rice husk
rice straw
used coffee

0.8

rice husk
rice straw
used coffee

1.4

0.6

1.2

0.4

1

0.2

0.8
0.6

0
1

1.5

2

2.5

3

1

3.5

1.5

2

2.5

3

3.5

Column thickness (cm)Column thickness (cm)Fig. 3 Relation between the column thickness ofresidues and the dispersivity for nitrate ion

Fig.5 Relation between the column thickness ofresidues and the retardation factor for nitrate ion.
1.6

1
rice husk
rice straw
used coffee

0.8

rice husk
rice straw
used coffee

1.4
1.2

0.6
1

0.4
0.8

0.2
0.6
1

0
1

1.5

2

2.5

3

3.5

1.5

2

2.5

3

3.5

Column thickness (cm)Column thickness (cm)Fig. 4 Relation between the column thickness ofresidues and the dispersivity for chloride iontransport parameters that characterizes solute
dispersion in porous media [10]. The results of thedispersivities in rice husk, rice straw and used coffee,
which were identified based on Eq.(3), in nitrate andchloride ions are shown in Figs. 3 and 4,
respectively, as a function of column thickness ofeach residue. In the column having only silica sand,the values of the dispersivity for nitrate and chloride
are 0.16 cm and 0.32 cm, respectively. The mixtureof rice husk and rice straw provides an increase
tendency of the dispersivity for nitrate ion, while theopposite tendency is shown in used coffee as well as
chloride ion. The dispersivity in nitrate ion exhibits
lower values than that in chloride ion. This featurereflects that each anion has its own degree of solute
spread with respect to mixed agricultural and foodresidues. The difference of the dispersivity between
the anions or the agricultural residues may appear in
the outcome of the retardation factor.

Fig. 6 Relation between the column thickness ofresidues and the retardation factor for chloride ion.

anion mobility, the retardation factor was employed
as a measure and estimated using Eq.(4). The
relation between the column thickness of residues
and the retardation factor for all residues are shownin Figs.5 and 6, in terms of nitrate and chloride ions,
respectively. As seen in Fig.5, the retardation factor
in rice husk remains constant value of about 1.0
despite of the mixture of rice husk. This means thatno retardation or no sorption occur in porous
formations. The retardation factor in rice straw
becomes slightly larger than the value of 1.0,
indicating that the mobility of nitrate ion decreases
during the transport in porous formations. Therefore,
from a viewpoint related to the application of ricestraw in a field, it is expected that nitratedecomposition by microbes may occur andcontribute to the reduction of nitrogen mass inporous media during a transport with retarded
velocity.
On the other hand, the results of the nitrate
mobility exhibit below the unity in used coffee
grounds. This implies the solute transport velocity
becomes larger than the seepage velocity in columns

Retardation of Solutes
In order to quantify the degree of the variation of442

GEOMATE-Nagoya, Nov.13-15, 2013

filled with used coffee grounds. On average, theused coffee grounds contain up to 15% oil, although
the amount of oil in the coffee source depends on its
types [11]. It is inferred that surface hydrophobicity
of used coffee provides the increase of the velocity
of nitrate and results in the lower values of theretardation factor. Rice husk also has the surfacehydrophobicity and may affect the variation of theretardation factor in chloride ion. As a whole, thedegree of retardation in nitrate ion is larger than thatin chloride ion, indicating that the mobility ofchloride ion is higher than that in nitrate ion. At amicroscopic level, it is likely that the degree ofreaction between the anion and the surface ofresidues is substantially different.

From a practical viewpoint, the degradation of solute
mass in a cropland is expected to attenuate theimpact on water quality in soils as well as ingroundwater. Therefore, the use of agricultural andfood residues in soils has a potential to theattenuation of nitrate and chloride ions.
CONCLUSIONSIn this study, the reuse of agricultural and foodresidues in order to retard and attenuate the impactof nitrate or chloride ions in porous media wasassessed through column experiments undersaturated flow conditions. Temporal moments
associated with observed breakthrough curves wereused to quantify the dispersivity, the retardation
factor, the mass recovery fraction and thedegradation rate. The increase of the mixture of ricehusk and rice straw resulted in the slight increase of
the dispersivity, while the opposite tendency was
shown in used coffee columns. Remarkably, themobility of anions showed the increase tendency inused coffee columns. Moreover, rice husk and usedcoffee were found to have a property to decrease themass balance in both anions. These findings may be
attributed to the nature of nitrate and chloride ionshaving its own degree of solute spread associatedwith mixed residues.

Mass Recovery Fraction and Degradation of
Solutes
The change of mass balance is of interest and ofsignificance during a course of transport associatedwith the mixture of agricultural and food residues.
As another quantity of anion transfer, Table 2
summarizes the results of the mass recovery fraction(MRF) and the degradation rate (λ), which were
estimated from Eqs. (5) and (6), respectively.
Results in rice straw are not listed, since MRF andthe degradation rate became 1 and 0 in all
experimental cases.
As shown in Table 2, in all experimental cases,
values of MRF are less than 1 and the corresponding
degradation rate appears as non-zero values. In
Table 2, up to 44% and 56% attenuation of the total
mass in nitrate can be seen in nitrate and chloride
ions, respectively. This implies that part of nitrate orchloride ions may be strongly adsorbed onto thesurface of rice husk or used coffee and may be
trapped within pores. This is because rice husk andused coffee have a relatively high surface area [12].

ACKNOWLEDGEMENTS
The work reported here was supported by JSPS
Grant-in-Aid for Young Scientists (B).
REFERENCES[1] Bryan N, Alexander DD, Coughlin JR,
Milkowski AL, Boffetta P, “Ingested nitrate andnitrite and stomach cancer risk: An updated

Table 2 Results of the mass recovery fraction and the degradation rate.
Nitrate ion
Columnthickness(cm)
Rice husk
1.5
2.1
3.4
Used coffee
1.5
2.1
3.4

Chloride ion

MRF (-)λ (hr-1)

MRF (-)λ (hr-1)

0.77
0.95
0.73

0.43
0.072
0.50

0.44
0.71
0.44

1.6
0.50
1.7

1.0
0.59
0.56

0.
0.76
0.76

0.53
0.59
0.61

1.0
0.86
0.65

443

GEOMATE-Nagoya, Nov.13-15, 2013

review”, Food and Chemical Toxicology,
Vol.50, 2012, pp.3646-3665.
[2] Grosse Y, Baan R, Straif K, Secretan B, El
Ghissassi F, Cogliano V, “Carcinogenicity ofnitrate, nitrite, and cyanobacterial peptide
toxins”, The Lancet Oncology, Vol.7(8), 2006,
pp.628-629.
[3] Tsugane S, “Salt, salted food intake, and risk ofgastric cancer: epidemiologic evidence”, Cancer
Science, Vol.96(1-6), 2005, pp.1-6.
[4] Safarik I, Horska K, Svobodova B, Safarikova
M, “Magnetically modified spent coffee
grounds for dyes removal”, European Food
Research Technology, Vol.234, 2012, pp.345350.
[5] U.S. Department of Agriculture, Coffee: World
markets and trade, 2012.
[6] Kondamudi N, Mohapatra SK, Misra M, “Spentcoffee grounds as a versatile source of green
enegy”, Journal of Agricultural Food Chemistry,
Vol.56, 2008, pp.11757-11760.
[7] Das BS and Kluitenberg GJ, “Moment analysis
to estimate degradation rate constants fromleaching experiments”, Soil Science Society ofAmerica Journal, Vol.60, 1996, pp.1724-1731.

[8] Valocchi AJ, “Validity of the local equilibrium
assumption for modeling sorbing solutetransport through homogeneous soils”, Water
Resources Research, Vol.21(6), 1985, pp.808820.
[9] Pang L, Goltz M and Close M, “Application of
the method of temporal moments to interpret
solute transport with sorption and thedegradation”,
JournalofContaminantHydrology, Vol.60(1-2), 2003, pp.123-134.
[10] Fetter CW, Contaminant Hydrology 2ndedition : Prentice Hall, 1998.
[11] Daglia M, Racchi M, Papetti A, Lanni C,
Govoni S, Gazzani G, “In vitro and ex vivo
antihydroxyl radical activity of green androasted coffee”, Journal of Agricultural Food
Chemistry, Vol.52(6), 2004, pp.1700-1704.
[12] Kaupp A, “Gasification of Rice Hulls: Theory
and Practices”, Deutsches Zentrum Fuer
Entwicklungs
Technologien(GermanAppropriate Technology Exchange, GATE),
Eschborn, Germany, 1984.

444

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

MICROSCOPIC RANGE OF IMMOBILIZATIONBETWEEN HEAVY METALS AND AMENDMENT IN SOIL THROUGH
WATER MIGRATION

1

Shouhei Ogawa1, Masahiko Katoh2 and Takeshi Sato3
Graduate School of Engineering, Gifu University, Japan; 2,3 Faculty of Engineering, Gifu University, Japan

ABSTRACT
In order to identify the microscopic range of immobilization in soil, the pot test was conducted to evaluate
the distance that lead (Pb) and antimony (Sb) transport through water migration and the transport phases during
immobilization. The amount of amendment required to immobilize Pb and Sb was investigated on the basis of
the microscopic range of immobilization. The results clearly showed that Pb and Sb were transported amaximum of 5 mm and 6 mm, respectively, through water migration which corresponded to precipitation for one
month. Both metals were accumulated 1 mm from contaminated soil. The primary Pb transport phase was sorbed
on Fe/Mn oxide, while that of Sb was water-soluble. The amount of amendment required for Pb and Sb
immobilization was estimated to be 4.62% (w/w) from the microscopic range of immobilization (1 mm).
Keywords: Amendment ratio, Antimony, Immobilization, Lead, Water migration

the amendment’s maximum sorption capacity
estimated by a sorption experiment in solution [8].
However, Pb and Sb would be unstable in the soil
unless stable phases are formed, even though theamount of amendment is sufficient to immobilize
them. This is because heavy metal transport throughwater migration, and subsequent contact andreaction with the immobilization amendment, would
be essential before the stable phases are formed.
Thus, to calculate the required amount ofimmobilization amendment, it is necessary to
identify the microscopic range of Pb and Sb
immobilization, i.e., the transport distance of Pb andSb through water migration during the period ofimmobilization.
Heavy metals in soil particles would betransported through water migration, repeating
various processes, such as ion exchange,
precipitation and dissolution, sorption anddesorption to soil minerals and organic matters, andcolloidal transportation [9], [10]. In addition, heavy
metal phases would be altered during transportation.
Therefore, to identify the microscopic range of Pb
and Sb immobilization, Pb and Sb phases duringtransport should be taken into consideration.
As stated above, elucidation of the microscopic
range of Pb and Sb immobilization during theimmobilization period is also necessary to calculate
the amount of amendment required for reliable
immobilization. However, the required amount ofimmobilization amendment has not been evaluated inrelation to the microscopic range of Pb and Sb
immobilization, although heavy metal transport in thesoil has been well investigated [10] – [13].
The present study represented Pb and Sb

INTRODUCTION
Removing heavy metals, which are highly
persistent in soil, is difficult compared to othercontaminants, such as oil and volatile organic
compounds that readily decompose in soil [1].
Therefore, soil remediation techniques, including
excavation and transportation to landfill sites, thatcan easily reduce risk are often applied to heavymetal-contaminated soil. However, in addition to
construction costs, excavation and transportation tolandfills incur conveyance and management costs,
which in all probability would lead to an increase intotal cost [2].
Chemical immobilization is one of the mosteconomical in situ techniques because the soil canbe reused at the site after treatment [3]. The additionof an immobilization amendment to the soil cantransform a heavy metal into chemically stablephases and thus reduce solubility, which prevents
leaching of heavy metal into groundwater. In thiscontext, immobilization has been investigated forlead (Pb-) and antimony (Sb-) contaminated soil
from a shooting range, where contamination is more
extensive and asset value is very low [4], [5]. Pb can
be immobilized by an apatite, precipitating Pb
phosphate minerals, such as pyromorphite [6], andSb can be immobilized by an iron compound,particularly iron hydroxide, forming surface
complexation [7]. However, if the amount of theamendment is not sufficient to immobilize Pb andSb completely, the treatment can potentially lead to
Pb and Sb redissolving in the soil [7].
The required amount of immobilization
amendment in the soil is calculated on the basis of445

GEOMATE-Nagoya, Nov.13-15, 2013

microscopic transport through water migration insoil from a shooting range by using acompartmentalized pot to represent water flow inunsaturated soil. The objective of this study was toevaluate the distance of Pb and Sb transport andtransport phases during the immobilization period,
and to identify the microscopic range of theirimmobilization in the soil. In addition, the required
amount of immobilization amendment wasinvestigated on the basis of the microscopic range ofimmobilization.

soluble Pb of the contaminated soil was 95.7 mg/kg,
which is 1000 times greater than the standard (0.1mg/kg) for soil in Japan. The physicochemical
properties of non-contaminated soil collected outside
the contaminated site were similar to those of thecontaminated soil, except for Pb and Sb. The noncontaminated soil was passed through a 1 mm sieve
prior to the water migration experiment. Commercial
Andosol was used as cultivation soil.

MATERIALS AND METHODS

Apatite and iron hydroxide were used as Pb andSb immobilization amendments, respectively. The
apatite was synthesized from gypsum anddiammonium hydrogen phosphate [14]. Apatite canimmobilize Pb in soil through the precipitation of Pb
phosphate minerals such as pyromorphite. The ironhydroxide was synthesized from iron nitrate hydrate[15]. Iron hydroxide can immobilize Sb in soil
through the formation of an inner-sphere complex.
Both amendments were passed through a 0.425 mmsieve, and equal amounts were well mixed prior touse. Table 1 shows the physicochemical propertiesof the amendments.

Materials Preparation and Characterization

Study Area
This study was conducted using soil from ashooting range located at 35° 28′ 6′′ N and 137° 29′
2′′ E in Tajimi, Gifu Prefecture, Japan. The meanannual precipitation and temperature at the shooting
range are 2200 mm and 14 °C, respectively.
Soil Preparation and Characterization
The Pb- and Sb-contaminated soil was collectedfrom depths of 5–15 cm. The contaminated soil
sample was air-dried, passed through a 2 mm sieve,and used for chemical analysis and the water
migration experiment. Table 1 shows thephysicochemical properties of the soil samples.
Total Pb and Sb content of the contaminated soil
was 19700 and 261 mg/kg, respectively. The water-

Water Migration Experiment
Figure 1 is a schematic of the experiment. The
experimental pot was comprised of four layered
compartments: contamination, non-contamination,
amendment, and plant compartments (CC, NCC, AC,

Table 1 Physicochemical properties of the soil and immobilization amendment
Particles
Soils andpH(H O) density
Immobilization amendment

Total

Water-soluble

2

C

Fe

Ca

P

[g/cm3 ]Contaminated soil

Pb

Sb

Pb

Sb

95.7 >

7.6 >[mg/kg]

7.18

2.62

51000

Non-contaminated soil

6.06

*

N.A.

Cultivation soil

5.56

N.A.

Immobilization amendment

7.70

3.29

33700

7570

386

14300

25500

1390

39.3

11.3

1.7

0.1 >

0.1 >

71200

40100

5650

1710

58.3

5.8

0.1 >

0.1 >

N.A.

254000181000

45500

14.8

3.5

0.1 >

0.1 >

19700

261

* : Not Analyzed

Transpiration
P C [Plant Compartment] ：65×65×20（mm3）WatersupplyA C [Amendment Compartment] ：65×65×2（mm3）
N C C [Non-Contamination Compartment]：65×65×1（mm3）×n Layers

Evaporation

C C [Contamination Compartment] ：65×65×28（mm3）：Water migration：Heavy metals transport

Fig. 1 Water migration schematic446

GEOMATE-Nagoya, Nov.13-15, 2013

and PC, respectively). NCC was composed of five orten 1-mm-thick layers (5 mm NC-Pot and 10 mm
NC-Pot, respectively). Then, 107.50, 4.68, 8.60, and100.00 g of contaminated soil, non-contaminatedsoil, amendment, and cultivation soil, respectively,
were added to each layer. The layers were separatedusing a 25-µm nylon mesh. Ultra-pure water wasadded to maintain 50% of the water-holding capacityof each soil or amendment. After adding 5 mL ofsolution containing nitrogen, phosphorus, andpotassium as fertilizer at 10 mg/kg to the PC, twoGuinea grass (Panicum maximu J.) plants weregrown in the compartment. Guinea grass can tolerate
Pb toxicity. The plants were grown at room
temperature (25 °C). This experimental design
represented water flow in unsaturated soil. The
bottom of the pot had 25 holes with a diameter of 5mm. The plants were watered the amountcorresponding to the lost weight of pot from the lastwater supply from the bottom at 2 or 3 times a week
(Fig. 1). The total water supply was 170 mm, whichcorresponded to precipitation for one month at theshooting range site. The period of immobilization
was defined as one month. After the experiment, theNCC soil samples were collected, air-dried, andpassed through a 2 or 0.425 mm sieve.

and diluted in a 50 mL measuring flask. All theextracted or digested solutions were passed througha 0.45 µm filter, and analyzed to determine theelemental concentrations by inductively coupledplasma optical emission spectrometry (ICP-OES;ULTIMA2, HORIBA Ltd., Japan) or inductively
coupled plasma mass spectrometry (ICP-MS;
7500cx, Agilent Technologies Inc., USA).
RESULTS AND DISSCUSSION
Distance of Pb and Sb Transport through Water
Migration
Figure 2 shows the levels of total Pb and Sb in
each NCC layer in the 5 mm NC-Pot. The levels of
total Pb in all the layers were more than twice ashigh as those in the original non-contaminated soil,
indicating that Pb was transported 5 mm from CC in
the NCC through water migration during theimmobilization period. The highest levels of total Pb
were found in the 1 and 4 mm layers of NCC, andthe lowest was in the 5 mm layer. The levels of total
Sb in all the layers were also more than twice ashigh as those in the original non-contaminated soil.
The highest level of total Sb was found in the 1 mm
layer, and the lowest was in the 5 mm layer. This
result indicated that Sb was also transported 5 mm.
Moreover, it is reasonable to conclude that the levelsof transported Pb and Sb would decrease with theincrease in transport distance because the lowest
level of total Pb and Sb was found in the 5 mm layerof NCC. The Pb and Sb transport distance throughwater migration in unsaturated soil may depend on
the distance between CC and PC. Therefore, anotherwater migration experiment was conducted using the
10 mm NC-Pot to compare with the results using the
5 mm NC-Pot.

Methodology

D i stance f rom CC [mm]The pH value of the soil sample was measured inultrapure water using a pH meter (MM-60R, DKKTOA Co., Japan). The total carbon (C) content of thesoil sample was determined using an NC analyzer(MT-6, Yanaco New Science Inc., Japan). The
water-soluble Pb and Sb in the soil was extractedusing ultra-pure water (1:10 soil:solution ratio). The
total Pb, Sb, calcium (Ca), iron (Fe), and phosphorus(P) content of the soil was determined by aciddigestion with 14.5 M HNO 3 and 12 M HCl using a
microwave. Sequential extraction was performed on
the soil sample following the procedure described in[16]. Then, 1.0 g of soil that had been passed
through a 0.425 mm sieve was extracted with 25 mLof a 1 M MgCl 2 solution (exchangeable). The soil
remaining after the first extraction procedure was
extracted with 25 mL of a 1 M sodium acetate
solution with pH 5 (carbonate). The soil remaining
after the second extraction was further extractedwith 20 mL of 0.04 M NH 2 OH-HCl in 25% (v/v)
HOAc in a 95 °C water bath with occasional
agitation (bound to Fe/Mn oxide). The soil
remaining after the third extraction was extractedwith 3 mL 0.02 M HNO 3 and 5 mL 30% H 2 O 2solution in an 85 °C water bath with occasional
agitation. After extraction for 3 h, 5 mL 3.2 M
NH 4 OAc in 20% (v/v) HNO 3 was added and the soil
was shaken for 20 min (bound to organic matter).
The remaining soil was digested with 5 mL HNO 3
and 2 mL HCl using a microwave oven (residual)

5

5

4

4

3

3

2

2

1

1
0

100

200

Total Pb［mg/kg]

0

2

4

6

8 10

Total Sb［mg/kg]

Fig. 2 Total heavy metal levels in NCC (5mm NCPot). Broken lines indicate the background levelsin the original non-contaminated soil.

447

GEOMATE-Nagoya, Nov.13-15, 2013

10

10

9

9

8

8

7

7

6

6

5

5

4

4

3

3

2

2

1

1
0

50 100 150 200
Total Pb ［mg/kg]

range soil decreased relative to soil depth. However,in this study, Sb was transported farther than Pb in
NCC (Fig. 3). This observation suggested that,compared to Pb, Sb was transported easily throughwater migration. Sb would exist as an anion(Sb(OH) 6 –) of Sb (V) in the shooting range soil
under oxic conditions, and Sb would be transported
as Sb(OH) 6 – through water migration. In contrast,
Pb would exist primarily as a Pb compound, such as
PbCO 3 and PbO. The Pb compounds weredissolved; dissolved Pb would be transported andsorbed onto the colloid containing iron oxide andorganic matter [10], [19]. Therefore, Sb wasprobably transported easily because transport of acolloid is more difficult than that of an anion. These
results suggest that Sb is effectively immobilized insoil because easy transport in soil results in frequentcontact and reaction with immobilization
amendment.
Transporting Phases of Pb and Sb
The ratios of water-soluble Pb and Sb to total Pb
and Sb in NCC in the 5 mm NC-Pot are shown in
Fig. 4. The ratios of water-soluble Pb to total Pb in
all layers were very low. The ratio in the 1 mm layer,
in which the highest level of total Pb was found, wasless than 2%. In contrast to Pb, the ratios of watersoluble Sb in all layers were high, and 30% of thetotal Sb in the 1 mm layer was water-soluble.
Figure 5 shows the ratios of water-soluble Pb
and Sb to total Pb and Sb in the 10 mm NC-Pot. As
was observed with the 5 mm NC-Pot, the ratios ofwater-soluble Sb were higher than those of watersoluble Pb in all layers. The ratio of water-soluble
Pb in the 1 mm layer was 2%, while that of watersoluble Sb was 42%. Furthermore, 30% to 40% of
the total Sb in the 1 to 6 mm layers, in which thelevel of total Sb exceeded that of the original non-D i stance f rom CC [mm]D i stance f rom CC [m m]Figure 3 shows the level of total Pb and Sb in
each NCC layer in the 10 mm NC-Pot. The level of
total Pb in the 1 mm layer of NCC, which wasnearest to CC, was the highest; it was 14 times
higher than that in the original non-contaminatedsoil. In addition, the level of total Pb in the 3 mm
layer was approximately two times higher than thatin the original non-contaminated soil. However, thelevel of total Pb in the layers 6 mm or more, which
was not provided in the 5 mm NC-Pot, was the sameas that in the original non-contaminated soil. These
results suggested that Pb was transported 3 mm fromCC in the NCC through water migration during theimmobilization period in the 10 mm NC-Pot. The
level of total Sb was the highest in the 1 mm layer,
reduced with the distance, and was the same as theoriginal non-contaminated soil in layers 7 mm ormore. Thus, in contrast to Pb, these results
demonstrated that Sb was transported 6 mm throughwater migration during the immobilization period in
the 10 mm NC-Pot.
The Pb and Sb transport distances did not differ
significantly in the water migration experiments
using a 5 mm NC-Pot and a 10 mm NC-Pot.
Accordingly, these results demonstrated that Pb andSb can be transported 3-5 mm and 6 mm,
respectively, through water migration, whichcorresponds to precipitation for one month. Tlustoš
et al. [17] and Fitz et al. [18] conducted a plant
growth experiment using a rhizobox and reported
that the plant absorbed Pb and arsenic through water
uptake from rhizosphere soil, which is a few
millimeters away from the root. These results are
consistent with those obtained in this study. Thus,
the Pb and Sb transport distances in this study would
be valid.
Steely et al. [12] and Cao et al. [19] haveobserved that the levels of Pb and Sb in the shooting

0

2

4

6

8 10

5

5

4

4

3

3

2

2

1

1
0 10 20 30 40 50

Total Sb ［mg/kg]

0 10 20 30 40 50

R a tio of water-soluble Pb R a tio of water-soluble Sb
to total Sb [%]to total Pb ［%]Fig. 3 Total heavy metal levels in NCC of 10 mm
NC-Pot. Broken lines indicate the backgroundlevels in the original non-contaminated soil.

Fig. 4 Ratios of water soluble to total in NCC of 5mm NC-Pot
448

GEOMATE-Nagoya, Nov.13-15, 2013Pb levels of each fraction［ mg/kg］

30

Pb and Sb. Therefore, to enhance the effectivenessof immobilization, the type of heavy metal should betaken into account. In this study, only one type soil
was used. Further investigation should consider
more soil types because soil particle size andchemical composition strongly affect Pb and Sb
sorption on the soil surface.
Required Amount of Immobilization Amendment
by Microscopic Range
It was anticipated that, in the case ofimmobilization in contaminated soil, Pb and Sb
would be transported through water migration amaximum of 5 to 6 mm, which corresponds toprecipitation for one month. However, thetransported Pb and Sb were particularly accumulated
in the 1 mm layer. Therefore, assuming that thetransporting distance to immobilize Pb and Sb is 1
mm, the required amount of amendment wascalculated from the following equations on the basisof the microscopic range of immobilization. The
overview of the microscopic range is shown in Fig.
7. The microscopic range of Pb and Sb
immobilization was calculated according to thefollowing equation:

D i stance f rom CC [mm]contaminated soil, was water-soluble. These ratios
are consistent with the results (Pb: 2%–10%, Sb:
4%–72%) obtained by Sanderson et al. [20]. These
results demonstrated that Sb in the shooting range
soil would be more water-soluble, and thus, Sb
would have higher mobility through water migration
than Pb.
The Pb and Sb that were passed through the 0.45
µm filters were defined as water-soluble in thisstudy. However, Pb underwent colloid transport in
the soil, and Pb transport would strongly relate with
0.45–0.8 µm colloid particles [10]. Thus,
approximately Pb transported into the layers of NCC
likely existed in the sorbing phase on the colloid; Pb
would be transported as non-water-soluble phases.
Sb was also sorbed on iron oxides. However, thelevel of Sb sorption was reduced under neutral toalkali soil pH [20]. Therefore, in the soil used, Sb
was less likely to be sorbed, which probably induced
Sb to be more water-soluble.
Sequential extraction was performed to evaluate
Pb transporting phases because Pb was probablytransported in non-water-soluble phases. The levelsof each Pb fraction in the 1 and 5 mm layers of NCC
in the 5 mm NC-Pot are shown in Fig. 6. The levelof Pb fraction in the 1 mm layer was highest in thefraction bound to Fe/Mn oxide at 27 mg/kg. The
level of Pb fraction in the 5 mm layer, where thelevel of total Pb was the lowest, was also highest in
the fraction bound to Fe/Mn oxide at 6 mg/kg. The
levels of the carbonate and Pb fractions bound to
Fe/Mn oxide in the 1 mm layer were significantly
higher than those in the 5 mm layer. The level of theresidual fraction, which was the most stable, was thesame for the 1 and 5 mm layers. Therefore, Pbphases transported through the layers appeared to be
Pb compounds, such as carbonate. In addition, thePb phase bound ro Fe/Mn oxide; the Pb phasetransported with the colloid would be phase sorbedon the iron oxide. In acid soil, Pb carbonate and Pb
sorbed on iron oxide are likely to be dissolved anddesorbed, respectively [20]. However, in the soil
used, the dissolution and desorption was suppressed
because of neutral soil pH.
These results indicate that the distance andphases during transport in the soil differed between

10

10

9

9

8

8

7

7

6

6

5

5

4

4

3

3

2

2

1

1
0 10 20 30 40 50

R a tio of water-soluble Pb
to total Pb ［%]0 10 20 30 40 50
R a tio of water-soluble Sb
to total Sb ［%]Fig. 5 Ratios of water soluble to total in NCC of 10mm NC-Pot
Distance from CC

1 mm

20

5 mm

10
0
Exchangeable

Carbonete

Bound toBound toFe/Mn oxide organic matter

Residual

Fig. 6 Pb fractions of sequential extraction in NCC of 5 mm NC-Pot
449

GEOMATE-Nagoya, Nov.13-15, 2013

Amendment particle
Immobilization

Vi
D

Va

L
Pb or Sb

To fill 1 m3
contaminated soil

Fig. 7 Overview of microscopic range for immobilizationItwould be effective
for chemical
3
immobilization to add the phosphorus amendment
4π ⋅ ( L + D 2)
with 0.6 molar ratio of Pb in the soil and P in the
(1)
Vi =
3
amendment because Pb is immobilized in soil withthe precipitation of Pb phosphate minerals such aswhere V i is the microscopic range of Pb and Sb
pyromorphite (Pb 5 (PO 4 ) 3 OH); its P/Pb molar ratio
immobilization (mm3), L is the transporting distanceis 0.6 [6]. In the case that the amendment has been
during the immobilization period (1 mm), and D is
added to the soil at 5% (w/w), the molar ratio of Pb
the diameter of the amendment particle. In case thatin the soil and P in the amendment would be 0.771.
D = 1 mm, the value of V i was obtained as 14.1 mm3Thus, addition of amendment with 5% (w/w) isusing Eq. (1). The required number ofprobably sufficient to immobilize Pb. Moreover,immobilization amendment particles to fill 1 m3 ofÁlvarez-Ayuso et al. [7] added 5% (w/w) iron oxide
contaminated soil for the established range of Pb andto the Sb-contaminated soil in which the level of
Sb immobilization (N) can be expressed as
total Sb was 25 times higher than that in the soil
used in this study. The results of that study indicated
9that
Sb was completely immobilized. Therefore, in
1× 10
(2)
the soil used in the current study, the addition ofN=Viamendment with 5% (w/w) would be sufficient for
Pb and Sb immobilization. Further investigation is7
necessary
because this study simplified estimation
The value of N was calculated to be 7.09 × 10 .
conditions to calculate the required amount of
The volume of one immobilization amendment
immobilization amendment.
particle (V a ) can be calculated asVa =4π ⋅ ( D 2) 3
3

CONCLUSION(3)
The present study evaluated the distance of Pb
and Sb transport through water migration and theirtransporting phases during the immobilization period
to identify the microscopic range of immobilizationin the soil. In addition, the required amount ofimmobilization amendment was investigated on thebasis of the microscopic range of immobilization.
The results obtained in this study are as follows:
1) Pb and Sb were transported 5 mm and 6 mm at
most, respectively, and were particularly
accumulated 1 mm from contamination.
2) Thirty to forty percent of transported Sb waswater-soluble, which suggests that Sb was easilytransported in soil to contact and react withimmobilization
amendment.
Pbphasestransported through water migration sorbed on
Fe/Mn oxide and carbonate. Thus, Pb probably
has lower mobility than Sb.

Moreover, using V a and N, the required volume ofimmobilization amendment (A v ) in 1 m3 ofcontaminated soil can be expressed asAv =Va ⋅ N× 100
1 × 109(4)

The value of A v was calculated to be 3.72% using
Eq. (4). By converting the volume ratio to weightratio using the density of the amendment and thecontaminated soil (Table 1), the weight ratio of
amendment was calculated to be 4.62%.

450

GEOMATE-Nagoya, Nov.13-15, 2013

3) The distance and phases during transport in thesoil differed between Pb and Sb. To enhance theeffectiveness of immobilization, the type ofheavy metal should be considered.
4) The required amount of immobilization
amendment was estimated from the range ofimmobilization (1 mm) to be 4.62% (w/w).

[9] Zhang W, Tsang DCW, “Conceptual frameworkand mathematical model for the transport ofmetal – chelant complexes during in situ soil
remediation”, Chemosphere, Vol. 91, 2013, pp.
1281–1288[10] Yin X, Gao B, Ma LQ, Saha UK, Sun H, Wang
G, “Colloid-facilitated Pb transport in two
shooting-range soils in Florida”, J. Hazard.
Mater., Vol. 177, 2010, pp. 620–625[11] Garrido F, Helmhart M, “Lead and soil
properties distributions in a roadside soil: Effectof preferential flow paths”, Geoderma, Vol. 170,
2012, pp. 305–313[12] Steelya S, Amarasiriwardena D, Xing B, “Aninvestigation of inorganic antimony species andantimony associated with soil humic acid molar
mass fractions in contaminated soils”, Environ.
Pollut., Vol. 148, 2007, pp. 590–598[13] Wanga S, Choi JH, “Simulating fate andtransport of chromium in saturated sediments”,
Appl. Math. Model., Vol. 37, 2013, pp. 102–111
[14] Furuta S, Katsuki H, Komarneni S, “Removal oflead ion using porous hydroxyapatite monoliths
synyhesized from gypsum waste”, J. Ceram.
Soc. Jap., Vol. 108, 2000, pp. 315-317[15] Mitsunobu S, Sakai Y, Takahashi Y,“Characterization of Fe(III) (hydr)oxides inarsenic contaminated soil under various redox
conditions by XAFS and Mössbauer
spectroscopies”, Appl. Geochem., Vol. 3, 2008,
pp. 3236–3243[16] Tessier A, Camphell PGC, Bisson M,“Sequential extraction procedure for the
speciation of particulate trace metals”, Anal.
Chem., Vol. 51, 1979, pp. 844–851[17] Tlustoš P, Száková J, Kořínek K, Pavlíková D,
Hanč A, Balík J, “The effect of liming on
cadmium, lead, and zinc uptake reduction byspring wheat grown in contaminated soil”, Plant.
Soil Environ., Vol. 52, 2006, pp. 16–24[18] Fitz WJ, Wenzel WW, Zhang H, Nurmi J,Štípek K, Fischerová Z, Schweiger P,
Köllensperger G, Ma LQ, Stingeder G,“Rhizosphere characteristics of the arsenic
hyperaccumulator Pteris vittata L. andmonitoring of phytoremoval efficiency”,
Environ. Sci. Technol., Vol. 37, 2003, pp.
5008–5014[19] Cao X, Ma LQ, Chen M, Hardison Jr DW,
Harris WG, “Lead transformation anddistribution in the soils of shooting ranges in
Florida, USA”, Sci. Total Environ., Vol. 307,
2003, pp. 179–189[20] Sanderson P, Naidu R, Bolan N, Bowmanc M,
Mclure S, “Effect of soil type on distribution
and bioaccessibility of metal contaminants inshooting range soils”, Sci. Total Environ., Vol.
438, 2012, pp. 452–462

ACKNOWLEDGMENTS
The ICP-OES and CHO analyzer used forchemical analysis in this study was made available
by the Division of Instrumental Analysis at Gifu
University. The authors are grateful to Prof. F. Li
and Prof. T. Yamada (Gifu University) for allowing
the use of the ICP-MS. This study was partly
supported by Japan Society for the Promotion of
Science (JSPS) KAKENHI Grant Number 23710089
and the Maeda Engineering Foundation.
REFERENCES[1] Dickinson NM, “Strategies for sustainable
woodland on contaminated soils”, Chemosphere,
Vol. 41, 2000, pp. 259–263[2] Allen A, “Containment landfills: the myth ofsustainability”, Eng. Geol., Vol. 60, 2001, pp.
3–19[3] Mulligana CN, Yong RN, Gibbs BF, “Anevaluation of technologies for the heavy metal
remediation of dredged sediments”, J. Hazard.
Mater., Vol. 85, 2001, pp. 145–163[4] Sorvari J, Antikainen R, Pyy O, “Environmental
contamination at Finnish shooting ranges—thescope of the problem and management options”,
Sci. Total Environ., Vol. 366, 2006, pp. 21–31[5] Siebielec G, Chaney RL, “Testing amendments
for remediation of military range contaminatedsoil”, J. Environ. Manage., Vol. 108, 2012, pp.
8–13[6] Chrysochoou M, Dermatas D, Grubb DG,“Phosphate application to firing range soils for
Pb immobilization: The unclear role ofphosphate”, J. Hazard. Mater., Vol. 144, 2007,
pp. 1–14[7] Álvarez-Ayuso E, Otones V, Murciego A,
García-Sánchez A, “Evaluation of different
amendments to stabilize antimony in mining
polluted soils”, Chemosphere, Vol. 90, 2013, pp.
2233–2239[8] Chiang YW, Santos RM, Ghyselbrecht K,
Cappuyns V, Martens JA, Swennen R, Gerven
TV, Meesschaert B, “Strategic selection of an
optimal sorbent mixture for in-situ remediationof heavy metal contaminated sediments:
Framework and case study”, J. Environ.
Manage., Vol. 105, 2012, pp. 1–11

451

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SUB-DARCY-SCALE MODELING OF NON-UNIFORM FLOW
THROUGH POROUS MEDIA WITH MIXED WETTABILITES

1,3

Junichiro Takeuchi1, Takuya Takahashi2, and Masayuki Fujihara3
Graduate School of Agriculture, Kyoto University, Japan; 2 Kawasaki Kisen Kaisha, Ltd., Japan

ABSTRACT
A physically-based conceptual model is developed using spatially distributed sub-Darcy-scale clusters in a
regular grid to reproduce both the hydraulic properties and the non-uniform wetting and drainage fronts throughporous media mixed with hydrophilic and hydrophobic grains. In the model, cellular automaton-like algorithm is
employed to route water- and air-intrusion paths through the mixed porous media. Water retention characteristics,
which are ones of the macroscopic properties of porous media, are estimated by accumulating a certain numbersof clusters after reaching equilibrium states in a wetting or drainage process. In the experimental part of thisstudy, normal (hydrophilic) and artificially hydrophobized glass spheres, whose diameter is about 0.2 mm, areused as materials, and hydraulic properties of homogeneously mixed glass spheres with various rates aremeasured. The measured data are compared to model estimation, and the availability of the model is shown.
Keywords: Glass Spheres, Water Retention Properties, Hydrophilicity, Hydrophobicity, Cellular Automaton
Modeling

INTRODUCTION
From the early 1900’s, it has been reported that
there exist soils that have resistance to water
infiltration in various countries such as New Zealand,
Australia, Netherlands, and so on, and major
concerns have been raised because such soils, which
are referred to as water-repellent soils, cause soil
erosion and productivity reduction in farmlands [1].
In some cases of a natural environment, soil gains
water repellency by being coated with organic
matters decomposed by fungi, and it is observed thatinterfusion of hydrophobic grains into hydrophilic
grains makes dramatic differences in flow behavior
and hydraulic properties [2].
Various works assessing and quantifying water
repellency and hydraulic properties of artificial
water-repellent soils as well as natural ones havebeen conducted, and it is shown that the hydraulicproperties of soils change gradually with theincreasing mix rate of hydrophobic grains [3][4].
While measured properties could be represented
with relative ease in some functional form such asvan Genuchten-Mualem model, predicting those
properties effected by grains’ wettabilities needs
microscopic approaches. For instance, a functionalmodel is proposed by Ustohal et al. (1998) [3], inwhich the Brooks-Corey model is extended using
probability distribution of apparent contact angles on
grain clusters with mixed wettabilities. And porescale network modeling also proficiently predicts
multiphase flow properties through mixed porous
media [5]. But this approach requires large
computational load even for several cubic
centimeters of porous media.

In this study, a physically-based conceptualmodel, which needs relatively low computationalload, is developed by adopting the concept on thecluster of grains. The model realizes a spatial
distribution of clusters and makes it possible toreproduce non-uniform wetting and drainage fronts
through porous media mixed with hydrophilic andhydrophobic grains. And water retention propertiesof the mixed porous media are estimated from thecomputed results in a bottom-up manner.
MODEL
Model Structure
The physically-based conceptual model proposed
here employs a cellular-automaton-like algorithm totrack water- and air-intrusion paths through porous
media. Generally, a cellular automaton is referred toas a collection of cells that have several variablestates in a regular grid, and the cells evolve
according to a set of rules based on the states ofneighboring cells during iteration of discrete time
steps. The rules are applied to initial cell states, andnew cell states are obtained according to the rules.
This process is repeated for as many time steps as
desired [6].
In this study, cells correspond to clusters ofmultiple grains as illustrated in Fig. 1. This figure
depicts a schematic of the model two-dimensionally,
but grains, cells and capillary tubes are defined as
three-dimensional objects in the model. The concept
about the cluster is originally used by Ustohal et al.
(1998) [3] for modeling hydraulic properties of
mixed porous media by using a functional form,
452

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 2
Realizations of a cell, apparent contact
angles, and probabilities in a case where the mix rateof hydrophobic grains is 0.75.
Fig. 1 Relation between grains and cells in a caseof a square grid.
Pporous medium is p , the probability of thegDrealization that has ni (  0,1,..., n ) hydrophilic
grains is described by the binominal distribution.

and they presumed that the contact angle in eachcluster is homogeneous, based on the Cassie’s law.
The contact angle, which is apparent one
synthesized from mosaic of various contact-angle
surfaces, is determined, depending on the ratio ofhydrophilic and hydrophobic surface areas includedin each cluster. While Ustohal et al. (1998) [3]treated a cluster itself as a meso-scale wall surface,
we assume in this model that each cluster
conceptually possesses a bundle of circular tubes
with various diameters. And it is also assumed thateach tube has constant diameter through a single cell,and that the apparent contact angle of the tubes in acell has identical value. The apparent contact angle
is estimated from the Cassie-Baxter equation,
depending on the ratio of surface areas of the grains
with different contact angles. When grains withadifferent n types of contact angle are included, theapparent contact angle of the i th cellcc( i  1,..., n ; n is the number of cells) isrepresented as follows.
ng

P ( ni , n ) 
D

(1)

a

fij  Aij /  Aik

(2)

k 1

where  is the apparent contact angle of the i thacell,  j is the j th contact angle among n types,
f is the ratio of the surface area with j th contact
angle to the total area, and Aij is the surface area. If
the size of all grains is equal and two types of
wettability, i.e., hydrophilic and hydrophobic grains,
are included, Eqs. (1) and (2) could be represented
as follows.
c

i

ij

cos i  fi cos   (1  fi ) cos 
D

D

D

P

(3)

fi  ni / n(4)gwhere n is the number of grains included in a cell,Dand ni is the number of the hydrophilic grains in
the i th cell. Equations (3) and (4) imply thatgapparent contact angle of a cell that has n grainsgcan have ( n  1) types of realization, depending ongD
the number of ni (  0,1,..., n ). When the fractionof the hydrophobic grains included in a whole
D

D

g

D

D

g

D

 grij(6)

where hij and rij are the potential capillary height
and the radius of the j th tube in the i th cell,respectively,  and  are the surface tension andthe density of water, respectively, and g is thegravitational acceleration. Equation (6) means thatccapillary rise could occur when hij is positivecc( i  90 degrees ), and that capillary fall when hijcnegative ( i  90 degrees ).
There are various options for arrangement ofcells and grains. For cell arrangement, the following
grids are considered, such as a simple cubic grid andbody-centered cubic grid as shown in Fig. 3. Twoclasses of grain packings are introduced in Ustohal
et al. (1998) [3]: tetrahedral packings and cubic
packings. One of the essential indices for selectionof grid is connectivity of cells, which is the numberof neighboring cells. It is reported that theconnectivity of pores is an essential factor that
effects hydraulic properties of porous media by
Gharbi and Blunt (2012) [5]. In this case, the cellconnectivity has an effect on likelihood of statechange of cells.

with

c

2 cos i
c

j 1

n

D

c

hij 
c

c

(1  p P ) ni ( p P )n ni (5)ni !( n  ni )!
In a case where a cell has four grains, the contact
angles of hydrophilic and hydrophobic grains are
30.0 degrees and 120.0 degrees, respectively, andthe mix rate of hydrophobic grains is 0.75, a cell has
five realizations. The apparent contact angles andprobabilities of the realizations are shown in Fig. 2.
Capillary tubes in each cell have an ability ofcapillary rise or fall, depending on the apparent
contact angle and the radius of tube, if the lower endof tube is connected to a water pool. The height ofthe capillary rise or fall from the surface of the waterpool is termed ‘potential’ capillary height here, andthe height is represented based on the YoungLaplace equation for circular tubes.

acos  i   fij cos j

n !

g

g

453

GEOMATE-Nagoya, Nov.13-15, 2013

holds the following four conditions.
1) the objective wet cell connects to the waterpool through other wet cells or directly,2) any of its neighboring cells is dry,3) any of the neighboring dry cells connects to the
air pool through other dry cells or directly, and4) the potential capillary height of all the capillarytubes in the objective wet cell satisfies thefollowing inequality.

hij  hicFig. 3 Three-dimensional cell arrangement.



p



j  1,..., n

t



t



(8)

The proposed model treats water and air
intrusions in a sub-Darcy scale as mentioned above.
The hydraulic properties of porous media such as thewater retention property and permeability are macroscale ones. So, to estimate such macroscopic
properties, some operation such as integration andaveraging over some part of a computational domain
is needed using a computed result.
To evaluate water retention properties, saturation
at a certain water pressure head is calculated from
cells within a certain range of water pressure heads
as follows.

In this model, each cell has two states: dry state
and wet state. And one state of a cell could change
into the other, depending only on the current statesof its own and neighboring cells. After all cells areevaluated based on the current states, all the cells are
updated simultaneously and a new set of states isobtained. This process is iterated until any change
does not occur or desired time steps are satisfied. To
simulate water intrusion into a dry porous medium(wetting process) or air intrusion into a fully wet
medium (drainage process), the conditions for statechange are given as described below.
In the wetting process, initially each cell in an
objective domain is set to be dry state, and cells at
the upper end and at the bottom end are supposed toconnect to exterior air and water pools, respectively.
An objective dry cell changes into wet, if the cellholds the following four conditions:
1) the objective dry cell connects to the air poolthrough other dry cells or directly,2) any of its neighboring cells is wet,3) any of the neighboring wet cells connects to thewater pool through other wet cells or directly,and4) the potential capillary height of any of thecapillary tubes in the objective dry cell satisfies
the following inequality.
cj  1,..., n

Estimation of Water Retention Properties

Rules for Wetting and Drainage Processeshij  hipnt

Sw ( p) nt r / ri ( p ) j 1

2
ij ij

i ( p ) j 1

2
ij

(9)

with

1 if the jth tube in the ith cell is wet(10)0 if the jth tube in the ith cell is dry

 ij  

 ( p) i  1,..., n p   p  pi  p   p (11)where  ij is a coefficient that distinguishes whether
the tube is wet or dry,  ( p ) is a set of cells undercwater pressure head from p   p to p   p , n iscthe number of cells, and pi is the pressure headplaced on the i th cell.
EXPERIMENT(7)

The soil column method is employed to measure
the water retention properties of porous media mixedhydrophilic and hydrophobic grains. The soilcolumn is made by piling up acrylic circularcylinders whose inner diameter is 4.8 cm and heightis 4.0 cm, and each cylinder is taped together strictly
to avoid air and water leaking (Fig. 4). Dry materials
are packed in the column at a prescribed density, andthe top and bottom of the column are covered byporous filters to prevent air entrapment. In a case ofa wetting process, preliminarily materials are driedadequately in a desiccator. In a case of a drainage
process, a packed column is saturated by the vacuum
method, because materials containing a highpercentage of hydrophobic grains will not inundate
spontaneously. Then, a certain water pressure isconstantly placed on the bottom of the column until

where hi (   pi /  g , pi is the water pressure
placed on the i th cell) is equal to the heightfrom the surface of the water pool.
The first condition assumes that the air pressure in
dry cells that connect to the exterior air pool is equal
to atmospheric pressure, which is supposed to beconstant here, and that the air pressure of enclosed
air in dry cells that do not connect to the air pool
could change and constrict water entry by airpressure increase. The third condition assumes thatthe water pressure in wet cells that connect to thewater pool is hydrostatic one.
In the drainage process, initially all cells are set
to be wet. Cells at the top end and at the bottom end
connect to exterior air and water pools, respectively,in the same way with the wetting process. An
objective wet cell changes into dry, if the wet cellp454

GEOMATE-Nagoya, Nov.13-15, 2013

the column reaches an equilibrium state (72 hours inthis study), and weights of materials in each cylinder
is measured before and after oven-dry. All theseprocedures are conducted in a room whose
temperature is kept at 20 degrees Celsius.

Fig. 5
Measured water retention properties atvarious mix rates of hydrophobic grains (wetting
process).

Fig. 4 Soil column method.

MATERIAL
In this model, we assume a uniform grain size foreach wettability. So, for the experiments glass
spheres whose diameter is 0.2 mm are used ashydrophilic materials. It is checked that the
distribution of the diameter is narrow enough fromimages taken by a microscope. After washing anddrying, the original glass spheres are hydrophobizedby vapor-depositing octadecyltrichlorosilane ( CH 3 (CH 2 )17SiCl 3 , OTS), which is a popular chemicalmaterial used in other works [3][4]. Specimens are
made by homogeneously mixing hydrophilic andhydrophobic spheres at the following mass-based
rates of hydrophobic grains: the mix rates ofhydrophobic grains are 0.00, 0.25, 0.50, 0.75, and1.00. And the bulk density of specimens is3
controlled to be 1.58 g/cm , when materials arepacked in the acrylic cylinders.

Fig. 6
Measured water retention properties atvarious mix rates of hydrophobic grains (drainage
process).
Parameters and Computational Conditions
In this study, a simple cubic grid, in which inner
cells have six neighboring cells, is employed. The
grid interval is estimated from the following
equation, based on the diameter of grains and thenumber of grains in one cell.
1 4  g rg 3 n p  3l  3 b 

RESULTS AND DISCUSSION(12)

where l is the grid interval,  g is the density ofglass,  b is the bulk density of the specimen, and rg
is the radius of the glass sphere. The number ofcapillary tubes in a cell is also estimated, assuming
grains are arranged in a simple cubic grid.

Experimental Results
The measured water retention properties of bothwetting and drainage processes are shown in Figs. 5
and 6, respectively. These results show that the mix
rate of hydrophobic grains has a great effect onwater retention properties, and that the water
retentivity decreases as the rate increases in bothwetting and drainage processes.

2
1
 
 
3
 2  3 b  tn  round  l 
 1 
3    4  g rg 



455

(13)

GEOMATE-Nagoya, Nov.13-15, 2013

where round() is the function that rounds input
value off to the closest whole number.
The computational domain is set as a cuboid andthe size is
10 cm  10 cm  80 cm, which isbased on the experimental column used here.
Simulations are conducted with three types of grain
number included in one cell: the number is 4 in TypeI, 8 in Type II, and 27 in Type III. The parameters
included in the model are given or estimated basedon the materials used for experiments and those aresummarized in Table 1. The radius of the capillarytubes is determined here by the normal distributionttwhose average  and standard deviation  are
0.04 mm and 0.006 mm, respectively. These values
are based on the previous work that estimatedhydraulic conductivity of porous media using a porescale network model [7].

for the cell size. This implies that the number ofgrains in a cell has an influence on computed results.
Next, the computed water retention properties ofwetting and drainage processes are shown in Figs. 8
and 9, respectively. These figures show that water
retentivity decreases clearly as the mix rate ofhydrophobic grains increases. While all thesaturations varies smoothly in Type III, there exist
several step-like changes in Type I and Type II.
Such a step-like change is also observed in Fig. 7 (b),which shows that the ratio of dry cells increases
obviously above about three-quarters of the sample
height. The cause of the sudden change in saturationis considered that each realization of the apparent
contact angle in Type I and Type II has relatively
large probability compared with Type III because
the number of grains in a cell is small. This alsomeans that cells become more homogeneous as thenumber of grains in a cell increases.
Compared with the experimental results (Figs. 5
and 6), the computed results shows some differences.
In wetting processes, water enters capillary tubes
under negative water pressure even in the case of
0.50 of the mix rate, while spontaneous water-entry
is prevented from only 0.25 of the mix rate. This
indicates that in actual cases a single hydrophobic
grain has an influence on all the hydrophilicneighboring grains, and which is left out ofconsideration by dividing the grain gathering into
many clusters in the model.
In drainage processes, water is drained promptly
depending of the mix rate in the computed results,
while much water is kept up to 20 cmH 2 O even in
the high rate cases of the measured results. The
reason is considered that speed of air-water interface
movement is not considered in the model. In actual
cases, water in large pores is drained in advance ofthat in small pores, and such non-uniform drainage
could make water isolation in a pore-network. But inTable 1 Parameters Used for Each Type.

 (deg)P (deg)t (mm)t (mm)
gnType IDtnl (mm)

4
3
0.298

Type II
45
120
0.04
0.006
8
4
0.376

Type III

27
9
0.564

Computed Results
Some of the computed results of non-uniform
water-intrusions in wetting processes are shown in
Fig. 7. The mix rate of hydrophobic grains is 0.50
and the height of the depicted samples is 5 cm. The
pressure head placed on the bottom of the samples is
5 cmH 2O. Though the samples are cut out from theoriginal computed domains in the same position,
those are markedly different in appearance except

Fig 7 Water intrusions in a case where the mix rate of hydrophobic grains is 0.50.
456GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 8 Water retention properties of wetting processes.

Fig. 9 Water retention properties of drainage processes.
REFERENCES

the model all waters included in cells that satisfies
the drain conditions are drained at once in one
discrete time step.

[1] DeBano LF, “Water repellency in soils: ahistorical overview”, J. of Hydrol., Vol. 231232, 2000, pp. 4-32.
[2] Bauters TWJ, Steenhuis TS, DiCarlo DA,
Nieber JL, Dekker LW, Ritsema CJ, Parlange
JY, and Haverkamp R, “Physics of water
repellent soils”, J. of Hydrol., Vol. 231-232,
2000, pp. 233-243.
[3] Ustohal P, Dtauffer F, and Dracos T,“Measurement and modeling of hydrauliccharacteristics of unsaturated porous media with
mixed wettability”, J. of Contam. Hydrol., Vol.
33, 1998, pp. 5-37.
[4] Annaka T, “Wettability indices and water
characteristics for sands of mixed wettability”, J.
Jpn. Soc. Soil Phys., Vol. 102, 2006, pp. 79-86.
[5] Gharbi O and Blunt MJ, “The impact of
wettability and connectivity on relative
permeability in carbonates: A pore networkmodeling analysis”, Water Resour. Res., Vol.
48, W12513, 2012.
[6] Chopard B and Droz M, Cellular Automata
Modeling of Physical Systems, Cambridge
University Press, 2005.
[7] Ijiri Y, Takeuchi J, and Fujihara M, “Estimationof hydraulic conductivity by pore-scale
network”, in Proc. Applied Hydraulics
Workshop, JSIDRE, 2012, pp. 92-92 (inJapanese).

CONCLUSION
A physically-based conceptual model was
proposed to reproduce non-uniform water- and airintrusions through porous media mixed withhydrophilic and hydrophobic grains. In the model,
the cellular automaton-like algorithm was employed
to figure out the intruding paths, and the hydraulicproperties were estimated from the computed
intrusion paths in a bottom-up manner.
The computed results that had reproduced
wetting and drainage processes were compared withthe experimental results using glass sphereshydrophobized by OTS. Although there werediscrepancies in the water-entry pressure for thewetting processes and in the air-entry pressure forthe drainage processes, the dependence of water
retentivity on the mix rate of hydrophobic grains andnon-uniform water and air intrusions were illustrated.
And it was also shown that the number of grains in acell was one of the essential factors in this model,
because it effects the value and probability of theapparent contact angle in cells. From these results, it
is concluded that the proposed model has thepossibility of being provided as a useful tool toestimate the hydraulic properties of porous media
with different wettabilities.
457

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CAPTURING PEDESTRIAN MOVEMENT SAFETY AND SECURITY
ISSUES AT MAJOR TRANSPORTATION INTERCHANGES
Zulfadly Azizi Bohari1, Syahriah Bachok1 and Mariana Mohamed Osman1
1

Kulliyah of Architecture and Environmental Design, International Islamic University
Malaysia
ABSTRACT

More often than not, transportation nodes such as stations, interchanges and terminals were designed without
much consideration to the needs, ergonomics and behavior of prospective passengers and public transport users.
This research reports the first phase of the validation of data for the capturing of pedestrian behaviours at majorinterchanges. Applying the methods of video recording and manual passenger counting, the study used a casestudy of Masjid Jamek public transport interchange in Kuala Lumpur, to record and validate the pedestrian
access and egress movements. This research aims at analyzing these empirical data to estimate these movements
to estimate and calibrate the more appropriate models for improving pedestrian flows at these interchanges.
Public transport operators and authorities may use the models to plan and design these nodes more effectively
and ensure safety and security of passengers and users, especially during peak hours and irregular influx of trip
making during seasonal holidays or major events.
Keywords: Pedestrians, Public Transport Interchanges, Multimodal, Movements,Modelling

INTRODUCTION
PROJECT BACKGROUNDThis study attempts at evaluating the movement
characteristic of passenger in the interior space of astation building. The case study of a typicalmultimodal interchange facility, found in Kuala
Lumpur, Malaysia, has been selected to represent
commuting trip makings involving more than one
modes of public transport.

The research aims at determining the pedestrianvolumes and movement patterns in a crowded public
transport interchange station. Kuala Lumpur, with apopulation of 2.1 million and a size of 243 km2, isthe capital of Malaysia. It is currently served by fivemain rail-based public transportation services,namely RAPIDKL systems (Ampang and Kelana
Jaya Lines), Monorail system, KLIA Ekspres and
KLIA Transit systems and the heavy rail KTM
Komuter system (Figure 1).

Using the case study of Majid Jamek Interchange,
where passengers transferred from one light railsystem to another, this research applied two types ofdata collection namely passenger counting and video
recording. Masjid Jamek Interchange or station is
located at the heart of the city, a busy and rapidly
growing district in Kuala Lumpur. Major landuses
are commercial, retails, businesses and financial.
In an urban centre, public transport plays animportant role in transporting the passenger fromone place to another. The services efficiency
provided by the transit agencies has resulted in ahigh number of public transport ridership. Numbersof projects such as increasing train frequencies andcapacities, upgrading the ticketing and information
system, improving the station integration are
conducted in order to meet the demand of users. In
such improvements, transit agencies also take into
account the circulation of passengers in stationbuildings. Heavy flows of people moving throughstation buildings especially during peak hours
require careful planning during the design phase.

Figure 1: Kuala Lumpur rail network map(source: www.kuala-lumpur-rail-transit.com )Previously, Masjid Jamek Station served as
regular station between two separate lines, namely
Kelana Jaya Line (KLJ Line) and Ampang Line

458

GEOMATE-Nagoya, Nov.13-15, 2013

(AMG Line). However, passengers could notaccomplish their transfer movement directly becauseof different ticketing system from both lines. Due tothat, passengers who wanted to transfer between
KLJ Line to AMG Line and vice versa needed toexit the paid area before completing their transfer
activities (required to buy new ticket) to the next line.

for case studies in developing cities due to thevariations in buildings’ or facilities’ architecturaldesigns, evacuation strategies and pedestrians’
characteristics.
Safety issues in public transport interchange
facility
A public transport interchange or transfer
facilities are the first points of contact between thepassengers and multimodal public transport services.
The spacing, location, design, and operation ofinterchanges significantly influence the transit
system performance and pedestrian movements. Asa basic necessity for interchanges or transfer
facilities, the design of these buildings or sections ofbuildings should fulfill certain parameters such as
distance from origin/destination to the platforms andthe walking time, whilst its physical conditions
should be ergonomic and weather proof in design.

Recently, in November 2011, the integration ofticketing system was implemented between KLJ
Line and AMG Line to meet the demands ofpassengers and to encourage direct transfer activity.
Integration of Masjid Jamek Station and ticketingsystem has resulted in direct paid to paid movement
between KLJ Line and AMG Line. This requires
some improvement towards the interior space ofMasjid Jamek Interchange Station such as raising thefloor level of existing Concourse 1 of AMG Linestation; relocating of the ticketing counter of AMG
Line Station and the new ticket gates. The changes
of interior space of Masjid Jamek Station influenced
the passengers’ movement especially at theconcourse area and have led to confusion among
passengers. Hence, pedestrian movement in a
crowded public transport interchange is an area lessstudied by scholars, particularly in Malaysia. Thereis a limited research on crowd movement issues,
warranting a research such as this to be conducted.

Entry and exit points location are crucial
elements to improve the quality of interchanges. The
determination of these points is an important aspect
for operational consideration as the strategic andeasily identified and accessible points will ensure atimely and systematic and smooth evacuation
procedures, minimising the number of casualties anddamages to properties. It should also be visible forpedestrians to identify exits or entry gates orturntiles for safety and must have the easy exit to thecongregation areas and the criteria of comfort andconvenient. In addition, these facilities should instill
the feeling of safety and security among passengers,away from the fear of crime.

Crowd Movement Study
Microscopic
Researchers [1], [2] & [3] highlighted thatmicroscopic level refer to individual pedestrian
behavior that exists in the crowd. Several behaviors
such as collision avoidance and selecting the shortest
path to the target are taken into account at this level.

The use of cameras in determining and capturing
the pedestrian movements, particularly in crowded
areas is very common nowdays. There are so many
issues related to the CCTV and real time cameras
provided in the present practice of precautionary
safety and security measures, these included that:i.
In certain blind spots, two cameras maybe
required to cover the varied movements ofpedestrian entering and exiting the transfer
facilities.
ii.
Capturing, digitising and separating therequired frames for purposes of modelling,
estimating and calibrating required great
effort and longer time period.
iii.
The dataset such as speed, volume,
direction and way finding behaviours mayneed to be confirmed and validated using
another set of methods such as CCTV andpedestrian counting or observations.

Macroscopic
Meanwhile, macroscopic level is different frommicroscopic. It deals only with the generalproperties of the whole crowd such as flow anddensity, disregarding the interactions of anindividual pedestrian with the environment andothers [3]. Macroscopic models use the relation ofdensity to walk speed and flow to calculate overall
movements of the crowd.
Some attempts have been identified to have been
lacked in modeling of the agent-based or
disaggregated models of pedestrian movements incrowded places. In particular, limited studies havebeen focused on the comparison of peak and offpeak hours of commuting trips. It was also
inconclusive as to how pedestrians’ typological andphysiological variations affected the speed andvolume of movements in these places. Moreover,travelling speed from the point of origin towards theend destination could not be modeled appropriately

PROBLEM STATEMENTS

459

GEOMATE-Nagoya, Nov.13-15, 2013

The review of literature has established thefollowing problem statements:i.
There are inconsistent pedestrian behaviors
in way finding especially during off-peak
and peak hour of commuting in developing
cities’ interchanges facilities.
ii.
It is still unclear which primary factors
influence the speed and movement ofpedestrians in crowded situations such as
during multimodal transfers activities.

ii. Variation in peak and off-peak passenger
volumes, andiv. Travel distance between entrance and exit
points (in meter).
Three cameras were set at strategic locations tocapture passengers’ or pedestrians’ movements.
During the site appraisal, several blind spots wereidentified.
Due to mobility and logistics reasons, several
limitations during the surveys have been overridden
by increasing the number of equipments andpersonnel in charge as enumerators. Enumerators
were assigned to record the pedestrian counts using
traffic counters.

RESEARCH QUESTIONS AND OBJECTIVES
Research questions raised from the above
problem statements are:i.
What are the pedestrian behaviours in way
finding in especially during off-peak andpeak hour of commuting in developing
cities’ interchanges facilities?
ii.
How best can the speed and movement ofpedestrians in crowded situations such as
during multimodal transfer activities bemodelled?

The camera setting activities were undertaken during
the weeks of 27th December 2012 (Thursday) until
14th January 2013 (Monday). Pilot survey ofpedestrian count and pedestrian movement
observation were also conducted during this period.
Pedestrian counts were carried out during the week
beginning 18th February until 22nd February 2013.

The objectives are:i.
To identify the pedestrian behaviours inway finding in interchanges facilities.
ii.
To evaluate the factors influencing speed
and movement of pedestrians in crowded
situations.

Video Recording of Pedestrian Activities
During the pilot study, video recording has been
performed to identify the strategic points for locatingrecording equipments. This was important to ensure
the installed video cameras covered all the section of
the study area and high data accuracy can beensured. Figures 2 through to 5 show the location ofcameras and the recorded angles.

METHODOLOGY AND APPROACHESThis section will highlight the methods andapproaches that were adopted in the study. The two
methods applied in the study were video recording
and manual passenger counting. Studies [4] and [5]illustrated that the significance video recording inpedestrian study provide many advantages such as
the ability to represent the movement of pedestrians
and the variables interactions in real time.
Three types of primary data were collected forthe modelling exercise. First, three cameras were set
up at different points in the stations to capture realtime movement of the pederstrians. Second,passengers or pedestrian counts were conducted on
the selected days and time period. Finally, stations’and interchange facililities’ layout designs were
hand-drawn to identify possible routes, entry andexit areas as well as potential conflicts and collision
points. Secondary data collected through therecordings of CCTV and computer-aided
designed/drawn stations and facilities layout were toreinforce and reconfirm the following variables:
i. passenger’ travelling speed (meter/second),ii. Passengers’ typological and physiologicalattributes,

Figure 2: Three points are identified for video
camera installation.

460

GEOMATE-Nagoya, Nov.13-15, 2013

and survey forms. Passenger number were recorded
and transcribed into the forms. The lapse intervals
were set to 5 minutes so as to evaluate variations in
the data. The collection of field data was made forsample length of 7 hours per during both peak andoff peak periods for comparison purpose.

Figure 3: Recorded angle from Camera 1.

Figure 4: Recorded view from Camera 2

Figure 6: Position of enumerators in Masjid Jamek
Interchange Station.
Sampling
The sample size was selected from movement of one
direction i.e. from point O-D at 7.15 am to 7.45 am.
Figure 7 shows the direction of movements from O(escalator and staircase) to D (ticket gates).

Figure 5: The view from Camera 3 location withenumerators, positioned at strategic points in theinterchange facility, were capturing the pedestrian
movement by the utilization of traffic counters.
Passenger Counting
Passenger counting was also performed in thisstudy. It was one of the manual count methods inpedestrian study [4]. The manual counts bring hugebenefits towards the study, for example providing
large set of necessary data (i.e. age, gender, physicalattributes and behavior). Further, manual counts also
could capture and gather significant data such asclassifying volumes and recording observations [4].

Figure 7: Movement direction of passenger fromescalator/elevator (point O) to ticket gates (point D).
Performing Video Analysis and Speed Capture

The passenger counting survey required a large
number of enumerators. They were located mainly at
the ingress and egress points of the concourse area
(Figure 6). Their task was to count the number ofpassengers passing the ingress and egress point
based on gender, physical attributes and age.
Enumerators are equipped with mechanical counter

A video analysis phase was carried out in SemiAutomated Video Analysis (SAVA) program. Then
video analysis was performed on the segmented
frames to determine the agent’s gender, physicalattribute, age, familiarity, travel time and walk461

GEOMATE-Nagoya, Nov.13-15, 2013

speed. Figures 8 and 9 show the process of video
analysis.

Figure 9: Pedestrian numbered 60 has reached thesecond line at 00:04:30:440.
DATA ANALYSIS
Based on the manual counting data, it was foundthat
there were 35 males, 68 females and one physically
impaired pedestrian traveling from point O-D
between 7.15am and 7.45am. The highest number ofpassenger moving from point O-D was between
7.30am -7.35am. Within this time interval, the total
number of passenger moving from O-D was 33. In
the tabulated data, females walked at slower speed toreach the destination points, ranging from 0.22
meter/second to 1.34 meter/second. Meanwhile,
male pedestrians walked slightly faster, ranging
from 0.75 meter/second to 1.5 meter/second.
Several attempts at modeling the agent-based
movement have been carried out. Two of thealternative models were estimated in Tables 1 and 2.
Table 1: Regression Analysis Output 1

Variables

T-statistics

p-value

In Figure 8, the orange boxes indicate the labeledpedestrian number and the starting time. For
example, the pedestrian labelled 60 was a female
and she reached the first line at 00:04:20:040.

Regression Statistics
Coefficient

R-square = 0.47

Constant

1.07841

14.07190.0001

Gender

-0.0292-0.6558

0.5134

Physical
Attributes
Familiarity-0.1732-0.7986

0.4263-0.2951-9.4991

0.0001

Directional
Movement-0.1254-2.5282

0.0129

Table 2: Multiple Regression Analysis Output 2

p-valueT-statistics

Variables

Regression Statistics
Coefficient

R-square = 0.54

Constant

1.821410.14640.0001

Gender

-0.1067-3.35030.0011

Physical Attributes-0.0877-0.5761

0.5658

Familiarity-0.3079-9.99160.0001

Directional
Movement-0.0647-1.80520.0740From the tables, the estimated models have r2
values ranging from 0.47 to 0.54 indicating a462

GEOMATE-Nagoya, Nov.13-15, 2013

moderate relationship between the combinations ofparameters in determining the speed of pedestrian.
The estimations have also indicated that at 95%
confidence level, factors such as familiarity with thestation layout and facilities, walking pattern or
directional movements and gender may influence thespeed of travel from the escalators to the ticketing
exit gates and from the ticketing entry gates to theescalators.

tendency of walking systematically in agroup should be properly guided andassisted by evacuation or emergency
personnel to congregation areas.
This research has attempted to model pedestrian
movements in a crowded interchange facility, withthe aim of minimizing the impacts of safety andincreasing the smooth and systematic evacuation
strategy during an emergency. The models estimatedcan be of great use to operators and otherstakeholders so as to increase the safety levels andensure security is kept at the highest level possible.
In the era where safety and security threats have also
impacted and effected public transportation
operations, safeguarding the pedestrians andpreventing an emergency should always be firstconsidered in designing and planning of public
transport transfer infrastructure and facilities.

DISCUSSION AND CONCLUSION
The safety levels in an interchange can be influenced
by the transfer facilities’ layout design, thelocational distribution of the facilities, entry and exit
points as well as pedestrians’ movement speed froman entry point to an exit point.
This research has employed a combination ofcamera, CCTV and manual pedestrian counts to
identify pedestrian movement and speed in a
crowded rail station where users transferred fromone rail mode to another. The use of cameras,
CCTV, and manual counts were not without theirdrawbacks. Analyzing the videos recording also
proved to have posed some challenges to theresearch team.

ACKNOWLEDGEMENTS
The authors would like to express their gratitude to
Research & Development Division of Syarikat
Prasarana Negara Berhad for their assistance,
advice and resources rendered during theundertakings of this research project.

Accuracy and validity of the research data depended
very much on the methodology adopted for thisresearch. The moderate correlations between the
speed and factors influencing the movement ofpedestrian have been explained in the previous
sections. In essence, gender, familiarity with thestations or interchanges facilities and directional
movements of pedestrian indeed determined thelevels of speed with which passengers can ensure
their safe and smooth transfer from one mode toanother.

REFERENCES[1] Steenbakkers J. and Van der Weij S. (2010),
Pedestrian Logistics Simulation– Crowd
Management in Stadiums,
Gert Zülch &Patricia Stock (Hrsg.) Karlsruhe, KIT Scientific
Publishing[2] Sarmady S. (2008), Modelling and Simulationof Movements and Behaviours in Large Crowd
Using Cellular Automata[3] Burger M., Markowich P., Pietschmann J. F.
(n.d), Continuous Limit of a Crowd Motion andHerding Model: Analysis and Numerical
Simulations[4] Miranda and Carrasco, 2011, “Pedestrian
Volume Studies: A case study in the city ofGothenburg”, Department of Civil andEnvironmental
Engineering,
Chalmers
University of Technology.
[5] Teknomo K, Takeyama Y, and Inamura H.,
2000, data collection method for pedestrian
movement variables. Jurusan Teknik Sipil,
Fakultas Teknik Sipil dan Perencanaan –Universitas Kristen Petrra[6] http://www.spad.gov.my[7] http:// www.kuala-lumpur-rail-transit.com

This research is limited, however, by theinterpretation of physiological attributes of thepedestrians including the height, shoulder width andpersonal characteristics.
Based on the estimation carried out, the following
conclusions can be drawn:i.
To reach the exit and assembly points
within 2 minutes of an emergency
situations, the distance from the escalator
should not be more than 150 meters, while
ensuring 95% of passengers to be
evacuated safely and smoothly.
ii.
During crowding and evacuation
activities, pedestrians such as females,
those who are unfamiliar with the stationlayout design and those who has lesser

463

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ASSESSMENT OF CHROMIUM CONTAMINATION IN SEDIMENTS
OF SOUTHERN KAOHSIUNG HARBOR, TAIWAN

1

Cheng-Di Dong1, Chih-Feng Chen1 and Chiu-Wen Chen1
Department of Marine Environmental Engineering, National Kaohsiung Marine University, Kaohsiung
81157, Taiwan, ROC

ABSTRACT
Major objectives of this study are to evaluate the enrichment, accumulation, and potential ecological risk ofchromium (Cr) in the surface sediments of southern Kaohsiung Harbor, Taiwan. Twelve sampling locations were
installed of southern Kaohsiung Harbor to collect sediment samples for analyzing Cr. Results showed that the Crconcentrations varied from 13.4–265.7 mg/kg with an average of 53.2±71.2 mg/kg. The spatial distribution of Cr
reveals that the Cr concentration is relatively high in the river mouth region, especially in Jen-Gen River, andgradually diminishes toward the harbor entrance region. This indicates that upstream industrial and municipal
wastewater discharges along the river bank are major sources of Cr pollution. Results from the enrichment factor
and geo-accumulation index analyses imply that the sediments collected from the river mouth can becharacterized between severe and very severe degree enrichment and between moderately strong and strong tovery strong accumulation of Cr, respectively. However, results of potential ecological risk index indicate that the
sediment has low ecological potential risk.
Keywords: Accumulation, Chromium, Ecological Risk, Enrichment, Sediment.

electronic and foundry), municipal surface runoff,and transportation pollution [6]. All the pollutants
will eventually be transported to the river mouth
and/or harbor to deposit and accumulate in thebottom sediment.
The objective of this study is to investigate the
Cr distribution in the surface sediment of the water
body between river mouths (i.e., Jen-Gen River andSalt River) and harbor entrance of Kaohsiung
Harbor so that the degree of Cr enrichment,
accumulation, and potential ecological risk can beevaluated.

INTRODUCTION
Chromium (Cr) is moderately toxic to aquaticorganisms; its presence threatens the water
ecological environment. [1]. Therefore, muchresearch effort has been directed toward the
distribution of Cr in water environment.
Anthropogenic activities including tanning, mining,smelting, domestic and industrial wastewaters, steam
electrical production, and sewage sludge are themajor source of Cr pollution [1,2]. In receiving
water body, Cr is presented essentially as hydroxycomplexes of low solubility associated with thewater-borne suspended particles [3,4]. After a seriesof natural processes, the water-borne Cr finallyaccumulates in the sediment, and the quantity of Cr
contained in the sediment reflects the degree ofpollution for the water body [5].
Kaohsiung Harbor is located on the southwestern
shore, and it is the largest international harbor in
Taiwan. the harbor receiving effluents from fourcontaminated rivers, including Love River, CanonRiver, Jen-Gen River, and Salt River. Results ofprevious research indicate that the Kaohsiung
Harbor is heavily polluted with Cr, and the Jen-Gen
River and Salt River are both major pollution
sources [6]. The two rivers flow through the
downtown area of Kaohsiung City and finallydischarged into Kaohsiung Harbor (Fig. 1). The
major pollution source includes domestic wastewater
discharges, industrial wastewater discharges (e.g.
tanning, metal processing, chemical production,

22°35.8'
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22°31.0'120°22.5'

120°17.0'

Fig. 1

Map of the study area and sampling
locations.

MATERIALS AND METHODS

464

GEOMATE-Nagoya, Nov.13-15, 2013

Twelve sampling stations were distributed insouthern Kaohsiung Harbor, Taiwan (Fig. 1).
Surface sediment samples were collected at 12
stations selected in this study in February, 2011 with
Ekman Dredge Grab aboard a fishing boat. The
collection, pre-processing and analysis program ofsediment sample have been detailed previously [7,8].
The collected samples were characterized foraluminum (Al), chromium (Cr), grain size, watercontent, and organic matter (OM). The Al and Pb
contents were determined using a flame atomic
absorption spectrophotometry (Hitachi Z-6100,
Japan) after digestion procedures [7,8]. The
sediment grain size was measured using a Coulter
LS Particle Size Analyzer; water contents were
determined by oven-drying at 105°C; OM wasdetermined using the LOI (loss-on-ignition) method
at 550°C. The characteristics of sediment (e.g. grainsize, water content, and OM) have been reported indetail previously [8].

pollution source can influence the partition of Cr in
sediment organic matter.
enn-G er
Riv

N

Je
S10

LegendCr(mg/kg)

S9

50
100
S8
150

Harbor Entrance

S7
S6
S11

S5

S4

S12

S2
S3

S1
Salt
River

Fig. 2

Spatial distribution of chromium (Cr)contents in the surface sediment of southernKaohsiung Harbor.

RESULTS AND DISCUSSION
400

Chromium (mg/kg)

Distribution of Chromium in Sediments
All surface sediment samples collected at 12
monitoring stations studied contain 13.4–265.7
mg/kg with an average of 53.2±71.2 mg/kg. Spatial
distributions of Cr concentration in the surface
sediment shown in Fig. 2 reveal that the sediment Cr
content is relatively higher near the mouths of JenGen River (site 10), and Salt River (site 1), andgradually decreases in the direction toward themouth of harbor (sites 11 and 12). Theseobservations clearly indicate that the upstream
pollutants brought over by rivers are the major
source of harbor Cr pollution. The both rivers
receive a great amount of industrial and domestic Cr
from Kaohsiung city because about 40% domestic
wastewater is discharged directly without adequate
treatment [6]. Moreover, several industrial plants(e.g. metal processing, paint and dye, chemical
manufacturing, electronic, motor vehicle plating andfinishing, and foundries) discharge industrial
wastewater effluents into the tributaries in or
adjacent to Kaohsiung city, and the pollutants aretransported by river flow and finally accumulate
near the river mouth. Some pollutants may drift withsea current to be dispersed into open sea [6].
The Pearson correlation between the sedimentcharacteristics and Cr content was carried out. The
surface sediment Cr content is not obviously
correlated to OM content (p>0.05) and particle size(p>0.05). However, based on the 11 sites, except site
10, the significant correlation (r=0.920, p<0.01)
between Cr and organic matter content was found(Fig. 3). The results suggest that the sedimentorganic matter played an important role incontrolling the Cr distribution in sediments, whereas

300

site 10200

r = 0.920
p<0.01(n=11)

100

00.0

Fig. 3

2.0

4.0
6.0
Organic matter (%)

8.0

10.0

Correlation between the organic matter andCr content in the surface sediment ofsouthern Kaohsiung Harbor (except site
10).

Comparison with Sediment Quality Guidelines
Several numerical sediment quality guidelines
have been developed for assessing the contaminationlevels and the biological significance of chemical
pollutants recently [9,10]. One of the widely used
sediment toxicity screening guideline of the US
National Oceanic and Atmospheric Administration
provides two target values to estimate potential
biological effects: effects range low (ERL) andeffect range median (ERM) [10]. The guideline wasdeveloped by comparing various sediment toxicity
responses of marine organisms or communities withobserved metals concentrations in sediments. These
two values delineate three concentration ranges foreach particular chemical. When the concentration is
below the ERL, it indicates that the biological effectis rare. If concentration equals to or greater than the465

GEOMATE-Nagoya, Nov.13-15, 2013

ERL but below the ERM, it indicates that abiological effect would occur occasionally.
Concentrations at or above the ERM indicate that anegative biological effect would frequently occur.
Fig. 4 shows the measured concentrations of Cr in
comparison with the ERM and ERL values. Amongthe 12 sediment samples collected, the Cr is between
ERL (81 mg/kg) and ERM (370 mg/kg) in 2 samples.
This indicates that the sediment concentrations of Cr
found in sites 1 and 10 may cause adverse impact onaquatic lives. All other samples are below ERL for
Cr indicates that biological effects would rarely
occur.

all sampling stations, and EF values in the rivermouths of Jen-Gen River (site 10) and Salt River(sites 1-3) are greater than 1. This indicates that the
sediment Cr has enrichment phenomenon withrespect to the earth crust and that the Cr originatesfrom man-made sources. Sites 1–3 are classified asminor enrichment, site 10 is classified as moderateenrichment, and the other sites are classified as noenrichment, respectively. These results point out thatthe sediment near the mouth of rivers experiencesminor to moderate enrichment of Cr that originatesfrom the upstream sources of pollution. Additionally,
the average EF value of 4.5 obtained in site 10 (JenGen River mouth) is lower than the average EF
value of 8.4 reported earlier [11] indicating that the
upstream pollution has been reduced so that theaccumulation of pollutants in sediments is not as
serious as during earlier years. This observation may
show the effectiveness of intercepting the river flow
and dredging the river mouth.

400

ERM = 370 mg/kg

Cr (mg/kg)

300

200

100

Table 1 Enrichment factor of Cr for each station
studied at southern Kaohsiung Harbor
Site EF value
EF class
EF level
S1
1.4
2
minor
S2
1.1
2
minor
S3
1.1
2
minor
S4
0.4
1
no enrichment
S5
0.3
1
no enrichment
S6
0.3
1
no enrichment
S7
0.3
1
no enrichment
S8
0.3
1no enrichment
S9
0.9
1
no enrichment
S10
4.5
3
moderate
S11
0.5
1
no enrichment
S12
0.3
1
no enrichmenta1: EF <1 (no enrichment), 2: 1 < EF ≤ 3 (minor), 3:
3 < EF ≤ 5 (moderate), 4: 5 < EF ≤ 10 (moderately
severe), 5: 10 < EF ≤ 25 (severe), 6: 25 < EF ≤ 50(very severe), and 7: EF ≥50 (extremely severe) [13].

ERL = 81 mg/kg

0
S1 S2 S3 S4Fig. 4S5 S6 S7 S8 S9 S10 S11 S12
site

Distribution of chromium (Cr) contents inthe surface sediment of southern Kaohsiung
Harbor.

Enrichment Factor
The enrichment factor (EF) is a good tool fordifferentiating the man-made and natural sources ofmetal contamination [6,11]. This evaluating
technique is carried out by normalizing the metal
concentration based on geological characteristics of
sediment. Aluminum is a major metallic elementfound in the earth crust; its concentration issomewhat high in sediments and is not affected byman-made factors. Thus, Al has been widely used
for normalizing the metal concentration in sediments[6,11].
EFisdefinedas:EF=(X/Al) sediment /(X/Al) crust , where (X/Al) is the ratio of
Cr to Al. The average Cr and Al content in the earth
crust were 100 mg/kg and 8.23%, respectively,
which excerpted from the data published by Taylor(1964) [12]. When the EF of a metal is greater than
1, the metal in the sediment originates from manmade activities, and vice versa. The EF value can beclassified into 7 categories [13]: 1, no enrichment for
EF < 1; 2, minor for 1 < EF < 3; 3, moderate for 3 ≤EF < 5; 4, moderately severe for 5 ≤ EF < 10; 5,
severe for 10 ≤ EF < 25; 6, very severe for 25 ≤ EF
< 50; and 7, extremely severe for EF ≥50.
Table 1 show EF values of the sediment Cr
for 12 monitoring stations studied; the Crconcentration is consistent with the Cr EF value for

Geo-accumulation Index
Similar to metal enrichment factor, geoaccumulation (I geo ) index can be used as a referenceto estimate the extent of metal accumulation. The
I geo values for the metals studied were calculatedusing the Muller’s (1979) [14] expression: I geo =log 2 (C n /1.5B n ), where C n is the measured content
of element Cr, and B n is the background content of
Cr 100 mg/kg, in the average shale [6]. Factor 1.5 isthe background matrix correction factor due tolithogenic effects. The I geo value can be classified
into 7 classes: 0, none for I geo <0; 1, none to medium
for I geo = 0–1; 2, moderate for I geo = 1–2; 3,
moderately strong for I geo = 2–3; 4, strong for I geo =
3–4; 5, strong to very strong for I geo = 4–5; and 6,
466

GEOMATE-Nagoya, Nov.13-15, 2013

very strong for I geo >5. Based on the I geo data andMuller’s (1979) [14] geo-accumulation indexes, theaccumulation levels with respect to Cr at each site
are ranked in Table 2. Site 10 is classified as none tomedium accumulation, and all other sites areclassified as none accumulation.

Table 3 Potential ecological risk index of Cr foreach station studied at southern Kaohsiung
HarborSite
PI
PERI
Risk level
S1
0.9
1.8
low
S2
0.5
1.1
low
S3
0.6
1.1
low
S4
0.2
0.4
low
S5
0.1
0.3
low
S6
0.1
0.3
low
S7
0.2
0.4
low
S8
0.2
0.3
low
S9
0.5
0.9
low
S10
2.7
5.3
low
S11
0.3
0.5
low
S12
0.1
0.3
low
c
PERI < 40 indicates low risk, 40 ≤ PERI < 80 ismoderate risk, 80 ≤ PERI < 160 is higher risk, 160 ≤PERI < 320 is high risk, and PERI ≥ 320 is serious
risk [15].

Table 2 Geo-accumulation (I geo ) index of Cr foreach station studied at southern Kaohsiung
Harbor
Site I geo value I geo class
I geo level
S1
-0.7
0
none
S2
-1.5
0
none
S3
-1.4
0
none
S4
-2.9
0
none
S5
-3.4
0
none
S6
-3.5
0
none
S7
-3.1
0
none
S8
-3.3
0
none
S9
-1.7
0
none
S10
0.8
1
none to medium
S11
-2.5
0
none
S12
-3.4
0
none
b
0: I geo <0 (none), 1: I geo = 0–1 (none to medium),
2: I geo = 1–2 (moderate), 3: I geo = 2–3 (moderate tostrong), 4: I geo = 3–4 (strong), 5: I geo = 4–5 (strong
to very strong), and 6: I geo >5 (very strong) [14].

CONCLUSIONSThe surface sediment samples collected from thesouthern Kaohsiung Harbor contain 3.4–265.7
mg/kg with an average of 53.2±71.2 mg/kg. The
distribution of Cr in surface sediments reveals that
the Cr originates from the river upstream discharges
of industrial and domestic wastewaters; it istransported along the river and finally deposited andaccumulated near the river mouth. Results from the
EF and I geo analyses imply that the sediments
collected from the river mouth can be characterized
between minor and moderate degree enrichment andbetween none to medium accumulation of Cr,
respectively. Compared to the EF values reported
earlier [4], the degree of Cr enrichment at the JenGen river mouth has been obviously reduced. Baseon the comparison with SQGs, the concentrations of
Cr in the mouths of Jen-Gen River and Salt Riversediments may cause acute biological damage.
Results of PERI evaluation show that the Crcontained in surface sediment at southern Kaohsiung
Harbor has low potential ecological risks. The
results can provide regulatory valuable information
to be referenced for developing future strategies torenovate and manage river mouth and harbor.

Potential Ecological Risk
The potential ecological risk index (PERI) is
applied to evaluate the potential risk associated withthe accumulation of Cr in surface sediments. PERI
that was proposed by Hakanson (1980) [15] can beused to evaluate the potential risk of one metal or
combination of multiple metals. The PERI is definedas [15]: PERI = PI × T i , where PI (pollution index)= (C i /C f ); C i is the measure concentration of Cr in
sediment; C f is the background concentration of Cr;
T i is its corresponding coefficient, i.e. 2 for Cr [15].
In this study, the average Cr concentration in earth
crust of 100 mg/kg Taylor (1964) [11] was taken as
the Cr background concentration. The calculated
PERI values can be categorized into 5 classes ofpotential ecological risks [15]: low risk (PERI < 40),moderate risk (40 ≤ PERI < 80), higher risk (80 ≤PERI < 160), high risk (160 ≤ PERI < 320), andserious risk (PERI ≥ 320). Table 3 lists the PI value,
PERI value, and risk classification for the Crcontained in the surface sediment samples collectedin this study. All stations are classified as low risk
with respect to Cr pollution. The above evaluation
results indicate that the Cr contained in surface
sediments at the study area has low potential
ecological risks. However, the PERI value near theriver mouth of sites (sites 1–3 and 10) are higher
than other sites (Table 3).

REFERENCES[1] Callender E, “Heavy metals in theenvironmenthistorical trends”, Treatise on
Geochemistry, Holland HD, Turekian KK, Eds.
New York: Elsevier, 2003, pp. 67–105.
[2] Pertsemli E, Voutsa D, “Distribution of heavy
metals in Lakes Doirani and Kerkini, Northern467

GEOMATE-Nagoya, Nov.13-15, 2013

Greece”, J. Hazard. Mater., Vol. 148, 2007, pp.
529–537.
[3] Kotaś J, Stasicka Z, ” Chromium occurrence inthe environment and methods of its speciation”,
Environ. Pollut., Vol. 107, 2000, pp. 263–283.
[4] Pawlikowski M, Szalińska E, Wardas M,
Dominik J, “Chromium Originating fromTanneries in River Sediments: a Preliminary
Investigation from the Upper Dunajec River(Poland)”, Pol. J. Environ. Stud., Vol. 15, 2006,
pp. 885–894.
[5] Selvaraj K, Ram-Mohan V, Szefer P,“Evaluation of metal contamination in coastal
sediments of the Bay of Bengal, India:
geochemical and statistical approaches”, Mar.
Pollut. Bull., Vol. 49, 2004, pp. 174–185.
[6] Chen CF, Dong CD, Chen CW, “Evaluation of
sediment toxicity in Kaohsiung Harbor,
Taiwan”, Soil. Sediment. Contam., Vol. 22,
2013, pp. 301–314.
[7] Chen CW, Chen CF, Dong CD, “Distribution
and accumulation of mercury in sediments ofKaohsiung River Mouth, Taiwan”, APCBEE
Procedia, Vol. 1, 2012, pp. 153–158.
[8] Dong CD, Chen CF, Chen CW, “Evaluation of
mercury contamination in surface sediments ofsouthern Kaohsiung Harbor, Taiwan”, Adv.
Mater. Res., Vol. 716, 2013, pp. 459-464.
[9] Riba I, Casado-Martínez MC, Forja JM,
delValls TA, “Sediment quality in the Atlantic

coast of Spain”, Environ. Toxicol. Chem., Vol.
23, 2004, pp. 271–282.
[10] Long ER, Macdonald DD, Smith SL, Calder
FD, “Incidence of adverse biological effects
within ranges of chemical concentrations inmarine and estuarine sediments”, Environ.
Manage., Vol. 19, 1995, pp. 81–97.
[11] Chen CW, Kao CM, Chen CF, Dong CD,“Distribution and accumulation of heavy metals
in the sediments of Kaohsiung Harbor, Taiwan”,
Chemosphere, Vol. 66, 2007, pp. 1431–1440.
[12] Taylor SR, “Abundance of chemical elements inthe continental crust: a new table”, Geochem.
Cosmochim. Acta, Vol. 28, 1964, pp. 1273–
1285.
[13] Birth G, “A scheme for assessing humanimpacts on coastal aquatic environments using
sediments” In: Woodcoffe CD, Furness RA,
Eds. Coastal GIS 2003, Wollongong University
Papaers in Center for Maritime Policy, 14,
Australia. 2003.
[14] Müller G, “Die Schwermetallbelastung der sedimente des Neckars und seiner Nebenflusse:
EineBestandsaufnahme“, Chemiker Zeitung,Vol. 105, 1981, pp. 157–164.
[15] L. Hakanson, “An ecological risk index foraquatic pollution control.a sedimentologicalapproach”, Water Res., Vol. 14, 1980, pp. 975–
1001.

468

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

GPS/GIS IDENTIFICATION OF POTENTIAL BUS STOP LOCATIONSAND PASSENGER’S ACCESS AND EGRESS POINTS
Syahriah Bachok 1, Zakiah Ponrohono 1, Mariana Mohamed Osman 1 Zulfadly Azizi Bohari1
1

Kulliyah of Architecture and Environmental Design, International Islamic University Malaysia

ABSTRACTThis research reports the study of identification and determination of bus stop locations and passengers boarding
and alighting positions through the application of Global Positioning System (GPS) and Geographical
Information System (GIS) methods. Previously, the locations of bus stop were designed without muchconsideration to the access and egress points of prospective passengers and other users. Using the case study of
public bus operation in Kerian, Perak, a district in Malaysia, GPS method captured the locational points during
on-board surveys while the GIS method produced the points mapping. As a result, the possible bus stop locations
can be recorded and validated based on the passengers access and egrees points and volume patterns. This
research aims to analyse these empirical data to estimate the possible location of new bus stops within certain
distance ratios. From this findings, public bus operators and authorities can determine/allocate/distribute the bus
stop locations that may reduce the waiting time.
Keywords: GIS mapping, GPS points, Bus stop, passengers access, passengers egresswith Larut, Matang and Selama districts; and in thewest is the Strait of Malacca. The uniqueness of thiscase study is that the public transport routes plies
through the Kerian River which is the borderline ofthree states namely Penang, Kedah and Perak. Thereare eight (8) sub-districts under the administration of
Kerian District Council: Parit Buntar, Bagan Tiang,
Tanjung Piandang, Kuala Kurau, Bagan Serai,
Beriah, Gunong Semanggol and Selinsing [13 and
14].

INTRODUCTION
This paper deals with the application andimplementation of Geographic Information and
Global Positioning System in the identification anddetermination of bus stop locations and passengers
boarding and alighting positions. This research isfunded partially by the Government of Malaysia,
State of Perak. The case study has been selected to
be a district in Perak, a state still rapidly
experiencing economic and social growths, toachieve its development mission by 2015. District of
Kerian, Perak has a population of approximately
180,340 people, with a density of 7 people per km².

Kerian has a good road and highway network. The
network stretches approximately 225.0 km andconnects the eight sub-districts. The main northsouth road that cuts through this district is IpohButterworth road. Kerian District road is accessible
from Kampung Dew, Simpang Ampat, Changkat
Lobak and Kuala Kurau. The major town is Parit
Buntar that is located at the border of Penang and
Kedah. As the district has a large commercialized
agricultural area with ample buildings and facilities,
Kerian contributes to Perak’s economics growth andcapital generation, with a 5.7% GDP growth rate in2012 [13 and 14].
LITERATURE REVIEW
Transportation planning is an art and science ofarranging the transportation infrastructure andfacilities according to suitability and appropriatenessof the distribution basing on the population andsocio-demographic needs of the locality. It deals
largely with issues and problems encountered bytransportation services, operation, infrastructure andFigure 1: Kerian District
District of Kerian (Figure 1) is located in the State ofPerak Darul Ridzuan. In the north are Penang and
Kedah states. In the east and south, Kerian borders
469

GEOMATE-Nagoya, Nov.13-15, 2013

facilities, as highlighted by the contemporary
literature.

bus stop keep passengers away from the fear ofcrime [1]. There are various issues relating to thebus stop location provided in the current public
transportation services, [3] including that:I.
In certain areas, two bus stops maybe areclosely located resulting depletion of
resources.
II.
In other areas the bus stops are sparsely
sited forcing the people to walk far
distances or to take other modes oftransport to reach their destinations.
III.
Some bus stop locations are found to be
hazardous, posing danger to other vehicles
and may also cause traffic congestion.

Public transportation system includes all multiple
occupancy vehicles services designed to transport
people/customers on local and regional routes andtheir sub-systems. The systems include vans, buses,
taxis, or rails or other conveyance, privately or
publicly owned, providing their services to the
public general or segmented group of users.
Generally, the public transportation system in
Malaysia comprises bus, railway and taxi services
and plays a significant role in finding solutions to
the numerous challenges. Whether it is more jobs, acleaner environment, higher energy independence ora better quality of life, public transportation gets theright to be included [9, 10 and 11].

One method to locate the best location of bus stop is
by applying Geographic Information Systems (GIS).
GIS also offers a better solution in overcoming theabove issues. The use of GIS in determining andplanning the public transport facilities particularly
bus stop location is very common nowdays [2]. Thisapproach to locate the bus stop will help inmodelling preferred solutions to different forms ofspatial issues [3]. In short, the review of literature
has established the following problem statements:i.
There are inconsistent hierarchy,
operation systems and supply-demand gapsof bus services in Kerian District.
ii.
Bus stops locations and passengers’
pick-up and drop-off points in Kerian
District have not been clearly identified forpolicy making and implementation
purposes.

A more sustainable future can be promoted whenmore trips are made by public transport modes as it
will reduce the number of trips made by private
vehicles, leading to less congestion on the roads anda more efficient road system. Apart from that,
efficient public transportation services enhance
personal opportunities, save fuel, provide economic
opportunities, save money and reduces carbon
footprint [5]. It will contribute towards rapid
economic growth and healthy social development ofa city. However, there are a number of issues
relating to public transportation services such as thelimitation of facilities, the use of low quality of
public transport facilities and interchanges,
inconvenience of fleet, low passenger trips and longwaiting time [8].

RESEARCH QUESTIONS AND OBJECTIVESAll public transport demand will relate to what theoperators can offer to the passengers such as routefrequency,
availability
andaffordibility.
Additionally, the demand also depended on thefacilities and accessibility to the bus stop [1]. A bus
stop is the first point of contact between thepassengers and the bus services. The spacing,location, design, and operation of bus stops
significantly
influencethetransitsystemperformance and customer satisfaction. As a basic
necessity for public bus service, the design of bus
stop location should fulfill certain parameters suchas distance from origin/destination point to the bus
stop and the walking time, its physical conditions
should be ergonomic and weather proof [1].

Research questions arising from the above problem
statements are:i.
What are the hierarchy, operation
systems and supply-demand gaps of bus
services in Kerian District?
ii.
How best can bus stops locations andpassengers’ pick-up and drop-off points in
Kerian District be identified for policy
making and implementation purposes?
The objectives are:i.
To identify the existing of hierarchy,
operation systems and supply-demand gapsof bus provided in Kerian District.
ii.
To evaluate possibility of determining
bus stops locations and passengers’ pick-up
and drop-off points in Kerian District using
geographicalinformation
andgeopositioning systems.

The consideration of bus stops location is an
important aspect for operational purposes as thestrategic location of bus stop will ensure acomprehensive coverage and easy accessibility to all
categories of users [7]. Bus stops should also bevisible for users. Safety and easy access to theservicing buses are essential. Bus stops must fulfill
the criteria of comfort and convenience. Moreover,

In order to provide convenient bus services, some
performance indicators such as bus operation
characteristics were analysed to determine the470

GEOMATE-Nagoya, Nov.13-15, 2013

effectiveness of the bus service [8]. These
performance measurements are known as levels ofservices or LOS and the variables of measurement
are shown in the Table 1 and 2:

could affect the operating speed of the bus service.
Variation of speed may contribute towards the delayof travel time and schedule.
Stage Bus Service Characteristics and Regularity of
Bus Service

Table 1: Fixed-route Service Frequency LOS
Average
Comments
VehicleLOS Headway
per hour(min)
Passengers do not needA
<10
>6
schedules
Frequent service, passengers
B
10-14
5-6
consult schedules
Maximum desirable time to
C
15-20
3-4
wait if bus/train missed
Service unattractive to choice
D
21-30
2
ridersService available during the
E
31-60
1
hour
Service unattractive to allF>60<1
riders

A study of bus stop location for loading andunloading passengers is to measure the level of bus
service efficiency. It also important to determine theregularity of bus service and the actual acceptable
range of departure times so as to provide a better bus
service scheduling.
METHODOLOGY AND APPROACHES
The data for analysis was collected through a seriesof on-board surveys. For service frequency survey,
observation was done by locating enumerators onroad sides to record the number of buses and thefrequency of buses passing the observation points. .
Based on the service frequency survey, bus
performance indicators were computed including:i. time headway (minute),
ii. cycle time (minute),
iii. number of trips (trip/bus/day), andiv. travel distance (km/bus/day).

Table 2: Fixed-route Hour of Service LOS
Hours of Comments
LOS
service
Night ‘owl’ service provided
A
19-24
Late evening service provided
B
17-18
Early evening service provided
C
14-16
Daytime service provided
D
12-13
Peak hour service only or limited middayE
4-11
service
Very limited or no service
F
0-3

On-board Survey
The survey was conducted from 6 November 2012
to 10 November 2012 with target of 100
convenience sampling unit of on-board passengers
due to mobility and logistics reasons. During the onboard surveys for purposes to observe the bus routeenumerators have identified the name and the
distance between bus stops or others point of stops.
The enumerator assigned inside one particular bus
would record the number of passengers’ boarding or
alighting at or between stops, excluding him/herself
as a passenger. This task was conducted repeatedly
between the two terminals (start and end points) for
the operating duration of the bus services, but theenumerator did not necessarily ride the same bus
repeatedly. Since intercity buses have one door forpassengers to embark and disembark, therefore only
one enumerator was required to be located at thefront door of the bus. Another enumerator was
assigned to read and record the GPS of passengers’
access and egress points. The bus speed was also
recorded using the GPS apparatus that wassynchronized with the mobile satellite.

On the other hand, other parameters that can be used
to measure the efficiency of the bus services [5] aresuch as:Terminal, Bus Stop and the RouteTerminal or station is where the end/start of bus
route at which transit vehicle may arrive and depart.
It is the station for the vehicle to havelayover/recovery
time,
used
for
resting,administrative purposes and for maintaining proper
headways. The preliminary observation showed that
there was no layover/recovery time provided at bus
stations in Parit Buntar and Bagan Serai,. The bus
lay by areas were used for the passengers to embark
and alight only. A bus stop is the first point ofcontact between the passenger and the bus service.
The spacing, location, design, and operation of bus
stops significantly influence transit system
performance and customer satisfaction.
Travel Time and Schedule and Operating Speed in
Mixed Traffic

Plotting of GPS point Using GIS

It is important to study the travel time and scheduleof bus service in order to assess the level of
efficiency and satisfaction of the riders. Operating
speed is another variable that can measure the bus
service performance as the condition of mixed traffic

The use of GPS for the co-ordinates collection and
GIS for the spatial analysis will offer the following
advantages:
i. Graphical and attribute data input and editing
471

GEOMATE-Nagoya, Nov.13-15, 2013

ii. Use of spatially referenced data

upgraded. The buses also used the ring button
system that was located at the bottom of passengers’
seats. The system was not universally designed tocater for physical disability users. Bus conductors
and paper tickets were the operational systems
applied by Red Omnibus Sdn. Bhd, which was thesole intra-city bus service operator. The fare rate wascalculated based on the distance and interval time.

For this study the co-ordinates/GPS points ofpassenger’s access and egress were recorded throughthe on-board survey, where the points were plottedon the projected map using GIS.
DATA FINDINGSThe generalization of findings from this study is
subject to the data collected according to the specifictime and routes. Survey was conducted during theboth peak and off-peak of public transport services.

Terminal and Bus Stop
Kerian District has two bus stations: Hentian Raya
Parit Buntar and Hentian Raya Bagan Serai. The
station design was a sheltered ground floor building
with the waiting seats at each route’s bus bay. Bothof the bus station buildings were of two levels withthe upper level providing the public toilets andprayer room facilities. The ground level has theticket counters placed facing the bus bays. The
location of bus station was in the middle of town
center and it was easy to access with ample size ofroad width for buses to reverse or manouver. Bus
stations’ main entrance were diverted from the mainroad of the town centre and managed to avoid thetraffic flow conflicts at the main access point.
However, there was no specific bus layoverprovided in Kerian bus stations.

Travel Time, Schedule, Fare and Regularity of
Bus Service for Inter-city and Intra-city
Bus services in Kerian district offered both intra-cityand inter-city services that can be accessed by thecase study population. The inter-city bus services to
Kuala Lumpur, Johor, Singapore, and Pulau Pinang
were offered by the express bus operators. The intracity bus routes were within the Kerian district andthe concentration of service was within residential in
Kuala Kurau, Tanjung Piandang and Kuala Kurau(Table 3) [4]. However, there was only one bus
under one operator to cover each intra-city route. As
such, the frequency of bus was low, i.e. one service
per up to 45 - 70 minutes. Previously there wasadditional route to Selama but the route has been
discontinued recently. The minimum bus fare was
RM1.00 and the maximum bus fare was RM5.20.

The bus stops were provided along the Kerian mainroad with no specific standard design. Each of thebus stop were of different types of shelter and size.
Some of the bus stops were not equipped withseating facilities and there was no loading andunloading kerb for passengers. Most of the bus stops
were not provided with proper lighting or public
phones. Additionally, from the secondary sourcesand observation conducted, the buses services were
only till 7.00pm and most passengers embarked anddisembarked at door-to-door points along the mainroad of the routes.

Table 3: Intra-city Bus route and frequency
Route Number and
Route

No.
Frequency
of
(min)
buses
Bus services at Parit Buntar station
A
Parit
Buntar1
70
Taiping
B
Parit
Buntar1
45
Kuala
Kurau
C
Parit
Buntar1
45
Tanjung
Piandang
Bus services at Bagan Serai station
A
Bagan
Serai1
70
Tanjung
Piandang
B
Bagan
Serai1
70
Kuala
Kurau

Distance(km)

Travel
time
(min)

98

60

16

30

Bus Route, Bus Stop Locations and Passengers’
Access and Egress Points

13

30

36

60

44

60

Three major bus service routes (Figures 2, 3 and 4)
provided by the Red Omnibus Sdn. Bhd wereselected as the case study. The data recorded waspresented in the GIS route map with attached theattributes of GPS data table. There were fivepossible points along route 3 to be proposed as bus
stop locations. Along route 5, there were 7 points
identified as potential locations for future bus stops.
For route 8, there were 15 points of possible bus stop
locations, determined using the number ofpassengers accessing and egressing.

Existing Bus Condition and Ticketing System
Observation on the existing bus condition showedthat buses were not equipped with air conditioning
system and some of the bused needed to be
472

GEOMATE-Nagoya, Nov.13-15, 2013

SUMMARY OF FINDINGS
Overall findings showed that the Kerian Districtneeded better bus services operations. The
dependency on the future demand of public
transportation service in the district was still highwith 68% of respondents expressing their
willingness to use public bus at least 3 days per
week. It is recommended that the local authority andstate government to provide an allocation to upgradeand enhance the public transport service and its
facilities to sustain the mobility of Kerian District’s
people in economic and other daily activities. Levelof Service (LOS) of public transport service analysis
was very important in determining the efficiency andthe quality of current service provided. The LOS is afactor that influences the future demand on public
transport services. Table 4 shows the LOS matrix.

Figure 2: Route 3 Bagan Serai – Kuala Kurau
Passengers’ Drop Off Points Map.

Table 4: Matrix of LOS for Public Transport
Services in Kerian

R8

Station 1

Station 2

Station Bagan
Serai

Station Parit
BuntarFixed-route Service
Frequency LOS
Fixed-route Hour ofService LOSLOS Scheme fortransit speed
Passengers Loading
LOS Thresholds(Off-peak)Service Frequency
LOS Thresholds(Off-peak)

Train
Service

A

A

C

-

-

D

D

D

D

C

-

-

A

A

D

E

E

-

-

-

-

A

A

C

A

A

-

-

E

E

E

A

A

-

-

Criteria

Figure 3: Route 5 Parit Buntar-Tanjung Piandang
Passengers’ Drop Off Points Map.

Taxi
Service

R5

Bus Service

R3

Mark

Source: Kerian Bus Services Surveys, November 2012.

DISCUSSION AND CONCLUSION
The points where high number of passengers were
dropped off can represent the possible suitablelocations to designate a bus stop. However, there
were some issues arising during the stage of plotting
the GPS points into GIS maps. Some maps showederrors in alignment of their north points. This may
be due to the GPS readings being recorded on
moving buses and determination of points was
influenced by the satellite connectivity in cloudy
areas. The level of accuracy of the GPS points were
accepted, with 90% from the points recorded being
able to be plotted into the maps. Those errors in GPS
points were eliminated to avoid inconsistency andcan be represented using the nearby points where theeast points were referred. Even though the GPS
points were accepted, there was a 5% to 10%
inaccuracy of actual points on the ground. As a

Figure 4: Route 8 Parit Buntar-Taiping Passengers’
Drop Off Points Map.

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GEOMATE-Nagoya, Nov.13-15, 2013

result, a mapped GPS points in GIS application canmodel the overview of bus routes and passengers’
access and egress points for the purpose ofdetermining possible areas to locate bus stop
facilities.

Study, Journal of Public Transportation, Vol.
12, No. 2.

[4] Laporan Penemuan Rancangan Tempatan
Kawasan Pentadbiran Majlis Bandaraya
Kerian,2020[5] Madzlan Napiah, Amirah Suriati Ahmad Farid
and Suwardo, 2010, Trip Productivity
Evaluation Of Bus Service: Medan Kidd Bus
Station, MUTRFC 2010.
[6] Noorfakhriah Yaakub and Madzlan Napiah,
2001, Quality of Service and Passenger’s
Perception – A review on Bus Service in Kota
Bharu, International Journal of Civil &Environmental Engineering IJCE-IJENS Vol:
11 No: 05, p. 1-9.
[7] Olowosegun Adebola and Okoko Enosko, 2012,
Analysis of Bus-stops locations using
Geographic Information System in Ibadan
North L.G.A Nigeria, Industrial Engineering
Letters, ISSN 2224-6096 (print) ISSN 22250581 (online), Vol 2, No.3, 2012, www.iiste.org[8] Suwardo, M. Napiah and I. Kamaruddin,
2007(a), “Bus Operation Characteristics andPerformance Indicators as a Preliminary Studyin Promoting Public Transport: A Case Study
based on the Kerian-Lumut Corridor in Perak”,
Prosiding Kebangsaan Awam ’07, Pusat
Pengajian Kejuruteraan Awam, USM.
[9] Suwardo, M. Napiah and I. Kamaruddin 2008(b), Review on Motorization and Use of Public
Transport in Perak Malaysia: Realities andChallenges, 2nd International Conference on
Built Environment in Developing Countries(ICBEDC 2008).
[10] Suwardo, Madzlan B. Napiah, and Ibrahim B.
Kamaruddin, 2008(c), Punctuality and Expected
Waiting Time of Stage Buses in Mixed Traffic,
Jurnal Transportasi Vol.8 Edisi Khusus no.3
Oktober 2008: 213-226.
[11] Suwardo, Madzlan B. Napiah, and Ibrahim B.
Kamaruddin, 2009 (d), On-Time Performanceand Service Regularity of Stage Buses in Mixed
Traffic, International Journal of Business,
Economics, Finance and Management Sciences
1:3 2009[12] (http://mdkerian.gov.my/web/guest/latar).
[13] (http://mdkerian.gov.my/web/guest/latar).
[14] http://www.spad.gov.my

In general, the overall bus service in Kerian has
many areas to be improved based on the passengers’
perception of overall bus service, trip frequency, bus
condition, bus punctuality, bus efficiency andeffectiveness. Based on the responses obtained fromthe survey, it can be concluded that:i.

ii.

Route 3 from the station to Kuala Kurau
respondents needed more frequent bus trips
with at least 30 minutes interval for waitingtime. 13 respondents had chosen the 30
minutes interval, 4 respondents preferredthe 20 minutes interval and 19 respondents
selected the 15 minutes interval.
All respondents of the three routes
agreed to pay higher fares if services were
upgraded with comfortable bus interiors
with air conditioning system.

ACKNOWLEDGEMENTS
This research was funded by Institute Darul Ridzuan(IDR) http://www.idrperak.com . The authors wish
to thank IDR for funding this research.

REFERENCES[1] Giuseppe SALVO and Simona SABATINI,
ND, A Gis Approach To Evaluate Bus Stop
Accessibility.
Retrieved
at http://www.iasi.cnr.it/ewgt/16conference/ID1
08.pdf on 10/5/2013 at 11.45am.
[2] John C. Sutton, 2005, GIS Applications inTransit Planning and Operations: A Review ofCurrent Practice, Effective Applications andChallenges in the USA, Transportation Planning
and Technology, August 2005, Vol. 28, No. 4,
pp. 237_/250, ISSN 0308-1060 print: ISSN
1029-0354
Taylor&Francis
DOI:
10.1080/03081060500247655[3] Khaled Hazaymeh, 2009, GIS-Based Safety Bus
Stops— Serdang and Seri Kembangan Case

474

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

GEOCHEMISTRY OF PALEOGENE RED BEDS IN THE NORTHERNIRAQ FORELAND BASIN: EVIDENCE FOR PROVENANCE
Muatasam Hassan,1,2* Brian G. Jones,1 Ali Ismail Al Jubory,2 Sabah Ahmed Ismail,3Abdual Salalm Mehdi Saleh4
1School of Earth and Environmental Science, University of Wollongong, Australia; 2College of Science, Mosul
University, Iraq; 3School of Earth Science, University of Kirkuk, Iraq; 4School of Earth science, University of
Tikrit, Iraq
ABSTRACTThe Paleogene Red Bed deposits in northern Iraq crop out as a narrow northwest-southeast trending belt
within the thrust zone in an active foreland basin developed adjacent to the Zagraos orogenic belt. The Red Beds
are divided vertically into four units. The lower part (unit 1) is mainly composed of red mudstone and siltstone.
The middle part (unit 2) is mainly composed of sandstone with thin interbeds of red siltstone. The upper part iscomposed of conglomerate (unit 3) covered by 100-120 m of red mudstone, siltstone and sandstone (unit 4).
The geochemical stratigraphy shows an increase in transition elements and REEs while LILE and HFSE
elements decrease in the lower part of the sequence. These features indicate that a mafic source supplied detritus
during the deposition of the lower Red Beds and decreased in importance during the deposition of the middle
and upper parts as a result of erosion or tectonic activity.
Keywords: Red Beds, Mafic Source, Iraq, Zagros Orogenic Belt
strength elements (HFSE) in the lower parts of the
Red Beds and depletion of HFSE upward towards
the middle and upper parts. This pattern probably
reflects regressive erosion of the mafic components
upwards through the section with the effect of aminor felsic source in the middle and upper parts of
the Red Bed sequence.
Laterally, the Mawat-Chwarta area section has
been more affected by mafic and ultramafic sources
than Qandel area section (Suwais).

INTRODUCTION
The geochemical composition of rocks is
generally a useful tool to determine the chemical
characteristics of the the source area [1] and draw
tectonic conclusions [2]. The diagenesis, nature of
the source rock and the weathering of the sourcearea can also be deduced from the geochemicalcomposition of clastic rocks [3], [4], [5], [6].
One section was selected from the Mawat area
(Sorakalat section) in the south-eastern part of thebasin and one section was selected from Qandelarea (Suwais section) on the northwest side of thebasin (Fig. 1). Rare earth element studies are very
useful because their distribution is stable in various
rocks and minerals under different conditions, suchas weathering, transportation and metamorphism.
Rare earth elements were normalized tochondrite, average shale and upper continental crustand plotted on spider diagrams and showed that thelower parts of the sequence in the Mawat area isenriched in HREEs in comparison to the middle
and upper parts of the Red Beds which have less
HREEs. Trace elements were normalized to Upper
Continental Crust [7] and plotted on spider
diagrams and also plotted versus stratigraphic
height to assess their vertical distribution.
The REE patterns indicate the lower part
derived from a mafic source with minor
contributions from a felsic source. This is distinctly
different from the middle and upper parts of thesequence. Trace element diagrams show aconcentration of transition elements and high field

Fig. 1. Location map of the study area (Qandel and
Mawat-Chwarta areas.
GEOLOGICAL SETTINGThe Zagros Mountains of northern Iraq are
geologically part of the extensive Alpine mountainbelt. They form a narrow strip along the border
between Iraq and Iran and include two main zones:
the Zagros Simply Folded Belt in the southwest andthe Zagros Suture Zone in the northeast. Thesezones are included in the Zagros Orogen. A

475

carbonate beds are confined to the lower part of theunit. In most places the lower contact of the Red
Beds with the Tanjero Formation is conformable, as
occurs in the Mawat-Chwarta area (Fig. 3). This
contact is sharp in some areas and a transition inothers [12]. An angular unconformity was also
recorded in the study area close to the Suwais
sections (Fig. 3). The variety of detrital components
in the stratigraphic column through the Red Beds
reflects the unroofing history of the thrust sheetsthat provided the components to the Red Bed basin.

foreland basin occurs southwest of the Zagros
Mountains. The tectonic development of the Zagros
Mountains indicates that the foreland basin was
initiated in the Late Cretaceous during ophiolite
obduction along the Zagros Suture Zone followedby continental collision of the Arabian plate withEurasia in the Cenozoic [8], [9]. Late Cretaceousand Paleogene foreland basin deposits have been
folded and are therefore now part of the Zagros
Simply Folded Zone. In northeast Iraq, the former
Zagros foreland basin included Cretaceous shallowmarine deposits of the Shiranish and Tanjero
Formations overlain by continental deposits of the
Paleogene Red Beds (Fig. 2). The Paleogene
sedimentary rocks in the foreland basin record
sedimentation developed during the Alpine
orogeny. The Red Beds are structurally overlain bythrust sheets that are part of the Zagros Suture
Zone. In the Mawat-Chwarta area the Red Beds are
structurally overlain by the volcanic rocks of the
Naopurdan Group [10] whereas the contact with theunderlying Tanjero Formation is gradational as
confirmed by the current study.
Tanjero Formation (Maastrichtian)
The Tanjero Formation is another rock unit of
the Late Cretaceous succession in the study area. It
is widespread in the Kurdistan region of northern
Iraq [11] (Fig. 3). The formation is over 2010 m
thick. The upper part of the Tanjero Formation
contains
foraminifera
consistent
withaMaastrichtian age for the unit. The lower part of thesuccession is composed of 480 m of globigerinal
marl and rare siltstone. Its upper part consists of1530 m of mixed siliciclastic and carbonate
sedimentary rocks including silty marl, siltstone,sandstone, conglomerate, and organic detrital
limestone. An interfingering interval ~45 m thickwith gradational contacts between the Tanjero andAqra Formations occurs in the Mawat-Chwarta area
(Sorakalat section). It is composed of sandy detrital
limestone, which progressively changes upwards toa calcareous sandstone, rich in shell debris. The
boundary between the Tanjero Formation and theoverlying Red Beds in the Mawat-Chwarta area islocally marked by Quaternary sediments.
Furthermore, such a boundary is also recognized in
nearby Sorakalat village, where fossiliferous
limestone beds are recognized within the lowermost
part of the Red Beds.

Fig. 2. Regional geological map of northern Iraq
(Kurdistan area) and northwestern Iran showing
locations of the study areas and Late Cretaceous
formations and thrust sheets [13].

Red Beds (Paleocene-Eocene)
Fig. 3. The stratigraphic relationships of the Late
Cretaceous-Paleogene rocks from the Suwais
section (Qandel area) and Basina-Chwarta area
within the former foreland basin [13].

The Red Beds are composed of mudstone, sandstone and conglomerate. Clastic sedimentary rocks
are distributed throughout the succession while476

Geochemical studies show that a diversity ofsource rocks supplied detritus to the Red Beds,
reflecting uplift of older rocks coupled withintensive orogenic movements during Red Bed
deposition. The Red Beds are divided on the basisof provenance into two parts. A lower unit isdominated by radiolarian chert detritus with aminor component of ophiolitic detritus. An upper
unit lacks radiolarian chert and ophiolitic detritus
and has a mixed provenance of volcanic,
metamorphic and sedimentary rocks.
SAMPLING AND METHODS
Fig. 4. Plots of REEs from average shale [16],upper continental crust [12] and the selected
samples from the Suwais section normalized tochondrite values [17].

The current study used conventional geologicalmethods including geological surveys in the field;
X-ray fluorescence (XRF) and inductively coupledplasma-mass spectrometer (ICP-MS) analysis.
Fifty five samples from the Suwais andSorakalat sections were analysed by XRF for traceelements in the School of Earth and Environmental
Sciences at the University of Wollongong. Twenty
four samples were analysed using ICP-MS in
Brisbane for REEs from two sections (Suwais andSorakalat, Tables 1-2).
RESULTS AND DISCUSSION
Rare Earth Elements (REEs)
Rare earth elements (Tables 1-2) provide very
important evidence for determining sedimentarysource rocks because they are stable in different
rocks and minerals and are not modified duringmetamorphism [14].
Fig. 4 shows the different patterns for the
average shale [16] and upper continental crust [12]normalized to chondrite [17]. The figure showsenrichment in the LREE in the upper continental
crust as a result of the LREEs fractionating into theliquids generated during magma formation andintrusion into the upper crust. For this reason thecomposition of REEs in the MORB and upper
continental crust is different. The enrichments of La
to Sm are similar in the Qandel and Mawat areas
but with some increase in La in the Mawat area.
All the samples were plotted on spider diagrams
after being normalized to chondrite [4] (Figs 4-5).
Generally there is a similarity pattern of thegeochemical signatures between all the samples inthecurrent
study.
These
patterns
arestratigraphically characterized by non-uniformity of
REE distributions showing relative enrichment of
LREEs with little flat pattern or depletion of
HREEs. The LREEs increase in abundance towards
the middle and upper parts of the Red Beds in

Fig. 5. Plots of REEs from selected samples in the
Sorakalat section normalized to chondrite values[17].
Table 1. Average REE results for Suwais section.

Units
Unit1
Unit2
Eu
0.4
0.6

La
4.9
7.7
Gd
1.5
2.4

Ce
8.2
16
Tb
0.3
0.4

LREEs
Pr Nd Sm GdYb LaSm
1 4.4 1.1
3.5
4.5
2 8.2 2.1
2.4
3.1
HREEs
Dy Ho Er Tm Yb Lu
1.5 0.3 1.0 0.1 1.0 0.1
2.6 0.6 1.8 0.2 2.1 0.3

Table 2. Average REE results for Sorakalat section.

Units
Unit1
Unit2
Eu
0.4
0.7

477

La
8.6
14
Gd
1.7
2.0

Ce
16
27
Tb
0.3
0.5

LREEs
Pr Nd Sm GdYb LaSm
1.8 6.9 1.5
1.8
5.8
3.2 13 2.8
1.8
5.3
HREEs
Dy Ho Er Tm Yb Lu
1.6 0.3 0.9 0.1 0.9 0.1
2.6 0.5 1.5 0.2 1.6 0.2

comparison to the lower parts. The increase of
LREEs in the lower mudstone-dominated facies
probably results from their adsorption onto clays,
which coincides with findings in the eastern desertof Egypt [15].
The Gd/Yb ratio ranges from 1.06-3.2 in thelower and middle parts decreasing to 0.6-0.8 in theupper part. The pattern of the samples is orderedfrom bottom to top of the sections. In Figs 4-5 thepattern of the elements in all sections was similar
but there are differences between samples from thelower, middle and upper parts. Samples from units
one and two reflect high ratios of HREEs whilesamples from units three and four have lower
HREE ratios. The chondrite normalized samples
also show positive anomalies represented by Eb, Er
and Gd with negative anomalies represented by
Tm, Eu and Ce. In sandstone samples the Ce
content from the lower, middle and upper parts isvery high ranging from 32-118 ppm.
The patterns in the middle and upper parts are
similar to each other with similar HREE patterns
and a little enrichment by LREEs in the upper part
relative to the middle part. Although the middle andupper parts were at least partly derived from felsicor different thrust source rocks, the patterns forthese parts are slightly less than 1; therefore, amafic source has still affected these parts as well. In
contrast, patterns from the lower part of the Red
Beds are well below 1 which indicates that a main
mafic and ultramafic source has affected this part.
Also the depletion of LREEs within this lower part
indicates that the source area for this part wasdifferent from the middle and upper parts and it was
not derived from the upper crust. The REE patterns
in the current research are similar to the clayeysiliceous rocks (normalised to shale) from the
Bazhenov Formation in Russia [18]. They also
stated that the Ce distribution was not affected byearly diagenesis and variable redox conditions
which is similar to the Red Beds. The enrichmentof LREEs in some samples from the lower andmiddle parts does not necessarily mean that thesesamples were affected by the felsic source becauseof two reasons.

Table 3. Average concentrations of transition
elements in the Suwais section of the Red Beds.
Units
Unit1
Unit2

V
56
63

Co
26
24

Ni
26
23

Cr
237
172

Cu
484
459

Ce
26
32

Table 4. Average concentrations of transition
elements in the Sorakalat section of the Red Beds.
Units
Unit1
Unit2

V
98
64

Co
40
64

Ni
39
71

Cr
399
22

Cu
711
38

Ce
29
40

ultramafic rocks and they are more common inpelitic rocks than in shale and the NASC [6]; [20];[21].
V in the Red Beds includes high values reaching
up to 208 ppm in some parts of the Red Beds,
especially within the Kalacholan-Mawat section(Table 3). This element occurs in the structure ofpyroxene, amphibole, biotite and the oxides that
contain titanium [22]. Therefore, V has high values
in some samples that are probably rich in pyroxene.
Cr occurs in igneous rocks in spinel minerals, suchas chromites, and it also occurs in ferromagnesianminerals, such as pyroxene and olivine [23]. In
ultramafic igneous rocks Cr content is more than2000 ppm, in basalt it ranges between 150-200
ppm; it reduces to 25-80 ppm in intermediate rocks
while it decreases to less than 20 ppm in granitic
rocks. During weathering of the source rocks the
behaviour of Cr+3, which occurs in the silicate
minerals, is geochemically similar to Fe+3 and Al+3,
therefore, it occurs in the clay minerals. During
more intense oxidation conditions Cr+3 is probably
oxidised to Cr+6 to form CrO42- that may bedeposited in chromate minerals such as CaCrO4 and
PbCrO4. The Cr that occurs in chromite and spinel
is generally resistant to geochemical weathering;
therefore, it is transported from the source area tothe sedimentary environments in the resistantminerals which strongly reflect the Red Beds.
The increase of Co and decrease of othertransition elements may not reflect a mafic rockorigin but could reflect sedimentary sorting
processes [21]. This has happened in the Red Beds
in the Mawat-Chwarta area in the upper part (unit2) of the Sorakalat section (Table 4). There is anegative relationship between Co/Ni versus Cr in
several samples from the upper part of unit two in
the Sorakalat and Suwais sections (Tables 3 and 4)
while generally there is similarity in the Co/Ni in
the other samples although strong variability occurs
in Cr contents in unit one. This probably indicatesthat the Cr in the Red Beds occurs mainly in detrital
chromite mineral grains. Chromite was not

Transition trace elements (TTE)This group, also called ferromagnesian traceelements, is composed of V, Co, Ni, Cr and Cu
which show convergent behaviour during theevolutionary processes of volcanic rocks and they
decrease with increasing silica content. Theseelements are very important for determining
provenance and tectonic setting [19]. It is wellknown that these elements concentrate in mafic and478

field of post-Archean crust reflecting derivationfrom granite and gneiss in the Baster craton [25].

uniformly distributed in the source rocks but wasconcentrated in pockets and, therefore, the amountof chromite derived from this source depends on
the surface area of chromite bodies that were
exposed to weathering.
The ratio of Co/Ni in the Red Beds is notaffected by the previous factors because theseelements occur in the silicate minerals and theirabundance is related to weathering products such as
illite-smectite and montmorillonite that arecommon in the Red Beds. The small variation in
the Co/Ni ratio in the lower part of the Red Beds
indicates little variation in the nature of the source
rocks during their sedimentation. The stronger
variation of this ratio in the upper parts of the Red
Beds reflects contribution from another source
whereas there is little variability in the Cr content inthis part of the sequence relative to the lower parts.
When the Co/Ni ratios and Zr contents werecompared to data from other rocks from northern
Iraq and elsewhere it was shown that most of thelower Red Bed samples were close to values fromdunite, harzburgite, lherzolite and basalt while mostof the middle Red Bed samples plus sample S20
from the lower part are similar to the upper
continental crust analyses (Table 3). Recently
analysed Cr-spinels from serpentines in northern
Iraq showed that much of the matrix of theserpentines was derived from harezburgite andlherzolite of forearc affinity [24].
The amount of Ni in the Red Beds increases in
the upper parts within the conglomerate facies,
which probably reflects a contribution of felsic
components. It should be mentioned that the Cr and
Ni in the Red Beds have low concentrations in the
Merga and Kanarroy sections which probably
reflects less exposure to an ultramafic source during
the deposition of these sections or because a
different river channel supplied these deposits tothe basin. The Cr contents in the Taconian orogenfrom North America reached 3950 ppm [1]. If Cr
and Ni > 100 ppm and they show a high correlation
they probably indicate derivation from ultramafic
components in the source area [3]. A Cr/Ni ratio of
2 or more indicates a mafic source and, therefore,
since most Cr and Ni values from the lower part of
the Red Beds plotted within this range they would
have come from a mafic source while the middle(sandstone) and upper part (conglomerate) of thesequence were under this range and would have had
a less mafic source. These results exactly coincidewith findings from the Bastar craton [21].
Pelite samples tend to be enriched with Cr andNi [21] but contents are slightly lower than theactual mafic volcanic rock samples from the Bastercraton [22]. In contrast, their coarser grained
samples of sandstone and quartzite plotted in the

CONCLUSIONS
Generally, the trace and REEs indicated that the
sediments in the Red Beds were affected by a major
ultramafic to mafic source, especially in the
mudstone facies from the lower part, and thegeochemical data were compatible with a mixed tomafic impact especially within the coarse-grained
sediments in the middle and upper parts. The dataalso indicated that the Red Beds were affected by amoderate degree of weathering and a lack ofrecycled sediments. Rare earth elements werenormalized to chondrite, average shale, upper
continual crust and mid oceanic ridge values. The
diagrams of chondrite normallised values generally
show enrichment in LREEs with negative Eu
anomalies and the lower part of the Red Beds ismainly enriched with HREEs ascribed to mafic andultramafic source rocks contrary to the middle andupper parts which have less HREES and were
probably affected by a felsic source.
The concentration of transition elements thelower parts and depletion in the upper parts reflectregressive erosion of the mafic components
upwards through the section with little effect from a
felsic source. Spider diagrams reflect the mainderivation of mafic sediment in lower parts of the
Red Beds with a minor felsic contribution fed into
the middle and upper parts.
According to their geochemical signatures the
Red Bed sediments were deposited in a range of
sedimentary environments and derived from asource area with varied source rocks. The
provenance of the Red Beds can be inferred fromthe geochemical evidence to be predominantly
mafic as shown by the REEs and transition
elements.
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480

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DEVELOPMENT OF BASE MATERIALS FOR SEAWEED BEDS
USING VOLCANIC ASHES AND RECYCLING MATERIALSOF INDUSTRIAL WASTESK. Yamamoto1, T. Negami2, T. Nakajima1, H. Yano3, Y. Futsuhara3 and K. Shima3
1
Kagoshima University, 2Saga University and 3Infratec Company, Japan

ABSTRACTThe frequency of eruptions at Mt. Sakurajima in Kagoshima peaked in 2011, the highest since observations
began in 1955. Large amounts of volcanic ashes from Mt. Sakurajima were falling in the surrounding areas. The
total volcanic ashes have been observed to be over 6.1 million tons in 2012. Most of the volcanic products havebeen disposed as industrial wastes, but the supply of these volcanic products is anticipated to be unending for theforeseeable future. On the other hand, the area of Japanese seaweed beds has decreased by around 40% in thelast 40 years. Seaweed beds play a very important role in the ecosystem of the coastal area. The purpose of thisstudy is to develop maintenance-free base materials for seaweed beds artificially using volcanic ashes andrecycled materials of industrial wastes.
Keywords: Volcanic ashes, Recycled materials, Seaweed beds, Solidification, Low-environmental load

fixation and environmental restoration produced by
the base materials for seaweed beds in this study. As
shown in this figure, seaweed beds are an importantpart of the marine food system through thephotosynthetic activities, absorbing carbon dioxideand discharging oxygen. Furthermore, seaweed beds
play a virtual role in the ecology of the aquatic
ecosystems, serving as buffers of seawater quality.

INTRODUCTION
An active volcano, Mt. Sakurajima is located in
Kagoshima, Japan. Due to the cyclic nature ofmagma, a number of eruptions have recently been
activated. A large amount of volcanic ashes are
already supplied in the Kagoshima area and aconstant supply of these ashes is anticipated fromnow on.
Seaweed beds are communities consisting oflarge benthic plants (seaweed/seagrass) and they
form rich underwater forests. These forests play animportant role in the ecosystem of the coastal area,
serving as nursery grounds for fish and shellfish,
including egg-laying sites and feeding grounds [1]–[3]. But they have been remarkably reduced in Japan.
Not only coastal engineering works such asreclamation and dredging but also the phenomenon
known as barren ground (called “isoyake” in
Japnaese) has led to the deterioration of coastal
environments. It is also important to consider that astable supply of iron indispensable for seaweed
growth is lacking under the sea due to the change in
the nutritional composition of the sea caused bydeforestation and the development of dams in theland.
This study develops the base materials forseaweed beds using volcanic ashes and recycledmaterials of industrial wastes for the maintenance of
natural environments. The mixture of industrial
wastes is recycled gypsum, scrapped ceramics, ironpowder, cement and so on. The main solidificationmaterial is recycled gypsum and the use of cement isadditional. Figure 1 shows the image of carbon

PHYSICO-CHEMICALVOLCANIC ASHESPROPERTIESOF

The volcanic ashes of Mt. Sakurajima were
sampled in Kagoshima city. The following
fundamental properties were obtained from the soil
test [4]–[5]; soil particle density ρ s =2.708 g/m3;
coefficient of permeability k=2.0×10-4 cm/s; andpH=7.91 (weak alkaline). Figure 2 shows the grain
size distribution curve. This figure shows that thepercent finer by weight is over 40% when the grain
size is less than 0.1 mm.
Next, the compaction curve is shown in Fig. 3.
The compaction test was conducted using the A-b
method [6], where the compaction energy is low andthe sample is not repeatedly used. The optimum
water content and the maximum dry density are
15.1% and 1.62 g/cm3, respectively. Thus, it is foundthat the volcanic ashes are good materials suitablefor compaction.
RESULTS OF TEST PIECES
The unconfined compression test was carried out

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GEOMATE-Nagoya, Nov.13-15, 2013

Photosynthesis
CO2

Food and
Bioethanol

CO2

Increase offishery products

Seaweed (better habitat)

Provide mineralssuch as iron

Environmental
enhancement ofcoastal fishery

Seawater purificationand prevention of soil
deterioration

Placement ofbase materials
for seaweed beds

Fig. 1 Image of carbon fixation and environmental restoration produced by base materials for seaweed beds.

ρ d max = 1.62 g / cm3
wopt = 15.1%

Fig. 3 Compaction curve.

Fig. 2 Grain size distribution curve.

0.8

Unconfined compressive strength (MPa)0.80

Gypsum 30%, w/G=2.0, Cement 5%, 7days
Gypsum 30%, w/G=2.0, Cement 5%, 28days
Gypsum 30%, w/G=2.5, Cement 5%, SC 30%, 7days
Gypsum 30%, w/G=2.5, Cement 5%, SC 30%, 28days

Compressive stress (MPa)

0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0.0

0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0

1.0

2.0
3.0
Axial strain (%)

4.0

5.0

Fig.4 Stress-strain curve (7 and 28 days curing).
ample of compressive stress – axial strain curves
482

Gypsum 30%, w/G=2.0, Cement 5%
Gypsum 30%, w/G=2.5, Cement 5%, SC 30%
Gypsum 30%, w/G=2.5, Cement 5%
Gypsum 30%, w/G=2.0
Gypsum 30%, w/G=3.0, Cement 5%, SC 50%

10

15
20
Curing time (days)

25

Fig. 5 Relationship between unconfinedcompressive strength and curing time.

GEOMATE-Nagoya, Nov.13-15, 2013in our laboratory to obtain the unconfinedcompressive strength of test pieces. Figure 4 shows
an example of compressive stress – axial strain
curves after 7 and 28 days curing. In the graphlegend, the mixture ratio is the weight ratio for theabsolute dry condition of volcanic ashes. Note thatw/G and SC mean water-gypsum ratio and scrapped
ceramics, respectively. The volumes of gypsum andcement are 30% and 5%, respectively in this paper.
For the mixing of the cement, water is added at aratio of w/C (water-cement ratio)=0.8. Three
specimens were prepared for each test case toconsider the imperfection of specimens and thevariation of test results. The cases with w/G=2.0
show higher peak compressive stress than those with
w/G=2.5. Naturally the compressive stress after 28
days curing is higher than that after 7 days curing foreach case. Also, the stress-strain curves for the casesof mixing with scrapped ceramics showed toughness
on materials after the peak compressive strength. It
is found that a higher compressive stress can beobtained when the water content is moderate(w/G=2.0) and cement is additionally added.
The
Relationshipbetweenunconfinedcompressive strength and curing time is shown in
Fig. 5. The increase of unconfined compressive
strength for the case of Gypsum 30%, w/G=2.0 and
Cement 5% is remarkable with the increase of
curing time. In particular, the use of small amountsof cement and scrapped ceramics is more effective
for the preservation of the shape of the basematerials and the improvement of interlocking.

axial strain curves for the base materials after 28
days curing. In the graph legend, the mixture ratio isthe weight ratio for the whole weight. Particularly inthe cases with cement 14.7% and 12.3%, thecompressive stress reduces noticeably after the peakstrength. Fig. 7 shows photographs of the specimen
before and after completion of the unconfinedcompression test after 28 days curing. The specimen
is composed of volcanic ashes 29.4%, recycled
gypsum 23.5%, water 14.7%, scrapped ceramics
17.6% and cement 14.7%. It is found from Figs. 7(a)and (b) that the whole surface of specimen is quitesmooth before the test and the noticeablelongitudinal crack can be seen after the failure. Also,
the fragments in the crack are scrapped ceramics asshown in Fig. 7(b).
Table 1 contains a summary of results obtained

Sakurajima35.1%,Gypsum24.6%,Water14.0%,SC17.5%,Cement8.8%
Sakurajima29.4%,Gypsum23.5%,Water14.7%,SC17.6%,Cement14.7%
Sakurajima30.8%,Gypsum24.6%,Water13.8%,SC18.5%,Cement12.3%

4.00

Compressive stress (MPa)

3.50
3.00
2.50
2.00
1.50
1.00
0.50

PRODUCTION OF BASE MATERIALS FORSEAWEED BEDS

0.00
0.0

0.5

1.0
1.5
2.0
Axial strain (%)

2.5

3.0

The unconfined compression and dissolution
tests and the analysis of components were carriedout on the specimens of the developed basematerials. Figure 6 shows the compressive stress -Fig. 6 Stress-strain curve (base materials forseaweed beds, 28 days curing).

(a) Before test(b) After failure

Fig. 7 Specimen before and after unconfined compression test (Volcanic ashes 29.4%, Recycled gypsum
23.5%, Water 14.7%, Scrapped ceramics 17.6%, Cement 14.7%, 28days curing).
483

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Results obtained from unconfined compression test (base materials for seaweed beds, 28 days curing)
Volcanic ashes
Recycled gypsum
Mixing ratio
Water
(%)
Scrapped ceramics
CementUnconfined compressive strength
(MPa)

35.1
24.6
14.0
17.5
8.8

29.4
23.5
14.7
17.6
14.7

30.8
24.6
13.8
18.5
12.3

2.12

3.50

2.55

Water content (%)

19.0

19.7

19.5

Wet density （g/cm3 )

1.91

1.93

1.76

from the unconfined compression test. The watercontent for each case is over 19.0% and thespecimen shows the same black color as the volcanic
ashes including some extent of water. The
unconfined compressive strength becomes higher
when the mixture ratio of cement increases. In
addition, it is noted from visual observations that thesurface of specimen in the case of volcanic ashes
30.8%, recycled gypsum 24.6%, water 13.8%,
scrapped ceramics 18.5% and cement 12.3%, wasvery rough and the wet density was the smallest
among all cases due to the small amount of water forthe cement.
As a result of the dissolution test, a change on
pH of specimen after 28 days curing, dipping in
artificial seawater is shown in Fig. 8. The graphlegend is the same as that in Fig. 6. The initial pH
value for the artificial seawater was 9.37. The pH
values of all cases were increased by more than 1.0
immediately after dipping the specimen and thevalues were almost constant after 5 days dipping.
The reason why the pH value increased rapidly wasthat the curing of the specimen was not long enoughfrom visual observations, the specimen was notcompletely hardened and the volume of artificial
seawater for the specimen was small. In the element
analysis of constituent parts of artificial seawater,
the dissolution of hazardous elements like mercury
and hexavalent chromium was not detected within
30 days dipping.
Finally, examples of developed base materials
for seaweed beds (6 cases) are shown in Fig. 9. As
shown in Fig. 9, the surface of first specimen has
many small circular holes and is different with othercases due to the mold. The weight for each basematerial is approximately 23.0 Kg. In the second tosixth specimens, the half part of the surface iswashed by water after the curing to make the roughsurface. The pieces of scrapped ceramics on thesurface can be seen in the rough part. These would
be effective for the rooting of seaweed pores in

Sakurajima 35.1%,Gypsum 24.6%,Water 14.0%,SC 17.5%,Cement 8.8%
Sakurajima 29.4%,Gypsum 23.5%,Water 14.7%,SC 17.6%,Cement 14.7%
Sakurajima 30.8%,Gypsum 24.6%,Water 13.8%,SC 18.5%,Cement 12.3%

13.0

12.5

pH

12.0

11.5

11.0

10.5

0

5

10

15
20
Dipping days

25

30

Fig. 8 Change on pH of specimen dipping in
artificial seawater.
comparison with the smooth surface of non-washedpart. The third, fourth and sixth specimens are thecases with the inclusion of iron powders. In the third
specimen, the iron powders of 300g were covered on
the surface of the half part of mold, and the sameamount of iron powders were mixed into the halfpart of mold in the fourth specimen. The sixth
specimen was the case of mixing the iron powders(3.0% of the whole weight) into the whole part ofmold. Additionally, 10.1% shells of the whole
weight were mixed into the whole part of mold forincreasing the rooting of seaweed in the fifth
specimen.
Thus, the effects of the roughness of surface, themixture of iron powders and shells are regularly
monitored for the rooting and growth of seaweed
after setting the base materials into Kagoshima Bay.
It was observed that the color of surface of the base484

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 9 Example of developed base materials for seaweed beds (6 cases).

485

GEOMATE-Nagoya, Nov.13-15, 2013

materials changes gradually from black to white andsmall amount of calcium hydroxide comes from thesurface, when the base materials are becoming dry.
The tendency which the base materials require sometime to harden has been confirmed from visualobservations in the process of curing.

Kenkyusha Co. Ltd., 2003, pp. 100–106 (inJapanese).
[2] Terada R, “A review of a long-term survey forseaweed/seagrass communities in Japan”,
Aquabiology 195, Vol. 33 No. 4, Seibutsu
Kenkyusha Co. Ltd., 2011, pp. 291–297 (inJapanese).
[3] Okuda K, “Coastal environment and seaweedbed ecology in Japan”, Kuroshio Science 2-1,
2008, pp. 15–20.
[4] Yamamoto K, Negami T, Hira M, Aramaki N
and Hayashi Y, “Mechanical properties of
volcanic
products
appliedphysical
improvement”, Proc. of the Tenth National
Symp. on Ground Improvement, 2012, pp. 439–
442 (in Japanese).
[5] Negami T, Yamamoto K, Hira M, Hayashi Y
and Aramaki N, “Unconfined compressive
strength of volcanic ash treated with hardening
materials”, Proc. of the Tenth National Symp.
on Ground Improvement, 2012, pp. 443–446 (inJapanese).
[6] Japanese Geotechnical Society, Soil test –basis
and guideline- (first revised edition): Maruzen
Print Co. Ltd., 2011, pp. 71-78 (in Japanese).

CONCLUSION
In this study, the base materials for seaweed
beds which reduce the environmental impact could
be developed using volcanic ashes and recycledmaterials of industrial wastes. Now the developedbase materials have been set into Kagoshima Bay
and long-term survey has begun to monitor the
rooting and growth of seaweed for these materials atfixed intervals.
ACKNOWLEDGEMENTS
Scrapped ceramics and recycled gypsum areprovided by Fukushima Youzai limited company.
The authors appreciate the kind cooperation.
REFERENCES[1] Terawaki T, Nakayama N, Arai S and Shikida A,“For the restoration of seagrass and seaweedbed”, Aquabiology 145, Vol. 25 No. 2, Seibutsu

486Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CARBON FOOTPRINT AWARENESS – AN INVESTIGATION FROMTRAVEL DIARY SURVEY

1,2

Nur Sabahiah Abdul Sukor1and Nur Khairiyah Basri2
School of Civil Engineering, Engineering Campus, Universiti Sains Malaysia, 14300, Nibong Tebal,
Penang, Malaysia.

ABSTRACTIn this study,hundred university students were recruited to fill in the seven days travel diary that described
their use of privately owned motor vehicles. The diaries were collected and the respondents were given a
motivation session on the carbon emission causedbymotor vehicles. Then, they were asked to record their travel
pattern for another seven days and were encouraged to change their travel pattern to be more pro-environment. A
statistical analysis was done to examine the differences of the individual’s carbon footprint before and after the
motivation session. The result revealed the significant differences in the carbon footprints between first andsecond travel diaries. The structural equation modeling demonstrated that among the psychological variables,
pro-environment attitude was the most significant factor affecting the respondent’s intention to reduce the usageof motor vehicle, thus influencing the respondents’ behavior to be more pro-environmentalist.
Keywords: Carbon Footprint, Travel Diary, Theory of Planned Behavior, Pro-Environment

However, according to Wiedman and Mix [7],there is still no common consensus has beendeveloped on how to measure the carbon footprint
whilst the definition is also still intangible. There
are few studies which introduce the carbon footprintconcept by measuring the CO 2 together with othergreenhouse emissions in units of carbon dioxide
equivalent (CO 2 -e) [8-12]. However United States
Environmental Protection Agency [13] stated thatgreenhouse emissions such as CH4 and N2O arecomplex to calculate due to their dependency control
equipment, vehicle miles travelled, maintenance andoperational practice.
In GHG protocol mobile v1.3 [14] it is stated thateither fuel-based or distance-based method can beapplied to straightforward calculate CO 2 emission
for all transportation sources. Fuel-based Method is
calculations that based on aggregate fuelconsumption data meanwhile distance-based method
is calculations based on distance travelled anddistance based emission factors.

INTRODUCTION
The continuous rise in the number of vehicles
together with increasing mileages of travelling on
the road have triggered a serious issue of air
pollution from these motor vehicles [1]. In fact, thenumber of motor vehicles, as oppose to humanpopulation, in the world is growing more rapidly as
since 1960’s, 3.5 billion people having 50 million
cars in 1950 to over 600 million cars for 6.7 billion
people. It was estimated that there will be about abillion cars produce by 2020.
Moreover, Stern [2] reported in his book that thetransportation sector accounts for 14 % of total
global world GHG emissions,in which the roadtransport contributes three-quarters of the emissions.
In addition, the World Energy Outlook project
claimed that the global transport demand appears to
be growing up to 45 % by 2030 [3]. Therefore, GHG
emissions, resulting from the transportation sector,
are undoubtedly posing a serious concern andrequireattention
becauseofitsgrievousconsequences of the global warming.
The impact of human activities on global
warming was usually measured via the carbon
footprint calculation [4]. Nowadays, there are
numerous carbon calculators available online as well
as from consultants regarding the voluntary carbon
foot-printing [5]. Wright, Kemp and Williams [6]stated that individual carbon footprint calculator isused to calculate the individual GHG emissions inorder to link them to the more pro-environment
lifestyle and activities.

Lifestyle-travel pattern and psychological impact
towards carbon emissions.
Individual lifestyle is also claimed as one of thefactors that contributed to the individual carbon
footprint, including the individual travel patterns.
Vanderbergh, Barkenbus and Gilligan [15] in theirstudy reported that the use of private cars usuallyrelated with the idling of the motor vehicle engine.
This can be a source of increase in CO 2 emissions.
Meanwhile, Susilo and Stead [16] found that theindividuals that were young with high income,members of smaller household, and with privately
487

GEOMATE-Nagoya, Nov.13-15, 2013

owned vehicle were more likely to travel farther.
These indicators unfortunately lead to the highcarbon emissions which areinstigated by their travel
pattern and lifestyle.They also revealed that some
proportion of their respondents were in the favor ofthis suggestion that in order to reduce the CO 2
emissions, the public transport system should be
strategized and promoted.
In order to promote the pro-environment lifestyle
Stern [17] suggested that psychology can contributeto the reduction of carbon emissions throughdeveloping the understanding of climate relevant to
the household, individual and organizational
behaviors. For example, the voluntary actions inorder to reduce the carbon emissions (by reducing
the use of cars) were always directed to theawarenessandknowledge
towards
theenvironmental issues [18]. In the psychology andbehavioral study, the Theory of Planned Behavior(TPB) is renowned in explaining the diversity ofhuman behavior through the prediction of intention,
attitude, subjective norms and perceived behavioral
control (Fig.1).

individual carbon footprint based on the altered
Theory of Planned Behavior after a motivation
session on carbon emissions. This research applies
the distance-based method obtained from the travel
diary to calculate the CO 2 emissions. For thispurpose, this study performed several analyses basedon the respondents’ travel diary survey. In reporting
this study, this paper is organized as follows: Section
2 describes the travel diary, questionnaire and how
the survey was implemented; Section 3 presents theresults of the analysis of data; finally, section 4 isdevoted to discussion and conclusion from theresults found.
METHODThe sample and travel diary
This study is focused on the factors affecting theuniversity students’ carbon footprint throughout
their use of private motor vehicles. A hundred
students from School of Civil Engineering,
Universiti Sains Malaysia were recruited and asked
to fill in a 7 day travel diary that reported their daily
activities and travel patterns. The information fromthe diaries was used to indicate each of theindividual carbon footprints. After they finished withthe 7 day diary, they were required to attend a
motivational session that was aimed at increasing
their awareness towards carbon emission andenvironmental issues. At the end of the session, they
were requested to answer the questionnaire survey
pertaining to the psychology. After that, they wereasked to fill in another 7 day travel diary in order tocheck any behavioral change towards their way oftravel.

Attitude

Subjective
Norm

Intention

Behavior

Perceived
Behavioral
Control

Fig. 1

Theory of Planned Behavior [19]The extended of TPB were also used to measure
the psychological effects towards the proenvironment travel behaviour. For example, Anable[20] in her study to promote the alternative modes
for car users found that the voluntary behaviour ofswitching to more pro-environmet mode oftransports were affecting by psychological factors
such as attitude and beliefs. She stated that theperson who die-hard drivers were likely to create
reluctant attitude to switch their mode.
On account of believing that psychology could
give positive impact in reducing the emission causedby the private vehicles, Fuji and Taniguchi [21]implemented the motivational approach towards
groups of people at different county in Japan inorder to promote the pro-environment travel
behavior.Their study resulted in reduction of CO 2
emissions and car use thus increased in public
transport use.

Carbon footprint calculation
Data on distance traveled were collected throughthe travel diary survey that included the vehicle typeand fuel type. The distance estimated from the eachindividual travel diary was converted to CO 2
emissions by multiplying with distanced-based
emissions factor. In this study the distanced-based
emission factor was using the source from GHG
protocol mobile guide v1.3 [14]. The equation to
calculate CO 2 emissions based on the distancetraveled method is presented below.

CO2 = ∑ Distancej × dj
d=bxf

(1)
(2)

where
d = distance based emission factors (kg/100km)
j = different modes of transportationb = liters per 100km (liter/100km)
f = fuel based emission factors (kg/liter)In this study, all the respondents were consumed
RON95 for their motorized vehicle.

Study Objective
Therefore, the objective of this study is to
discover the underlying psychological factors of the488

GEOMATE-Nagoya, Nov.13-15, 2013

Questionnaire survey
RESULTS
Table 1 Questionnaire statements for psychologicalvariables
StatementItisanobligation foreach individual
to reduce theusage of private
motor vehicles
to reduce thecarbonemissions.
In my opinion,
an attempt totravel without
using
privatemotor vehicles
is one of thebest acts to
reducethecarbonemissions.
I do not attempt
to travel byprivate motor
vehiclestoreducetheconsequencesofcarbonemissions.
It is hard for me
to travel by not
using
privatemotor vehicles.

The people thatclose to me do
not support me
to reduce theusage of private
motor vehicles.

PsychologicalvariablesMoralobligation

OpinionAttitude

Descriptive analysis
The results of frequency analysis in Table 2
revealed that the age range for the sample recruitedis within 19 to 33. The male and female categories
are almost balanced with 52% of male and 48% offemale. 36.7% of the respondents possessed a car,17.3% owned a bicycle, 8.2% owned a motorcycle
and 31.6% with no vehicle ownership. However inthis study, students with bicycle and no vehicle
ownership were included in the same group namely
students without motor-vehicle ownership.

Answer scale
1= Strongly
Agree
2= Agree
3=Disagree
4=Strongly
DisagreeTable 2 Descriptive statistic of the respondents

1= Strongly
Agree
2= Agree
3=Disagree
4=Strongly
Disagree

Variable
Age
GenderMale
FemaleVehicle ownershipAt least one
motorized vehicle
ownership
No motorized
vehicle ownership

1= Strongly
Agree
2= Agree
3=Disagree
4=Strongly
Disagree% (N)-Mean (S.D)
23.08 (2.82)

52 (52)48 (48)0.56 (0.502)
0.37 (0.489)

49 (49)0.49 (0.502)

31.6 (52)0.52(0.502)

Individual Carbon Footprint
Perceived
Behavior
Control

Subjective
Norms

T-test statistical analyses were undertaken inorder to examine the differences of carbon footprint
values in travel diary 1 and 2. The results showedthat there were significant differences on individualcarbon footprint emission before and after the
motivational lecture session according to gender andmotor vehicle ownership. This demonstrates that the
motivation session was a success in terms ofincreasing the students’ awareness towards carbon
emission issues. The findings also disclosed thatafter the lecture session, 62% of the respondents had
intention to reduce the usage of motor
vehicles.However, the respondents who did not own
motor
vehiclesdemonstrated
nosignificant
difference of carbon footprint between travel diary 1
and 2. It indicates that they kept their carbon
footprint low.

1= Strongly
Agree
2= Agree
3=Disagree
4=Strongly
Disagree
1= Strongly
Agree
2= Agree
3=Disagree
4=Strongly
DisagreeThe questionnaire form to measure thepsychological effects were given after the
motivation session. Since Ajzen [19] suggested that
the TPB is open to expansion, so the questionnaire
was constructed according to the TPB variables withthe addition of moral obligation and opinion. The
statements measuring the psychological variables in
the questionnaire form are shown in Table 4. The
data for all the psychological variables listed below
was examined through the structural equation
modeling (SEM).
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GEOMATE-Nagoya, Nov.13-15, 2013

Table 3 Statistical t-value for carbon footprint
before and after motivation session
according to gender and vehicle ownership
VariableCF
beforeCF
after

Furthermore, according to the estimation results,
several path coefficients were statisticallysignificant. Fig. 5 illustrates the path diagram withthe resulting estimates of entire structural parameters
have shown on the path. For statistical analysis
purpose, the variationsin the students’ individualcarbon footprint were used as the dependent
variable. The results indicated that attitude was the
only important psychological factor, related to theintention of reducing the individual carbon
footprint,whereas, other psychological variables
were not that significant. In addition, the attitude
also delivered the strongest coefficient value among
the psychological variables associated with the
behavioral intention of the respondents. The
negative coefficient of attitude indicates that the
respondents who were not willing to travel byprivate motor vehicles in order to reduce the carbon
footprint aremost probably on the verge of making aplan to change their travelling behavior to be more
pro-environment, after the lecture session.
The results also indicated that intention was also
an extremely important variable associated with the
respondents’ behavioral change. The positivecoefficient showed that the respondents who have an
intention to be pro-environment are likely todemonstrate some changes in their individual carbon
footprint, after the lecture session. In the case ofcorrelation between the psychological variables,
moral obligation was found to be significantly
related with the respondents’ opinion and attitude. It
also disclosed that the respondents who felt it is an
obligation to avoid using the privatelyowned
vehicles in order to reduce the carbon emissions
areexpected to decrease their usage. On the other
hand, the respondents with moral obligation werealso likely to agree that travelling without using
motorized vehicle would be one of the best options
to be a pro-environment.

t-statGenderMale
17.024 9.717 1.825*
Female16.823 12.105 2.169#
Vehicle ownership
Motorized
26.348 16.775 2.176*
vehicleownership
Non-Motorized
7.876
5.184
1.665
vehicleownership
Note: p-value for male (0.035), female (0.074),
motorized owner (0.035), non-motorized owner(0.102); #p<0.10, *p<0.05, **p<0.01, ***p<0.001
Psychological Effect
Table 5 presents the estimation results ofpsychological factors based on the structural
equation modeling. Results are presented in terms of
estimated parameters and their corresponding t
statistics. The overall maximum likelihood
estimation of the model yields a chi-square value of
2.799 with 4 degrees of freedom. A review of thegoodness-of-fit statistics showed that the model
provides a reasonably good fit to the data In
particular,the RMSEA value is lower than 1. The
chi-square/d.f. of 0.67 is well below therecommended value of 3.00. The GFI, NFI and CFI
values seem probably acceptable and exceed thecutoff value of 0.90
Table 4 Estimated causal effects (standardized)
among variables
Path To
Intention

Path
From
Atd

E.P

S.E

Moral
Obligation+

C.R

Opinion-+-0.2050.071-2.123***
Intention
PCB
0.143
0.061
1.497
IntentionSN-0.1380.059-1.467
IntentionMO-0.1460.082-1.531BC
SN-0.0522.827-0.534BC
Intention
0.197
4.542
2.002
***
BC
Opinion-0.1603.419-1.646
Note: Atd = Attitude, PCB = Perceived Behavior
Control, SN = Subjective Norm, MO = Moral
Obligation, BC = Behavior Change, E.P = estimatedparameters, S.E =standard error, C.R = critical ratio,*p<0.05, **p<0.01, ***p<0.001

Attitude
Perceived
Behavior
Control

Intention+

Behavior
Change+-+Subjective
Norm

Fig. 2 Estimated model of relationships among
psychological variables towards individual carbon
footprint behavioral change
Note: N = 100; Cmin = 2.799; d.f=4; Cmin./d.f.=
0.670; CFI =1.0; GFI = 0.992; AGFI=0.945; 90%
confidence interval

490

GEOMATE-Nagoya, Nov.13-15, 2013

Discussion and Conclusion

REFERENCES

This study emphasized on the effectiveness of amotivation session in order to increase the awarenessof the carbon footprint that caused by theindividual’s pattern of travel. The individual carbon
footprints were collected through two time frames(each time frame constitutes 7 days) and interspersed
by a motivation session that was relatedto
environmental awareness. At the end of the
motivation session, the respondents were required toanswer the psychological questionnaire.
Our findings reinforced existing evidence for theimportance of attitude and intention in predictingchanges towards pro-environmental travel behavior.
Among the psychological factors, the attitudedisplayed significantly stronger effect than theintention. However intention was statisticallynoteworthy towards the behavioral changes. Other
psychological antecedents were found to be not thatsignificant.
The differences of carbon footprint value
between diary one and diary two revealed that the
motivation sessions have delivered a positive impact
on the respondents' attitude towards carbon emission
issues that instigated by human travel patterns. Male
students were found to be morecommitted with the
reduction of their carbon footprint value ascompared to female students. This is because mostof the male students owned motor vehicles and the
motivation session seemed managed to convince
them to reduce the use of their private motor
vehicle.It is consistent with the t-test findings where
the students who owned motor vehicle reduce theircarbon print more than those who do not owna
vehicle.
However, this study did not confirm whether the
motivation session will affect the students' behavior
in the long term. It is suggested to assess the
respondents' behavior at 6 months interval after the
motivation
session.
Furthermore,otherpsychological variables except for attitude andintention were not found to be significant thatmight
be due to the small sample size for this study. Thismight have an impacton the SEM results.
Nonetheless, the aim of this study is also to examine
the capability of travel diary to gain the carbon
footprint data. This is because the travel diary survey
is less concerned to be implemented in Malaysia.
Therefore, for future research it is aimed to increase
the number of samples to gain more accurate results.
As a conclusion, this study suggested that a travel
diary survey can be used to collect the data forcarbon footprint. In addition, this study also
confirmed that motivational sessions are effective
for increasing awareness on individual’s carbon
emission, thus affecting the individual’s way oftravelling.

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we alter our carbon footprint? Estimating GHG
emissions based on travel survey information",Transportation, Vol.40,2013,pp 131-149[13] "Direct Emissions from Mobile Combustion
Sources",
UnitedStatesEnvironmental
Protection Agency, 2008 .
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Sources”
GHG
Protocol-Mobile
Guide(03/21/05)v.13
Available
at http://cf.valleywater.org/Water/Where_Your_
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ange/Guidance_for_mobile_emissions_GHG_protocol.pdf. Accessed on 13 February 2013
491

GEOMATE-Nagoya, Nov.13-15, 2013[15] Vanderbergh ,MP., Barkenbus, J. and Gilligan,
J., "Individual Carbon Emissions: The LowHanging Fruit", Vanderbilt University Law
School Public Law and Legal Theory, 2008[16] Susilo, YO and Stead,D., "Individual CO2
emissions and the potential for reduction in the
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Annual Meeting of the Transportation Research
Board, 2010.
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Limiting
ClimateChange",AmericanPsychologist, Vol. 66, No. 4, 2011, pp. 303 –
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492

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

OPTIMAL MONITORING NETWORK DESIGN FOR EFFICIENTIDENTIFICATION OF UNKNOWN GROUNDWATERPOLLUTION SOURCES
1

Om Prakash1, 2 and Bithin Datta1, 2
Discipline of Civil and Environmental Engineering, School of Engineering and Physical Sciences, James
Cook University, Townsville QLD 4811, AUSTRALIA.
2
CRC for Contamination Assessment and Remediation of the Environment, Mawson Lakes SA 5095,
AUSTRALIA.
ABSTRACT

Application of linked simulation-optimization approach for solving groundwater identification problems is wellestablished. Pollutant concentration measurements from different sets of monitoring locations, when used in alinked simulation-optimization approach, results in different degrees of accuracy of source identification.
Moreover, the accuracy of source identification results depends on the number and spatiotemporal locations ofpollutant concentrations measurements. This study aims at improving the accuracy of source identification results,
by using concentration measurements from an optimally designed monitoring network. A linked simulation
optimization based methodology is used for optimal source identification. Genetic programming based impact
factor is used for designing the optimal monitoring network. Concentration measurement data from the designed
network is then used, in the Simulated Annealing based linked simulation-optimization model for efficient source
identification. The potential application of the developed methodology is demonstrated by evaluating its
performance for an illustrative study area. These performance evaluation results show improvement in theefficiency in source identification when such designed monitoring networks are utilized.
Keywords: Optimal Monitoring Network; Groundwater Pollution; Genetic Programming; Multi-Objective
Optimization; Pollution Source Identification; Simulated Annealing[1], cost-effective sampling design [2], samplingstrategy in space and time using Kalman filter [3],optimal monitoring network for early detection ofpollutant [4], [5], minimizing the number ofmonitoring wells [6]. Optimization based solution
for reducing the redundancy in a groundwater
quality monitoring network [7], sequential
monitoring network design [8], and variation of
dynamic monitoring network design methodology is
discussed in [9].
Most of the existing methodologies of source
identification using linked simulation-optimizationuse concentration measurements from arbitrarily
located monitoring wells. Limited amount of work
has been reported for improving the accuracy ofsourceidentification
using
concentration
measurements from an optimally designed
monitoring network. A methodology is proposed fordesign of optimal monitoring network for improving
the accuracy of source identification results using
concentration measurements from a designed
monitoring network. The simulated response of theaquifer is compared to the observed response of theaquifer at these optimal monitoring locations in aclassical linked simulation-optimization technique.
The monitoring network designed to improve theaccuracy of source identification is based on two
conflicting objectives, (1) reduce the possibility of
missing an actual source, and (2) decreases thedegree of non uniqueness in the set of possible

INTRODUCTION
The most common problem encountered in
remediation of a polluted aquifer, is the accurate
identification of pollution source locations and theirrelease histories from sparse set of spatiotemporalconcentration measurements. In scenarios where
potential source locations and activity duration are
known with fair degree of certainty, linked
simulation-optimization based approach is often
applied for solving groundwater pollution source
identification problem for recreating the flux releasehistory of the sources.
A large number of concentration measurements
spread over time and space is necessary for accurate
identification of pollution sources. However, longterm monitoring over a large number of monitoring
locations has budgetary constraints. Hencemonitoring locations should be chosen such thatconcentration measurements from such designed
monitoring network when used in a linked
simulation-optimization approach, improves theaccuracy of source identification results. Contrary tothis, monitoring locations often consists ofarbitrarily located single water supply well, or agroup of arbitrarily placed wells which may not be
optimally located for accurate source identification.
Design of monitoring networks may havedifferent underlying objectives, such as optimal
sampling plan for groundwater quality monitoring493

aquifer responses to subjected geo-chemical
stresses. The proposed methodology uses genetic
programming (GP) models to calculate the impact
factor of a source on a candidate monitoring
location. This impact factor is utilized as the design
criteria for choosing the optimal monitoring
locations out of the candidate well locations. The
conflicting objectives considered are, (1)maximization of the normalized impact of all
potential pollution sources at selected monitoring
locations and (2) to maximize the relative impact ofa potential source at the chosen monitoring location.
The Pareto-optimal solutions obtained from the two
objective model is utilized to relate the variation in
the accuracy of source identification results and thetrade-off between the above stated conflicting
objectives for designing an optimal monitoring
network. Performance of the proposed source
identification methodology is evaluated by solving
an illustrative problem. The results of source
identification are compared for different random
monitoring networks with that of the optimal
network. This method can be applied to practicalscenarios where the observed concentration data is
to be restricted to a few monitoring locations.

variable (pollutant concentration at chosenmonitoring locations and times) and the independent
variables (flux values of pollutant at potential
pollutant source locations).
Specified number of best individual GP models
is used for computing the impact factor. The impact
factor is described as a measure of how much an
input variable accounts for the output result i.e., afactor by which the result would differ if the variable
was removed. This essentially implies that, if byremoving a variable from the mathematical function(GP model) there is a large change in the output, thenthe removed variable has a high impact on the output
and hence the impact factor of that variable will behigh. The impact factor value is then used as design
criteria in a multi-objective optimization
formulation for designing an optimal monitoring
network.
Multi-Objective Optimization for Monitoring
Network Design Model
An SA based multi-objective optimization
model is utilized for choosing monitoring locations
such that the possibility of missing an actual sourceis reduced, and at the same time reduces the degreeof non-uniqueness due to overlapping of multiple
pollutant plumes. This is accomplished by an SA
based multi-objective optimization model that finds
monitoring well locations with the following
objectives (1) finding well locations with maximum
normalized impact from all the potential sources and(2) finding well locations with maximum
normalized relative impact from an individual
potential source over a chosen observation period.
Finding well locations with maximum normalized
average impact (objective 1) reduces the possibilityof missing an actual source as it chooses locations
where overlapping of plumes due to potential
sources is maximum. This also reduces thelikelihood of choosing monitoring locations where
the impact of potential sources are small. However
objective 1 is in conflict with objective 2 of finding
well locations with maximum normalized relative
impact from an individual potential source. The
second objective essentially reduces the nonuniqueness due to overlapping of different pollutant
plumes resulting from different sources.
A multi-objective optimization model isformulated to design an optimal monitoring networkwith multiple conflicting objectives. One of theobjectives is traded off to improve the otherobjective and vice versa. The constrained method is
utilized, which iteratively maximizes one of theobjectives subject to the other objective achieved ata specified level. The number of monitoring wells tobe selected is essentially governed by budgetary
constraints. The formulation for the multi-objective
optimization for monitoring network design is given
in Eq. (1) through Eq. (11).

METHODOLOGY
In this proposed methodology, first GP models
are trained against a large set of data patterncomprising of source flux history for all the potential
sources as input and corresponding aquifer response
at all potential monitoring locations as the output.
Based on R2 value specified, a number of fittest GP
models are chosen for calculating the impact factorof potential source on a monitoring location. The
impact factor is calculated for all candidate
monitoring locations at each monitoring time step.
A multi–objective optimization formulation isapplied to select the optimal set of monitoring
location for source identification using linked
simulation-optimization technique. In the second
step, a SA based linked simulation-optimization
model for source identification is solved to minimize
the deviation between the simulated and measured
pollutant concentrations at these optimally chosenmonitoring locations.
Genetic Programming and Impact Factor
GP is an evolutionary optimization algorithm
based on the concepts of genetics and natural
selection. It starts with an initial population of
randomly generated computer programs andoptimizes the parameter values of a given model
structure within predefined parameter space to finda highly fit computer program that produces desired
output for particular set of input. Each GP model isessentially a computer program that represents themathematical relationship between the dependent

494

nt

α is integer constant representing the maximum

(1)

S
St
IFiob
)
= ∑ ( Fiob

number of wells that can be chosen

t =1

IFiobS is the impact factor of source S on monitoringf iob represent the binary decision variable to select awell location iob

monitoring well location f iob ≡ {0,1} such that whenf iob value equal to 1 representing monitoring well to
be selected at location iob, and zero otherwise

St is the impact factor of source S on monitoring
Fiobwell location iob at stress period t
nk

(2)

S
S k
= ∑ ( IFiob
SumIFiob
)

nob

∑

k =1

iob =1

Re l

(9)

norm
SumIFiob
f iob − λ ≥ 0

S is the sum of the impact factors of a
SumIFiob

MaxF 2 ≥ λ(10)potential source S at any given monitoring location
iob for nk sampling steps

F 2 MaxF 1 ≤ λ

(11)

S =1

The two objective multi-objective optimization
model is solved using the constrained method where
one of the objective function (F1) is maximized
keeping minimum level of satisfaction (λ also
termed as the trade-off constant) of the second
objective function (F2) as shown in Eq. (9). All
solutions lying on the Pareto-optimal front
corresponds to a different monitoring network.

(3)

S
SumIFiobnS

norm
SumIFiob=∑

1 nob∑ SumIFiobS
nob iob=1

norm is the normalised sum of impact factor at
SumIFiob

any monitoring location iob due to all the potential
sources nS for all nk monitoring time steps
nt is the total number of stress periods

Linked Simulation-Optimization
Source Identification

nk is the total number of monitoring time steps
1 nob∑ SumIFiobS is the average impact factor due to a
nob iob =1

source S at all monitoring well locations nob
nS

Re l

S
S
S
SumIFiob = Max{SumIFiob} − ((∑ ( SumIFiob)) − Max{SumIFiob
})
S =1

(4)
Re l

SumIFiob is the relative impact factor due to all thesources nS at a given monitoring well location iob
Re l

Re l

norm
=
SumIFiob

Re l
SumIFiob
1 nS∑ SumIFiobSnS S =1(5)

norm is the normalized relative impact factor
SumIFiob1∑ SumIFiobS is thenS S =1nkkkcest iob= f (q s , C s ) f (qs , Cs , cestiob) v iob , k

iob =1
nob

f iob

(13)

qs is the volumetric flux
C s is the concentration of the sources or sinks

The two objectives F1 and F2 of the multi-objective
optimization model for optimal monitoring network
design for accurate identification of unknown
pollution sources is defined by Eq. (6) and Eq. (8)respectively.
MaximizeF1 = ∑ SumIF(12)

q s C s is the pollutant source fluxes

monitoring well location iob for all potential sources

norm
iob

nob

k =1 iob =1

average impact factor at

nob

for

Groundwater flow (MODFLOW) and solutetransport (MT3DMS) simulation model are used tosimulate the physical process within the
optimization model.Simulated Annealing (SA) is
used as an optimization algorithm to solve theoptimization problem. Candidate values of unknown
variables (source fluxes) are generated in
optimizations algorithm for simulations of flow andtransport models. The difference between simulated
and observed pollutant concentrations are computed,
and finally obtain an optimal solution that minimizes
the difference between observed and simulated
values.
kk)
MinimizeF = ∑ ∑ ABS (cestiob− cobsiob

at monitoring well location iob for all potential
sourcesnS

Model

ABS is the absolute differencekcestiob
is the simulated concentration

nk is the total number of monitoring time steps
nob is the total number of observation wellskcobsiob
is the observed concentration

(6)

norm
MaximizeF 2 = ∑ Re l SumIFiob
f iob

(7)

PERFORMANCE EVALUATION

nob

(8)

The performance of the developed methodology
was evaluated for the study area shown in Fig. 1,
with hydro-geological parameters as given in Table

iob =1∑f

iob =1

iob

≤α

495

1. Three sources with three stress periods of 500days
each were considered. The pollutant flux from eachof the sources is assumed to be constant over a stressperiod. Four temporal concentration measurements
at each potential location (starting t = 1600 days) aretaken after every 200 days.

10% for testing the GP models. DiscipulusTM 5.1(RML Technologies, Inc.) is used for training,validation and testing. Based on R2 fitness value, top
30 GP models are used for computing the impact
factor. The impact factor for all the potential
monitoring locations at every sampling time step iscalculated likewise which is then used to calculate

Fig. 1 Plan view of the Illustrative Study Area

the normalized relative impact factor SumIFiob
and normalised sum of impact factor due to all the

Table 1 Hydro-geological Parameters

potential sources SumIFiob .

Re l

norm

norm

Optimal Monitoring Network and Arbitrary
Monitoring Network
The optimal monitoring design model is solved
using normalised impact factor values as calculated
above. The value of the minimum satisfaction levelof objective function F2 is varied from a minimum 1.7 to a maximum of 8.06 to obtain 12 different
Pareto-optimal solutions representing different
Pareto-optimal monitoring networks: MN1to MN12.
To show the comparison, 10 arbitrary monitoring
networks ARMN1 to ARMN10 are chosen. A totalof 6 monitoring wells are selected in eachmonitoring network.
Source Identification using Data from ParetoOptimal Monitoring Networks and Arbitrary
Monitoring Network
Parameter

Unit

Value

Maximum length of study area
Maximum width of study area
Saturated thickness, b
Grid spacing in x-direction, Δx
Grid spacing in y-direction, Δy
Grid spacing in z-direction, ΔzHydraulic conductivity, K
Effective porosity, θLongitudinal Dispersivity, αLTransverse Dispersivity, αT
Horizontal Anisotropy
Initial contaminantconcentration
Diffusion CoefficientContaminant Flux

m
m
m
m
m
m
m/d

2100
1950
30
50
50
30
20
0.3
20
10
1
0
0
0-100

m/d
m/d
g/l
g/s

To evalutate the performance, observed
concentration
measurements
aregeneratedsynthetically. These simulated measurements arethen perturbed with random error term (maximum
deviation of 10 percent of the measured
concentration data) to incorporate realistic
measurement errors (Eq. 17 to Eq. 18). A linked
simulation-optimization model is solved using
measurements from 12 Pareto-optimal monitoring
networks (MN1to MN12) and 10 arbitrary
monitoring networks (ARMN1to ARMN10). The
source identification model is solved with error free
data and perturbed erroneous data.
Pert
k
k
(14)
cobsiob= cobsiob+ err
err = µper × rand
Pert

(15)

cobs is the perturbed concentration valuekiob

kis the numerically simulated concentration
cobsiob

Genetic Programming Impact Factor

value
err is the error term
µper is the specified maximum deviation expressed
as a fraction < 1
rand is a random fraction between -1 and +1

The impact factor is calculated for 3 sources and25 (W1 to W25 as shown in Fig. 1) potential
monitoring well locations. The input data consists offlux values for each source at every stress period.
The corresponding output data consists of theresulting pollutant concentration measurement due
to these source fluxes at all the 25 potential
monitoring well at t = 1600, t = 1800, t = 2000 and t= 2200 days. 3000 data patterns are used of which
50% is used for training, 40% for validation, and496

the estimated source flux for all the 12 Paretooptimal monitoring networks is calculated using
error free data and erroneous data (Fig. 5 and Fig. 6).
Absolute difference of actual source flux and theestimated source flux for all the 12 Pareto-optimal
monitoring networks (MN1 to MN12) with error
free data and erroneous data show similar trend. The
average of the absolute difference, between theactual source flux and the estimated source flux is
minimum for monitoring network 5 (MN5), hence
can be designated as the optimal monitoring
network.

RESULTS AND DISCUSSION
The Pareto-optimal solution for the twoobjective optimal monitoring network design modelis shown in Fig. 2. The first objective function
values F1 is plotted against the minimum
satisfaction level of the second objective function
value F2. The non-inferior solutions show theconflicting nature of the two objective functions andObjective Function Value
F1

9
8.578.49
8.23
8.04
8

7.65

7.38

7

S11
S23
S21
100

7.02
6.63

5

-2

-1

0

1

2

3

4

5

6

7

Absolute Difference of Actual andEstimated flux gms/sec

6.02

6

5.59
5.08
5.01
8
9

Objective Function Value F2

Fig. 2 Pareto Optimal Solution Front
their trade-off.
The results of source flux identification solution
results obtained by using linked simulationoptimization model is compared for all the 12
Pareto-optimal monitoring locations (MN1 to
MN12), obtained as solutions, using error free andperturbed error data (Fig 3 and Fig 4).
MN1
MN5
MN9

MN2
MN6
MN10

2

3

4

5

MN3
MN7
MN11

7

8

9 10 11 120.0001

Pareto-Optimal Monitoring Network 1 to 12

Fig. 6 Difference of Actual Flux and Estimated FluxErroneous S11
Data
S12
S13

60
40
20

S11 S12 S13 S21 S22 S23 S31 S32 S33

Fig. 3 Identification Results using Error free data
MN2
MN6
MN10

6

0.01

S21
S31
Average

MN1
MN5
MN9

S22
S33

Fig. 5 Difference of Actual Flux and Estimated FluxFig. 4free
Identification
Results using Erroneous data
Error
Data

0

Source Flux gms/sec

180

Actual Flux
MN4
MN8
MN12
125

S13
S32

1

0.000001

Absolute Difference of Actualand Estimated flux gms/sec

Source Flux gms/sec

Actual Flux
MN4
MN8
MN12
100

S12
S31
Avg

MN3
MN7
MN11

S22
S32

S23
S33

100

10

1
1

2

3

4

5

6

7

8

9

10 11 120.1

0.01
Pareto-Optimal Monitoring Network 1 to 12

The source identification model is solved for 10
arbitrary networks (ARMN1 to ARMN10) with both
error free data and erroneous data. The estimatedflux values using the arbitrary networks is averaged
and compared with the actual flux values andestimated flux value from monitoring network 5(MN5), both for error free data and erroneous data
(Fig. 7 and Fig. 8). It is seen that the estimated flux
using monitoring network 5 (MN5), are closer to theactual flux values as compared to the flux estimatedusing the arbitrary networks (AVG-AR).

100
75
50
25
0
S11 S12 S13 S21 S22 S23 S31 S32 S33

To choose the best monitoring network out of the
12 Pareto-optimal monitoring networks (MN1 to
MN12), absolute difference of actual source flux and497

Source Flux gms/sec

100

ActualAVG_ARof monitoring wells, resulting in increased capitalcost. This method can increase the accuracy ofsourceidentification
withconcentration
measurement data from limited number ofmonitoring wells in a designed monitoring network.

MN5

80
60
40

REFERENCE

20[1] Loaiciga, H. A. (1989), An optimization
approach for groundwater quality monitoring
network design, Water Resource Research,
25(8):1771–1782.

0
S11 S12 S13 S21 S22 S23 S31 S32 S33

Fig. 7 Comparison of Identification Results using
Optimal Network and Arbitrary Networks: Error
free Data[2] Mugunthan, P., and C. A. Shoemaker (2004),
Time varying optimization for monitoring
multiplepollutants
under
uncertainhydrogeology, Bioremediation Journal, 8(3–4):129–146.

Source Flux gms/sec

CONCLUSIONS
100

ActualAVG_AR

MN5[3] Kollat, J. B., P. M. Reed and R. Maxwell(2011),
Many-objective
Groundwater
Monitoring Network Design using Bias-Aware
Ensemble Kalman Filtering, Evolutionary
Optimization, and Visual Analytics, Water
Resource Research, v47, W02529.

80
60
40
20

Fig. 8 Comparison of Identification Results using
0
Optimal S11
Networkand Arbitrary
S12 S13
S21 S22 Networks:
S23 S31 S32 S33
Erroneous Data

[4] Loaiciga, H. A., and P. F. Hudak (1992), A
location modelling approach for groundwater
monitoring network augmentation, Water
Resource Researce, 28(3):643–649.

Not all monitoring locations are ideally locatedfor accurate identification of source flux using
linked simulation-optimization. The solution resultsin the illustrative example problem show that theaccuracy of source flux identification varies whenusing pollutant concentration measurement datafrom different monitoring locations. A methodology
has been developed for designing an optimal
monitoring network for accurate source flux
identification. Concentrations measurements fromsuch a designed monitoring network when used insource flux identification, can improve the accuracyof the source identification results.
An optimal monitoring network design forsource flux identification is a multi-objective
problem. It requires the right balance between welllocations where the impact of all the potential
sources are significantly large, reducing thepossibility of missing an actual source and, welllocations where non-uniqueness due to overlappingof source plumes is less. In all real world problemsof source identification, the degree of uncertainty interms of source locations and aquifer response to
subjected geo-chemical stress are large. Moreover,the number of monitoring wells to be implemented
for concentration measurement data is governed bybudgetary constraints. The proposed methodology
can be applied to polluted aquifer sites. This method
can decrease such uncertainties using limited
number of monitoring wells which otherwise will
have to be reduced by implementing large number[5] Loaiciga, H. A., and P. F. Hudak (1993), An
optimization method for network design in
multilayered groundwater flow systems, Water
Resource Research, 29, 2835.
[6] Meyer, P. D., A. J. Valocchi and J. W. Eheart(1994), Monitoring network design to provide
initial detection of groundwater pollution,
Water Resource Research, 30, 2647.
[7] Dhar, A., and B. Datta (2010), Logic-Based
Design of Groundwater Monitoring Network
for redundancy Reduction, Journal of Water
Resource
PlanningandManagement,
136,88(2010).
[8] Dhar, A., and B. Datta (2007), Multi-objective
design of dynamic monitoring networks for
detection of groundwater pollution, Journal of
Water Resource Planning and Management,
133(4):329–338.
[9] Sreenivasulu, C., and B. Datta (2008), Dynamic
optimal monitoring network design for transienttransport of pollutants in groundwater aquifer,
Water Resources Management, 22(6):651–670.

498

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SPATIAL DISTRIBUTION CHARACTERISTICS OF SUBTERRANEAN HOT
WATER EVALUATED USING WATER QUALITY CONCENTRATION DATA
Takamitsu Kajisa1, Si Senfi1, Yasunori Mori1,2, Homayoon Ganji1,
Abdul Saboor Rahmany1, Masaaki Kondo1, and Hajime Narioka1
1Graduate School of Bioresources, Mie University, Japan
Mie Prefecture Health and Environment Research Institute, Japan

2

ABSTRACT
Spatial distribution characteristics of subterranean hot water were indexed using correlation coefficient's (R)p-values for hot spring water quality indicators. For example, in a case where the p-value of R was smaller than
5%, the correlations of a set of water qualities for two hot springs were significant. In this study, in a dense hotspring area, the minimum distance with a p-value greater than Pc (critical p-value) was proposed as a stochastic
and critical distance (Xc) for both new and existing hot spring owners. By using data from 10 hot springs in eacharea, 45 sets of distances and p-values were examined. Of the five areas examined, three and four Xcs more than
1,000m were found for Pc 1% and Pc 5%, respectively. The experimental relation between the given Xc and the
hot spring depth could not be confirmed. Results indicate that the influence of water quality from new hot
springs located outside of the Xc range is not always insignificant, even though the water quality of the new hot
springs should primarily influence existing springs located within the Xc range.
Keywords: hot spring, subterranean hot water, hot springs law, correlation coefficient, p-value

order to receive authorization for a hot spring, it isnecessary to obtain water quality data. Therefore,much hot water quality data is available. In thisstudy, we focused on five areas with available hotspring water quality data. Ten hot water springs
were used for each area, totaling to 50 hot springs.
Particular types of water qualities were selected todetermine correlations among the hot springs.
Hot springs with similar water quality may havethe same source. Digging a new hot spring with asimilar water quality is a potential water resource
hazard for the existing hot spring owner. If the water
quality difference of two hot springs can be
estimated by the distance between them, a parameterthat is easily determined, this could help in avoiding
such hazards. Therefore, the water quality
differences between two hot springs were discussed
relative to the distance between the hot springs. For
analysis, the following three hypotheses were made.

INTRODUCTION
In Japan, in areas where wells for hot spring spas
are numerous, decaying water quality has been
observed. To combat this problem, the “Guideline
for the protection of hot spring resources” wasdeveloped under the Hot Springs Law by theJapanese Ministry of the Environment [1].
A water source is determined to be a hot spring by
the “Hot Spring Law” (Onsen-ho), if the hot water
discharged from underground is equal to or above
25°C. When it is below 25°C, it must satisfy at least
one of the 19 elements listed in Table 1.
According to the guidelines [1], the limiting
distance for new wells, Xg, is 300–500m, as set forth
by the questionnaires administered in 23 prefectures.
Xg being the critical limiting distance proposed inpractice for public judgment (m). Some Xgs were
given numerically by questionnaires, water balanceand heat balance. From the viewpoint of waterbalance, Xg is 406 m. For deep hot springs, Xgs are
1,000–2,000 m. By calculating heat balance, Xgs are
1,030–1,780 m. On account of numerous hypotheses
applied, the logic of employing these distances is notparticularly strong. Hence, using critical limiting
distance, Xg, is very simple.
The depth of hot spring wells can substantiallydiffer. Wells with depths of more than 1,000 m arecalled deep hot springs, whereas those with depths
lower than 1,000 m are called shallow hot springs. In

1) Steady state hypothesis is used. The correlation
coefficient (R) of water quality between two hot
springs can be numerically given as a constantnumber by a stochastic method.
2) In cases where the correlation is significant, as thep-value of R is smaller than the critical value Pc, thewater source or root of the flow is expected to benear.
3) In cases where the water source or root of theflow is near, digging a new hot spring may affect the499

GEOMATE-Nagoya, Nov.13-15, 2013

existing hot spring.
Estimation of the critical distance Xc would assist
both a new owner digging a new hot spring and theexisting hot spring spa owner. In this study, Xc is thecritical distance determined by using stochastic
method, which is numerically given by evaluating
the similarity of certain chemical data measured ineach of the hot springs.

for seven types of water quality indicators (ppm) areillustrated in Fig. 1. A logarithmic function was usedbecause of the varying order of magnitude for water
quality parameters.
The correlation value for both hot springs can beobtained using a stochastic method. Seven types ofwater quality indicators, shown in Table 2, wereselected on the basis of the following three points:(1) The hot spring water qualities as defined by theministry in the hot-spring standard (Table 1). (2)The water qualities derived from previous hot
springs, shown in [2][3]. (3) The geology-based
water qualities shown in Piper’s trilinear diagram. In
this study, we selected Na, K, Ca, F, Cl, SO4, andH2SiO3. Because these seven water quality
indicators were used, the data number n for
determining R is seven.
The p-value was used as the index that demonstrates

OBJECTIVES

Logarithm of the density of water quality

Under all three hypotheses given in the
Introduction, three objectives were created, which
are mentioned as follows:
1) Confirm how the combination samples of X andp-value will be classified by Xc and Pc.
X being the distance between the new and existing
hot spring (m).
2) Determine whether Xc varies with hot spring
depth.
3) Clarify the essential meaning of Xgs and Xcs bydiscussing the difference between them.
These three objectives were examined by collecting
and analyzing water quality data of existing hot
springs.

CALCULATIONS
The mutual relations among the logarithm values

3.0

Cl2.0

H2SiO3
1.0

Ca

0.0
-1.0

0.0

系列1
線形 (系列1)

2+

F-

K+

Table 1 Standard of hot spring spa

SO42- 1.0

2.0

3.0

-1.0

≥25°C

Logarithm of the density of water quality≥1,000 mg/kg(a) A case where p-value is 1%≥250 mg/kg≥1 mg/kg≥10 mg/kg≥5 mg/kg≥10 mg/kg≥10 mg/kg≥1 mg/kg≥5 mg/kg≥1 mg/kg≥2 mg/kg≥1.3 mg/kg≥1 mg/kg≥1 mg/kg≥5 mg/kg≥50 mg/kg≥340 mg/kg≥2 × 10−9 Ci/kg≥1 × 10−8 mg/kg

s

Logarithm of the density of water quality

temperature
total solublecomponent
CO2
Li+
Si2+
Ba2+
Fe2+,Fe3+
Mn2+
H+
BrI−
F−
HAsO42−
HAsO2
S
HBO2
H2SiO3NaHCO3RnRa

y = 1.1046x - 0.1549
R² = 0.7542

Na+

3.0

Na+ y = 0.6473x + 0.0872
2.0

R² = 0.5672

H2SiO3
Cl-

1.0

Ca

線形 (系列1)

K+
0.0
-1.0

0.0

SO42-1.0

F-

2.0

-1.0

Logarithm of the density of water quality(b) Case where p-value is 5%
Fig. 1 Examples of a set of data.

500

系列1

2+

3.0

GEOMATE-Nagoya, Nov.13-15, 2013

the significance of the correlation R. Although theprocedure for calculating p-value using R and n isessential, it is widely explained in other books andhence not elaborated in this study.
When the p-value of R is larger than Pc, thecorrelation is not significant. From the second
hypothesis given in the Introduction, a high p-value
suggests that digging a new hot spring will not affectthe water of the existing hot spring.
In sections I and II of Fig. 2, where the p-value ismore than the threshold value Pc, the correlation is
not significant. In section I, there is no theoreticalplot. Therefore, in this study, Xc is defined as theminimum distance X of the plots in section II. The
possibility that the new hot springs affect theexisting ones is presumed small for this section.
On the other hand, in sections III and IV, thecorrelation is significant. For the range IV plot group,
even if the distance is longer than Xc, the correlationof water quality may be significant. Therefore, the
new hot spring may affect the existing spring.

p-value

Pc

Xc

X

Fig. 2 The condition Pc and selected Xc on X-(pvalue) plane, where each point indicates theresult for the hot-spring combinations.

Table 3 Major depth types
for each area

area
1
2
3
4
5

HOT SPRINGS USED FOR ANALYSIS
In this study, the prefecture shown in Fig. 3 wasused. Ten spa facilities for each of the five areas
were selected; that is, the water quality of 50 hot
springs was used. By combining all hot springs ineach area, a total of 45 sets of two hot spring
combinations were possible (i.e., 45 distances X andR coefficients for each area).
As shown in Table 3, in area 1, most hot springs
were deep. On the other hand, in area 5, which waswell known for its hot springs, most hot springs
were shallow. In areas 2, 3, and 4, deep hot springs
were more in number than shallow hot springs.

deeper than
1,000 m9
6
7
6
1

shallower
than 1,000 m
1
4
3
4
9

the major
type
deep
deep
deep
deep
shallow

Nagoya
area2

area1

N35°
area3

Osaka

area5
area4

RESULTS
N34°

Table2 Dataset used for analysis
water quality
Sodium ion 2, 3
Potassium ion 2, 3
Calcium ion 2, 3
Fluoride ion 1, 2
Chloride ion 2, 3
Sulfuric acid ion 2, 3
Metasilicic acid 1, 2

chemicalsymbols
Na+
K+
Ca2+
F−
Cl−
SO42−
H2SiO3

E136°

E137°

Fig. 3 Map of hot spring locations in each area.

1: water quality shown in the hot-spring standard
2: water quality shown in [2] and [3]3: water quality used in the trilinear diagram

501

Distance X between the two hot springs (m)(1) area 1

p-value

As some of the water qualities are numerically zero,
the logarithm of all data points could not becalculated. As the data number (n) was expected tobe constant, the R values for such cases were notused in this study. Therefore, the given numbers of R
were not always 45, as shown in Table 4. For areas
1–5, the numbers of plots were 36, 45, 45, 36, and45, respectively.
By using the concept of Xc and Pc as shown in Fig.
2, the combinations of the Xs and p-values wereseparated by Pc 5% as shown in Figs. 4 (1)–5).
There is no theoretical plot in section I because thevertical line is drawn for making such a situation.
Alternatively, there was no area without plots in thesection IV. This result was the similar for the
combination of Xs and p-values separated by Pc 1%.

p-value

GEOMATE-Nagoya, Nov.13-15, 2013

DISCUSSION
Xcs can also be explained using Figs. 5 (1)–(5),where each hot spring is shown as a plot. The five
figures in the left-hand column represent the raw
data.
The middle five figures present the distances whose
p-values are less than 5%. The right-hand-side
figures show the distances whose p-values are lessthan 1%.
In Figs. 5 (1)–(5), if the group of solid lines show
almost the same direction in one area, and yet if sucha group is not shown in the figures on the left, itsuggests that underground the water is flowing in thesame ground layer. However, this type of groupingof solid lines was difficult to see.

Distance X between the two hot springs (m)p-value(2) area 2

Distance X between the two hot springs (m)(3) area 3

p-value

1) The samples classified by Xc and Pc
As the combination samples of Xs and p-values
were classified as shown in Figs. 4 (1)–(4), each
could be counted without the samples having water
quality that is numerically zero (Table 4).
The four samples having the smallest distance had
p-values of 0.00001, 0.00040, 0.00202, and 0.00000
for distances of 0, 187, 331, and 392 m, respectively.
The order of these numbers means that the p-value
becomes very small as distance X becomes verysmall. Because such a small X is rare, it was lucky
for us that the p-value could be obtained.
For large distance X, the numbers of the samples forwhich there was a combination of X and p-value
were not small, as shown in the section IV in Table
4. Therefore, digging a new hot spring in such cases
may affect the existing hot spring located at a large
distance.

Distance X between the two hot springs (m)p-value(4) area 42) Order of Xc along the depthDistance X between the two hot springs (m)(5) area 5

In Table 5, for the four deep hot spring areas (areas

Fig. 4 Given p-values versus distance between
two hot springs, in which Pc 5% is applied.
502

GEOMATE-Nagoya, Nov.13-15, 2013

1–4), Xcs are distributed between 659 and 6641 m.
For the shallow hot spring area (area 5), Xcs are
distributed to 1512 m. Therefore, the relationshipbetween depth and Xcs was not a simple one.
3) Difference of the meaning about Xg and Xc
Prior to the analysis, the given Xcs werenumerically nearer to Xgs more than what was
expected, as depicted in the second row of Table 6.
As shown in Table 4, although section I is empty,
there are many plots in section IV. This indicatesthat the p-value which is larger than Pc cannot be
distinguished by distance X alone. Thus, correlationof the new hot spring’s water quality with anexisting spring located outside of the Xc range is notalways insignificant as shown in column (4) of
Table 6. This is despite the fact that correlation of
the new hot spring’s water quality with an existing
spring located within the Xc range should always besignificant, as shown in column (2) of Table 6.

(1) area 1 (raw data)(P-value <5%)(P-value <1%)(2) area 2 (raw data)(P-value <5%)(P-value < 1%)(3) area 3 (raw data)(P-value <5%)(P-value <1%)(4) area 4 (raw data)(P-value <5%)(P-value <1%)(5) area 5 (raw data)(P-value <5%)(P-value <1%)

CONCLUSIONSWith regard to the unclear phenomena occurring
very deep in the ground layer, the simple stochastic
view was applied because we were expecting some
simple rules. Most of the results seem to give somepower to existing hot spring owners. The results,
however, were not good for new hot spring owners
as the critical limiting distance was confirmed to be
insufficient for explaining the sustainable digging of
hot spring.

Table 4 Number of the samples of the set of X
and p-value
Pc 5%
Pc 1%
Area
1
2
3
4
5

I
0
0
0
0
0

II
5
15
3
19
12

III
24
6
2
1
7

IV
7
24
40
16
26

total
36
45
45
36
45

I
0
0
0
0
0

II
7
31
13
25
26

III
24
1
0
1
7

IV
5
13
32
10
12

0

10 km

Fig. 5 Distances given for Pc 5% or Pc 1%.

Table 6 Difference between Xg and Xc

total
36
45
45
36
45

Criticaldistance
Reason of
the distanceOrder ofthe distance

Table 5 Given critical distance,
where Pc indicates critical p-value
Major type of
Xc
Area
depth
Pc 5%
Pc 1%
1
deep
6641
6641
2
deep
2256
1200
3
deep
1668
824
4
deep
659
659
5
shallow
1512
1512

503

Xg shown in [1]Questionnaires,water balance, andheat balance.
300–500m or
1,000–2,000m as
explained in
Introduction

Xc
Stochastic approach

659–6,641m
from Table 5

Hot springs
at adistancesmallerthan thecriticaldistance(1) mutually
influenced.

(2) influenced
in the section III

Hot springs
at adistancelarger thanthe criticaldistance(3) not influenced.

(4) not influenced in
the section II

GEOMATE-Nagoya, Nov.13-15, 2013

Society of Hot Springs Science, 22-36, 2010 (inJapanese with English abstract)

References[1] Ministry of the Environment, Government ofJapan: Guideline for the Protection of Hot Spring
Resources, 2009 (in Japanese)[3] Mori Y, Yoshimura H, Maeda A, Shimura K,
Ohkuma K, Kondo M, Kajisa T: Investigation of the
Influence of Lift Pump Installation Based on the"Guideline for the Protection of Hot Spring
Resources", Hot Springs Science 60(2), The
Japanese Society of Hot Springs Science, 161-176,
2010 (in Japanese with English abstract)[2] Mori Y, Yoshimura H, Maeda A, Shimura K,
Ohkuma K, Ogawa M, Hashizume K, Nohara S,
Kondo M, Kajisa T: Geochemical Influence ofDrilling a New Hole Adjacent to an Existing Hot
Spring, Hot Springs Science 60(1), The Japanese504

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

IDENTIFICATION OF POLLUTANT SOURCE CHARACTERISTICS
UNDER UNCERTAINTY IN CONTAMINATED WATER RESOURCESSYSTEMS USING ADAPTIVE SIMULATED ANEALING AND FUZZY
LOGIC

Mahsa Amirabdollahian1,2 and Bithin Datta1,2
School of Engineering and Physical Sciences, James Cook University, Australia; 2CRC for Contamination
Assessment and Remediation of Environment, Australia

1

ABSTRACT
Effective environmental management and remediation strategies are required to remediate contaminatedwater resources. Accurate characterizing of unknown contaminant sources is vital for selection of appropriate
environmental management plan and reduction of long term remedial costs. In order to characterize the sourcesof contamination, the aquifer boundary conditions and hydrogeologic parameter values need to be estimated or
specified. In real life contaminated aquifers, often there are sparse and inaccurate information available. On theother hand, extensive collection of data is very costly. The uncertain and highly variable natures of water
resources systems affect the accuracy of contaminant source identification models.
In this study, an optimal source identification model incorporating Adaptive Simulated Annealing
optimization algorithm linked with the numerical flow and transport simulation models, is designed to identify
contaminant source characteristics. The fuzzy logic concept is used to identify the effect of hydrogeologicalparameter uncertainty on groundwater flow and transport simulation. The fuzzy membership values incorporate
the reliability of specified parameter values in to the optimization model. An illustrative study area is used toshow the potential applicability of the proposed methodology. The incorporation of fuzzy logic in source
identification model increases the applicability of contaminant source detection models in real-life contaminatedwater resources systems.
Keywords: Pollution Detection, Aquifer Contamination, Groundwater, Source Identification, Uncertainty.

available sparse and sometimes erroneousconcentration measurements at the site. Mainly
source identification includes a simulation problem,
like groundwater flow and pollutant transportmodels, which is used to estimate past phenomena or
predict future scenario. The estimated values arethen compared with observed values. Availability ofadequate data is vital regarding the structure ofsource identification procedure. However, acquiring
data is a cost and time intensive task.
The source identification model requires anaccurate flow and transport model to estimate thecontaminant concentration distribution in aquifer.
The lack of adequate geographic and parameter
information, results in uncertain groundwater andsolute transport model. The solution of source
identification model is highly sensitive tomeasurement errors either in the observation data ormodel parameters [1].
Various techniques has been proposed inliterature to characterize the contamination sources
including stochastic methods [2]; response matrix[3], [4]; embedded optimization [5] and linked
simulation-optimization [6], [7]. Amirabdollahian

INTRODUCTION
Groundwater as the major source of potable,
agricultural and industrial water is subject to various
sources of contamination. The first signs of thepresence of contaminate underground water may be
detected from the water extracted from current
extraction wells. Often surface water quality likerivers or lakes, is affected by contamination ofunderground water. The spread of pollution inunderground water increases the necessity todevelop efficient techniques for remediation ofcontaminated aquifer. The effectiveness of a
remediation strategy depends on how efficiently thecontamination source characteristics are identified.
Accurate identification of the contaminant sources
and reconstructing their release history plays animportant role in modeling of subsurface flow andtransport processes, and help to reduce the long-term
remedial costs.
The source identification problem deals with thespatial and temporal variations of the location,
activity duration, and the injection rate of thepollutant source and is mostly inferred from the505

GEOMATE-Nagoya, Nov.13-15, 2013and Datta [8] presented a comprehensive overview
iob, and the time period k.
kon different source identification methods.
can be defined as follows:
The weight w iob
Most of the techniques represented in literature
are designed for the case where the aquifer
k
k
(3)
w iob
1 / (cobsiob+ n) 2hydrogeological parameter values are known. Jha =and Datta [7] tested their proposed method under
Where n is a constant and it should be
uncertain hydrogeological parameter values. Theirsufficiently large so that errors at low concentrations
method is able to manage moderate degree of
do not dominate the solution [5]. The objective
uncertainty. By increasing the degree of uncertainty
function is constrained by the flow and transport
the accuracy and reliability of source identification
simulation models.
decreases.
In this study the linked simulation-optimization
Optimization Methodmodel is used to characterize the sources ofcontamination. The Adaptive Simulated Annealing
In this paper the ASA optimization method is(ASA) is utilized as the optimization method. In
utilized to characterize the sources of contamination.
contrast to deterministic viewpoint where all the
Simulated Annealing (SA) optimization starts from amodel parameters were considered known, in thefeasible solution and a specific objective function. A
proposed methodology the uncertainty in
new solution is randomly selected from its neighbors
hydrogeologic zonation and parameter values are
and the objective function is evaluated for the newconsidered using Fuzzy Logic concept. In this way
selected solution. If the new solution has a betterthe available sparse model parameter data, in
objective function value, the most recent solution isaddition to available uncertain information about
definitely better than the old one. Therefore, it ishydrogeologic zones are utilized to increase thethen accepted and the search moves to a new point
reliability of pollutant source characteristics
and continues from there. On the other hand, if theidentification.
new solution is not better than the current one, the
new solution may be or may not be accepted
METHODOLOGY
depending on the acceptance probability. The
acceptance probability is strongly influenced by the
The source identification model consists of an
choice of a parameter temperature (T). ASA is a
optimization algorithm linked to flow and transportvariant of SA in which the algorithm parameters thatprocess simulation models. The optimal solution iscontrol temperature schedule and random selection
obtained by minimizing the differences between
are automatically adjusted as the algorithm
observed and simulated values. The objective
progresses. This makes the algorithm more efficient
function for the optimization problem is defined as
and less sensitive to the user defined parameters thanfollow.
SA [9].
nkk

Min F1 =∑ ∑ µiobk (cest iobk − cobsiobk )2 w iobk / (cobsiobk )2

Simulation Model

k 1=
iob 1
=

(1)

The ASA based source identification model
estimates the source fluxes using a linked
simulation-optimization model. The simulation
model evaluates the contaminant concentration
values at monitoring locations corresponding tocandidate contaminant source characteristics.
Groundwater Flow and contaminant transport
simulation models used in this study are,
MODFLOW-2000 [10] and MT3DMS [11],respectively.
MODFLOW is a computer program thatnumerically solves the three-dimensional groundwater flow equation for a porous medium by using afinite-difference method. The MT3DMS transportmodel uses a mixed Eulerian-Lagrangian approachfor the solution of the three-dimensional advectivedispersive-reactive equation. The Lagrangian part ofthe method, used for solving the advection term,
employs the forward tracking Method of
Characteristics (MOC), the backward-tracking

Subject to:cest = f(x,y,z,D,q,R)(2)

The above constraint essentially represents the flow
and transport process simulation models.
Where:k=Concentration estimated by the simulation
cest iob
model at observation well location iob and at the endof time period k.
nk =Total number of concentration observation time
periods;
nob =Total number of observation wells;k=Observed concentration at well iob and at
cobsiob
the end of time period k;k=The fuzzy reliability factor for well iob and atµiob
the end of time period k;k=Weight corresponding to observation location
w iob
506

GEOMATE-Nagoya, Nov.13-15, 2013

p = power;
Power p determines the contribution of values atknown points in estimation of value at unknown
points with respect to distance between points withknown and unknown values. This means that higher
value of p results in using more near points withknown values by the IDW interpolation method.
The uncertainty in aquifer zonation with respect tohydraulic conductivity value is studied using
different p values in IDW interpolation method. To
calculate the fuzzy reliability factors, the fuzzy
membership function is utilized. The reliability
membership function is calculated using Equation 6.

Modified Method Of Characteristics (MMOC), or a
hybrid of these two methods. The Eulerian part ofthe method, used for solving the dispersion andchemical reaction terms, utilizes a conventional
block centered finite-difference method [11].
Fuzzy Reliability Factor
When there is inadequate available information
about the hydrogeologic zonation and parametervalues, the contaminant source identification model
is subjected to uncertainty. The simulation modelneeds exact aquifer parameter information toaccurately estimate contaminant concentration atmonitoring locations. In practice usually aninterpolation method is utilized to calculatehydrogeologic parameter values for entire aquifer
using sparse data. Substantial variation ofhydrogeologic parameter values in heterogeneousand non-uniform aquifers impose high level of
uncertainty to the contaminant source identification
model.
The hydraulic conductivity values are used by
the flow simulation model to generate the head
distribution in the study area. This head information
is used by the simulation model to calculatecontaminant concentration at different monitoring
locations.
In this study the inverse Distance Weighting(IDW) interpolation technique is used to evaluate
hydraulic conductivity value for entire aquifer using
available sparse information. The IDW is a typeof deterministic
method for multivariate
interpolation with a known scattered set of points.
The assigned values at unknown points arecomputed using a weighted average of the known
values at the known points. A general form offinding an interpolated value u at a given
point x based on samples u i =u(x i ) for i=1,2,..,N
using IDW is as below.
Nv (x) u iu(x) = ∑ Ni
i =0
∑ v j (x)

k
k
k
k
µiob
=1 − (cest iob,1− cest iob) 2 / (cest iob)2kis estimated concentration values
Where cest iob,1obtained using simulation model at observation welllocation iob and at the end of time period k, with
p=M 1 for the IDW interpolation method (equation 5).
kis estimated concentration values obtained
cest iob
using simulation model at observation well location
iob and at the end of time period k, with p=M 2 for
the IDW interpolation method (equation 5). In the
optimal source identification model (equation 1) theconcentration estimations are based on p=M 2 . Whenthe available information about field hydraulicconductivity zonation is not adequate, theconcentration values estimated using simulation
model will not be precise. On the other hand, there
would be large discrepancy between simulated
concentrations using two different p values by the
IDW interpolation technique. Therefore, the fuzzy
reliability factor will be less than one.
The fuzzy reliability factor for each observation
location and at the end of each time period is
estimated
progressively
using
optimization
generated candidate source characteristics.
PERFORMANCE EVALUATION(4)
Performance of the developed methodology isevaluated using synthetic hydrogeologic data. The
advantage of using synthetic data is that the true
source characteristics are known for evaluation. This
allows for the testing of the source identification
methodology. Figure 1 shows the hypotheticalaquifer study area. There are three candidate
locations for contamination sources. Two of them
are active sources and the third one is dummysource. There are two active extraction wells and 9
monitoring locations. The study area is 1500 meterby 1000 meter and is 40 meter deep. The threedimensional model of aquifer includes two layers,
each of 30 rows and 20 columns. The hydraulicconductivity is generated using truncated Latin
hypercube and lognormal distribution.

j= 0

Where:vi (x) =1d(x, x i ) p

(6)

(5)

u(x) =Interpolated value at given location x;
N =Number of nearest points which are utilized toestimate interpolated value;u i =known value corresponding to point i;v j =Weight corresponding to point i;d(x, x i ) =distance between point x and x i ;507

GEOMATE-Nagoya, Nov.13-15, 2013

Three different zones with respect to hydraulicconductivity value are considered. The mean
hydraulic conductivity values for low, moderate andhigh permeable zones are 3, 10 and 20 m/day,
respectively. The standard deviation is 0.1 times
mean value for all zones. These hydraulicconductivities represent actual field condition andare generated at 50 meter intervals of the study area.
Thesimulation
model
requireshydraulicconductivity values at each node. These values wereobtained by interpolation using Kriging. The
resulting filed is utilized by the simulation model toestimate the spatial and temporal concentration
values. Figure 2 shows the generated actual
hydraulic conductivity field.
To evaluate the performance of the proposed
methodology the hydraulic conductivity is assumed
to be uncertain. Therefore the actual hydraulicconductivity values are assumed to be known at
every 300 meters distance. By this assumption the
known actual hydraulic conductivity values are
reduced from 1303 values to 61 values. Using these61 values, the uncertain hydraulic conductivity fieldis generated by interpolating the available 610
values to entire aquifer using IDW technique. The
selected p value is 2.
To conduct the fuzzy ASA source identification
the fuzzy reliability factor needs to be calculatedusing candidate source characteristics. The fuzzy
membership function is estimated using equation 6.
The selected M 1 and M 2 values are 4 and 2,
respectively. Figures 3a and 3b show the hydraulicconductivity generated fields using IDW method. In
Figs 3a and 3b, the p value (equation 5) is set to 2

Fig. 1and 4, respectively. Since the hydraulic conductivity
data used to generate both fields is the same, theillustrated difference is due to uncertainty and lackof adequate amount of data.
RESULTS AND DISCUSSION
Table 1, 2 and 3 show the results of source
identification model for sources 1, 2 and 3,
respectively. In these tables, the first row shows theactual source fluxes during each stress period. The
fluxes corresponding to source 2 is zero whichmeans that it is a dummy source.
Second rows show the result of crisp source
identification model solution where there isunaccounted uncertainty in the estimation of
hydraulic conductivity field. For the crisp source
identification the ASA optimization model uses thesame objective function (Equation 1). However, in
this case the fuzzy reliability factor is considered to
be always equal to one.
The huge discrepancy between the resulting
source fluxes and actual ones show the deficiency ofthe crisp source identification model in estimatingof source characteristics while there is inadequate
available data for the hydraulic conductivity field
The third rows show the result of fuzzy ASA
source identification model. Comparing the results
show that the fuzzy model is able to increase theaccuracy of the source identification.
Results show that the use of fuzzy logic can
improve the source identification results by 47.3 and25.6 percent for sources one and three, respectively.

Study area

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GEOMATE-Nagoya, Nov.13-15, 2013

20.2
17.6
15.1
12.5
9.8
7.2
4.6

Table 2 Estimated contamination fluxes for sourcetwo (g/s)
MethodStressStressStressPeriod 1
Period 2
Period 3
a
0
0
0
b
0.3
9.55
15.6
c
1.2
11.5
19.2
Note: a: Actual source fluxesb) Result of crisp source identification.
c) Result of fuzzy ASA source identification.

Fig. 2

Actual hydraulic conductivity values(m/day) (Dot points show the candidate
source locations)

Table 3 Estimated contamination fluxes for source
three (g/s)

Although both models are not able to specify
zero fluxes for source two (dummy source), theestimated source fluxes by both models are small
comparing to the magnitude of flux for othersources. However, the performance of both models
will improve if more precise information about
hydraulic conductivity field or more monitoring data
are actually available. Since the inputs for the flow
simulation model have associated high level of
uncertainty, limited accuracy in source identification
results is expected. However, by using the fuzzymodel, the error in estimation of source fluxes has
been reduced. Table 4 shows the estimation error
using crisp and fuzzy ASA source identification
models, and demonstrates improvement inestimation of source fluxes using fuzzy logic
concept.

MethodStressStressStressPeriod 1
Period 2
Period 3
a
95
85
75
b
39.3
65.1
52.1
c
40.68
78.8
62.3
Note: a: Actual source fluxesb) Result of crisp source identification.
c) Result of fuzzy ASA source identification.
Table 4 Error in estimation of contamination fluxes(g/s) and the improvement percentage
SourceSource
1
134
70.7
47.3

Source
2
25.45
31.9
-*

Source
3
98.5
73.22
25.7

b
c
Improvement(%)
Note: b) Result of crisp source identification.
c) Result of fuzzy ASA source identification* Source two is dummy.

Table 1 Estimated contamination fluxes for source
one (g/s)
MethodStressStressStressPeriod 1
Period 2
Period 3
a
70
90
35
b
5.7
40.4
55.1
c
46.9
59.7
52.3
Note: a: Actual source fluxesb) Result of crisp source identification.
c) Result of fuzzy ASA source identification.

CONCLUSION
A new methodology for unknown groundwaterpollution source identification, using Adaptive
Simulated Annealing (ASA), linked simulationoptimization, and fuzzy logic is proposed.
Uncertainties in hydrogeologic parameters areincorporated by using fuzzy membership function.
Limited performance evaluations show the
improvement in source identification using the
proposed methodology.

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GEOMATE-Nagoya, Nov.13-15, 2013

21.4
18.8
16.2
13.5
10.9
8.3
5.6

(a)
Fig. 3(b)

Uncertain hydraulic conductivity fields (m/day). Generated using IDW interpolation method where a)p=2; and b) p=4[7] Jha, M, and Datta, B, “Three dimensional
groundwatercontamination
sourceidentification
using
adaptive
simulatedannealing”, J. of Hydrologic Engineering, Vol.
18, No. 3. 2012, pp. 307-313.
[8] Amirabdollahian,M,
andDatta,
B,“Identificationofcontaminantsourcecharacteristics and monitoring network designin groundwater aquifers: an overview”, J. ofEnvironmental Protection, accepted, 2013.
[9] Zheng C, and Bennett, GD, Applied
contaminant transport modeling. New York:
Wiley-Interscience, 2002.
[10] Zheng C, Hill, MC, and Hsieh PA,
MODFLOW-2000, the U.S. Geological Survey
Modular Ground-Water Model- User guid to the
LMT6 Package, the linkage with MT3DMS for
Multi-Species Mass Transport Modeling.
Denver, Colorado: U.S.G. Survey, 2001.
[11] Zheng C, and Wang, PP, A Modular ThreeDimensional Multispecies Transport Model for
simulation of advection, dispersion, andchemical reactions of contaminants ingroundwater systems. Documentation anduser’s guide. Denver, Colorado: U.S.G. Survey,
1999.

REFERENCES[1] Sun NZ, Inverse problems in groundwatermodeling. Boston: Kluwer academic, 1994.
[2] Gelhar LW, “Stochastic subsurface hydrology
from theory to applications”, Water Resource
Research, Vol. 22, No. 9. 1986, pp. 135-145.
[3] Gorelick, SM, Evans B, and Remson, I,“Identifying Sources of Groundwater Pollution:
An Optimization Approach”, Water Resource
Research, Vol. 19, No. 3. 1983, pp. 779-790.
[4] Datta B. et al., Development of an Expert
System Embedding Pattern Recognition
Techniques for Pollution Source Identification.
Virginia: National Technical Information
Service, 1989.
[5] Mahar, PS, and Datta, B, “Optimal
identification of ground-Water pollution sources
and parameter estimation”, Water Resource
Planning and Management- ASCE, Vol. 127,
No. 1. 2001, pp. 20-29.
[6] Chadalavada, S, Datta, B, and Naidu, R,“Optimalidentificationofgroundwaterpollution sources using feedback monitoring
information: a case study”, Environmental
Forensics, Vol. 13, No. 2. 2012, pp. 140-153

510

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

POINT-BASED RENDERINGFOR MASSIVE POINT CLOUD VISUALIZATION
Masafumi Nakagawa
Department of Civil Engineering, Shibaura Institute of Technology, Japan

ABSTRACTA laser scanner can acquire a 3-D point cloud by measuring the distance to a surface and the scanning angles.
Accurate 3-D point data are used for various applications in urban areas. An advantage of 3-D point-cloud data isthat it allows accurate display from an arbitrary viewpoint. In contrast, panoramic imagery has the advantage ofproviding more attractive images with fewer data. We test whether these advantages can be combined by a pointcloud projection into panoramic space. Our objective is to develop a point-based rendering application with asimpl filtering algorithm, which we call a layered image-based depth arrangement refiner for versatile rendering(LIDAR VR). We have focused on the following features. First, panoramic imagery can be generated fromarbitrary viewpoints from several observation data sets. Second, a spatial interpolation with rendering results can
reduce the processing task. These features have been verified using case studies.
Keywords: Laser scanning data, Point-cloud, Point-based rendering, Spatial interpolation

inefficient at representing urban and natural objects
as GIS data. In particular, we consider that a simpler
filtering algorithm is important to achieve highvolumes of point-cloud processing with high speeds.
Thus, our objective is to develop a point-based
rendering application with a simpler filtering
algorithm, which we call a layered image [13] based
depth arrangement refiner for versatile rendering(LIDAR VR). We have focused on the following
features. The first feature is panoramic imagery
generation with a translated viewpoint from several
observation data sets. In general, an image from aviewpoint should be created from an observation.
Moreover, when panoramic images are taken fromseveral viewpoints, position data from RTK-GPS
and rotation data from a gyrosensor are required to
calculate relative positions and rotations between
cameras. LIDAR VR images from many viewpoints
can be simulated from observation data through our
proposed approach. Moreover, the proposed
methodology can simulate camera translation andgenerate new simulated imagery without the position
and rotation sensors. The second feature is real-time
spatial interpolation. In general point-cloudinterpolation processing, missing points can beinterpolated by a traditional 3-D filter from otherpoints in the space. This type of 3-D interpolation
requires huge amounts of processing capability.
Therefore, we tested whether spatial interpolation
with rendered results can reduce the processing task.
We have also developed a pixel-selectable averaging
filter. This function can replace spatial filtering in 3D space by spatial filtering in 2-D space with realtime processing. Thus, any quality reduction causedby viewpoint translation can be solved in real time.

INTRODUCTION
Accurate 3-D scanning techniques such as
terrestrial laser scanning are used for various
applications such as geographical information
systems (GIS) data acquisition in urban areas [1]-[3].
A laser scanner can acquire a 3-D point cloud by
measuring the distance to a surface and the scanning
angles. Moreover, a calibrated digital camera with alaser scanner can be used to acquire color
information with the point-cloud data.
An advantage of 3-D point-cloud data is that they
allow accurate display from an arbitrary viewpointand 3-D modeling [4]-[7]. In contrast, panoramic
imagery has the advantage of providing more
attractive images with fewer data [8], [9]. In
addition, panoramic image georeferencing anddistance-value-added panoramic image processing
show that both advantages can be combined for 3DGIS visualization [10], [11]. Thus, we tested
whether these advantages can be combined by apoint-cloud projection into panoramic space.
Point-cloud visualization has two issues. The
first is a near-far problem caused by distancedifferences from the viewpoint to scanned points.
The second is a transparency effect caused byrendering hidden points among near-side points.
These effects degrade the quality of a point-cloudvisualization.
Splat-based ray tracing [12] is a methodologythat generates a photorealistic curved surface on a
panoramic view using normal vectors from pointcloud data. A problem is the large amount of timerequired for surface generation in the 3-D work
space. Furthermore, the curved-surface description is511

GEOMATE-Nagoya, Nov.13-15, 2013

Based on this spherical panorama, the range data
are generated using the point cloud with a translated
viewpoint, as shown in Figure 2. When points from
P 1 to P 10 are projected into a panorama space
generated from a viewpoint X o , these points arearranged continuously from P 1 to P 10 in the range
data. An azimuth or elevation angle from aviewpoint X o to a measured point P 1 is denoted as
R o . When the same scene is captured from adifferent viewpoint X t , the angle from the viewpoint
X t to the measured point P 1 is denoted as R t . The
position of the projected point in the range data
moves according to the change in angle from R o to
Rt.

METHODOLOGY
The processing flow of the proposed
methodology is described below. First, sensors
acquire a point cloud with additional color data such
as RGB data or intensity data. The sensor position isdefined as the origin point in a 3-D workspace. If
color data cannot be acquired, distance values areattached to a color index. Thus, for example, we canuse a laser scanner or a stereo camera. Second, a
LIDAR VR image from the simulated viewpoint isgenerated using the point cloud. Finally, thegenerated LIDAR VR image is filtered to generatemissing points in the rendered result using distancevalues between the viewpoint and objects.

Real surface

Overwrite P1
P1

LIDAR VR image generation using point-cloud

P2
P3 P

Ro
Xo

The colored point cloud is projected from 3-D space
to panorama space. This transformation simplifies
viewpoint translation, filtering, and point-cloudbrowsing. The LIDAR VR data consist of a
panorama model and range data. The panorama
space can be a spherical model, a hemisphericalmodel, a cylindrical model, or a cubic model. Here,the spherical model is described. The measured
point data are projected onto a spherical surface, andcan be represented as range data as shown in Figure
1. The range data can preserve measured point datasuch as X, Y, Z, R, G, B, and intensity data in thepanorama space in a multilayer style. Azimuth andelevation angles from the viewpoint to the measured
points can be calculated using 3-D vectors generated
from the view position and the measured points.
When azimuth angles and elevation angles areconverted to column counts and row counts in therange data with adequate spatial angle resolution, aspherical panorama image can be generated from thepoint cloud.
Spherical panorama model

P6

Range data
Rt

Elevation

P8

Occluded points

Fig. 2 Point distribution calculated by viewpointtranslation in range data, occlusion detection using
the point cloud, and point-cloud interpolation with
distance information
Filtering using distance values
viewpoint and measured points

betweena

Three types of filtering are performed after the
viewpoint translation, as shown in Figure 2. The first
filtering is the overwriting of occluded points. Whenthe viewpoint is translated to X t , the projected point
P 1 becomes an occluded point behind P 2 . Therefore,
P 1 is overwritten by P 2 .
The second filtering is the generation of new
points in the no-data space. This occurs when the
viewpoint is translated to X t and a no-data space
exists between the projected points P 3 and P 4 . Thus,
Figure 2 shows that P new1 is generated.

↑↓

The third filtering is the detection of occluded
points and generation of new points to replacedetected occluded points. When the viewpoint istranslated to X t , point P 8 exists between points P 9
and P 10 after the first filtering. However, the actual
point P 8 should be occluded because the point P 8
exists behind the real surface. Therefore, theoccluded point P 8 should be given a new distancevalue as P new2 , calculated using interpolation
processing and the distance values of points P 9 andP10. In addition, new points are generated with the
pixel-selectable averaging filter developed in thisresearch, which we now describe.

Range image
・Azimuth・Elevation

Pnew2
P10

Delete occluded points andGenerate a new point Pnew2

3D vector from viewpoint to measured point

・X,Y,Z・Viewpoint
・R,G,B, Intensity

P7

Generate a new point Pnew1“Projected point” (X,Y,Z), (R,G,B), (Intensity)

Point cloud

P9

Xt

Azimuth→Projected point

No-data space
new1
P4

P5

Range image (Panoramic image)“Measured point” (X,Y,Z), (R,G,B), (Intensity)

Occluded point

・Row index
・Column index
・R,G,B, Intensity

Fig. 1 LIDAR VR consisting of a spherical
panorama (left side of the figure) and range data(right side of the figure)512

GEOMATE-Nagoya, Nov.13-15, 2013

Pixel-selectable averaging filter

1 m from experience.
Finally, an average distance value from theviewpoint to the valid points is calculated. Then, thefocus point value is overwritten by the average value.
However, when the focus point has a distance value
within the search range, the point is defined as thenearest surface approximately, and the overwriting
processing is not performed in that case. This
processing sequence is applied to all points.

In general, when an image is transformed, eachpixel in the image has its color data resampled byusing pixel values around it. Points projected into
the panorama space are also processed using asimilar technique to improve the quality of the range
data. However, general resampling techniques suchas nearest interpolation reduce the quality of therange data because valid, erroneous, and missing
data are blended in the resampling. Therefore, weapply a focused pixel-selectable averaging filter tothis problem. The filtering processing uses only
valid pixels around a pixel for the resampling, asshown in Figure 3. This processing is equivalent tomissing-point regeneration without reducing
geometrical accuracy by a uniform smoothing effect.
For example, a three by three block of pixels in therange data set is prepared. The center point in theblock is the focus point in the range data set. Whenthe focus point is a missing point and the otherpoints are valid points in the point cloud, a new pixel
value is given to the focus point using the otherpoints. This processing is applied to each channel in
the RGB image and to an intensity image.
Thus, this processing uses only valid points in
the range data. The detailed flow of the pixelselectable averaging filter is described as follows.
First, the data are checked to see whether valid
points exist. When more than one pixel in a three by
three block exists, including the focus point and thepoints around it, processing proceeds to the next step.
If no point exists in the block, the next processing
step is omitted.
Second, the number of valid pixels in the block is
counted. When there are more than two valid pixels,
the processing proceeds to the next step. If there is
only one valid pixel and the extracted point is thefocus point, it is deleted as spike noise. If there is
only one valid pixel and the extracted point is not
the focus point, the focus point remains without thefiltering processing.
Third, after these point-extraction steps, a rangeof search distances is given to extract valid points.
The start value of the search range is the distancefrom the viewpoint to the nearest point found among
the extracted points, while the end value is the startvalue plus a defined distance parameter. Then, allvalid points in the block within the search range are
extracted. The defined distance parameter depends
on the continuity of the points in the point cloud. For
example, when trees and building walls aremeasured, the defined parameter would be 10 cm to

Near

Far

“Near point” and “Near 8 points”
Copy“Far point” and “Far 8 points”
Copy“Far point” & “Near 8 points”
Interpolation(1) Reject far points(2) Calculate an average of near points

Fig. 3

Pixel-selectable averaging filter

EXPERIMENTS
We conducted experiments using a point cloud
taken from a terrestrial laser scanner VZ-400
produced by RIEGL Laser Measurement Systems
GmbH. This scanner can acquire panoramic distancedata and corresponding color data over 360° in thehorizontal direction.
We prepared three test sites. The first site was a
gymnasium consisting of flat planes. The second site
was a park (Tsukuba city) that has good visibility,
including flat ground planes and individual trees.
The third site was a historical building(“Goryokaku” in Hokkaido), including tiles, facades,
and signboards.
RESULTS
Gymnasium data set
We acquired 200 million points in the indoor and513

GEOMATE-Nagoya, Nov.13-15, 2013

outdoor environments from 10 viewpoints. A
panoramic image (1800 × 450 pixels) was renderedwith 0.20° angle resolution after 3 cm3 spatial
filtering. The average processing time for the
panoramic image conversion and iterative filterings(three times) by parallel programming in C was 0.13
s (Intel Core i7, 2.80 GHz, eight threads) for oneshot generation in multiple viewpoints without file
I/O. Figure 4 shows a part of the panoramic imagegeneration result after a viewpoint translation.
Figure 5 shows the same part of the panoramic
image-generation result after viewpoint translationand filtering.
Fig. 6

Part of an ortho image map

Fig. 4
Part of the panoramic image-generation
result after viewpoint translation

Fig. 7
Part of the panoramic image-generation
result after viewpoint translation

Fig. 5
Part of the panoramic image-generation
result after viewpoint translation and filtering

Fig. 8
Part of the panoramic image-generation
result after viewpoint translation and filtering

Park (Tsukuba city) data set

Historical building (“Goryokaku” in Hokkaido)
data set

We acquired 400 million points in outdoor
environment from 28 viewpoints. A part of an ortho
image map generated from the point cloud is shownin Figure 6. A panoramic image (3600 × 900 pixels)
was rendered with 0.10° angle resolution after 1 cm3
spatial filtering. Figure 7 shows a part of thepanoramic image-generation result after a viewpointtranslation. Figure 8 shows the same part of thepanoramic image generation result after viewpointtranslation and filtering.

We acquired 800 million points in outdoor
environment from 30 viewpoints. A panoramic
image (3600 × 900 pixels) was rendered with 0.10°
angle resolution after 1 cm3 spatial filtering. Figure 9shows a part of the panoramic image-generation
result after a viewpoint translation. Figure 10 shows
the same part of the panoramic image-generation
result after viewpoint translation and filtering.

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GEOMATE-Nagoya, Nov.13-15, 2013_____

Fig. 9Fig. 10

Part of the panoramic image-generation result after viewpoint translation

Part of the panoramic image-generation result after viewpoint translation and filtering

processing for missing points in the panorama space
generates new point data from the new viewpoint.
Thus, almost all of the missing data are recovered
after filtering. As a result, a higher-quality image is
generated, as shown in Figure 5. Finally, although
the panorama projection requires a long processing
time in proportion to the number of points, we haveconfirmed that the proposed overall processing canbe achieved in real time. Moreover, even if missing
points remain, they can be removed via two or moreiterative filterings in most cases.
In addition, Figure 11 shows an example ofmissing points caused by puddles. Generally,
median filtering is applied to improve a noise affectin image processing. However, missing points areinterpolated from surrounding pixels with noise.
Thus, a blending effect occurs, as shown in Figure
12. We have confirmed that our approach can avoid
this blending effect, as shown in Figure 13.
However, larger translations of the viewpoint
expose more occlusions in the point cloud.
Therefore, even if iterative processing is applied to a
generated image from a more distant viewpoint, theinterleaved pixels may not be correct. This is not a
critical problem because a common interpolation isundesirable in a case with data.

DISCUSSION
We can verify the features of our LIDAR VR
generation as follows. The first feature is panoramic
image generation with an arbitrary viewpoint. We
have verified that the proposed methodology can
successfully generate panoramic images with several
observation data sets from one viewpoint
automatically. Moreover, we have verified thatcamera movement and rotation from a viewpoint canbe simulated successfully to generate a new image
without a position sensor such as RTK-GPS or adirection sensor such as a digital compass. In
addition, we have confirmed that continuous camera
trajectory simulation can achieve panoramic imagery
generation from accurate viewpoints.
The second feature is real-time spatial
interpolation using the point cloud. We haveconfirmed that spatial interpolation with rendering
can be processed in real time (approximately 8 fps
with parallel processing) including panoramic image
generation. First, a panorama projection is
performed successfully as shown in Figure 4. Next,
a viewpoint translation simulates a new panoramic
image with some missing point data as aninterleaved pixel array. Then, the interpolation
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GEOMATE-Nagoya, Nov.13-15, 2013

Affairs and Communications, Japan. This work isalso supported by RIEGL Japan Co. Ltd. in our dataacquisition.
REFERENCES

Fig. 11[1] Jan B, “Terrestrial LiDAR in Urban Data
Acquisition”, Photogrammetric Week ’09,
pp.169 – 178, 2009.
[2] Shi P, George V, “Knowledge based
reconstruction of building models fromterrestrial laser scanning data” ISPRS Journal of
Photogrammetry and Remote Sensing, Volume64, Issue 6, pp. 575–584, 2009.
[3] Eloïse D, Renaud B, Caroline B, “Towards roadmodelling from terrestrial laser points”, IAPRS,
Vol. XXXVIII, Part 3A, pp.293-298, 2010.
[4] George V, “Advanced point cloud processing”,
In: Photogrammetric Week '09, pp. 137-146,
2009.
[5] Remondino F, “From point cloud to surface :the modeling and visualization problem”,
International Archives of the Photogrammetry,
Remote Sensing and Spatial Information
Sciences, Vol. XXXIV-5/W10, 2003.
[6] Augustine T, Chun.F H, I-Chou H, Wen-Kai
Liu, “Plane and Boundary Extraction from
LiDAR data using Clustering and Convex Hull
Projection”, International Archives of the
Photogrammetry, Remote Sensing and Spatial
Information Sciences, Vol. XXXVIII - Part 3A,
pp.175-179, 2010.
[7] Jan B, Maria P, “From Point Samples to
Surfaces”, On Meshing and Alternatives ISPRS
Image Engineering and Vision Metrology,
XXXVI, pp.50 – 55, 2006.
[8] Shenchang, E.C, “QuickTime VR - An imagebased approach to virtual environment
navigation”.
Proceedingsof
ACM
SIGGRAPH’95: 29–38, 1995.
[9] Katsushi I, Masao S, Hiroshi K and Imari S,“Constructing Virtual cities by Using
Panoramic Images”, International Journal ofComputer Vision, Vol. 58, No.3: 237-247,
2004.
[10] Jason D, “An approach to virtual environmentsfor visualization using linked geo-referenced
panoramic imagery”, Computers, Environment
and Urban Systems 24, 127-152, 2000.
[11] Edward V, Sisi Z and Sander D, “Distancevalue-added panoramic images as the base data
model
for
3D-GIS”,
Panoramic
Photogrammetry Workshop, 2005.
[12] Lars L, Karsten M and Paul R, “Splat-based
Ray Tracing of Point Clouds”, Journal of
WSCG, Vol.15, Issue: 1-3: 51-58, 2007.
[13] Jonathan S, Steven Gortler, L. He, and Richard
S, “Layered Depth Images”, SIGGRAPH '98,
pp.231-242, 1998.

Input point cloudFig. 12Result after median filtering

Fig. 13

Result after proposed filtering

SUMMARY
We have developed a point-based rendering
application called LIDAR VR with high-speed
spatial interpolation using a point cloud. Thisapplication has achieved not only a transformationfrom point cloud to panoramic image but also
automatic regeneration of missing points in therendered result from a chosen viewpoint. Moreover,
we have focused on two features, panoramic
imagery generation from arbitrary viewpoints andthe processing task reduction in spatial interpolation
with rendering results. Finally, we have presented
results that confirm these features in case studies.
ACKNOWLEDGEMENTS
This work is supported by the Strategic
Information and Communications R&D Promotion
Programme (SCOPE) of the Ministry of Internal
516

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

REDRAWING AN UNKNOWN MASONRY CAISSON BY
GEOPHYSICAL METHODS

1

Ming-Hung Chen1, Shun-Min Lee2, Yung-Chuan Chou2, Yao-Jen Hsu2 and Chih-Hsin Hu3
China Engineering Consultants, Inc., Taiwan; 2 CECI Engineering Consultants, Inc., Taiwan; 3HCKGeophysical Company, Taiwan

ABSTRACTAn old railway bridge built in 1911 was damaged in a series of typhoon events from 2005 to 2009. The rail
bridge was out of service since a new bridge was built beside, and this old bridge became as a reserved heritage.
Knowing the true depth and size of the caisson is significant before the rehabilitation designing. Unfortunately,
the original design plot was not well stored for such an aged structure, which leads to extremely difficult
situation when the local government considered rehabilitating this vulnerable historical structure. Hence, sevendifferent non-destructive investigation ways were implemented to confirm the real geometry of pier beneath theground surface. These methods include 2D & 3D ERI (electrical resistivity image), cross-hole resistivity
tomography, ultra-seismic, parallel seismic, borehole GPR (ground penetration radar), and multiple offsets ofvertical seismic profiling. All the tests were used to finalize the estimation of actual foundation depth withconfidence. Not alike most reinforcement concrete structures constructed with steel bar inside, a masonry
structure is more challengeable when employing resistivity method.
When doing the NDT tests, three boreholes were drilled to survey the subsurface soil property at site. These
investigations gave not only the opportunity to plot stratum profiles of the investigating area, but also provided
essential information for judging the resistivity variation between primary deposits and artificial configurations.
A proving excavation was also executed within the overall survey work. All the test results conclude thatgeophysical survey could explore the masonry structures nondestructively, when it is well designed and finely
conducted.
Keywords: NDT, bridge, caisson, masonry, geophysics
electrical resistivity imaging method and other wide
variety of geophysical or Non Destructive Tests(NDT). The tops of footings and pile caps may beburied below riprap, backfill, and/or channel soils.
The bridge conditions may range from dry riverbed
to marsh to flowing water with water conditions
ranging from fresh to brackish to saltwater. The
actual type of NDT method chosen is site specificdepending on access, foundation configuration,
nature of subsurface soils, etc.
Olson et al. [1] studied some NDTdeterminations of unknown bridge foundations interms of their capabilities and limitations. Six
surface methods and four borehole methods werediscussed. Wightman et al. [2] summarized some
Surface NDT Methods and Borehole NDT Methods
to determine the unknown depth of foundations.

INTRODUCTION
The design drawings of bridges built decades ago
were mostly lost and can not assure the actual
penetration depth and size of pier foundations. These
unknown bridge foundations pose a significant
problem to the bridge managing agencies because ofscour vulnerability concerns. The foundation depth
information in particular is needed to achieve an
accurate scour evaluation at each bridge site, alongwith as much other information on foundation type,geometry, materials, and subsurface conditions as
can be obtained. Assessing and characterizing pierfoundations at existing bridges for scouring problem
has become an essentially necessary task.
Surface geophysics can provide information
concerning substructure geometry and relevantmaterial properties. The methodologies currently
available to determine unknown foundations can begrouped as (1) direct methods such as probing,augering, drilling or digging, (2) deductive methods
with borings alongside the foundation such asparallel seismic method, borehole ground
penetration radar method, vertical seismic profiling
method, cross-hole electrical resistivity tomographymethod and, (3) surface interpolation methods suchas seismic refraction method, ultra-seismic method,BACKGROUNDS AND ENVIROMENTAL
CONDITIONSThe historical rail bridge selected in this study
was built in 1911~1913 by Japanese technicians.
The old bridge was assigned as national heritage andretired from service in 1987 as a new bridge
constructed alongside. It crosses a wide and flat river
section in alluvial plain field. Total length of the rail
517

GEOMATE-Nagoya, Nov.13-15, 2013bridge is 1,526 m with 23 brick-masonry-made piers
along with simple supported steel truss
superstructure. After a series of typhoon events from2005 to 2009, several piers were destroyed inscouring. Some existed piers were temporally
reinforced by micro-piles as shown in Fig. 1.

There were seven test methods adopted in this study
as: 2D & 3D ERI, ultra-seismic, parallel seismic,
cross-hole resistivity tomography, borehole ground
penetration radar, and multiple offsets of verticalseismic profiling. Although an excavation can’t beclassified as a nondestructive test, it is agreed to be
the most convincing manner. Generally speaking, it
is unusual to put so many various ways to be appliedat the same time. The only explanation is theinvestigating team did really want to discover thetrue solution of foundation geometry,layer 1RESULTSlayer 2The entire investigation process took months tofinish. The process should be divided into twophases, separated by the proof excavation. A
preliminary survey was executed in Phase I,
followed by the proof excavation thereafter. The
proof excavation, however, gave the answer that the
preliminary conclusion needs to be corrected.
Therefore, some supplementary tests were added togain better solution in Phase II. In Phase II the
Borehole NDT Methods were mainly taken into
account. Results from each test are illustrated asfollows.

layer 3Fig. 1

An existed pier in the water way withtemporally reinforced by micro-piles

From Fig. 1, the upper part of pier is formed by 3
different layers. The investigated pier is illustrated
as Fig. 2 (pointed by the yellow arrow). For
designing an effectively strengthen method, it isnecessary to realize the actual depth of the existed
pier foundations. For that reason, the bridge owneroriginated an investigation project to confirm theactual depth of these foundations. For these masonrypiers, however, without steel reinforced rebar inside
cuts the advantage of judging the distinct resistivity
variation between metal and soil, which leads toevaluate through resistivity methods become moredifficult.

Phase I2D ERIFor conducting 2D Electrical Resistivity Image,survey line was deployed along the longitudinal axisof bridge to test the resistivity of undergroundmaterials. In Fig. 3, there is a clear boundary at 5 m
below ground surface, which refers to the interface
between granite and brick (layer 3 and layer 4). The
bottom of foundation is unrevealed in 2D ERI since
the lower part on the image exhibits uniform
resistivity distribution.
高
30

端

BH-4

20
15

砂

砂

5

東 端

P6

P5
/土

BH-6

/礫 石

砂

/礫 石

10

護 墩 鼎
塊 干 擾

0

黏 土

-5
0

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140 145 150 155 160

Distance (m)studied pier0 40 80 120 160 200 240 280 320 360 400 500 6001000ohm-m

黏 土Fig. 3Fig. 2

屏

P4-P6

P4

25

Elevation (m)

雄

/

砂

/

礫 石

2D ERI image profile

The environmental condition of studied pier
3D ERIINSPECTION METHODS
3D ERI was achieved by two perpendicularsurvey lines to construct a set of cross images at thecrossing location. Again, an obvious interface wasindicated at -5 m as shown in Fig. 4, same as 2D
ERI. According to 2D and 3D ERI results, as has
been mentioned, the resistivity methods can not get

To evaluate the real depth of foundation, all thepotential and available methods were applied on thisstudy case. The tests comprise Surface NDTMethods and Borehole NDT Methods, as well as a
proof excavation was also conducted at the same site.
518

GEOMATE-Nagoya, Nov.13-15, 2013

well outcomes since no steel rebar consisted inside
the foundation. The shallower part of foundationshows lower electrical resistance is constructed by
granite. Below the granite is made by brick, where
resistance becomes closer to the surrounding
geological materials. For such condition, not muchfindings can be expected through just resistivity
method.

Interface at -4.9 m

Fig. 4

3D ERI cross images profile

Fig. 5Ultra-seismic vertical profiling dataset

Fig. 6

Wave sequence of parallel seismic for
Phase I

Ultra-Seismic
For Ultra-Seismic Test, the source is given on
the pier and the receivers are attached along the sidewall of pier. When every strike hits on the source
point, it produces a downgoing flexural wave down
to the lower part of pier, and then reflects frombottom of foundation. The interface of different
layers of foundation, or the bottom of foundation canbe calculated from the intersection of downgoing
and upgoing events. The downgoing flexural waves
have a linear positive moveout with travel timeincreasing with distance and upgoing events having
a negative linear moveout. For this field geometry,
the interface of the foundation is easily found at -4.9m as shown in Fig. 5.
Parallel Seismic
Parallel Seismic Test is performing by using ahammer to produce some artificial impact wave onto
the pier, then measuring the transmitting wave at
different depth in an adjacent borehole. The
measurement was recorded every 0.5 m from thebottom of hole (-20 m) upward to surface.
The crucial character of wave sequence in Fig. 6
is to find some depth at which the frequency oramplitude of wave behaves discontinuously. This
character denotes some material interface
encountered when stress wave traveling downward,
and induces another source effect. In Fig. 6, at depthof -5 m and -10 m exist two diffraction responses
which can be concluded as interfaces identified byparallel seismic test.

Proof Excavation
The project includes a proof excavation to verify
NDT results. After finishing four NDT tests
mentioned above, a proof excavation was used toconfirm the actual solution. Based on the
preliminary founding from Phase I, the depth offoundation was assumed to be about -9 m mainly
fitting to the judgment from parallel seismic. Fig. 7
presents a design for the temporal retaining wallwith steel sheets of 13 m at length. The excavationlevel was lowered down to -4 m with an open
519

GEOMATE-Nagoya, Nov.13-15, 2013

excavation of 1:1 slope. Another two struts wereused to provide horizontal support to against lateralearth pressure.

Fig. 8The brick portion (layer 4) of the studied
foundation exposed by excavation

Phase II
After knowing the foundation depth might be
deeper than -13 m, more NDT tests were applied toreconfirm the true depth.

A-A section

Ultra-Seismic
The ultra-seismic vertical profiling data wasreanalyzed. In addition to an interface of thefoundation is clearly found at -4.9 m, anotherinterface is at -12.36 m (end of brick caisson).
Moreover, it is found an indistinct pair of upgoingand downgoing events intersect at the lowest
position is about 17.36 m underneath the groundsurface (Fig. 9).
Interface at -17.36 m

Fig. 7

Design drawing of temporal retaining wallfor proof excavation

Fig. 8 displays side wall of brick caisson of
investigated foundation, which implies to the layer 4.
It is amazing to realize the marvelous craft at theearly age as seeing the smooth and ordered brickwall. Considering the geological condition andconstruction technique at the early 19th century, it isthought the estimated foundation depth of -9 m
should be reasonable. The caisson bottom, however,
was not met at that depth. The excavation evencontinued to proceed 4 m further to -13 m, but could
not reach the bottom yet. For the sake of safety, theexcavation finally stopped at -13 m and remained
the foundation bottom unrevealed.

Fig. 9Another deeper interface estimated fromultra-seismic vertical profiling

Cross-hole Resistivity Tomography
For conducting some Borehole Nondestructive
Tests, two boreholes with depth of 20 m were drilled
next to the study pier. Fig. 10 shows an image
plotted from the cross-hole resistivity tomography.
This image gives also strong electrical resistancetransformation at -5 m as well as some further
information because the electrical rods are closer tothe foundation. An unclear layer was found at -9.5 m.
Furthermore, another possible interface is guessed at-16.5 m ~ -17 m only with slight variation inresistivity.

520

GEOMATE-Nagoya, Nov.13-15, 2013

popular test on underground investigation. Borehole
GPR holds same function but puts the sensors in aborehole to get closer to the investigating target. As
shown in Fig. 12, from ground surface to -5 m
presents fast radar signals refer to granite portion.
From -5 m to -9.5 m demonstrates diffraction due togravel material. The signals become uniform from 9.5 m to -20 m in which an interface is discovered at-16.5 m to -17 m. Beneath -20 m is another gravel
layer and followed with clay layer. It is more likely
the foundation bottom at -16.5 m to -17 m byborehole GPR result.

Fig. 10 Cross-hole resistivity image

Parallel Seismic
By the second parallel seismic test, wave
sequences were collected deeper than the first time.
The crucial clues are commonly hidden in wave
sequence, and should accompany with extra hints todiscover. Through a carefully picking, threeinterfaces at -5 m, -17 m and -22 m were identified
by parallel seismic test.

Fig. 12 Profile image of borehole GPR test
Multiple Offsets of Vertical Seismic Profiling
Multiple Offsets of Vertical Seismic Profilinguses a series of receivers in a borehole, and theseismic source hits on ground surface at different
offsets away from the borehole. As the investigatedfoundation sits between the source and borehole,every stress wave will pass through the foundation
before arriving at the receivers in borehole. Eachstress wave trace can reflect its path-dependent
effect. Fig. 13 shows a record of multiple offsets ofvertical seismic profiling where the offset was set at
26 m. It is found there are three dispersion points at 16 m, -21 m and -18 m, respectively.

Fig. 11 Wave sequence of parallel seismic for
Phase II
Borehole GPR

Fig. 13 A record of Multiple Offsets of Vertical
Seismic Profiling at offset of 26 m.

Ground Penetration Radar (GPR) is a very
521

GEOMATE-Nagoya, Nov.13-15, 2013

above, that wisely picking the suitable geophysicalmethods is essential in surveying unknown
underground structures. In addition, a solid
conclusion only could be made if two or moremethods obtain the same answer.

According to all the investigating methods
employed in this study, different test results arelisted as Table 1. The major interfaces of interesting
are the interface of layer 3 and layer 4, andfoundation bottom. ERI can effectively find only theinterface of layer 3/4. Cross-hole resistivity
tomography, ultra-seismic, parallel seismic, andborehole GPR can relatively detect lighter
dissimilarity and give similar answers at deeper
ground. In addition, multiple offsets of verticalseismic profiling is another promising method todetermine the foundation bottom within an
acceptable range.

ACKNOWLEDGEMENTS
The authors would like to express the special
gratitude and thanks to Bureau of Cultural Affairs ofKaohsiung City Government for funding this project.
REFERENCES[1] Olson LD, F Jalinoos, and MF Aouad,“Determination of Unknown Subsurface Bridge
Foundation,” Federal Highway Administration,
Geotechnical Notebook Issuance No. 16, 1998.
[2] WE Wightman, F Jalinoos, P Sirles, and K
Hanna, Application of Geophysical Methods to
Highway Related Problems, FHWA, 2003.

Table 1 Summary of NDT results in this study
Investigated Pier
MethodInterface oflayer 3/4

Foundation
bottom1

2D ERI

-5.0

NA

2

3D ERI

-5.0

NA

-5.0

-17.0

-4.9

-17.4

-5.0

-17.0

-5.0

-17.0

-

-16 ~ -18

3
4
5
6

7

Cross-holeResistivity
Tomography
Ultraseismic
ParallelSeismic
Borehole
GPR
Multiple
Offsets ofVerticalSeismic
Profiling

CONCLUSION
An old rail bridge was surveyed in this study toinvestigate the original foundation depth. This
investigated masonry bridge caisson represents areal construction technical art as well as a heritage
which should be well preserved. Thus as many asseven NDT methods were used in the meantime to
discuss the foundation depth. From the seven NDT
methods, to put it briefly, the Surface NDT Methods
provide fundamentally understanding about thestratum profile and likely foundation depth. Someambiguous messages mixed with unanalyzable dataneed to be verified cautiously. It is suggested to
combine several methods to give a more confident
solution. Conversely, Borehole NDT Methods give
more accurate information of foundation boundary.
It should be concluded, from what has been said522

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CONTRIBUTION OF GEOLOGICAL MAPPING AND NEWTECHNOLOGIES TO THE IDENTIFICATION OF A MAJOR, PREEXISTING AND ACTIVE FAULT OVER THE CAPITAL OF TUNISIA
Adnène KASSEBI 1,2 and Fouad ZARGOUNI 1
1

Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia; 2 National Center for Mapping andRemote Sensing, Tunis, Tunisia

ABSTRACTGreater Tunis, which covers a quarter of the population, is an area of vulnerability to natural hazards, because
it is built on a series of hills sloping down to the lake of Tunis, and has a steep slope in away from the top of abowl direction: sebkha Sejoumi. Among the active north-east of Tunisia, the El Nahli-Ben Arous and Kechabta
major faults are the most dynamic. The application of a directional filtering on HRVIR images SPOT-4 andLandsat-7 ETM+, combined with digital elevation models produced from topographic data and aerial
photographs combined with geomorphological and geological observations on the field. We identified theexistence of a pre-existing fault, deep and active. The potential and low activity of the major fault can cause
catastrophic damage for the state of buildings in the city and taking into account the results of past earthquakes.
Keywords: Structural, Microtectonic, lineaments, satellite imagery, Seismicity(Fig. 1).
The Greater Tunis area is characterized byoutcrops often disjointed and plains lined withquaternary geological structures, which makes it
difficult to understand the whole approach togeometric and kinematic relationships between thevarious structural elements.

1. INTRODUCTION
Orientation NS to NNW-SSE of limestone
outcrops south of the city of Tunis, in contrast to themajor direction of the rest of Atlasic folds trending
NE-SW. has led us to establish a tectonic andstructural study of these outcrops at the end tounderstand their geodynamic significance andstructural feature.
The discution major tectonic events that led tothe deformation of the study area: the thickness
variation, the pre-existing fracture, folds or twists
that affect the superficial layers geological levels
related to fault movements and states constraints thatare closely related to this structure.
The analysis of satellite imagery and aerial
phtographies, in addition to the analysis of historicalearthquakes in the city of Tunis, we identified theexistence of a major and active fault above thecapital Tunisia.
2. GEOGRAPHICAL AND GEOLOGICALSETTING OF THE STUDY AREA
The study area belongs to the north-east of
Tunisia, which is an area of interference major
structural zones of Tunisia, namely the eastern area,
the north-south alignment and fault Zaghouan andAtlas North, including the dome zone [1]. It consistsof limestone outcrops south of the city of Tunis,
from El Jellez cemetery in the north to the outcropof Souk el Jomla South. This area is often called"horst Tunis" [2], [3], [4] and [5] because of its
morpho-structural position between Sebkhet
Essijoumi raised in the West and Lake Tunis East

Fig. 1 Geographical and geological map of the study
area.

523

GEOMATE-Nagoya, Nov.13-15, 2013

3.
GEOMETRICANALYSISANDSTRUCTURAL

3.1. Geometry structures
In our study area, attempts to detail geometricanalysis and determination of the kinematics ofdeformation of fold structures and / or faulted arefew [2], [3] and [6]. They are intended todemonstrate the complex appearance [4] and [5] andoften disharmonic structures [5] without defining amodel of folding. Lithological heterogeneities
present within the sedimentary pile involve different
attitudes to deformation. Thus, levels of incompetent
lithologies locate separations and are causing
disharmony. Relevant levels proportionally fewer
and thinner form markers within the structures.
Because of the abundance of fracturing andabundance of directions within the limestone
outcrops, we tried to represent the outcrops by thevarious major structures indicating the landscape ofthe outcrop and small details like small horst andgraben. The folding and minor flaws will be
described in part microtectonic analysis.
Mass in the study area are distinguished by theirdifferent sizes and geometries. The major structures
are all asymmetrical and show only one periclinal
termination. The layout of all structures in space has
a more or less rectangular.

Fig. 2 Interpretive structural diagram of limestone
outcrops, south of the city of Tunis [7].
This block is identified in contact with major
faults in the sector, while in the center, where theshortening is less strong, there are series in
Horizontal (Jbel Boulaâdham).

3.2. Structural framework

3.3. Discussion

The structural study of the study area, hasallowed us to reconstruct the geometry of the main
structures that shape the landscape of the area, as
well as major faults that affect it.
The major direction of fold axes in our study
area is NW-SE to north-south (Fig. 2). This direction
may be related to a rotation in the space of thedirection of the major constraint known acrossTunisia NW-SE to NE-SW to NS.
Structural cuts were made at the end to simplify
the structure of these outcrops (Fig. 2). The reversalof the dip is the most widespread in these outcrops
landscape with same rotation sets in space. This isdue to the presence of a preexisting deep and caused
this accident chaotic deformation, indicating theblockage which is pronounced by the geologicalfeature of the area: a sign of tectonic interference
region of the main structural zones of Tunisia,
North-South alignment and fault Zaghouan insouthern sector of the basin-Kechabta Messeftine
north, the area of the water and the dome zone to thewest.

The tectonic study of beam folds the study area
showing major faults that are often parallel to thelarge structures (Fig. 2). Other faults assumed
effective, are derived from the geometry and spatial
arrangement relay certain structures. So off faults,
low emissions, related folds themselves. According
to the different outcrops.
- Flaws numbered from F1 to F15 (Fig. 2) have amajor NW-SE direction. The majority of these faults
indicate normal oblique very important games,
putting yprésienne series abnormal contact with theCampanian-Maastrichtian series, or clays Santonian.
The normal game these existing accident before thegame setback sinister dexter or even a game asreverse faults.
- Flaws in Fa1 Fa2 (Fig. 2) have a NS direction
and has normal games that precede the inverse
operation of these major accidents.
- Flaws numbered Fb1 to Fb10 (Fig. 2) have amajor NE-SW direction. The majority of faults that
this direction have a game in normal fault followedby the reverse Thurs Some vulnerabilities have awinning dexter sinister in some localities of thestudy area Thurs- Flaws and Fx2 Fx1 direction N160 to N165 (Fig.
2) affect the quaternary land border East Sebkhet
Essijoumi.
524

GEOMATE-Nagoya, Nov.13-15, 2013orange, F: photography with a slot voltage NW-SE
older (1) blocking a younger slot voltage NE-SW (2)G: χ deviation theory with the first generation ingray the second in orange, H photography with a slot
voltage older NE-SW (1) cut by a younger slot
voltage NE-SW (2).

4. MICROTECTONIC ANALYSIS
4.1. Related criteria chronology
In the field study, since the age of the youngest
rocks with the means of microtectonic data is theCampanian-Maastrichtian. Criteria for timing are
essential to approach the Cenozoic tectonic history.
The kinematics deduced devices mirror flaw havebeen detailed by several authors [2], [3], [4] and [5],but the criteria of chronology were rarely discussed
in detail. Several traps can be produced, which canlead to erroneous conclusions. These criteria can be
distinguished cross cutting relationships between all
devices and chronologies vectors of tectonic faults
on mirrors.

If filling is homogeneous it involves synchronous
opening due to a simple radial extension (σ2 = σ3)(Fig. 3 D). For λ-Type, cross the broken slot is
actually the second generation as the spread was
blocked by the previous straight slot (Fig. 3 E and F).
In such a case the filling slot is clearly different [8].
4.1.2. Timelines involving flaws
The film features recorded on mirrors faults are
frequently associated with pressure-solution process
and conduct a detailed analysis of the relationshipbetween the striations, the stylolites and fills ore.
There are two kinds of relative chronologies, firstintersection between devices and other tectonic
reactivation of the same discontinuity Paléochamps
under different constraints.
The first is more obvious since the intersections
are very clear, for example, a slot voltage can be
striped or striated plane can cross without being
moved, a stylolitique plan can be displaced by afault where the mirror flaw can be affected bystylolitiques ridges or fault plane can be moved byreactivation of the fault itself.
As in a single scheme palaeostress conjugate
faults, cracks and stylolitiques plans have very
different directions [9], such a division is very
common and is not significant in determining thetiming of Paléochamps constraints [10]. On oppositechanges and film for the same asserted discontinuity,changing Paléochamps constraints is clear.
Fills minerals observed mirrors faults are ofprimary interest to establish the chronology of
Paléochamps constraints, according to their types.
The first example is affected by a fault movement(Fig. 8) slot.

4.1.1. Slot against Slot
The division between two slots can be of three
types: X, λ and χ-type, with different interpretations(Fig. 3). For the X-type crossing, if mineral fillers
are clearly different for each direction, it clearly
defines two distinct generations with σ3 (Fig. 3 B
and C).

4.2. Age and significance of structures
The first extensional tectonic phases have arisen
from the Campanian-Maastrichtian, then from theupper Paleocene-Eocene. As in all of Tunisia, thephases of the deformation are more visible in the
Neogene. After these phases Neogene most of
currently observable structures in place, but on asmaller scale deformations, continue to be felt.
Recent movements of age post-Villafranchian haveaffected the older Quaternary formations.
The three tectonic features: faults, tension gashes
and stylolites were associated with a step or normal
movement, when their directions σ3 were consistent
with stylolites and / or flaws in the same location. In

Fig. 3 Criteria relative chronologies between tension
gashes; A: problem of determining chronology B:
photography with a slot oldest NW voltage (1), cut
by a younger slot voltage NE-SW (2); C: theory for
the X-type with the first generation and the second
yellow orange, D: theory for the X-type with ageneration for the radial extension, E: Theory of λtype for the first generation gray the second in525

GEOMATE-Nagoya, Nov.13-15, 2013

some cases it was not possible to remove theambiguity between the two tectonic regimes.

ETM+4 and PC1 can raise even more discontinuities
images corresponding to structural lineaments.

5. EXTRACTION OF LINEAMENTS AND
VALIDATION5. 2. Natural lineaments from the analysis of theDTM

5. 1. Image processing of Landsat-7 ETM +The realization of a mapping project, using theLeica Photogrammetry following LPS extraction
field, we succeeded in the automatic generation of adigital terrain model (DTM for each display quality
indicators) by correlation of ten IKONOS 2004
satellite imagery (Fig. 4) oriented.

The Principal Component Analysis (PCA) was
performed on seven soundtracks ETM + Landsat-7
image of Grand Tunis has generated neo-channels(principal components). The first three components
contain a high percentage of the total variance(Table 1). This table shows a strong correlation of
the visible bands (1, 2 and 3) with coefficients of 0.9.
There is also a correlation in the order of 0.7 thoseof the infrared. The combined use of these channels
gives redundant information because they containcommon data. The CPA has helped identify the
information contained in these multispectral images
by eliminating data redundancy: the linear
geostructures are best seen in the first principal
component (principal component 1 or PC1) on themultispectral image.
Table 1 Correlation matrix of the Landsat ETM+
bands of the area of Great Tunis
Band
ETM+
1
2
3
4
5
6
7

1

2

1,00
0,96
0,95
0,88
0,87
0,66
0,78

3

1,00
0,95
0,87
0,91
0,66
0,79

4

5

6

7
Fig. 4 Correlation of ten IKONOS 2004 satellite
imagery.

1,00
0,79
0,93
0,64
0,91

1,00
0,86
0,58
0,74

1,00
0,66
0,88

1,00
0,75

1,00

Some details in the images obtained could thenbe enhanced through the application of the techniqueof combining images using simple mathematicaloperations that generate reports bands (PC1 / ETM+7) and indices standardized (ETM+6 – ETM+4) /(ETM+6 + ETM+4).
Table 2 The application of high-pass filter(Laplacian modified) 5X5
0

0

-1

0

0

0

-1

-2

-1

0

-1

-2

16

-2

-1

0

-1

-2

-1

0

0

0

-1

0

0

Fig. 5 Hillshading from the DTM of the Greate
Tunis region.
Existing data (support points, field points control
connection (aerial triangulation) and text files),digital terrain model and external vectors from thetriangulation of an image block, and extraction of

The application of high-pass filter : Laplacian
modified (Table 2), directional Sobel filter type 7x7
and finally gradient filter Yésou [11] bands ETM+7,
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GEOMATE-Nagoya, Nov.13-15, 2013

elevation and creation from orthorectified aerial
photography (2012) images, are used to improve thecorrelation process.
Using the "3D Surfacing Tool" tool LPS Corewas merged NCD and added line breaks.
The extraction of lineaments from MNT (Fig. 5),
corrected and validated, with the manual method,
takes into account the removal of the water systemand human lineaments and other lineaments that can
not correspond to a fault or fracture.

Area
Utica
Kairouan
Tunis
Tunis
(Zerkachi)
Tunis
Tunis Bab El
Mejaz
Tunis, Arianaand LaGoulette
Tunis
Tunis Mejaz
El Bab
Tunis
Mornaguia
Tunis
Tunis
Tunis Khereddine
Tunis
Tunis
Tunis

5.3. Discussion
The extraction of lineaments was performed inpart on the initial and transformed bands (or filteredfrom the ACP) and secondly the DTM extracted.
Treatment and filtering have been to accentuate andfacilitate the detection of discontinuities-images,
allowing them lifted by visual observation. Only theorigin of structural lineaments, have an interest in
this study. Also, by synthesis of information througha GIS anthropogenic previously vectorized
linearities (paved roads, trails, power line, transects
bounding forest and cultivated land ...) have been
identified in all the lineaments and eliminated.
Geological and structural lineaments identified inprevious mapping [2], [3], [4], [5] and [7], but few
based on aerial photographs and field observations
therefore considered as true, were found in our
network of lineaments. The ability of the method,
based on the interpretation of satellite images, findreal fractures already known, not only among thelargest, validates our extraction method. Thisvalidation leads us then extrapolated to give a
structural value to all our lineaments and move fromthe use of the term lineament than divide.
This work on satellite images finally provides a
new structural map and much richer in Greater Tunis,
where it has been introduced by mistake or overlook
some fractures, especially among smaller (length ofa few kilometers) to the observation scale images.

Date
5th century (between 410 and 412 BC)
9th century (855) 13 villages destroyed
around Kairouan
In 856; 45000 victims
In 1425
In 1735, 1750 and 1758 AD C.
March 14, 1872
15 to 21 December 1863
March 17, 1904
25 February 1920
October 7 and September 26, 1922
27 and June 28, 1927
July 22, 1929
February 21, 1932
19 and May 21, 1948
1st December 1970; magnitude 6
December 16, 1976; magnitude 4.5

These locations are located just within thealignment seismotectonic NE-SW Tunis-Mornaguia
in with data from the instrumental seismicity. The
most violent earthquakes that are at the northernedge of Lake Tunis, seem to be related to the NWSE fault. This fault extends about ten miles andshifts the anticline Jbel Nahli sinistral strike-slip.
Recent activity of this accident is shown by the factthat it affects the last limestone crust and upper
Pleistocene [16] red silts.
Further south in the region of Tunis, themoderate seismic activity seems, but in reality it isimportant for the large number of low shaking
whose magnitudes do not exceed 3 degrees Richterand have not been shown in card. It seems that someevents are to be attached to the accident Zaghouan
and others are to be attached to the N-S fault
M'hamdia and NE-SW fault Jbel Tella [16].
The instrumental seismicity data from the
National Institute of Meteorology (INM) andcorrespond to recorded from 1976. It is generally
low to moderate seismicity (magnitude between 2
and 5 degrees).

6. ACTIVE SEISMICITY
6.1. Historical seismicity
The historical seismicity of Tunisia is very
poorly known, the documents produced by several
authors [12], [13] and [14] show that the Greater
Tunis known in the history of destructive
earthquakes as shown in Table 3.
It is noted that the historical earthquakes in the
study area often affect areas of Tunis city northern
suburbs, and Mornaguia-Borj Amri.

6. 2. Macroseismic companion
A macroseismic companion made following theearthquake April 29, 2003, in the Greater Tunis,
reveals an epicentral area, elongated along a NNWSSE, which follows the same direction of our major
flaw identified in the field [7]. This is an earthquakeof magnitude 3.5 and intensity VI on the MSK scale.
This earthquake caused a lot of damage to the oldMedina founded in 698 and the outskirts of the city

Table 3 The history of destructive earthquakes inGreat Tunis area.

527

GEOMATE-Nagoya, Nov.13-15, 2013that are currently at risk of collapse, and moisture inbuildings spread in very bad condition. This shows
the current risk associated with stronger and possible
earthquake damage.

oldest directions. Therefore, we can provide a base
cut by accidents NS who suffered during the time ofraised portions repetitive image of the domainalignment NS.

7. INTERPRETATION

8. CONCLUSIONS

Major tectonic lineaments regional extension,often coincide with pre-existing map vulnerabilities
directions N060, N090, N180 and N140. The faults
trending N065 el Mannoubia of N140 direction
Nahli Ben Arous and Mhamdia define structural
panels NE-SW direction, they form a system strap
tectonic
shear
associatedwithanticlinal
megastructures NS to N140.

Our study area has a great diversity of viewpoint
geodynamics, structural and tectonic. Though this isa natural extension of the Tunisian Atlas, its tectonic
features also recall NS alignment (Fig. 6); it is also
up on its northern extension. It can thus be seen as
an interference area structures. Indeed, the tectonic
division is configured holes directions N60-70 andN120-140 known the Atlas area.
Therefore, these limestone outcrops correspondto folds associated with a major setback to NW-SE
to NS. This accident is presented in the study area by
several segments, probably corresponds to theextension of the accident affecting NS el-Manar
Nahli area. This even affects the Quaternary depositsof the sector [13].
9. REFERENCES[1] Zargouni F. et Abbès C., 1987. Zonation
structurale de la Tunisie. Rev. Sci. Terre,édition I.N.R.S.T., Tunisie, V-3. pp. 63-69.
[2] Solignac M., 1927. Etude géologique de laTunisie septentrionale. Dir. Gen. Trav. Pub.,
756 p; Thèse es Sciences, Lyon.
[3] Jauzein A., 1967. Contribution à l’étude
géologique des confins de la dorsale tunisienne(Tunisie Septentrionale). Ann. Mines Géol.,Tunis, N°22, 475 p, 92 fig., 5 pl. Ht.
[4] Ben Ayed N., 1986. Evolution tectonique del’avant-pays de la chaîne alpine de Tunisie dudébut du Mésozoïque à l’actuel. Thèse d’Etat,
Univ. de Paris, Sud- centre d’Orsay.
[5] Boutib L., 1998. Tectonique de la région duGrand Tunis : évolution géométrique etcinématique des blocs structuraux duMésozoïque à l’actuel (Atlas nord oriental de laTunisie). Thèse de Doctorat, Univ; Tunis, 151p.
[6] Boutib L. et Zargouni F., 1997. Évolution
géométrique des mégastructures anticlinales etdécoupage en lanières tectoniques de l’Atlas
centro-méridional de Tunisie. 14ème Coll.
Bassins Sédimentaires. Marocains, p. 142.
[7] Kassebi, A. 2007. Signification géodynamiquedes pointements calcaires au Sud de la ville deTunis. Thèse de 3ème Cycle, Faculté desSciences de Tunis, 95 P.
[8] André G., 2002. Evolution des paleocontraintes
tectoniques le long d’un accident régional,
exemple de la faille de Vittel, Journée del’Ecole Doctorale RP2E, Nancy. CD-R.
[9] Arthaud F. et Mattauer M., 1969. Exemple destylolites d’origine tectonique dans leFig. 6 Seismotectonic map of the study area and its
surroundings ([7], modified).
The major faults trending N120-140 N060-070
are involved in the genesis and deformation of theupper Pliocene basin Cretaceous.
The Late Cretaceous is the most demonstrative
when major faults are subject to a transtensional
regime resulting from the opening of the Tethyanareas mesogean and Atlantic [18]. Faults NW-SE to
EW were activated primarily from the Upper
Cretaceous, while the NS faults in the N060 is the528

GEOMATE-Nagoya, Nov.13-15, 2013

Languedoc, leurs relations avec la tectoniquecassante. Bull. Soc. Géol. de France (7), XI, n°5,
pp. 738-744.
[10] André
G.,
2003.
Caractérisationdesdéformations
méso-cénozoïques
etdescirculations de fluides dans l’Est du Bassin deParis. Thèse de 3ème cycle, Université Henri
Poincaré, Nancy, 311 p.
[11] Yésou, H., Besnus, Y., Rolet, J. et Pion, J.-C.
(1993) Comparaison et évaluation des données
SPOT, ERS-1, Seasat, Landsat et des données
combinées lors d'études de géologie structurale.
In 8e congrès de l’Association Québécoise de
Télédétection, 16ème Symp. Télédétection,
Sherbrooke, pp. 521-526.
[12] Ambrasseys N. N. (1962) - The seismicity ofTunis. Anali di geofisica, vol. Xl, n°2-3, Roma.
[13] Rothe J. P. (1969) - Mission d'information
seismolor que, Moyen-Orient et Afrique dunord. UNESCO, n° de serie: 1759/BMS. 336p.
24 fig., 50 tabl., Paris.
[14] Zenati H. (1990) - Etablissement dun catalogue
des seismes historiques de la Tunisie: evolution
des donnees recueillies pour la periode 3651950. Tome I, Soc. Tun. Elec. Gaz (rapport
inedit).
[15] Kassebi, A., Khémiri S., Ajmi M., Hamza M. H.
et Zargouni F. 2010. Les risques d’inondation
associés à l’évolution de l’environnement
urbain dans le Grand Tunis. CongrèsInternational Géotunis : 5ème édition, intitulé :« L’utilisation des SIG et la Télédétection pourle développement durable ». pp. 21-22.
[16] Kacem J., 2004. Etude sismotectonique etévaluation de l’Aléa sismique régional duNord–Est de la Tunisie : apport de lagéophysique dans l’identification des sources
sismogéniques. Thèse Es Sciences Géologique,Univ. Tunis II, Fac. Sc. Tunis, 389 p.
[17] Dlala M. et Kacem J., 2006. Cartesismotectonique du grand Tunis, programme decollaboration INM–FST, et OTC–Tunis.
[18] Dlala M., 2002. Les manifestations tectonosédimentaires d’âge Campanien-Maastrichtien
en Tunisie : implication sur l’évolution
géodynamique de la marge Nord-Africaine. C.R
Geoscience, 334, pp. 135-140.

529

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECT OF GRAIN SIZE ON MINERAL CARBONATION OF COALCOMBUSTION FLY ASH FOR CO2 SEQUESTRATION
N. L Ukwattage and P.G Ranjith
Deep Earth Energy Lab, Bld 60, Monash University, VIC 3800, Australia
ABSTRACT
Mineral sequestration with alkaline waste materials is being studied extensively for its application asa way of reducing the increased level of CO 2 in the atmosphere. Coal combustion fly ash has the potential toreact with CO 2 to form minerals which are stable over geological times. For industrial level application of thisconcept, the mineralization reaction is required to enhance. One possible way of achieving it is through selectionof best reactive material. Therefore, the objective of the present study was to investigate the effect of the grain
size of fly ash on rate and efficiency of mineralization reaction . In the study, three Australian fly ashes from
Hazelwood, Loy Yang and Yallourn power plants were carbonated inside a closed reactor at 3 MPa CO 2pressure and 40 0C temperatures. For each fly ash type, 50 g of oven dried samples from four different particle
size classes as < 100 µm, 100-250 µm, > 250 µm and bulk particles were tested and compared for the weightgain after carbonation. From the results 100-250 µm samples were found as the best particle size range for themineral carbonation reaction of all three tested fly ashes whereas particles larger than 250 µm diameters gave theleast sequestration. Also, Yallourn fly ash showed the highest sequestration potential at each particle size of all
three tested fly ashes which could be attributed to its available oxide content and purity.
Keywords: Mineral sequestration, CO 2 , Fly ash, Grain size

the ex-situ carbonation with manipulated reaction
parameters such as temperature, CO 2 pressure,moisture content and mixing [6, 7]. In addition,
selection of a suitable candidate material helps toincrease the sequestration efficiency and also therate of reactions.
Coal combustion fly ash is a solid waste material
contains oxides such as CaO and MgO that can beconverted to carbonates in the presence of CO 2 .
Also it is an abundant solid waste of which,production is expected to increase as a result of theworld’s increasing reliance on coal-fired power
generation over the next few decades. Although
there are many potential uses of fly ash including
cement production, road sub-base construction, minereclamation and as aggregate substitute material, it ispresently identified as a resource that is significantly
under-utilized [8]. Each year a large mass of fly ash
is collected in storage ponds, which emphasizes theneed for the investigation of large- scale applications
for this waste product.
Over the last few decades fly ash has attracted
attention as a potential source in the mineralsequestration process, which involves the captureand storage of atmospheric C in alkaline materials[6] ,[9]. The utilization of fly ash to capture and fix
CO 2 has an added advantage, since it assists in the
management of this potentially hazardous waste. As
the carbonation process helps to alter the chemical
stability of the fly ash, the leachability of heavy
metals such as Pb, Zn tends to reduce after

INTRODUCTION
Mineral sequestration of CO 2 using alkalinematerials is another novel CO 2 sequestration concept
which provides a beneficial use for certain rapidly
accumulating waste materials [1]. Solid wastes
produced during coal combustion (fly ash andbottom ash), municipal solid waste incineration (flyash, bottom ash and air pollution control residues)
and by-products such as steel slag are some of theresidues which are being evaluated for their potential
for CO 2 sequestration [1]-[3]. In mineralsequestration, atmospheric CO 2 is taken up byalkaline oxides and hydroxides present in thecandidate materials to form thermodynamicallystable forms of carbonates [1], [4]. Basically,
mineral carbonation is an acid base reaction wherean acid formed by dissolution of CO 2 in water(H 2 CO 3 ) is neutralised by a solid base (alkaline
mineral). It is one of the steps in natural rockweathering which comprises of a complex series ofchemical and mineralogical transformations [3].
Under ambient conditions Ca and Mg-bearing
silicate minerals are naturally carbonated to form Ca
and Mg carbonates. But this natural weathering
takes geological times to complete [5]. Therefore inorder to achieve quick transformation of CO 2 into
stable minerals, for the applications in CO 2
sequestration, the natural reaction should beenhanced through aqueous mineral carbonation. In
this, the carbonation reaction is accelerated through530

GEOMATE-Nagoya, Nov.13-15, 2013carbonation [10]. This allows the safe disposal ofcarbonated fly ash into landfills or dumpsites.
However the mineral carbonation of coal fly ash
for CO 2 sequestration is still not implemented inindustrial level due to several drawbacks in theprocess which needs to be solved through further
research on the discipline. One of the identified
research needs is to optimize the carbonation
reaction by investigating the effect of parameters on
the mineralization process. As a material
characteristic, the grain size of the fly ash being
carbonated can influence the overall reaction rateand efficiency. Therefore, the objective of thepresent study is to evaluate the effect of fly ash grain
size on the mineral carbonation for CO 2
sequestration.

Gas inlet
Gas outlet

Reactorcell
Heating
element

MATERIALS AND METHODS
The fly ash samples for the test were collectedfrom three power plants (Hazelwood, Loy Yang andYallourn) located in Latrobe valley, Victoria,
Australia. Victorian brown coal is the parental
material for all three of these ashes. The morphologyof the Latrobe valley ash particles is generally
irregular and ranges from sub-angular through torounded, sometimes spherical. The powder used in
the study came from the collection ponds andinitially contained large clods of ash which needed
to be broken into individual particles for testing.
Fly ash samples were then sieved with 250 µm
followed by 100 µm sieves to get material under 100µm, between 100 to 250 µm and above 250 µm
diameters. Bulk sample was randomly drawn fromthe bulk material. Then the samples were oven driedat 105 0C for 24 hours to remove all moisture. From
the dried material 50g of samples belong to eachgrain size category were taken for testing. For eachtest two replicates were taken. Then these samples
were added with 20% weight of distilled water andplaced in stainless steel dish containers for reaction.
The carbonation reactions were carried out inside
the pressure chamber shown in Fig. 1. Sample
containers were placed inside the rector cell and thecell was heated up to 400C temperature. Then CO 2
gas was charged into the cell until the cell insidepressure becomes 3 MPa. After achieving thepressure the reactor cell was isolated and the ash wasallowed to react with gas for 10 hours. After 10hours’ time the remaining gas in the cell wasdischarged and the samples were taken out. Reacted
samples were then oven dried until a constant weight
and then the final dry weights were recorded.
Weight gain after the carbonation in different
particle size category was analyzed for all the three
fly ashes tested. In order to confirm the carbonation,
the reacted samples were looked under the scanningelectron microscopy (SEM).

Fig. 1 the reactor setup used for the carbonation
reaction
RESULTS AND DISCUSSION
The optimum grain size of coal fly ash for themineral carbonation reaction for CO 2 sequestration
was determined using the percentage dry weightgain after the carbonation. During the carbonation
process the formation of carbonates from oxides
increases the dry weight of the solid material. Out of
all available oxides, CaO forms the most stable formof carbonate, Calcite (CaCO 3 ) at the presence ofmoisture and CO 2. The series of mineralogicaltransformations occur during the carbonation
process is shown under Eq. (1) to (4).

H 2 O + CO2 → H 2 CO3(1)

H 2 CO3 → H + + HCO3 − → 2 H + + CO3 2 − (2)CaO + H 2 O → Ca (OH ) 2 → Ca 2+ + 2OH − (3)Ca 2 + + CO3 2 − → CaCO3(4)

According to the chemical reactions ultimately thegaseous C occurred in CO 2 is stored within calcite
as carbonate carbon. Therefore after the reaction fly
ash material gain some weight due to stored carbon.
Fig. 2 shows the average weight gain after
carbonation of different grain size categories of eachfly ash type.

531

Average weight gain after carbonation(g)

GEOMATE-Nagoya, Nov.13-15, 2013mineral carbonation lies within this grain size range.
The results of the present study are in agreementwith similar studies done on municipal solid waste
incineration (MSWI) ash and coal fly ash by someother workers. In their experiment on carbonation of
air pollution control residues (APC ash) of MSWI,[9] observed that the fraction below 212 µm as the
optimum for carbonation. Also [6] studied the effectof particle size on the carbon sequestration potentialof coal fly ash and concluded that 20–150 μm
particle size range as the optimum. The least potent
was observed for the >150 μm fraction.
Considering the average weight gain after
carbonation for each sample tested, the sequestration
potential could be estimated. Fig. 3 compares theCO2 sequestration potential of three different coal
fly ashes for each particle size range.

1.4
1.2
1
0.8
0.6
0.4
0.2
0
<100 100-250 >250
Grain size category
HazelWood

Loy Yang

Bulk

Yallourn

30
CO2 sequetration potential(kg/tonne)

Fig. 2 Weight gain after carbonation

25

According to the results shown in Fig. 2 all three
fly ash types had their maximum weight gain after
carbonation for the grain size category of 100 to 250µm. Also all three ashes showed the least weightgain for the ash particles > 250 µm diameter. In
order to verify the significance of the differences inweight gain obtained for different grain size classes,
two factor ANOVA statistical test was performed for
all the samples. Fly ash type and the grain size
category were considered as the sources of variance.
According to the test results, at α level of 0.05 there
was a significant difference in the weight gain after
carbonation among different grain size categories ( Ftest 14.51 > F critical 4.75). Also, the average
weight gain for the same experimental conditions
was significantly different on the fly ash type.
These results can be interpreted with thedifferent factors affecting on the rate and efficiencyof the mineralization reaction. Particle size can
influence the overall carbonation efficiency of solid
waste materials due to several reasons. Smaller thesize of the particles the reactivity of those tends to
be increased. Smaller particles become morereactive for two reasons: 1) they have a larger
specific surface area for reactions, 2) as they cool
faster upon exiting the combustor they undergo morechanges. Therefore they possess a more reactive
structure [11]. In addition to the increased reactivity,
the comparatively high CaO content found insmaller particles is another factor which helps themto show a higher degree of carbonation efficiency
than larger ones. Usually the CaO content increases
with decreasing particle size. Therefore the largest
particle size category records the lowest weight gain
after carbonation.
However, the maximum weight gain wasobserved for the grain size of 100 to 250 µm.
Therefore the optimum grain size of coal fly ash for

20
15
10
5
0
>250 μm
HazelWood

Bulk<100 μm 100-250μm
Size fraction
Loy Yang

Yallourn

Fig. 3 CO 2 sequestration potential of different size
fractions
The highest sequestration potential for all three
types of ashes was observed for the size range of
100 to 250 µm. Among three tested fly ashes
Yallourn ash showed the highest sequestration
potential of 26.4kg per tonne of fly ash. The lowest
potential was shown by Hazelwood fly ash. This ismainly due to the change in the chemicalcomposition of three different fly ashes. Hazelwood
fly ash has the highest CaO content among all threeashes followed by Yallourn and Loy Yang fly ashes.
However the Hazelwood ash used for the study werealready weathered heavily due to long term storage
in waiting ponds. Therefore it showed the lowest
capacity to capture CO 2. Yallorn and Loy Yangashes were subjected to almost similar degree ofnatural weathering and therefore the available CaO
content for the reaction was much higher.
The results of the present study were comparedwith some other studies (results are under review ofjournal publication) done by the authors on the same
fly ashes. During those tests authors observed grater
532

GEOMATE-Nagoya, Nov.13-15, 2013

sequestration potentials for all the three fly ashes
compared to the present study. Table 1 summarizes
the results of present study and the past study.

CONCLUSIONS
Mineralization of alkaline coal fly ash has thepotential to store CO 2 permanently. The
sequestration n of carbon in fly ash can be enhanced
through optimization of parameters affecting themineral carbonation reaction. Fly ash particle size isan important material characteristic that can be
optimized. According to the results of the present
study Latrobe valley fly ashes showed the maximum
sequestration within the grain size range of 100 to
250 µm. Larger particles (>250 µm) had the lowest
sequestration. Also, among the tested fly ashes
Yallourn ash had the highest sequestration which is
26.4 kg per tonne of fly ash. The insufficient
reaction time under provided reaction conditions did
not allow obtaining the maximum sequestration
potential recorded in a past study done by theauthors.

Table 1 This is the example for table formatting

Study

Present
Past

Highest sequestration potential(kg/tonne)
HazelWood
LoyYang Yallourn
9.8
20
26.4
10.7
22.1
28.4

This change in the maximum potential ofsequestration could be mainly attributed to thereaction conditions used in the present study. The
past study was conducted with the continuous
stirring provided to the ash material with CO 2 inwhich the reaction was observed to be completed
within 8 hours. But in the present study only a set
time duration of 10 hours was used for the reaction
without provision of any stirring. This resulted
incomplete carbonation at the end of reaction time
and therefore the sequestration potential was slightly
lower than the maximum.
Finally, in order to confirm the carbonation
occurred in the samples SEM pictures were obtained
for the tested samples with NOVA Nano SEM 450
available at Monash University. Fig.4 shows theSEM picture.

ACKNOWLEDGEMENTS
Authors are thankful to everyone who contributed indifferent ways for the success of the present study.
Special thank goes to the supervisor of the PhD
research of the first author and the lab staff of the
Department of Civil Engineering.
REFERENCES[1] Huijgen WJJ, Witkamp GJ, Comans RNJ.
“Mineral CO 2 sequestration by steel slag
carbonation”, Environmental Science and Technogy
Vol. 39(24), 2005, pp 9676-82.
[2] Reddy KJ, Weber H, Bhattacharyya p, Argyle M,
Taylor D, Christensen M, Foulke T, Fahlsing P.
“Instantaneous capture and Mineralization of Flue
Gas Carbon Dioxide: Pilot Scale Study”, Nature
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available
at http://dxdoiorg/101038/npre201054041. 2010.
Acessed on 28 May 2012.
[3] Fernandez Bertos M, Li X, Simons JR, Hills CD,
Carey PJ. “Investigation of accelerated carbonation
for the stabilisation of MSW incinerator ashes andthe sequestration of CO 2 ” , Green Chemistry, Vol.
6(8), 2004, pp 428-36.

Fig. 4 SEM picture of a carbonated fly ash sample[4] Baciocchi R, Polettini A, Pomi R, Prigiobbe V,
Nikulshina V, Zedwitz V, Steinfeld A. “CO 2sequestration by direct gas solid carbonation of air
pollution control (APC) residues”, Energy andFuels,Vol. 20, 2006,pp 1933-40.

Formation of carbonate crystals was clearlyvisible in the SEM images as seen in Fig.4. Rod
shape carbonate crystals were abundantly observed
all the reacted samples scanned through themicroscope. Therefore the weight gain due tocarbonation is evident.

[5] Costa G, Baciocchi R, Polettini A, Pomi R, Hills
C, Carey P. “Current status and perspectives ofaccelerated carbonation processes on municipal
waste
combustion
residues”
Environmental
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Monitoring and Assessment, Vol 135(1), 2007, pp
55-75.
[6] Nyambura MG., Mugera GW., Felicia PL.,
Gathura NP “Carbonation of brine impacted
fractionated coal fly ash: Implications for CO 2
sequestration”
JournalofEnvironmental
Management. Vol 92, 2011, pp 655-64.
[7] Fernandez Bertos M, Simons SJR, Hills CD,
Carey PJ, “A review of accelerated carbonation
technology in the treatment of cement basedmaterials and sequestration of CO 2” Journal ofHazardous Materials. Vol 112, 2004, pp 193-205.
[8] Da Costa JCD, Prasad P, Pagan RJ. “Modern
environmental improvement pathways for the coal
power generation industry in Australia” Process
Safety and Environmental Protection, Vol 82(3 B),
2004, pp 191-9.
[9] Montes-Hernandez G, Pérez-López R, Renard F,
Nieto JM, Charlet L. “Mineral sequestration of CO 2
by aqueous carbonation of coal combustion fly-ash”
Journal of Hazardous Materials, Vol 161(2-3), 2009,
pp 1347-54.
[10] Van Gerven T, Van keer E, Arickx S, Jaspers
M, Wauters G, Vandecasteele C. “Carbonation of
MSWI bottom ash to decrease heavy metal leaching,in view of recycling” Waste Management, Vol 25,
2005, pp 291-300[11] Iyer RS. and Scott JA. “Power station fly ash review of value-added utilization outside of theconstruction industry” Resources, Conservation andRecycling, Vol 31(3), 2001, pp. 217-228.

534

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STUDY SEISMICITY PARAMETERS OF RUDBAR REGION AND
SEISMOLOGICAL ASSESSMENT OF RUDBAR-MANJIL (IRAN)
EARTHQUAKE OF JUNE1990
Noushin Naraghi Araghi , Mohd. Nawawi and Syed Mustafizur Rahman
School of Physics, University Science Malaysia (USM), 11800, Penang, Malaysia
ABSTRACTThis paper presents the seismicity characteristics of Rudbar and adjacent regions, the study area is a radius of
100 km from the center of Rudbar (36.80˚N –49.41˚E) where it was destroyed seriously on June 20, 1990 by oneof the largest earthquake in Iran with magnitude of 7.7 (M s ) and the peak ground acceleration greater than 0.6g.
More than 40,000 people were killed, and 60,000 were injured. Geological maps were used to provide the faults
map of this region. Using global database of earthquakes provided as well as a catalog of historical (pre-1900)
and early- instrumental (1900-1963) earthquakes, a uniform catalog of earthquakes for the interest region has
been provided. To unify the scale of earthquake magnitude, we established empirical relations to convert m b toM s . Based on this uniform catalog and after eliminating foreshocks and aftershocks, seismicity of the interest
region was studied, and seismicity parameters were calculated. In order to achieve more reliable results, thecompleteness of the catalog and uncertainty of magnitudes have been estimated and considered in our
calculations for the interest region, the results show that b-value is equal to 0.82 ± 0.3, λ is equal to 0.40 ± 0.08
for m c =4 and M max =8. 20 ± 0.54.
Keywords: Seismicity, Seismotectonic, Seismic Parameters, Completeness of Catalog, Rudbar

for the time and the volume of the consideredwindow. The b-value (size distribution) is a measurefor the relative abundance of the strong to the weak
earthquakes and is considered to be related to thetectonic regime of the area [5].
A variation of the b-value inregion iscommonly correlated with characteristics of regional
seismic activities [6] .
Previous studies pointed out that the region withlow b-value implies large stress.[7]The objectives of this research are to carry out apreliminary analysis of seismicity studying in thishazardous area and assessment of seismic hazard
parameters .

INTRODUCTION
In 20 of June 1990 a large magnitude (Ms = 7.7,
M W = 7.3, M b = 6.4, focal depth of 19 km)
earthquake with the peak ground acceleration greaterthan 0.6g was recorded, located about 10 km fromthe earthquake fault in north of Iran near Rudbar [1].
Rudbar is a city situated in Gilan Province and 268
kilometers from Tehran. This huge event wasreferred as the Manjil earthquake [2] and Rudbar –Tarom earthquake [3].
In the literature, the epicenter of the Rudbar
earthquake (36.95˚N–49.40˚E) is determined by the
USGS in 1990. It affected both urban and rural
regions, where it completely destroyed 700 villages
in the Sefidrud river valley and also the cities of
Rudbar, Manjil and Loshan, killing more than
40,000 people, injuring 60,000 and making morethan 500,000 homeless [3], so seismicity studies isessential in this area.
One of the power-law relations commonly
employed in seismicity studies is the frequencymagnitude earthquake distribution .
log N =a -bM

SEISMOTECTONIC AND SEISMICITY OF
THE AREA
The study region is an area in the radius of 100
km from the center of the Rudbar city (36.80˚N –49.41˚E). According tosomegeological,
geophysical and seismological similarity with theassumption of uniform earthquake potential, Iran
could be divided into sesimotectonic provinces. The
seismotectonic province of Iran is defined as an areabounded by geological features which make adifference in seismic characteristics of one province
from its neighboring provinces. Each province has
equal seismic potential and uniform geologicalstructure and trends. This study area is situated in
Azerbaijan-Alborz seismotectonic province asshown in Fig1 [8].

(1)which predicts the distribution of earthquakes withrespect to magnitude. In Eq. (1), M is magnitude, aand b are constants and N is number of earthquakes
equal to or larger than M. The b-value is in mostcases close to unity for long time periods and large
areas [4].
The a-value is related to the seismic activity and so
535

GEOMATE-Nagoya, Nov.13-15, 2013DATA
The first step in the seismic hazard study ispreparation of complete data in the study area. The
available earthquake catalogs usually contain two
types of information: Macroseismic observations ofmajor seismic events that occurred over a period of afew hundred years and complete instrumental datafor relatively short periods of time (last 50 years themost).
Earthquake catalog of Iran includes two kindsof data.
-The historical or pre-instrumental earlier 1900
-The instrumental period . (1900-present)
The instrumental era includes early instrumental(1900-1963) and modern instrumental era post 1963
to present [14] .
For historical data in this area we used
Ambraseys and Melville [15]. Six historical eventswere recorded which can be seen in table 1. (Quality
in table 1 indicates the quality and quantity ofMacroseismic information marked by A to F).
Instrumental data for this research provided by
global and local databases as followed.
-USGS (U.S. Geological Survey)-ISC (International Seismological Centre)-BHRC (Building and Housing Research Center )Fig .1 Sesimotectonic provinces in Iran [8]Alborz mountains (north of Iran) are considered
as mountains without root that its uplift is due tothrusting of allochthonous masses over each other in
a compressional tectonic regime [9]. The depth of
Moho in Alborz mountains is less than 35km [10].
Geological - tectonic investigations in the Alborz
mountains obviously show that these mountains
have been formed by thrusting of folded rocks overeach other [11], [12]. The focal mechanism ofAlborz’s earthquake indicates the strike - slip
mechanism with some reverse component [13]. The
focal mechanism of the Rudbar- Tarom earthquake
shows a left- lateral strike slip. Although reverse
faults and folding contributed an important role in
the formation of Alborz folded and thrust active
mountains but the occurrence of the Rudbar- Tarom
earthquake indicates that the Alborz belt in the
Rudbar-Tarom area is affected by left- lateral shear.
Main active faults of the study area can be seen in
Fig2.

Table .1 historical events in study Area
Date
1052
1119
1367
1678
1803
1844

Latitude (˚)
36.60
36.38
37.30
37.20
36.33
37.50

Longitude (˚)
50.30
50.00
49.90
50.00
48.95
48.00

Ms
6.8
6.5
5.5
6.5
5.3
6.9

Quality
B
C
D
B
C
B

Relation between m b and M s
Normally earthquake catalog includes different
magnitude scales , M s is the surface wave magnitude,
mb is the body wave magnitude, Mw is the moment
magnitude and Ml is the local magnitude .
The historical earthquake in Iran has been
defined in Ms also Ms and mb are the most reported
magnitudes for instrumental events in this area.
The saturation level of mb is around magnitude
6.2 whereas the saturation level of Ms is 8 so surface
wave magnitude is the most appropriate magnitude
scale for this region [16].
To evaluate seismic hazard parameters ahomogenized catalog is needed .
To unify the scale of earthquake magnitude foreach seismotectonic province, we establishedempirical relations to convert mb to Ms. Since

Fig .2 Major active faults of the study area with the
focal mechanism solution for earthquakes
536

GEOMATE-Nagoya, Nov.13-15, 2013

historical earthquake in Iran have been defined in Ms
and lack of events with magnitudes above thesaturation level of Ms in the interest region, surface
wave magnitude is the most appropriate magnitude
scale for the region,. There is a linear relation
between Ms and mb as in Eq. 2.

Ms= dmb + c

Based on the uniform catalog, seismicity of theregion studied, seismicity parameters were
calculated utilizing the method proposed by Kijko
and Sellevoll [14]. In order to achieve more reliable
results, the completeness of the catalog anduncertainty of magnitudes was estimated andconsidered in our calculations. In this method,
dataset of the catalog was divided into extreme andcomplete part. Using a global and local database ofearthquakes provided by USGS, BHRC and ISC for
complete part , as well as catalog of historical (pre1900) and early- instrumental (1900-1963)
earthquakes provided By Ambraseys and Melvillefor extreme part, a uniform catalog of earthquakes
for the interest region has been provided. To
estimate the magnitude threshold (Mc) maximum
curvature method was used. Fig. 4 shows the
cumulative number of earthquakes with magnitudeand calculation of Mc. Before and after the main
shock, foreshocks and aftershocks happen and since
the complete list of earthquake usually do not follow
the Poisson distribution, all foreshocks andaftershocks must be excluded from the catalog bywindowing method in time and space domains byGardner and Knopoff [19]. According this algorithm
all events under the time- magnitude and distancemagnitude curve were considered as dependent
events and should be eliminated from catalog for
further analysis (Fig.5).

(2)d and c are constants. In order to establish
empirical relations between mb and Ms we applied
the regression method as shown in Fig.3.This
relation was used for converting all magnitudes to
Ms.

Fig.3 Regression between Ms and mb
DATA ANALYSISThe event list was homogenized and surface
magnitude , Ms was applied in the analysis. When
mapping b-value completeness of the employedearthquake catalogue is crucial.
Obviously, an incomplete catalogue cansubstantially modify the b-values. The fractions of
missing (small)events will result in a reduction of b .
Magnitude of completeness (Mc) is theminimum magnitude which above it is thought that
all earthquakes are reliably recorded, so assessing
magnitude of completeness is prerequisite toseismicity analysis. Mc magnitude was estimatedfrom the observed frequency magnitude distribution.
As follows from the diagram in Fig. 3 Mc ismagnitude of completeness where the frequency–
magnitude curve starts to deviate from a linear trend[17]. Mc = 4, meaning that the event list, covering
the cataloge period, is complete for magnitude 4
and bigger [18].

Fig. 4 Distributions of frequency Magnitude

537

GEOMATE-Nagoya, Nov.13-15, 2013

CONCLUSION

Fig.5 the timemagnitude curve

magnitudeandThe significant results of this research is thegeneration seismic parameters In this study, theparameter of Magnitude completeness (Mc) plays animportant role in determining the b-value anda-value, the Mc value in research location is around
4. The results show that b-value is equal to 0.82 ±0.3, the recurrence rate of the seismic events λ isequal to 0.40 ± 0.08 for Mc=4 and Mmax=8. 20 ± 0.54
(table 2). The seismicity analysis is just one part ofan integrated research about the vulnerability
characteristic of a region of the earthquake, therefore
other studies related to geotectonic, geology, faultrow, as well as earthquake history can help in
supporting the calculation and analysis of seismic
hazard in the region to mitigate earthquake disaster.

distance-

Table 2. Seismic parameters for study area

The maximum regional magnitude Mmax of anearthquake is the maximum limit of the magnitudeof a seismic tectonic source [20]. By constraining
the observed largest magnitude to be the expectedvalue of the largest observed magnitude, Kijko has
obtained an estimator for Mmax , which requires
knowledge of the mean seismic activity rate λ(λ=N/T) and the parameter b [21].
The constant coefficients a-value and b-value of
Guthenburg–Richter was obtained by the seismicity
data for this area. The constant ‘a’ is defined as thenumber of seismic events with a magnitude greaterthan M in a definite time interval and dependent on
the number of earthquakes, area of seismic zone andthe length of the time interval. The b–value is theslope of the b line is the seismicity factor and shows
the relation of number of weak and strong seismic[22].

Seismic
Parameters

MC

Mmax

λ

Value

4.0

8.20±0.54

0.40±0.08

a-valueb-value4.56

0.82±0.3

ACKNOWLEDGEMENTS
The support for the research presented in this paper
had been provided by the Universiti Sains Malaysia(USM) Short Term Grant No 304/PFIZIK/6312025.
The support is gratefully acknowledged.

538

GEOMATE-Nagoya, Nov.13-15, 2013[12] Berberian M. 1982. “Continental Deformationin the Iranian Plateau (Contribution to theSiesmotectonics of Iran (Part IV)”, Geol. Surv.
Iran, Rep. No. 52, 625p.
[13] McKenzie D P. 1972. “Active Tectonics of theMediterranean Region”, Geophys. J. R. Astr.
Soc, Vol.30, pp.109-185.
[14] Kijko A and Sellevoll M. 1992. “Estimation ofearthquake hazard parameters from incomplete
data files. PartII. Incorporation of magnitude
heterogeneity”, Bulletin of the SeismologicalSociety of America, Vol. 82 (1), pp 120-134.
[15] Ambraseys N N and Melville CP. 2005. “ Ahistory of Persian earthquakes. ”, Cambridge
University Press.
[16] Singh S K, Rodriguez M and Esteva L. 1983.
“Statistics of small earthquake and frequency ofoccurrence of large earthquakes along the
Mexican subduction zone”, Bull. Seism. Soc.
Am, Vol 73, pp. 1779-1796.
[17] Nuannin P, Kulhánek O and Persson L.2012.
“Spatial and temporal characteristics ofaftershocks of the December 26, 2004 andMarch 28, 2005 earthquakes off NW Sumatra”,
Journal of Asian Earth Sciences, Vol 46,
pp.150-160.
[18] Nuannin P, Kulhanek O, Persson L. 2012.
“Variations of b-values preceding large
earthquakes
intheAndaman-Sumatra
subduction zone”.Journal of Asian Earth
Sciences, Vol 61,pp.237-242[19] KnopoffL.
andGardnerJ.
1969.
“Homogeneous catalogs of earthquakes”,
Proceedings of the National Academy of
Sciences,Vol. 63, pp.1051-1054.
[20] Reiter L. 1990. “Earthquake hazard analysis”,
Columbia University Press, New York, pp. 245.
[21] Kijko A and Sellevoll M A. 1989. “Estimationof earthquake hazard parameters fromincomplete data files. Part I. Utilization of
extreme and complete catalogs with different
threshold magnitudes ” ,Bulletin of the
Seismological Society of America Vol 79, no. 3,
pp. 645-654.
[22] Amiri GG, Motamed R, Hashemi R and Nouri
H. 2006. “Evaluating the seismicity parametersof Tehran, Iran”, Proceedings of the Institutionof Civil Engineers-Geotechnical engineering,Vol. 159, pp.275-283.

REFERENCES[1] MoinfarA A and Naderzadeh A .1990. “An
immediate and preliminary report on the Manjil,
Iran earthquake of 20 June 1990”, Building andHousing Research Center, Ministry of Housing
and Urban Development, pp. 68-119[2] Niazi M and Bozorgnia Y. 1992. “The 1990
Manjil, Iran, earthquake: Geology andseismology overview, PGA attenuation, andobserved
damage”,
BulletinoftheSeismological Society of America, Vol 82, pp.
774-799.
[3] Berberian M, Qorashi M, Jackson J, Priestley K
and Wallace T. 1992. “The Rudbar-Tarom
earthquake of 20 June 1990 in NW Persia:
preliminary
field
and
seismologicalobservations, and its tectonic significance”,
Bulletin of the Seismological Society ofAmerica, Vol. 82, pp. 1726-1755.
[4] Gutenberg B and Richter CF. 1942.
“Earthquake magnitude, intensity, energy, andacceleration ” Bulletin of the SeismologicalSociety of America ,Vol 32, no. 3 ,pp. 163-191.
[5] Jafari MA. 2008. “The distribution of b-value indifferent
seismic
provincesof Iran”.
International Association
for Earthquake
Engineering.
[6] Sanchez JJ, Nutt S R, Power J A, Wyss M.2004.
“Spatial variations in th e frequency– magnitude
distribution of ea rthquakes at Mount Pinatubo
volcano” Bulletin of the Seismological Societyof America ,Vol 94,pp. 430 –438.
[7] Schorlemmer D, Wiemer S and Wyss M. 2005.
“Variations in earthquake-size distribution
across different stress regimes” Nature 437 Vol
22,pp. 539– 542.
[8] Mirzaei N. Mengtan G and Yuntai C. 1998.
“Seismic source regionalization for seismic
zoning of Iran: major seismotectonic provinces”,
Journal of Earthquake Prediction Research,
Vol.7, pp. 465-495.
[9] Abdi F, Mirzaei N and Shabani E.
2013 .“Ground-motion scenarios consistent with
PSH deaggregation for Tehran, capital city ofIran”, Nat. Hazards Earth Syst. Sci, Vol. 13, pp.
679-688.
[10] Dehghani G A and Makris J. 1983. “The
Gravity Field and Crustal Structure of Iran”,
Geol. Survey Iran, Rep, No. 51, pp. 51-68.
[11] Stocklin J. 1968. “Structural History and
Tectonics of Iran; A Review”, Bull. Am. Assoc.
Petrol. Geol,Vol. 52, pp. 1229-1258.

539

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

UNDERSTANDING TO PREDICT SOIL BEHAVIOR
J. Rajaraman1 K.Thiruvenkatasamy2 and S. Narasimha Rao3
ABSTRACT
Geotechnics is a branch of civil engineering which is firmly founded on experience. Theoretical concepts aredeveloped and continuously improved through a continuous analysis and interpretation of experimental data; inturn, experiments are used to validate the new theoretical concepts. A clear example is the development of the
Critical State Theory which is based on evidence coming from laboratory testing on reconstituted saturated clay.
Its extension to unsaturated soils, has been developed based on laboratory experiments on unsaturated soil
samples. The important Geotechnical property shear strength links of coastal soils, stability of slopes, landslides
and turbidity currents. Sometimes inter and multi-disciplinary approach is needed to analyze and predict soil
behavior. It is surprising to notethat when additional, new environmental information, or parameters areincluded, the present estimated shear strengths take paradigm shift. Thus the modified approach becomes morereliable. . In other words the new environmental information increases Reliability. Based on the analysis andinterpretation of documented cases as stated above, this paper makes a new conceptual model in interpretation of
the influence of Carbonate Compensation depth on turbidity currents in Abyssal plain and the geotechnicalbehavior of the sediments in Abyssal plains. Documented Cases are: 1) Liquid Limit of a soil calculated by using
distilled water is not representative sample in marine condition. The distilled water overestimates Geotechnicalproperty. 2) The failure envelope of reconstituted clay mixed with distilled water is different from the one mixed
with Nacl solution. 3) The Oedometer test on undisturbed specimens exposed to distilled water display higher
strains than tested in solution. Turbidity current consists of hydraulic loading ( Saline water ) inorganic /organic
loading (includes mineral skeletons /organic remains) and velocity. When the . turbidity current approaches
Lysocline layer. It begins to lose calcium carbonate particles. The velocity of the turbidity current slows down
and on the way sheds inorganic load and further slows down. At this point the concept of Soil is Rock on its way
to Ocean stops. The abyssal plain maintains moderate Shear strength. The abyssal plain is a controlledenvironment which controls any events of the restless earth around it. Thus the Carbonate Compensation Depth
influences both Turbidity Currents and Abyssal plain.

Keywords: Abyssal plains

Carbonate Compensation depth

Lysocline layer

Reliability

Shear Strength.

1.0 INTRODUCTION

2.0 DOCUMENTED CASES

Turbidity currents are a subclass of the broader
category of density currents. Density Currents also
are termed gravity currents. A density Current “isthe flow of one fluid within another caused by thedensity difference between the fluids. Turbidity
currents exist when the density difference is due tosuspended sediment and of course the fluids
involved are both water. Soil is Rock on its way to
Ocean ( Abyssal Plain ). Through Subduction Zone
soil is returned to continental crust as Rock. The
next cycle begins.

2.1 Case (i):The liquidity limit obtained with distilled water isabout two times the one obtained with Nacl solution,
regardless its molarity.

The weathering and stress history of thecontinental Rock transported as sediment as varying
stages to abyssal plain meets varying or different
environmental conditions on the way. Any
Experimental data collected on Continental areas
should be viewed with environmental information as
an additional parameter to interpret Marine
conditions. A few documented cases are discussed
below.

Take y axis twice the given scale. (wl in %) [1]A soil with a higher liquid limit will settle more.
Distilled water is not a suitable pore liquid because it
helps to obtain more settlement. In this context
saline water is a better pore fluid compared to540

GEOMATE-Nagoya, Nov.13-15, 2013

distilled water. The salinity of fresh water is in
between distilled and Saline Sea water.
2.2 Case (ii):
An example of possible effects of infiltration of
fresh water in a natural deposit subjected to swellingis shown in fig (2 ). The results of a Oedometer tests
carried out on two couples of undisturbed specimensof a type of clay shale taken respectively at a depthof 2.5 and 21m. A specimen of each couple wastested in a 1 m Nacl solution. The influence of thenature of the bath does not appear significant in thestage of compression, when the pore water isexpelled from the specimen, but becomes prominent
in the following stages of swelling, when someliquid is absorbed from the bath. The specimens
tested in the distilled water ( and specially the one
taken at the greatest depth) display higher strains
than those tested in the solution.

Fig.3b

2.4 Case (iv):
Figure 4 shows the results of conventional tests
conducted under a normal stress lower than swellingpressure ( around 0.6 M Pa) while part of specimens
were allowed to swell, as usual, for 48h,others weresheared only after 10-100 days during which theyexperienced a high volumetric strain. The differencein shear strength is very clear.
All data show that swelling in distilled water as
usual in laboratory, is responsible for a radical
change in soil behavior. In addition fig 4 shows thatthe effect of swelling is higher if secondary swellingis allowed.
The conceptual qualitative model of Turbidity
currents: Repeated short term environmental
changes influence in the long run the initiation of
Turbidity currents.

At the end of the tests performed in the Nacl
solutions, when the axial stress was 10 kPa, thesolution was substituted with distilled water giving
immediately rise to further strong soil deformation.

Fig.2[1] [2]
2.3 Case (iii):
Fig (3) shows the results if a triaxial tests onreconstructed normally consolidated specimen
obtained by mixing powdered clay with distilledwater and a 1M Nacl solutions. It suggests that that afriction angle at constant volume ( i.e. the critical
friction angle) can strongly depend on the nature of
the liquid. Similar data feature the residual friction
angle.

[1] [2]ratio

X axis MPa Fig. 3a[1] [2]

Fig. 4 .

[1] [2]3.0. RELIABILITY AND SOIL BEHAVIOR
3.1. Understanding To Predict Land Fill (Soil)
Shear Strength to Increase Reliability [4] [5]Decrease In Shear Strength Due To Man Induced
Reasons In A Bioreactor Land Fill.
Injection of Liquids in a Bio-Reactor Land Fillendangers the stability of waste mass slopes, for thefollowing reasons.
1 ) Increased driving force due to the increase inunit weight of the waste mass due to liquid injection.
2 ) Decrease in strength due to decrease in theeffective (inter-granular) stress corresponding to theincrease in pore pressure that result from liquid
injection(leach-ate head build-up.
3 ) Decrease in strength due to transformation of

Y axis Void
541

GEOMATE-Nagoya, Nov.13-15, 2013

Waste
mass by the biological and chemical
processes that enhance degradation, turning thewaste into an inherently weaker material.
Lack of reliable data on shear strength of degradedwaste is the main reason for all the problems/.
Isenberg et al (2001) conducted sensitivity modelingusing a typical land fill.
Configuration to better understand how potential
reduction in shear strength coupled with increases inunit weight will influence waste mass (soil ) slope
stability.
3.2 Understanding to Predict Shear Strength of
Coastal and Shallow Water Marine Sedimentwith Increase in Reliability.
Hyperpycnal flow: At a river mouth, a flow of riverwater that is denser than the water in the basin
receiving it. This occurs during floods. The densewater flows beneath the basin water, as a density
current, carrying sediment beyond the shore andinhibiting the pro-gradation of a delta
When Hyperpycnal flow erodes a shallow bed
changes the soil behavior. Shallow layers of highly
plastic marine OC clay subjected to swelling
Udepending shear strength decrease due toinfiltration of fresh rain water which presents a very
different composition than the natural pore liquid.
The accumulated influence of the above changes inthe environment will induce long term slope failure
even in a gentle slope

Fig. 5 b.
3.4 Understanding to Predict Shear Strength ofMarine Turbidity Sediments of Deep Water
before Passing through CCD, with Increase in
Reliability.
Carbonate Compensation Depth ( CCD ). CaCo 3
shells ( tests ) sink from surface water Tests may
reach a depth where water is significantly undersaturated with respect to CaCo 3 . At this depth,
called Lysocline, shells begin to dissolve. In themodern Oceans, there is also a depth at which there
is no longer any free CaCo 3 . This depth, called the
Cabonate Compensation depth CCD = - 4 Km.
CaCo 3 tests accumulate only if they settle on Sea
Floor above the CCD.

3.3 Understanding to Predict Shear Strength ofMarine Slope Sediments of Intermediate Water
Depth with Increase in Reliability.
Like Mineral Particles ( Solids of the Soil
Predominant ) CaCo 3 Skeleton (particles) could beclassified as Angular, Sub-angular, Sub-rounded,
Rounded and well rounded. The angle of the internal
resistance (phi) decreases due to weathering ofparticles from angular to well rounded stages. In thedown slope depths the shear strength is less because
angle of friction is less.

3.5 Understanding to Predict Shear Strength ofMarine Turbidity Sediments of Deep Water after
passing through CCD with Increase in Reliability.
The final stage of Turbidity Current consists ofhydraulic loading (saline water ) Inorganic/Organic
loading ( includes mineral skeletons/Organic
remains) and Velocity. The turbidity Current Passing
through CCD it begins to lose all the Calcium
Carbonate particles. The Velocity of Turbidity
Current slows down and the Shear Resistancedecreases and spreads as Submarine fans. At thispoint the concept of Soil is Rock on its way to
Ocean stops.

Fig.5.a542

eGEOMATE-Nagoya, Nov.13-15, 2013

Turbidity deposits on a horizontal slope with
contours.
Before passing ccd.

x- position of down slope
y-position of crossslope.
After passing ccd.

Fig.6b.

Fig. 6a3.5.1 A Conceptual hypo- Cycloidal Model andExplanation for the Behavior of Turbidity Current.
In Fig (7 ) the pore with Saline Water as Pore Fluid
is shown as a circle with radius ‘a’ and the Solid
Calcium Carbonate representing angle of internal
friction, is shown as solid circle with radius ‘b’ . In
other words a solid circle with radius ‘b’ is rotating
inside a fluid circle of radius ‘a’. At selected points
on the circumference of this fluid circle the particle( CaCo 3 ) makes contact to mobilize shear resistance.
Taking a = R and b = r. The Selected number ofcontacts depends upon R/r ratio. The figure (7 ) is aself explanatory for the particle behavior. Here themathematics part is omitted.
Before reaching lysocline or CCD layer, the pore
fluid and solid CaCo 3 fertile balance each other instrength to maintain dynamic equilibrium. The
friction resistance is due to solid particle resistancebalance each other the pattern of the fan is more orless circular in nature. When these solid particles are
dissolved, the pore fluid circle alone exists withradius R. The small ‘r’ is already dissolved. The
disappearance of solid particles and filling by fluid
can be imagined, as a reverse consolidations thefluid is expelled and solid particles come closer toeach other. Where as in the marine environment( CCD ) the solids is expelled and fluid is closer the
space occupied by solid ( CaCo 3 ). Under these
conditions the fluid dominates and the pattern of thefans are elongated elliptical one because the fluid
after the collapse of the Turbidity Current will run
further distance creating elliptical fans.

Fig.7.Figure 8 is an illustration of the position of the
ccd and lysocline and their relationship to ocean
bathymetry, carbonate accumulation rate andcaco3 content.

Fig.8.

543

Hypo –cycloidal model with different b.

GEOMATE-Nagoya, Nov.13-15, 2013

and silt even in abyssal depth. Any combination of
the environmental factors which will change theShear strength of sediments will become theadditional information and the reliability will
increase the correct prediction of shear strength
within that particular environment.

3.6 Understanding to Predict Shear Strength ofAbyssal Sediments in Abyssal Depths withincrease in Reliability.
The abyssal plain is a naturally Controlledenvironment which controls any event of the restless
earth around it. In abyssal plain carbonates can not
impart shear strength as particles but in dissolved
state Calcium Carbonate with saline water can
influence shear strength. In abyssal plain sediments
derive shear strength from two sources ( 1) Cohesionof abyssal clay ( pure shear or Coaxial component ofshear strength). ( 2 ) Angle of internal friction (phi )from sand (Simple shear or Non-Coaxial componentof the shear strength ) along with mud and oozes.
The third factor is saline water which modifies shear
strength according to the environmental needs since
CCD is not a fixed depth. It changes withenvironment and sensitive to Carbon stress from
Continental areas.

5.0 REFERENCES[1] Di Maio C, Onorati R ( 2000 ) . Influence ofpore liquid composition on the shear strength of anactive clay In: Bromhead E. N Dixon and M.L Ibsen(eds ) , Proceedings. 8th International .Symposiumon Landslides, Cardiff 1: 463-468.
[2] Picarelli L Di Maio C.Olivares L . Urciuoli G(1998). Properties and behavior of tectonised Clay
Shades in Italy In:Evengelista A and L Picarelli(eds). Balkema Proceedings Second International
Symposium on The Geotechnics of Hard Soils, Soil
Rocks, Napoli 3,pp. 1211-1241.
[3] (1964) . Shear Strength and related properties ofsediments
fromexperimental
Mohole( Guadalupesite ) Journal of Geophysical Research
Volume 69. Pp 4271-4291[4] Kavazanjian.E ., Hendren D., and Corcoran,
G.T ., strength and stability of bio-reactor landfills.,
PP 63-70 in proceedings of the SWANA land fill
symposium, 2001.
[5] Isenberg, R.H.,Law, J.H. Neill., and Denver, R.
J., Geotechnical aspects of land fill bioreactor design
is stability a fatal blow? Pp, 51-62 in proceedings of
the SWANA land fill symposium, 2001.

Fig. 9. Influence of carbonate content on
undrained
strengthofsediments
fromexperimental Mohole.
In Fig. 9 . When the Carbonate percentage is very
low the Cu/p predicted is equal to Cu/p observed,
where Cu = un-drained shear strength and P =Vertical effective stress. This information increases
the reliability and prediction becomes meaningful.
Any additional information will always help in
propagation of the predicted value of shear strength
to the true value of shear strenngth of sediments.
4.0 CONCLUSIONS
1. Soils/ Sediments are Rocks on its way to Ocean.
2. The Moving Sediment is subjected to changing,environmental factors. The Shear Strength changes
according to the existing conditions.
3. Starting from ( urban ) continental areas to deep
ocean floor the reduced shear strength is a functionof different environmental parameters.
4. The important environmental factors are:i) Saline Waterii) Hyperpycnal flowiii)
Oversteepening of slope. iv) Calcium Carbonate
shells.
v) Lysocline layer. vi) Carbonate
Compensation depth . vii) Flat or very slight slope ofAbyssal plain. viii) Turbidity Currents. ix ) Shapeand size of Soil Particles. x ) The resistance of sand544

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CASE STUDY ON SHALLOW FAILURE OF CONGLOMERATE AND
SILTSTONE SLOPES DUE TO A HEAVY RAINFALL
Satoshi Kagamiahra1, Satoru Shibuya1, Byeong - su Kim2, Shunzo Kawajiri3, Tara Nidhi Lohani1 andTakashi Okimura4
2
3
1
Kobe University, Okayama University, Railway Technical Research Institute, Construction Engineering
Research Institute

ABSTRACTThis paper describes a case study in which the mechanism of shallow slope failure occurred in Aichi
Prefecture on October 8, 2009 has been addressed. The slope that collapsed due to a heavy rainfall of Typhoon
No. 18 was comprised of a sedimentary soft rock. The total rainfall by this typhoon accounted as much as
250mm/day, and the rainfall at the instant when the slope failed was 75mm per hour. A field test of the slope
section adjacent to the failed site was carried out. The undisturbed soil samples were also collected from thecollapsed slope plane so as to determine the strength and saturation characteristics of the soil layer where thefailure took place. A series of direct box-shear test (DST) on the undisturbed specimens under low confiningpressures were then performed. In addition, a simulation of the rainfall infiltration for Typhoon No. 18 was
carried out by using a saturated/unsaturated ground seepage program. A slope stability analysis was also
performed based on the results of DST. By comparing the result, it is found that the slope was saturated due tothe rainfall infiltration, and the shallow slope failure occurred because of a decrease in the shear strength of theslope.
Keywords: shallow failure, Conglomerate and Siltstone Slopes, direct shear test, the saturated-unsaturated
seepage program

SUMMARY OF SLOPE FAILURE SITE AND
THE WEATHERINTRODUCTION
The Typhoon No. 18 had knocked the Chita
Peninsula of Aichi Prefecture on October 18, 2009 andcaused a heavy damage of building structures andflooding. A hill slope facing towards the Nagoya
Railway, Tokoname Line, was collapsed and thelarge amount of accumulated debris has stopped thetrain operation for quite a long period. The total
rainfall by this typhoon accounted for 250mm/day
and the rainfall at an instant when the slope actually
failed was 75mm per hour.
In this post-failure study, the mechanism behindthe slope failure mentioned above was investigatedby performing a series field tests, laboratory tests
and FEM simulation. The field tests were carried out
at a slope section adjacent to the failed portion. The

70

Hourly Rainfall

60

Cumulative Rainfall

50

200
150

40
30

100
50

10
0

0

2009/10/5 2009/10/6 2009/10/7 2009/10/8
TIME

Figure 1 Rainfall observation data at the slope
failure site

545

Cumulative Rainfall (mmconsiderably low confining pressures, so as tosimulate the shallow in-situ condition. The
simulation of the rainfall infiltration was done byusing a saturated/unsaturated ground seepage
Program. A slope stability analysis was thenperformed based on the results of direct shear test
and saturated-unsaturated seepage analysis.

250

80

Hourly Rainfall (mm)the collapsed slope surface to determine the strength
properties of the soil layer involved. In thelaboratory, series of direct shear tests were

Figure 1 shows a rainfall observation data of thetyphoon No. 18 prepared by the Chita City Fire
department at the failure site. As can be observed
from this figure, the precipitation, until 5:00 a.m. on
October 8 from 0:00 a.m. on October 7, was about
93mm. The record high rainfall for an hour
thereafter, reached as high as 75mm per hour andhad initiated a shallow slope failure of approximate
dimension, 20m wide, 20m high and 1.5m thickness(Photo 1).

GEOMATE-Nagoya, Nov.13-15, 2013

The Typhoon was also accompanied by strong
wind (7~30m/sec) in north-northwest and northwest
direction [1]. As the slope failure under investigation
was also facing north-west, it is believed that thestrong wind blow has also played a partial role in the
failure.

borehole data. The red dots in the figure show thesection with Nd =5. For the region having Nd <5, Vsof siltstone layer is <= 120 m/s and that ofconglomerate is <= 160 m/s. Therefore, not only Ndvalues but also the type of geological formation has
affected the Vs magnitude. The figure also points
that there is strong weathering at shallow depths andthe velocity is quite low as compared to the baserock mass.
Nd value

0

10

20

30

40

50

0

shallow failure Non shallow failure
survey lines

50

Depth (cm)100

Photo 1 Shallow landslide site at Aichi
Prefecture, Japan

150

200

The convex type hill slope, where the failure
occurred, had relative height of 30m, NW
orientation, and the slope gradient of 40-45 degrees.
The geology is understandable by the presence of a
Tertiary (Tokoname formation) conglomerate andsiltstone layers. The dip slope is about 5-15 degrees
as compared to the slope inclination. Although mostpart of slope collapse involves the heavily weatheredsiltstone rock, some part of heavily weatheredconglomerate layer has also slipped together.

250

300

Figure 2 Nd -value against the penetration depth
from dynamic cone penetration test(m)

表面波探査解析結果

35.0

Bor C-3

30.0

FIELD SURVEYS AND LABORATORY TESTS

S 波速度

Vs

500
20.0

Elevation

In-situ investigation
標In order to identify the collapsed mechanism, a
simple dynamic cone penetration test was performedat the adjacent undisturbed slope section of thefailed site, shown by a straight line in Photo 1, by
assuming similar topography and cross-section tothat of the failed mass. Figure 2 shows the result
which indicates that the rate of increase in Nd values
with depth is different at around Nd = 5. Including
the landslide depth from site observation, it can be
estimated that failure took place across the section
where Nd < 5. The information on sectional soil
profile was further added by undertaking a PS
logging test, a surface wave exploration and bydrilling boreholes.
Figure 3 is a two-dimensional shear wave
velocity (Vs) sectional profile obtained from thisstudy. The PS logging result was applied in drawing
the profile by surface wave exploration analysis inorder to increase the accuracy. Besides, the layerboundary identification was done by observing the

Conglomerate

25.0

Bor C-2

15.0

400
330

Siltstone
Sandstone

280
240
200

高 10.0160

Siltstone

5.0

140
120

0.0

100
80

-5.0

60
40

-10.0

(m/sec)0.0

5.0 10. 0 1 5.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0

距 離 程Horizontal distance(m)
縮尺（横）＝1/50

Figure 3 A two-dimensional sectional profile ofshear wave velocity (Vs)Laboratory test
In order to understand physical and mechanicalproperties of the collapsed soil, undisturbed samples
were collected from the strongly weathered siltstone
and conglomerate layers by a nail samplingtechnique [2].

546GEOMATE-Nagoya, Nov.13-15, 2013

Shear wave velocity of the collected undisturbed
samples was evaluated in the laboratory by using a
consolidation apparatus fitted with bender elements(hereinafter referred to as BE) [3]. The undisturbed
samples were also tested in a direct shear apparatus
to determine the shear strength parameters (cohesion,c and friction angle, φ). Table 1 shows the physicalproperties of the undisturbed samples. The physicalproperty tests show that the strongly weatheredconglomerate can be classified into a clayey-sandygravel, whereas, the strongly weathered siltstone isclassified as a sandy clay.
Table 1

Bor C- 2（ シ ル ト 岩）

Slt

DLc:strongly
weatheredDLs:strongly
weathered siltstone

clayey-sandy-gravel

sandy clay

3

Soil paticle density ρ (g/cm )

2.647

2.602

Natural water content wn(%)

13.7

18.3

Wet density ρ (g/cm )

1.527

1.391

Dry density ρ (g/cm3)

1.346

1.176

Bor C- 3（ 砂 礫 岩 ）

Cg

0
試料 採
取深 さ

)
m
( 2
z,
度
深

Physical properties of soil

Soil classfication3of conglomerate stratum, (Vs)lab,u is far above the (Vs)f .
It is likely that the result was affected because of thepresence of large-sized gravel particles in the sample
as compared to the propagated shear wave
wavelength [3]. The (Vs)f for disturbed specimen isindeed similar to that shown by field test (Vs)f.

4

6: 乱 さない 試料: 乱した試 料

0

200
400
S 波 速 度 , V s (m/s)○ disturbed■ undisturbed－: PSin-situ
検層
250
500
S 波 速 度 , V s (m/s)

Vs(m/s)Figure 4 Shear wave velocity profile from in-situ
and laboratory tests

BE tests were performed by using undisturbed
samples and those prepared by molding the sampled
soil from the site, for which, in-situ moisture content
overburden stress and wet density states werereproduced. The consolidation pressures applied tothe specimens were relatively low by considering thein-situ stress levels involved in the shallow failure.
Figure 4 shows a shear wave velocity profile fortwo different types of geologic layers, siltstone andconglomerate. In the plot, shear wave data obtained
from the laboratory BE tests for undisturbed, (Vs)lab,u,and disturbed siltstone samples, (Vs)lab,d, and thoseevaluated by field PS-logging, (Vs)f are compared.
The following points for siltstone stratum areunderstandable. Firstly, the (Vs)f and (Vs)lab,u at about
1m depth, the depth where sampling was done,
substantially match each other by confirming thefact that the effect of sample disturbanceincorporated during sampling, while transporting to
the laboratory and specimen preparation process isquite insignificant. Secondly, at deeper depths below
1.8m, (Vs)f is larger than (Vs)lab,u, suggesting that the insitu soil is significantly aged and structured atincreasing depths, which is absent in the sample thatwas stressed beyond the in-situ overburden stress.
The shear wave velocity for remolded (disturbed)
samples, (Vs)lab,d, remain slightly on the lower side of(Vs)lab,u, inferring a partial destructuration ofundisturbed samples [4]. On the other hand, in caseIn order to determine the shear strengthparameters, drained constant pressure direct shear
test were performed on undisturbed samples, both atunsaturated (natural water content) and saturated
conditions [5]. The test was conducted withcylindrical specimens of 6cm diameter and 2cm
height. Shearing was conducted at the speed of
0.1mm/min after consolidating at three different
vertical stresses, 15kPa, 30kPa, 50kPa respectively,
for each series.
Figure 5 is a graph showing a relationshipbetween the applied vertical stress, σv, forconsolidation and shear stress, τ, for both formations.
It clearly confirms a comparatively higher strengthof specimens at unsaturated condition than that when
they are saturated. On the other hand, on comparing
the slope of failure lines, angle of internal friction
can be said to be roughly equivalent for bothsaturated and unsaturated states. Furthermore,cohesion intercept interestingly vanishes on
saturation by inferring a non-cohesive nature of soil
and also a complete loss of suction during saturation.
The above trend is valid for both siltstone andconglomerate formations.

547

GEOMATE-Nagoya, Nov.13-15, 2013state analysis, the rainfall by typhoon No. 18 for two
weeks period before the actual slope failure wasconsidered.

60)

Shear stress,τ(kPa)Sa
h kP 40
ea (
rs 
,
tr 力
es
s 応 20
,τ 断
(k ん
P
a) せ

Siltstone: Undisturbed
Bor C- 2（ シルト岩）
乱さない試料Unsaturated

不飽和状態
c = 9.0 kPa
φ = 31.8°

Rainfall infiltration conditions
Saturated
飽和状態

Conglomeratec = 0 kPa
φ = 31.8°

Siltstone

060

Figure 6 A 2D model section used for seepage
analysis

Bor C- 3（ 砂礫岩）
Conglomerate: Undisturbed

Shear stress,τ(kPa))
a
乱さない試料kP
40(
Unsaturated
不飽和状態

,
c = 10.0 kPa
力
Saturated
φ = 35.2°
飽和状態
応 20
c = 0 kPa断
φ = 35.2°
ん
せ
0
0
20
40
60
鉛直応力, ⌠v (kPa)

Conglomerate

Siltstone

Vertical stress,σv(kPa)

Figure 5

Mohr-coulomb failure line
Figure 7 A 2D mesh model used for seepage
analysis

ESTIMATION OF THE COLLAPSEMECHANISM BY STABILITY ANALYSISAND SATURATED-UNSATURATEDSEEPAGE FLOW ANALYSIS
Saturated-unsaturated
model

seepageflow

Table 2 Seepage flow analysis parameters
hydraulicconductivity

analysis

A saturated-unsaturated seepage flow analysis
with a two-dimensional cross-section was conductedin order to simulate the rainfall infiltration conditionof the landslide area. The model uses a seepage flow
advection-dispersion code, "Dtransu-2D". The
model X-section before failure was taken as that of
the survey line adjacent to the failed slope by
Typhoon 18. Boundary conditions were set in thefollowing way. The sloping surface is taken as apermeable boundary for rainfall infiltration, thewater level on sideways is kept at a constant leveland decided as per the well and river water levels in
the close proximity. Figure 6 shows the set boundary
conditions and Figure 7, the analysis model.
The permeability parameters used in the analysis,
which were obtained from laboratory tests as well as
literatures, were as shown in Table 2 [6]. About theunsaturated characteristics of strongly weatheredlayer, water-retention curve was obtained bylaboratory tests. The hydraulic conductivity ratio
curve was estimated by Van Gennuchten formula[7]. For steady state analysis, a mean annual rainfallof the site from the nearby weather stations, 1340
mm, was used. On the other hand, for non-steady-effective
Porosity

specificstorage

DLc:strongly weatheredconglomerate

2.62×10-20.51

2.0×10-4

DHc:weatheredconglomerate

1.30×10-3

0.51

1.0×10-4

CLc:gconglomerate

2.76×10-6

0.51

3.3×10DLs:strongly
weathered siltstone

2.62×10-4

0.56

2.6×10DHsweatheredsiltstone

2.76×10-90.56

1.3×10

CLs:siltstone

2.76×10-9

0.56

3.3×10-6

-6

-3

-3

Results of saturated-unsaturated seepage flow
analysis
The temporal change of degree of saturation isshown in Figure 8. It can be seen that degree ofsaturation of the strongly weathered rock increases
with time. Particularly, a higher degree of saturation
due to the pooled water at the boundary of highly
permeable weathered conglomerate and lesspermeable weathered siltstone layer is clearly noted.
Stability analysis model
Stability analysis was performed on the model
shown in Figure 9 based on the result of saturatedunsaturated seepage flow analysis. The topography
548

GEOMATE-Nagoya, Nov.13-15, 2013

Table 3 Slope stability analysis parameters

after the failure has been taken as the shape of slip
surface. Table 3 shows the soil parameters used in
the analysis. Unit weight of strongly weathered rock
was altered depending on the degree of saturation[8]. Shear strength parameters were adopted fromthe laboratory shear tests conducted at low confiningpressure. Suction pressure was estimated by using
Van Gennuchten model [9], [10]. Figure 10 shows
the relationship for unit weight and the suction stress.

wet unit weightcohesionγt(kN/m )c(kN/m )friction angle
φ(degrees)

DLc:strongly weatheredconglomerate

15.2

10.0

35

DHc:weatheredconglomerate

15.2

15.2

35

CLc:conglomerate

17.1

44.3

37

DLs:strongly weatheredsiltstone

13.9

9.0

31

DHsweathered siltstone

15.4

19.6

31

CLs:siltstone

16.4

23.5

32

3

2

26

22
20
18
16
14
12
10
0

The strongly weatheredconglomerate
The strongly weatheredsiltstone

cohesion c(kN/m2 )3

Unit weight γt(kN/m )

20
18
16
14
12
10
8
6
4
2
0

The strongly weatheredconglomerate
The strongly weatheredsiltstone

24

20
40
60
80 100Degree of saturation Sr(%)

0

20 40 60 80 100
Degree of saturation Sr(%)

Figure 10 Variation of unit weight and cohesion
values against the degree of saturation used in the
model
Results of stability analysis

Figure 8

Figure 11 shows a time-wise variation in thefactor of safety from the stability analysis. The
continuous rainfall infiltration has lowered the safety
factor from 1.0, thereby loosing the mechanicalbalance of the sloping mass. The instant is consistent
with the time of the largest amount of rainfall perhour that initiated the landslide.

Analysis results (saturation distribution)

DHc

2.00

DLc

DLs

DHs

Factor of safety

CLc

1.50
1.00
Facter of safety
0.50

Limit factor ofsafety

CLs

0.00
390

Figure 9

A sectional model used for stability
analysis

395

400

405
410
Time(hours)

415

420

Figure 11 Variation in the factor of safety against thetime from stability analysis

549

GEOMATE-Nagoya, Nov.13-15, 2013of water took place at the boundary of two soil
formations due to a smaller permeability of soil on
the downward side, which then further added
saturation of down-slope layers, and, iii) the suction
reduced so much so that the disturbing force
exceeded the shear strength of soil formations
causing a slope collapse.

CONCLUSION
The findings of this study are summarized below.
In this post-failures study of slope failure, asurface wave exploration technique wasapplied for in-situ testing and the sampled soil
was further tested in the laboratory to evaluate
strength parameters. When applied at the steep
failure site, it was found that shear wave
velocity difference observed for various soil
strata from surface wave exploration method
appeared accordingly in the shear strengthparameters in laboratory tests. Therefore,
surface wave exploration is quite useful andquick method in order to obtain twodimensional
sectional
informationofmechanical properties of soil layers.
 Internal friction angle, φd, shown by the slopeof failure line, is roughly equivalent for bothsaturated and unsaturated conditions. However,cohesion intercept, cd, disappears completely
confirming a complete loss of suction on
saturation. Although conglomerate stratum
show slightly higher strength, siltstone
formation also has similar trend.
 Result of the unsaturated-saturated seepage
flow analysis shows a tendency of higher
degree of saturation at the boundary of highly
permeable strongly weathered conglomerate
stratum and that of less permeable strongly
weathered siltstone.
 Result of the stability analysis, by using a
distribution of degree of saturation obtained
from the unsaturated-saturated seepage analysis,shows that factor of safety turned below 1.0
and the slope collapsed at the same instantwhen the site observed the maximum rainfall
per hour.
With the results and discussion above, thecollapse mechanism of the weathered conglomerateand siltstone slope could be related to be the
combination of, i) heavy rainfall at the site
penetrated to the weathered soil layers at shallow
depth and unit weight of soil increased, ii) pooling

REFERENCES[1]

Japan Meteorological Agency web site,
http://www.jma.go.jp/jma/indexe.html[2] Chiaki A, et al. “Physics and mechanics test andsampling of decomposed granite soil is not
disturbed”, Soil Engineering Society, 1985,
pp.89-92.
[3] Tomohito H, “Shear wave velocity andliquefaction strength of freezing sampling andreconstituted specimens”, Proceedings of Japan
Society of Civil Engineers Hokkaido branch.
Vol. 58, 1994, pp. 526-529.
[4] Kansai Branch of The Japanese GeotechnicalSociety, “The disaster investigation by thetyphoon No. 9 in 2009”, 2009.
[5] Shibuya S, et al “Interpretation of direct shear
box testing of sands as quasi-simple shear”,
Geotechnique, 47, No. 4, 1997, pp.769-790.
[6] The Japan Geotechnical Society “Measures andenvironmental impact assessment for the
groundwater flow conservation”, 2004.
[7] Van Genuchten “A closed-form Equation for
Predicting the Hydraulic Conductivity of
Unsaturated Soil”, Journal of Soil Science
America, Vol.44, 1980, pp.892-898.
[8] Japan highway public corporation, “Design
guidelines”, Vol.2, 2000, pp. 2-9.
[9] Daizo K, “The relationship between themechanical behavior and the state of pore waterin unsaturated soil”, Proceedings of Japan
Society of Civil Engineers, Vol. 535, 1996, 8392.
[10] Research Committee on Evaluation of
permeability
characteristics
unsaturated“Analysis of the current state on permeability
evaluation in unsaturated soil”, The Japanese
Geotechnical Society, 1996, pp.11-13.

550

Authors Index

B
113

A
B. A. M. Shahriar
A. Kadir Marsono

304

47
B. A. MirA. Nishida416

89
B. BaiA. Oya493, 505

274
Bithin Datta

A.Kumar475

389
Brian G. Jones

A.M.K.N. Nadeesha

32

164, 169
Bujang B.K.Huat

Abdoullah Namdar

545

339
Byeong - su Kim

Abdual Salalm Mehdi Saleh

475

Abdul Naser Abdul Ghani

384

C

Abdul Saboor Rahmany499

C F Leung59

Abdul Sukorand

487

C. Gallage

389

Adhilla Ainun Musir

384

C.T. Nguyen

298

Adnène KASSEBI

523

Chattarin Sunsin

357

Afshin Asadi

32

Chen, B.K.

229

AGLIPAY Mary Roxanne

262

Cheng-Di Dong

464

Akihiko HAYASHI

394

Chih-Feng Chen

464

Akihiro Mieda

422

Chih-Hsin Hu

Akio Takigawa

422

Chiu-Wen Chen

464

Akira Asaoka

2

Chung-Yue Wang

280

Alejandra María Gómez Jiménez

12

Ali Ismail Al Jubory

475

D

Aniroot Suksan

235

D.H Lee154

Apichit Kumpala235

Dai Nakamura

71

Ardyono Priyadi

411

Daisuke Hayasaka

427

Asano Kanako

205

Dicky Nova Wardana

411

Ashish Juneja

304

Dimas Anton Asfani

411

Atsushi Mikami

241

Donovan Mujah

148

Ay Lee Saw

59

Du N L

286

551

280, 517

Authors IndexE
Ehsan Momeni
Erwin Oh

47

Hiroshi Yamato53, 310

Hiroyuki Kyokawa

F

142
95, 205

Homayoon Ganji

499

Hoshina T

286

Fauziah Ahmad

148

Houman Sohaie

47

Ferney Quiñones Sinisterra

12

Hyeon-Tae Kim

379

Fouad Zargouni

523

Fumio Tatsuoka

345

I
Ideris Bin Zakaria

G
G. Ren258

Gary chai53, 310

164, 339

Inge Hoff

333

Isobe K

286

Girum Y. Yesuf

333

J

Goh Chin Ong

217

J Wu and M Ryu

154

Guangli Xu

268

J. Rajaraman

540

Gurumurthy Hegde339

J. Ramanujam

389

J.F. Camacho-Tauta

187

J.F. Gaitán-Serrano

187

Jaehun Ahn

363

113, 181, 199, 205

Jan Vaslestad

333

H. Tokhi

258

Je-Min Baek

323

H. Yano481

Jennifer E. Nicks

252

H. Yukimoto

89

Jidong Teng

268

H.Y Wang

416

Jim Shiau

175

Ha H. Bui

274, 298

Jin-Suk Hur323

Haider Al-Ani

53

Jinwoo Jung

363

Hajime Narioka

499

Jirayut Suebsuk

235

Helsin Wang

280

Jun Sugawara

83

Hemanta Hazarika

148

Junichiro Takeuchi

452

Hideto Nonoyama

136

Junpei Saito

327

H
H. M. Shahin

552

Authors Index

Márcio Muniz de Farias

K

12

K. Hayano

169

Mariana Mohamed Osman

K. Shima

481

Masaaki Kondo

499

K. Yamamoto

481

Masafumi Nakagawa

511

K.Thiruvenkatasamy

540

Masahiko Katoh

445

Kaneda K

286

Masaki Makano

142

193, 373

Masaki Nakano

130, 136

Kaoru Kobayashi

458, 469

Kato Morihiro

181

Masashi Ito

394

Kazunari Suzuki

142

Masaya Hinokio

142

Kazunobu Matsumoto

193, 373

Masayuki Fujihara

452

Kazuya Inoue

433, 439

Masuda Saki

199

Kenichiro Nakarai

247, 394

Mauridhi Hery Purnomo

411

Kenji KAWAI

394, 400

Md. Shahidul Islam

113

Kimitoshi Hayano

223

Mehdi Pouragha

24

Kiyota Takashi

107

Melia K. Iwamoto

252

KONAGAI Kazuo

262

Michael T. Adams

252

Kyokawa Hiroyuki

107Michiyuki Harata

345

Ming-Hung Chen

517

Minoru Kawaida

142

L
Leila Eslami-Andargoli

53

Mio Susumu

199

Lyn A. Gettys

427

Miura Minami

160

Mohammad Raihanul Islam

406

Mohammad Shariful Islam

113

M
M. Iwata

89

Mohd Ashraf Mohamad Ismail

217

M.P. Ortiz-Pulido

187

Mohd. Nawawi

535

M.R. Islam

169

Morikawa Yukihiro

Mabrouk Touahmia

119

Moshe Livneh

65

Maeda Kenichi

211

Muatasam Hassan

475

Mahsa Amirabdollahian

505

Muhammad Ekhlasur Rahman

148

Man-Kwon Choi

379

Muhammad Irfan

292

553

199, 211

Authors Index

Musahaq Ali

42

Phacharaporn Bunyawanichakul

357

Mustapha Boukendakdji

367

Phillip S.K. Ooi

252

Mutsumi Tashiro

124
R

N

R. Fukagawa

274, 298

N Minakata

154

Ramli Nazir

47, 77

N. Hiraoka

274

Ranjith, P.G.

229

N. L Ukwattage

530

Richard Wan

24

Na Li

317

Romziah Azit

217

Nakai Teruo

199

Ryan Kemp

175

Nasim Mosavat

310

Ryoki Ohashi

95

Nguyen Hong Son

124

Ryuta Ogawa

223

Noam A. Livneh

65

Norzani Mahmood

217

S

Noushin Naraghi Araghi

535

S A Tan

59

Nur Khairiyah Basri487

S Nishiyama

154

Nur Sabahiah

487

S. Jayakody

389

Nurmunira Muhammad

164

S. Narasimha Rao

540

Sabah Ahmed Ismail

475

Saki Matsuyama

439

O
Ohashi Ryoki

205

Sarah Khosravani

24

Ohtsuka S

286

Satoru Ishiguro

406

Okuda Kazuaki

181

Satoru Kawasaki

101

Om Prakash

487

Satoru Nakafusa

373

Osman El Hussien

77

Satoru Nakafusa

193

Satoru Shibuya

323

Satoru Shibuya

545

PP. Rajeev

274

Satoru Shimobe

327

P.G Ranjith

530

Satoshi Kagamiahra

545

Peng Yin

317

Satoshi Yamashita

71

554

Authors Index

Seungbae Kim

363

Takayuki Sakai

Shao, S.S.

229

Takeshi Sato

445

Sharma Keshab

107

Takuya Takahashi

452

Shibuya Satoru

160

Tara Nidhi Lohani

323, 545

Shigeko Haruyama

42

Taro Uchimura

Shinsuke Matsumoto

379

Tatsuya Ishikawa

Shotaro Yamada

130

Teruo Arase

427

Shouhei Ogawa

445

Teruo Nakai

95, 181, 205

Shun-Min Lee

517

Tetsuya Tokoro

Shunzo Kawajiri

545

Thammakorn Sasanawin

Shushi Sato379

Toshihiro Morii

193, 373

Si Senfi

499

Toshihiro Noda

124, 136

Suksun Horpibulsuk

235

Tsutomu Tanaka

433, 439

Syahriah Bachok

458

Syahriah Bachok

469

W

Syed Mustafizur Rahman

535

William T. HallerT

130, 142292
71, 351

71, 351
357

427

X

T Yano154

X.W Tang

416

T. Hara89

Xinye Han

345

T. Kato89

Xue J. Huan

427

T. Nakajima

481

T. Negami

481

Y

Taizo Uchida427

Y. Futsuhara

481

Takafumi Inoue

241

Y. Honjo

89

Takamitsu Kajisa

499

Y. Otake

89

Takashi Danjo

101

Yafei Zhang

268

Takashi Kiyota

345

Yao-Jen Hsu

517

Takashi Okimura

545

Yasunori Mori

499

Takayuki Fujiwara

433

Yi Yang317

555

Authors Index

YM Cheng

317

Yongzhen Peng

422

Yuan Zhang

351

Yuji Hatano

400

Yuki Hasegawa

379

Yuki Yokoyama

247

Yung-Chuan Chou

517

Yutaka Okame

400

Z
Zakaria Hossain

42

Zakiah Ponrohono

469

Zhang Feng

211

Zulfadly Azizi Bohari

458

Zulfadly Azizi Bohari

469

Zulkifli Nordin

217

556

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Geotechnique
Developments of geosynthetic-reinforced soil technology in Japan: retaining walls and bridge
abutments
Fumio Tatsuoka

3

Seepage-deformation coupled numerical analysis of unsaturated river embankment using anelasto-plastic model
F. Oka, S.Kimoto and R.Kato

15

Progressive failure of shallow anchor in dense sand evaluated by 2D and 3D finite element
analysis and model tests
T. Sakai and M. Rokonuzzaman

23

Design of single pile foundations using the mechanics of unsaturated soils
Vanapalli S. and Taylan Z.N.

31

Problematic soil: in search for solution
Bujang B.K. Huat

39

Characterization and modeling of various aspects of pre-failure deformation of clayey
geomaterials – fundamental theories and analyses
J.N. Mukabi

47

The maintenance of ground anchors in Nippon Expressway
Yuu Fujiwara and Toshinori Sakai

57

Stress distribution in khon kaen loess under spread footing
Pairoj Yodsa-nga and Watcharin Gasaluck

61

The effect of sheet pile length on the capacity of improved pile foundation on sand undervertical and moment loading
Tuan Van Nguyen and Pongsakorn Punrattanasin

65

Investigation of a reliable reinforcing method for embankment ground
H. M. Shahin, T. Nakai, M. Kikumoto, R. Sakai, Y. Yoshida, I. Saito, N. Nagao and K. Toda

71

Evaluation of stamps and latex shell influence on stabilometer testing results, modeled withsimulia abaqus
Dmitriy Volik

77

Characterizing the interaction of geomat with fine grained black cotton soils
Wekesa S., Mukabi J. , Okado J., Kogi S., Ndeda M. and Ogallo J.

81

Soil liquefaction susceptibility zoning due to earthquake using GIS and geotechnical data
Bhuyan Md. Habibullah, Rama Mohan Pokhrel, Jiro Kuwano and Shinya Tachibana

87

Evaluation on the results of multistage shear test
Hormdee D. and Kaikeerati N.

93

Verification of effects of countermeasures for seepage of river levees by on-site monitoring of
the water level of levees
Hiroyuki Masuyama, Yukiko Saito, Masanori Ishihara, Tetsuya Sasaki and Hirotoshi Mori

97

Influence of decreasing of soil suction on unconfined compressive strength for bentonite
Tomoyoshi Nishimura

103

557

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)The relationship between soil suction and the maximum unsaturated undrained shear
strengths of compacted khon kaen soil
R. Nuntasarn and W. Wannakul

107

Interpretation of coaxial and non-coaxial strain on directional variation of undrained strength ofclay
J.Rajaraman and K. Thiruvenkatasamy

113

FEM analysis of innovative shallow foundation system for reactive soils
Mostafa A. Ismail and Mohamed A. Shahin

117

Delay times of elastic waves at discontinuities in laminated specimens
Yota Togashi, Kazuo Tani, Tetsuji Okada and Hiroaki Sato

123

Geotechnical investigation of valleys using lightweight dynamic cone penetration test forlandslide risk assessment
Takashi Hanaoka, Takashi Tsuchida, Shoichi Kawabata and Shota Nakagawa

129

Study on individual landslide risk assessment of natural valleys and slopes during heavy rain
based on geotechnical investigation and analysis
Shouichi Kawabata, Takashi Tsuchida, Takashi Hanaoka and Shouta Nakagawa

135

Analyses of piping under foundation of weirs in different ground density by FEM
Okajima Kenji141

Shear deformation and failure of sandy slope according to pore pressure generation due torainfall infiltration
Katsuo Sasahara and Naoki Sakai

147

Load settlement relationships of circular footing considering dilatancy characteristics of sand
Yusuke Tomita, Tatsuaki Nishigata, Takeshi Masui and Shintaro Yao

153

Thermally modifying bentonite for construction industry
Abdoullah Namdar

159

Mesh-free analysis of beam on elastic foundation
S. M. Binesh

163

Frictional Performance Of Infilled I-Blocks With Geosynthetic Inclusions
Faisal Hj Ali, Md. Zahidul Islam Bhuiyan, Firas A. Salman and Siau Lian San

167

Varying ground water level to minimise liquefaction hazards in urban areas
Heitor A., Oka F., Kimoto S. and Higo Y.

173

Development of a new type reinforced soil wall
Hara T., Tsuji S., Yoshida M., Ito S. and Sawada K.

177

Development of design charts for reinforced embankment using excel spreadsheet slope
stability analysis
Ito Kazuki, Md. Zakaria Hossain and Toshinori Sakai

183

Numerical simulation of 2D crack growth with frictional contact in brittle materials
Kai Zhang, Jing-cai Jiang and Qing Yang

187

Interface behaviour of basalt geosynthetic with sand in direct shear mode
M.B. Hossain, M.Z. Hossain and T. Sakai

191

Effect of soil parameter uncertainty on seismic response of buried segmented pipeline
Chaminda Gallage, Pathmanathan Rajeev and Jayantha Kodikara

197

558

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)The sorption capacity of cu by sc-soil from batch and column tests
Arwut Yimtae, Pongsakorn Punrattanasin and Noppadol Sangiumsak

203

Construction materials
Green construction: the role of palm oil fuel ash in concrete
A.S.M. Abdul Awal

211

Behavior of collapsible loessic soil after interparticle cementation
Arrua Pedro, Aiassa Gonzalo, Eberhardt Marcelo and Claverie Eliana

221

A study on hardened soil brick using liquid type and powder type hardening agent
Jin Sung Ki., Jung Seung Yong. and Kim Tae Ho.

227

The effect of salt content in soil on the sorption capacity of heavy metals
Lerd Kerdchaiyaphum and Pongsakorn Punrattanasin

233

Manufacture of Housing Construction Materials with Jute Polymer Composite (Jutin)
Mubarak A. Khan, Fahmida Parvin, Jahid M M Islam and Md. Zakaria Hossain

239

Evaluation of strength of granulated construction waste sludge with quick lime and its
application to soil structure
Makoto Kobayashi, Hiroaki Nakamura and Hideaki Mizuno

245

Analysis of enhanced strength and deformation resistance of some tropical geomaterials
through application of in-situ based stabilization techniques
Kogi S., Ndeda M., Mukabi J.N. and Wekesa S.

251

Further developments in the swelling model of expansive clays under ASTM 4546 and CBR
testing
Moshe Livneh

257

The effect of clay, lime and rice husk ash contents on the sorption capacity of Cu, Ni and Zn by
Soils
Pongsakorn Punrattanasin and Noppadol Sanggiumsak

263

The effect of temperature on the sorption capacity of copper by soils
Noppadol Sangiumsak and Pongsakorn Punrattanasin

269

Experimental Investigation for Nitrate Reduction Using Iron Powder in Porous MediaHaruka Shimada, Kazuya Inoue, Ikko Ihara, Katsutoshi Suzuki and Tsutomu Tanaka

275

Using spatial moments in conjunction with image processing to estimate macrodispersion in
stratified porous formations
Katsutoshi Suzuki, Kazuya Inoue, Tsutomu Tanaka and Akira Kobayashi

281

The novel technology of desertification control and ecological restoration with an Hydrolysis
Polyurethane(W-OH)
Weimin Gao, Zhiren Wu, Zhishen Wu, Kentaro Iwashita, Hirondo Inagaki and Caiqian Yang

287

Migration of radioactive materials through porous media: theory and a solution for an unsteadystate problem
Khaled I. Hamza

293

Fundamental study on ecosystem support canal using porous concrete
Masuma Yoshihiro, Hasegawa Yuki, Md.Rokunuzzaman, Yamada Toshio,Kassai Hirofumi and
Sato Shushi

299

559

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Alternative employment of crushed shell particles in capillary barrier of soil
Satoru Nakafusa, Kaoru Kobayashi, Toshihiro Morii,Tomoyoshi Nishimura

305

A novel statistical approach for investigating the significant factors that influence theperformance score of the Turkish method
Kshama Sundar Roy, Kamrul Islam and Md. Shams Arafat

311

Ultimate strength and fatigue life of concrete structural elements reinforced with carbon fiber
sheet
Hidenori Tanaka and Yutaka Toi

317

Development of functional carbon nanotubes -asphalt composites
Tatsuo Shirakawa, Akio Tada and Noriyasu Okazaki

323

Hydraulic character of estimation method on roughness coefficient of concrete canal
Koichiro Otagaki, Koji Sai,Kenichi Fujisawa, Shinsuke Matsumoto and Shushi Sato329

Na-bentonite as rock containment barrier against heavy metals and acid leachates
Angelica Naka, Takeshi Katsumi, Toru Inui, Giancarlo Flores and Takehiro Ohta

333

The comparison of monotonic behaviors of two different calcareous sands
R. Rezvani, H. Shahnazari, H. Salehzadeh and Y. Dehnavi

337

Soaking effect on strength and performance of fine grained soil stabilized with recycled
gypsumAly Ahmed, Keizo Ugai and Taira Jinno

343

Removal of Zinc in soils using natural zeolite
Wiparat Nisapai , Arthit Neramittagapong and Sutasinee Neramittagapong

349

Heat control of pavement surface temperature using oyster shell lime
Satoru Ishiguro and Masayoshi Yamanaka

353

Buckling behavior of composite triangular plates
T.Farsadi, P.Amani and E.Heydarnia

357

Durability of cement treated highway materials
Jiraroth Sukolrat, Apisit Klummeng and Sekchai Anuvechsirikiat

365

Porous geopolymer concrete
Tawatchai Tho-in, Vanchai Sata and Prinya Chindaprasirt

371

Design and Fabrication of Composite Technology for Earth Slope Protection
Md. Toriqul Islam, Md. Zakaria Hossain and Masaaki Ishida375

Study of slump testing for hydraulic plastic grout
Hiroyasu Ishii, Kenichi Horikoshi and Masaki Kitazume381

Behavioral comparison of coarse aggregate from various quarry sites of pakistan, effect on
hardened concrete, economics and environment
Faisal Malik and S. Muhammad Jamil

387

Methods for execution of concrete piles in corrosive and destructive marine environments,
based on study of the Persian Gulf marine installations
Nasser Arafati, Abdol Hossein Fazli and Seyed Mehdi Mousavi

393

Fundamental study on particle size distribution of coarse materials by image analysis
G.H.A.J.J. Kumara, K. Hayano and K. Ogiwara

399

560

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Environment
Calibration and simulation of runoff models for developing watershed respond knowledge at
tropical area
Arien Heryansyah and Zulkifli Yusop

407

Effect of geological succession on macrophyte and microbiota in aquifer ecosystem in urban
coastal zone
Kazuhito Murakami and Akiko Inoue-Koham

411

Bioclean and liquid biofertilizers a new way to the green area
Sittisak Uparivong

417

Massive point cloud acquisition on a soil surface using a stereo camera
Masafumi Nakagawa, Anna Nakanishi, Hirotaka Endo and Kenta Ochiai

421

Estimation of earthquake ground motion in Padang, Indonesia
Rusnardi Rahmat Putra, J. Kiyono and Y. Ono

425

Groundwater contamination due to irrigation of treated sewage effluent in the werribee delta
Hiroyuki Ii, Masanobu Taniguchi, Ataru Satoh, Graeme Allinson, Matt Kitching, George
Croatto and Bruce Shelley

431

Process of invading the alien plant species into the river ecosystem
Michiko Masuda, Yumie Ito and Fumitake Nishimura

437

Recent meandering pattern of the Irrawaddy, Myanmar
Mayumi Matsumoto and Shigeko Haruyama

443

Physical and chemical properties of tsunami deposit in northeast area in Fukushima prefecture
after Tohoku-Kanto earthquake
Tomonori Fujikawa, Hiromu Okazawa, Takahiko Nakamura, Yasushi Takeuchi and Masaharu
Komamura

447

Changes of bottom sediment caused by Construction of the Airport Island in the Ise Bay, Japan.
Maki Oyagi, Motohiro Kawase and Akihiko Yagi

453

Proposal of simple measurement method for evaporation rate by using oxygen isotopic ratio in
the inawashiro lake
Satoshi Miyahara and Hiroyuki Ii

457

Landslide susceptibility mapping using logistic regression model with neighborhood analysis:
a case study in mizunami city
Wang Liangjie, Sawada Kazuhide and Moriguchi Shuji463

The evaluation of the river environment and water quality by image analysis in the YamatoRiver Basin in Japan
Masanobu Taniguchi, Hiroyuki Ii and Tatemasa Hirata

469

Distribution of oxygen and hydrogen stable isotopic ratios and estimation of the spring waterorigin in the Kushiro Moor
Natsuki Kawabe and Hiroyuki Ii

473

A debris flow and its risk analysis related to the 2008 Wenchuan earthquake
Yange Li, Guangqi Chen, Chuan Tang and Lu Zheng

479

Impact analysis of water price reform of Zhangye, China
Atsushi Koike, Zhongmin Xu, Kang Wang and Bunei Itoga

485

561

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Post earthquake rapid inspection planning for bridges in western Kentucky
Norimitsu Koike and Issam E. Harik

491

Organophosphoric acid triesters from landfill sites and sewage plants in Japan
Haruki Shimazu

497

Ground water pollution around the Oyachi-Heizu district of Yokkaichi city
Yukimasa Takemoto, Masaaki Takahashi, Kayoko Awaya, Mikihiro Ioka and Peng Guo

501

Characteristics of damage to structures induced by the tsunami of the 2011 east Japan megaearthquakeÖmer Aydan, Hisataka Tano and Takahiro Iwatate

505

Characteristics of strong motions induced by the 2011 east Japan mega earthquake with anemphasis on Tokyo bay area
Takahiro Iwatate, and Ömer Aydan

511

Inquiry of the value of parks in the characteristics and use of park planning through urban
revival planning projects in Maebashi city
Shinya Tsukada, Tetsuo Morita and Akira Yuzawa

517

A study on evaluation of quality of life in consideration of water/green environment
Tetsuo Morita, Yoshihito Kogure, Hiroshi Sugita, Tsuyoshi Baba, Shinya Tsukada and Naoki
Miyazato

521

Changes and issues in green space planning in the tokyo metropolitan area: focusing on the"capital region plan"
Tetsuo Morita, Yoshihide Nakagawa, Akinori Morimoto, Masateru Maruyama and Yoshimi
Hosokawa

527

Application of traffic simulation in road policy assessment accompanied by railway elevation
Maekawa Takuya and Hiroshi Inouye

533

Impact estimation of land cover changes of recharge area on spring discharge in marshy
environment
Masaaki Kondo and Takamitsu Kajisa

541

Numerical Study on Characteristics of Levee Breach Flood Disasters in Alluvial Floodplain
Md. Serazul Islam and Tetsuro Tsujimoto

547

Purification system of ocean sludge by activating microorganisms
Kyoichi Okamoto, Kenji Hotta, Takeshi Toyama and Hideki Kohno

553

Author index

559

Volume 2
Characterization and modeling of various aspects of pre-failure deformation of clayey
geomaterials – applications in modeling
J.N. Mukabi and M.Z. Hossain
An emergency medical care information system for fetal monitoring
Muhammad Ibn Ibrahimy
Effects of gypsum on the swelling and dispersion behaviour of fine grained soils from Sudan
Abdul Karim, M. Zein and Ahmed M. Elsharief

562

563

573

577

Contents of GEOMATE2011-Volume 1(1) and Volume 1(2)Comparison of bearing capacity equations for vertical central loading
Muhammad Awais Shafique and Tanvir Iqbal Qayyum

583

Pull-out resistance of selected native plants in Hong Kong
Leung F.T.Y., Yan W.M., Tham L.G. and Hau B.C.H.

589

Inland navigation in carrying injured and sick disaster victims in case of a massive earthquake
in the Tokyo metropolitan area
Kazuya Egami, Keiichi Noto, Wataru Miyazaki, Kazukiyo Yamamoto and Takeo Kondo

593

Model calculation and geotechnical interpretation of the correlation co-efficient between finite
and incremental strain path of a formation
J.Rajaraman and K. Thiruvenkatasamy

597

Geocell reinforced bed subjected to simulated traffic loads
P. Sharifi, and S.N. Moghaddas Tafreshi

601

Effects of gradation of various sand deposits of Pakistan on strength of hardened concrete
Gauhar Sabih and S. Muhammad Jamil

607
613

Strengthening of landslide retaining pile wall after geodetic monitoring
Frangov G., Zayakova H., and Hamova M.

Response of tapered piles under lateral harmonic vibrations
Ahmad Dehghanpoor and Mahmoud Ghazavi
Investigation of ground movement in soil-nailed walls using 1g models and PIV method
H. Mahdavi, and M. Hajialilue-Bonab

627

623

629
Author Index

563

Contents of GEOMATE2012 - Volume 2(1)ID Keynote Papers
1

Use of microbial technology in geotechnical engineering
Jian Chu, Volodymyr Ivanov, Jia He and Viktor Stabnikov

1-4

2

A study on slow moving slopes
L G Tham and Xu Kai

5-11

3

Bearing capacity and settlement behaviour of shallow foundations in unsaturated
sands
Sai K. Vanapalli and Fathi M. O. Mohamed

12-21

4

Development of Piled Geo-wall
Hara, T., Tsuji, S., Yoshida, M. and Sawada, K.

22-29

5

Measurement of strain distribution along precast driven pile during full scale pileload test
Faisal Ali and Lee Sieng Kai

30-39

6

Unique grouting material composed of calcium phosphate compounds
S. Kawasaki and M. Akiyama

40-46

7

Stiffness Anisotropy and Resilient Modulus of an Unsaturated Soil under Static andCyclic loads
Charles W.W. Ng, C. Zhou and J. Xu

47-62

8

Nanoparticles for Geotechnical Engineering
Mohd Raihan Taha

63-68

Technical Papers
Geotechnique69

24

Damage Assessment and Strengthening of R/C Building Constructed on Expansive
Soils
Osama M. A. Daoud

70-75

29

Gravitational Sphere Packing Method To Find The Porosity Of The Soil Particles
With The Identical Size in cylindrical container
Mohammad Mahdi Roozbahani , Bujang B. K. Huat, Afshin Asadi

76-78

34

Parametric Study of Piled Raft Foundations to improve the Design Method
Tohidi A., MH .Sadagiani

79-84

39

Experimental Study of Suction-Monitored CBR test on Sand-Kaolin Clay Mixture
Purwana, Y.M., Nikraz H., and Jitsangiam P.

85-90

41

Foundation Strengthening of Historic Buildings by Micropiles
Azza M. Elleboudy

91-96

564

Contents of GEOMATE2012 - Volume 2(1)44Group effects of piles due to lateral soil movement
Hongyu Qin1 and Wei Dong Guo

97-10245

Collapse-Settlement Calculations for Embankments Based on a Collapsible Soil
Subgrade
Moshe Livneh

103-108

46

The influence of trench soil properties on the accuracy of pressure cellmeasurements in an earthfill dam
D. Elmi, A. A. Mirghasemi

109-11250

Studying the effects of considering dilation angle over the performance ofgeotechnical elements using numerical methods
Salman Hanifi, Amin Naeimabadi , Mohammad Reza Atrchian113-11750aComparing the excavating effect of single and twin tunnels on the earth surface
settlement by numerical methods
Amin Naeimabadi, Salman Hanifi , Mohammad Reza Atrchian

118-124

107

Excess Pore Pressure Characteristics of Sand Mat using Dredged Soil
M.S LEE, K. ODA

125-130

110

Effect of clays fraction to california bearing ratio laboratory test value with andwithout soaked
Soewignjo Agus NUGROHO, Syawal Satibi and Ferry Fatnanta131-136

111

Compressibility Characteristics of Residual Soil Subjected to Microbial Treatment
Lee Min Lee, Ng Wei Soon, and Yasuo Tanaka

137-140

115

Strength and aging of cement treated low plastic soils
Fabien Szymkiewicz, Antoine Guimond-Barrett, Alain Le Kouby

141-145

119

Performance Of Cantilever Sheet Pile Supporting Excavation Adjacent To Strip
Footing
Yousry M. Mowafe, Ahmed M. Eltohamy and Ahmed A. Mohamed

146-153

119a

Enhancing Stability of Slopes with Cement Kilin Dust Sand Mixture Layer
Al Serif M. Abd Alazez1, Ahmed M. Eltohamy and Ahmed Rusdy Towfek

154-161122

The effect of confining stress on the analysis of excavations with adjacent existingbuildings
Sabzi Zahra, Fakher Ali

162-166

125

Bored Pile Socket in Erratic Phyllite of Tuang Formation
D.E.L. Ong

167-171

133

Swelling deformation of the bentonite mixed with silica fume or sodium carbonate
in calcium hydroxide solution
Yuki YOKOYAMA and Kenichiro Nakarai

172-175

136

A Combined Probabilistic Method for Engineering Failure analyses andApplications in Typical Geotechnical Structures
Duruo Huang

176-181137

Parametric Study of Crossing Tunnels at Different Level
A. Tohidi, MH.Sadagiani

182-189

143

Use of post-floatation copper tailings in the construction of dump dams
Tschuschke W., Wierzbicki J.

190-195

565

Contents of GEOMATE2012 - Volume 2(1)150

Effects of Slope Inclination on the Rain-induced Instability of Embankment Slopes
Chaminda Gallage, Shiran Jayakody and Taro Uchimura

196-201

225

Extension of an integrated AHP and TOPSIS approach in the earth dam site
selection
Minatour Yasser, Khazaie Jahangir

202-208

227

Using Geogrid Boxes as a New Approach for Reinforcement of Rock Slopes
Ahmad Fahimifar, Arvin Abdolmaleki

209-214228

Volume Change Characteristics of Clay Mixes with Different Bentonite Percentages
J. M. Kate, Sunil Kumar, M. P. Bhorkar

215-218236

FE Analysis for Settlement of Peat Ground under Embankment Loading
Satoshi Nishimoto and Hirochika Hayashi

219-224

237

Seismic behavior of pile group in soil slopes: 1g shake table tests
H. Elahi, M. Moradi,A. Ghalandarzadeh and A. Elahi

225-229

239

Electrophoresis of Bacteria and Electro-Biogrouting
Hamed A. Keykha, Bujang B. K. Huat, Afshin Asadi, Satoru Kawasaki

230-232240

Consideration concerning reasonable modified form of Floating-type Improved
GroundHijiri Hashimoto, Satoshi Nishimoto and Hirochika Hayashi

233-236

241

Numerical Study Effect of Nail Angle Change on Stability and Displacement of
Excavation Wall in Cohesive and Cemented Non-Cohesive Soils
Navid Shahnazi, Jahangir Khazaie, Mohamad Sharifipour and Kiarash Ashtari237-241242

An investigation on behavior of geogrid reinforced soil retaining walls applying
finite difference method (F.D.M)
Jahangir Khazaie and Alireza Sadeghabadi242-252

243

Effects of humic acid and salt additives on the behaviour of lime-stabilised organic
clay.
N.Z. Mohd Yunus, D. Wanatowski, and L.R. Stace

253-256

244

Sodium Tripolyphosphate For Stabilizing Of Contaminated Soil
Amin Falamaki ,Hossein Tavallali and Shahrbanoo Rezanejad Farahmand257-260

246

Evaluation of Soil Water Characteristic Curves for Sand-Expansive Clay Mixture
T. Y. Elkady, M. A. Dafalla, A. M. Al-Mahbashi1 and Mosleh Al Shamrani261-265

247

Coastal soils improvement
Mohammad reza Atrchian, Morteza Ala,266-269

248

A Hybrid Intelligent System of Fuzzy C-Mean Clustering and Neural Networks to
Predict the Compaction Characteristics of Fine Grained Soils
Iman Ashayeri, Mahnoosh Biglari270-273249

Equivalent linear seismic ground response analysis of unsaturated soil deposits
Mahnoosh Biglari, Iman Ashayeri274-278251

The Correction of Shallow Foundation Settlement Equations by Finite Element
MethodMohammad Arab Ameri, Hakime Rabbanifar and Mehdi Arab Ameri

279-284

Amin Naeimabadi

566

Contents of GEOMATE2012 - Volume 2(1)255

Numerical study of earthquake hazards of liquefaction occurring on the site andsustainable transport pipes
Hamed Bavanpouri, Jahangir Khazaie, Dr.Hasan Sharafi

285-288

266

Analysis of geogrid reinforced soil retaining walls with limit equilibrium and finite
difference method
Alireza Sadeghabadi ,Jahangir Khazaie and Mostafa Yousefi Rad

289-293

270

Recent Development in Electrokinetic Stabilization of Soft Soil, A review
Hossein Moayedi, Sina Kazemian, and Bujang B. K. Huat

294-298

275

Application of ion-exchange solution soil stabilizer in increasing CBR values ofclayey soils
Reza Ziaie Moayed, Seyed Ali Hashemi and Farzad Allahyari

299-302

276

Assessment of Low Strain Wave Attenuation for Piles Cast in Very Dense Granular
Soil
Ramli Nazir and Osman El Hussien

303-307279

Dynamic Soil-Structure Interaction Considering Pore-Water Pressure Coupling
Qutayba Nazar Al-Saffar, P Akram Y. Al-Sa’aty, Mohamad T. Al-Layla

308-325

281

Analysis and design of tunnel lining in alluvial soil deposits
Nuri al-Mohamadi

326-330285

Effect of silt content on the anisotropic behaviour of silt-sand mixtures
Navid Khayat , Abbas Ghalandarzadeh

331-337

288

Optimizing the twin tunnels position for reduction the surface ground movements
Mehdi Mokhberi, Seyed Ali Farjam

338-344290

Evaluation of pile lateral capacity in clay applying evolutionary approach
Alkroosh I., Nikraz H

345-348

293

Effect of Reservoir Drawdown Rate on Phreatic Line Recession in Homogeneous
Earth Dams
R. Ziaie Moayed, V. Rashidian349-352294

The effect of lime-microsilica stabilization on California Bearing Ratio of silty soils
R. Ziaie Moayed, Y. Daghigh2, B. Pourhadi and N. Sahebzamani

353-356295

Effect of elastic modulus varieties in depth on modulus of subgrade reaction on
granular soils
Reza Ziaie Moayed, Mahdi Ali Bolandi357-360

296

Flexural Buckling Behavior of Steel Pile with Vertical Load in Liquefied Soil
Yoshihiro Kimura and Koichi Onohara

361-365

305

Two-dimensional finite difference pseudo-static deep-seated slope stability analysis
of embankments over stone column-improved soft clay
Farshad Fayyaz Jahani, Mohammad Sharifipour

366-371

308

Parametric study of Geo-grid soil reinforced retaining walls under dynamic loading
by ABAQUS software
Atrchian mohammad reza, Daghigh younes, Ghanbari namin hamed372-3802010

Sensitivity analysis in soil nail wall for Tehran-Tabriz railway by considering thecoefficient of variation for effective parameters in stability analysis
Mohammad Moghadaripour , Ardalan Akbari Hamed, Ali Ghozat

381-384

567

Contents of GEOMATE2012 - Volume 2(1)2012

Evaluation of Strength Parameters of Improved Collapsible Soils with Current
Additives (Case study: Atrak zone, Iran)
Mohammad Arab Ameri, Samaneh Kargar and Mehdi Arab Ameri

385-390

2100

Influences of soil material parameters in compaction simulation with soil/water/air
coupled F.E. code
S. Sakamoto, K. Kawai, V. Phommachanh and A. Iizuka

391-3962105

Lower bound limit analysis of strip footings resting on cohesive soils
S.M. Binesh, A. Gholampour

397-4022106

Upper bound limit analysis of strip footings resting on cohesive soils
S.M. Binesh, S. Raei

403-4082108

Evaluating and optimizing different methods of treating and cleaning contaminatedsoil
Mohammad Reza Atrechian,Seyed Salman Musavi Khosro Ebrahimkhani

409-412

2112

Experimental study concerning impact characteristics by collision of weight onsand cushion over steel beam
Tam Sy Ho, Hiroshi Masuya and Naoto Takashita

413-4192114

Landslides in Tea Plantation Fields in Shizuoka, JapanJun Sugawara

420-425

2115

Natural base isolation system for earthquake protection
Srijit Bandyopadhyay, Aniruddha Sengupta and G.R. Reddy

426-4312116

Comparison of Effect of Percent of Compaction, Sand and Cement on The Amountand Time of Swelling of Bentonite
Mohammad S. Pakbaz and B. Rafiee

432-435

2118

Prediction of the Axial Bearing Capacity of Piles by SPT-based and Numerical
Design Methods
Issa Shooshpasha, Ali Hasanzadeh and Abbasali Taghavi436-4392120

Application of recently developed mechanistic-empirical methods for the design ofheavily loaded pavement structures
John N. Mukabi

440-447

2121

Design of support system for excavation in black cotton soils in Guntur, India
D. Neelima Satyam, Akhila Manne

448-451

2127

Numerical modeling of pullout capacity of a pile in sand under oblique load
Md. Iftekharuzzaman and Dr. Bipul Hawlader452-4572130

Slope Failure in Residual Soils of Peru
A.Carrillo-Gil

458-461

2131

Back-analysis of Frictional Jacking Forces Based on Shear Box Testing of
Excavated Spoils
Choo Chung Siung and Dominic Ong E. L.

462-467

2132

Lime Stabilization of Tropical Soft Soils
Dygku Salma Awg Ismail, Tan Jui Siang and Siti Noor Linda Taib468-471

2138

Increase Of Piles Bundle Capacity By Making A Base Joining Them
Jan Jaremski

472-478568

Contents of GEOMATE2012 - Volume 2(1)2139

The Effects of soil-Pile Interaction on Seismic Parameters of Superstructure
Mahdy Khari1, Khairul Anuar Bin Kassim, Azlan Bin Adnan

479-4842140

Investigation on Finite Element Modeling of Group of Stone Columns
M. Mirshekari , C. Behnia and S. Fakhretaha

485-4882147

Suction Controlled Triaxial Apparatus for Saturated-Unsaturated Soil Test
Luky Handoko, Noriyuki Yasufuku, Kiyoshi Oomine, Hemanta Hazarika

489-4932154

Monitoring Program and Dilapidation Survey for Grouting of Karst Cavities
Hasan A. Kamal and Hassan J. Karam

494-4972156

Numerical Analysis of Soil Nail Walls under Seismic Condition in 3D Form
Excavations
Siavash Zamiran, Hamidreza Saba

498-501

2159

Shear strength improvement of fibrous peat due to consolidation pressure
Vivi Anggraini, Nurly Gofar and Bujang bin Kim Huat

502-506

2164

Factors affecting the stability analysis of earth dam slopes subjected to reservoir
drawdown
T. Souliyavong, C. Gallage, P. Egodawatta and B. Maher

507-5122165

Lateral stress induced due root-water-uptake in unsaturated soils
Mu’azu Mohammed Abdullahi and Nazri Bin Ali

513-5172166

The effect of pre-tensioned rock bolts on seismic behavior of urban tunnels
Farshad Fayyaz Jahani, Mohammad Sharifipour

518-5232170

Effect of silt content on the anisotropic behaviour of silt-sand mixtures
Navid Khayat , Abbas Ghalandarzadeh

524-530

Construction Materials
24b

Production and Properties of High Strength Concrete for Concrete Dam
Heightening Project in Sudan
Osama M. A. Daoud and, H. S. Sagady

531-537

27

Effect of openings locations of quadratic folded plate roofing systems on their staticand dynamic behavior
Ahmed Hassan

538-54448

Improving concrete compression strength using natural additive
Abdoullah Namdar, Ideris Bin Zakaria and Nurmunira Binti Muhammad Atan

545-548

53

DEM simulations and laboratory experiments on physical and mechanicalproperties of sand-gravel mixtures
Janaka J. Kumara, Kimitoshi Hayano, Yuuki Shigekuni and Kota Sasaki

549-554

120

Rock slope stability problems in Gold Coast area in Australia
Shokouhi Ali, Gratchev Ivan, Charrismanagara Arry

555-558

121

Techno-commercial development of pre-fabricated structures using geopolymer
concrete
J. Santhosh, R.Sanjeev, P.Sethu Raja, A. Rajendra Prasad, A. Abdul Rahman

559-563

569

Contents of GEOMATE2012 - Volume 2(1)124

Mechanical Properties of Recycled Steel Fibre Reinforced Concrete
A.S.M. Abdul Awal, Lim Lion Yee, M. Dianah1 and M. Zakaria Hossain

564-569

134

Effects of Gradation of Various Sand Deposits of Pakistan on Strength of Hardened
Concrete
Gauhar Sabih , S. Muhammad Jamil and Kamran Akhtar

570-574

203

Assessment of recycled concrete aggregates for road base and sub-base
S. Jayakody, C. Gallage, A.Kumar

575-579232

Estimation of consolidation properties of Holocene clays with artificial neuralnetwork
Kazuhiro ODA , Minsun Lee and Shotaro Kitamura

580-585250

Measurement of The Crack Displacement Using Digital Photogrammetry for
Evaluation of The Soundness of Tunnels
A. Kanazawa, S.Nishiyama, T.Yano, T.Kikuchi

586-592

259

Numerical modelling of a small scale shallow foundation reinforced by
Soil-Mixing
Anna Grzyb, Mahmoud Dhaybi and Frederic Pellet

593-598

262

Physical modelling of a small scale shallow foundation reinforced by Soil-Mixing
Mahmoud Dhaybi and Frederic Pellet

599-604282

Prediction compressive strength of concretes containing silica fume andstyrene-butadiene rubber (SBR) with a mathematical model
A.Haghollahi, M.Shafieyzadeh

605-610283

287

Sliding stability of dry masonry block retaining structure with a resistance plate
Akihiro Hashimoto, Noriyuki Yasufuku, Yoshio Suematsu, Kazuo Fujita1 andToshimitsu Komatsu
Evaluation and Prediction Method on Neutralization of Supplied Long-term
Hydraulic Concrete Structure
Man-Kwon Choi , Yuki Hasegawa, Shinsuke Matsumoto, Shushi Sato and Tsuguhiro
Nonaka611-616617-621297

Measurement of tensile properties of geogrids
Raid R. Al-Omariand Mohammed K. Fekheraldin

622-631306

Modeling the Swelling strain and pressure of Weak Rock using Adaptive
Network-Based Fuzzy Inference System
Ramin Doostmohammadi

632-636309

Centrifuge Modeling Of Reinforced Embankments On Soft Foundation
Ali Sobhanmanesh, Nurly Gofar

637-6422102

Centrifuge model tests and finite element analyses on the seismic behavior of thequay walls backfilled with cement treated granulate soils
Hayano, K., Morikawa, Y., Fukawa, H., Takehana, K. and Tanaka, S.

643-6502109

Response of Piered Retaining Walls to Lateral Soil Movement Based on Numerical
Modeling using Matlab
Siamak Pahlevanzadeh

651-6542122

Evaluation of Thermal Response Tests in Energy Piles
Seung-Rae Lee, Seok Yoon, Hyun-Ku Park , Gi-Dae Oh

655-659

2134

Experimental Study on Mechanical Characteristics of Soil-Geosynthetic Interface
Md. Bellal Hossain, Md. Zakaria Hossain and Toshinori Sakai

660-665

570

Contents of GEOMATE2012 - Volume 2(1)2136

An Interpretation of Mechanical Properties of Bentonite as a Non-linear Elastic
Material
Y. Takayama, S. Tsurumi, A. Iizuka, K. Kawai

666-6712149

Effect of carbonation on strength of cement treated sandKenichiro Nakarai and Tomomi Yoshida672-675

2167

Application of PML to Analysis of Nonlinear Soil-Structure-Fluid Problem using
mixed element
Pahaiti Reheman, Hiroo Shiojiri

676-681

Environment
28

Recycled Bassanite as a Stabilizing Agent for Cohesion-less Soil
Aly Ahmed and Keizo Ugai

682-687

31

The effects of environmental on today construction industry
Mahdy Khari1, Khairul Anuar Bin Kassim, Azlan Bin Adnan

688-692

33

A Case History of Quay Wall Failure and Remedial Design
C. S. Chen

693-696

37

Environmental economical efficiency in treatment/reutilization of construction
sludges considering delay in process flow
Shinya Inazumi, Hiroyasu Ohtsu and Takayuki Isoda

697-70242

Evaluation and validation of elastic-fragile damage modeling for unsaturated
porous media in θ-stock
B. Gatmiri , M. Fathalikhani

703-708

43

47

Estimation of the Landslide Dam Sustainability in the Gigantic Seimareh Landslide
Using the Rate of Sedimentation
Zieaoddin Shoaei
Influence of soil and rock mineralogy and geomorphology on Landslides
Occurrence and soil erosion in the Merek Catchment, IranMosayeb Heshmati , Nik Muhamad Majid, J. Shamshuddin, Arifin Abdu andMuhamad Ghaituri709-7012

713-719112

The effect of historical land use on landslide initiation
Gholamreza Shoaei

720-723

114

Integrated Environmental Management for Sustained Development
J.Rajaraman and K.Thiruvenkatasamy

724-729

114a

Lowland Environmental Geotechnology of Seismosediments of Kandla Port In
India
J.Rajaraman and K.Thiruvenkatasamy

730-735

123

Single step extraction to find out soluble lead in soil
Masahiko Katoh, Satoshi Masaki, Takeshi Sato736-741

127

Biogas Production from Tannery Sludge
A.Rajendra Prasad, A.Dhanalakshmi, S.Usha and A.Abdul Rahman

742-746

131

Water Harvesting and Salinization Prevention by Capillary Barrier of Soil
Toshihiro Morii, Mitsuhiro Inoue, Kaoru Kobayashi, Tetsuya Suzuki and Takayuki
Kawai

747-752571

Contents of GEOMATE2012 - Volume 2(1)204Study of the Performance of anaerobic digestion of greasy skim as a renewableenergy source
Salam J. Bash Al-Maliky

753-756

209

Seismic evaluation of NARGES soil nailed wall under Cyclic loading and Pseudo
Static forces
Ardalan Akbari Hamed , Mohammad Moghadaripour , Ali Ghozat

757-761229

Purification System of Ocean Sludge by and Using Coagulants and then Activating
Microorganisms
Kyoichi Okamoto and Kenji Hotta

762-767

233

Mechanical properties of volcanic products mixed with industrial wastes
K. Yamamoto, T. Negami2, M. Hira, N. Aramaki and Y. Hayashi

768-771

235

Measurement of Hydraulic Conductivity for Peat Ground Using CPTU
Hirochika Hayashi and Satoshi Nishimoto

772-775

252

Extraction of temporal and spatial properties on habitat of snail by means ofstatistical approach
Masaaki Kondo and Takamitsu Kajisa

776-781

265

267

268

271

274

280

The use of Nano Zero Valent Iron to remediation of contaminated soil andgroundwater
Taghizadeh Maryam , Yousefi Kebria Daryoush and Gholamreza Darvishi
A Multi-parameter Water Quality Analysis by onsite filtered 2mL Sample to
Monitor Urban River Eutrophication
Akira Kikuchi, Nor Eman Ismail, Narges Janalizadeh, Musa Mutah and Muhamad
Faiz
The intelligent performance installations in energy efficiency in green buildings
Hooman Abadi, Rouzbeh Abadi, Poona Abadi
Study the Effect of Polyvinyl Chloride (PVC) Addition on the Permeability ofAnbar Soils
Ahmed H. Abdul Kareem & Omar Mustafa
Monitoring deforestation and rangeland destruction through land use alteration
during 1955- 2002, using GIS and RS in Merek sub-basin, west Iran
Mohammad Gheitury, Mosayeb Heshmati, Mohammad Ahmadi and Nik Muhamad
Majid
The comparison of phytoremediation and electrokinetic methods in remediation of
petroleum hydrocarbons contaminated soil
Gholami Meade, Yousefi Kebria Daryoush782-785786-790791-796797-802803-807808-811286

Using Metacognitive Strategies On Listening Comprehension
Mahshid Mirzaaghaee

812-822298

Evaluation of Run-Off Supply Projects in Hamedan Province(Iran)N. Rostam Afshar, M. Abdoli

823-827

299

Protective measures of the monumental pine in Rikuzentakada withsoil-water-air-solved material coupled model
Y. Sugiyama, S. Nomura, K. Kawai and A. Iizuka

828-833

304

Effects of Biosurfactants in Electrokinetic Remediation of contaminated soils
Bour Moslem and Yousefi kebria Daryoush834-838

2117

Change in structure of ground-beetle assemblage on river areas after construction of
biotopes using the technique, “Nature oriented river works”
Michko Masuda, Takaaki Tsukada and Fumitake Nishimura

839-844572

Contents of GEOMATE2012 - Volume 2(1)2123

Dense granular-fluid mixture: the effects of the natural grains characteristics andthe interstitial fluid viscosity
Anna Maria Pellegrino and Leonardo Schippa

845-850

2131

Back-analysis of Frictional Jacking Forces Based on Shear Box Testing of
Excavated Spoils
Choo Chung Siung and Dominic Ong E. L.

851-8562137

An idea of multi-functional reservoirs in mountain regions
Jan Jaremski

857-8622141

Estimation Method of Amount of Tsunami Disaster Wastes during the 2011 off the
Pacific Coast of Tohoku Earthquake
Minoru Yamanaka, Naoya Toyota, and Shuichi Hasegawa, Atsuko Nonomura

863-866

2143

Assessment of Runoff in the High Humid Foot-hill Areas of Arunachal Himalayas
Using Thornthwaite Equation
Md. Eahya Al Huda and Surendra Singh

867-871

2161

2163

2171

Natural Radiation level in Groundwater from Katsina, a Semi Arid Region of
Northern Nigeria
B.G. Muhammad and M.S. Jaafar
Cost-Performance Studies of Abandoned Shell Husks (ASH) for Soil
Reinforcement Applications
Md. Toriqul Islam, Md. Zakaria Hossain, Masaaki Ishida, Md. Bellal Hossain
and Md, Jamal Uddin
Cyclones Path and Severities: Effect on Flood Height and Damages of Land and
Embankments in BangladeshMusahaq Ali, Zakaria Hossain and Shigeko Haruyama
Author index

872-876877-880881-884885

573

ISBN978-4-9905-9580-1
C3051 \5000E
9784990595821
定価 （本体5０００＋税）
1923051050000

The “International Journal of
GEOMATE” is a Scientific
Journal the GEOMATEInternational Society thatencompasses a broad area inGeotechnique, Construction
Materials and Environment.
The key objective of thisjournal is to promoteinterdisciplinary research fromvarious regions of the globe.
The editorial board of thejournal is comprised ofextensively qualified
researchers, academicians,
scientists from Japan andother countries of the world.
It is peer-reviewed journal thatis published quarterly. All
articles published in thisjournal are available on line.
For more details, please visit:
http://www.gi-j.com/

Fourth International Conference on
Geotechnique, Construction Materials & Environment
University of Southern Queensland, Springfield Campus, Brisbane, Australia

VOLUME 3(2)Edited by
Md. Zakaria Hossain
Hossain Md. Shahin

GEOMATE 2013 NAGOYA, JAPANGEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENTiPROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE – GEOMATE 2013
GEOTECHNIQUE, CONSTRUCTION MATERIALS AND ENVIRONMENT NAGOYA, JAPAN
13-15 NOVEMBER, 2013

Geotechnique, Construction
Materials and Environment
Edited by

Md. Zakaria Hossain
Graduate School of Bioresources
Mie University

Hossain Md. Shahin
Graduate School of Engineering
Nagoya Institute of Technology

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2013 by The GEOMATE International Society
All rights reserved. In principle, no part of this publication or the information contained herein may be
reproduced in any form or by any means, translated in any language, stored in any data base or retrieval
system, or transmitted in any form or by any means without prior permission in writing from the publisher.
Disclaimer: The editors and the publisher have tried their best effort to ensure the integrity and the quality ofthis publication and information herein. However, they give no warranty of any kind, expressed or impliedwith regard to the material contained in this book, and will not be liable in any event for the consequences of
its use.
Published by:
The GEOMATE International Society
Tsu city, Mie, Japan
E-mail: geomate@gi-j.com
www.gi-j.com

ISBN Number: 978-4-9905958-2-1 C3051

iii

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Table of Contents

PrefaceOrganizationx
xi

ID Keynote Papers

1

1k

GROUND DEFORMATION DURING AND AFTER EARTHQUAKES–SIMULATION AND PREDICTION BASED ON ELASTO-PLASTIC SOIL MECHANICSAkira ASAOKA

22k

USE OF RECYCLED AGGREGATES FROM CONSTRUCTION AND DEMOLITION WASTES FOR THE
CONSTRUCTION OF FLEXIBLE PAVEMENTS
Márcio Muniz de Farias, Alejandra María Gómez Jiménez and Ferney Quiñones Sinisterra

12

3k

EFFECTIVE STRESS IN UNSATURATED GRANULAR MEDIA IN THE PENDULAR REGIME
Richard Wan, Sarah Khosravani and Mehdi Pouragha

24

4k

RECENT GEOTECHNICAL RESEARCH ADVANCES IN UNIVERSITY PUTRA MALAYSIA
Bujang B.K.Huat and Afshin Asadi

32

Technical Papers Volume 3(1)IDTechnical Papers Volume 3(2)40-573574

3120

DEVELOPMENT OF RAINFALL INFILTRATION INTO UNSATURATED SOIL COLUMN USINGELECTRICAL CAPACITANCE VOLUME-TOMOGRAPHY (ECVT)
Aniza Ibrahim, Muhammad Mukhlisin and Othman Jaafar

575

3126

SITE RESPONSE ANALYSIS TO DERIVE GROUND MOTION SIGNALS FOR ENGINEERINGAPPLICATIONS
Thayalan Nall, Greg Hackney and Harry Poulos

580

3131

A STUDY OF THE PARAMETERS AFFECTING THE PERFORMANCE OF ROADS UNDER AN EXTREME
RAINFALL EVENT
Helen Fairweather and John Yeaman

586

3167

EFFECT OF STIFFNESS OF LOAD-BEARING LAYER ON RESISTANCE CHARACTERISTICS AT PILE TOE
OF STEEL PIPE PILE ON THIN LAYER
Kazuhiro Oda and Shuhei Takegawa

592

3186

INFLUENCE OF SHEAR SPEED ON DIRECT SHEAR STRENGTH FOR COMPACTED BENTONITE WITH
DIFFERENT SOIL SUCTIONSTomoyoshi NISHMURA and Junichi KOSEKI

598

3194

EFFECTS OF HYDROLOGICAL PARAMETERS ON DESERTIFICATION IN CHINA BASED ON THE
SATELLITE DATA
Nozomu Hirose, Fengzhi DAI and Keiko Okada

604

iv

3213

STRENGTH PARAMETER SELECTION IN STABILITY ANALYSIS OF RESIDUAL SOIL NAILED WALLS
Atefeh Asoudeh and Erwin Oh

608

3231

TENSILE STRENGTH AND SUCTION OF SATURATED NSF CLAY AND THEIR RELATIONSHIPS WITH
UC STRENGTH
Surendra Bahadur Tamrakar and Toshiyuki Mitachi

613

3255

COUPLED ANALYSIS OF BIFURCATION AND SHEAR BAND IN SATURATED SOILS: EFFECT OF
CHARACTERISTIC LENGTH SCALE
Peijun Guo

619

3260

BEARING CAPACITY OF SOIL REINFORCED WITH SOIL-CEMENT COLUMNS FORMED BY THE DEEP
MIXING METHOD
Ahmad Safuan A Rashid and Jonathan A Black

625

3261

INTEGRATED QUALITY ASSURANCE AND CONTROL FOR DEEP SOIL MIXING IN WATERWAYPROJECT
S.H. Chew, C.Y. Tan, T.Y. Yap, K.E. Chua, H.M. Yim, S.Y. Kee, T.K. Khoo and Ja Naw

631

3263

EMPIRICAL CORRELATION OF SHEAR WAVE VELOCITY AND N-SPT VALUE FOR JAKARTA
Achmad Fauzi, Masyhur Irsyam, Usama Juniansyah Fauzi, and Muhammad Addifa Yulman

637

3265

ELECTRICALLY CONDUCTIVE GEOMEMBRANE ENHANCES LINER LEAK DETECTION SURVEYS ATPOST INSTALLATION
H.B. Ng, D. Gallagher and A. Beck

642

3266

INVESTIGATION OF CESIUM DIFFUSION IN CRACKED CONCRETE BY USING MICROFOCUS X-RAY
CT
Ivan Sandi Darma, Shohei Ikeda, Takafumi Sugiyama

646

3278

MODELLING THERMO-ELASTO-PLASTIC BEHAVIOUR OF NORMALLY CONSOLIDATED AND
OVERCONSOLIDATED SOILS
Yang-Ping Yao and Annan Zhou

652

3279

STABILITY OF A ROCK SLOPE SUSCEPTIBLE TO SEASONAL MOVEMENTS
A. K. Alzo’ubi

658

3289

REAL-TIME BRIDGE SCOUR MONITORING SYSTEM BY USING CAPACITOR SENSOR
S. M. A. Motakabber, M. I. Ibrahimy and A. H. M. Zahirul Alam

664

3291

SKIN FRICTION TESTS ON MODEL PILE IN WET SOIL
Mohamed M. Shahin

667

3299

A NEW UPPER BOUND SOLUTION TO QUANTIFY THE ULTIMATE BEARING CAPACITY OF
SHALLOW FOUNDATIONS ON RESTRICTED SOIL
Reza Afshar-mazandaran, Hadi Khabbaz

673

3304

SOME THOUGHTS ON THE ULTIMATE RESISTANCE OF PILES
Stephen Buttling

679

3307

WIRELESS SENSOR NETWORK FOR LANDSLIDE MONITORING
S. M. A. Motakabber, M. I. Ibrahimy and F. Anwar

685

3311

INFLUENCE OF THE SOIL-STRUCTURE INTERACTION ON THE SEISMIC BEHAVIOR OF BUILDINGSON SHALLOW FOUNDATIONS
Z. Benadla, K. Hamdaoui, S. Aissaoui and A. Baouch

688

3328

NUMERICAL STUDY OF PLASTICITY-BASED CONSTITUTIVE MODELS FOR SOIL IN SIMULATION OF
BRACED EXCAVATION
Samuel J. Verghese, Ha H. Bui

694

v

3339

A NUMERICAL MODEL TO PREDICT SETTLEMENT OF CHEMICALLY STABILISED LANDFILL
Behnam Fatahi, Hadi Khabbaz

700

3340

SHEAR PROPERTIES OF HIGH-DENSITY BENTONITE-SAND MIXTURE UNDER UNSATURATED AND
SATURATED CONDITIONS
Takeshi Kodaka, Ying Cui and Hidenori Takada

706

3352

ENVIRONMENTAL CONDITION INDEX FOR ESTIMATION ON EUTROPHIC STATE OF ENCLOSEDAQUIFER ECOSYSTEM
Kazuhito Murakami, Michio Gomyo, Saki Agatsuma and Yoshimasa Amano

711

3170

SHALE FAILURE AND CRACKING IN A SEMI-ARID AREA
Muawia Dafalla, Mutaz E. , Mansour Al humimidi, Loni Allafouza Oumar and Mosleh Al Shamrani

717

3300

EARTH MASONRY UNIT: SUSTAINABLE CMU ALTERNATIVE
Joseph Dahmen, Jose F. Muñoz

721

3285

CONSTRUCTION AND MAINTENANCE OF EMBANKMENTS USING HIGHLY ERODIBLE SOILS IN THE
PILBARA, NORTH-WESTERN AUSTRALIA
J.V. Smith and L.A. Sullivan

728

vi

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

PrefaceOn behalf of the GEOMATE 2013 Organizing Committee, it is our great pleasure to welcome you to theInternational Conference on Geotechnique, Construction Materials and Environment held at the Meitetsu
New Grand Hotel, Nagoya, Japan organized in conjunction with Nagoya Institute of Technology,
GEOMATE International Society, Japanese Geotechnical Society, AOI-Engineering, Useful Plant SpreadSociety, HOJUN and Glorious International. On Friday 11 March 2011, at 14:46 Japan Standard Time, thenorth east of Japan was struck and severely damaged by a series of powerful earthquakes which also caused amajor tsunami. This conference was dedicated to the tragic victims of the Tohoku-Kanto earthquake andtsunami disasters. Since this is the third conference in this series, we have received a lot of positive feedback
from the participants.
The conference covers three major themes with 17 specific themes including:●
Advances in Composite Materials●
Computational Mechanics●
Foundation and Retaining Walls●
Slope Stability●
Soil Dynamics●
Soil-Structure Interaction●
Pavement Technology●
Tunnels and Anchors●
Site Investigation and Rehabilitation●
Ecology and Land Development●
Water Resources Planning●
Environmental Management●
Public Health and Rehabilitation●
Earthquake and Tsunami Issues●
Safety and Reliability●
Geo-Hazard Mitigation●
Case History and Practical Experience
This year we have received many paper submissions from different countries all over the world, including
Albania, Algeria, Australia, Bahrain, Bangladesh, Belarus, Benin, Canada, China, Colombia, Czech Republic,
Egypt, Ethiopia, Germany, Hong Kong, India, Indonesia, Iran, Iraq, Japan, Kenya, Libya, Malawi, Malaysia,
Norway, Poland, Romania, Russia, Saudi Arabia, Singapore, South Korea, Sri Lanka, Sudan, Taiwan,
Thailand, Tunisia, Ukraine, United Arab Emirates, United States and Vietnam. The technical papers wereselected from the vast number of contributions submitted after a review of the abstracts. The final papers in
the proceedings have been peer reviewed rigorously and revised as necessary by the authors. It relies on thesolid cooperation of numerous people to organize a conference of this size. Hence, we appreciate everyone
who support as well as participate in the joint conferences. Last but not least, we would like to express our
gratitude to all the authors, session chairs, reviewers, participants, institutions and companies for theircontribution to GEOMATE 2013. We hope you enjoy the conference and find this experience inspiring andhelpful in your professional field. We look forward to seeing you at our upcoming conference next year.
Best regards,
Prof. Teruo Nakai, Conference Chairman
Dr. Md. Zakaria Hossain, Conference General Secretary
Dr. Hossain Md. Shahin, Conference Secretaryvii

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

Organization
Scientific Committees:
Conference Chairman: Prof. Dr. Teruo Nakai, Nagoya Institute of Technology, Japan
Conference Honorary Chairman: Emeritus Prof. Dr. Sohji Inoue, Mie University, Japan
Conference Organizing Committee:
Prof. Dr. Teruo Nakai, Nagoya Institute of Technology, Japan
Prof. Dr. Feng Zhang, Nagoya Institute of Technology, Japan
Prof. Dr. Kenichi Maeda, Nagoya Institute of Tech., Japan
E/Prof. Dr. Sohji Inoue, Mie University, Japan
A/Prof. Dr. H.M. Shahin, Nagoya Institute of Tech
A/Prof. Dr. Zakaria Hossain, Mie University
National Advisory Committee:
Prof. Dr. Fumio Tatsuoka, Tokyo University of Science, Japan
Prof. Dr. Toshinori Sakai, Mie University, Japan
Prof. Dr. Masaki Nakano, Nagoya University, Japan
Prof. Dr. Toshihiro Noda, Nagoya University, Japan
Prof. Dr. Jing-Cai Jiang, University of Tokushima, Japan
Prof. Dr. Noriyuki Yasufuku, Kyushu University, Japan
Prof. Dr. Masuya Hiroshi, Kanazawa University, Japan
Prof. Dr. Toshihiro Morii, Niigata University, Japan
Prof. Dr. Nishimura Tomoyoshi, Ashikaga Inst. of Tech., Japan
Prof. Dr. Yoshihiro Kimura, Tohoku University, Japan
Prof. Dr. Kimitoshi Hayano, Yokohama National Univ., Japan
A/Prof. Dr. Kenichiro Nakarai, Hiroshima University, Japan
International Advisory Committee:
Prof. Dr. Sai Vanapalli, University of Ottawa, Canada
Prof. Dr. M. Bouassida, National Sch. of Engg. of Tunis
Prof. Dr. L.R. Austriaco, Angles Univ. Found., Philippines
Prof. Dr. A.S.M. Abdul Awal, Univ. Technology Malaysia
Prof. Dr. M. Ibn Ibrahimy, Int. Islamic Univ., Malaysia
Prof. Dr. Md. Zahurul Islam, BUET, Bangladesh.
Prof. Dr. Bujang B.K. Huat, Univ. Putra Malaysia
Prof. Dr. Nemy Banthia, UBC, Canada
Prof. Dr. Ian Jefferson, Univ. of Birmingham, UK
Prof. Dr. John Bolander, Univ. of California, USA
Prof. Dr. Shamsul Chowdhury, Roosevelt Univ., USA
Prof. Dr. Isabel Pinto, University of Coimbra, Portugal
Prof. Dr. Mark Jaksa, University of Adelaide, Australia
A/Prof. Dr. Mohamed Shahin, Curtin University, Australia
A/Prof. Dr. Jim Shiau, Univ. of Southern Queensland Toowoomba
A/Prof.. Dr. Hj. Ramli Bin Hj. Nazir, UTM, Malaysia
A/Prof. Dr. Aly Ahmed, Beni-Suef University, Egypt
Dr. J.N. Mukabi, President of Kenya Geotech Soc., Kenya

viii

Conference Secretariat:
Dr. H.M. Shahin, Secretary, A/Prof. NIT, Japan
Dr. Zakaria Hossain, General Secretary, A/Prof. MU, Japan
Mr. Musahaq Ali, Assistant Secretary
Division of Environmental Science and Technology
Graduate School of Bioresources
Mie University, 1577 Kurima Machiya-cho
Tsu-city, Mie 514-8507, Japan
E-mail: geomate@gi-j.com
Tel+Fax: +81-59-231-9578
Editorial Committee:
Dr. Md. Zakaria Hossain
Dr. Hossain Md. Shahin
Executive Committee:
A/Prof. Dr. Md. Zakaria Hossain
A/Prof. Dr. Hossain Md. Shahin
Prof. Dr. Teruo Nakai
E/Prof. Dr. Sohji Inoue
Mr. Musahaq Ali

Note- A: Associate, E-EmeritusixGEOMATE-Nagoya, Nov.13-15, 2013

Technical Papers Volume 3(2)574Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

DEVELOPMENT OF RAINFALL INFILTRATION INTOUNSATURATED SOIL COLUMN USING ELECTRICALCAPACITANCE VOLUME-TOMOGRAPHY (ECVT)

1

Aniza Ibrahim1,2, Muhammad Mukhlisin1,3 and Othman Jaafar1
Department of Civil and Structural Engineering, Universiti Kebangsaan Malaysia,
2
Faculty of Engineering, Universiti Pertahanan Nasional Malaysia,
3
Department of Civil Engineering, Polytechnic Negeri Semarang, Indonesia.
ABSTRACT

Infiltration caused by rainfall will effect to the changes of moisture content and pore water pressure of thesoil. These changes indicate the behavior of the soil especially during wetting and drying process, which leads tothe soil instability especially slopes. The objective of this paper is to study the effect of rainfall intensity andduration to the image developed by ECVT during infiltration process. Normally, most of the studies of
infiltration for unsaturated soil used time-domain reflectometer (TDR) and tensiometer that attached to the soilcolumn to measure the parameters. This paper present the experimental result that not only obtaining the data ofvolumetric water content and pore water pressure, but also images of water infiltration throughout the column.
This real time 3 dimension images were developed by Electrical Capacitance Volume Tomography (ECVT) that
attached to the soil column. Type of soil used in this study is gravelly sand which is commercially obtained. Twotypes of simulated rainfall with designated duration were applied to the soil column. The result showed that thereal time images were successfully performed throughout the wetting and drying process by ECVT. The 3
dimensional images show that the water infiltration pattern is responded with the gravelly sand. Other than real
images, the normalized permittivity obtained can be used to obtained volumetric water content, which normallyobtained by TDR in the infiltration study. This new technology is expected to enhance the understanding soil
behavior especially in the area of water infiltration relates to soil instability.
Keywords: Infiltration, Pore water pressure, Soil column, ECVT, , Volumetric water content.

rainfall intensity and duration, with the rationale thatthe parameters mentioned can be achieved.
Soil column apparatus is widely known as anapparatus to perform simulate water infiltration into
soil. This apparatus has been used extensively tofacilitate understanding of rainfall infiltration
mechanism. Normally, few equipments are attachedto soil column to measure the parameters such as
TDR and tensiometer. Even soil column apparatus
can attained parameters related to rainfall induced
soil instability, the parameters that obtained are atthe point where the equipments are installed. The
high quantity of equipment attached, moreparameters obtained, and higher understanding of
the soil behavior. As a result, there are limited spaceof locating TDR into the soil column. On the other
hand, the result will measure only at the points
where the equipments are installed.
ECVT is the innovative technology in civilengineering especially in geotechnical engineeringresearch. Previously the principle of tomography
was widely used for other area such as Magnetic
resonance imaging (MRI), X-ray micro tomography,
Optical tomography, resistive tomography, Acoustic
tomography, Positron-emission tomography (PET),
Capacitance tomography, and others [11]. ECVT is

INTRODUCTION
There are several factors that caused soil
instability; human activities especially on slope,
rainfall, hillside development, and climatic condition
such as geological features, topography, vegetation,or combination. For tropical country, high seasonalrainfall is the main reason for many slope instability
event [1],[2]. In Malaysia, the residual soil iscomposed with the negative pore water pressure
above the groundwater table, which vigorously
subjected by climatic and hydrological changes suchas precipitation, infiltration, evaporation andtranspiration [8]. Therefore, these rainfall-induced
slope failures are caused by the loss of pore waterpressure of soils by rainwater [1],[6].
The mechanism of rain water infiltration into thesoil event is complex due to its high nonlinearity ofsoil water characteristic and soil permeability [12].
Supported by [3] and [5], the complexity isconcerning the parameters such as soil initialmoisture condition, soil water retention ability, soil
porosity, evaporation rate and others. For thatreason, the desires to study the infiltration
mechanisms are essential with the intention ofunderstanding the behavior of soil under various
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GEOMATE-Nagoya, Nov.13-15, 2013

the 3 dimensional real-time imaging system
considered as " the most promising technique fordynamic flow imaging, which has a relatively hightemporal resolution, up to few milliseconds , withreliable spatial resolution "[4].
The basic principle of ECVT is based on themeasurement of electrical properties with forward
and inverse problem [10]. Forward problem engage
with the collection of capacitance data fromelectrodes to the data acquisition system. Theseelectrodes act as sensors are located at the perimeterof ECVT wall vessel. Then, inverse problem will be
conducted which including retrieving thecapacitancedatabypersonalcomputer.
Subsequently, the measured data capacitance is used
for the reconstructing images.
Previously, the principle of ECVT has been used
to explore the transient occurrence in the entrance
region of column using a single nozzle gas
distributor with paraffin liquid, air, and glass beads
as flow media [9]. In this research, these technique
was proved to facilitate a real time 3D imaging ofexperiment perform for the moving object. On theother hand, [7] used ECVT to capture real time
imaging of water infiltration that can be seen in eachlayer of the vessel.
The objective of this paper is to study the effectof rainfall intensity and duration to the image
developed by ECVT during infiltration process. The
imaging of 3 dimension real-time imaging is
captured along the experiment, and the capacitancedata is then converted to evaluate volumetric watercontent for the gravelly sand.

Water flow regulator for rainfall simulation wasused as a water supply in infiltration test. The pumpwhich is manufactured by Cole-Parmer, model
07554-80 Masterflex L/S economy with variablespeed console and the speed are varies from 1 to 10,
was attached with Masterflex L/S Easy –Load IIpump heads.
Table 1: Soil Properties of Gravelly sand.
Soil Properties

Symbols

θ𝒘𝒘

Moisture content
Bulk density
Saturated volumetricwater content
Residual volumetricwater content
Fitting parameters

Saturated hydraulicconductivity (m/s)

g cm

θ𝒔𝒔

−𝟑𝟑

Gravelly
Sand
0.00131.572
0.0883θ𝒓𝒓
α0.03131.2931nm
Ks

1.43960.30546.333e-4

Soil Column Apparatus
The main component of soil column in thisexperiment was the ECVT apparatus system which
include the vessel with sensors, data acquisition
system, and the parameters can be retrieved bypersonal computer. Size of the vessel is 11.5 cm x
27 cm, and there are 32 pixel for all x, y, and z axes.
Therefore, the length of vessel is divided by the total
pixel resulted of 0.844 and 0.11 cm3 per voxel. The
parameters were set to be logged for every 1 minutethroughout the experiment.
Using the equation proposed by [7], the value of
normalization permittivity, and volumetric watercontent can be determined.

MATERIALS AND METHOD
Properties of soil
Soil used for the experiment was gravelly sand,and basic properties of the soil such as moisture
content, porosity, and bulk density were determinedin the laboratory.
Other than that, saturated
hydraulic conductivity, k s was measured throughconstant head permeability test. Plate pressure
extractor apparatus was used to measure Soil Water
Characteristic Curve (SWCC) of the soil, which theresult was fitted using Van Genuchten Method(1980). The results of soil properties are as in the
Table 1.

Normalized permittivity,
𝜺𝜺𝑵𝑵 =

𝜺𝜺−𝜺𝜺𝒓𝒓𝒓𝒓𝒓𝒓(1)

𝜺𝜺𝒔𝒔𝒔𝒔𝒔𝒔 − 𝜺𝜺𝒓𝒓𝒓𝒓𝒓𝒓

Volumetric water content,𝜽𝜽 = 𝜼𝜼 �Experimental set up

𝜺𝜺−𝝐𝝐𝒓𝒓𝒓𝒓𝒓𝒓

𝜺𝜺𝒔𝒔𝒔𝒔𝒔𝒔 − 𝜺𝜺𝒓𝒓𝒆𝒆𝒆𝒆

�

𝟎𝟎.𝟓𝟓

(2)

where 𝜺𝜺𝑵𝑵 , 𝜺𝜺, 𝜺𝜺𝒓𝒓𝒓𝒓𝒓𝒓 , 𝐚𝐚𝐚𝐚𝐚𝐚 𝜺𝜺𝒔𝒔𝒔𝒔𝒔𝒔 are normalized, relative,residual, saturated permittivity respectively, and𝜼𝜼 is the porosity.

The infiltration test was conducted in a soilcolumn apparatus which consists of water supply
system, soil column, and percolation collection
system.

It is noted that the relative permittivity for air,water, residual soil , and saturated soil are 1, 80, 2-4,
and 23-28 respectively.

Water supply system

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GEOMATE-Nagoya, Nov.13-15, 2013

The experimental schedule

However, the ECVT vessel which attached to thesensors cannot be intruded for assembling of TDR
and tensiometer. Therefore, top of the vessel was
extended with acrylic tube for this purposes. TDR
used in this experiment was TRIME-IT TimedomainReflectometry
withIntelligent
MicroElements by IMKO Micro modultechnik
Gmbh. Other than that, mini tensiometer used wastype T5, from UMS GmbH product. All data from
ECVT , TDR and tensiometer were obtained throughseparately data acquisition system attached to thesoil column for every ten minutes except from
ECVT which was every 1 minute. The schematic
diagram of the soil system component is illustrated
in Figure 1.

The infiltration tests were carried out with two
simulated rainfall flow rate and durations. The firstexperiment was carried out with 1.93 mL/s flow rate,
for 3 days. In addition, second experiment was donewith 10 mL/s flow rate, for 1 day. 1 hour is allocatedfor drying process for each test respectively.
RESULTS AND DISCUSSIONECVT images
3-Dimensional images
For the imaging of ECVT, there are 32
slices/sections produced for every frame. Total
frame is indicated by the duration times for theexperiment is conducted. In other word, there are 32
slices or sections per frame for 6347 minutes , which
the total of 203,104 sections altogether from top tobottom of the vessel.
The example of the images captured by sensors
as shown in Figure 2. The images that obtained wereconverted to the video, before slicing the sections toshow the details of rainfall infiltration. In Figure 2,
the normalized permittivity which indicates thevalue of zero approaching 1,was represented by thecolor code of red, orange, yellow, light blue, andblue.
In this example, infiltration of water was clearly
verified by the Figure 2(a) to Figure 2 (h). As a start,
the vessel was filled with soil, showed by the redcolor code. (Figure 2a). Figure 2(b) demonstrated
blue color on the top of the vessel which indicatedthat water started to infiltrated into the vessel after
simulated rainfall was applied. Then the water
infiltration continued approaching bottom of thevessel ,as proved in Figure 2 (c), and (d). In Figure2(e), while the whole vessel was occupied by thewater , but there was light blue color on the top ofvessel, which indicated that the drying process wasstarted on that particular sections. Subsequently,
Figure 2 (f) and (g) suggested that the soil in thevessel continued to dried up after simulated rainfall
has stopped. Finally, the color of the whole vessel
was changed to red color indicated that soil in mostof the sections was in drying process.

Percolation Collector System
Water percolation collection system in thisexperiment was used to measure the discharge ofrainwater through infiltration. Rainlog Datalogger
by Rainwise was used to collect discharge from soilcolumn. The 8 inches diameter collector tipping
bucket will collect 0.01 inch/tip and 0.5 min/tip
minimum and maximum respectively. This battery
operated logger fits inside the polypropylene rain
gauge and will measure the total rainfall at every ten
minute. For this experiment, rain gauge was set for0.01 inch/tip.

Volumetric Water Content(ECVT)The parameter obtained from ECVT was
normalized permittivity, which can be converted torelative permittivity for analysis. Equation (1) wasused for conversion in the analysis. After obtaining
relative permittivity , equation (2) was use to convert
the value of relative permittivity to volumetric watercontent. Figure 3(c) shows the effect of rainfall
infiltration to the volumetric water content for the

Figure 1 : Schematic diagram of soil column
apparatus using ECVT

577

GEOMATE-Nagoya, Nov.13-15, 2013selected points along the height of ECVT vessel,
which represent the differences among each level ofvessel.

(f)

(d)

(g)

(h)

Flow rate (mL/s)(c)

Pore water pressure
(hPa)

(e)

(b)

12
10
8
6
4
2
0
1000
800
600
400
200
0

Volumetric water content(m3/m3)(a)water infiltrates into the soil resulted in decreasing
the value of pore water pressure, but increasing
while drying process. On the other hand, volumetricwater content was increased while wetting , but
decreased during drying process. For the
percolation, Figure 3 (d) indicated the first drop ofwater at the 50.5 hours after the experiment started.

Figure 2: 3-Dimensional images of ECVT

Percolation Collector(mm/10 min)The graph shows that the pattern of volumetricwater content moves from the left to right side of thegraph, proved that the water infiltration affect thevalue of volumetric water content. The volumetricwater content increased when applying the first
rainfall event, then decreased as drying process took
place. In addition, the second rainfall event was also
having the same pattern as the first event.
It was being observed that the middle section of
the vessel achieve higher value of volumetric watercontent compared to others. This phenomena wasperceived due to the fact that the water infiltrates
into the soil , and trapped into the middle section,
before leaving the section, and continue infiltrates
into the bottom section. Other than that, theconditions was the effect of the soil porosity, rainfall
intensity, and the soil capacity of holding water.

(a)

(b)

0.25

1
4
5
9
10
11
15
16
17
21
22
23
27
28
32
TDR

(c)

0.20
0.15
0.10
0.05
0.00
0.6
0.5
0.4
0.3
0.2
0.1
0.0

(d)

0

20

40
60
Time (hour)

80

100

Figure 3: Relationship of (a)Flow rate, (b)Pore waterpressure, (c)Volumetric water content, and(d)Percolation

Pore water pressure (tensiometer) and percolation
systemCONCLUSION

Other than results acquire by ECVT, theexperiment also acquire results from the equipments
attached to the soil column system. The TDR, andtensiometer were used to compare the pattern ofparameters of volumetric water content and porewater content from ECVT. As shown in Figure 3(b),the result for pore water pressure has the same
pattern of volumetric water content along theexperiment. As rainfall was applied to the column,

In this study, one dimensional infiltration test using
soil column was conducted in the two components;
attaching TDR and tensiometers to the soil column,
and using real time imaging of ECVT sensors. The
analysis and results show that real time imaging ofwater infiltration can be captured by ECVT method.
The 3 dimensional images produced the water
infiltration pattern response with the gravelly sand.
578

(d)

GEOMATE-Nagoya, Nov.13-15, 2013

Other than real images, the normalized permittivity
obtained can be used to obtained volumetric watercontent, which normally obtained by TDR in theinfiltration study. It is suggested that 2 dimensional
images also can be produced in order to check the
performance of the infiltration parameters at the
points selected. Finally, this new technology is
expected to enhance the understanding thecomplexity of soil behavior especially in the studyof water infiltration.

[5] Mukhlisin M, Kosugi K, Satofuka Y, andMizuyama T,"Effects of Soil Porosity on Slope
Stability and Debris Flow Runout at a
Weathered Granitic Hillslope",Vadose Zone J,
Vol 5, 2006,pp. 283-295.
[6] Mukhlisin, M., and Taha, M.R.,"Numerical
Model of Antecedent Rainfall Effect on Slope
Stability at a Hillslope of Weathered Granitic
Soil Formation", Journal Geological Society ofIndia, Vol 79, 2009 ,pp.525-531 .
[7] Mukhlisin M, Saputra A, El-Shafie A, and Taha
M. R, "Measurement of Dynamic Soil Water
Content Based on Electrochemical Capacitance
Tomography," Int. J. Electrochem. Sci., vol. 7,
2012,pp.5457-5466.
[8] Rahardjo H, Ong T.H, Rezaur R. B, Leong E.C,
and Fredlund D.G, "Response Parameters for
Characterization of Infiltration," Environment
Earth Science, vol. 60, 2010,pp. 1369-1380.
[9] Van
Genuchten
M.TH,"A
Closed-form
Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils", Soil Sci.
Soc. Am. Journal, vol.44(5),1980,pp. 892-898.
[10] Warsito W and Fan L.S, "Dynamics of spiralbubble plume motion in the entrance region of
bubble columns and three-phase fluidized beds
using 3D ECT", Chemical Engineering Science,
vol. 60, 2005,pp.6073-6084.
[11] Warsito W, Marashdeh Q, and Fan L-S,
"Electrical Capacitance Volume Tomography",IEEE Sensors Journal, vol. 7, 2007,pp.525-535.
[12] Willians R. A and Beck M. S., 'Introduction toprocess tomography', Process Tomography:
Principles, Techniques and Applications., 1 ed.:Butterworth-Heinemann, 1995,pp.3-10.
[13] Yang H, Rahardjo H, and Leong E. C,"Behavior of Unsaturated Layered Soil
Columns during Infiltration," Journal of
Hydrologic Engineering, July / August 2006,
pp. 329-337.

ACKNOWLEDGEMENTS
The authors would like to express theirappreciation to the financial supports provided by
Universiti
Kebangsaan
Malaysia
through
ERGS/1/2012/TK03/UKM/02/2, and the Faculty of
Civil Engineering and Built Environment.

REFERENCES[1] B. B.K, Ali F. H and Low T.H, "Water
Infiltration Characteristics of Unsaturated Soil
Slope and its Effect on Suction and Stability,"
Geotechnical amd Geological Engineering, vol.
24, 2006,pp. 1293-1306.
[2] Gofar N, Lee L. M, and Kassim A,"Instrumented Soil Column Model for Rainfall
Infiltration
Study,"
presented
atthe
GEOTROPIKA 2008.
[3] Lee L. M, Kassim A, and Gofar N,"Performance of Two Instrumented Laboratory
Models for the Study of Rainfall Infiltration into
Unsaturated Soils", Engineering Geology, vol.
117, 2011, pp. 78-89.
[4] Marashdeh Q, Fan L.S, Du B, and Warsito W,"Electrical Capacitance Tomography - A
Perspective," Ind. Eng.Chem. Res., vol. 47,
2008, pp. 3708-3719.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SITE RESPONSE ANALYSIS TO DERIVE GROUND MOTIONSIGNALS FOR ENGINEERING APPLICATIONS
Thayalan Nall1, Greg Hackney2 and Harry Poulos3
Coffey International, Australia

ABSTRACT
Design ground motions for earthquake related analyses are typically specified as ‘rock outcrop’ motions.
Often they have to be modified for use as input signals at depth for engineering assessments of stress, strain anddisplacement. Modifications are often undertaken using a site response analysis with commercially available
programs such as SHAKE, Proshake and Quake/W, which have been developed based on wave propagation
techniques. This is seemingly a simple process; however is often the subject of considerable confusion. In a
recent study, site response analyses have been undertaken to de-convolute and convolute free-field outcrop
ground motion signals using Proshake. Convoluted signals from various other commercially available and inhouse programs were examined and compared. This paper outlines the concepts, discusses compatibility issues
and presents examples illustrating the process and verification of the resulting input ground motion signals. This
study highlights it is imperative that a suitable site response analysis is undertaken to arrive at an appropriate
input signal for engineering applications. Further when two different programs are used care should be taken to
ensure that material models and functions adopted are compatible.
Keywords: Site Response, Earthquake, De-convolution, Convolution, Acceleration-Time Signal

method has fundamentally different mathematicalformulations to solve for ground response.

INTRODUCTION
For earthquake engineering assessments design
earthquake ground motion signals are generally
developed based on site specific Seismic Hazard
Studies (SHS) and are usually presented as free fieldrock outcrop motions (i.e. the signal that would bemeasured by a seismograph positioned on a rockoutcrop). However for seismic analyses, (finite
element or semi-empirical methods), the seismic
input must be relevant to the ground model and thelocation in the model that the signal is applied. For
Finite Element Models (FEM), Acceleration-Time(A-T) functions are usually applied at the base of themodel and for liquefaction assessments; the PeakGround Acceleration (PGA) must be relevant to theliquefiable layer. This gives rise to the question:
what input motion should be considered in order toadequately simulate the design ground motion?
In a recent study, site response analyses havebeen undertaken to de-convolute and convolute freefield outcrop ground motion signals to obtain adesign input motion. De-convolution was performed
using Proshake to obtain input signals for Dynamic
PLAXIS modeling to assess earthquake-induced
displacements. While convolution has been
performed to validate the de-convolution process
and assess compatibility between Proshake and
PLAXIS, additional site response analyses were
undertaken to examine and compare convoluted A-T
signals from programs such as ERLS (Earthquake
Response of Layered Soils, a Coffey in-houseprogram), Proshake, PLAXIS and Quake/W, as each

FORMULATIONS
The formulations adopted for the various
programs are described below:
ProShake is based on a frequency domain
formulation. This method uses a Fast Fourier
Transform (FFT) to convert the input motion from atime domain into a Fourier series in the frequency
domain. The response at any location in thefrequency domain can be obtained by using the input
motion together with a transfer function. Aftercomputing the response in the frequency domain, themethod uses an inverse FFT to transform thesolution back to the time domain [1].
QUAKE/W is based on a finite element
formulation which uses Wilson Theta integration
scheme in the time domain. This does not involve
transformation of the motion equations into thefrequency domain and the motion equations are
solved directly using a finite-difference timestepping procedure [2].
PLAXIS is also based on a finite element
formulation which uses a damped implicit Newmark
integration scheme. The advantage of an implicit
scheme is that it is more stable and less dependent
on the chosen time step [3].
ERLS is a one-dimensional program that
employs a forward marching explicit finite
difference scheme in the time domain [4]. This isbased on the lumped mass model as developed by580

GEOMATE-Nagoya, Nov.13-15, 2013

Seed and Idriss [5]. The basis of this model is thereplacement of each soil layer with a series of
lumped masses connected by strain-dependent
springs and dash-pots.

displacements. To assess earthquake induced
parameters in relation to those mobilized at the baseof the model, input ground motion signals are
generally modified to yield zero displacement.
PLAXIS adopts an ‘absorbent’ boundary to absorb
incremental stresses caused by dynamic loading andto avoid reflection into the soil body [3].

NONLINEARITY OF MATERIALSThe characterization of dynamic material
properties is a fundamental consideration in dynamicsite response analyses. It is well known fromlaboratory testing that soils exhibit pronounced
nonlinear behavior under shear loading conditions.
Shear modulus decreases with increasing strain andis accompanied by an increase in material damping.
As this behavior is applicable to in situ geotechnicalmaterials subjected to earthquake loading, site
response calculations need to accommodate strain
dependent nonlinearity of stiffness and damping.
Although it has been long recognized that there
are problems such as sample disturbance andlaboratory tests that do not exactly simulate thedynamic stress path caused by shear waves in thefrequency range up to 20Hz, various parametric
relationships have been proposed based onlaboratory test results for use in dynamic analysis.
Each nonlinear model has its advantages andlimitations in describing the response of soil to thetype of loading produced by seismic disturbances.
The goal of the de-convolution and convolution
exercise through site response analysis is to estimate
the appropriate base input motion to the model suchthat the design outcrop motion is recovered at the
top of rock (outcrop) level. Within the PLAXIS
model, the nonlinear Hardening Small Strain (HSS)
model was adopted [6]. Both Proshake andQuake/W have the flexibility of user defined strain
dependent shear modulus and material damping
functions [2], [7]. However in ERLS, thecoefficients of reference parameters were adjusted toarrive at similar strain dependent relationships [4].
PLAXIS and Quake/W also have the capability
to incorporate pore pressure build up and dissipation[2], [3]. In the site response analysis describedherein this capability was used only in PLAXIS™
by adopting the ‘Undrained A’ drainage model. Allother programs used a total stress approach.

SITE DESCRIPTION AND INPUT DATA
The subject site comprised a complex profile ofmarine, alluvial and variable strength rock to
considerable depth, which would be used to support
an earth-and rock structure, as described in Figure 1.
A-T signals as rock outcrop motions (formaterial having a shear wave velocity (Vs) of
1000m/s) were obtained for the site from the SHS.
For the dynamic analysis, ground conditions down
to 450m depth were modeled. Broadly, this profile
comprised 115m of sediments and weak rocks,
underlain by two distinct high strength rock layers.
The upper rock layer is approximately 135m thick
and was characterized by Vs value of 1000m/s. The
lower rock layer is approximately 200m thick and ischaracterized by a Vs value of 1200m/s. A site
response analysis was undertaken to de-convolute
the outcrop A-T signals through the two highstrength rock layers to obtain suitable input signals
at the base of the model.

Outcrop Motion

Structure

Quaternary Sediments
Weathered Rock-1
Weathered Rock-2
Rock-1Rock-2

Input Motion
Fig. 1 Earthquake Ground Motions

DYNAMIC ANLAYIS IN PLAXISNONLINEAR MODEL IN PLAXIS

Dynamic PLAXIS (2-D) has been used as theprimary tool in a study to assess earthquake induced
stress, strain and displacement for an earth and rock
structure in an active earthquake zone. A key focusof the site response analysis was to establish
appropriate A-T signals as inputs into the modeling.
Earthquakes are usually modeled by means ofprescribed horizontal displacements at the base of
the model, while maintaining zero vertical

Functions for shear modulus and material
damping used in the PLAXIS model are describedbriefly.
Strain Dependent Shear Modulus
To characterize the degradation of the shear
modulus of soil and rock with strain, PLAXIS uses a
hyperbolic law proposed by Santos & Correia [8]581GEOMATE-Nagoya, Nov.13-15, 2013

which is a modified version of the Hardin &Drnevich [9] relationship. The function is definedusing the small-strain shear modulus (G 0 ) and theshear strain (γ 0.7 ) at which the secant shear modulus(G s ) reduces to about 70% of G 0 .
𝐺𝐺 𝑆𝑆 = 𝐺𝐺 𝑜𝑜 /(1+0.385 𝛾𝛾⁄𝛾𝛾 0.7 )(1)

𝐺𝐺 𝑢𝑢𝑟𝑟 = 𝐸𝐸 𝑢𝑢𝑟𝑟 /2(1+𝑣𝑣 𝑢𝑢𝑟𝑟 )

(2)
(3)

a = γ 0.7 /0.385(4)Strain Dependent Material Damping
PLAXIS incorporates hysteretic material
damping in addition to viscous damping [11]. The
hysteretic damping is estimated as the ratio ofenergy dissipated between each cycle of loading(E D ) and maximum strain cycle (Es). Hysteretic
damping increases with increasing shear strain as
shear modulus decreases, but remains constant assoon as the cutoff modulus G ur is reached.

PLAXIS, incorporates a lower cutoff shear
modulus at G ur , so that the stiffness reduction curve
does not extend far into the plastic region. G ur andcutoff strains are computed as per the expressions
below.

𝛾𝛾 (𝑐𝑐𝑢𝑢𝑡𝑡𝑡𝑡−𝑜𝑜𝑓𝑓𝑓𝑓) = a(𝐺𝐺 0 /𝐺𝐺 𝑢𝑢𝑟𝑟 −1)0.5

𝐷𝐷 ℎ =𝐸𝐸 𝐷𝐷 /((4π𝐸𝐸s ) )𝐸𝐸 𝐷𝐷 =4a𝐺𝐺 𝑜𝑜(7){2𝛾𝛾 𝑐𝑐 −𝛾𝛾 𝑐𝑐 /(1+a⁄𝛾𝛾 𝑐𝑐 )−2a(6)ln[1+(𝛾𝛾 𝑐𝑐 /a)]}

𝐸𝐸𝑠𝑠=𝐺𝐺 0 𝛾𝛾 (𝑐𝑐𝑢𝑢𝑡𝑡−𝑜𝑜𝑓𝑓𝑓𝑓) 2/(2+2a𝛾𝛾 𝑐𝑐 𝑢𝑢𝑡𝑡−𝑜𝑜𝑓𝑓𝑓𝑓 )Therefore in PLAXIS in addition to G 0 and γ 0.7 ,the ratio G 0 /G ur is user defined to establish the shear
modulus verses shear strain relationship. The strain
dependent modulus reduction function adopted in
the analysis, along with a published reduction
function [10], is shown in Figure 2.

(8)

At small strains, hysteretic damping is
insignificant.
PLAXIS incorporates viscousdamping through Rayleigh damping parameters. For
this study, a viscous damping ratio of 0.5% has been
adopted and the Rayleigh parameters α and β were
estimated based on the natural site period (Ts). The
strain dependent material damping adopted in theFig. 2 Shear Modulus Reduction Function

analysis is shown in Figure 3, together with apublished damping function [10].
Stress Dependent Shear Modulus
Fig. 3 Material Damping Function
At each analysis step, PLAXIS updates thematerial shear modulus based on stress state. This
stress dependent shear modulus is implemented by apower law, as given below.

DE-CONVOLUTION USING PROSHAKEAs the SHS did not consider upper soil or weakrock layers in the derivation of the design outcrop
motions, it was considered reasonable not toconsider these in the de-convolution analysis. The‘rock outcrop’ level was considered as the top of thehigh strength Rock-1, which was evident around RL
880m (site datum), whilst mean sea level is RL
1000m (site datum). The base of the analyticalmodel was at RL 550m (site datum). The groundmodel considered in de-convolution process isshown schematically in Figure 4.

𝐺𝐺 0 = 𝐺𝐺 0𝑟𝑟𝑒𝑒𝑓𝑓 {(σ’ 3 𝑠𝑠𝑖𝑖𝑛𝑛𝜑𝜑+𝑐𝑐 𝑐𝑐𝑜𝑜𝑡𝑡𝜑𝜑)/(𝜎𝜎 𝑟𝑟𝑒𝑒𝑓𝑓 𝑠𝑠𝑖𝑖𝑛𝑛𝜑𝜑+𝑐𝑐 cot𝜑𝜑)} 𝑚𝑚

The stress dependency of the G 0 is incorporated
in the other programs by dividing the layers into
number of sub-layers of thickness 4m and 5m for
Rock-1 and Rock-2 respectively and assigning eachlayer a G 0 computed as per the above power law.

582

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 7 De-Convoluted Ground Motion H1 (RL
550m)

De-convolution was performed using the
program Proshake considering the two provided
horizontal components (H1 and H2) of the design
earthquake.
The outcrop earthquake signals used are shownin Figures 5 and 6, while the de-convoluted motions
obtained through site response analyses at the baselevel of the model are shown in Figs 7 and 8.
Outcrop Motion
Rock-1
G0: 2400 MPa

RL: 880m(Rock head level)
RL: 743m

Rock-2

G/Go - Fig 2

G0: 3240 MPa

Material Damping - Fig 3

De-convoluted Motion

Fig. 8 De-Convoluted Ground Motion H2 (RL
550m)

RL: 550m (Base of Model)

These analyses indicated that there was asignificant reduction in the amplitude of the deconvoluted ground motion signal. Given thepotential influence on the measured earthquake
induced stresses, strains and displacements, avalidation process to convolute the base motion
signals was undertaken using PLAXIS to compare
and assess the ground motion signal recovered at therock outcrop level.

Fig. 4 Ground Model

CONVOLUTION USING PLAXISIn these analyses, the de-convoluted A-T signals
were applied on a prescribed displacement boundary
at the base of PLAXIS model. The ground model
was constructed with the two rock layers and theanalyses were performed using the HSS constitutive
model with modulus reduction and material damping
as discussed above. The convoluted A-T signals
measured at the top of the model were thencompared with the design outcrop earthquake
motions shown in Figures 5 and 6. These details are
given in Figures 9 and 10.

Fig. 5 Outcrop Earthquake Ground Motion H1

Fig. 6 Outcrop Earthquake Ground Motion H2

Fig. 9 Comparison of Earthquake Motion H1(Outcrop Motion)

583

GEOMATE-Nagoya, Nov.13-15, 2013and material damping functions as per the PLAXIS
and Proshake models were adopted, except in ERLS,
where the cutoff modulus G ur and damping could
not be incorporated. The functions employed in
ERLS are shown in Figures 13 and 14.

Fig. 10 Comparison of Earthquake Motion H2(Outcrop Motion)
Convoluted A-T signals obtained through above
analyses show reasonably close agreement with thedesign outcrop signals. To further verify the process,acceleration response spectra of the convoluted andoutcrop earthquake ground motions were compared
and are shown in Figures 11 and 12. These functions
show close agreement, providing a high level ofconfidence in the site response process and the use
the de-convoluted A-T signals for assessment ofother earthquake induced parameters using PLAXIS.

Fig. 13 Implemented G/G 0 Functions

Fig. 14 Implemented Material Damping
Computed A-T signals are shown in Figures 15
and 16 along with the design outcrop earthquake
motion for comparison. The results indicate good
agreement in spite of the varying mathematicalformulations used.
Fig. 11 Response Spectra Earthquake Motion H1

Fig.15 Quake/W Convoluted Earthquake Motion H2

Fig. 12 Response Spectra Earthquake Motion H2
COMPARISON WITH OTHER PROGRAMS
The study was extended to compare deconvoluted A-T signals from other programs such as
Quake/W and ERLS. For these assessments, the deconvoluted A-T signals from Proshake were used as
input ground motions. Shear modulus degradation

Fig. 16 ERLS Convoluted Earthquake Motion H2584

GEOMATE-Nagoya, Nov.13-15, 2013[2] Geo-Slope international Ltd, “Dynamic
modeling with Quake/W – an engineering
methodology” 2012.
[3] PLAXIS, “Material Model Manual” 2012.
[4] Coffey Partners International Pty Ltd,
“Earthquake response of layered soils – User
guide” 1991.
[5] Seed HB, and Idriss IM. “Soil moduli anddamping factors for dynamic response analyses”
1970, Report No. EERC 70-10, Earthquake
Engineering Research Center, University ofCalifornia, Berkeley.
[6] Schanz T, Vermeer PA, Bonnier PG, “Thehardening soil model: Formulation andverification” in proc. Beyond 2000 incomputational geotechnics, 1999, Balkema,
Rotterdam, pp. 281-290.
[7] EduPro Civil Systems, “Proshake user’s manual
version 1.1”, 2005.
[8] Santos JA, Correia AG, “reference thresholdshear strain of soil” in 15th International
Conferenceon
Soil
Mechanics
andGeotechnical Engineering, 2001, Istanbul
Turkey, vol. 1, pp. 267-270.
[9] Hardin BO, Drnevich VP, “Shear modulus anddamping in soil” Proc. ASCE: Journal of theSoil Mechanics and foundation Division, 1972,
98(SM7), pp. 667-692.
[10] Schnabel PB, Lysmer J, and Seed HB “SHAKE:
A computer program for earthquake response
analysis of horizontally layered sites” Report
No. EERC 72-12, Earthquake Engineering
Research Center, University of California,
Berkeley, California 1972.
[11] Brinkgreve RBJ, Kappert MH, Bonnier PG,“hysteretic damping in a small-strain stiffness
model” in Proc. NUMCOG X, pp. 737-742.
[12] Seed HB, Wong RT, Idriss IM, and Tokimatsu
K “Moduli and damping factors for dynamic
analyses of cohesionless soils” Journal of
Geotechnical Engineering, ASCE, 1986, Vol.
112, No. 11, pp. 1016-1032.
[13] Kokoshu T, “Cyclic triaxial test of dynamic soil
properties for wide strain range”, Soils andFoundations, 1980,Vol. 20, No. 2, pp. 45-60[14] Dobry R, and Vucetic M, “Dynamic properties
and seismic response of soft clay deposits”,
Proceedings, International Symposium on
Geotechnical Engineering of Soft Soils, 1987,
Mexico City, Vol. 2, pp. 51-87.

CONCLUSION
This study highlights the relevance of site
response analysis in earthquake engineering
assessments. As input of an earthquake motion into
PLAXIS is generally achieved through a prescribed
displacement boundary at the base of the model, it isimperative that a suitable site response analysis isundertaken to arrive at an appropriate input signal.
Depending on the available design or target
earthquake signals, they may have to be either deconvoluted or convoluted to arrive at input
earthquake ground motions.
Few commercially available site response
programs can perform de-convolution of signals; but
all have the capability to convolute the signals to thesurface and within layers at higher elevations.
Except for PLAXIS and Quake/W, the others
programs considered herein are 1-D programs andare suited for horizontally layered strata. PLAXIS
and Quake/W are multi-faceted and their site
response capability is only a secondary module. As aresult they involve more computation time andrequire more storage capacity. For this study,
Proshake was used successfully to perform deconvolution of earthquake ground motion signals to
obtain input signals for PLAXIS and arrive at PeakGround Acceleration parameters in the upper soil
layers for pseudo static and liquefaction
susceptibility analyses.
It is important that, when two different
programs are used (i.e. one to obtain input
earthquake signal and the other to obtain earthquake
induced displacement) care should be taken to
ensure that material models and functions adopted
are compatible and that the target earthquake signal
is recovered at designated levels in the subsequent
analysis.
From the comparative A-T plots presented, it isevident that PLAXIS, Proshake, Quake/W and
ERLS are remarkably close, considering that thesepackages are based on different theoreticalformulations. Whilst there are some differences, it ishard to identify any one formulation being moreaccurate than the others.
REFERENCES[1] Kramer
SL“Geotechnical
Earthquake
Engineering” Prentice Hall, Upper Saddle
River, New Jersey, 1996.

585

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

A STUDY OF THE PARAMETERS AFFECTING THE
PERFORMANCE OF ROADS UNDER AN EXTREME RAINFALL
EVENT
Helen Fairweather and John Yeaman
Faculty of Science, Health, Education & Engineering, the University of the Sunshine Coast, Australia
ABSTRACT
Sunshine Coast Regional Council has recently upgraded a section of Sippy Downs Drive adjacent to the
University of the Sunshine Coast campus. Prior to opening, the pavement was instrumented to monitor strain
and moisture in the surface and the subgrade layers and the temperature under the surface layer. At the time of
installation, traffic was light, as University classes had not yet commenced. Traffic increased when classes
commenced in February 2013 and is projected to grow substantially as a new suburb and two major shopping
centres are built over the next three years. Data are recorded every minute and downloaded by mobile phone
connection every 24 hours. These data are analysed automatically every day. Six weeks after opening, a major
rainfall event occurred with nearly 500mm of rain recorded over three days. The paper discusses the impact onpavement strain as a function of changing moisture content and temperatures. These data have potential for
identifying future maintenance requirements.
Keywords: Pavement Monitoring, Subgrade, Asphalt Pavements

Engineers with the Sunshine Coast Council
agreed that the Sippy Downs road works provided asuitable site to install instrumentation to assess
pavement
performanceparametersunder
operational conditions. An additional advantage of
the Sippy Downs site is that it will be under the
influence of increasing traffic (volumes and loads)
over the next five to ten years.
This report is limited to an analysis of data
received from the instruments at the site between
the 24th and 28th January 2013 during a cyclonic
rainfall depression.
The configuration of the instruments also fits inwith the research being undertaken by a Higher
Degree (by research) student whose study is“Intelligent Highway Engineering and Maintenance
Optimisation”. Therefore the data being collected
will be utilised by this student over the next three
years. It is anticipated that further final year
undergraduate engineering projects will also be
possible using this site over the coming years.

INTRODUCTION
The Sunshine Coast Council undertook an
upgrading of Sippy Downs Drive adjacent to the
University of the Sunshine Coast (USC) during
2012. The road works included a duplication of thecarriageway, the installation of traffic lights at themain entrance to the University, an upgrade of thesecondary entrance and street scaping including
drainage incorporating Water Sensitive Urban
Design (WSUD) installations.
The purpose of the road works was not only toprovide improved access to the university for theever burgeoning student population but also tocater for future traffic demands of the growing
Sippy Downs Township. This township includes aplanned new suburb of 50,000 residents and two
major shopping malls.
During late 2011, Engineering at USC wasseeking projects for students completing their final
year in Civil Engineering. These major projects areequivalent to a 0.5 study load conducted over a full
year. The projects are designed to test the student’s
knowledge gained over the previous three years ofstudy. In addition the project thesis should be as
demanding as a Science Honours Thesis, which is
conducted over a full year.

EXPERIMENTAL DESIGNThe first undergraduate engineering student
working on this project in 2013 was tasked withsourcing preferred equipment and arranging its

586

GEOMATE-Nagoya, Nov.13-15, 2013

installation into the pavement. The aim of themonitoring is to determine the pavement
performance as a function of strain and moisturemeasured at two locations (bottom of the boundlayer and top of the subgrade layer) and pavement
temperature underneath the bound layer.
The instrumentation and road works werecompleted in December 2012 and monitoring
commenced on the 19th December. Over theAustralia day long weekend (25th to 28th January2013) a cyclonic rainfall depression passed throughSippy Downs with total rainfall over the period of
three days of nearly 500mm. During this period themonitoring station remained operational andcontinued to provide details of the strain, moistureand temperature every minute.

Test Site

Fig. 1 Test site location, Sippy Downs Drive,
Queensland.
The test site is on the upstream direction fromthe traffic lights at the intersection and in the outerwheel path of the median lane.
It is nowrecognised that this may not be the optimum
position as the traffic is relatively fast moving. In
addition the surface layer of this lane may not be
fully compacted due to the closeness of the kerb
and concern of the roller operator that damage may
occur to the gauges.
From observations, this lane receives the least
traffic except in peak periods such as start andfinish times at the adjacent school and university.
In hind-site the optimal position would be where
the traffic is slower moving and is generally
concentrated.
Notwithstanding
the
above
limitations,
measurements being taken every minute of every
day provide considerable data for analyses. Data
are being streamed to the writers’ desks on a daily
basis, with updated data being streamed every threeminutes for strain and moisture content andtemperature.

STUDY BACKGROUND
The objective of this study is to understand the
behaviour of a newly constructed section of roadunder extreme weather conditions. Achieving thisobjective will provide the basis to use this studysite to further investigate pavement behaviour
under real traffic conditions.
Traditionally pavement performance has beentested using Accelerated Pavement Testing (APT)
facilities. These facilities generally include a heavy
vehicle simulator [1]-[2].
Instrumentation of pavements in-situ is arelatively new advancement, but has mostly been
limited to a localised and short-term installation [3].
These authors are developing a smart monitoring
system using a ‘pebble’ sized strain sensor. The
size of this sensor and the development of a reliablelong-term energy supply will eventually allow a
multitude of these sensors to be installed during
construction [3]. However, to date, it appears that
this system has only been installed in a test facility.

Monitoring Equipment and Placement

MONITORING THE TEST SITE

The configuration of the instrumentation anddata logger are described below with the indicateddepths all measured from the top of the asphalt.
The centres of the strain gauges are at depths of
115mm and 395mm in the surface and subgrade
layers, respectively. The moisture content gauges
are placed at the bottom of the surface andsubgrade layers at depths of 395mm and 670mm,
respectively. The temperature sensor is installed in
the surface layer at a depth of 70mm.

The pavement under test is part of a major
upgrading of Sippy Downs Drive (Fig. 1). During
the construction it was decided to instrument thepavement so that the parameters affecting
pavement performance could be monitoredcontinuously.

587

GEOMATE-Nagoya, Nov.13-15, 2013

LOGGING AND CALIBRATING THE DATA
Data logger
Equilibrium Moisture Content
The key to the data collection facility is the datalogger. For this installation a dataTaker DT82EM
Series 3 Data Logger was chosen as it has several
desirable features; ultra-low power design,integrated cellular modem, automatic data transfer
to email or FTP, support for up to 10 SDI-12
sensors, and can house up to 6 (30V) sensor units.
The software associated with this equipment
provides a continuous and visual data feed. The
logger is configured so that each morning theprevious day’s data is emailed direct to theresearcher’s computer. This process has enabledreal time processing of the 1400 lines of data from
5 transducers, with the ability to upgrade to moretransducers as deemed necessary.

From the 19th December 2012 through to the
23 January 2013 (43 days) a period of stable hot
and dry weather conditions dominated. The
readings (at one minute intervals) for this period
were analysed to determine if this stability
translated to a stable moisture content measured ineach of the layers.
The optimum moisture content for each of theunbound component materials is 8.6% [4]. The
moisture content measured over the 43 day hot anddry period is considered to provide the equilibrium
state. The average moisture content over this period
was 15% and 18% from the surface layer andsubgrade layers, respectively. An analysis of the6300 moisture contents measured during the hot
and dry period indicated reasonable consistency as
the baseline for detecting changes in moisture
content with time (Table I).
rdStrain transducer KM 5000
The KM series strain transducers are designed
to measure strain in materials such as concrete andpavement layers. Their extremely low modulus
�40

N

mm2

Table I

� and waterproof construction make them

Equilibrium moisture contents

Layer
Surface
Subgrade

ideal for this type of test.
The built inthermocouple sensor in the surface layer measurestemperature in addition to strain. Both strain gauges
were embedded in the pavement vertically.
The installation of the strain gauges wasaccording to the manufacturers’ convention. For
vertical installation, the manufacturer advised
positive strain (+ve) indicates values incompression and negative values (-ve) indicatesvalue in tension.

Mean
15.5%
18.5%

Std Dev
0.69%
0.51%

C of V
4.4%
2.8%

Calibration of Strain Data
In an attempt to relate the strain measurements
to axle loads, a calibration exercise was undertakenon the 6th March 2013. The Sunshine Coast Council
provided a single axle, dual tyre truck loaded with
8.2 tonnes on the rear axle. Tyres were inflated to760 KPa. This unit made 10 passes over the testsite between the hours of 9:30AM and 10:30AM
and again between the hours of 1:30PM and
2:04PM. These times were chosen as this is when
the pavement appears to be generally at the medianof the temperature regime. The strains, moisture
contents and temperature were recorded for eachpass (Table II).
Considering only the ‘TEST TRUCK’ results
shown in Table II, the temperature in the morning
test run increased from 27 to 28oC. During thistime the strain in the surface layer varied from -23
to -30µε for a moisture content stabilised at ~18.1%.
For these runs, the strain in the subgrade layer
varied from -4 to -9µε for a relatively steadymoisture content of ~18.74%.

Soil moisture content sensor
For this study the Theta probe ML2X waschosen as the preferred instrument for measuringmoisture. The measurement accuracy of this probe
is quoted at ±1% with a measurement range of up
to 50% volumetric moisture content. This
capability was considered ideal for this study.
Power source
The whole system is powered by a 13.5 longlife battery charged by a solar panel; Steca Solsum
Range - 6.6F, Solar Charge Regulators, 12/ 24 V,
load current 6A, with LVD 1 Solarwatt Solarpanels rated at 40W.

588

GEOMATE-Nagoya, Nov.13-15, 2013

and these results are recorded in Table II forinterest. The very large strains recorded when the
TEST TRUCK was parked on the test site for 3
minutes (-971 and -305µε in the surface andsubgrade layers, respectively) indicates the impactof this static load is greater in the surface, though
the change in the subgrade layer is substantial.

For the afternoon runs, and again considering
only the ‘TEST TRUCK’ results in Table II, thesurface temperature increased from 33.7 to 34.4oC.
The corresponding surface layer strain increased
from -81 to -84µε (tension), while the moisture
content remained steady at ~18.03%. In thesubgrade layer the strain ranged from -51 to -54µε,
for a moisture content steady at 18.79%.
During the calibration test two other heavy
different vehicles drove over the instrumentation
Table II

Calibration data collected on the 6th March 2013 using a vehicle with a known load (TEST TRUCK)
Surface layer

Subgrade layer
Strain(µε)

TimeStrain(µε)

Moisture(%)

Temperature(oC)

9:48:00

-24

18.1

27.0

10:06:23

-27

18.2

27.6

-4

18.76

TEST TRUCK

10:14:25

-55

18.1

27.8

-23

18.74

Truck with Excavator

10:17:32

-35

18.1

27.8

-9

18.74

TEST TRUCK

10:23:25

-23

18.1

28

-7

18.74

TEST TRUCK

10:30:30

-57

18.1

28.1

-20

18.74

Bus followed by TEST TRUCK

13:30 to 13:33

-971

18.03

33.5

-305

18.79

TEST TRUCK parked on site for3 minutes

13:36:33

-84

18.03

33.7

-53

18.79

TEST TRUCK

13:43:24

-82

18.03

33.9

-51

18.79

TEST TRUCK

14:03:38

-81

18.04

34.4

-54

18.79

TEST TRUCKMoisture(%)

Remarks
TEST TRUCK

Table III Rainfall at Sippy Downs during thecyclonic depression in January 2013

EXTREME WEATHER EVENT RESULTS
AND DISCUSSION
Australia Day Weekend, 2013
Between commissioning of the equipment on
the 19th December 2012 and 24th January 2013, a
period of high temperatures and zero rainfall was
experienced at the site. During this period thestreetscape planting of grasses, trees and shrubs
was watered manually.
Rainfall

Day

Date

Rainfall(mm)Thursday

24th

42

Friday25th

52

Saturday

26th

92

Sunday27th

198

Mondayth

95

28

Moisture content

From the 25th to 28th January a cyclonic
depression passed over the site with high winds andlarge rainfall amounts recorded (Table III). Overthe five days the total rainfall recorded was 479mm.

In the surface layer the moisture content was
stable, fluctuating between 16.5 to 17% on the 24thand 25th January. The moisture content rose
rapidly from 5:00PM on the 26th January to a589

GEOMATE-Nagoya, Nov.13-15, 2013

maximum of 20% at 4:30PM on the 28th and fallingto 18.3% by 9:00AM on the 29th January (Fig. 3).
Similarly, the subgrade layer had a stablemoisture content fluctuating between 17.8 to 17.9%
between the 23rd and 25th January. The moisture
content in the subgrade layer rose steadily fromabout 2:00PM on the 27th January to a maximum of
19.6% at 3:00PM on the same day (Fig. 4).

Critical Strains
During this cyclonic event the surface layer
strain moved from compression to tension on the
25th January. The surface layer strain returned tocompression on the 31st January (after the extropical cyclone event).
At the time of the above surface layer strainchanges, the subgrade strain moved fromcompression to tension with a maximum tensile
strain of around 60µε on the 29th January. Subgradestrain showed signs of recovery by the 30th January
after which no further rainfall was recorded (Fig. 4).

Fig. 2 Surface layer moisture contents recorded
over the period 24th to 29th January 2013.

Fig. 4 Surface layer strain (SL STRAIN, blue
diamond and line) and temperature (SLTEMPERATURE, green triangle and line) andsubgrade strain (SB STRAIN, red square and line)
measurements.
Strain and moisture content relationships
There is reasonable correlation between surface
layer strains and change in moisture (R2=0.31), at aconstant temperature. The surface layer strains
increase in tension with increasing moisture content,
when both variables are averaged over a constanttemperature (Fig. 5).
The correlation between the strain and moisturein the subgrade layer is slightly higher (R2=0.58),
with the strain increasing in tension as moisture
content rises (Fig. 5). Again a constant temperatureis used to average strain and moisture content.
There is good correlation (R2=0.73) between thestrain in the subgrade layer and the surface layer
moisture (both averaged over constant temperature).
The strain in the subgrade layer increases in tension
as surface layer moisture content increases (figure
not shown).

Fig. 3 Subgrade layer moisture contents recorded
over the period 24th to 29th January 2013.
Temperature
The temperature of the surface layer varied
from a minimum of 35ºC at 9:00AM and maximumof 51ºC at 4:30PM on the 24th January. From the26th to the 29th January the temperature remained
relatively constant fluctuating between 27ºC and
29ºC (data not shown).
Surface layer temperatures averaged ~42°C
prior to the event. However, during the event the
average dropped to ~25°C. The temperature
returned to the pre-event average on the
29th January. This behaviour prompted a further
evaluation of the respective influence oftemperature and moisture on the critical strains.

590

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 5 Strain as a function of moisture content (averaged over constant temperatures) for surface and subgrade
layers.
correlation was observed between the strain andmoisture in the subgrade layer.
Further research will develop methods to utilise
these data to more precisely predict pavement
failure and therefore better target road maintenance.

Strain and temperature relationships
There is a strong relationship between surface
layer strain and temperature (R2=0.85), with strain
becoming increasingly positive with increasing
temperature. At temperatures above ~32ºC thestrain switches from tension (-ve) to compression(+ve) (Fig. 4).
The relationship between the strain in thesubgrade layer and surface layer temperature is notstrong (R2 = 0.20).

REFERENCES[1] Chen D, Zhou F, Cortez E "Determination ofload damage relationships throughAccelerated Pavement Testing", Jof Testing and Evaluation, ASTM, Vol. 34, Jul.
2006, pp. 312-318.
[2] Chen T, Chang J Chen D, “Applying data
mining technique to compute LDE for rutting
through full scale Accelerated Pavement
Testing”, Road Materials and Pavement
Design, Vol. 9. 2, 2008, pp. 227-246.
[3] Lajnef N, Rhimi M, Chatti K, Mhamdi L and
Faridazar F, “Toward an integrated smart
sensing system and data interpretation
techniques for pavement fatigue monitoring”,
Computer-Aided Civil and Infrastructure
Engineering, Vol. 26, 2011, pp. 513–523.

CONCLUSIONS
An extreme weather event over a four-day
period provided an opportunity to assess thepotential damaging effect to a roadway fromknown critical damage determinants. These
determinants are tensile strains at the underside of
the bound pavement and compressive strains on thesubgrade.
The collected data showed that in the surface
layer the temperature is a key determinant ofpavement performance. The strains in the subgrade
layer were seen to be predominately in tension
irrespective of surface layer temperature.
There is only a small correlation between
surface layer strain and moisture. A stronger[4] Cardno Bowler, Density and moisture ratio test
results, “Unpulished”, Report Number
3747/R/2157-1, 2012.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECT OF STIFFNESS OF LOAD-BEARING LAYER ON RESISTANCE
CHARACTERISTICS AT PILE TOE OF STEEL PIPE PILE ON THIN LAYER
1,2

Kazuhiro Oda1, Shuhei Takegawa2
Graduate School of Engineering, Osaka University, Japan

ABSTRACT
It has been known that the sufficiently stiff layer can be considered as a load-bearing layer of piles, even if its
thickness is thin. The authors have studied the toe bearing resistance of pile on a thin load-bearing layer, in orderto establish the design method about pile on a thin load-bearing layer. In this paper, the effect of stiffness ofload-bearing layer on characteristics of toe resistance of steel pipe pile on a thin load-bearing layer is discussed
through a series of numerical simulations. First, a field loading test of steel pipe piles with a concrete bulb on athin load-bearing layer is reproduced through the numerical simulations, in which a soil-water coupled with anelast-plastic finite element method is applied, to confirm the availability of the numerical analysis proposed.
Second, a series of numerical simulations are carried out in which the deformation modulus of the load-bearing
layer is chosen as a variable parameter. The results of the numerical simulations show that the stiffness of loadbearing layer does not remarkably affect the resistance when the yielding of load-bearing layer occurs.
Keywords: Steel pipe pile, stiffness of load-bearing layer, Load-bearing resistance at the pile toe, Thin load-bearing layer,
Numerical simulation

the load-bearing layer is chosen as a variable
parameter. The effect of stiffness of load-bearing
layer on characteristics of toe bearing resistance of
pile on a thin load-bearing layer is discussed byfocusing on both the relationship resistance anddisplacement at pile toe and the development oflocal failure in the bearing ground.

INTRODUCTION
Most big cities in Japan have been constructedon Holocene plains. In general, such plains arecomposed of sand or sandy gravel layers and thickclay layers what accumulated alternatively. A stiff
and thick layer which can be considered as loadbearing layer for piles could not be found in manycases. In particular, it has become more difficult tofind a sufficiently stiff and thick load-bearing layer
because a large number of pile foundations withlarge diameters have been constructed recently.
The appropriate estimation of toe bearing
resistance of pile on a thin load-bearing layer cangive the economical advantage for construction ofpile foundations. The authors have studied thecharacteristics of toe bearing resistance of pile on athin load-bearing layer in order to establish thedesign method about pile on a thin load-bearing
layer. It is elucidated that the toe bearing resistanceof pile on a thin load-bearing layer is affectedsignificantly by the thickness of load-bearing layer
in the case where it is less than 3 times pile diameter.
Also, the yielding of thin load-bearing layer must be
dominated by the punching shear failure [1], [2], [3].
In this paper, the effect of stiffness of loadbearing layer on the characteristics of toe resistanceof pile on a thin load-bearing layer is elucidated
through a series of numerical analyses. First, a fieldloading test of steel pipe piles with a concrete bulb
on a thin load-bearing layer is reproduced throughnumerical simulations, in which a soil-water coupledwith an elasto-plastic finite element method isapplied. Second, a series of numerical simulations
are carried out in which the deformation modulus of

TEST PILE AND FIELD LOADING TEST
Figure 1 shows the configuration of the
instruments that were used to measure thedisplacement of pile with a concrete bulb, thedisplacements of bearing ground below the concretebulb, and the axial force [4]. As shown in Fig.1 (a), a
standard penetration test (SPT) was carried out toinvestigate the ground conditions at the southeast
part of the Osaka Bay area. Based on the results of
the SPT, it was found that the ground is composed ofalternate layers of clay and sand or sandy gravel.
The sand layers that show an N-value of more than
50 in the SPT were found to have a thickness of lessthan 2 m, which indicates that no clear load-bearing
layer is available.
The tested pile was a steel pipe that is 34 m inlength and 1 m in diameter, with a concrete bulb thatis 1 m in length and 1 m in diameter. The length ofthe embedded part of the pile is about 27.9 m. The
pile was born on a sand layer that is 0.9 m thick,which is underlain by a stiff clay layer. First, the pile
was installed by a combination of inner excavationand penetration into the ground, until the pile toereached the bearing ground. Second, the groundbelow the pile toe was excavated and a cavity wascreated in the bearing ground. Third, a cement mix
592

GEOMATE-Nagoya, Nov.13-15, 2013

pile

2m
Concrete
bulb

Sand
layer

0.9 m
2m
3m

Clay
layer

*) Symbols denote themeasuring instruments
and correspond to those in
Figures 5 and 6.

a) Strain gauges aroundpile shaft, load cell,and displacementgaugesb) Wire-type displacementgauges in the groundFig.1 Configuration of instruments used tomeasure the displacement of pile withconcrete bulb, the displacements of the
bearing ground below the concrete bulb,
and the axial force
with high pressure of about 20 MPa was injected
into the cavity, creating a concrete bulb below thepile toe.
The load and displacement at the pile head were
measured by a load cell and a displacement gauge. A
displacement gauge was also set up at the pile toe.
The displacements of the concrete bulb and thebearing ground below the concrete bulb were
measured by wire-type displacement gauges. Strain
gauges were also set up around the pile shaft. The
axial force, which is denoted by symbols, wascalculated from the measured strain. The axial force,
which was calculated from the measurements of thestrain gauges closest to the pile toe, was defined as
the pile toe load.

Fig.2 Analytical model
failure threshold of the model. When the stresses didreach the failure threshold, the constitutive model ofsandy soils was replaced with the Drucker-Prager
model. For clayey soils, an elasto-plastic model
proposed by Matsui and Abe [6] was used. When the
stresses reached the failure threshold of the elastoplastic model, the constitutive model of clayey soils
was replaced with the von Mises model. A joint
element proposed by Goodman et al. [7] was used torepresent the discontinuity between pile and soil.
The soil parameters used in the numericalsimulation were determined from data from soil
investigations that included the SPT and unconfinedcompression test. Few parameters were reasonably
rearranged to fit the results of the numericalsimulation to the field measurements.

ANALYTICAL MODEL
A soil-water coupled elasto-plastic finite element
method with an axisymmetric condition was used in
the numerical simulation. Figure 2 and Table 1 show
the analytical model and the values of the soil
parameters used in the simulation, respectively. The
soils were fundamentally modeled as elasto-plastic
materials to realistically reproduce the complicatedbehavior of the ground. The steel pipe pile and theconcrete bulb were modeled as being composed ofelastic materials. For almost all sandy soils, the tijsand model, which was proposed by Nakai [5], wasused, provided that soil stresses did not reach the

RELIABILITY OF NUMERICAL ANALYSIS
Figure 3 shows the relationship between theapplied load and the displacement at the pile head.
In the analytical relationship between the applied
load and displacement, the slope of the analytical

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GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Values of soil parameters used in the analysis
Division

Model

Parameters

S1
S2
S3
S4
C1
C2
S5
S6
C3
S7
C4
S8
S9
S10
C5
S11
C6
C7
S12
C8
S13
C9
S14
C10

Elasticity
Elasticity 2
Elasticity 3
Elasticity 4
Elasticity 5
Elasticity 6
Elasticity 7
Elasticity 8
Matsui-Abe modeltij-sand modelMatsui-Abe modeltij-sand modeltij-sand modeltij-sand modelMatsui-Abe modeltij-sand modelMatsui-Abe modelMatsui-Abe modeltij-sand model 6
Matsui-Abe modeltij-sand modelMatsui-Abe modeltij-sand modelMatsui-Abe model

E = 18.9 MPa, ν = 0.2
E = 37.8 MPa, ν = 0.2
E = 72.5 MPa, ν = 0.2
E = 15.8 MPa, ν = 0.2
E = 18.9 MPa, ν = 0.2
E = 25.2 MPa, ν = 0.2
E = 31.5 MPa, ν = 0.2
E = 72.5 MPa, ν = 0.2
λ = 0.0360, κ = 0.00899, M = 1.635, ν = 1/3, ηk0 = 0.75
Ct = 8.77 × 10-3, Ce = 6.20 × 10-3, m = 0.3, α = 0.90, Re = 5.83, D f= -0.36, ν = 0.325
λ = 0.0450, κ = 0.00563, M = 1.551, ν =1/3, ηk0 = 0.75
Ct = 1.90 × 10-2, Ce = 1.35 × 10-2, m = 0.3, α = 0.85, Re = 4.49, Df = -0.3, ν = 0.325
Ct = 5.93 × 10-2, Ce = 4.19 × 10-2, m = 0.3, α = 0.65, Re = 3.36, Df = -0.15, ν = 0.325
Ct = 2.56 × 10-2, Ce = 1.48 × 10-2, m = 0.3, α = 0.85, Re = 4.56, Df = -0.20, ν = 0.325
λ = 0.0257, κ = 0.00642, M = 1.551, ν = 1/3, ηk0 = 0.75
Ct = 6.43 × 10-2, Ce = 3.71 × 10-2, m = 0.3, α = 0.55, Re = 2.49, Df = -0.15, ν = 0.325
λ = 0.0692, κ = 0.0173, M = 1.179, ν = 1/3, ηk0 = 0.75
λ = 0.0309, κ = 0.00773, M = 1.551, ν = 1/3, ηk0 = 0.75
Ct = 4.80 × 10-2, Ce = 2.77 × 10-2, m = 0.3, α = 0.75, Re = 3.89, Df = -0.18, ν = 0.325
λ = 0.0592, κ = 0.0148, M = 1.221, ν = 1/3, ηk0 = 0.75
Ct = 5.99 × 10-2, Ce = 4.14 × 10-2, m = 0.3, α = 0.80, Re = 4.02, Df = -0.20, ν = 0.325
λ = 0.1021, κ = 0.00681, M = 1.551, ν = 1/3, ηk0 = 0.75
Ce = 4.94 × 10-2, m = 0.3, α = 0.90, Re = 4.60, Df = -0.45, ν = 0.325
λ = 0.247, κ = 0.0124, M = 1.418, ν = 1/3, ηk0 = 0.75

curve changes at about 3 MN of the applied load at
the pile head. Then, the slope of analytical curve
becomes gradually steeper with an increase in theapplied load at the pile head. Finally, the analyticaldisplacement of the pile head significantly increases
at an applied load of about 4.8 MN. It is consideredthat the resistance of the pile head at this load levelis closer to the ultimate bearing resistance of the test
pile.
Figure 4 shows the relationship between theresistance and displacement at the pile toe. The slopeof the analytical curve hardly changes up to a

resistance of about 1.8 MN. The analyticaldisplacement then significantly increases at a load
level of about 1.8 MN. It is found that the yield of
the resistance and displacement behavior at the pile
toe occurs at this load level.
Figure 5 shows the axial force distribution of thetest pile. The numerical simulation reasonably
reproduces the friction behavior around the pile
shaft.
Figure 6 shows the relationship between theresistance at the pile toe and the displacements in theunderlying bearing ground, in addition to that of the

Applied load at pile head (MN)
2

4Resistance at pile toe (MN)
60

Displacement at pile toe (mm)Displacement at pile head (mm)

0

30

60

90
Data points : Measured
Solid curve : Analytical

0.0
0

0.5

1.0

1.5

2.0

30

60

90
Data points : Measured
Solid curve : Analytical

120

120

Fig.4 Relationship between resistance anddisplacement at pile toe

Fig.3 Relationship between applied load anddisplacement at pile head
594

2.5

GEOMATE-Nagoya, Nov.13-15, 2013concrete bulb. The analytical relationship between
the resistance and displacement, which is indicatedby a solid circle at the toe of the concrete bulb,
agrees closely with that which is indicated by an
empty circle at the inner concrete bulb, indicatingthat the concrete bulb acts in coordination with thesteel pipe piles. In addition, it is considered that
failure of the concrete bulb did not occur. It should
be noted that the displacement at a point 1 m below
the toe of the concrete bulb, i.e., at the bottom of thesand layer, which is denoted by an open rhombus,
increases more significantly than that at the point 2
m below the toe, which is denoted by a solid
triangle, as the resistance and displacement
behaviors at the pile toe begin to yield.
As shown in Figures 3, 4, 5 and 6, the agreement
between the measured and analytical results is good,thus confirming that the numerical simulation
realistically reproduces the bearing behavior of thepile and the foundation behavior of the groundaround the pile toe in the field loading test [2].
Figure 7 shows the analytical results of thedeformation of the bearing ground below theconcrete bulb in the final stage of loading. The
bearing ground behaves as if the pile might punchthrough the thin load-bearing layer. In particular, thefinite elements of the thin load-bearing layer directly
below the perimeter of the concrete bulb deform as
if they were subject to simple shearing. Thissuggests that the punching shear failure occurs in the
bearing ground below the concrete bulb.

Axial force (MN)
0

0

2

4

6

Depth (m)10

20

Solid curves: Analytical
Data points: Measured

30

Fig.5 Axial force distribution of pile
Bearint resistance at pile toe (MN)

Displacements ofbearing ground (mm)

0.0
0

0.5

1.0

Steel
pipe

30

1.5

2.0

*) Symbolds
denotemeasuring
instruments

E
Sand

2m
Clay

60

J
0.9m

Sand

A
Clay

90

2m
3m

P
C

120

ANALYTICAL
STUDY

CASES

IN

PARAMETRIC

Fig.6 Relationship between resistance at pile toe
and displacement of the concrete bulb andunderlying bearing ground¢

Table 2 shows the analytical cases in theparametric study. In this paper, the stiffness of loadbearing layer could be considered as thecompressibility of sands or sandy gravels whichforms the load-bearing layer. C t , which is one of themost important parameters in tij-sand model, waschosen as variable parameter, in order to change thedeformation modulus of the load-bearing layer. C t ismechanical parameter for controlling the volumetriccompression behavior. The volumetric strain rate,εvol , can be defined by the following equation.

p ′Sand layer
Clay layerm −1

εvol = m C t p′

Concretebulb(1)where p′ is mean principal stress at the initialcondition and m is a material parameter. Also, thedot denotes the rate. On the other hand, thevolumetric strain rate in the elastic media is definedby the Eq.(2).
(2)εvol = Kp ′where K is bulk modulus. Also, K can be given by
the following equation.
E(3)
K=3(1 − 2ν)Fig.7 Analytical results of the deformation of bearing
ground around concrete bulb at the final stageof loading
Table 2. Analytical cases
Case
E1014
E830
E670

595

Deformation
Modulus1014 kgf/cm2
830 kgf/cm2
670 kgf/cm2

Ct
5.69×10-3
6.95×10-3
8.60×10-3

GEOMATE-Nagoya, Nov.13-15, 2013

where E is deformation modulus and ν is poisson’s
ratio. From Eq.(1), Eq.(2) and Eq.(3), E is given by(4)
E = 3(1 − 2ν)m C t p′m−1
Strictly speaking, 𝐸𝐸 does not imply the elastic
modulus in this paper.

Resistance at pile toe (MN)
Displacement at pile toe (cm)0.0

EFFECT OF STIFFNESS OF LOAD-BEARING
LAYER ON BEARING CHARACTERISTICS
AT PILE TOE
Figure 8 shows the relationship between
resistance and displacement at pile toe in the casewhere the thickness of the load-bearing layer isequal to 1.5m. The resistance at pile toe increases as
the deformation modulus of load-bearing layer isgreater at the same displacement before the yieldingof the relationship between resistance anddisplacement at pile toe occurs. In the case of E1014,
the yielding in relationship between resistance anddisplacement at pile toe occurs at toe displacementof about 4.0cm and at toe resistance of about 2.8MN.
Also, in the case of E830, the yielding in
relationship between resistance and displacement at

c/

1.0

2.0

E1014

2
E1014
E830
E670

4
6

E670

8

12
14
16

pile toe occurs at toe displacement of about 8.0cm
and at toe resistance of about 3.1MN. However, inthe case of E670, the yielding does not occur until
the displacement at pile toe reaches 10cm which isequal to 10% of the pile diameter. In general, the toe
resistance at the displacement of 10% of pile
diameter can be estimated as the ultimate bearingc/Concrete bulb
Load-bearing
layer
Clay
layer

c/

c/
Load-bearing
layer

E830

Clay
layer

c/

c/
Load-bearing
layer

E670

Clay
layer
4cm

E830

10

E1014

c/

4.0

Fig.8 Relationship between resistance anddisplacement at pile toe

c/

c/

3.0

0

8cm

12cm

Displacement
at pile toe

Fig.9 Development of local failure in the bearing groundunderneath a concrete bulb
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GEOMATE-Nagoya, Nov.13-15, 2013

resistance in design method, in Japan. The yielding
occurs at the toe displacement of about 12cm and at
toe resistance of 3.3MN in the case of E670.Afterthe yielding occurs, the resistance at pile toe hardly
increase with the displacement in each analyticalcase. Also, the resistance at pile toe in each case isclosely agreed with those in the other cases at thedisplacement of 15cm.
Figure 9 shows the development of the local
failure in the bearing ground underneath a concretebulb. In figure 9, the zone in which the local failure
occurs is painted red. In E1014, the local failurezone surrounds the compressed zone underneath thetoe of concrete bulb in the load-bearing layer andreaches nearly the clay layer underlying the loadbearing layer at toe displacement of about 4cm. The
yielding of relationship between resistance anddisplacement at pile toe occurs at toe displacementof 4cm in E1014, as shown in Fig.8. It is, therefore,suggested that the punching shear failure, in which ahighly compacted core of soils is formed underneatha concrete bulb due to the installing the pile into theload-bearing layer, is the prevailing bearing
mechanism.
In E830, the local failure develops slowly than in
E1014. The local failure zone does not reach theclay layer underlying load-bearing layer at toe
displacement of about 4cm surrounding thecompressed zone underneath the toe of concrete bulb.
The failure zone in the bearing layer reaches nearly
the clay layer underlying at toe displacement of
about 8cm. At toe displacement of about 8cm, theoccurrence of yielding is confirmed as shown in
Fig.8. It is suggested that punching shear failure is
the prevailing bearing mechanism in E830, too.
In E670, the local failure zone surrounding thecompressed zone underneath the toe of concrete bulb
reach nearly the clay layer underlying at
displacement of 12cm.

2. The resistance at pile toe increases as the stiffnessof load-bearing layer is higher at the same level ofdisplacement before the yielding of relationshipbetween resistance and displacement at pile toe
occur.
3. The resistance at pile toe at the displacement of
10% of pile diameter might be not significantly
affected by the stiffness of load-bearing layer.
4. The punching shear failure is the prevailingbearing mechanism, regardless of the stiffness ofload-bearing layer.
ACKNOWLEDGEMENT
The authors would particularly like to thank theJapan Iron and Steel Federation for scholarship.
REFERENCES[1] Matsui, T., K. Oda, and M. Nakabatyashi, “Endbearing mechanism of bored pile on thin bearing
layer”, Proceedings of 9th Asian Regional
Conference on Soil Mechanics and Foundation
Engineering, Vol. 1, 1991, pp.251-254.
[2] Matsui, T., K. Oda, and M. Nakabayashi,“Deformation behavior of bored steel pipe piles withconcrete bulb on a thin bearing layer”, Proceedingsof the 4th International Offshore and Polar
Engineering Conference, 1994, pp.548-553.
[3] Takegawa, S., Oda, K., Ikefuji, Y., “Effect ofstrength of bored steel pile pipes with concrete bulb
on end bearing characteristics on a thin layer”, Proc.
47th annual meeting of J.G.S, 2012, pp. 1075-1076.
[4] Koike, M., F. Yasuda, T. Takasuga, and T.
Katayama, “Loading test of large-scale bored steel
pipe pile on a thin bearing layer”, Proc. 46th annual
meeting of J.S.C.E., 1991, pp. 828-829.
[5] Nakai, T. “An isotropic hardening elastoplastic
model for sand considering the stress pathdependency in three-dimensional stresses”, Soils &Foundations, (29), 1, 1989, 119-137.
[6] Matsui, T. and N. Abe. “Multi-dimensionalelasto-plastic consolidation analysis by finite
element method”, Soils & Foundations (21), 1, 1981,
79-95[7] Goodman, R.E., R.L. Taylor and T.L. Brekke,“A model for the mechanics of jointed rock”,
ASCESM3, 1968, 637-659

CONCLUSIONSIn this study, the effect of stiffness of loadbearing layer on bearing characteristics of a steel
pipe pile with concrete bulb on a thin load-bearing
layer was investigated through a series of numericalsimulations. The main conclusions are summarized
as follows.
1. The numerical analysis which was developed byauthors, realistically reproduces the bearing
behavior of the steel pipe pile with concrete bulb
on a thin load-bearing layer in a field loading test.

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hThird International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INFLUENCE OF SHEAR SPEED ON DIRECT SHEAR STRENGTHFOR COMPACTED BENTONITE WITH DIFFERENT SOIL SUCTIONS

1Tomoyoshi NISHMURA1 and Junichi KOSEKI2
Ashikaga Institute of Technology, Japan, 2Institute of Industrial Science, University of Tokyo

ABSTRACT
Geotechnical engineered barriers for isolating nuclear waste disposal at great depths are constructed ofcompacted bentonite. Hydraulic mechanism of bentonite is widely known to be affected by changes in watercontent or suction. Soil suction can be used for predicting shear strength of compacted bentonites. Direct shear
tests with different shear speed are presented to describe effect of hydraulic process of compacted bentonite.
Direct shear tests conducted with different shear speed to reach failure or stable residual conditions. Measured
direct shear strength related to soil suction and soil moisture. Shear strength of suction of 2.8 MPa decreased
with increasing shear speed. Also, compression curve of compacted bentonite was influenced due to change ofsoil suction (i.e. total suction). Soil suction is extended to incorporate the effect of external loading, creating a
shear resistance.
Keywords: Bentonite, Suction, Direct shear strength, Shear speed, Compression properties

Table 1
bentonite.

INTRODUCTION
Geotechnical engineered barriers used for
isolating nuclear waste disposal at great depth areconstructed of compacted bentonite. Hydraulicmechanism of bentonite is a widely known behavior
resulting from change in water content. Somegoverning parameters of compacted bentonite
properties are related via the soil-water characteristic
curve and therefore, soil suction can be used forprediction of shear strength of compacted bentonites.
It is well known that the use of suction as agoverning parameter introduces the presence of
hydraulic mechanism for compacted bentonite. For
compacted bentonite, a non-negligible quantity ofwater is strongly adsorbed on montmorillonite
minerals, and physical-chemical effects related tomontmorillonite-water molecular interactions areimportant.
Standard mechanical models arecompleted to account for the additional complexity
related to physical-chemical effects for heavily
compacted swelling soils (Cui et al., (1993), Cui etal., 2002).
Hydration-mechanism tests showed some
limitation of existing elasto-plastic models forcompacted bentonite with collapsible macro-pores
resulting from changes in soil suction, andestablished the concept of critical swelling curves.
The concept accounts for the couplings between
hydraulic and mechanism effects.
A new direct shear tests are presented that
included the effect of hydraulic process forcompacted bentonite. Direct shear strengths ofcompacted bentonite with different suction are
conducted with different shear speed to reach

Summary of chemical component for
SymbolPercentage %

SiO 2

69.7

TiO 2

0.14

Al 2 O 3

15.8

Fe 2 O 3

1.69

MgO

2.19

CaO

2.00

Na 2 O

2.04

K2O

0.24

failure or stable residual conditions. The shear
speed ranged from 0.004 mm per a minute to 0.5mm per a minute for a total horizontal displacementof 8 mm. Measured direct shear strengths haverelation with soil suction and soil moisture. In
addition, volumetric behavior of bentonite in
response to change in water content has effect on
shear properties.
TEST PROCEDURE
Soil materials
Sodium bentonite was used for this test program.
Silica sand was mixed into the bentonite at a ratio of
30 % by dry weight. The bentonite had chemicalcomponents shown in Table 1.
The soil specimen was statically compacted in
the shear box under a compression stress of 3.5 MPa
and had an initial water content of 5.9 %. The soil
specimen had a dry density of 1.6 g/cm3, a diameterof 6 cm and a height of 2.5 cm. Initial suction wasdetermined as 105 MPa using soil-water
598

GEOMATE-Nagoya, Nov.13-15, 2013

Ball bearing
Head of rod

Rod
Porous stone

Soil specimen
Lower shear box
FilterBasement

Fig. 2
Fig. 1

Relative humidity air circulation system.

2.8 MPa, compacted bentonite applied decreasing ofsuction under relative humidity of 98 %. Suction ofzero value in the compacted bentonite was produced
due to swell in de-aired water. The swelled
specimen in de-air water was prepared decreasing
suction as zero suction value, and it was remained aconstant initial height during soaking. The swelling
period was at least over than one month. After
swelling all specimen approached to saturation
condition, and suction of compacted bentonite
reduced from 105 MPa to zero value. Each sample
was loaded and unloaded the ranged from 20 kPa to1000 kPa.
Other hands, all specimens controlled of suction
were installed in the modified direct shear apparatus
as shown in Fig. 2 and a normal stress of 200 kPa
was loaded and consolidated to all specimens. It
was remained at least twenty four hours before a
direct shearing.
This testing program modified a conventional
direct shear apparatus to maintain constant suction
around specimen and that was performed two
different processes before shearing correspond toeach specimen. In case of compacted bentonite withsuction of 2.8 MPa, air circulation was flowed
through direct shear chamber using relative humidity
control system which was maintained at relative
humidity of 98 % as shown in Fig. 2. Potassium
sulfate was put in a container placed outsidechamber and a conventional pump circulated the air
at relative humidity of 98 % through the system.
The air in chamber of direct shear apparatus
maintained a constant suction that was predicted forthe surface of specimen at constant suction of 2.8
MPa. This air circulation system was similar to thesystem suggested by Blatz and Graham (2000) or
Nishimura and Fredlund (2003).
In case of saturated specimen, the de-aired water
was supplied in the chamber of direct shear
apparatus till water level approached upper surface

Direct shear box used in this test program.

characteristic curve obtained from vapor pressuretechnique with suction range from 2.8 MPa to 296
MPa (Nishimura et al. 2010).
The shear box was shown in Fig. 1. The shear
box consisted of upper box and lower box. Fiverings were placed between upper box and lower box
which were subjected to fluorination treatment forminimizing friction resistance. The shear box wasplaced in the chamber of modified direct shear
apparatus.
The specimens were subjected to two different
suction values of 2.8 MPa and zero (i.e. saturation
condition). Vapor pressure technique using K 2 SO 4
induced to suction of 2.8 MPa for compacted
bentonite. Reduction of suction from 105 MPa to
2.8 MPa caused expansion of upper surface ofcompacted bentonite.
This closely related todecreasing dry density and changing of macro-micro
structures (Wang, et al., 2012, Nowanmooz and
Masrouri (2012)). Nishimura et al. (2012) had
measured expansion of compacted bentonite, which
had a diameter of 2 cm and height of 1 cm. Applied
suction was lower than initial suction. Expansion of
volume change of the sample approached to 31.1 %.
Many cracks occurred on the surface of sample, andit can be predicted to change micro-macro structure
in compacted bentonite. More and more cracks wereobserved on the surface of sample with time and all
cracks advanced to significant depths.
This study performed compression test on
compacted bentonite with three different suctions inorder to understand compression properties. The
compacted bentonite had a diameter of 6 cm and aheight of 2.5 cm. Required suctions were 105 MPa,
2.8 MPa and zero value. The suction of 105 MPa
was correspond a suction of initial direct shear
compacted benronite specimen. In case of suction of599

GEOMATE-Nagoya, Nov.13-15, 2013

1.2

1.1

Initial compacted bentonite
Suction 105 MPa○ Loading path
□ Unloading path1
0.9

Void ratio

Void ratio

1.2

0.8
0.7
10
100
1000
Compression stress kPa

0.8

10000

1

Compression curve for suction of 105 MPa.

Fig. 510
100Compression stress kPa

1.1
1
Suction 2.8 MPa○ Loading path
□ Unloading
path

0.9
0.8
0.7

10
100
1000
Compression stress kPa

Summary of compression parameters.

Suction MPa

Cc

Cs

105
2.8
0

0.05
0.47
0.05

0.04
0.01
0.01

Cc: Compression index, Cs: Swelling index
compression stresses approach to a maximum stressvalue, because a bentonite sample was applied
significantly high stress in order to remain a target
dry density. Figure 4 shows the curve of bentonite
subjected to decreasing suction due to vapor
pressure technique, which expansion was observed
on upper surface.
Hydration effort inducedchanging of void ratio that increased from 0.75 to
1.12. It was predicted that macro-micro pore
distribution and soil moisture distribution wereconsiderable different to initial bentonite.
Compression deformation gradually progressed withincreasing compression stress. After compression
stress was over 40 kPa, reduction of void ratio waslarge and the curve was seemed to be liner on asemi-logarithmic scale. Determined void ratio was
0.635 when maximum compression stress was
loaded. Its deformation was large compare to thecurve of initial compacted bentonite shown in Fig. 3.
Subsequently, expansion deformation was measured
at unloading path.
Swelled bentonite showed similar to the curve ofinitial bentonite, it seemed to small reduction of void
ratio through entire vertical stress ranges. The
swelled bentonite may maintained undrained
condition in macro structure which had much lowhydro-conductivity. It meant draining of pore-waterin void structure was not induced due toconsolidation, and compression deformation wasslightly at loading path. Also, swelling deformation
was small at unloading path. Compression index
and swelling index were summarized in Table 2.
Measured compression index of suction of 2.8 MPa
was largest among other two bentonite samples.
Regard to swelling index, its value was relatively
large compare to other two bentonite samples whensuction was 2.8 MPa. Thus, compression properties
was clearly difference and the influence of suction

0.6
1

1000

Compression curve for suction of zero.

Table 2

1.2
Void ratio

0.9

0.6
1

Fig. 4

1

0.7

0.6

Fig. 3Swelled bentonite
Suction 0 MPa○ Loading path
□ Unloading path

1.1

10000

Compression curve for suction of 2.8 MPa.

of specimen and swelled bentonite remained atsaturation condition during direct shear process. It
was unknown whither either drained condition or
undrained condition exited in bentonite during
shearing as excess pore-water pressure was notmeasured in this testing. Four different shear speeds
ranging from 0.004 mm/min to 0.5 mm/min wereapplied to specimens under constant normal stress of
200 kPa.
TEST RESULTS
Compression properties of compacted bentonite
Compacted bentonite sample subjected todecreasing suction indicated expansion or peeling on
upper surface, which controlled suction was 2.8 MPa
corresponding to RH of 98 %. Change of macromicro structure cause its volume deformation. This
study conducted compression test for three different
suctions such as initial compacted bentonite, suctionof 2.8 MPa and bentonite. Each bentonite specimen
was maintained to constant suction values inchamber through compression tests.
Appliedcompression stress from 10 kPa to 1000 kPa, bothloading path and unloading path were performed thatwas to determine compression index and swelling
index.
The compression curves of bentonite for threedifferent suctions are shown in Figs. 3 to 5. Initialcompacted bentonite having a suction of 105 MPa
showed not so much reduction of void ratio through600

GEOMATE-Nagoya, Nov.13-15, 2013

300

500

Shear speed
0.05 mm/min

400
300

Initial compacted
bentonite
Suction 105 MPa
Water content 5.9%

200
100

200
150
100

200

400
600
800
Normal stress kPa

1000

0
0

1200

Fig. 6
Relationship between vertical stress andshear strength for initial compacted bentonite.

Apparent cohesion
182.7 kPa

Shear stress kPa

300
Shear speed 0.004 mm/min

250

8

300

Strength parameters for initial bentonite.

Angle of internal friction
16.6 degrees

2
4
6
Horizontal displacement mm

Fig. 8Stress-strain curve for suction of 2.8
MPa under shear speed of 0.05 mm/min..

Shear stress kPa

Table 3

Suction 2.8 MPa

50

0
0

Shear speed 0.05 mm/min

250

Shear stress kPa

Shear strength kPa

600

200

せん断変位速度0.025mm/min
0.05mm/min
Shear
speed
0.25
mm/min
周波数
2.0Hz

250
200
150
100

サクション2.8MPa
Suction
2.8 MPa
サクション2.8MPa

50
0

150

0

100
Suction 2.8 MPa

50

8

300
Shear stress kPa

2
4
6
Horizontal displacement mm

8Fig. 9Stress-strain curve for suction of 2.8
MPa under shear speed of 0.25 mm/min.
.

0
0

2
4
6
Horizontal displacement mm

Fig. 7
Stress-strain curve for suction of 2.8
MPa under shear speed of 0.004 mm/min.
was effectively.
Failure envelope for compacted bentonite beforechanging suction

250

Shear speed 0.5 mm/min

200
150
100
Suction 2.8 MPa5000Initial compacted bentonite samples wereconducted out direct shear test under constantnormal stress of 200 kPa at a shear speed of 0.05
mm/min and the relationship between vertical stressand shear strength was shown in Fig. 6. Applied
normal stresses ranged from 200 kPa to 1000 kPa.
Relationship between normal stress and shear
strength showed a straight line at this limited normal
stress ranges. The measured failure envelope hadstrength parameters (i.e., angle of internal friction
and apparent cohesion). The strength parameters are
summarized in Table 3.

2
4
6
Horizontal displacement mm

8Fig. 10
Stress-strain curve for suction of 2.8
MPa under shear speed of 0.5 mm/min.
maximum shear stresses were indicated on the
stress-strain curve using black narrow. The shear
stress rapidly increased at beginning of shearing
except 0.05mm/min, and gradually increased whenhorizontal displacement was over 2.0 mm. These
specimens described maximum shear stress value till
horizontal displacement was 8.0 mm.
Eachmagnitude of horizontal displacement at failure wasdifferent. It was difficult to make available tendencywith shear speeds. In case of 0.5 mm/min, shear
stress showed small reductions such as softening.

Stress-strain behavior in suction of 2.8 MPa
Direct shear tests under constant normal stress of
200 kPa were performed under four different shear
speeds for compacted bentonite controlled frominitial suction of 105 MPa to 2.8 MPa. These stressstrain behaviors were shown in Figs. 7 to 10. The
601

GEOMATE-Nagoya, Nov.13-15, 2013

Table 4
Summary of shear strength ofcompacted bentonite with four different shear speeds.

Shear stress kPa

300
250

Shear speed 0.004 mm/min

200
150
Swelled bentonite

100

0

0.05

0.25

0.5

Suction 2.8MPa

168.8

153.4

140.0

129.0

Suction 0 MPa

50.7

56.4

53.2

－

Stress-strain
bentonite

2

4

6

8

Horizontal displacement mm

300
Shear speed 0.05 mm/min

250
200
150

Swelled bentonite

100
50
0
0

2
4
6
Horizontal displacement mm

8Fig. 12
Stress-strain curve for swelled bentonite
under shear speed of 0.05 mm/min.

200
150
Swelled bentonite

50
0
0

2

4

6

8

Horizontal displacement mm

Fig. 13
Stress-strain curve for swelled bentonite
under shear speed of 0.25 mm/min.

Shear strength kPa

300
250
200

▲ Suction 105 MPa● Suction 2.8 MPa□ Suction 0 MPa

150
100
50
0
0.001

0.01
0.1
1
Shear speed mm/min

swelledsaturated

Relationship between shear strength obtained
constant normal stress in direct shear test under avariety of shear speeds is shown in Fig. 14. Shear
speeds were plotted on logarithmic scale, whichranged from 0.001 mm/min to 10 mm/min. Shearstrength of bentonite with suction 105 MPa wasplotted that it was initial bentonite sample. The
shear strength of compacted bentonite with different
both suctions and shear speeds was summarized inTable 4. The shear strength of suction of 105 MPa
indicated largest among other suction values thatmentioned significant effort to shear strength. Shearstrengths reduced toward to one fifth at least incomparison between suction of 105 MPa andswelled saturation condition.
The shear strength of 168.8 kPa was describedon 0.004 mm/min for suction of 2.8 MPa and theshear strength gradually decreased with increasing
shear speed. At shear speed of 0.5 mm/min, shear
strength decreased to 129.0 kPa. It described thatshear speed influenced to shear strength forcompacted bentonite subjected to suction of 2.8
MPa. Other hands, the swelled bentonite indicatedsimilar shear strength regardless of shear speed atlimited speed ranges. Magnitude of shear strength
indicated around 50 kPa. Eventually, the influenceof shear speed on direct shear strength was different
to suction value of compacted bentonite.

Shear speed 0.25mm/min

100

of

Influence of shear speeds on shear strength

300
250

behavior

Stress-strain behaviours of the swelled bentonite
at three different shear speed in shown Figs. 11 to 13.
Shear stress increase gradually at beginning andmaximum shear stress was approached at small
horizontal displacement compare to bentonite ofsuction of 2.8 MPa. Horizontal displacements toreach maximum shear stress were less than 3.0 mm.
All specimens showed small reduction of shear
stress beyond maximum shear stress and remained at
residual shear stress. Maximum shear stresses wereclose to 50 kPa and these values indicatedsignificant reduction compare to bentonite with bothsuction of 105 MPa and 2.8 MPa. Also, thedifference between maximum shear stress andresidual shear stress was small.

Fig. 11
Stress-strain curve for swelled bentonite
under shear speed 0.004 mm/min.

Shear stress kPa

0.004

50
0

Shear stress kPa

Shear speed
mm/min10

Fig. 14
Relationship between shear speed andshear strength for compacted bentonite.
602

GEOMATE-Nagoya, Nov.13-15, 2013[2] Cui, Y.J. and Delage, P. On the elasto-plastic
behaviour of an unsaturated silt. Unsaturated
Soils, American Society of Civil Engineers,
1993. 125-126.
[3] Cui. Y.J., Yahia-Aissa, M. and Delage, P. A
model for the volume change behavior ofheavily compacted swelling clays. Engineering
Geology, 2002, Vol.64, 233-250.
[4] Nishimura, T. and Fredlund, D.G. A new
triaxial apparatus for high total suction using
relative humidity control. 12th Asian Regional
Conferenceon
Soil
Mechanics
andGeotechnical Engineering, 2003, 65-68.
[5] Nishimura, T., Rahardjo, H., Koseki, J. Direct
Shear Strength of Compacted Bentonite underDifferent Suctions. Proceedings of the Fifth
International Conference on Unsaturated Soils,
2010, 323-328.
[6] Nishimura, T., Koseki, J. and Matsumoto, M.
Measurement of swelling pressure for bentonite
under relative humidity control. Unsaturated
Soils: Research and Applications, E-UNSAT
2012, 2012, Vol.1, 235-240.
[7] Nowanmooz, H. and Masrouri, F. Soil fabricand soil water retention curve of a compactedsilt-bentonites. Geotechnical Testing Journal,
ASTM, 2012, Vol.35, No.1, 18-30.
[8] Wang, Q., Tang, C., Tang, Anh-M. and Cui, Y-J.
Effect of suction changes on the microstructureof compacted crushed argillites under constantvolume conditions. Unsaturated Soils: Researchand Applications, E-UNSAT 2012, 2012, Vol.1.
185-190.

CONCLUSIONSThis study investigated shear speed influence on
shear strength of a compacted bentonite in direct
shear test under constant normal stress, while
suction was controlled to 2.8 MPa or swelledsaturation. As in previous compression test, eachcompression index and swelling index was describedin order to realize the influence of suction changes.
The results obtained from this testing program aresummarized as following;(1) Void ratio of compacted bentonite increased
when suction changed from from 105 MPa to 2.8
MPa before compression test. Large compression
index was measured. Its index was ten times as highas that of initial compacted bentonite.
(2) Decreasing of suction influenced on shear
strength of compacted bentonite, and induced thedecrement of shear strength.
(3) In case of suction of 2.8 MPa, the shear strengthof compacted bentonite decreased gradually withincreasing shear speed, while the influence of shear
speed was small for swelled bentonite.
ACKNOWLEDGEMENTS
This study was supported by the grant for 2012
from Ashikaga Institute of Technology.
Also
authors
would
like
to
make
gratefulacknowledgement to Dr. Julian K. GAN, P. Eng.
(MDH Engineered Solutions Corp.) for discussions.
REFERENCES[1] Blatz, J.A. and Graham, J. A system forcontrolled suction in triaxial tests. Geotechnique,2000, Vol.50, No.4, 465-469.

603

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EFFECTS OF HYDROLOGICAL PARAMETERS ON
DESERTIFICATION IN CHINA BASED ON THE SATELLITE DATA
Nozomu Hirose1, Fengzhi DAI2 and Keiko Okada1
Civil and Environmental Engineering, Matsue College of Technology, Japan;
2
College of Electronic Information and Automation, Tianjin University of Science and Technology, China;
1

ABSTRACT
Desertification is defined as land degradation of arid or semiarid ecosystems driven by climate variation andhuman disturbances. In this study, we explore the expansion of desertification in China and the effects ofhydrological change under global warming on it by investigating satellite data. We used Normalized Difference
Vegetation Index (NDVI), soil moisture, snow cover, and precipitation from 2002 to 2012. Two study areas are
determined by classifying the vegetation type based on IGBP land use.
We found that NDVI in August decreases as soil moisture decreases in June and July in semiarid area.
Precipitation in the area is decreased from 1957 to 2011.On the other hand, it is found that the relationshipbetween NDVI and soil moisture in crop land is obscured due to agricultural irrigation.
Keywords: Desertification, NDVI, soil moisture, satellite data

virescence.
China has done some measures such as ecomigration and large-scale reforestation aiming at thestatus quo of desertification, but the globallyeffective strategy appears rarely.
The present governance is aimed at local analysis
of a region. However, only global countermeasures
resolve the problem in Beijing-Tianjin area.
Therefore, widespread monitoring by satellite
remote sensing technology is bound to be theimportant means.
The accurate model for monitoring and analyzing
desertification by satellite technology is rare. But it
is feasible to obtain data of soil moisture, migrationof surface vegetation and from which to calculate
the direction and speed of desertification. The
research is by the satellites that long-termly monitor
the plant growth and water cycles, thereby analysis
the current desertification situation as well as its
influence on the Beijing-Tianjin region of China.

INTRODUCTION
Recently, desertification eastward and sand dust
has become one of the most serious ecological andenvironmental problems in China. The affected areas(where vast dust that is blown by powerful wind inwestern Inner Mongolia autonomous region falls
down after roaming to the east through the air) are
not only limited in Beijing and Tianjin, but have
expanded to Korea and Japan [1]-[6].
The desertification from western China to
Beijing-Tianjin area has raised serious problem insociety and damaged the function of the capital of
China. In the future, it may be an important factor
result moving the capital to another city. In the
future, with the temperature rises and theprecipitation decreases caused by global warming,
the soil will become drier and irrigation will makethe water resource drains distinctly. It can bepredictable that the process of desertification will be
more and more serious.
The United Nations has signed the Convention to
Combat Desertification, where pointing out that theclimate changes and human activities are the maincauses of soil deterioration and environmental
destroy. Therefore, it is necessary, with the
exception of reducing man-made sabotage, to grasp
the annual changes in desertification of earth’s
surface in a long period, and clarify the influencethat climate change could make for desertification
by observation and statistical analysis. Furthermore,
we can utilize some approaches like numericalanalysis to predict the direction and rate ofdesertification in order to deploy the long-term
effective prevention and treatment program of

DATA
Vegetation Index
Vegetation conditions are collected by The
Moderate Resolution Imaging Spectroradiometer(MODIS) that are carried on the Terra and the Aqua
satellite (spatial resolution is 0.05°). The used
vegetation index is the EVI (enhanced vegetationindex) since the EVI value changes more remarkably
than that of the NDVI (normalized difference
vegetation index) [7].

604GEOMATE-Nagoya, Nov.13-15, 2013as bushes and weeds in the semi-arid area, andRegion B (Longitude: 115°-117°, Latitude: 37°-40°)
where more crops like rice grow in humid area.
All the data are collected from September 2002 to
December 2011. Fig. 3 and Fig.4 provide thevegetation and soil humidity distribution of this areain August 2011. Notice that the striking distinctionof vegetation and soil humidity in different region is
also near the boundary basically.

Soil Moisture
Soil moisture [g/cm3] is obtained by using themeasured data of AMSR-E carried by the Aqua
satellite (spatial resolution is 0.25°) [8].
Air temperature and precipitation
The research adopts the high-resolution datasetof daily precipitation and air temperature from
Aphrpdite’s water resources project (spatial
resolution is 0.25°) [9]. This dataset is for the sakeof ascertaining the impact that global warming
makes on water resources in Asia area, collects andprovides the long-term daily precipitation andaverage air temperature in this area.

Fig. 2 Land covers classification in the study area.

Fig. 1 Altitude figure of the study area.
STUDY AREA
Firstly, an area which contains Beijing-Tianjin
area and has significant effect on them is selected.
Figure. 1 is the altitude figure of study area. We use
the IGBP Land Cover Dataset 2006 to classify thegrowth status of the land cover vegetation to 17
classes in the study area, which is shown in Fig. 2. It
can be seen from Fig.2 that this region is divided to
two main parts by a remarkable boundary. Morebushes and weeds are located in the arid areas ofNorthwest (displaying as the yellow parts in color
print), yet more crops like rice spread over thehumid areas of Southeast (the green parts). By
comparing Fig.1 and Fig.2, it is obviously that theboundary is consistent with the varying altitude.
Around the Beijing-Tianjin region within theanalytical scope, we differentiate 2 regions (shownas two rectangular frames A and B in Fig.2) near theboundary where vegetation growth and soil humidity
change sharply in order for statistics and analysis ofdata [10], [11].
They are Region A (Longitude: 114°-117°,
Latitude: 41°-45°) covered by scrubland plants such

Fig. 3 The distribution of vegetation index (NDVI)
in August 2011.

Fig. 4 The distribution of soil moisture in August
2011.
605

GEOMATE-Nagoya, Nov.13-15, 2013

RESULT
Long-term change of vegetation and soil moisture
To analyze long term trend of desertification
around target areas, monthly average of vegetation
growth and soil humidity of selected areas in Sept.
2002 to Dec. 2011 is used. The vegetation growthand soil humidity change with season: They
increased in summer and decreased in winter since
there is more rain in summer. And with the increaseof precipitation, the growth of plant became actively.
Monthly average change of vegetation and soil
moisture
Fig. 5 and Fig.6 illustrate the monthly change ofvegetation and moisture. The records are long-termmonthly means of vegetation growth and soil
moisture, so that we can clearly see the averages thatdifferent months influence on vegetation indexes.
The curves suggest that it is obviously to find bothchanges in two areas (just paying attention tosummers when vegetation grows): in Region A, thevegetation growth varies greatly from June to
September. In contrast, the soil moisture changes
largely from May to August. Namely, the rise of soil
moisture is ahead of vegetation growth. In Region B,
the vegetation growth shifts much from June to
September while the soil moisture does this from
June to October, especially both the curves ofvegetation and soil moisture rises sharply from June[10], [11].

Fig. 5

Fig. 6The Monthly average of a) vegetation index
and b) soil moisture with climate in area B.

The curves suggest that it is obviously to findboth changes in two areas (just paying attention tosummers when vegetation grows): in Region A, thevegetation growth varies greatly from June to
September.
In contrast, the soil moisture changes largely
from May to August. Namely, the rise of soil
moisture is ahead of vegetation growth. In Region B,
the vegetation growth shifts much from June to
September, while the soil moisture does this from
June to October. Especially both the curves ofvegetation and soil moisture rise greatly from June.

The Monthly average of a) vegetation index
and b) soil moisture with climate in area A.

Fig. 7606

Long-term changes of precipitation in areaa) A and b) B.

GEOMATE-Nagoya, Nov.13-15, 2013[3] Gu, Y., E. Hunt, B. Wardlow, J. B. Basara, J. F.
Brown, and J. P. Verdin (2008), Evaluation of
MODIS NDVI and NDWI for vegetation
drought monitoring using Oklahoma Mesonet
soil moisture data, Geophys. Res. Lett., 35,
L22401, doi:10.1029/2008GL035772.
[4] Kaneko, D. ， T. Kumakura, P. Yang (2008),
Crop yield and CO2 fixation monitoring in Asia
using a photosynthetic-sterility model withsatellites and meteorological data，Proceedingsof the Global Conference on Global Warming2008 (GCGW-08), 6-10, July, 2008, Istanbul,
Turkey, Paper No.378, 227-238.
[5] Ishizuka, M., M. Mikami, J. Leys, Y. Yamada,
S. Heidenreich, Y. Shao, and G. H. McTainsh(2008), Effects of soil moisture and driedraindroplet crust on saltation and dust emission,
J Geophys Res, 113, D24212.
[6] Darmenova, Kremena, Irina N. Sokolik, Yaping
Shao, Beatrice Marticorena, and Gilles
Bergametti (2009), Development of a physically
based dust emission module within the Weather
Research and Forecasting (WRF) model:
Assessment of dust emission parameterizations
and input parameters for source regions inCentral and East Asia, J Geophys Res, 114,
D14201.
[7] Rouse, J. W., Jr., H. R. Haas, D. W. Deering, J.
A. Schell, and J. C. Harlan (1974), Monitoring
the vernal advancement and retrogradation(green wave effect) of natural vegetation, typeIII final report, 371 pp., NASA Goddard Space
Flight Cent., Greenbelt, Md.
[8] H. Fujii, T. Koike, and K. Imaoka, (2009),
Improvement of the AMSR-E Algorithm for
Soil Moisture Estimation by Introducing a
Fractional Vegetation Coverage Dataset
Derived from MODIS Data, Journal of The
Remote Sensing Society of Japan, VOL.29,
282-292[9] A.Yatagai, K. Kamiguchi, O. Arakawa, A.
Hamada, N. Yasutomi, A. Kitoh (2012),
Aphrodite: Constructing a long-term daily
gridded precipitation dataset for Asia based on adense network of Rain Gauges. Bulletin ofAmerican Meteorological Society, Vol. 9: 401415.
[10] Okada Keiko, Hirose Nozomu, Dai Fengzhi.
Analysis Desertification and its affect in China
by satellite data. Proceedings of 2012 Annual
Conference, Japan Society of Hydrology andWater Resources, September 26-28, Horoshima,
Japan, 236-237, 2012.
[11] Okada Keiko. The condition and influence ofdesertification in mainland of China based onsatellite data. Matsue College of Technology
2013.

The variation of long-term precipitation
Fig. 7 reveals the variation of annual
precipitation means from 1951 to 2007. Through thecomparison between the precipitations of two
regions, we can see that Region A has more
precipitation than Region B, but Region A has adownward trend during the last 50 years while there
has almost no change in Region B
CONCLUSION
This research monitors the vegetation growth
and water circulation in a long period near the
Beijing-Tianjin area in China by utilizing the data
observed by the satellites. According to the result ofanalysis, there is an apparent shift, with seasons, forboth vegetation growth and soil moisture. And also,
the precipitation has a falling tendency year by year.
On the contrary, although vegetation growth and soil
humidity in Region B keep change with seasons,precipitation in this area has no such inclination.
Besides, the soil moisture in Region B increases
sharply in June even exceeds Region A, thoughmore precipitation is in Region A. The cause is thatat farming area Region B, irrigative leads to a great
rise of soil moisture. In terms of the existing data,
the areas covered by plants in the semi-arid region in
Northwest of China will continuously tend to
reduce, following the decreasing of precipitation in
future [10], [11].
ACKNOWLEDGEMENTS
The authors thank Hideyuki Fujii for providing
newly soil moisture data.
This research is partly supported by the OpenFoundation (YF11700102) of Key Laboratory for
Water Environment and Resources, Tianjin Normal
University; Dr. Fund of Tianjin Normal University(52LX24); Natural Science Foundation of China(41172315).
REFERENCES[1] Ishizuka, M., M. Mikami, Y. Yamada, F. Zeng,
and W. Gao (2005), An observational study ofsoil moisture effects on wind erosion at a gobisite in the Taklimakan Desert, J. Geophys. Res.,
110, D18S03, doi:10.1029/2004JD004709.
[2] Myoung, B., Y.-S. Choi, S.-J. Choi, and S. K.
Park (2012), Impact of vegetation on landatmosphere coupling strength and its
implication for desertification mitigation overEast Asia, J. Geophys. Res., 117, D12113,
doi:10.1029/2011JD017143.

607

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STRENGTH PARAMETER SELECTION IN STABILITY ANALYSIS OFRESIDUAL SOIL NAILED WALLS

1,2

Atefeh Asoudeh1 and Erwin Oh2
School of Engineering, Griffith University, Australia

ABSTRACTThis paper investigates slope stability of soil nailed walls which are located on sites formed with mostly
residual soils. Residual soils, forming from weathered rocks can be found in many parts of the world withdifferent characteristics and appearance based on type of the parent rock they have been formed of. A review on
geotechnical properties of residual soils that have been used in previous studies in different parts of the world
will be presented and then evaluated to be used as parameters for numerical analysis of soil nailed walls. Slopestability assessment is performed by LEM analysis and a discussion on the results of analysis is presented in thispaper.

Keywords: Residual Soil, Slope Assessment, Soil Nailing, Numerical Analysis
INTRODUCTION
General Characteristics of Residual Soils
Slope stability is one of the most unpredictableproblems in geotechnical projects and the cause ofthis unpredictability can be returned to ambiguity inseveral factors such as condition and location of
failure, geotechnical parameters of soil and historyof loading on the slope. This issue gets even more
serious when the slope is on residual soil, whichmeans that unlike sedimentary soils, the strengthparameters of soil cannot be obtained trustfully
based on stress-strain relationships.
Therefore, this paper tries to find a reliable
solution in slope stability assessment of residual soil
slopes by concentrating on selection of right values
for strength parameters in this type of soil. First, areview on previous studies on residual soil slopes
will be presented. Afterward, some samples ofstrength parameters for residual soils that have beenused in previous studies will be introduced.
Accordingly, critical geotechnical parameters thatshould be considered in assessment of a residual soil
slope will be identified.

According to Townsend [1], three main chemical
weathering factors that can lead to production ofresidual soils are: a) climate, b) parent rock’s
minerals and c) topography. Effect of climate inweathering is obvious as the rainfall provides therequired moisture for chemical reactions and then
the temperature dictates the chemical reaction’s rateand considering these two components, best climate
in which weathering can occur and therefore residualsoils can be found is tropical weather.
The role of parent rock in weathering process isonly predominant on initial stages of weathering andtopography can influence the weathering procedureby controlling the surface run off and therefore
moisture content of soil and also by rate of erosion.
Chean and Sew [2] highlighted the main traits ofresidual soils as very heterogeneous with highpermeability. They summarized the importance of
weathering profile regarding to its role in control of1) potential failure surface and mode of failure 2)
groundwater hydrology and 3) the erosion
characteristics of material.
Valuable information regarding to generalcharacteristics of residual soils has been gathered in
the book prepared by Wesley [3]. In his book,
Wesley presents basic aspects of residual soil andthose properties that should be considered bygeotechnical engineers while working with this typeof soil.

A REVIEW ON RESIDUAL SOIL SLOPES
Residual soils form from weathered rocks andcan be found in many parts of the word withdifferent characteristics and appearance based on thetype of parent rock they have formed of. This large
range of difference in residual soils leads to variety
of studies that focus on different aspects of this typeof soil and therefore in the following paragraphs
summary of these studies will be presented based on
the area they are focusing on.

608

609

using multistage consolidated undrained triaxial tests
using a strain rate of 0.05% per min.
Coutinho and others [5] carried out a project toinvestigate the instability problems of a road
constructed in Brazil after occurrence of a landslidein a natural non-homogenous unsaturated residual
soil slope of this road. As a result of an intensive
laboratory investigation, geotechnical parameters ofresidual soil were obtained and have been shown in
Table 2.

By remarking some important characteristics ofresidual soils such as a) being heterogonous, b)
having specific types of clay minerals and c) having
unusual form of structure, Wesley concludes that indesign of geotechnical structures on residual soil,
engineers should give more attention to observation,
experience and judgment instead of just relying on
analytical and theoretical part of problem. Moreover,he emphasizes that application of e-log p graph forinterpreting the behavior of residual soils ismeaningless, as sedimentation process has notformed them.

Table 2 Strength parameters of residual soil bydirect shear test (Coutinho & others, 2000)

Engineering Properties of Residual Soils
Townsend [1] also investigated the engineering
properties of three different types of residual soilthat are Lateritic Soils (highly weathered reddish
tropical soils), Allophanic Soils (derived fromvolcanic ash) and Black Soil (or dark clays). Table 1
presented by Townsend [1] shows the shear strengthparameters for the above-mentioned soils that had
been obtained in previous studies.

Soil Type

Dept
Test
φ’ (°)
h (m) condition

MatureResidual

0.75

Young Residual
MatureResidual
Young Residual

Table 1 Example of Strength Parameters for
Residual Soils (Townsend, 1985)
Soil Type &Location
Lateritic gravels,
AfricaLateritic clays,
AfricaLateritic soil,
PanamaGranitic laterite
soil, Venezuela
Granitic laterite,
BrazilAndosol, JavaBlack clay,
Cameroonφ’ (°)c’(kPa)

Reference

37.5

0-40

Horn (1982a)

22.50-100 Horn (1982a)

38

0

Townsend(1970)

21.5

20

Pursza (1983)

31

0

36

24

Submerged 31.9
Nat. M.C. 41.6
Submerged 29.3
8.70
Nat. M.C. 29.5
Submerged 35.5
1.9
Nat. M.C. 37.8
Submerged 30.3
4.6
Nat. M.C. 31.2

c’
(kPa)
10.8
71.4
2.8
7.0
0.0
15.8
0.0
38.3

Azevedo and others [6] performed an extensive
laboratory work on undisturbed samples of residualsoils and used the results of these tests in modelingthe behavior of residual soils with non-associatedelasto-plastic model in finite element analysis of atunnel excavation. They compared the results ofnumerical analysis with both empirical predictions
and field instrumentations and proposed coefficientsthat can be used in numerical simulation of tunnel
construction stages in residual soils.
A series of examinations were conducted by
Rahardjo and others [7] in Singapore to specify the
relationship between the degree of weathering andsoil behavior in residual soils. As a result, theyfound that the higher the degree of weathering is, themore pore volume is which means a larger range ofpore-size distribution.
As a part of their work, they took samples fromdifferent depths corresponding to different degrees
of weathering and conducted consolidated, drained
tri-axial compression tests under both saturated andunsaturated. Table 3 shows the summary of data thatthey found as a result of the above-mentioned tests.
Rahman and others [8] performed a testing
program on reinforced and unreinforced residual soil
samples by considering six different stress strain
paths. Then, they introduced parameters related to

Vargas(1953)
Wesley(1974)

16.1-20.1 47-58 Horn (1982b)

Loganathan and others [4] suggested acorrelation factor for shear strength of residual soil
in order to achieve more accurate results. This
correlation factor can be applied into the laboratory
shear strength of a specific type of residual soil thathas been obtained by specific method of sampling
and testing. For instance, the samples should besaturated under an effective stress of 10Kpa andshear strength parameters should be determined609

Huat and others [11] collected lots of data and intheir book, presented an overview of the index andengineering properties of some tropical residual soils.
Based on their findings, values for soil strength inresidual soils ranges from 2 to 123KN/m2 forcohesion and 10 to 58 for friction angle (φ). They
related this large range of variety to the great
difference of soil formation in residual soils.
Furthermore, Wesley [3] related the high shear
strength in these soils to existence of clay minerals.
Also, microstructural effect and its contribution to
the cohesive component of shear strength (C) can bechosen as another reason.

the Cam Clay model in simulating the finite element
analysis of reinforced residual soil and as a result
they could find a good agreement between the resultof their numerical simulations and measured
response.
Table 3 Shear strength of residual soil in different
depths (Rahardjo and others, 2004)c’
φ’
Depth Grade of(kPa)(m) Weathering (°)

Soil Type

Granitic Bukit Timah formation
Sandy Silt
5-9
Silty Sand
10-15
Silty Sand
15-21
Sedimentary Jurong formation
Purple silty sand 3-4
Purple silty sand 4-5
Orange silty sand 9-10
Purple silty sand 22-24

VI
V
V

27
35
38

26
13
12

IV
IV
IV
III

42
51
45
50

125
55
35
225

Slope Stability on Residual Soils
There are several studies that have been carriedout to study the stability of slopes in residual soil
areas in different parts of the world and thefollowing paragraphs is a brief on some of thesestudies.
One important part of work carried out by
Coutinho and others [5], was a back analysis inorder to find the shear strength parameters ofresidual soil that can lead to the slope failure. As aresult they concluded that shear strength parameters
obtained from laboratory tests could explain the
failure condition (FoS=1) by considering a low orvery low amount of suction in wet seasoning.
Moreover, they introduced several factors as theimpacting factors on the landslide including
excavation for the purpose of road construction,
sever rainfalls and prolonged high precipitation.
Tan and others [12] performed a parametricstudy on stability analysis of residual soil slopes in
Malaysia and investigated the effect of several
factors such as slope geometry, soil parameters,piezometric surface, surcharge and soil nailingreinforcement on the tropical residual soil slope
stability. However, the summary of their work does
not show any sign of considering specificcharacteristics for residual soil and therefore,
residual soil has been treated and analyzed in thesame way that sedimentary soil is examined.
Another important study on residual soil slopes
is a section of book prepared by Huat and others[11] on failure of 6 slopes (including natural, manmade and filled slopes) on tropical residual
weathered soil located in different parts of Malaysia.
As a result of this study they recommended the useof Consolidated Isotropically Undrained (C.I.U.) triaxial test in obtaining the peak shear strength anduse of ring shear test to find the residual shear

Ogunro and others [9] presented the geotechnicalproperties of Piedmont residual soil on which somemajor cities and centers in the east coast of U.S. arefounded and it is the result of chemical andmechanical weathering of Piedmont Palezoic Rocks(schist, gneiss, and granite). Table 4 shows a sample
of results from Borehole Shear Test (BST) and CU
triaxial test in a site located in North Carolina.
Table 4 Sample of result from BST and CU triaxial
test for Piedmont residual soil

Borehole#

1

2

Depth
(m)

10
15
20
5
10
15
20

Borehole
Shear Test
(BST)c’φ’ (°) (kPa)
45
43
40
44
23
40
42

0
0
9.65
0
7.9
0
6.9

CU triaxial
Test
φ’
(°)

c’
(kPa)

29
37
41
30
30
36
29

5.9
11
0
24.1
18.3
14.1
20

In another paper, Anderson and Cottingham [10]introduced the average values for Cohesion (c ) andfriction (φ) of Piedmont residual soil equal to 26.9
kPa and 26.3 degree, respectively.
610

As shown in Fig.1, two rows of nails with length of
5m, angle of 15° and horizontal space of 2m wereconsidered in stabilization of slope. In order to findthe FoS of slopes method of Morgenstern-Price,which is able to satisfy both force and moment
equilibriums, was used in LEM analysis.

strength and they suggested the use of residual
strength in residual soil slope stability design.
Discussion and Concluding Remarks From
Previous Studies
One important point that can be concluded fromprevious section is that almost all types of theresidual soils that have been studied possess a
relatively high value of friction angle (φ) with aminimum record of 20 degrees and average value of
35 degrees. Unlike friction angle, cohesion ofresidual soils has shown a wide range of values indifferent studies from zero to very high values nearto 200kPa in deeper distances from ground level.
This important fact demands a crucial attention to
impact of cohesion on stability of residual soil
slopes. Therefore, a parametric study has been
performed and three different cases (Case-I: φ=20°,
Case-II: φ=35°, Case-III: φ=45°) were used toinvestigate the effect of different values of cohesion
on stability of nailed slopes in residual soils. Next
sections present a summary on detail of slope
assessment and results of Limit Equilibrium Method(LEM) of analysis performed by geotechnicalsoftware Geo-Slope for the above-mentioned cases.

RESULT OF ANALYSIS AND DISCUSSION
In order to examine the impact of cohesion value (c)on stability of these slopes, a sensitivity check was
performed and the obtained Factor of Safety (FoS)
for each case has been presented in Figure 2. For the
purpose of sensitivity check, a wide range ofcohesion changing from zero to 200kPa wasassumed for the cohesion parameter of slopes.

NUMERICAL ANALYSIS OF DIFFERENTSLOPES IN RESIDUAL SOILS
Three different cases with three different values offriction angle (φ=20°, 35° & 45°) were simulated in
geotechnical software Geo-slope, which uses LEM
in slope stability analysis. Geometrical properties ofslopes and general properties of soil nails wereidentical for all three cases and it has been presented
in Fig.1

Fig.2 FoS of nailed slope for different values ofcohesion
According to result of analysis presented in Fig.2 , anearly linear relationship exists between FoS andcohesion of soil and the slope of this line is almost
the same for all three cases. However, thisrelationship is more variable in low values ofcohesion and almost in all three cases the cohesion
value of less than 10kPa will lead to unacceptable
FoS, which is less than 1.5.
CONCLUSION
A review of previous studies on residual soils andspecifically residual soil slopes was presented in thispaper and strength parameters of soil which had
been considered in each study was presented inseparate tables. Based on assumed strengthparameters in previous works, three different cases
were modeled and analyzed to investigate the impact
of cohesion on residual soil slopes. As a result,findings of the present study demonstrated that
residual soil slopes with cohesion parameter of lessthan 10kPa (no matter how much is the friction

Fig.1 Geometry of modeled soil nailed slope

611

angle) and with acceptable amount of reinforcement
have the high probability of collapse and these typesof slopes are sensitive to value of cohesion. Also, it
can be concluded that more attention needs to betaken in finding the cohesion parameter of residualsoils.

[7] Rahardjo, H., et al., Characteristics of residualsoils in Singapore as formed by weathering.
Engineering Geology, 2004. 73: p. 12.
[8] Rahman, M.M., S.A. Mofiz, and M.R. Taha,
Experiments and Finite Element Analysis of
Geosynthetics Reinforced Residual Soil, in
Slopes and Retaining Structures Under Seismic
and Static Conditions. 2005. p. 1-12.
[9] Ogunro, V.O., et al., Characterization andGeotechnical Properties of Piedmont Residual
Soils, in GeoCongress 2008. 2008. p. 44-51.
[10] Anderson, J.B. and M.A. Cottingham, Resultsof Consolidated Drained Triaxial Tests on
Granitic Residual Soil, in Contemporary
Topics in In Situ Testing, Analysis, andReliability of Foundations. 2009. p. 74-78.
[11] Huat, B.B.K., D. G.Toll, and A. Prasad,
Handbook of Tropical Residual Soils
Engineering. 2012: CRC Press/Balkema.
[12] Tan, L.P., C.Y. Lee, and T. Sivadass.
Parametric studies of stability of residual soil
slopes. in ICCBT. 2008. Malaysia.

REFERENCES[1] Townsend, F., Geotechnical Characteristics ofResidual Soils. Journal of GeotechnicalEngineering, 1985. 111(1): p. 77-94.
[2] Chin, I.T.Y. and I.D.G.S. Sew, The
Determination Of Shear Strength In Residual
Soils For Slope Stability Analysis, in Seminar
Cerun Kebangsaan2001: Cameron Highlands,
Malaysia.
[3] Wesley, L.D., Geotechnical Engineering in
Residual Soils. 2012: Wiley.
[4] Loganathan, N., S. de Silva, and A. Thurairajah,Strength Correlation Factor for Residual Soils.
Journal of Geotechnical Engineering, 1992.
118(4): p. 593-610.
[5] Coutinho, R.Q., J.B.S. Neto, and F.Q. Costa,
Design Strength Parameters of a Slope on
Unsaturated Gneissic Residual Soil, in Advancesin Unsaturated Geotechnics. 2000. p. 247-261.
[6] Azevedo, R., A. Parreira, and J. Zornberg,
Numerical Analysis of a Tunnel in Residual
Soils.
Journalof
GeotechnicalandGeoenvironmental Engineering, 2002. 128(3): p.
227-236.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

TENSILE STRENGTH AND SUCTION OF SATURATED NSF CLAY
AND THEIR RELATIONSHIPS WITH UC STRENGTH
Surendra Bahadur Tamrakar and Toshiyuki Mitachi2
Asscociate Professor, Kyoto University, Japan; 2 Professor, Nihon University, Japan

1

ABSTRACT
Tensile strengths of saturated and normally consolidated NSF clays prepared under consolidation pressures(P′ c ) 50, 100, 200 and 300 kPa are measured using a modified version of Tensile strength measuring apparatus
given by Tamrakar et al. (2005) [2, 3] so that suction could be measured at bottom and mid height of thespecimen before as well as throughout the tensile test. Tests were conducted at different tensile pulling rates;
0.01, 0.1, and 1.0 mm/min. Increment in the tensile strength with the increase in tensile pulling rate is seen.
Tensile strength and suction measured at 0.1 mm/min tensile rate are compared with the unconfined compression
strength and suction measured with the specimens prepared under same condition and compression rate. Strength
ratio (q u /q t ) obtained lies in the range of -2.54 to -2.99. The ratio of q t /P′ c ranges from -0.13 to -0.21 andsimilarly, the ratio of q u /P′ c ranges from 0.34 to 0.56. Also, it is seen that the suction values measured at failure
in both tests show the similar value.
Keywords: Tensile strength, Suction, Unconfined compressive strength, Tensile strength measuring apparatus

with tensile strength. But with the apparatus of
Tamrakar et al. [2, 3], one cannot measure suction.
But it is necessary to measure suction and compare
this value with tensile strength. Therefore, here,
tensile strength measuring apparatus is modified sothat it can measure suction at the mid height and thebottom of the specimen before as well as throughout
the test. In order to measure the suction, saturated
ceramic discs with air entry value (AEV) equal to240 kPa is used. To see the effect of tensile pullingrates (0.01, 0.1 and 1.0 mm/min), tensile tests wereconducted at different tensile pulling rates.
Unconfined compression tests were also
conducted with compression rate of 0.1 mm/min.
Here also, suction is measured before and though out
the test. Finally, suction behavior and strength
values of both tensile and unconfined compression
tests were compared.

INTRODUCTION
In order to understand the development of tensile
crack which leads to the failure of slopes, earth dams,
embankments, pavements and ice lens development
process, it is necessary to know the exact value oftensile strength that the particular soil exhibits. At
the same time, development of simple and proper
method for the determination of tensile strength in
the laboratory is necessary.
In the past, tensile strength of soils is generally
neglected as its value is very small in comparison
with compressive strengths. Also, there is difficulty
in measuring the tensile strength directly in thelaboratory. In the past, several tests such as uniaxial
direct tensile test, simple splitting test, unconfined
penetration test, flexure (beam) test, indirect
Brazilian test and hollow cylinder test were used.
But most of those tests were focused to brittle andelastic materials (stiff, compacted and cement mixedsoils) which have higher tensile strength rather thanfor ductile materials (soft, saturated and clayey soils)
which have lower tensile strength. Very few testing
methods have been mentioned for the measurementof tensile strength of soils which have lower tensile
strength values.
Recently, Nahlawi, et al. [1] and Tamrakar, et al.
[2, 3] have introduced new tensile strength
measuring apparatus which measures the tensile
strength directly. One developed by Tamrakar et al.
(2005) [2, 3] could be used for both compacted
unsaturated and saturated soils simply and easily.
But this apparatus cannot measure the suction. Thereis importance of measuring suction values along

TESTING APPARATUS
In this paper, tensile testing apparatus andunconfined compression testing apparatus are used.
Suction in both tests is measured with pore waterpressure measuring transducers. For both tests, test
specimens are prepared under at the same time andunder same condition.
Tensile Test Apparatus
General layout of the modified tensile test
apparatus is shown in Fig. 1. The shape of tensile
mold is like that of numeric letter “8” consisting of
two equal halves, which are connected to outer mold.
613

GEOMATE-Nagoya, Nov.13-15, 2013

These outer molds are connected to lower plates;
one of which is fixed and another is movable. Fixedmold (plate) is directly connected to bottom main
horizontal platform whereas the movable mold(plate) is connected to bottom main platform via
linear sliding roller. This roller will reduce thefriction between movable plate and lower plate.
Both halves of tensile mold are kept in contact witheach other during specimen preparation (insertion)by two horizontal screws, one on each side. Just
before starting the test, those two horizontal screws
are unscrewed. Then movable half is pulled away inhorizontal direction by the motor at constant tensile
pulling rate until the soil specimen fails in tension
with tensile crack appearing at the middle of thespecimen where two halves of the mold is attached.
Load cell placed between the movable half andmotor axis measures the tensile load. This tensile
load is then divided by the area of the tensile crack
perpendicular to horizontal pulling direction, to get
tensile stress. The minimum width at the constrictedsection of the mold is 3 cm and the depth of thetensile mold is 5 cm, which gives tensile failure
plane of 15 cm2. Displacement during pulling ismeasured either by using laser sensor or adjusting
Pore water pressuretransducer (Side)

Tensile mold

setup of the specimen into the mold and once thevalue of suction becomes constant, it is represented
as initial suction. Suction measured at tensile failure
is generally represented as the maximum (max)values of pore-water pressure.
In this paper, tensile tests are conducted at
different tensile pulling rates varying from 0.01 to
1.0 mm/min. Tensile force is measured by load cellis then divided by the tensile failure plane (15 cm2)
to get the tensile stress. By plotting tensile stress andtime (or displacement) graph, tensile strength, themaximum value of tensile stress, q t for the
Ceramic disc (Side)

Motor

Ceramic disc (Pedestal)corresponding test specimen is obtained.

Load cellFig. 2 Tensile test apparatus showing ceramic discs.
Unconfined Compression Test Apparatus

Pore water pressuretransducer (Pedestal)
the tensile pulling gear.

General unconfined compression testing machineis used for the measurement of unconfinedcompression stress. But in this test also, suction ismeasured throughout the test. For this, ceramic discis placed at the bottom pedestal which is thenconnected to pore-water pressure transducer (Fig. 3).
Once the suction becomes constant after the set-upof the specimen, i.e., initial suction values, thenunconfined compression test is started. Suction
measured at failure (or at 15% of axial strain) isrepresented as maximum suction at failure.
Unconfined compression test is conducted at
displacement rate of 0.1 mm/min. Unconfinedcompression stress and axial strain relationship isthen plotted. Maximum value of unconfinedcompressive stress within 15% of axial strain istaken as unconfined compressive strength, q u of thattest specimen.

Laser

Fig. 1 Newly modified tensile test apparatus.
In contrast to tensile mold used by Tamrakar et al. [2,3], here two ceramic discs are used to measure thesuction (Fig. 2) at two places of test specimen; oneat the bottom, i.e., at Pedestal (ped) and another at
the mid-height via side; i.e., at side. In the first case,ceramic disc lies at the bottom of the fixed moldwhereas in the second case, ceramic disc in from ofa small bulb is inserted from the side of the fixedmold upto its center as shown in Fig. 2. Both ofthese ceramic discs must be fully saturated before
the test. Pore-water pressures through these ceramic
discs are measured separately using separate porepressure transducers. Suction measured from the

SPECIMEN PREPARATION AND TESTINGMETHODS
Dried test soil (clay) is mixed with de-aired
distilled water for about 30 minutes in a mixture.
614

GEOMATE-Nagoya, Nov.13-15, 2013

The amount of water mixed is equal to two times theliquid limit of the soil specimen. The slurry preparedis then moved into a special cell where mixing aswell as simultaneous de-airing is possible. Mixing
and de-airing in this cell is done for 3 hours. Slurryis then de-aired by applying suction into that cell.

compression test. Wire saw is used for cutting aswell as trimming the consolidated test specimens.
Since side trimming of the test specimen is not
required, disturbance to the test specimen is highly
reduced.

Dial gauge

Pore-water pressuretransducer
Ceramic disc (pedestal)
(a)

(b)

Fig. 4 Special consolidation molds for (a) tensile testand (b) unconfined compression test.

Fig. 3 Unconfined compression test apparatus.

Once the consolidation is finished, thenconsolidated specimens are shifted to respective
testing apparatus. In case of tensile test, direct
moving of consolidated specimen from TCM totensile mold of tensile testing apparatus is done.
Adjustment of the positions is made so that theconsolidated specimen easily slides into tensile moldwhen pushed from the top. Proper care is taken to
reduce the disturbance. Once the specimen touch thebottom pedestal (ceramic disc), reading of the porewater pressure starts to change. A small pressure isapplied to the specimen so that the test specimen
touches the bottom of the mold. After this, ceramic
disc from the side of the tensile mold is inserted inorder to measure the suction at the mid height of thespecimen. Proper care is taken so that side ceramic
disc just reaches the center of the fixed mold. Once
this is done, then the test specimen is separated fromthe TCM by cutting it using wire saw which is presetup between the TCM and tensile mold. Upper
portion of the test specimen is then trimmed andcovered with a polythene sheet to avoid moistureloss. Pore-water pressures from both ceramic discs
are measured continuously until they reach to certain
constant value, called initial suction. Then two
horizontal screws which keep the halves of tensile
mold combined, are loosened and removed andwhole the apparatus is covered by a box. This will

De-aired slurry is then poured into consolidation
molds; tensile consolidation mold (TCM) andunconfined compression consolidation mold
(UCCM) as shown in Fig. 4. TCM is used for
preparing tensile test specimen and UCCM is used
for preparing unconfined compression test specimen.
Before pouring the slurry into each consolidation
mold, greasing of inner part of consolidation mold isdone. Also, upper and lower porous stones used ofdrainage during consolidation of each mold are deaired and saturated. Filter paper is placed on thelower porous stone before pouring the slurry into it
and then after finishing the pouring, filter paper isplaced on the top and with upper porous stone. Bothporous stones and filter papers enhance theconsolidation. Here, two-way drainage is allowed inboth consolidation molds. Consolidation loads arethen applied in steps.
Here, five test specimens are prepared byapplying consolidation pressure, P' c equal to 50,
100, 200 and 300 kPa, respectively. All the test
specimens are normally consolidated.
The inner cross sections of TCM as well as
UCCM are same as that of tensile test specimen and
UC test specimen, respectively. Therefore, during
the test, only thickness of the test specimen from theconsolidation mold is to be adjusted; 5 cm thick fortensile test and 10 cm height for unconfined615

GEOMATE-Nagoya, Nov.13-15, 2013

prevent the moisture lost during the test. Tensile
pulling is then started at constant rate via motor
gear. Tensile load is measured from the load cell anddisplacement is measured using laser sensor.
Continuous measurement of tensile load,
displacement and suction (-u w : negative pore waterpressure) are done.
In case of unconfined compression test, theconsolidated specimen from UCCM (Fig. 3(b)) ispushed out and then cut into a length of little longer
than 10 cm. Finally trimming of upper and lower
surfaces of this cut specimen is done so that test
specimen of exactly 10 cm length is obtained. Test
specimen is set up on the unconfined compression
testing apparatus shown in Fig. 2. Once the suction
measured at the lower pedestal becomes constantthen compression is started at a constant rate of 0.1
mm/min.
Unconfinedcompressive
stress,displacement (or axial strain) and suction aremeasured simultaneously.

0

12

-2

10

-4

8

-6

6

-8

4

-10

2

-12
-14

Tensile stress (kPa)

Suction (kPa)

Suction (ped)Suction (side)
Tensile stress

0
0

10

20 30 40
Time (min)50

Fig. 7 Tensile stress, suction (ped) and suction (side)
Suction (ped)Tensile stress25
20

Suction (kPa)In Figs. 5 and 6, the effect of tensile pulling rateis shown. With the increase in tensile pulling rate,
there is increase in tensile stress. Here, the medium
value of tensile pulling rate, 0.1 mm/min is chosen
for comparing the tensile strengths values withothers.

15
105

Tensile stress (kPa)

0
-5
-10
-15
-20
-25
-30
-35
-40

TEST RESULTS AND DISCUSSIONS

0
0 10 20 30 40 50 60 70
Time (min)measured during the tensile test (50 kPa).

Suction (ped)Suction (side)
Tensile Stress0

Suction (kPa)-10

Fig. 5 Tensile pulling rate effect (P′ c 200 kPa).

-20
-30
-40
-50
0

40
35
30
25
20
15
10
5
0

Tensile stress (kPa)

Fig. 8 Tensile stress, suction (ped) and suction (side)
measured during the tensile test (200 kPa).

10 20 30 40 50 60 70
Time (min)Fig. 9 Tensile stress, suction (ped) and suction (side)
measured during the tensile test (300 kPa).
In Figs. 7, 8 and 9, the tensile stress curves alongwith the measurement of suction at the pedestal

Fig. 6 Tensile pulling rate effect (P′ c 50 kPa).
616

GEOMATE-Nagoya, Nov.13-15, 2013(ped) and side ceramic discs from the start to end of
the tensile pulling test are shown. As seen, tensile
pulling is started when the values of suction become
almost constant. Although there is little variation in
the values of suction measured at the pedestal andside ceramic discs, they show almost same trendwith almost closer values.
In case of tensile stress curves, a peak value isseen showing the tensile strength (q t ). Around thetensile failure, there is an increase in suction values.
(suction at failure).
In Figs. 10, 11 and 12, unconfined compressive
stress and suction (measured at pedestal ceramicdisc) from the start to end to the test are shown. Herealso, the compression is started only after the initialsuction value of specimen became constant. The
peak value of unconfined compression curve given
the unconfined compression strength (q u ). Just near
the compressive failure, the change is suction value
is seen. Here, in contrary to tensile test, decrease insuction values at failure is seen.

and at failure. With the increase in the consolidationpressure, there is increase in tensile as well as
unconfined compressive strengths. The ratio ofq t /P′ c lies in the range of 0.13 to 0.21 and the ratioof q u /P′ c lies in the range of 0.35 to 0.56.

0

120

-20

100
80

-40

60
-60

40

-80

20

-100

UC stress (kPa)

Suction (kPa)

Suction (ped)UC stress

0020

40 60 80
Time (min)100Fig. 12 Unconfined compression test (300 kPa).
suction (ped)

Table 1 Tensile test results

UC stress

0

35

-5

25
20

-10
15
10

-15

P′ c 'UC stress (kPa)

Suction (ped) (kPa)

30

5
-20

0
0

10 20 30 40 50 60
Time (min)

0

5

qt
(kPa)

q t /P′ c

Ped

Side

Ped

50

10.5

10.7

11.3

-10.3

-0.21

100

17.1

17.0

19.7

-17.0

-0.17

150

20.5

20.4

27.1

20.9

-0.14

200
300

28.8
41.7

25.1
37.0

33.2
43.3

-25.1
-37.8

-0.13
-0.13

(kPa)
50
100
150
200
300

UC stress (kPa)

Suction (kPa)

80
70
60
50
40
30
20
10
0

Failure

(kPa)

P′ c

UC stress

0
-10
-20
-30
-40
-50
-60

InitialTable 1 Unconfined compression test results

Fig. 10 Unconfined compression test (50 kPa).

Suction (ped)Suction (kPa)

Suction (Ped)(kPa)
Initial
Failure
-16.9
-11.5
-30.2
-19.7
-43.3
-25.8
-40.4
-31.2
-77.2
-72.7

qu
(kPa)

qu
/P' c

q u /q t

28.2
43.4
53.1
75.1
111.4

0.56
0.43
0.35
0.38
0.37

-2.74
-2.55
-2.54
-2.99
-2.95

In Tables 1 and 2, the values of q t , q u , initial andfinal (at failure) suction values measured at pedestal(ped) and (side) are shown. Also, the effect ofconsolidation pressure on q t and q u are shown.
Accordingly with the increase in consolidationpressure, both strengths show increment. The ratioof q t /P′ c ranges from -0.13 to -0.21 and similarly,
the ratio q u /P′ c ranges from 0.34 to 0.56.
In the Table 2, the ratio of q u /q t for various
consolidation pressures is shown. For the saturated
NSF clay, this ratio lies between -2.54 to -2.99,

10 15 20 25
Time (min)Fig. 11 Unconfined compression test (200 kPa).
Tables 1 and 2 show the values of tensile
strength, unconfined compressive strength, andsuction values measured just before (initial) the test
617

GEOMATE-Nagoya, Nov.13-15, 2013

showing almost same ratio.
Comparing the suction values measured at thepedestal (ped) during tensile and compressive
failures, their values are almost same (except for 300kPa). This shows that the suction values at failure inboth tests will be same.
CONCLUSION
Here, the effect of tensile pulling rate on tensile
strength is checked. At the same time the ratios
q t /P′ c and q u /P′ c as well as the strength ratio, q u /q t
and suction measured at failure of both tests areshown. From the tensile test as well as unconfinedcompression test with suction measurement,
following conclusions are made;1. Tensile strength increases with the increase
tensile pulling rate.
2. Both tensile strength and unconfinedcompression strengths increase with the increasein the consolidation pressure. The ratio of q t /P′ cand q u /P′ c are -0.13~-0.21 and 0.34~0.56,
respectively.
3. The ratio of q u /q t for the saturated NSF clay isfound to be in the range of -2.54~-2.99, showing
almost the same value.
4. Suction values measured at the pedestal during
failure in both tests show almost same values,
except for the case of 300 kPa consolidationpressure.
REFERENCES[1] Nahlawi, H., Chakrabarti, S. and Kodikara, J.,“A direct tensile strength testing method forunsaturated geomaterials”, Geotechnical Testing
Journal, 27, 4, 2004, pp. 356–361.
[2] Tamrakar, S.B., Toyosawa, Y., Mitachi, T. and
Itoh, K., “Tensile strength of compacted andsaturated soils using newly developed tensile
strength measuring apparatus”, Soils andFoundations, 45, 6, 2005a, pp. 103-111.
[3] Tamrakar, S.B., Mitachi, T., Toyosawa, Y. and
Itoh, K., “Development of a new soil tensile
strength test apparatus, Proc., Geo-Frontiers
2005, Geotechnical Special Publication 138(CD-ROM) Site Characterization and Modeling,
ASCE, Reston, Va., 2005b.

618

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

COUPLED ANALYSIS OF BIFURCATION AND SHEAR BAND IN
SATURATED SOILS: EFFECT OF CHARACTERISTIC LENGTH
SCALEPeijun Guo
Department of Civil Engineering, McMaster University, Hamilton, Ontario, Canada

ABSTRACTFor saturated soils, owing to its inherent dilation or contraction feature under shearing, the presence of pore
fluids alters the deformation process and may either facilitate or delay material instability or bifurcation. A
perturbation approach is used to investigate the bifurcation of saturated soils sheared under undrained conditions.
Even for rate-independent materials, the diffusion of pore pressure involves a certain characteristic length scale(or time scale) and the rate effect. The coupling between soil skeleton deformation and pore fluid can result indifferent types of bifurcation, in the form of localization of soil skeleton, the diffuse mode of either soil skeleton
or pore pressure. The diffuse mode is activated at the state near the peak deviator stress and it is delayed when
the inertia effect is taken into account. When pore pressure bifurcation occurs, the thickness of shear band isaffected by the rate of deformation, the amplitude of strain difference across the shear boundary.
Keywords: Bifurcation, Shear band, Instability, Perturbation method

stress-strain relations are formulated using the
mixture theory. The sign convention in continuum
mechanics is adopted; i.e., compressive stresses andstrains are referred to as negative.

INTRODUCTION
The bifurcation and unstable behaviour of soils
have been extensively investigated both analyticallyand experimentally. It has been shown that soil
specimens uniformly stressed may undergo nonuniform strains such as surface buckling, volume
instability, or shear banding at certain critical statesof stress or strain [1]-[7]. Conventional bifurcation
analysis, such as the Thomas-Hill-Mandel shearband model [7], consists of finding perturbation
solutions (i.e., difference between the heterogeneousandhomogeneous
fieldsofincremental
displacement) that satisfy the constitutive law andthat are compatible with boundary condition. Somepublished researches have different conclusions on
the effect of pore fluids on bifurcation anddeformation instability of saturated soils under
undrained conditions (see, for example, [1], [2], [6]and [7]).
In this paper, a perturbation approach is used toinvestigate the bifurcation of saturated soils sheared
under undrained conditions. The mixture theory isused to formulate the governing equations of the allphases in the soil. Depending on material properties
and the rate of shearing, the variation of perturbationin both pore pressure and soil skeleton deformation
may result in either diffuse or localized bifurcation
modes.

Stress-Strain Relations and Governing Equations
Stress-strain relations
Following Rice [6], let us consider a layer ofsaturated soil sheared in plane strain, as shown in
Figure 1. Within this layer, all field quantities vary
only with y (across the layer) and time t. The shear
strain γ and volumetric strain ε are expressed as:

g=

ｶ ux
,
ｶy

e=

ｶ uy
ｶy

(1)

where u x and u y are displacement components of amaterial point. Strain rates are decomposed into

PROBLEM FORMULATIION
Figure 1: A layer of saturated soil of 2ℓ thickness
subjected to simple shear

In this section, the governing equations for fullysaturated soil subjected to simple shear and the619

GEOMATE-Nagoya, Nov.13-15, 2013

1 ｶn ｶe 1 ｶr s=+
t rs t1- n telastic and plastic components such thateij = eije + eijp . The elastic shear and volumetric-strain rates areg e = t / G,e e = s ｢/ M(2)n ｶr w
ｶ-e 1 n ｶ r s++ｶt
r s ｶtr w ｶtparticles respectively. By introducing Darcy's law
q= -

k ｶp
r w g ｶy

in

which

is

the

hydraulicspecific discharge and n is the porosity of soil. The
mass balance equation, Eq. (8), for the fluid phasecan be rewritten as(3)-b D = sin y m ) are both assumed to be functions ofｶ 踐- k ｶp ・ ｶe 1 n ｶr sn ｶr w
・・++・・=・ r w g ｶy ・
r s ｶtr w ｶt
ｶy ・
ｶt
顏

(9)

Equations of linear momentum balance

appropriate hardening variables. It should be notedthat bD is positive for dilation and negative for

The equations of the linear momentum balance
are established using the mixture theory. In mixture
theory, the linear momentum balance must holdseparately for each constituent and for the wholemedium. The interaction forces between the solidand fluid phases and the linear momentum resulting
from the mass transfer should also be included in the
momentum balance. For a constituent α, the balanceof linear momentum reads

contraction. The plastic shear strain rate g p isrelated to plastic volumetric strain rate e p by
(4)

Following the standard procedure in the theory ofelasto-plasticity, the incremental stress strain
relations are expressed as [6]:s ija, j + n a r a gi + pi = n a r a(5)

ab ( dt + mds ｢) ・
1 ・踐
・・
de =
・・ds ｢+・M顏hkconductivity of the material, q = n(vwy - vsy ) is thedilitancy y m (and hence µ and the dilitancy factor

dt + mds ｢・1踐
・・
dg = ・・dt +
・
・
G顏
h

(8)

vw and vs are the velocity of water and solid

The mobilized friction angle j m and the angle ofe p = b D ( e, g p , g p )g p

ｶy=in which wy = vwy - vsy is the pore velocity of water,where G and M are the shear and constrained
modulus, respectively. The constrained modulus canbe related to the shear modulus and Poisson's ration by M = 2G(1 - n ) / (1 - 2n ) .
The linear Mohr-Coulomb model is selected as
the constitutive model, for which the yield function
F and plastic potential Q are expressed
F = t + s ｢m( e, g p , g p ); Q = t + s ｢b D ( e, g p , g p )ｶ (nwy )(7)

D 2uiaDt 2(10)

where s ija is the partial Cauchy stress tensor for the
α-th phase, pi is the interaction force (i.e, the dragforce) component and gi the gravity component.
For a two-phase material, the linear momentum
balance for the bulk material requires

where h = - s ｢ht / G , ht = dm/ dg , a = M / G .
Under undrained conditions, setting de = 0 results
in
p

ab D
h + abmGdg
dt =Gdg , ds ｢ = H
1 + h + abm

s ij, j + fi = r

(6)

ｶ 2ui
ｶ wi
+ nr w
ｶt2
ｶt

(11)

with wi = vwi - vsi , fi = (1 - n ) fis + fiw is the bulk
body force per unit volume, r = r s (1 - n ) + nr w iswhere H = 1 + h + abD m , G * = G( h + abm) / H .

the bulk density, s ij is the Cauchy stress tensor of
Equations of mass balance

the mixture as a whole. The interaction (or the dragforce) induced by water flow is expressed as ([8][9]):When taking into account the compressibility of
pore-fluid and soil grains, the equations of massbalance for solid phase and fluid phase read ([7],page 147):pi =nr w gn2r w gqi =(vwi - vsi )kk

It follows that
620

(12)

GEOMATE-Nagoya, Nov.13-15, 2013

ｶ u ( y,t )= Gexp(St + ib y )ｶtp ( y,t ) = P exp(St + ib y )g ( y,t ) =n2r w gd 2uiw
dp-n+ nr w gi (vwi - vsi ) = nr w
dxi
k
dt 2

- (1 - n )ｶ p ｶ s ij+
+ (1 - n )r s gi
ｶ xi ｶ x j

where P and Γ are the amplitude of initial
perturbations in the shear strain and pore pressure,respectively; S is a quantity reflects the growth of a
perturbation with time; b  = p / 2 with l = 2 being
considered as the wavelength of the perturbation.
The initial value of maximum perturbation shear
strain rate is g 0 = g( y,t ) / t|t = 0 S . When S > 0,a perturbation grows exponentially with time andeventually becomes infinite. Correspondingly, anegative S shows that the perturbation is stable.
Perturbation induced shear stress and volumetricstrain are determined from the stress-strain relationasd 2uis n 2 gw
(vwi - vsi )dt 2
kd 2uisdwi
ｶ p ｶ s ij 鴿+
+ ・(1 - n )r s + nr w gi = r+ nr w
2dt
dt
ｶ xi ｶ x j= (1 - n )r s

for the fluid phase, solid phase and the mixture,
respectively.
For a layer of soil subjected to simple shear as
illustrated in Figure 1, when applying the stressstrain relations and neglecting the compressibility ofwater and soil grains, the equation of massconservation for the fluid phase and the linear
momentum balance are simplified asbD ｶg
ｶs ｶp ・k ｶ p 1 + h + ab D m踐
・
=
+
+
・
・
2
・
・
r w g ｶ+yaｶG (1 ｶ h) 顏+t ｶ t
1 h t

(15)

t = - mp + hg p ,

e =

p
+ b D g p
M

(16)

2

(13)

The mobilized frictional coefficient µ, the dilatancy
factor bD and the plastic modulus h should beunderstood as functions of the unperturbed
homogeneous strains. The evolution of theperturbations must satisfy the equations for massconservation of water and the linear momentum
balance:

2
2
2
2
踐2
h 鴿
・G ｶ g - m・・ｶ s + ｶ p ・・ = (1 - n )r s d g + n r w g ｶ g
2
2
2 ・
2
・
・
1+ h ・ y
h 顏y
y ・
dt
k
t

(14)
COUPLED PERTURBATION ANALYSIS FOR
SATURATED SOILS

1 + h + ab D m ｶ p1 ・踐
ｶ g ・k ｶ 2 p
=
+ bD
・
・
2
1 h ・顏
r w g ｶ+y
aGｶ
tｶ
t・

Perturbation Equations

(17)

h 踐
d 2 g n 2 r w g ｶ g
ｶ 2 g m ｶ 2 p ・・・ = (1 - n )r s 2 +
(18)
G 2・
2 ・
・
h y ・
dt
k
t
1+ h 顏 y

For a shear soil sample under constant normal
stress σ as illustrated in Figure 2, let us consider
small perturbations, u ( y,t ) and p ( y,t ) , within theshear band over the homogeneous displacement andin pore pressure fields, u( y,t ) and p( y,t ) , outside
the band. For continuous bifurcation, the materials
within and outside the shear band can be describedby the same stress-strain relation [6]. We study
spatial perturbations at zero normal stressperturbation s = 0 with the following forms:

Considering the perturbations in Eq. (15), the above
equations expressed in terms of the magnitude of
initial perturbations are given as- Pb2 =

踐r wg ・
1 + h + ab D m
・
P + b D G・・・S・
k (1 + h)顏
aG

鴿
n2r w gh 踐m・
(1 - n )r sS +- GG+ P ・GS
b2 = ・
・
・
・
・
顏
h
k
1+ h ・
・

(19)
(20)

Elimination of P and Γ from Eqs. (19) and (20)yieldsf (S ) = A0S 3 + AS 2 + BS + C = 0

where
Figure 2: Inhomogeneous displacement field
induced by a shear band

A0 = (1 - n )kr s H / ( aG )A = (1 - n )r s b 2k 2 (1 + h ) + n 2 H / ( aG )

621

(21)

GEOMATE-Nagoya, Nov.13-15, 20132
B = kb 2 鴿・n (1 + h ) + ( h + ab D m) / a

Eq. (24) has real roots when h ｳ max( h1cr , h2cr ) or

C = Gb 4k 2 h;h ｣ min( h1cr , h2cr ) . During frictional hardening (i.e.,k = k / (r w g )h > 0 ), D

For perturbations of long wave length (i.e.,b ｮ 0 ) corresponding diffuse bifurcation, Eq. (21)yieldsS= -crcrn < 1 / a ) and h > h1 > h2 > 0 . It can be shownthat any bifurcation prior to h = h1cr is stable. Ath = h2cr , the root of Eq. (24) isn<0(1 - n )kr s
2

(22)
S= -

The negative value of S shows that the perturbationis stable.
For perturbations of short wave length that
corresponds to thin shear band when b ｮ ･ , Eq.
(21) takes the following form
鴿aG 2 b 2k h
A0S 3 + Gb 2k h = 0; S = - ・・(1 - n )kr s H
・

1/ 3

踐
1
・
・
・・
> n > max ・・ - b D m,
・
・
・
a
a
b
m
顏
D

When the inertia effect of the fluid phase inconsidered, Eq. (21) can be rewritten as after
applying Eq. (24):and ( A - A1 ) are positive, for unstable perturbation(S > 0), the condition f (S ) = 0 requires f1 (S ) < 0 .
As the value of f (S ) decreases with decreasing
hardening parameter h, the inertial effect delays thebifurcation of deformation.
DIFFUSE BIFURCATION VS. LOCALIZEDBIFURCATIONThe bifurcation of saturated soil deformation
under undrained conditions may manifest itself ineither diffusive mode or localized mode, dependingon the wavelength of the perturbation, which isdetermined as l = 2 = p / b . We examine thefollowing cases.

(25)

with
cr

a (n -(28)

where ( A - A1 ) = (1 - n )r s b 2k 2 (1 + h ) . As both A0

where A1 = n 2 H / ( aG ) , B and C are the same as
defined previously.
The stability of perturbation evolution can be
explored by examining the nature the roots of thequadratic equation in Eq. (24). The determinantof Eq. (24) can be expressed as
2(27)

Instability with Inertia Effects(24)

D = a - 2k 2 b 4 (1 - a n 2 ) (h - h1cr )(h - h2cr )(26)

In other words, depending on the materials
properties, unstable perturbation is possible forsaturated soils with the porosity satisfying the above
constraints and when h < h2cr .

f (S ) = A0S 3 + (A - A1 )S 2 + f1 (S )f1 (S ) = A1S 2 + BS + C = 0, h2 =

1 - an)- bD m2

1

Let us first examine the stability of deformation
when the rate of deformation is small enough andhence the inertia effect can be neglected.
Corresponding to this assumption, Eq. (21) is
simplified as

1 - an2

)(

or

(23)

Instability without Inertia Effects

h1cr =

(

踐
1
1 ・・
・
n < min ・・ - b D m,,・・顏a - b D m a ・・

DEFORMATION INSTABILITY ANALYSIS- b D m)2

2a n 1 - a n - b D m n -which is positive when

which implies that perturbations of very short wave
length are generally stable when h > 0 . Obviously,
for the perturbation zone with finite thickness as
illustrated in Figure 2, the two extremes at b ｮ ･and b = 0 , however, undermine the spatial variationof both shear strain and pore pressure. Consequently,
it is more relevant to examine evolution of
perturbations under general condition with limited
values of wave number β or the wave length l = 2 .

a (n +

0 is possible only when 1 - a n 2 > 0 (orCase 1: Zero pore pressure perturbation P = 0- b D m)2

For zero pore pressure perturbation (i.e., P = 0),
according to the mass conservation in Eq. (19), the1 - an2622

GEOMATE-Nagoya, Nov.13-15, 2013

non-trivial perturbation solution with non-zero valueof G exists only if bD = 0 . The balance of linear
momentum, Eq. (20), yields
Gh
1
=2
b
1+ h

1
(1 - n )r sS 2 +which requires -n2r w g< S < 0 when h > 0.
k(1 - n )r sl = pRecalling that the amplitude of shear strain rate
associated with the perturbation g 0 = SG , Eq. (29)becomes
s 
h
kGG 鴿
1
・1 + k(1 - n )r g 0
=2
2
2
n r wg Gb
1 + h n r w g g 0 ・
・

- 1

Gh
2k
(1 - n )r s
n2r w g 1 + h(30)

One observes that l min is affected by the porosity,
hydraulic conductivity and the hardening parameterh. However, the bifurcation is stable since S < 0 .
In general, for saturated soils under undrained
conditions, a displacement perturbation may induce
local volume change and hence pore pressure
variation. As such, zero pore pressure perturbation P= 0 is only a special case that is applicable toimpermeable soils or soils with very low
permeability.

It has been known that the time (t c ) required toestablish pore pressure equilibrium is related to thecharacteristic length scale (l c ) and the diffusion (orconsolidation) coefficient c v by lc = cv tc . When l c
is smaller than the perturbation wavelength λ for thetime of interest t c , the inhomogeneous pore pressure
distribution described in Eq. (15) could bemaintained. For this case, the coupled bifurcation
analysis under isochoric conditions as discussed
previously is valid. Given cv = k / ( mv r w g ) that
depends on the hydraulic conductivity k and thecoefficient of volume compressibility mv of soil,
with a decrease of k and the modulus of soil, thediffusion length may decrease to its minimum value
at the material micro-structural length scale that isabout the diameter of soil grains [10]. On the other
hand, if l c is larger than λ, the dissipation of porepressure within the zone of perturbation and porewater flow will take place, accompanied by the local
volume change ([2], [3], [11]). When the diffusion
scale length is of the order as the dimension of thespecimen, diffuse instability takes place. From a
perturbation analysis of pore pressure when both thenormal and shear stresses are unchanged (i.e.,s = t = 0 , Garagash [10] related l c to the shear

For small perturbations, when neglecting theinertia effect and eliminating Γ from Eqs. (19) and(20), one obtains after applying g 0 = SG :2

(32)

Bifurcation is possible when β has real values,
which requires
(33)

with
hcr 3 =

(35)

CHARACTERISTIC LENGTH OF PORE
PRESSURE DIFFUSION

Case 2: non-zero pore pressure perturbation P ｹ 0

b D < 0, h < hcr 3 , 1 - a n 2 > 0mkPr w g n - b D m g 0• Bifurcation with P ｹ 0 can take place only incontractive soil with bD < 0 ;• The perturbation wavelength λ tends todecrease as the shear strain velocity increases;• Both the hydraulic conductivity and porosity ofsoil have influence on λ;• As the pore pressure difference within andoutside the shear band increases, theperturbation wavelength λ will increase.

(31)

1k (h + ab D m)- a (1 + h)n P
=
2
b
r wg
ab D n 2
g 0

(34)

It should be noted that the wavelength tends toincrease as h decreases with continuous plastic
deformation. In summary, the following conclusions
can be drawn:

The minimum perturbation wavelength l min isdetermined asl min = p2

It is found that unstable bifurcation is possible when
the hardening parameter h = h2cr , with thewavelength being(29)

n2r w gSkk (1 - a n )h + a (b D m- n ) Pr wg
ab D n 2g 02

l = 2 = p

a (n 2 - b D m)
1 - an2

The corresponding wavelength of perturbation is623

GEOMATE-Nagoya, Nov.13-15, 2013

strain rate g by lc =ACKNOWLEDGEMENTS( k / r w g ) M g - 1 with M being

the constrained modulus of soil.
For simplicity, let us only examine thebifurcation and deformation stability close to thepeak of the effective stress path whenh = hP = - amb D . At this state, the dilitancy factor is

Funding provided by the Natural Sciences andEngineering Research Council of Canada isgratefully acknowledged.
REFERENCES

generally bD < 0 . According to Eq. (34), thewavelength length of perturbation is鴿 k 1 - ab m PDl G *= 0 = p ・・- r g
b
g 0
D
・ w

[1] Vardoulakis I, Goldscheider M, Gudehus G,"Formation of shear bands in sand bodies as abifurcation problem", Int. J. Numer. Anal. Meth.
Geomech. 2(2), 1987, 99–128.
[2] Finno RJ, Viggiani G, "Shear bands in planestraincompressionofloose
sand",
Geotechnique 47 (1), 1997, 149–165.
[3] Desrues J, and Viggiani G, "Strain localizationin sand: an overview of the experimental results
obtainedin
Grenobleusing
stereophotogrammetry", Int. J. Numer. Anal. Meth.
Geomech. 28, 2004, 279–321.
[4] Kodaka T, Higo Y, Kimoto S and Oka F,"Effects of sample shape on the strain
localization of water-saturated clay", Int. J.
Numer. Anal. Meth. Geomech. 31, 2007, 483521.
[5] Nicot F, and Darve F, "Diffuse and localized
failure modes: Two competing mechanisms",
Int. J. Numer. Anal. Meth. Geomech. 35, 2011,586-601.
[6] Rice JR, "On the stability of dilatant hardening
for saturated rock masses", J. GeophysicalResearch, 80, 1975, 1531-1536.
[7] Vardoulakis I, and Sulem J, Bifurcation
Analysis in Geomechanics. Chapman & Hall:
London, 1995.
[8] Hueckel TA, "Water-mineral interaction inhydromechanics of clays exposed toenvironmentalloads:amixture-theory
approach", Can. Geotech. J. 29, 1992, 10711992.
[9] Loret B and Prevost JH, "Dynamic strain
localization in fluid-saturated porous-media", J.
Eng. Mech. 117(4):, 1991, 907-922.
[10] Garagash DI and Rudnicki JW, "Stability of
undrained deformation of fluid-saturated
geomaterials", In: Proceedings of the 9thInternational Symposium on Plasticity (Khan A
and Lopez-Pamies O Eds.), 2002, 492-494.
[11] Guo P, "Undrained shear band in water
saturated granular media: a critical revisiting
with numerical examples", Int. J. Numer. Anal.
Meth. Geomech., 37(4), 2013, 353-373.

1/ 2

(36)

which can be related with the characteristic lengthscale (l c ) as
鴿1 - ab m P
l G *= 0
D
= p・
・bD
lc
M
・

1/ 2

(37)

which implies that perturbation wavelength exists
when bD < 0 . Depending on the value of bD , theperturbation wavelength may be smaller than or of
the same order as the characteristic length scale (l c ).
In addition, since g 0 = SG , one may conclude thatthe perturbation growth rate is inversely proportional
to the square of the wavelength. Localized
deformation mode with small shear band thickness
cannot be precluded; however, it will experiencemaximum amplitude growth and cause instability
comparing with diffuse bifurcation at this point.
CONCLUSION
A perturbation approach is used to investigate
the bifurcation of saturated soils sheared under
undrained conditions. Even for rate-independent
materials, the diffusion of pore pressure involves acertain characteristic length scale (or time scale) andthe rate effect. The coupling between soil skeleton
deformation and pore fluid can result in different
types of bifurcation, in the form of localization ofsoil skeleton, the diffuse mode of either soil skeleton
or pore pressure. When uniform pore pressure,bifurcation can only take place when soil has no
militancy (i.e., bD = 0 ). On the other hand,bifurcation with P ｹ 0 can take place only incontractive soil with bD < 0 . The perturbation
wavelength λ tends to decrease as the shear strain
velocity increases, and it is also affected by thehydraulic conductivity and porosity of soil.

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BEARING CAPACITY OF SOIL REINFORCED WITH SOIL-CEMENTCOLUMNS FORMED BY THE DEEP MIXING METHOD

1

Ahmad Safuan A Rashid1 and Jonathan A Black2
Faculty of Civil Engineering, University Teknologi Malaysia, Malaysia; 2 Department of Civil and
Structural Engineering, University of Sheffield, United Kingdom

ABSTRACTThe paper presents on a series of sl-scale pne strain 1g physical model tests designed to examine the bearing
capacity of soil-cement columns formed via Deep Mixing (DM). Pre-formed soil-cement columns 24mm indiameter were installed in a soft clay bed with the improvement area ratios, ap, was 26% beneath a rigid
foundation of width 100mm. Two types of column installation which is fully and partially penetrated were
investigated in the laboratory scale. Particle Ie Velocimetry (PIV) was implemented in conjunction with close
range photogrammetry in order to track soil displacement during loading from which the failure mechanisms
were derived. Bearing capacity performance was verified using numerical analysis software (LimitState:GEO).
The bearing capacity increased between 78% and 140% from the untreated soil model.
Keywords: Bearing Capacity,Soil Cement Column, Deep Mixing Method, Particle Image Velocimetry (PIV)

A model of a soft ground was prepared in a rigid
400 mm in length x 150 mm in width x 430 mm indepth aluminum box as shown in Fig. 1. The front
side of the box was fitted with a transparent Perspex
panel to allow a real time observation on soil
movements during the loading tests. Speswhitekaolin clay was used to model 200 mm thick of thesoft ground. The foundation soil model was preparedin slurry form and then was consolidated inside thetesting chamber to achieve a strength of 5 kPa.

INTRODUCTION
Deep Mixing (DM) is a soil modification
technique commonly employed to improve thebearing resistance of soft soil ground. Soil is mixed
in column form with a cement stabilising agent that
improves the engineering properties of soft ground,providing increased strength and stiffness, as well as
reduced permeability [1], [2], [3]. A number oflaboratory physical model and field tests have been
conducted in order to evaluate the ultimate bearing
capacity of soft soil reinforced via DM [4], [5], [6],[7], [8], [9], [10], [11], [12]. However, fewer
attempts have been made to study the performance
between fully and partially penetrated cases of deep
mixing method.
This paper presents results obtained from a seriesof small-scale experiments conducted using fully
and partially penetrated soil-cement columns in arectangular group formation, with improvement area
ratios of 26% (corresponding to 9 columns) andloaded to failure under a rigid footing. Failure
mechanics throughout the full loading history wereassessed in terms of soil displacement measurement
using Particle
Image
Velocimetry (PIV),
complemented by post examination of the columns
via model dissection. Numerical analysis in the formof an Ultimate Limit State software program(Limitstate:GEO) was employed to validate thelaboratory results.

Fig. 1 Equipment and test setup.
Pre-formed 100mm (partially penetrated) and
200mm (fully penetrated) long soil-cement columns
were then prepared by mixing the kaolin slurry(twice its liquid limit) with 15% of Ordinary
Portland Cement (OPC) derived from a kaolin dry
mass. The slurry was subsequently poured in two
equal layers into a Perspex tube of 23.5 mm indiameter, 100mm and 200mm in length using a 20

TEST PROCEDURES
Model Preparation

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GEOMATE-Nagoya, Nov.13-15, 2013

ml syringe, with the ends of the tube sealed using
adhesive. Air bubbles were removed by vibration,and the top surface was levelled and sealed using acap to prevent moisture loss. The soil-cement
columns were cured for 7 days at a controlled room
temperature of 20oC. The columns were carefully
removed from the casing using a specially-designed
extruder system before being installed into the clay
bed.
Following the removal of the consolidation
piston plate and filter sheet, a thin-wall brass tube
with a 25 mm outer diameter was pushed inside themodel ground at predetermined locations into a
rectangular pattern made from a drill template tocreate a hole for column installation. Three column
group configurations of 9 representing area
improvement ratios of 26% were considered. An
auger of 23 mm in diameter was used to bore a holeinside the tube. The process was conducted in stages
to avoid soil disturbance and ground heave. The
column was subsequently pushed slowly until itreached a depth of 100 mm from the top of themodel’s ground. A surcharge of 50 kPa was applied
to close the gap between the columns and thesurrounding soil. As previously stated, the stress was
reduced to 5 kPa. The groups of columns were left
inside the soil model for 5 days before the loading
test was conducted. Triaxial compression tests wereconducted to determine the strength of the soil
cement column.
A rigid plate of 100 mm in width and 150 mm inlength to replicate the raft foundation of a building
then was mounted on the model. All the tests were
performed under undrained condition based on
normalized velocity, V, approached [13]. During thetests, the stresses and displacements were recorded
using a load cell and Linear Vertical Displacement
Transducer (LVDT). A digital camera was employed
to capture the soil movements in continuous
shooting mode during the loading test. The
undrained strength and moisture content of the soil
were determined after the test was completed.
PIV algorithm was used to determine the soil
movements during the tests. The deformation wasdetermined by systematically comparing theintensities of patches in the first image to apredefined search zone in the following images (Fig.
2). Artificial texture (Flock) was used to improve thetexture and intensity bandwidth of the kaolin byspreading it on the exposed model surface before thetest was conducted. Calibration test was conducted
to determine the accuracy and precision of the PIV
system. It was found that the difference error
between the real coordinate and coordinate produced
from the PIV was less than 0.050 mm. The error wasconsidered small and insignificant with less than
0.25% from the total penetration of the footing (20mm).

Fig. 2 PIV analysis [14]RESULTS ANALYSIS AND DISCUSSION
Load – Displacement RelationshipThree series of tests (T1, T2 and T3) consists ofuntreated, fully and partially penetrated cases wereconducted on this study and the mechanicalcharacteristics of the ground model and the failure
stress of each test were listed in Table 1. The verticalstress – displacement/width of footing curves
recorded in this study are shown in Fig. 3. The
vertical load for untreated case (Test T1) increases
rapidly with the increase of settlement and reached aplateau at about 0.04 of displacement/footing width.
It can be deduced that the soft clay possessed aductile behaviour. On the other hand, a distinct
stress peak was observed in test T3 reinforced withfully penetrated soil cement column followed bystrain softening. This brittle response could be
attributed to the sudden failure of individualcolumns in the group, thus triggering a loss instrength of the foundation capacity. Meanwhile, forthe partially penetrated columns, a ductile behaviour
is observed, even though a group of soil-cement
columns is installed inside the model bed. Thisbehaviour is believed to have been due to the groupof columns bearing on soft ground.
The load corresponding to the peak and plateau
is taken as the ultimate bearing capacity, qult, of thefooting. Equation 1 was used to determine thebearing capacity factor, Nc (dimensionless) and bothof the tests were compared base on the Nc value. The
average undrained shear strength of the soil, cus, wasused for each case to obtain the factor.
Nc = qult/cus

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GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Mechanical characteristics of the ground
model
Test

cus
(kPa)

cuc
(kPa)

FailureStress, qult
(kPa)

Nc

T1

5.7

-

33.57

5.89

T2

5.6

83.71

90.11

14.08

T3

6.4

87.21

67.14

10.49

columns. A shearing failure of the central column
produced a double small break-out section at the
middle of the column. However, test T3 involved
only a bending failure of the columns at both edgesof the footing. The column bases move outwards byapproximately 20 mm from the top. The column at
the centre penetrates almost vertically downwards,
approximately, by the same displacement as that of
the footing. A combination of shear and bending,and bending failure were observed for fully andpartially penetrated columns respectively.

cus = undrained shear strength of surrounding soil
cuc = undrained shear strength of soil cement column
The value of Nc for the all tests are listed inTable 1. A higher result than the theoretical bearing
capacity factor of 5.14 for a long rectangular (strip)
foundation on clay was found. This might be due tothe non-homogeneity of the soil model and wall
friction between the testing chamber wall and thesoil during the loading. The relative increase inbearing capacity for the reinforced compared to
unreinforced soil was 78% and 140% for thepartially and fully penetrated respectively.

BeforeAfter(a) Test T2

BeforeAfter(b) Test T10

Fig. 3 Vertical Stress vs displacement/footing width
curved obtained from experiments.

Fig. 4 Failure pattern of DM columns under verticalloading

Column Failure Pattern

Ground Deformation

The failure patterns from Tests T2 and T3 arepresented in Fig 4. In the figures, the initial positions
and final positions of the columns are highlighted
for better inspection. Due to the approximately
similar failure mode of the columns in rows, only
the second row from Tests T2 and T3 are presented.
The difference in the failure modes of the columns
in rows may be due to progressive failure that
occurred in the group of columns, in which thecolumns did not fail at the same time but one by one
during loading. For the fully penetrated case,localised shearing of the outer columns wasprevalent at the interface with the footing edges anda bending was observed on the middle of the

The soil displacements over the model soil facewere observed through images captured and PIV
analyses. Figure 4 shows the accumulated
displacement vectors of Tests T1, T2 and T3 derived
from the analyses over a series of images prior to theloading right up to the final penetration depth of thefooting. It can be observed here that the footing
displaced the underlying soil symmetrically. The
failure mechanism obtained from the Tests T1 (Fig.
4a) and T2 (Fig. 4b) result compared well to thetypical Prandtl failure mechanism. The soil adjacent
to and below the footing was deformed over a
distance of approximately 100% of the footing
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GEOMATE-Nagoya, Nov.13-15, 2013

width, which is similar to the Prandtl failure
mechanism. Generally, a deeper failure mechanism
than the test T1 and T2 sample observed for test T3
as shown in Fig 4c. The soil adjacent to the footing
has been mobilised over a lateral distance of about
100% of the footing width, and over a distance ofapproximately 150% of the footing width below thefooting.

(a)

Validation of the Laboratory Result
The LimitState:Geo software, developed basedon Discontinuity Layout Optimization (DLO)
procedure was employed to validate the present
laboratory results [15], [16]. The dimensions of thenumerical model matched those of the testing
chamber. To perform the analysis, a rough interface
layer was assumed and applied between the groundmodel and the rigid footing. In addition, a fixedboundary was applied on the soil model and a nodal
density of 1000 nodes was used. An homogenize
method was used to analyse the soil model treatedby the soil cement column. The values of bearing
capacity factor Nc produced from the software arelisted in Table 2. Differences ranging from 7.4% to19.2% are found by comparing the results from theboth Nc obtained from the laboratory and theLimitState:GEO software. The difference could be
due to the friction between wall and the soil model
during the loading test.

Test T1
Table 2 Comparison of experimental results with
LimitState:Geo
Test

T1
T2
T3

Nc,Exp =(qult/cus)
(a)
5.89
14.08
10.49

Nc,limit =(qult,limit/cus)
(b)
5.45
12.16
8.48

qlimit = Failure stress
LimitState:Geo software.
(b)

Test 2(c)

Test 3Difference(%)(b) to (a)
-7.4
-13.6
-19.2

generate

from

the

Figure 5 shows the pattern of failure surface
produced by the PIV analyses for all tests that wassuperimposed on the computed failure pattern.
Generally, the sense of the soil movements for bothcases and the extent of displacement field (PIV
analysis) predicted quite well with the software.
However, the soil movement tailed off with distancefrom the footing. For the treated cases, thedifference in observations from both analyses could
be due to the fact that Limitstate:GEO is based on an
ideal rigid plastic material with no pre-failure strain,thus eliminating loading penetration in developing
the failure mechanism, in addition to the comparison
being limited by 3D column movement away fromthe viewing window.

Fig. 5 Ground deformation produce by PIV analyses

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GEOMATE-Nagoya, Nov.13-15, 2013

physical model tests. Numerical modelling based on
the Discontinuity Layout Optimization (DLO)
approach was used to verify the laboratory results
and mechanism patterns produced by the Particle
Image Velocimetry analyses (PIV). Several
conclusions that could be made from both thephysical and numerical modeling are listed below:
1) The relative increase in bearing capacity forthe reinforced compared to unreinforced
soil was 78% and 140% for the partiallyand fully penetrated respectively2) A combination of shear and bending, andbending failure were observed for fully andpartially penetrated columns respectively.
3) The soil adjacent to and below the footing
for the untreated and fully penetrated was
deformed over a distance of approximately
100% of the footing width, which is similar
to the Prandtl failure mechanism. While, adeeper failure mechanism than theuntreated and fully penetrated sample
observed for partially penetrated case.
4) LimitState:Geo software shows a good
agreement of Nc values with value obtained
from the laboratory work.
5) The failure patterns for all cases producedby the LimitState:Geo show slightdifference compared to the PIV analyses.
The difference was due to the different
material model and the effect of thecolumns.

(a) Test T1(b) Test T2
NOTATION
B
cus
cuc
Nc
qult

Width of the footing
Undrained shear strength ofsurrounding soil
Undrained shear strength of soilcement column
Bearing capacity factor
Ultimate bearing capacity

ACKNOWLEDGEMENTS
The work was financially supported by
Universiti Teknologi Malaysia and Ministry of
Science and Technology of Malaysia, MOSTI under
Research University Grant (R.J130000.7922.4S051).
(c) Test T3
REFERENCES
Fig. 5 Comparison between failure pattern produce
by LimitState:Geo software and PIV analysis .

[1] Karastanev, D., Kitazume, M., Miyajima, S., andIkeda, T. (1997). Bearing capacity of shallow
foundations on column type DMM improved
ground. Proc. of the 14th Int. Conf. on SMFE, Vol.
3, 721-724.
[2] Porbaha, A. (1998). State of the art in deep
mixing technology: part I. basic concepts and

CONCLUSIONSThe bearing capacity and ground deformation ofa soft clay were investigated based on a series of629

GEOMATE-Nagoya, Nov.13-15, 2013

overview. Ground Improvement, Vol. 2, No. 2, 8192.
[3] Topolnicki, M. (2004). In situ soil mixing.
Ground Improvement, New York, NY: Spon Press,331-428.
[4] Terashi, M. and Tanaka, H. (1981). Ground
improved by deep mixing method. Proceedings ofthe 10th ICSMFE,Vol. 3, 777-780.
[5] Kitazume, M., Ikeda, T., Miyajima, S., andKarastanev, D. (1996). Bearing capacity of
improved ground with column type DMM. Proc. ofthe 2nd International Conference on Ground
Improvement Geosystems, Vol. 1, 503-508.
[6] Kitazume, M., Yamamoto, M., and Udaka, Y.
(1999). Vertical bearing capacity of column type
DMM ground with low improvement ratio. Proc. of
the Int. Conf. on Dry Dry Mix Methods for Deep Soil
Stabilization, 245-250.
[7] Kitazume, M., Okano, K., and Miyajima, S.
(2000). Centrifuge model tests on failure envelopeof column type deep mixing method improved
ground. Soils and Foundations, Vol. 40, 43-55.
[8] Omine, K., Ochiai, H., and Bolton, M.D. (1999).
Homogenization method for numerical analysis of
improved ground with cement-treated soil columns.
Proc. of the Int. Conf. on Dry Dry Mix Methods for
Deep Soil Stabilization, 161-168.
[9] Boussida, M. and Porbaha, A. (2004). “Ultimate
bearing capacity of soft clays reinforced by a groupof columns-application to a deep mixing technique”.
Soils and Foundations, Vol. 44, No. 3, 91-101.
[10] Boussida, M. and Porbaha, A. (2004). Bearing
capacity of foundations resting on soft ground
improved by soil cement columns. International
Conference on Geotechnical Engineering (ICGE
2004), 173-180.
[11] Fang, Z. (2006). Physical and numericalmodelling of the soft soil ground improved by deep
cement mixing method. PhD Thesis, The Hong Kong
Polytechnic University.
[12] Yin, J.H. and Fang, Z. (2010). Physicalmodeling of a footing on soft soil ground with deep
cement mixed soil columns under vertical loading.
Marine Georesources and Geotechnology, Vol. 28,
173-188.
[13] Lehane B.M., Gaudin C., Richards D.J., andRattley M.J. (2008). Rate effects on the vertical
uplift capacity of footings founded in clay.
Géotechnique, Vol. 58, No. 1, 13-22.
[14] White, D.J. and Take, W.A. (2002). GeoPIV:
Particle Image Velocimetry (PIV) software for use ingeotechnical testing. Technical Report CUED/DSOILS/TR322, Cambridge University, Engineering
Department.
[15] Smith, C. and Gilbert, M. (2007). Applicationof discontinuity layout optimization to plane
plasticity problems. Proceedings of the Royal
Society A, Vol. 463, 2461 -2484.

[16] Gilbert, M., Smith, C., Haslam, I., andPritchard, T. (2010). Application of discontinuity
layout optimization to geotechnical limit.
Proceedings of the 7th European Conference on
Numerical Methods in Geotechnical Engineering.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INTEGRATED QUALITY ASSURANCE AND CONTROL FOR DEEP
SOIL MIXING IN WATERWAY PROJECT
S.H. Chew1, C.Y. Tan2, T.Y. Yap3, K.E. Chua4, H.M. Yim5, S.Y. Kee6, T.K. Khoo7 and Ja Naw8
1,2
Department of Civil & Environmental Engineering, National University of Singapore,
Singapore; 3,4,5,6Housing & Development Board, Singapore; 7,8Surbana International Consultants Pte Ltd,Singapore

ABSTRACT
Deep soil cement mixing (DSM) method has gained popularity over the years in Singapore due to theincrease in underground construction over difficult ground conditions. One of the concerns is the quality
assurance and quality control of this technique. Two aspects were evaluated: operational control and evaluationof the treated soil strength. Firstly, for the quality control of the treatment operation, an online record of themixing efficiency, in terms of mixing time, cement content and mixing energy etc; were recorded and evaluated.
After the completion of treatment works, a consistent and rationale methodology was developed for theevaluation of the strength variation of the treated soils over the area and over the depth. These will help in the
final development of the acceptance criteria for such ground treatment works. Illustration of the applicability ofsuch methodology was done in conjunction with a mega-project in Singapore – construction of the Punggol
Waterway. This paper discusses the proposed quality assurance and quality control methodology. It successfully
covers the long stretch of Punggol Waterway in good detail, yielding “accurate” representation of the quality of
the DSM columns installed, thereby, ensuring the quality of the soil improvement works by DSM before
excavation.
Keywords: Deep Soil Mixing, Soil Improvement, Clay, Quality Assurance, Control

INTRODUCTION
Implemented by the Housing & Development
Board, Singapore (HDB), the Punggol Waterway is
Singapore’s first man-made waterway. Its birth
injects a new lease of life to the former agriculture
and farmland, transforming Punggol Town into abustling and vibrant waterfront eco-town.
Construction of the Punggol Waterway had to be
carried out over difficult soil conditions. As such,
Deep Soil Mixing (DSM), which has gained
popularity in the past 10 years in Singapore [1], wasselected as the ground improvement method for theconstruction of Punggol Waterway (Part I). The
overall features of the Punggol Waterway and thesoil profiles at this site can be found in [2]. The
properties of the Singapore Marine Clay treated withcement mixing have been well studied [3], [4].
As DSM is carried out underground, it is difficult
to ascertain its quality after construction.
Furthermore, as deep excavation of about 13m was
required for the construction of the waterway, goodand consistent results for DSM soil improvement
works were required to ensure adequate slope
stability. In addition, DSM was carried out
massively over the site. As such, a rationale,elaborate and representative quality assurance andquality control methodology with clear acceptancecriteria were required for this project.

Fig. 1

Overall site layout

SOIL CONDITIONS & DEEP SOIL MIXINGGROUND TREATMENT DESIGN
Soil investigations comprising of a total of 42
boreholes & 66 numbers of Cone Penetration Tests(CPTs) were carried out for the project. Generally,
the ground consists of filled material overlaying alayer of either soft marine CLAY or Peaty CLAY,
underlined by the original formation of Old
Alluvium, which is a compacted, dense sand layer.
A typical soil profile is shown in Fig. 2.

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GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 2

Soil profile

Deep Soil Mixing (DSM) ground treatment
method is proposed and its design consists ofcolumn diameters of 850mm, with centre-to-centre
spacings of 750mm. Grid patterns of DSM are
installed instead of full blocks of DSM (shown in
Fig. 3). The composite properties of the treated soil
mass were carefully evaluated based on a
purposefully defined ratio of area improvement.

OPERATIONAL QA/QC CONTROL FOR DSM
To ensure the quality of the DSM columns
installed, stringent operational control was set up.
For every column installation, an online record of
the mixing efficiency, in terms of mixing time,
cement content and mixing energy etc; wererecorded. Contractors were required to submit
records of DSM piles installation and compare thatwith the designed curve as shown in Fig. 5. In thisfigure, vertical axis is the depth of penetration, while
the horizontal axis is the time. Superimposed on thesame diagram is the flow rate in each and every
depth. Based on this information, the rate of rotation
can be calculated, which gives an indication of thetime for mixing. The amount of cement mixed withthe soil at that particular depth can be evaluatedbased on the flow rate at that depth. The calculated
rate of mixing and cement used must be consistent
with the design value. Any variation will imply thatthe column was not properly installed and remedialaction must be done.
END RESULT EVALUATION

Fig. 3 Typical grid pattern of Deep Soil Mixing(DSM) Columns

The qualities of the end result of Deep Soil
Mixing (DSM) columns were inspected by coring
the completed columns after 21 days. To provide
consistent and representative quality sampling, theDSM treated area was divided into blocks of 25m
along each bank of the waterway. Sampling was
carried out with two core locations per block. Eachlocation of coring consists of three sampling points(i.e. top, middle, and bottom) from the selected
DSM columns, and the unconfined compressive
strength test is carried out.

The minimum design strength and stiffness of
the individual DSM columns were calculated andlisted as:
Unconfined Compression Strength, qu=1000kPa
Undrained Shear Strength, Cu = 500kPa
Undrained Young’s Modulus, Eu = 200,000kPa
A typical geometry of the waterway with the
DSM columns in place for slope enhancement isshown in Fig. 4. This was done over the whole
2.4km length of the waterway (Part I).

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GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 4

Typical scheme of DSM and Waterway

Fig. 5

DSM pile installation record – design curve633

GEOMATE-Nagoya, Nov.13-15, 2013

The cored location can be accepted if it satisfies
all the above mentioned criteria. Vice versa, thecored location cannot be accepted if any one of thecriteria has not been met. The acceptance criteria are
as illustrated in Fig. 6.

The Conventional QA/QC Criteria
The conventional acceptance criteria for this kind of
DSM works specified that for each sampling point,
the following criteria must be satisfied:a. Total core recovery (TCR) shall be at least 85%
b. Unconfined compressive strength (UCS) shall be
at least 1000kPa
c. Modulus of Elasticity (E) shall be at least
200MPa for each DSM column.
This conventional method indicates highly varied
and inconsistent results. It will be difficult to accessthe overall performance of the DSM blocks based on
the conventional criteria. Hence, an improvement of
the QA/QC criteria is needed.
Improved QA/QC For Completed DSM Columns
The quality assurance and quality control plan
was revised to ensure the quality of DSM columns
installed
complywithspecifications
andperformance requirements. The outlines of thisimproved acceptance criteria are as follow:
Coring tests
The quality of Deep Soil Mixing columns should
be inspected by coring the completed columns
throughout the depth. The coring shall be consistedof at least two cored locations per block of 25m
along each bank of the waterway.
Representative zones along DSM columns
Each cored location is divided into three zones,e.g. Upper Zone, Middle Zone and Bottom Zone. At
each zone, three cored samples is collected. The
samples are taken between each of these coredsamples with clear distance of at least 1m and not
more than 2m. The collected samples were then sent
for laboratory testing for Unconfined Compression
Test to obtain the UCS and modulus parameter.

Fig. 6

Acceptance criteria for DSM Column

ACTUAL CONSTRUCTION WORK
Actual construction works of DSM treatment
were carried out with the above revised operational
QA/QC control.
As an illustration, an operational record very
close to the design curve, yielded a very uniform andgood DSM column as revealed from the coredsample shown in Fig. 7. In comparison, as anillustration for the opposite, an operational recordthat deviates significantly from the design curve wasfound to produce DSM columns that were poor in
quality and highly non-uniform as revealed from thecored sample as shown in Fig. 8. The operational
mixing curves for the DSM treatment to yield goodand bad quality DSM columns are summarized inFig. 9.

Acceptance criteria for Deep Soil Mixing column
The acceptance criteria for unconfinedcompressive strength (UCS) are as follows:a. Average UCS for each zone (average of 3
samples) > 0.9MPa
b. UCS for each sample > 0.1 MPa
c. Average UCS for three zones (average of 9
samples) > 1.0MPa
The acceptance criteria for total core recovery(TCR) area as follows:a. Average TCR for each zone > 75%
b. TCR for each 1m > 10%
c. Average TCR of whole cored location> 85%634

GEOMATE-Nagoya, Nov.13-15, 2013

The evaluation of the end result for the treatedground is thus evaluated based on the above end
result QA/QC acceptance criteria. The result of thelater evaluation is presented below.
Coring samples were extracted from completed
DSM columns using wet boring method. Coring
samples were taken at least 21 days after the date ofcompletion of the columns. A total of 9 test samples
were tested for each coring location. The test results
for unconfined compressive strength and the TCR
for the two coring locations are summarized in Table
1.

Table 1 Summary of two coring locations
Ref
No.

Zone

UCS
(MPa)

Avg
UCS
(MPa)

TCR
(%)

1.23

90%

1.07

100%

0.97

95%

0.99

80%

0.66

90%

1.65

85%

Avg UCS for
whole coring
location
(MPa)

Pass/
Fail

1.09

Pass

1.10

Fail

1.06
TOP

1.15
1.48

N 92-06

1.18
MID

1.14
0.88
0.81

BOT

1.3
0.8
1.00

TOP

1.02
0.96

N 99-01

0.76
MID

0.55
0.66
1.84

Fig. 7

Fig. 8

BOT

Good sample photo

1.34
1.76

The average UCS test results for the top, middle
and bottom zone of the sample location N99-01 are
0.99MPa, 0.66MPa and 1.65MPa respectively. This
result has not met the acceptance criteria withrespect to the UCS criteria. Even though the average
TCR for all three zones passed the acceptancecriteria with respect to TCR, this column would beconsidered as “failed”. Rectification works werethen carried out and additional columns were
installed for this 25m panel.

Bad sample photo

RECTIFICATION

Fig. 9The DSM works for a 25m panel is accepted if
the results of both coring locations within the panel
meet the stated criteria. If at least one coring
location is found to be “failed”, DSM works for theentire 25m panel is not accepted and rectification
work is required to compensate for it. This will
ensure the whole panel achieves the required
treatment quality.
Rectification works was carried out bycomputing the additional number of columns neededto achieve an overall strength equivalent to thedesign strength by computing the number ofcolumns and the in-situ strength of the “failed” DSM
columns with respect to the total TCR.
This concept of compensation takes into accountthe presence of the actual in-situ quality of the failed
DSM columns that has been installed, and does notcompromise the overall quality of the DSM panel
after rectification.

Sketch of operational mixing curves

The average UCS test results for the top, middle
and bottom zone of the sample location N92-06 are
1.23MPa, 1.07MPa and 0.97MPa respectively.
These results have met the acceptance criteria withrespect to the UCS criteria. In addition, the average
TCR for all three zones also passed the acceptancecriteria with respect to TCR. Hence, this column has
been considered as “passed”.

635

GEOMATE-Nagoya, Nov.13-15, 2013

CONCLUSIONREFERENCES

A revised quality assurance and quality control
plan for Deep Soil Mixing treatment for Punggol
Waterway was developed. It consists of two
components: operational mixing control and end
result QA/QC check. This revised plan was carriedout and the results were found to be successful andeffective. It successfully ensured the long stretch of
Punggol Waterway was treated with good quality of
DSM columns.
The end results QA/QC plan also provided gooddetails, yielding accurate representation of thequality of the DSM columns installed, thereby,
ensuring the overall quality of the soil improvement
works by DSM before excavation.

[1] Tan, T.S., Goh, T.L., and Yong, K.Y.,“Properties of Singapore Marine Clays
Improved by Cement Mixing”, ASTM
Geotechnical Testing Journal, Vol. 25 Issue 4,
2002.
[2] Chew, S.H., Tan, C.Y., Yap, T.Y., Chua, K.E.,
Ng, K.C., Khong, Y.C., and Goh, P.L.,“Improving Soft Peaty Soil by Grouted Stone
Columns
Punggol
Waterway
Project,
Singapore” , 14th Asian Regional Conference
on Soil Mechanics and GeotechnicalEngineering, 2011.
[3] Kamruzzaman, A.H.M., Chew, S.H., and Lee,
F.H., “Structuration & Destructuration Behaviorof Cement-Treated Singapore Marine Clay”,
ASCE
Journalof
GeotechnicalandGeoenvironmental Engineering, Vol. 135 no. 4,
2009.
[4] Chew, S.H., Kamruzzaman, A.H.M., and Lee,
F.H., “Physiochemical and Engineering
Behaviour of Cement-Treated Clay”, ASCE
Journal of Geotechnical and Geoenvironmental
Engineering, Vol. 130 no.7, 2004.

ACKNOWLEDGMENTS
Special thanks to contractor Koh Brothers
Building & Civil Engineering Contractor (Pte.) Ltd,and geotechnical contractor – Ryobi Kiso (S) Pte
Ltd.

636

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EMPIRICAL CORRELATION OF SHEAR WAVE VELOCITY AND NSPT VALUE FOR JAKARTA
Achmad Fauzi1, Masyhur Irsyam2, Usama Juniansyah Fauzi3, and Muhammad Addifa Yulman3
Faculty of Civil Engineering and Earth Resources, Universiti Malaysia Pahang, Malaysia; 2Faculty of Civil
and Environmental Engineering, Institut Teknologi Bandung, Indonesia; 3Former Student at Faculty of Civil
and Environmental Engineering, Institut Teknologi Bandung, Indonesia
1

ABSTRACTThis paper proposes an equation representing shear wave velocity (Vs) as a function of SPT blow count (NSPT). The equation is generated by statistical regression of site investigation data at many building project inJakarta. The N-SPT values and Vs values were obtained from the same boreholes between 2005 and 2012. The
Vs values were obtained by the downhole seismic survey. A total of 22 building and 35 borings provided 234
pairs of N-SPT and Vs values were used to get a regression equation. The new and previously suggested
formulae have been compared and evaluated by using the same dataset. Wave propagation analysis require Vs as
an input parameter, and the empirical equation may be useful for estimating Vs at site where only N-SPT data
available. The information of empirical correlation can and perhaps should be considered in developing
microzonation map of Jakarta as inputs in a continuous process of risk assessment and disaster mitigation risk
reduction.
Keywords: Downhole seismic survey, shear wave velocity, standard penetration test, Jakarta soil, in-situ test
SPT and shear-wave velocity for soils from Jakarta
area.

INTRODUCTION
The shear-wave velocity of soils plays animportant role in the design of geotechnicalstructures under dynamic loads. It is used mostly for
determining the seismic site categories (e.g.,Indonesian Building Code SNI 1726-2002) and for
input of ground motion prediction equations whereIndonesia has large strain problems related toseismic loading. In Indonesia, the shear-wave
velocity is typically measured using the seismic
downhole test. However, the equipment is notwidely available and, consequently, the test is
generally too expensive to perform for mostconstruction projects. On the other hand, thestandard penetration test method (SPT) is one of themost common in-situ tests because its equipment is
widely available and it is easy to perform
Numerous relations between SPT blow count, NSPT, and shear wave velocity, Vs, exist in theliterature. Early efforts utilized laboratory results todevelop correlations, and the correlations were
subsequently refined as field measurement of Vs
became more common and data became available.
The most common functional form for the relations
proposed in the literature is Vs=a x N-SPTb, where
the constants a and b are determined by statisticalregression of a data set.
A study to develop correlations among
penetration test results and shear-wave velocity forsoils from Indonesia is currently being conducted.
This present paper present the development of acorrelation between the resistances obtained fromGEOTECHNICAL AND SEIMOTECTONICSETTING
Geological condition
Geologically, the study area, Jakarta is
dominatedbyquaternary
sediment
and,unconformably, the base of the aquifer system isformed by impermeable Miocene sediments which
are cropping out at the southern boundary, whichwere known as Tanggerang High in the west, Depok
High in the middle and Rengasdengklok High in theeast. They acted as the southern basin boundary. The
basin fill, which consist of marine Pliocene andquaternary sand and delta sediments, is up to 300 m
thick.
Individual sand horizons are typically 1 - 5 m
thick and comprise only 20% of the total fill deposits.
Silts and clays separate these horizons [1], [2]. In
detail, Reference [3] differentiated the lithology inthis area into some formations and explained asfollows {Figs. 1}.
a. Rengganis Formation consists of finesandstones and clay stone outcropped in thearea of Parungpanjang, Bogor. Unconformably, this formation is covered bycoral limestone, marl, and quartz sandstone.
b. Bojongmanik
Formation
consistsofinterbedded of sandstone and clay stone, withintercalated limestone.
637

GEOMATE-Nagoya, Nov.13-15, 2013c. Genteng Formation consists of volcanic
eruption material such as andesitic breccias
and intercalated tuffaceous limestone.
d. Serpong
Formation,
intebeddedofconglomerate, sandstone, marl, pumiceconglomerate, and tuffacueous pumice.
e. Coral Limestone, Holocene age and found in
Seribu Island Complex in Jakarta Bay,consist of coral colony, coral fragment, andmollusk shell.
Beside those above lithology, there are foundBanten Tuff, young volcanic eruptive material, fandeposits, paleo and recent beach ridge deposits
which are deposited parallel to recent coastal line.

wave velocity measurements performed using theseismic downhole test method were conducted in
one bore-hole. The coordinate of locations areshown in Table 1 and Fig. 4.

Fig. 3Major tectonic feature of Jakarta region

Table 1 Test location in this study
ID

Fig. 1

Geological map of the Greater Jakarta andits surrounding area.

Fig. 2

Bedrock profile of Jakarta

1
2
3
4
5
6
7
8
9
10
11

Coordinate
Longitude Latitude
106.8336 -6.2282
106.8764 -6.17113
106.9081 -6.15226
106.8277 -6.22972
106.788 -6.23653
106.7976 -6.21092
106.7942 -6.24675
106.6279 -6.24064
106.8267 -6.22923
106.78-6.29142

Soil Types

ID

Soft soil
Soft soil
Soft to stiff soil
Stiff soil
Stiff soil
Soft to stiff soil
Soft to stiff soil
Soft to stiff soil
Soft to stiff soil
Stiff soil
Stiff soil

12
13
14
15
16
17
18
19
20
21
22

Coordinate
Soil Types
Longitude Latitude
106.8384 -6.30495 Soft to Stiff soil
106.8162 -6.21073 Soft to Stiff soil
106.6279 -6.24064
Stiff soil
106.8353 -6.21677
Stiff soil
106.8236 -6.1992
Stiff soil
Stiff soil
106.8143 -6.24707
Stiff soil
106.7847 -6.23671
Stiff soil
Stiff soil
106.8197 -6.21167
106.7893 -6.1691
Soft soil
106.8341 -6.22476
sedangSeismotectonic settings
Jakarta is located in a tectonically very active
area. The study site is surrounded by a number ofactive faults. The Indo-Australia Subduction Zone,
Sunda Fault, and Lembang Fault are the mostimportant earthquake sources in the study site. The
2009 West Java earthquake, which resulted inextensive loss of life and damage to structures
particularly in the Sukabumi Region, was also felt inJakarta and its vicinity. General condition of themayor tectonic features was shown in Fig. 3.

Fig. 4

Locations of geotechnical and downhole
investigations

Standard Penetration Tests were performed along
borings with intervals of 1.5 m to 2m. Standard
Penetration Test procedure and equipment followed
the ASTM D 1586 – 84 [4], “Standard Method for
Penetration Test and Split Barrel Sampling of Soils”.
The resistance of soil is represented by the N-SPT
value. The number of blows of hammer striking
drilling rod to cause 3x6” penetration of the split
spoon at the tip into the soil was counted. The NSPT value is the total number of blows for the last2x6” penetration.
The seismic downhole tests were performed inaccordance with ASTM D7400 – 08 [5]. The tests

TEST PROGRAM
The test program considered in this study was
conducted in 22 locations; in each location a seriesof standard penetration tests and a series of shear638

GEOMATE-Nagoya, Nov.13-15, 2013

were conducted using 3-component, OYO Borehole
Pick Model 3315 geophone and McSeis 24-channel
portable engineering seismograph. The shear-wave
velocity was measured at 1.0 m interval. The seismic
shear-wave was generated using the 28-kgf, T6-6061
aluminum alloy shear-wave source equipped withground coupling spikes. The method is illustrated infigure below.

Table 2 Some existing correlations between N-SPT
and VsAuthor(s)Ohta and Goto (1978)
Imai and Tonouchi (1982)
Sykora and Stokoe (1983)
Jinan (1987)
Iyisan (1996)
Jafari et al. (1997)
Kiku et al. (2001)
Hasancebi and Ulusay (2007)SP
2

associate with each N-SPT value for statisticalregression.

1
Seismogram

1
P

S

2

Recorder

0

50

100

150

ID
A
B
C
D
E
F
G
H
Vs (m/s)
200

250

300

Depth (m)BallooFig. 5

Downhole seismic survey illustration

350

400

450
0

N-SPT
Vs

-5

Geophone triaxial

Equation(s)85.3N0.341
96.9*N0.314
100.5N0.29
116.1(N+0.3185)0.202
51.5N0.516
22N0.85
68.3N0.292
90N0.309

-5

-10

-10

-15

-15

-20

-20

-25

-25

-30

-30

-35

-35

-40

-40
-45

-45
0

PROPOSED EMPIRICAL CORRELATIONSFOR VS–N-SPT

10

20

30

40

50

N-SPT

Fig. 6

A significant number of correlations have been
published on various soil types {Table 2}. Reference[6] pointed out that geological age and type of soil
are not predictive of Vs while the uncorrected NSPT value is most important. Reference [7]examined the influence of the soil type on N-SPT
versus Vs correlation using data collected from anearthquake-prone area in the eastern part of Turkey.
The results showed that, except for gravels, thecorrelation equations developed for all soils, sandand clay yield approximately similar Vs values.
Reference [8] presented a detailed historical review
on the statistical correlation between N-SPT versus
Vs. Reference [9] studied similar statisticalcorrelations using 97 data pairs collected from anarea in the north-western part of Turkey anddeveloped empirical relationships for sands, clays,
and for all soils irrespective of soil type.
Significant differences exist among the various
published relations, which are likely partially causedby differences in geology, but also by errors inmeasurements of N-SPT and Vs. Resolving thedifferences among published relationships is beyond
the scope of this study.
Example data from ID 11 is shown in Fig. 6. The
graphs show the Vs profile and N-SPT profile at thesite. The Vs profiles were typically recorded at 1 m
intervals, whereas the N-SPT values were recorded
at much coarser sampling intervals typically 1.5m orlarger. A number of possible approaches wereconsidered for selecting an appropriate Vs value to

Example variation of N-SPT and Vs forstatistical regression

In this study, 234 data pairs (N-SPT and Vs)
were employed in the assessments. The correlations
were developed using a simple regression analysis
for the existing database. New relationships were
proposed between uncorrected Vs (m/s) andcorresponding N-SPT. {Fig. 7}. The following
relationships with its correlation coefficients (r) areproposed between Vs (m/s) and N-SPT values.

Vs = 105.03N 0.286 (r = 0.675)

(1)

500

400

Vs (m/s)300

200

Vs = 105.03N0.286
r = 0.675

100

0
0

20

40

60

80

100

N-SPT

Fig. 7

Present correlation between N-SPT and Vs

Comparisons between the measured Vs and Vs
predicted from {Eq. (1)} are presented in Fig. 8. The
plotted data are scattered between the lines with
1:0.5 and 1:2 slopes, with smaller Vs values (Vs <639

GEOMATE-Nagoya, Nov.13-15, 2013

300 m/s) falling close to the line 1:1.
1:2

CONCLUSION
In this study, based on the geotechnical andgeoseismic data from the Jakarta area, an attempt
was made to develop new relationships between NSPT and Vs to indirectly estimate the Vs to be used
for practical purposes. The regression equations
developed in this study compare well with most of
the previous equations and exhibit a good prediction
performance. Therefore, the use of an equation
developed for all soils based on uncorrected blowcounts is recommended for practical purposes.
A likely application of the correlations presented
in this work is the calculation of the thirty-meter
shear wave velocity, Vs 30 , which is defined as 30m
divided by the travel time of a vertically propagating
shear wave in the upper 30m. Vs 30 is a required
input for the Next Generation Attenuation models
and is therefore needed to quantify seismic hazard.
Geotechnical site investigations at many older sites
contain boring logs, but no geophysicalmeasurements. Obtaining a rough estimate of Vs 30
based on the recorded boring logs could therefore be
useful for assessing seismic hazard at sites with thatlack geophysical measurements, and for identifying
whether geophysical measurements are necessary tofurther refine the estimate of Vs 30 .
The differences between existing and proposed
equations are mainly due to the specific geotechnicalconditions of the studied sites, the quantity ofprocessed data and the procedures used inundertaking the SPTs and geoseismic surveys. The
proposed relations are not an accurate substitute forgeophysical measurements, and uncertainty in thepredictions should be considered when using therelations.

1:1

Predicted Vs (m/s)

400

200

1:0.5

0
0

100

200

300

400

500

Measured Vs (m/s)

Fig. 8

Measured versus predicted shear wave
velocities

Equation (1) are plotted in Fig. 9 together withseveral of the earlier regression equations given in
Table 2. Some of the correlations fit the data points
reasonably well, though there is tremendous
difference in the range of V s values predicted for agiven N-SPT value. It is unclear how much of these
deviations are caused by natural variability in soil
deposits, how much is caused by errors inmeasurements of N and V s , and how much is causedby exclusion of overburden correction in the existing
relations. All the equations including the equation of
the present study {Eq. (1)} yield similar Vs values.
There is only a slight difference between Eq. 1 andthose developed by Reference [10] and Reference[11]; Eq. (1) proposed in this study estimates Vsvalues considerably closer to those derived frommost of the existing equations.
1000
900

Ohta and Goto (1978)
Imai and Tonouchi (1982)
Sykora and Stokoe (1983)
Jinan (1987)
Iyisan (1996)
Jafari et al. (1997)
Kiku et al. (2001)
Hasancebi and Ulusay (2007)
This study

800
700

ACKNOWLEDGEMENTS
The writers wish to his sincerest gratitude toTeam for Microzonation Study of Jakarta, forallowing writers to incorporate the valuable datawhen the Team developed Jakarta Microzonation
Map. Financial support for the research wasprovided by Universiti Malaysia Pahang and Institut
Teknologi Bandung, Indonesia.

Vs (m/s)

600
500
400
300
200
100
0
0

20

40

60

80

100

N-SPT

Fig. 9REFERENCES

Comparisons between proposed andprevious correlations for N-SPT and Vs[1] Martodjojo, Evolusi Cekungan Jawa Barat,
Doctor Dissertation. Bandung: Bandung
Institute of Technology, 1984, ch. 3.
[2] Assegaf, Hidrodinamika Airtanah Alamiah
Cekungan Jakarta, Master Thesis. Bandung:
Bandung Institute of Technology, 1998, ch. 2.
[3] Delinom RM, “Conference proceedings”, inInternational
WorkshoponIntegrated
Watershed Management for Sustainable Water

Future efforts should aim to reduce thevariability in these relations by utilizing only highquality measurements of N-SPT and Vs, andproperly incorporating the influence of overburden.
This effort would involve re-interpretation of thedata available in published relations, which isbeyond the scope of this paper.

640

GEOMATE-Nagoya, Nov.13-15, 2013

Use in a Humid Tropical Region, 2007, pp. 4054.
[4] ASTM, Standard test method for penetration
test and split-barrel sampling of soils. Annual
book of ASTM standard, D1586, Vol. 04.08,
1984.
[5] ASTM, Standard test methods for downhole
seismic testing, Annual book of ASTM standard,
D7400, Vol. 04.09, 2008.
[6] Sykora and Stokoe, “Correlations of in-situ
measurementsin sands of shear wave velocity”.
Soil Dynamic Earthquake Engineering, Vol 20
1983, pp. 125–136.
[7] Iyisan, “Correlations between shear wave
velocity and insitu penetration test results (inTurkish)”, Chamber of Civil Engineers ofTurkey, Teknik Dergi, Vol 2, 1996, pp. 11871199[8] Jafari, Shafiee A, and Ramzkhah A, “Dynamic
properties of the fine grained soils in South of
Tehran”. Journal of Seismologogy and
Earthquake Engineering, Vol 4, 2002, pp. 25–35.
[9] Hasancebi N and Ulusay R, “Empiricalcorrelations between shear wave velocity andpenetration resistance for ground shaking
assessments”, Bulletin of Engineering Geology
and The Environment, Vol 65, 2006, pp. 203213.
[10] Ohta Y and Goto N, “Empirical shear wave
velocity equations in terms of characteristics
soil
indexes”,
Earthquake
Engineering
Structural Dynamic, Vol 6, 1978m pp.167-187.
[11] Imai T and Tonouchi K, “Conference
proceedings”, in the 2nd European symposiumof penetration testing, 1982, pp. 57-72.

641

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ELECTRICALLY CONDUCTIVE GEOMEMBRANE ENHANCESLINER LEAK DETECTION SURVEYS AT POST INSTALLATION

1

H.B. Ng1, D. Gallagher2 and A. Beck3
GSE Lining Technology Co., Ltd., Bangkok, Thailand; 2GSE Environmental Inc., Houston, Texas, USA;
3
TRI Environmental Inc., Austin, Texas, USA

ABSTRACT
Construction Quality Assurance (CQA) plays an important role in producing a quality containment system.
Electrical leak detection / liner integrity surveys are CQA non-destructive tests that help locate leaks and defects
at post-installation of the geomembrane systems before and after covered with soil and water. GSE Leak
Location Liner incorporates a thin layer of electrically conductive layer on the bottom surface of an insulatinggeomembrane which allows it to be sparked tested for defects. The paper discusses the utilization of electricallyconductive geomembrane liners in facilitating electrical leak detection surveys at post installation that helps
engineers achieve their goal of a leak free geomembrane barrier system. Based on large scale field tests and few
commercial scale tests that have been performed by third party surveyors, the surveys indicate that an electricallyconductive geomembrane can significantly increase the quality of electrical leak detection surveys used to locate
holes in a liner system. An electrically conductive geomembrane also allows the use of leak detection surveys inapplications that were previously impossible such as multiple-layer systems, on side slopes and in situation
where wrinkling has occurred in the liner.
Keywords: Conductive Geomembrane, Electrical Liner Integrity Survey, Leak Detection, Spark Test.

double-lined ponds and their slopes cannot be
surveyed
at
all
when
using traditional
geomembranes.
Recent studies, outlined below, show thatcovered ELI surveys are more thorough and accurate
over a variety of soil-moisture conditions and linercontact situations with an electrically conductive
geomembrane.

INTRODUCTION
The electrical leak detection / liner integrity(ELI) survey is currently the most effective andpractical means of locating leaks in installed
geomembranes after cover soil, as detailed in ASTM
D7007. The technology functions along the principlethat polyethylene geomembranes are electricallyinsulative. By applying an electrical potential acrossa geomembrane, an electrical current will flow only
if a hole is present in the geomembrane, allowing thecurrent a less-resistive path through thegeomembrane. Various survey methods then track
this current flow to pinpoint a leak.
When an ELI survey is performed in an
application where a cover material has already beenplaced over the liner, it requires that a sufficiently
conductive material—both above and below—is inintimate contact with the geomembrane. This
traditionally meant the cover material above andsubgrade below. However, due to various site
conditions nonconductive liners can have difficulties
meeting these requirements. For instance, withwrinkling or bridging of the liner, air gaps can exist
beneath the liner that prevents the intimate contact
required. Also, in cases where there is dry subgrade
or encapsulated geosynthetic clay liners (GCL), thematerial beneath the liner may not be sufficiently
conductive to conduct the leak survey (Peggs, 2007).
It is also because of these two requirements thatcovered ELI surveys cannot be performed easily on

IMPROVING ELI SURVEY QUALITY
The essence of covered ELI survey quality lies inthe size and number of leaks that are located in thegeomembrane during a survey for subsequent repair.
To compare the performance of both traditional andelectrically conductive geomembranes, the authors
chose to employ the sensitivity test portion ASTM
method D7007 to quantify survey quality bymeasuring the signal-to-noise ratio (signal) ofidentical holes in identical soil conditions wheneither type of geomembrane is used. A higher signal
means that smaller leaks can be located comparedwith a lower signal, based on the authors' field
experience. To eliminate other variables, all of thesecomparisons were made in a controlled environment
using a bench-scale rig in a climate-controlled lab.
Site conditions vary greatly and a sufficient levelof conductivity is a requirement of ELI surveys, so it
is important that the relationship between survey
performance and subgrade conductivity is wellunderstood. To evaluate this, surveys were642

GEOMATE-Nagoya, Nov.13-15, 2013

performed using both types of liner on subgrades ofvarious moisture contents. At each moisture content,
signals was measured using traditional liner as wellas the electrically conductive liner and for ease ofunderstanding these two signals were compared toeach other to produce an Improvement Factor ateach moisture content. For instance, an
Improvement Factor of 2.0 means the signal when
the conductive geomembrane was used was twice asstrong as when the traditional geomembrane wasused. Continuing this data collection at increasing
subgrade moisture contents populated the chart in
Figure 1, which shows the improvement in signal
strength when the conductive geomembrane wasused vs. a traditional geomembrane.

situations where a traditional liner had struggled in
the past, particularly when there is not intimatecontact between a hole in the geomembrane and thesubgrade. In this test, signals were measured
multiple times for each contact scenario and theaverages were recorded. It was found that when thehole was located over an imperfection in thesubgrade that prevented intimate contact as shown in
Figure 3, leak signals were eight times stronger
when conductive geomembrane was used. Similarly,
when the hole is located under a seam flap as shownin Figure 4, leak signals were 10 times greater when
conductive geomembrane was used. Lastly, in asituation similar to Figure 5, where the hole islocated on a wrinkle, a quantifiable comparison
could not be made because no signal was detected
when traditional liner was used.

Improvement Factors at Various Moisture Contentsof Sandy Clay Subgrade
8.00

3.175mm(.125(.125in) Hole
Size Size)Power(3.175mmin) Hole

7.00

6.350mm (.250 in) Hole Size
Power (6.350mm (.250 in) Hole Size)

Improvement Factor

6.00
5.00

4.00
3.00
2.00
1.00
0.00
0%

5%

10%

15%

Subgrade Moisture Content (% by Weight)

Fig. 1

Notice clean ring (No soil
touched) around the hole

Improvement factors at various moisture
contents of Sandy Clay subgradeFig. 3

At one moisture content, the signal strength wasmeasured at increasing lateral distances from thehole. The greater signal at the hole was maintained
at increasing distances from the hole as shown in
Figure 2. This translates to a greater likelihood that aleak will be found by surveyors even if they are notsurveying directly over the hole.

Hole over imperfection in subgrade

Hole located underseam flap

Signal Sensitivity vs Distance from Hole70
Expon.
(Leak
LocationLiner
Liner)
Leak
Location

60

Expon.
(Traditional
Liner [Dashed])
Traditional
Liner

Signal to Noise Ratio

50

40

Fig. 430

Hole under seam flap

20

10

Hole

0
0

2

4

6

8

10

12

14

16

18

Lateral Distance from Hole (cm)Fig. 2Signal sensitivity vs. distance from hole

Unlike the prior tests, where improvement wasstudied in a situation—moist, conductive subgradein intimate contact with the liner—where traditional
liner had historically been successful, the next test
was to evaluate performance in finding leaks in

Fig. 5643

Hole on simulated wrinkle

GEOMATE-Nagoya, Nov.13-15, 2013

RESULTSThe results of these tests have shown that anelectrically conductive geomembrane can be used tosignificantly increase the quality of ELI surveys
used to locate holes in a liner system as well as
allowing the use of ELI surveys in applications thatwere previously impossible such as multiple-layer
liner systems. The full detailed report of this study
was reported by Beck et al., 2013.
FIELD TESTING AND PERFORMANCE
The industry has begun to take notice of these
improvements and recently a project was completed
at a construction and demolition landfill in southern
Minnesota. The site was 1.5 hectares in size with anirregular shape and approximately 3:1 side slopes.
The site profile of the lining system was as follows(subgrade to surface): subgrade soils, BentoLiner
Geosynthetic Clay Liner (GCL Grade NSL), 1.5 mm
thick White Leak Location High Density
Polyethylene (HDPE) Geomembrane, Geonetcomposite drainage (GSE FabriNet 5mm thick)double sided 130 g/m2 nonwoven needle-punched
Polypropylene geotextile, 1.2 meters of cover soil
and above that, eventual waste placement.
Geosynthetic materials were installed by GSI(Geosynthetics Inc.) of Waukesha, Wisconsin.
After installation and cover soil placement a leaklocation/liner integrity survey was conducted by
Leak Location Services Inc. of San Antonio, Texas.
Figures 6 and 7 show the ELI survey was conducted
through the cover soil and an excavation near defectto locate the leak. The survey took approximately
two days to complete and identified two locations ofdamage to the geomembrane liner, one a crescentshaped cut of small size (Figure 8), the second aseries of imperfections adjacent to a pipe penetrationthat did not appear to visual inspection to penetrate
the liner, but were re-paired regardless.
The
necessary repairs were made and the site is currently
in successful service. Detailed information on thisproject was reported by Ramsey et al., 2012.

Fig. 6

Fig. 7

Photo of excavation near leak signal andpin-pointing the leakFig. 8

Photo of defect found during covered ELI
surveyCONCLUSIONS
Completion of this commercial field test has
demonstrated the ability of electrically conductive
geomembrane to be used to facilitate an ELI survey
in applications that would be impossible using
traditional liner. By demonstrating that the survey
can be completed through cover soils, and in
applications were the liner is not in intimate contact
with the subgrade opens up the possibilities to awide range of applications including use overgeonets, composites, GCLs, and textiles, as well as
on slopes and in situations where wrinkling has
occurred in the liner.
Results from testing indicate that the use ofelectrically conductive geomembrane does not havea negative effect on the ability to perform the ELI
survey or in its ability to find small holes when
installed properly. Based on the field test that has
been performed by third party surveyor, the ELI
survey indicates that an electrically conductive
geomembrane can significantly increase the qualityof electrical leak detection surveys for locating

ELI survey was in progress644

GEOMATE-Nagoya, Nov.13-15, 2013

defects and holes in a liner system. The utilization ofelectrically conductive geomembrane liners infacilitating electrical leak detection surveys at post
installation can assure a leak free geomembrane
barrier system before the facility is in operation.
REFERENCES[1] ASTM D7007-03 (2003), “Standard Practices
for Electrical Methods for Locating Leaks inGeomembranes Covered with Water or EarthMaterials.”[2] Beck A., Gallagher D., Kramer E., “LeakLocation Liner Performance Evaluation” Proc.
of Geosynthetics 2013 Conference, Long
Beach, California, USA, April 1-4, 2013.
[3] Peggs, Ian D. (2007). "Liner integrity/leaklocation survey: The significance of boundary
conditions." Geosynthetics, February-March
2007, pp. 34-38.
[4] Ramsey B. J., Peggs I., Gallagher D. et al.,“New Electrically Conductive Geomembrane
for Post-Installation Liner Integrity Surveys”
Proc. of the 5th European Geosynthetics
Conference, Valencia, Spain, September 16-19,
2012.

645

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan,Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INVESTIGATION OF CESIUM DIFFUSION IN CRACKED CONCRETE
BY USING MICROFOCUS X-RAY CT

1,2

Ivan Sandi Darma1, Shohei Ikeda2, Takafumi Sugiyama3
Graduate School of Engineering, Hokkaido University, Japan;
3
Faculty of Engineering, Hokkaido University, Japan

ABSTRACTThis paper addresses the diffusivity of cesium ions in cracked concrete. Concrete as a construction material isused in radioactive in-ground storage ponds. It is expected that a large amount of highly contaminated solution
by radionuclides has been stored. 134Cs and 137Cs have been considered as the major radionuclides in the waste
solutions. The presence of crack due to the application of load might increase the diffusion of cesium in theconcrete. In this research small beams made by OPC and fly ash concretes were prepared. The crack was
induced using flexural strength test. The unique approach of this research is in the application of microfocus Xray CT to characterize 3D crack geometry as well as the observation of the presence of cesium in the cracked
concrete through the CT number analysis. The result shows the addition of fly ash significantly reduced the
diffusion coefficient of cracked concrete.
Keywords: Cracked Concrete, Cesium, Diffusion Coefficient, X-ray CT

mortars in which the cesium carbonate solution has
been employed to trace the diffusivity of solute [3],[4]. Thanks to its relatively larger contrast under theobservation with micro-focus X-ray CT the
diffusivity has been successfully visualized. In thisresearch by using non-radioactive cesium carbonate
solution the transport phenomena of radioactive
cesium in cracked mortar have been simulated. It isconsidered that the transport of the cesium behavesin similar manner in concrete. In addition the crack
geometry
parameters
derivedfrommicrotomographic images were also studied.

INTRODUCTION
Cementitious materials are used in radioactive
waste disposal facility construction and also as waste
immobilization matrix due to their ability to act asmechanical barriers and to prevent convective waterflow.
Cementitious materials exhibit diffusion
controlled release for many radionuclides although,for some radionuclides, the release mechanism issolubility-limited. 134Cs and 137Cs have highly
solubility limits and therefore their release from
cement matrix will be diffusion controlled [1].
A millions of gallons of high level waste
solutions which contain radioactive cesium (137Cs) inconcentrations up to 2×1010 Bq/L reported haveleaked from concrete storage tank into subsurface atthe Hanford site, a former plutonium production
complex located in southeastern Washington State,
USA [2]. In this way it will be needed to evaluate
the transport of cesium in concrete in order to take apreventive measure against leakage in tosurrounding environment. The presence of cracks in
cementitious materials leads to the more complex
problem. Cracks inevitably arise in the most of
concrete member. They can be induced by load orvolumetric charge due to plastic settlement, highcuring temperature, various types of shrinkage, andcreep. These cracks have negative effect on transport
properties of concrete because crack space can act aspreferential channels and allow more ions topenetrate.
Recent studies show the application of X-ray CT
to evaluate the transport phenomena in cracked

EXPERIMENTAL PROGRAM
Sample Preparation
Table 1 shows two types of mix proportion for
mortar specimens used in this experiment. The
Ordinary Portland Cement was used for all mixturesand fly ash was used for FA specimen. Type II fly
ash that is specified in the JIS A6201 was used for
FA specimen. Due to the limited size of thespecimen for the measurement by X-ray CT the
maximum aggregate size was 1.7 mm. Fresh mortar
was placed in steel molds in a size of 40×40×160
mm and cured in water for 28 days.
Flexural strength tests were used to induce
cracks in the specimen. As shown in Figure 1,
10×20×60 mm beam specimens were manufactured
from mortars block. The beam was reinforced by
FRP sheet so as to avoid its sudden failure due to thebending load.
646

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1 Details of Mortar specimen
Specimen ID

Max. Agg. size
(mm)

W/B

S/B

FA/(OPC+FA)

28 days compressive
strength (N/mm2)

OPC
FA

1.7

0.5

2.5

0
0.3

45.7
31.8

Note: W/B is the water to binder ratio by mass, S/B is the sand to binder ratio by mass, and for FA specimen fly ash was replaced for OPC
by 30% by mass.
P

20 mm

10 mm

2 mm
Crack

FRP
10 mm
7.5 mm45 mm

Cs2CO3 40 wt% solution

7.5 mm(a)Fig. 1(b)

Experiment set-up (a) Bending test. (b) Cesium penetration test.

The residual crack widths after the removal of
bending load in the specimens were planned to bearound less than 50 µm. The observation of crack
width
was
conducted
using
microscopemeasurement. Since the nature of crack that closes tocertain extent after unloading, repetitive tests were
performed to obtain the target of crack width.
Furthermore, the specimens were oven dried before
cesium penetration test.

Crack Width Distribution
To calculate crack width distribution, we
implemented one of the plugins in BoneJ [6], [7]called Thickness. The operational definition ofThickness is based on the following equation [6]:𝛕𝛕(𝒑𝒑) = 𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐({𝒓𝒓|𝒑𝒑 ∈ 𝒔𝒔𝒔𝒔𝒔𝒔(𝒙𝒙, 𝒓𝒓) ⊆ 𝛀𝛀, 𝒙𝒙 ∈ 𝛀𝛀}) (1)Let p i ∈Ω be the set of an arbitrary point (1 unit
voxel) in crack structure (Ω). Subsequently, create
the largest spheres with center x and radius r
which contains the point ‘pi’ and completely inside
the crack structure (Ω). The thickness τ(pi) is
defined as the diameter (2rmax) of the largest sphere.
Furthermore, from point ‘pi’ which represent 1 unit
voxel we will have one data corresponding to thethickness of crack structure. This algorithm willcontinue to run until all the points (voxels) coveredin the crack structure (Ω). Finally, the information
regarding the thickness (diameter) and its volume incrack structure will be obtained.

Cesium Penetration Experiment and Image
Acquisition
In radioactive waste depositories, the presence ofwater, CO 2 gases and carbon containing materials
would lead to cesium carbonate. This is why cesium
carbonate (Cs 2 CO 3 ) was chosen [5].
Figure 1b shows the illustration of cesium
penetration test. Cesium carbonate solution(Cs 2 CO 3 ) 40 wt% with the solution concentration of
1.84 mol/L was prepared [3]. In order to prevent
diffusion in lateral direction, side-surfaces of thespecimens were sealed. Subsequently, X-ray CT test
was conducted after 24 hours exposure time incesium penetration test.
In this study, tube voltage and tube current of
microfocus X-ray CT were set to a value of 130 kV
and 28 µA, respectively. The position of FCD and
FID were set to 180 and 600 mm, respectively. The
stack of these slices provides the reconstructedvolumetric data of the scanned object. The
reconstructed 3D-image data set was composed of
377 contiguous gray scale images where each slice
image contained 1024×1024 pixel. The effective
size of pixel in the CT image is 22×22 µm with 44µm in slice thickness.

X-ray CT Number andConcentrations Relationship

CesiumSolution

In case of diffusion, the movement of solute isTable 2 Relationship between Cs2CO3 solution andCT Number
Cs2CO3 Concentration [mol/L]
CT Number

647

0.00

0.01

0.06

0.68

3.68

75

119

153

525

2219

GEOMATE-Nagoya, Nov.13-15, 2013

caused by different concentration between source ofsolution and internal crack space. In specificexposure time, the gradient of solute concentration
occurred along the crack. This phenomenon can beobserved clearly through X-Ray CT by using CT
Number as an indicator of solute concentration.
Therefore, the relationship between CT number andsolute concentration is needed for further analysis.
To clarify the relationship between changes in
CT number and solution concentration preliminary
test was conducted as follows. ∅2 × 50 mm
capillary-glass tubes filled with 0 (water), 0.003,
0.03, 0.34 and 1.84 mol/L of cesium carbonate(Cs2CO3) solution were prepared. The average CT
number of each solution was obtained. Table 2
shows CT Number values of each solution
concentration. It can be seen that the CT number are
linearly increased with increasing concentration ofion in solution.

crack used the average of maximum CT number
profiles, while in the determination of diffusion in
uncracked body, CT number profile is fully used.
CT number profile completely shows the Cs2CO3
concentration profile both in cracks and uncracked
body of mortar at specific height from the surface incontact with the solution. The diffusion coefficientperpendicular to the crack wall then was determinedfrom the best-fit curve represented by Eq.(2) for themeasured cesium solution concentration profile.
RESULTS AND DISCUSSION
Distribution of flexural crack width based on 3D
crack analysis
Figure 2(c) and (d) shows 3D crack space
derived from 3D microtomographic images (Figure
2a and 2b). Despite having slightly different
frequency of each value of crack width as shown in
Figure 2 (e) and (f), the average crack width for both
specimens was coincidentally the same as 88 µm
based on the 3D crack analysis. This means that thepresence of flexural crack for both OPC and FA
specimens appears to have the same geometricaleffect on the transport of solute in the crack.

Observation Method of Cesium Diffusion along
the Crack
First, a specific slice at the represented elevationfrom the surface in contact with the solution waschosen from the whole stack of reconstructed slices
in solution-exposed condition. Then, several crack
locations filled by cesium solution were specified.
Line segment which intersect perpendicularly to thecrack was applied in selected location. The profile ofCT number was obtained from each line segment.
Based on the relationship between CT number andcesium solution concentration derived from Table 2,
the average of maximum CT number was converted
into the cesium solution concentration. By applying
the same method for specific position to the exposed
surface, cesium solution concentration profile along
the crack would be obtained.
Diffusion due to a concentration gradient can ingeneral be described by Fick’s second law ofdiffusion as follows:
𝑪𝑪𝒙𝒙 = 𝑪𝑪𝒔𝒔 �𝟏𝟏 − 𝒆𝒆𝒆𝒆𝒆𝒆 �𝒙𝒙��𝟐𝟐√𝑫𝑫𝑫𝑫

Cesium diffusion within the crack space
Figure 3 shows an example to obtain the
distribution of Cs2CO3 concentration along the given
line position in the crack space at a certain elevation
surface of 4 mm from the surface in contact with thesolution. (FA Specimen). From Figure 3(c) theCs2CO3 concentration in the crack was determined
to 0.53 mol/L. This concentration is lower than theconcentration of the Cs2CO3 in the source solution of
1.84 mol/L meaning that the diffusion process
occurs along the crack passage. The same
methodology was applied to determine theconcentration in the crack at the height of 0, 2, 6 and
8 mm from surface exposed to the solution for both
specimens.
Figure 4(a) and (b) shows cesium penetration inboth specimens. The presence of cesium in the crack
is shown in white because of its large CT numbers.
Furthermore, Cs2CO3 concentration profiles wereobtained as shown in Figure 4(c) and (d). It is
obvious that the concentration decreases with theincreased heights.
As given in Table 3, the cesium diffusion
coefficient along the crack (Dcrack) in OPC specimen
is greater than that of in FA specimen. Considering
the crack width distribution for both cracked
specimens was similar, we suggest that difference in
diffusion coefficient between OPC and FA specimen
should be influenced by the movement of cesium
towardtotheuncracked
mortarbody.

(2)

where Cx is the Cs2CO3 concentration at distancex, x is the distance from the exposed surface, Cs is
the surface Cs2CO3 concentration, D is defined as
cesium diffusion coefficient in this study, t is the
exposure time, and erf is the error function. The
best-fit curve was used with the measured Cs2CO3
concentration profile along the crack.
Observation Method of Cesium Diffusion in
Uncracked Matrix
The similar methods applied to acquire CT
number profile in order to determine cesium
diffusion coefficient in uncracked body. In thedetermination of the diffusion coefficient along the648

GEOMATE-Nagoya, Nov.13-15, 2013

(b)

(a)
17.6 mm

13.2
mm

17.6 mm

8.8 mmCrack

13.2 mm

Crack

Z
Y

8.8 mm

Z
Y

X

X

(d)

(c)

8.8 mm

8.8 mm

Z

Y

X

40
30
20
10
0

X

50
40
30
20
10
0

Crack width (µm)

Fig. 2

Z

0-22
22-44
44-66
66-88
88-110110-132
132-154154-176
176-198
198-220220-242242-264264-286286-308

Relative Frequency (%)

50

0-22
22-44
44-66
66-88
88-110110-132
132-154154-176
176-198
198-220220-242242-264264-286286-308

Relative Frequency (%)

Y

Crack width (µm)(e)(f)
3-Dimensional cracked specimens, crack structures, and crack width distributions in a volume ofinterest (VOI) of (a), (c), (e) for OPC specimen and (b), (d), (f) for FA specimen
clarification.

To discuss the difference in diffusion coefficientalong the crack,
the diffusion coefficientperpendicular to the crack wall of each specimen
were studied.
The diffusion coefficients along the crack forboth specimens are lower than the diffusion
coefficient of cesium ions in free water (2.06 × 109 2
m /s, [8]). Although the defined D in this researchis based on the Cs2CO3 concentration this results
implies that the process of cesium moving along thecrack is somewhat hindered. Furthermore thecapillary absorption would occur because specimens
were dried prior to the penetration tests. In thisregard more researches will be needed for

Cesium diffusion in uncracked matrix
Figure 4(e) and (f) shows the limited diffusion in
the uncracked matrix for the FA specimen ascompared with OPC. The average apparent diffusion
coefficients of uncracked body (Duncracked) for OPC
and FA specimens are 9.12×10-11 and 3.47×1012 2
m /s, respectively. In general, at 28 days curing
period the diffusivity of ions in fly ash concrete ishigher than that of in OPC concrete due to slow in
pozzolanic reaction. However, in this research thedrying process before penetration test enhanced the649

GEOMATE-Nagoya, Nov.13-15, 2013

Table 3 Diffusion coefficient of each sample

SampleCrack width (µm)
Microscope*1

OPC

20-40

CT*2
88

FA-slice 97(Z= 4 mm)

Diffusion Coefficient(m2/s)
Duncracked*3

Dcrack
1.70 × 10-09

9.12 × 10-11

FA
45-55
88
9.30 × 10-10
3.47 × 10-12
Measured by microscope, 2*Average width by 3D crack
analysis, *3 Apparent diffusion coefficient*1

Line segment
Ypozzolanic reaction. This resulted in the increased
resistance to diffusivity due to the dense
microstructure for FA specimen.
Reduced diffusion coefficient for uncracked
matrix in the FA specimen might be the reason why
the cesium diffusion coefficient along the crack in
the FA specimen was lower than that of OPC
specimen. The presence of cesium within the crack
space inhibits the movement of cesium toward to thelower gradient. In this condition, a mechanism has
been formed where the diffusion in perpendicular
direction play important role in diffusivity within thecrack space. Cesium diffusion into the uncracked
matrix will trigger the diffusion along crack. The
easier diffusion into uncracked matrix, the greater
diffusion from the source solution along the crack. It
is noted that the apparent diffusion coefficientsobtained in this study lay within reported ranges by
previous research [1], [9].

CT Number

X

800
700
600
500
400
300
200
100
0

FA-slice 97(Z= 4 mm)

0

5000

10000

15000

20000

Length (µm)

Cs2CO3 concentration [mol/L]

CONCLUSION
Using flexural strength test, cracked OPC and
FA specimens were obtained. From the image
analysis of 3D crack analysis, it was found thatcrack width distribution for both crack spaces weresimilar although the microscope observation
provided their width ranging 20 to 40 and 45 to 55
for OPC and FA specimens, respectively
The addition of fly ash could reduce thediffusivity in uncracked matrix as compared with
OPC specimen of equivalent crack width
distribution. This condition led to lower diffusion
coefficient along the crack for FA specimen thanthat of in OPC specimen.

0.6

Experimental Data
FA-slice 97(Z= 4 mm)

0.5

Fitting Curve

0.4
0.3
0.2
0.1
0
0

5000

10000

15000

20000

Length (µm)

Fig. 3

Method to determine diffusion coefficientfrom representative microtomographic

ACKNOWLEGMENT[2] Serne R.J., Zachara J.M., Burke D.S.,“Chemical Information on tank Supernatants,
Cs Adsorption from Tank Liquids onto Hanford
Sediments, and Field Adsorption of Cs
Migration from Past Tanks Leaks”, PacificNorthwest National Laboratory, 1998, PNNL11495/UC-510.
[3] Ikegami
H.,
KikkawaT.,
Sugiyama
T.,“Visualization of solution transport throughcracks in concrete by X-ray CT”, The
65thAnnual Meeting of Japan Cement
Association, 2011, pp. 138-139 (in Japanese).

Part of this research was funded by Japan Society
for Promotion of the Science (Research
No.23360187). The first author also expresses
gratitude for the financial support from JICA.
REFERENCE[1] Bucur C., Olteanu M., Cristache C. et al.,“Radionuclide transport through cement
matrices”,Revista De Chimie, 61 (5), 2010, pp.
458-461.
650

GEOMATE-Nagoya, Nov.13-15, 2013

(b)

(a)

17.6 mm

17.6 mm13.2
mm13.2 mm

Z

Z
Y

Y

d)
Cs2CO3 Concentration[mol/L]

Cs2CO3 Concentration[mol/L]

0.8
0.6
0.4
0.2

1

0.8
0.6
0.4
0.2

0

0
2

4

6

8

10

2

4

6

8

10

Depth from exposed surface (mm)

(c)

(d)

1

OPC-slice 47(Z= 2 mm)

0.8
0.6
0.4
0.2
0
-8000

0

Depth from exposed surface (mm)

-3000

2000

7000

Cs2CO3 Concentration [mol/L]

0

Cs2CO3 Concentration [mol/L]

X

X

1

Fig. 48.8 mm

8.8 mm1

FA-slice 47(Z= 2 mm)

0.8
0.6
0.4
0.2
0
-8000

-4000

0

4000

Transport Distance (µm)

Transport distance (µm)

(e)

(f)

8000

3-Dimensional cesium penetrated samples of (a) OPC and (b) FA, Cesium concentration profile along
the crack of (c) OPC and (d) FA, and representative of Cesium concentration profile of uncracked
mortar of (e) OPC sample (f) FA at 2 mm from solution contact surface.

[4] Kikkawa T., Sugiyama T., Darma I.S., et al.,“Observation of flexural cracking and cesium
carbonate transport using X-ray CT”,
Proceedings of Annual Conference of JCI,
Vol.34 (1), 2012, pp. 1810-1815 (in Japanese).
[5] Boch Ph., Seiss M., Vetter G., et al., “Highalumina cements for cesium trapping, Cem.
Concr. Res, Vol 22, 1992, pp. 369-374.
[6] Doube M., Klosowski M.M., Argenda-Carreras
I., et al., “BoneJ: Free and extensible bone
image analysis in ImageJ”, Bone, 47,

2010pp.1076-1079.
[7] Doube M., “BoneJ [online]”,2009, Available
from: <http://bonej.org> [December 2012].
[8] Flury M., Gimmi T., Dane J.H. et al., “Solute
diffusion”, in Methods of Soil Analysis, Part 4,
Physical Methods, Soil Science Society ofAmerica, Madison, WI, 2002, pp. 1323-1351.
[9] KumarA., Roy D.M., “Retardation of Cs+ andCl- diffusion using blended cement admixtures”,
J. Am. Ceram. Soc., 69(4), 1986, pp. 356-360.

651

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

MODELLING THERMO-ELASTO-PLASTIC BEHAVIOUR OF
NORMALLY CONSOLIDATED AND OVERCONSOLIDATED SOILS
1

Yang-Ping Yao1 and Annan Zhou2
Civil Engineering Department, Beihang University, Beijing 100191, China; 2Discpline of Civil Engineering,
Royal Melbourne Institute of Technology (RMIT), Melbourne 3001, Victoria, Australia.
ABSTRACT

A constitutive, non-isothermal unified hardening (UH) model is presented to interpret the thermoelastoplastic behaviours of normally consolidated (NC) and overconsolidated (OC) clays. Two yield surfaces(the current yield surface and the reference yield surface) are adopted in the proposed model. A unified
hardening parameter (H) is developed to describe the evolution of the current yield surface, and the plastic
volumetric strain is employed to quantify the hardening of the reference yield surface. The similarity ratio (RT)between the current yield surface and the reference yield surface, which is a function of the temperature andplastic volumetric strain, is developed to govern the volume change behaviour and the shear strength of soils
with different stress histories and at varying temperatures. The proposed model is then validated through test
results in the literature.
Keywords: Temperature, Non-isothermal conditions, Constitutive modelling, Overconsolidation
proposed to interpret the thermally-induced yieldmechanism and reproduce the temperature-related
stress-strain relationships of soils (such as [4, 8-12]).
Because a soil’s stress history significantly
affects its thermal behaviour, studies (bothexperimental and theoretical) on the thermal effects
are commonly conducted on the soil with different
overconsolidated ratios (OCRs). Therefore, a solidand effective constitutive model for both normallyconsolidated and overconsolidated soils in
isothermal conditions should be the starting point for
further developing a reliable and robust thermoelastoplastic model. Very recently, the authors
proposed a new elastoplastic model [13] to interpretthe mechanical behaviours for both normallyconsolidated and overconsolidated soils in generalstress states based on the sub-loading surface
concept. The proposed model, referred to as theoriginal UH model, is simple and practical because it
only includes one additional parameter (theHvorslev slope) compared with the Modified Camclay model. The original UH model does not takethermal effects into consideration.
The main purpose of this article is to extend theisothermal UH model (i.e., the original UH model)
to non-isothermal states. The thermo-elastoplastic
behaviours of both normally consolidated andoverconsolidated soils will be interpreted andsimulated by the framework of the non-isothermal
UH model. For notational convenience, all stressvariables in this article are effective stress variables.

INTRODUCTION
Theoretical and experimental studies on theengineering properties of soils are usually restricted
to isothermal conditions, although soils inengineering are commonly exposed to nonisothermal conditions. In the natural environment,
soils experience seasonal temperature variations, andisothermal conditions exist only in the laboratoryenvironment. In addition to the natural temperature
variations, underground structures are also subject to
artificial non-isothermal conditions.
A typical
example is nuclear waste disposal [1], which
involves burying high-level radioactive nuclear
waste deep into soils with very low permeability.
The buried nuclear waste containers keep desorbing
energy to the surrounding soils and continuingly
heat the protective soil barriers.
Anothergeotechnical engineering practice related to nonisothermal conditions is buried high-voltage cables[2]. The electric current conveyed through thecopper cables produces heat that is continuouslytransferred to surrounding backfills. Similarly,
buried geothermal pipelines that transfer hightemperature fluid also continuously release heat tothe surrounding soils, which leads to soil
temperature changes.
After realising that soils in geotechnicalengineering are not always restricted to isothermal
conditions, intensive research on the soils’ thermomechanical properties has been conducted after thepioneering work by Campanella and Mitchell (see[3]). In the past 30 years, a variety of temperaturecontrolled laboratory tests were conducted on
different soils to investigate their thermo-mechanicalproperties [4-7]. Based on the experimental
observations, a number of constitutive models were

ISOTHERMAL UH MODEL: A REVIEWCurrent Yield Surface and Reference Yield
Surface652

GEOMATE-Nagoya, Nov.13-15, 2013

calculated from Eqs (1) and (2) when the yieldsurface expands from OC0 to OC. Conversely, thecurrent yield surface can be determined according to
Eqs (1) and (2) with a given increment of the plastic
volumetric strain in the strain-controlled loading.
In addition to the current yield surface, thereference yield surface (see Fig. 1, dash ellipse OR),
which is completely identical to the yield surface in
the Modified Cam-clay model, is adopted toconsider the effects of the stress history and further
determine the value of Mf (see the following section,‘Potential Failure Stress Ratio’). The reference
yield surface and its hardening law can be written as:q
T = const (Isothermal)
Mapping rule: η = q = q (i.e. straight line OAA )
p p

OCR =
R=

px0
px0

p
p

A( p, q )A (p, q)

px0

p
px

px0 pxq2− px = 0
f = p+pM 2 p = p exp  1 + e dε p 
x0
v 
∫
 x
 λ −κ


Fig. 1 Current yield surface and reference yieldsurface for the isothermal UH model.
In the original UH model, an ellipse is adopted as
the current yield surface following the Modified
Cam-clay model (see Fig. 1, solid ellipse OC). With
respect to the current yield surface, the unified
hardening parameter (H) is adopted to replace theplastic volumetric strain (εvp) that is used as thehardening parameter in the Modified Cam-claymodel. The current yield surface and its hardening
law are presented as follows:p+q2
 1+ e− px = 0; px = px0 exp  ∫
dH 
pM 2
 λ −κ
where p and q are the reference mean stress andthe reference deviator stress, respectively. px is the
cross point between the reference yield surface andthe p-axis. px0 is the isotropic preconsolidationpressure. The initial size of the reference yieldsurface is specified by the value of px0 (see initialellipse OR0 in Fig. 1). The expansion of thereference yield surface is controlled by the plastic
volumetric strain. The plastic volumetric strain
produced when the current yield surface expands
from OC0 to OC leads to the expansion of thereference yield surface from OR0 to OR (see Fig. 1).
It is noted that the expansion velocity difference
between the current yield surface and the reference
yield surface is controlled by the value of the term
( M f4 − η 4 ) ( M 4 − η 4 ) .

(1)

where p and q are the effective mean stress and thedeviator stress, respectively. q = ηp, where η is thestress ratio. px is the cross point between the current
yield surface and the p-axis. px0 is the equivalentinitial effective mean stress (i.e., px0 = p0 + q02/(M 2p0), where p0 and q0 are initial mean stress and initialdeviator stress, respectively). e is the void ratio. κand λ are the elastic unloading index andelastoplastic compression index for saturated soils,
respectively. M is the stress ratio at the critical state.
H is the unified hardening parameter proposed by
Yao et al. (see [13];), which can be written as:
H = ∫ dH = ∫M f4 − η 4 p
dε v
M 4 −η 4(3)

Mapping Rule and Similarity Ratio
The reference yield surface can be determined by
px0 and the term related to the plastic volumetricstrain (i.e., ∫ [ (1 + e) (λ − κ ) ] dε v ). A mapping rule isstill required to find the reference point (see point A
in Fig.1) on the reference yield surface to specify p
and q . A geometric mapping rule between thereference stress point and the current stress point isassumed as below:p(1)

where Mf is the potential failure stress ratio, which
will be discussed in detail in the following section,‘Potential Failure Stress Ratio’. The initial size ofthe current yield surface is determined by the valueof px0 (see initial ellipse OC0 in Fig. 1). During a
triaxial loading, e.g., conventional triaxial
compression (CTC, see stress path C0A in Fig. 1),
the current state point moves from C0 to point A, andthe current yield surface expands from OC0 to OC.
The increments of the unified hardening parameter(dH) and the plastic volumetric strain (dεvp) can be

η=

q q
=
p p

(4)

Following Asoka et al. (see [14]), the similarity
ratio, i.e., the ratio between the current mean stress(p) and the reference mean stress ( p ), is adopted asa state variable (R):653

GEOMATE-Nagoya, Nov.13-15, 2013

R=

p
p 
η2 
 1+ e=dε vp 
1 + 2  exp  − ∫p px0  M 
λ
−
κ



κ dp
 e
 dε v = 1 + e p + κ T dTdε p = λ − κ dp + ( λ − κ ) dTTT v 1 + e p(5)Potential Failure Stress Ratio
According to [15], we propose that therelationship between the potential failure stress ratio(Mf) and the similarity ratio (R) is as follows:1 
M f =  − 1 ( M − M H ) + M
R 

where dεve is the elastic volumetric strain increment
including the elastic and thermoelastic components;
dεvp is the plastic volumetric strain increment
including the plastic and thermoplastic components;
κT is the thermoelastic compression index, which
could be a function of the current stress, temperatureand stress history. However, in this paper, following
Cui et al. (see [8]), we assume κT is a soil constant(i.e. the negative value of the coefficient of thermal
expansion)forthesimplicity
purpose.
Thermoelastic swelling during heating is mainly
caused by the thermal expansion of the soil skeleton.
λT is the thermo-elastoplastic compression index andis usually positive for an irreversible contractive
volume change due to heating. In this paper, we
assume λT is a constant for simplicity, but it can be
set as a function of temperature, which may involve
additional fitting parameters, to simulate the nonlinear thermo-elastoplastic compression for normallyconsolidated soils. It is noted that Eq. (9) isapplicable to the normally consolidated soil only.
For overconsolidated soils, the volume change
equation can be derived from Eq. (9) and the yieldsurfaces.
If we set the plastic volumetric strain incrementin Eq. (9) to zero, the yield surface (p-T yieldsurface) in the plane of the mean stress (p) andtemperature (T) can be solved as:(6)

where MH is the slope of the Hvorslev surface andcan be determined by undrained triaxial tests on
soils with different OCRs. For clays, MH is usually
0.5 M ~ 0.9 M [15], which can be used to estimate
MH if no test results for the calibration are available.
However, Eq (6) in the original UH model neglects
the possibility that the value for η exceeds 3. This
intrinsic restriction (i.e. η ≤ 3) is taken into accounthere, and the above equation is revised as:
1 
M f = 3 − 3 −  − 1 ( M − M H ) − M
R 

(7)

are Macaulay’s brackets, which indicate
where
the following calculation rules for a variable x:
 x
x =
0

( x ≥ 0)( x < 0)

(9)

(8)

NON-ISOTHERMAL UH MODEL
Volume Change Equation in Non-isothermal
Conditions
In addition to the stress change, temperature
variation can also induce the volume change ofsaturated soils, even under constant stressconditions. Thermal volume change can be divided
into thermoplastic volume change (irreversible) andthermoelastic
volumechange(reversible).
Compared with the deformation due to a stresschange, the deformation caused by a temperaturechange has its own characteristics. For example,
experimental data indicate that the normal
compression lines (NCLs, in the plane of e vs. lnp)
of a saturated soil at different temperatures can beconsidered parallel to each other. In other words,
the temperature induced void ratio change of
normally consolidated soils can be considered
independent of stress levels.
According toexperimental observations ([3, 4, 6, 16, 17]), thefollowing two simple equations are developed todescribe the elastic and plastic strains due to both thetemperature change and the stress change:

p0T = p0 exp  − β (T − T0 ) 

(10)

where, v is the specific volume ( = 1+ e) and β =v(λT – κT)/(λ – κ). p0T is the yield stress in isotropic
conditions at the observation temperature (T), and p0
is that at the reference temperature (T0).
Shear Strength for Non-isothermal Conditions
Experimental results (e.g., [10]) support that thesoil’s drained shear strength increases during
heating. The mechanism of such an increase of theshear strength due to heating can be mainly
attributed to the density increase owing to thermal
compression.
In this paper, we assume thetemperature alters the soil’s strength by changing its
density. The influence of thermal fabric change on
soil’s strength is not taken into account here, since it
is not generally observed.
For a normally consolidated soil with a meanstress (p = p0) (see point A, Fig. 2a and Fig. 2b),increasing temperature (from T0 to T) leads to adensity increase under the same mean stress. The
state point moves to point B (p0, e1), which is654

GEOMATE-Nagoya, Nov.13-15, 2013

vertically below point A (p0, e0) in the plane of thevoid ratio and logarithmic mean stress, as shown in
Fig. 2a. The soil at point B is still a normallyconsolidated soil at T because point B is located on
the normal compression line at T (see point B, Fig.
2a) and the p-T yield surface (see point B, Fig. 2b).
For point B, the critical state stress ratio is MT(B),which is equal to the potential failure stress ratio(MfT(B)) because this soil is normally consolidated at
T (the similarity ratio is equal to one; therefore,
MT(B) = MfT(B)).

For overconsolidated soils at T (such as point D
in Fig. 2a), the potential failure stress ratio (MfT) can
be constructed based on Eq. (6):M fT = 3 − 3 − ( RT−1 − 1) ( M T − M H ) − M T(14)where MT can be found from Eq. (13) and RT is thesimilarity ratio at T. If the soil is normallyconsolidated at T, RT=1 and MfT = MT. For a given
temperature (T) and a similarity ratio at thistemperature (RT), the potential failure stress ratio
MfT can be calculated via Eq. (14).

 λT − κ T T − T ()0 λ − κ

p1 = p0 exp −Current Yield Surface and Referenced Yield
Surface in Non-isothermal Conditions

T=

T=

T0

T

Fig. 2 Density increase due to heating andoverconsolidation( p,

M f(B′) = 3 − 3 − ( R −1 − 1) ( M − M H ) − M= 3 − 3 − ( p1 p0 − 1)( M − M H ) − M

px

q)

px

T

px

OO 1

px

0

px
px

px

px
0

p
T

Fig. 3 Conceptual view of the current yield surface
and the reference yield surface in nonisothermal conditions
At a given temperature (T), the current yieldsurface (see C1O1 in Fig. 3) is assumed similar tothat in the isothermal condition (i.e., Eq. (1)). The
p-T yield surface (i.e., Eq. (10), see C1C in Fig. 3) is
adopted to consider the temperature variation. We
combine yield surface C1O1 and yield surface C1C
together, which generates the current yield surface(3-D) in the space of q-p-T (see OCC1O1 in Fig. 3):

(11)


q2
 1+ e− pxT = 0; pxT = px0T exp  ∫dHT  ,
 fT = p +
2
pM
λ
−
κ



T
(15)

4
4
dH = MfT −η dε p ; p = p exp −β ( T − T ) x00  T MT4 −η 4 v x0T

where p and q are the current mean stress anddeviator stress, respectively, at temperature T. MT is
the critical state stress ratio at temperature T. MfT is
the potential failure stress ratio at T, which has been
defined in Eq. (14) with a given RT (see Eq. (18)later). pxT is the cross point between the current
yield surface and p-axis at temperature T. px0T
stands for the equivalent initial mean stress when thedeviator stress is equal to zero at temperature T. If
εvp = 0, pxT is equal to px0T, and the current yieldsurface (see OCC1O1 in Fig. 3) is the same as the(12)

Let us substitute Eq. (11) into Eq. (12) andconsider the following: (i) p1 in Eq. (11) can befound from the p-T yield surface, i.e., Eq. (10); (ii)
MH is assumed independent of the temperature(experimentally supported by [9]); and (iii) point B
is an arbitrary point. We have:
M T =3 − 3 − ( M − M H ) exp  β ( T − T0 )  − M H

0T

0T

where R is the similarity ratio at T0, which is equal
to p0/p1 for point B’. Because the soils at point B
and at point B’ (see Fig. 2a) have same mean stressand density, it is reasonable to assume they have thesame potential failure strength if the temperatureremains unchanged during shearing (i.e., shearing at
T for point B and shearing at T0 for point B’):M f(B′) = M fT(B) = M T(B)

( p,

q)

//
AB 1

However, the soil with the same void ratio (e1)under the same stress level (p0) (see point B’ in Fig.
2a and Fig. 2b) can be obtained via unloading frompoint C (p1, e2) with a constant temperature (T0).
The mean stress at point C is assumed to be p1,
which is higher than p0. This soil (point B’) is an
overconsolidated soil at T0. The potential failure
stress ratio for point B’ can be calculated from Eq.
(6):

(13)
655

GEOMATE-Nagoya, Nov.13-15, 2013

temperatures, as reported by Cekerevac and Laloui(see [4]).
The remould kaolin clay is firstpreconsolidated to 600 kPa (e0 = 0.94) at room
temperature (T0 = 22oC) and then unloaded to 600,
500, 400, 300, 200, and 100 kPa to produce soil
samples with different OCRs (= 1, 1.2, 1.5, 2, 3 and6, respectively). These samples are then triaxiallycompressed in the drained condition to 20% of thedeviator strain at both room temperature (22oC) and
90oC. Isotropic compressions at room temperature(i.e., data set S2-T6 and S2-T8) are employed tocalibrate the elastic unloading index andelastoplastic compression index: λ is set to 0.18 andκ is set to 0.05. The isotropic heating test fornormally consolidated specimen is adopted tocalibrate the thermo-elastoplastic compression index(λT). λT is set to 1.8×10-4. The thermoelastic
compression index is estimated from the ratio
between κ and λ because the isotropic cooling test is
not available for this kaolin clay, namely, κT= - (κ/λ) λT =-0.5×10-4. The triaxial tests results are
replotted in Fig. 4 (circles for the 90oC series andtriangles for the 22oC series). The critical state
stress ratio (M) is calibrated by the triaxial
compression test (OCR =1) at room temperature (seeFig. 4a). The Hvorslev slope (MH) can be calibrated
by the triaxial compression test (OCR =1) at 90oC
via Eq. (14) (see Fig. 4a). M and MH are set to 0.87
and 0.4 for this remoulded kaolin clay, respectively.

initial yield surface (see OAA1O1 in Fig. 3) because
no hardening occurs. HT is the unified hardening
parameter at T. The p-T yield surface (i.e., Eq. (10))
is employed to relate the initial mean stress attemperature T (i.e., px0T) with that at T0 (i.e., px0).
Similarly, based on Eq. (3), the function of thereference yield surface in p-q-T space (see ODD1O1
in Fig. 3) can be written on the analogy of the above
procedure for the current yield surface:q2
 1+ e p  fT = p + pM 2 − pxT = 0; pxT = px0T exp  ∫ λ − κ dε v  ; (16)T p = p exp −β (T − T )
x0
0 

 x0T

where p is the reference mean stress and q is thepx0 is thereference deviator stress at T.
If ε vp = 0,
preconsolidation pressure at T0.
pxT = px0T , and the reference yield surface (seeODD1O1 in Fig. 3) is same as the initial reference
yield surface (see OBB1O1 in Fig. 3). The reference
mean stress at T can be solved from above equation:p=

px0 M T2
1+ eexp  − β ( T − T0 ) + ∫dε vp 2
2
M T +η
λ −κ



(17)

where η is the stress ratio at T (η = q/p = q / p ).
Based on the definition presented in Eq. (5), thesimilarity ratio at temperature T (i.e., RT) can be
written as
RT =

p 
η2 
1+ e


dε vp  (18)
1 + 2  exp  β (T − T0 ) − ∫px0  M T 
λ −κ



Once RT is calculated from Eq. (18), MfT in Eq.
(14) can be determined. The flow rule, which issimilar to that in the Modified Cam-clay model, isemployed here:
dε dp
2η
=
dε vp M T2 − η 2(19)The elastic volumetric strain and elastic deviatorstrain are defined as follows
dε ve =

κ dp
1+ e p+ κ T dT ; dε de =2 (1 +ν ) κ dq
9 (1 − 2ν ) 1 + e p(20)

where ν is Poisson’s ratio, which is assumed as aconstant (= 0.3) in this paper.
EXPERIMENTAL VALIDATIONS

Fig. 4 Drained triaxial compression and predictions
by the non-isothermal UH model

Drained conventional triaxial compression(CTC) tests on a remoulded kaolin clay with avariety of OCRs are conducted at two different
656

GEOMATE-Nagoya, Nov.13-15, 2013[1]

The soil responses (the stress strain relationships
and the volume change during shearing) are
predicted by the non-isothermal UH model andcompared with the experimental results in Fig. 4a-f
(OCR = 1, 1.2, 1.5, 2, 3 and 6, respectively). In Fig.
4, the solid curves stand for predictions at 22oC andthe dashed curves for predictions at 90oC. Threemain trends in these tests are visible and predictedreasonably well by the proposed model: (1) thestrength at a higher temperature is higher than thatwith a lower temperature for all OCRs; (2) thesoftening behaviour during shearing and the peakstrength become more visible as the OCR increases
for both temperatures; (3) the volume change during
shearing gradually turns from compression todilation with an increase of the OCR for the twotemperatures.

[2]

[3]

[4]

[5]

[6]

CONCLUSIONS
A constitutive model is proposed to interpret thethermo-elastoplastic
behaviourofnormally
consolidated and overconsolidated clayey soils.
Compared with the Modified Cam-clay model, theproposed non-isothermal UH model introduces only
3 new parameters, namely, the thermo-elastoplastic
compression index, the thermoelastic compression
index and the Hvorslev slope. All three parameters
have specific physical meanings and can becalibrated by conventional laboratory tests. In
addition to the adoption of the double yield surface
concept (i.e., the current/reference yield surface) anda novel hardening parameter (H), the other key
features of the proposed model include: (1) Strength
increase due to heating and overconsolidation is
explained in the same framework (i.e., density
increase under an unchanged effective mean stress).
The critical state stress ratio increases with anincrease in the temperature. (2) Both the current
yield surface and reference yield surface areextended to p-q-T space. The effects of both thestress history and the thermal history in isotropic andnon-isotropic conditions can be considered.
More details about this model can be found in Y.
P. Yao & A. N. Zhou (2013) “Non-isothermal UH
model: A thermo-elastoplastic model for clays”,
which has been accepted (Article Number 13-P035R2) and will be published on Geotechnique.

[7]

[8]

[9]

[10]

[11]

[12]

[13]

[14]

[15]

ACKNOWLEDGEMENT
This study was financially supported by the
Discovery Early Career Research Award (DECRA)
from the Australian Research Council (Project No.:
DE130101342).

[16]

[17]

REFERENCES

657

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Campanella, R.G. and J.K. Mitchell, Influence oftemperature variation on soil behaviour. Journal of
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Cekerevac, C. and L. Laloui, Experimental study ofthermal effects on the mechanical behaviour of aclay. International Journal for Numerical andAnalytical Methods in Geomechanics, 2004. 28(3):p. 209-228.
Hueckel, T. and G. Baldi, Thermoplasticity of
Saturated Clays: Experimental Constitutive Study.
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Sultan, N., P. Delage, and Y.J. Cui, Temperatureeffects on the volume change behaviour of Boom
clay. Engineering Geology, 2002. 64(2-3): p. 135145.
Kuntiwattanakul, P., et al., Temperature effects on
undrained shear characteristics of clay. Soils andFoundations, 1995. 35(1): p. 147-162.
Cui, Y.J., N. Sultan, and P. Delage, A
thermomechanical model for saturated clays.
Canadian Geotechnical Journal, 2000. 37(3): p. 607620.
Graham, J., et al., Modified Cam-Clay modelling oftemperature effects in clays. Canadian Geotechnical
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Hueckel, T., B. Francois, and L. Laloui, Explaining
thermal failure in saturated clays. Geotechnique,2009. 59(3): p. 197-212.
Hueckel, T. and M. Borsetto, Thermoplasticity of
Saturated Soils and Shales: Constitutive Equations.
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Laloui, L. and B. Francois, ACMEG-T: Soil
Thermoplasticity Model. Journal of Engineering
Mechanics, 2009. 135(9): p. 932-944.
Yao, Y.P., W. Hou, and A.N. Zhou, UH model:
three-dimensional unified hardening model foroverconsolidated clays. Geotechnique, 2009. 59(5):p. 451-469.
Asaoka, A., M. Nakano, and T. Noda, Superloading
Yield surface concept for highly structured soil
behaviour. Soils and Foundations, 2000. 40(2): p.
99-110.
Mita, K.A., G.R. Dasari, and K.W. Lo, Performanceof a Three-Dimensional Hvorslev–Modified Cam
Clay Model for Overconsolidated Clay. International
Journal of Geomechanics, ASCE, 2004. 4(4): p. 296309.
Baldi, G., et al., Developments in modelling ofthermo-hydro-mechanical behaviour of Boom clay
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Towhata, I., et al., Volume change of clays inducedby heating as observed in consolidation tests. Soils
and Foundations, 1993. 33(4): p. 170-183.

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

STABILITY OF A ROCK SLOPE SUSCEPTIBLE TO SEASONALMOVEMENTS
A. K. Alzo’ubi1
CECS, Abu Dhabi University, UAE

1

ABSTRACT
A rock slope, known as the Checkerboard Creek slope located in British Columbia, Canada, is moving underthe effect of seasonal temperature changes. Freezing and thawing processes are causing the rock to move at rateof 13 mm/year. A 60 m deep weathered zone has been identified along the slope. This paper discusses the
Checkerboard Creek slope, which is moving toward the reservoir, to propose a support system to stabilize theslope.
The numerical simulation conducted in this study shows that the failure is situated near the slope’s toe wherea road-cut has been made. To stabilize the rock slope, a support system comprising of cables and a shotcrete
layer was proposed and installed along the steepest portion of the weathered rock area. Comparison studies
showed that the proposed support system could successfully stabilize the moving rock slope at a reduced tensile
strength value. By using this support system, the risk of rock slope failure will be reduced to an acceptable limit
through increasing the Factor of Safety of the slope to 1.15.
Keywords: Support System, Rock, Slopes, and Stability.
possibility of any instability in the slope [1]. The
slope was moving toward the reservoir at a rate of
10-13 mm/year. This movement is seasonal
movement, beginning as the ground surface cools in
October and stopping when the ground begins towarm in May. The investigation established that themoving volume is between 2 to 3 million m3
concentrated in a weathered rock mass.
Monitoring of the rock slope from 1984 onward
has determined that the slope movement is triggeredby the thermal cycle experienced by the slope. This
thermal cycle, along with other environmental
effects, weathers the rock mass and results in aweathered region along the slope face. Aydin andBasu [2] found that as the tensile strength of the rockmaterial decreased, the material tends to behave withmore ductility and the rupture strain increased as afunction of the weathering degree.
Martin et al [3] found out that although totalcollapse of the slope is highly unlikely, the rockmass adjacent to the highway is susceptible tofailure under the continuous weathering process.
This study presents a supporting system consisted ofa shotcrete layer and a cable system to stabilize theslope. The strength reduction factor method wasused to evaluate the factor of safety of the supported
slope, and was found to be greater than 1.

INTRODUCTION
The Checkerboard Creek slope is located at the
Revelstoke hydroelectric dam, British Columbia(BC), Canada (Fig. 1). A series of active and oldtension cracks were discovered up to 150 m above
the highway rock cut immediately after the end of
construction of the dam. This finding prompted an
intensive geotechnical and geological program
carried out by BC Hydro to examine the moving
slope, define the moving volume, and monitor theslope to guarantee the safety of the Dam.

GEOLOGY AND CLIMATE
Fig. 1

The general location of the Revelstoke Dam

The geotechnical and geological settings of thesite was discussed by [4], [5], and [6]. The rockmass is composed of igneous rocks, mainly foliatedGranodiorite overlying the easterly dipping

In 1984, BC Hydro began an investigation of themoving slope under question. The thoroughinvestigation was conducted to determine the658

GEOMATE-Nagoya, Nov.13-15, 2013

Columbia River Fault. Steeply dipping joints andshears were identified. These joints and shears dip inand out of the slope at 60°-90° from the horizontal.
Toppling driven by shearing along these
discontinuities at the slope is kinematically possible.

Fig. 2temperature change. For the details of the
instrumentation and its distribution in the boreholessee [7]. Readings from the instruments were later
processed and showed strong relations between thevariation in the temperature and the movement of
the slope.
Monitoring revealed that the slope is moving in acyclic mode at a rate between 0.5 to 13 mm/year.
The cyclic nature of the displacement was found tobe associated with the seasonal temperature. Martin
et al [3] shows the displacement pattern along withthe temperature and water level variation in theslope. The slope movement resumes during the cold
weather between early autumn and late winter.
The average air temperature ranges from -25 °C
to 35 °C. Freezing occurs between November andMarch. Continuous readings were taken from thepiezometers installed in the slope; the readings
showed that the saturated conditions exist 50 m to 80
m below the ground surface. See Fig. 2 for theinterpreted water table location. The water table wasincorporated into the numerical model.

Cross-section along the Checkerboard Rock
Slope (modified from Watson et al, 2006)

THE NUMERICAL MODEL
The discrete element method has been longrecognized for its ability to model rock mass
behavior in underground and near-surface rockapplications. This method can simulate explicitly
discontinuities inside the rock mass.
UDEC [8] was originally not designed for
isolated joints or for joints terminating in intact rock.
However, Lorig and Cundall [9] described theimplementation of the voronoi joint option in UDEC
for modeling reinforced concrete beams. The
introduction of the voronoi joint provided a means
for simulating joints that were discontinuous andterminated in heterogeneous intact rock. The voronoi
tessellation generator can be used to create randomly
sized polygonal blocks between continuous joints[10]. The randomly sized polygons can beconsidered analogous to flaws in the intact rock.

A weathered layer exists within the top 60 m ofthe slope. This layer is composed of poor-quality
rocks: highly weathered, weak, altered and disturbed
rock with crushed zones and frequent shears. The
movement of the slope is concentrated in thisweathered region. Underneath this weathered layer,
a more competent layer was found of fair-to-goodquality rock. Localized zones of poor-quality rockwere found along the shear zones and joints. Figure
2 shows a cross-section through the slope. The
weathering of the rock slope was extensive within
the first 60 m from the ground surface (Fig. 3).

Fig. 2 Surface weathering of the slope adjacentto the highway cut
Between 1984 and 2000, slope instrumentation
was installed in the slope area to monitor the
displacement, pore water pressure, and theFig. 4659

Rock mass exposure showing the blocky

GEOMATE-Nagoya, Nov.13-15, 2013

nature of the rock mass.
Figure 4 shows the blocky nature of the rockmass that forms the rock slope. As shown in the
figure, the rock slope is highly heterogeneous withrandomly shaped blocks. This justifies the use of themosaic block tessellation to generate polygonal
blocks in two dimensions that can simulate the rockslope behavior realistically.
A network of flaws was generated numericallyinside the rock mass. These flaws have an average
length of 1.3 m, formed random polygonal blocks.
All the discontinuities and the geological units were
included in the simulation along with the weatheredregion. Figure 5 shows the UDEC-DM used in thispaper and fig. 6 shows the details of the UDEC-DM
in the area of concern.

Fig.5

The numerical model of the Checkerboard
rock slope.

Fig.6

The details of the joints and flaws generated
by using UDEC-DM.

then varied to investigate their effect on the slope.
The shear stiffness was varied between 1/10 and
4/10 of the normal stiffness. This range was found tohave insignificant effects on the displacements fromthe numerical model measured at the slope surface.
FAILURE PROCESS AND LOCATION
The progressive failure of geo-materials is a
gradual and time-dependent failure process at
localized areas, followed by the redistribution of thestresses in the slope. These new stresses build up
and cause the propagation of the failure. If thisfracturing continues, a rupture surface connecting all
the failed parts will form. Many factors can cause
progressive failure, such as the time-dependentdegradation of the strength parameters, increasing
pore pressures, and/or thermal stresses. In addition,
the presence of non-persistent joints andheterogeneity of the rock mass might cause tensilestresses inside the rock mass and also the initiationand propagation of cracks that might lead to failure.
To study the effect of weathering on the
Checkerboard Creek slope, the cohesion and frictionof each geological unit was estimated using the
Hoek-Brown criterion [11] and the GSI index foreach rock formation. The GSI index used in thisstudy was adapted from [7] (see Table 1). Martin etal [3] showed that failure will be concentrated near
the road cut and tensile strength degradation mightcause this failure. Although failure occurred, it waslimited to the steepest part of the slope (Fig. 7). As
a result of the analysis the region that is prone to
movement might be stabilized.

The Hoek-Brown failure criterion [11] was used
to determine the rock mass cohesion, friction andtensile strength. The discontinuities' properties weretaken from [7]. Table 1 shows the material andVoronoi microstructure properties used in thisnumerical study. The normal stiffness of the flaws
and the shear stiffness were assumed to be equal and

Fig.7

660

Failure at the rock slope, notice theconcentration of the moving rock mass.

GEOMATE-Nagoya, Nov.13-15, 2013

Table 1: Properties of the rock mass and the voronoi microstructure used in the UDEC-DM analyses
Gneiss & Mica Schist
Fresh
Weathered
78


45

26
E (GPa)6.5
0.25
νVoronoi micro-structure36
φ 
Coh. (MPa)2.40.02
σ t (MPa)kn (GPa/m)
18
ks (GPa/m)
1.8

Granodiorite
Fresh
Weathered

76

133

75

35
20
3.6
0.27

60
29
17.7
0.23

35
26
3.6
0.27

0.5
0.3

36
2.4
0.02
5
0.5

48
5
0.22
22
2.2

36
2.4
0.016
6
0.6

18
0.1
0
1.5
0.15

It is noteworthy to mention that the tensile
strength predicted by [11] ranged between 9 to 20
kPa, while the back-calculated tensile strengths inthis analysis range was 25 to 650 kPa depending on
the assumed unconfined compressive strength.
According to this present study, Hoek-Brown
criterion underestimates the tensile strength of rockmass.
Martin et al [3] showed the progressive
movement of the failed material toward the reservoir
as a result of tensile strength degradation. Anotherattempt was made to simulate the rock slope and to
predict the failure mechanism and extent, if any, by
assuming the same properties for the entire slope.
The flaws in the weathered and un-weatheredgeological units were assumed to have the same
unconfined compressive strength of 60 MPa, and thetensile strength was back calculated.

Fig.8

Columbia
River Fault &ShearsMPa, which is the same back-calculated tensile
strength when the weathered and un-weatheredrocks have different properties. The rock mass tends
to topple and this toppling was restricted to thesteepest slope portion near the highway cut, see Fig.
8.
SUPPORTING SYSTEM
The results of the analysis presented in [3] and in
this paper showed that the weathering process might
result in failure of the slope near the highway cut.
This might lead to retrogressive failure up the slope
as a result of steepening of the slope as the failed
material moves toward the reservoir. To further
investigate this possibility, the moved material at thetoe of the slope was excavated. As anticipated, thenumerical modeling showed that the previously
stable part of the slope started to move toward thereservoir. The newly formed surface resulting fromthe excavation was a 60° slope, which is very, close
to the original slope surface prior to movement.
To avoid the consequences of this scenario or
any retrogressive failure, a support system composedof a shotcrete layer and a cable system was designed
and tested numerically. Passive anchors were used tostabilize the Marble Shear Block slope, which isanother slide at the Revelstoke Dam project [12] andthe block was successfully stabilized.
In this paper, a cable system was installed inside
the weathered rock region and back into the stablerock mass, as shown in Fig. 9. Many configurationsof the cables and the shotcrete layer have beenmodeled numerically to optimize the supporting
system. Table 2 shows the properties of the shotcrete
layer and the cables.
The best results were achieved when the cables
were spaced at an average of 8 m apart, and 10 cmof shotcrete layer was applied at the surface, as
shown in Fig. 9. Based on the analysis conducted,

Progressive movement and toppling of theslope toward the reservoir.

Failure was initiated at a tensile strength of 0.2
661

GEOMATE-Nagoya, Nov.13-15, 2013

the weathered rock mass was assumed to have weakproperties: UCS of 30 MPa and tensile strength of
0.8 MPa to put the slope under marginally stablecondition. The tensile strength was then decreased
gradually to 0.5 MPa with no significant movement
observed. The velocity, displacement andunbalanced forces in the numerical model werewatched. According to the numerical analysis ofunsupported slope, the model would fail at 0.5 MPaof tensile strength. However, no excessive
movement was detected in the numerical model.

models. As shown in the Figure, the support system
was able to limit the displacements in the model,
while the unsupported model continued to deform.
To further investigate the model, the tensile strengthof the supported rock mass prone to movement was
reduced to 0.2 and 0.02 MPa, respectively. The
results were similar to those obtained from theprevious models. Supporting the rock slope
stabilized the movement, no excessive fracturing or
failure propagation was observed, and such
fracturing as was observed was very minimal.

Table 2 Support System properties
Property
Area (mm2)Thickness (mm)E (GPa)σ t at yield (MPa)
Coh (MPa)
Tensile bond (MPa)Grout k s (GN/m/m)
Grout τ (MN/m)

Shotcrete
100
20
3 MPa
30
2.0
1.0

Cable
625
98
0.55 MN
10^3

6
0.32

Fig.10 Effect of supporting system on thedisplacement of surface point A (in theinsert).
The cable-shotcrete system proposed andmodeled in this paper would hinder the cyclic
movement observed at the Checkerboard rock slope.
The question remains if this system would performon site in the same way as in the numerical model.
The only way to know is to install the system andmonitor the actual performance in the field.
FACTOR OF SAFETY

Fig.9

The strength reduction factor was used toevaluate the traditional factor of safety. The
proposed support system showed significant
improvement on the displacement pattern as shownon the previous section. The factor of safety of the
supported slope was 1.15. As the spacing between
the cables was reduced to an average of 6 m, thefactor of safety increased to 1.22. The reduction of
the distance between successive cables improved thestability of the slope as concluded from thenumerical simulation. Although this Factor of Safety
is relatively low, it is acceptable as long as the slope
is being monitored.

Suggested support system contains of 10
cm shotcrete layer and cables at an average
distance of 8 m.

Using the same strength properties for the intact
material and the Voronoi micro-structure, twomodels were examined. The first model was with nosupport, while the other model was with a support
system. The results were compared. As observed,
the suggested support system was able to limit thedisplacement and stabilize the rock slope. Figure 10
shows the effect of a support system on thedisplacement pattern of the slope.
The Figure shows a comparison between the two

CONCLUSION
The discrete element damage approach was662

GEOMATE-Nagoya, Nov.13-15, 2013

applied to simulate the Checkerboard Creek rockslope movement and a supporting system. The
weathering process at the slope site caused the rockmass properties to degrade. The rock slope
undergoes a seasonal movement that might
jeopardize the dam’s safety. According to thenumerical analysis, the failure is concentrated at theslope toe near the road cut at the steepest part of theslope.
To avoid the possibility of retrogressive failure, asupport system consisting of 10 cm shotcrete andcables spaced at 8 m, was used successfully tostabilize the rock slope movement toward thereservoir at a reduced tensile strength value.
This hybrid numerical modeling approach (UDEDM) adapted in this study was used successfully tomodel this complex rock slope supporting systemand showed high potential of success. The strength
reduction factor techniques showed that the factor ofsafety of the supported slope is 1.2. This Factor of
Safety is acceptable in such rock slopes, as long as
the rock slope remains under close monitoring to
avoid sudden failure of the rock slope.

[5] Moore D, Imrie A, Enegren E “Evaluation andmanagement of Revelstoke dam reservoir
slopes”, in Proc. The 19th ICOLD Congress,
Florence, Italy, Vol 3, 1997, pp. 1-22.
[6] Moore DP, Lewis MR “Rock slope
reinforcement with passive anchors”, in Proc.
23rd United States Symposium on RockMechanics, University of California, Berkeley,CA, 1982, pp. 945-952.
[7] Watson A, Martin C, Moore D, Thomas W,
Lorig J., “Integration of geology, monitoringand modelling to assess rockslide risk”, Rockand Soil Engineering, Felsbau Vol. 3, 2006, pp.
50-58.
[8] Itasca “Udec-Universal Distinct Element Code”,
Version 4.0. Itasca Consulting Group,Inc.,
Minneapolis. 2004.
[9] Lorig LJ, Cundall PA “ Modeling of reinforced
concrete using the Distinct Element Method”, in
Proc. Fracture of Concrete and Rock, SEMRILEM international Conference, Shah SB,
Swartz SE (eds), Springer-Verlag, New York
Inc., Houston, Texas, USA, 1987, pp. 276-287.
[10] Alzo'ubi, A.K., C.D. Martin, and D. M. Cruden.
“Influence of tensile strength on toppling failure
in centrifuge tests”, International Journal ofRock Mechanics and Mining Sciences Vol.
47(1), 2010, pp. 974-982.
[11] Hoek E, Carranza-Torres C, Corkum B “HoekBrown failure criterion-2002 edition”, in Proc.
The 5th North American Rock Mechanics Symp,
Toronto, Canada, Vol. 1, 2002, pp. 267-273.
[12] Martin CD, Kaiser PK “Analysis of rock slopes
with internal dilatioin”, Canadian Geotechnical
Journal, Vol. 21(4), 1984, pp. 605-624.

ACKNOWLEDGEMENTS
I would like to acknowledge the financial
contribution of the Railway Ground Hazard
Research Program sponsored by CP Rail, CN andtransport Canada, and the Natural Sciences andEngineering Research Council of Canada. I would
like also to extend my thanks to Dr. C. D. Martin forhis contribution during the initial stages of thisresearch.
REFERENCES[1] Watson A, Moore D, Stewart T “Temperature
influence on rock slope movements at
Checkerboard Creek”, in Proc. International
Symposium on Landslides, Evaluation andStabilization, Lacerda, Ehrlich, Fotoura, Sayao(eds) Rotterdam, Balkema, Rio de Janeiro, Vol
2, 2004, pp. 1293-1304.
[2] Aydin A, Basu A “The use of Brazilian test as aquantitative measure of rock weathering”, RockMechanics and Rock Engineering, Vol. 39(1),2006, pp. 77-85.
[3] Martin C.D, Alzo’ubi A.K., Cruden D.M.
“Progressive failure mechanisms in a slope
prone to toppling”, in Proc. International
Symposium on Rock Slope Stability in Open Pit
Mining and Civil Engineering, Vancouver,
Canada, 1st ed., Vol. 1, 2011, pp. 12.
[4] Lane L., “Brittle deformation in the columbia
river fault zone near Revelstoke, southeastern
British Columbia, Canada”, Canadaian Journalof Earth Sciences, Vol. 21, 1984, pp.584-598

663

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

REAL-TIME BRIDGE SCOUR MONITORING SYSTEM BY USINGCAPACITOR SENSOR
S. M. A. Motakabber, M. I. Ibrahimy and A. H. M. Zahirul Alam
Faculty of Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia

ABSTRACT
Scour is the erosion of stream bed or bank material from bridge foundations due to flowing of water. Data
logging from sensor and electronic communication systems can monitor scour in real-time to ensure the integrityof bridge structure. A number of parameters are associated with scour, thus different types of sensor are required
to measure the individual affecting factor. A simple capacitive type direct scour sensor system is proposed andvalidated by simulation. The result shows that any change of the river bed dielectric property is a directindication of scour. Due to simple capacitive structure of the sensor system, it is highly robust and easy to
implement. The system can easily be implemented with an existing bridge structure. A wireless telemetry system
can be used to send the real-time data from the proposed sensor to a desktop computer at the monitoring lab.
Keywords: Scour, Bridge Monitoring, River Bed Erosion, Capacitor Sensor

effect, natural hazards and environmental conditions.
Most of these type sensors are complex and very
expensive. The dielectric property of different
materials such as pure water is 80, dry soil is 5-8 and
mud is 30-65. This dielectric property can be used tomeasure the scour.
A bridge scouring real-time monitoring system[7] can provide a comprehensive, instant andfunctional monitoring platform to monitor the safetyof the bridge. It will reduce the costs of physicalmonitoring and bridge maintenance. Mobile

INTRODUCTION
Bridge scour is the meaning of removal of soil,
sand and rocks from around a bridge supports orpiers as shown in Fig. 1. Rapidly moving water canwash out the river bed materials and make scour
holes, compromise the existence of a bridge
structure [1]. Scour happens under the water and it ishard to see by naked eye. As a result, every year anumber of bridges are collapsed all over the world
which causes a lot of financial and life loses. The
three main reasons of bridge failure are collision,
overloading and scour. It has been estimated that
60% of all bridge failures is happened due to scourand other hydraulic-related causes [2]. Score is acomplex natural occurrence and a number ofparameters are associated with it. Hence to predict
the bridge failures and real time scour monitoring,different types of sensor are required to measure theindividual affecting factor [3], [4]. Among themsonar altimeter can be used to measure the distance
between sensor and river bottom [5]. A change indistance-to-bottom is an indication of scour. Noncontract radar water level sensor can be used tomeasure the water level across a wide temperature
range and varying water surface conditions [6].
Ultrasonic water velocity sensor and side-looking
acoustic Doppler current meter can be used tomeasure bidirectional velocity of the water. The
sensors read all the parameters including scouring,water levels and water flow velocity. These sensors
reading is transferred to a computer through wire or
wireless communication systems. The reading is
programmed to give an early warning to the monitor.
These sensors are generally selected and arranged
based on local weather conditions, climate change

Fig.1 Bridge scour [1]communications can be used to transmit relevant
information to bridge maintenance and management
units and users when a bridge would be potentiallydamaged by manmade or natural disasters. The
instant conveying of information will allow thebridge management unit to implement instantdisaster rescue measures and to notify users to avoid
dangerous situation that can protect people’s lives
and properties.

664

GEOMATE-Nagoya, Nov.13-15, 2013

Here, H = h 1 + h 2 +… … … + h n and ϵ 1 , ϵ 2 , …
… … ϵ n are the dielectric constant of each segments
respectively.
The change of dielectric constant at any segment
is the result of change of total capacitance of theelectrodes. In normal situation the electrodecapacitance will be remained constant over a long
period of time. An AC Wien bridge oscillator circuit(Fig. 3) can be used to measure the electrodes
capacitance change. The frequency of oscillation of
the Wien bridge oscillator is determined by Eq. (4).

DEVELOPMENT OF CAPACITOR SENSORS
Design and development of capacitor sensors formeasuring the parameters, which are related with thebridge scouring, is a challenging issue. 4 to 6 pairsof separate water-resist metal flat bar electrodes
surroundings each of the bridge piers can be used tomeasure the scour. The electrodes are piled
vertically under the river bed and each pair ofelectrode act as a parallel plate capacitor as shown in
Fig. 2. Since the dielectric constant of the water ishigher than the dielectric constant of the soil andmud, any amount of soil when washout between theelectrodes, increases the capacitance. By measuring
the capacitance of individual pair of electrode cangive a direct measurement of scouring.

Fig. 3 A basic Wien bridge oscillator circuit(a)

For a particular circuit, the values of resistors R 3 ,R 4 and the reference capacitor C REF are generally
kept constant. Therefore, the Wien bridge oscillator
circuit’s frequency is inversely proportional to thesquire root of the electrode capacitance and therelation can be represented by Eq. (5)(b)

Fig.2 (a) Cross sectional top view of bridge pierand electrodes arrangement, (b) Enlarge view of asingle electrode pairIf the dielectric constant ϵ between eachelectrode pair is considered as constant then the total
capacitance of electrode pair can be represented as:

Eq. (5) indicates the frequency becomes low
when the electrode’s capacitance C ELECT increases
and it can be happened if there is a scouring. The
important thing is that in this case, no need tomeasure the absolute value of the electrode’s
capacitance; it can directly show that the change of
frequency means there is a scouring.

When any scour hole is occurred surrounding thebridge pier, the dielectric constant all over the space
between the electrode pair is no longer remained
constant. If the electrode pair is divided into nnumbers of vertical strips and the dielectric constant
between each of the small h strip is considered as aconstant then the total capacitance of each electrodepair can be calculated as follows:

RESULT AND DISCUSSIONA PSPICE simulation is studied for the proposed
bridge scour monitoring system and the result isshown in Fig. 4.

665

GEOMATE-Nagoya, Nov.13-15, 2013

principle may help to develop a simple and low costreal-time bridge scour monitoring system.
REFERENCES[1] Warren LP, “Scour at Bridges: Stream Stability
and Scour Assessment at Bridges in
Massachusetts”, US Geological Survey, 2011.
[2] Parker G, Toro-Escobar CM and Voigt RL,“Countermeasures to protect bridge piers fromscour”, Vol. 1 (p. 27) and Vol. 2 (p. 360 ), 1998.
[3] Glaser SD, Li H, Wang ML, Ou J and Lynch T,“Sensor technology innovation for theadvancement of structural health monitoring: astrategic program of US-China research for the
next decade”, Smart Structure and System, Vol.
3, No.2, 2007, pp. 221-244.

Fig. 4 Variation of frequency with change ofelectrode capacitanceIn this simulation, it is considered that the riverwater stream direction is from electrode 1 toelectrode 3 (Fig. 1). From Fig. 4, it is found that
there is a slow scouring effect at the beginning, butnear about third month, there is an abrupt change of
frequency (low frequency) observed related with theelectrode number 3. It means a huge scour issuddenly occurred at this bridge pier.

[4] Lin YB, Lai JS, Chang KC, Chang WY, Lee FZ
and Ten YC, “Using MEMS sensors in thebridge monitoring system”, Journal of theChinese Institute of Engineering, Vol. 33, No.1,
2010, pp. 25-35.

CONCLUSION
A capacitor type sensor with an oscillator canbe used for bridge scour monitoring system. Thechange of frequency of the oscillator is a directindication of the scour and it does no need tomeasure the exact value of sensor capacitor. This

666

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SKIN FRICTION TESTS ON MODEL PILE IN WET SOIL
Mohamed M. Shahin
Faculty of Engineering, Misurata University, Libya

ABSTRACTThe shaft resistance of smooth and rough model pile in wet sand, silt and clay under static loading isinvestigated experimentally in a pile-soil skin friction test apparatus. This apparatus allows independent controlof the boundary stresses of a cylindrical soil specimen in the vertical and horizontal directions. The pile
installation technique used was designed to minimize soil disturbance so that the failure criterion for pile shaft
friction could be investigated. The load transfer along the shafts of smooth and rough surfaces aluminum model
piles in wet soil under static load was measured. The study shows that, the magnitude of pile-displacement at
failure, which necessary to mobilize the ultimate shaft resistance varies significantly with the soil type andsurface roughness of the pile. The study also, shows the importance of the boundary conditions of the soil
specimen surrounding the model pile. The results shows the effectiveness of using rough pile in increasing thepile capacity. Also, The results show that the angle of the pile-soil contact depends on the soil type, roughness ofthe pile surface, void ratio, initial density, and horizontal confining pressure.
Keywords: shaft resistance, model pile, static load, initial density.
INTRODUCTION
The computed values of shaft resistance for all the
tests are plotted as a function of the horizontal
confining pressure. The relationship is basically a
linear one which can be expressed as:
fs = σh tan (δ) = k σv tan (δ)
where σh is the effective normal stress acting aroundthe pile shaft at failure, δ is the angle of friction
between the pile and the soil, k is the coefficient oflateral earth pressure and σv is the effective verticalstress around the pile shaft. In this paper the skinfriction of smooth and rough model piles under
static loading in wet sand, silt and clay isinvestigated by skin friction tests on model pile.
The influence of the important mechanicalparameters is investigated to simulate shear
resistance along the pile shaft in different soil
densities, For every kind of soil, six tests werecarried out on smooth model pile and six tests onrough model pile which were tested in Triaxial
apparatus model pile tests as shown in fig, (1).
The test apparatus allows the control of horizontal
and vertical pressures on a cylindrical specimen ofsoil with a circular model pile erected in it. The axial
load on the model pile was measured by means of aload cell seated on top of the model pile, while theaxial displacement was measured using a dial gage.
EXPERIMENTAL PROGRAM
The specimen can be restrained to generate acondition approximately at rest. The bottom surfaceof the specimen is supported on a rigid base. The
physical properties of the soil testing are shown intable (1), the specific gravity are 2.65 for sand, 2.70
for silt and 2.80 for clay.

Fig. 1 Test apparatus
A number of static loading tests were performed
at a constant rate of displacement to determine theload capacity of an aluminum model pile (200) mm
in length and (26.5) mm in diameter for smoothsurface and (27.5) mm for rough surface.
Two types of boundary stress and displacement
conditions were imposed on the soil element in thisstudy as shown in tables (2) and (3). The successive
tests were achieved by increasing the verticalpressure while preventing the lateral deformation of
the soil element before and during the load test,
where, the specimen was not allowed to expand
horizontally.
667

GEOMATE-Nagoya, Nov.13-15, 2013

shear stress developed by rough surface piles ishigher than that developed by smooth surface piles.
Hence, the maximum shear stress means theultimate shaft capacity Pu, where (end bearing
resistance = 0). For loose and dense wet sand, theultimate shaft capacity of the rough piles is in ranges(1.25) times as much as that of smooth piles asshown in tables (2) and (3) for ( k = 0.35 and 0.26).

TEST PROGRAM
The soil specimen, (100) mm in diameter and(200) mm in height, were prepared by pouring thewet soil around the pile into a thin acrylic cylinder
which was holding a rubber membrane (100) mm indiameter and ( 3.0 ) mm in thickness.
The wet soil was deposited in 5 layers and eachlayer was tamped by a tamper to achieve a relative
density of approximately (28 and 72) % for loose
and dense wet sand respectively and (47 and 68) %for loose and dense wet silt respectively in all
specimens. After preparing the specimen and before
applying any confining pressure, the acrylic cylinder
was removed, then lateral confining pressure wasapplied on the rubber membrane encasing thespecimen and the vertical pressure was applied on
the top of the soil specimen and the test carried out
upon constant volume.
After preparing each specimen the pile wassubjected to a static axial load at a constant rate ofdisplacement. The axial load was applied through adownward movement of the pile relative to the fixedsoil element at a constant rate of displacement of(0.5) mm per minute. Table (1) shows the physicalproperties of the sand.
Table 1

Table 2

piles

Soil
condition
Loose wetsand
Dense wetsand
Loose wetsilt
Dense wetsilt

Physical properties of soilDrydensity[gm ⁄ cm3]
Loose wet
1.45
sand
Dense wet
1.67
sand
1.43
Loose wet
silt
1.80
Dense wetsilt
1.33
Loose wetclay
1.68
Dense wetclay

Conditionof soil

Summary of loading tests using smooth

Relative
density
Dr %
28

Water
content
%
5

72

5

47

10

68

10

---

10

---

10

Loose wetclay
Dense wet
clay

Test
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
S14
S15
S16
S17
S18

σh
K Pa
100
200
300
100
200
300
100
200
300
100
200
300
100
200
300
100
200
300

Pu
K Pa
344
677
1022
457
899
1354
352
706
1034
398
808
1219
359
715
1057
382
791
1163

Pf
(mm)
1.0
1.25
1.5
1.0
1.0
1.5
3.5
3.0
6.0
6.5
6.5
6.5
6.5
6.5
6.5
6.0
6.5
6.5

Figures (2) and (3) shows that the shape of theload-displacement curves for the smooth and roughpiles is similar until (1.0–2.0) mm of pile
displacement. However, after these points we foundthat the load-displacement curves are different: inthe rough piles the axial load is approximately
constant, but in the case of smooth piles a slight
reduction in axial load is shown, with the amount
depending on the density of sand. The ultimate
displacement of the model pile pf to mobilize themaximum shaft resistance is relatively small and isdependent on surface roughness of the piles asshown in tables (2) and (3).
In the case of smooth piles, Pf ranges from (1 - 1.5)mm, whereas, in the case of rough piles, it ranges
between (5.0 – 7.0) mm.

TEST RESULTS
Tables (2) and (3) list the results and conditionsof the load tests on the smooth and rough model
piles respectively
Effect of surface roughness
Surface roughness of the pile has an important
effect on the skin friction of the pile. The maximum
668

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 3 Typical load-displacement curves for roughpile surface tests [R1-R6] in wet sand.

Fig. 2 Typical load-displacement curves for smooth
pile surface tests [S1-S6] in wet sand.

Tables (2) and (3) shows that, for loose and dense
wet silt, the ultimate shaft capacity of the rough piles
is equal (1.3) times as much as that of smooth pilesfor ( k = 0.34 and 0.28). It should be pointed out thatthe shape of the load-displacement curves for thesmooth and rough piles is similar until (1.5-3.0) mm
of pile displacement as shown in figures (4) and (5).

Table 3 Summary of loading tests using rough piles

Soilcondition
Loose wetsand
Dense wetsand
Loose wetsilt
Dense wetsilt
Loose wetclay
Dense wet
clay

Test
R1
R2
R3
R4
R5
R6
R7
R8
R9
R10
R11
R12
R13
R14
R15
R16
R17
R18

σh
KPa
100
200
300
100
200
300
100
200
300
100
200
300
100
200
300
100
200
300

Pu
KPa
358
707
1060
462
914
1362
382
735
1087
420
828
1287
400
814
1153
467
884
1280

Pf
(mm)
6.0
6. 5
5.5
6.5
7.0
7.0
5.0
6.0
7.0
6.5
7.0
7.0
6.5
6.5
6.5
6.0
6.5
6.5

Fig. 4 Typical load-displacement curves for smooth
pile surface tests [S7-S12] in wet silt
However, after these points we found that theload-displacement curves are different: in thesmooth piles the axial load is approximately constant,but in the case of rough piles a slight increasing inaxial load, with the amount depending on the densityof silt The ultimate displacement of the model pile Pf
to mobilise the maximum shaft resistance isrelatively small and is dependent on surface
roughness of the piles as shown in tables (2) and (3).
In two cases of pile surfaces, Pf ranges from(5.0-7.0) mm. The pile displacement at failure
values corresponding to the tests on specimens intables (2) and (3) indicate that there is a generaltrend of increasing pile displacement at failure withincreasing lateral confining pressure.

The pile displacement at failure values indicatethat there is a general trend of increasing pile
displacement at failure with increasing lateralconfining pressure. The results clearly show that therough pile requires more displacement to reach
failure, which in turn generates more deformation of
the soil element.

669

GEOMATE-Nagoya, Nov.13-15, 2013of Pu depends on the surface roughness of the piles
and it is higher in rough piles than in smooth piles.

The results clearly show that the rough pilerequires a slight more displacement to reach failure,
which in turn generates more deformation of the soil
element.

Fig. 6 Typical load-displacement curves for smooth
pile surface tests [S13-S18] in wet clay
Fig. 5 Typical load-displacement curves for roughpile surface tests [R7-R12] in wet silt
The plastic limit of clay, which used for testing is
20, where we found that the loose and dense wet
clay, the ultimate shaft capacity of the rough piles isapproximately (1.14) times as much as that ofsmooth piles as shown in tables (2) and (3) for ( k =0.32 and 0.29 ). From figures (6) and (7) we foundthat the shape of the load-displacement curves forthe smooth and rough piles in wet clay is similar
until (1.5–2.5) mm of pile displacement, where, after
these points we found that the load-displacement
curves are different. In the smooth piles the axial
load is approximately constant, but in the case ofrough piles a much increasing in axial load, with theamount depending on the density of clay. The
ultimate displacement of the model pile pf tomobilize the maximum shaft resistance is relatively
small and is equal (6.0-6.5) mm in two cases of pilesurfaces as shown in tables (2) and (3). The pile
displacement at failure values corresponding to thetests on specimens in tables (2) and (3) indicate that
there is a general trend of equal pile displacement at
failure with increasing lateral confining pressure.

Fig. 7 Typical load-displacement curves for roughpile surface tests [R13-R18] in wet clay
Load-Displacement Response
Typical axial load-pile head displacement curves
obtained from the constant rate of displacement tests
are shown in figures (2), (3) (4), (5), (6) and (7). The
ultimate shaft capacity Pu increases with increasing
horizontal pressure applied on the lateral surface ofthe soil specimen. In case of rough pile model tests
in wet sand, the magnitude of the axial load stayed
constant after reaching the ultimate displacement
Pf ,where it showed a very slight reduction of theaxial load at displacement larger than Pf in case ofsmooth pile. This was attributed to the packing ofgrains of sand. The test results indicated that very
little pile displacement is required to reach the
maximum axial load and the failure of the friction
pile. In two cases of model pile surfaces tests in wet
silt and clay, the magnitude of the axial load stayed
constant after reaching the ultimate displacement Pf .

The results clearly show that the rough pilerequires slight more displacement to reach failure,
which in turn generates more deformation of the soil
element.
Influence of Lateral Confinement
The shaft capacity Pu of model piles in wet sand,silt and clay increases directly with increasing lateralconfining pressure. A similar observation wasreported in [1], [3], [4] and [5] for a pile in a sand,kaolinitic clay and silt. From figures (5) and (6) it isobserved that the load capacity depends on lateralconfining pressure. Furthermore, the rate of increase

The angle of pile-soil friction is seen to bedifferent for each soil specimen tested, depending on
the model pile test arrangement (pile diameter,
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GEOMATE-Nagoya, Nov.13-15, 2013

As seen in figure (11) and table (4) the peakinterface friction angle δp is affected by the soil typeand increasing with. increased roughness of the pileand density of the soil. We found that the value of δpfor sand soil is higher than that for other tested soil,
where, for clay soil is the lowest, this attributed tothe particle size of the soil.

length of pile-soil contact, and pile surface
roughness), the initial density of the soil specimen,
the void ratio, relative density .and water content.
The value of (tanδ) is affected significantly by thesurface roughness of the model pile. This isdemonstrated by the test results as shown in figures(8), (9) and (10).

Table 4 Parameters of the soil

Fig. 8 Shaft resistance versus horizontal confiningpressure [S1-S6] and [R1-R6] in wet sandSoilcondition
Loose wet
sand

Pile
surface
SmoothRoughc, kPaδp, deg

0
0

28
33

Dense wetsand

Smooth
Rough

0
0

33
38

Loose wetsilt

Smooth
Rough

4
7

21
27

Dense wetsilt

Smooth
Rough

6
9

26
32

Loose wetclay

Smooth
Rough

9
13

18
22

Dense wetclay

Smooth
Rough

14
25

22
27
27

SUMMARY
The test apparatus described to measure the loadtransfer along the smooth and rough shaft surface ofan aluminum model pile erected in a specimen of
wet soil proved to be a useful tool in studying shaft
resistance behaviour. It offers certain features thatcan be advantageous in analysing the pile-soil
interaction.

Fig. 9 Shaft resistance versus horizontal confiningpressure [S7-S12] and [R7-R12] in wet silt

Fig. 11 Relationship between initial compactness
and interface friction angle in Triaxial test

Fig. 10 Shaft resistance versus horizontal confiningpressure [S13-S18] and [R13-R18] in wet clay
671

GEOMATE-Nagoya, Nov.13-15, 2013

The results-based on tests on 18 samples of a wet
sand, silt and clay with different initial compactness,show that the angle of pile-soil friction is dependent
on the soil type, surface roughness of the piles, therelative density, the void ratio, water content and thestress level.
The magnitude of displacement to mobilise themaximum shaft resistance is relatively small, and isdependent on the soil type, length of the pile-soil
contact surface and the surface roughness. The
results clearly show that the rough pile requires
more displacement to reach failure, which in turngenerates more deformation of the soil element.
In summary the test results indicate that theamount of pile displacement to achieve themaximum load and the work done on the soil
element increase directly with increasing
pile-surface roughness and lateral confining pressure.
CONCLUSION
On the basis of the tests which were done
9-smooth piles and 9-rough piles, the following
conclusion can be drawn:
1- In this study, the shaft capacity of rough piles isgreater-as much as (1.25) than that of similar smoothpiles in loose and dense wet sand, where it is equal(1.3) higher than that of similar smooth piles inloose and dense wet silt, but in loose and dense wet
clay is higher in rough piles than that of similarsmooth piles by 1.15.
2- The shaft capacity of pile, Pu increases directlywith increasing lateral confining pressure.
3- The rate of increase of Pu with confining pressure
is much higher in rough piles than in smooth piles
4- A small displacement of the pile is sufficient tomobilize the shaft capacity, and varies with surface
roughness of the piles and the confining pressure on
the soil element surrounding the pile.
5- The displacement of failure Pf in wet sand ranges
from (1.0-1.5) mm in the case of smooth piles,
where, it ranges from (5.5-7) mm in the case ofrough piles .

6- The displacement of failure Pf in wet silt ranges
from (4–7) mm in the case of loose wet silt for two
surfaces of piles, whereas it ranges from (6.5-7) mmin the case of dense wet silt.
7- The displacement of failure Pf in wet clay ranges
from (6–6.5) mm for two surfaces of piles.
8- Loading the pile with a vertical load causes
downward displacement of the pile, which causes
downward deformation of the top surface of the soil
element.
9- The value of interface friction angle increases
with increasing of initial compactness of the soil,
relative density, roughness of pile surface and lateralconfining pressure.
REFERENCES[1] Edil, T.B. & Abdel Rahman. M A. 1995. Shaft
resistance of model pile in granular soil. Deep
Foundation on bored and auger piles, BAP 11,
Ed. Vane Impe, W.F., A. A. Balkema/
Rotterdam/Brookfield/ pp.279-284.
[2] Head, K. H. 1986. Manual of soil laboratory
testing. volume 3 Effective Stress Tests, ELE
Int. Limited.Annnn B, “Unpublished work but
accepted”, accepted, Year.
[3] Mochtar, I. B. & Edil, T. B. 1988. shaft
resistance of model pile in clay, J.Geotech.
Engrg, ASCE, Vol. 114, No..11 November.
pp.1227-1242.
[4] Shahin, M.M .1998. Shaft resistance of model
pile in dry sand. proceeding of National
Engineering conference 98, Misurata – Libya.
pp.43-52[5] Shahin M. M. 2006. Shaft resistance of model
pile in dry silt. CD of Sixth Asian Pacific
Structural Engineering and Construction
Conference, Kuala Lumpur - Malaysia, CD
E71- E78.

672

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan,Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

A NEW UPPER BOUND SOLUTION TO QUANTIFY THE ULTIMATE
BEARING CAPACITY OF SHALLOW FOUNDATIONS ON
RESTRICTED SOIL
Reza Afshar-mazandaran1, Hadi Khabbaz2
1,2
Centre for Built Infrastructure Research, School of Civil and Environmental Engineering, University ofTechnology Sydney (UTS), Sydney, Australia;

ABSTRACTOne of the controversial issues in geotechnical engineering is the bearing capacity of shallow foundations
placed on layered soil when the soil layer is overlying a rigid base; particularly when the soil layer thickness iscomparable to or less than the width of the rigid foundation. The effect of the bedrock position and its shear
strength properties are often not considered in conventional foundation design. A rigorous bearing capacity
solution for a restricted soil layer was introduced by Farzaneh and his co-researchers. In this study thepossibility of defining a modified collapse mechanism is investigated and consequently a revised collapse
mechanism by extending the original model is presented. The effects of the loading parameters, such as
eccentricity and inclination, and the influence of soli-substratum interface roughness on bearing capacity arepresented and discussed in detail. In addition, a detailed parametric study is carried out to evaluate the effects ofmain variables in determining the ultimate bearing capacity of shallow foundations on restricted soil, using the
proposed mechanism. Results are finally presented in design charts for practical use in geotechnical engineering.
Keywords: Bearing Capacity, Upper-Bound Limit State Analysis, Rotation-Translation Collapse Mechanism,
Rigid Basebe applied for calculating the bearing capacity of aconfined soil layer overlying a substratum. The
presented collapse mechanism included three rigid
blocks of which two blocks had rotationaltranslational movements and the other one just had
translational movements. They assumed theinterface properties can be indicated on a vast rangeof between completely smooth and completelyrough. They identified no shear strength factors forsoil-substratum interface as “perfectly smooth”, on
the other hand when these parameters were equal tonatural properties of beyond the soil layer; it was
assumed “perfectly rough”. The three block failure
mechanism is illustrated in Fig. 1. This figure
shows a strip footing resting on a thin layer of soil
overlying a rigid substratum.
The analysis conducted by [4] was based on an
upper bound state theorem; and they used the logspiral surface algorithm to derive the surface
equations. In current research the collapse
mechanism is modified by changing the equation ofslip surfaces. The modification can optimise thebearing capacity results also introduce the

INTRODUCTION
The presence of a substratum beneath a
restricted soil layer can have significant influenceon the bearing capacity of the soil layer. On theother hand the shear strength of soil and substratum
interface has a direct proportion on the figurationand size of soil collapse mechanism. This issue has
rarely been seen in the evaluation of bearing
capacity of confined soil layer. A number ofinvestigations have been conducted in this specificfield, Mandel & Salencon [6] focused on the effectof rigid base under a soil layer on bearing capacity.
They calculated the capacity of soft ground layer
on a rigid base according to the theory of limit
equilibrium. They categorized the interface of thesoil and the rigid base under two boundary
conditions. The friction condition of interface wasassumed (i) perfectly rough and (ii) perfectly
smooth. They presented the design charts forshallow foundation under eccentric applied load.
Farzaneh et al [4] introduced a slip surface equation
based on upper bound limit state theorem that can

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GEOMATE-Nagoya, Nov.13-15, 2013

For generating a new failure mechanism which
is based on Farzaneh et al [4] solution, a new groupof slip surfaces should be introduced in order toform kinematically admissible composite failure
mechanism. The new family of slip surfaces isobtained by altering the orientation of convexity ofrotational-transitional blocks that will be clarified
more in the following.

innovative solution for bearing capacity of shallow
foundation on a confined soil layer. In thefollowing, the new collapse mechanism isintroduced then verified by comparison withprevious solutions and finally the suggested design
charts are illustrated.

Slip surface for one block failure mechanism
Fig. 3 displays rigid block ABC which isaffected by translational and rotational velocities
simultaneously. V 0 and rω represent thetranslational and rotational velocities respectively.
Rotation takes place clockwise around the origin ofpolar coordinates (point O) and vector (V0) is
directed to the right side. The assumption velocities
are assigned to soil mass. To meet the plastic strain
compatibility condition, slip line AB should form
an angle φ with the vector of the relative velocity(V0+rω) at the whole points. It is assumed thatblock ABC slips on mass soil. Due to fixed soil
mass, the reaction of velocities, such as VM on an
optional point (M), causes to block ABC slips todownward.

Fig. 1 Translation-rotation failure mechanism [4]A NEW COLLAPSE MECHANISM
Problem Description
A rigid strip footing of width B is located on ahomogeneous cohesive frictional soil. The
thickness of the soil layer is H, which is confinedby a rigid base. The soil layer is considered to be an
isotropic, homogenous and assumed to follow the
Mohr-Coulomb plasticity criterion. The parameters
e and α signify the amount of eccentricity andinclination of the applied load respectively. The
foundation is assumed to be "perfectly rough". A
schematic diagram of the problem, analysed in thispaper, is shown in Fig. 2.

Fig. 3 Determination of the slip surface between arotational- translational black at the rest of masssoil
Two adjacent points, D and E with coordination
factors (r 1 , θ 1 ) and (r 2 , θ 2 ) respectively, should beconsidered for deriving the slip surface equation on
AB slip line. In Fig. 4 the geometric problem andthe required angles for obtaining the formulation
are illustrated.
In Fig. 4, α is the angle between the velocity
vector of block ABC at point D (V 1 ) with theradius of OD, β is the angle between sector DE andline DF which is drawn perpendicular to OE, and λis the angle between radius OD and sector DE.

Fig. 2 Strip footing under eccentric and inclined
loading based on a thin layer soil.

Derivation of Slip Surfaces

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GEOMATE-Nagoya, Nov.13-15, 2013

be resolved explicitly. However it can be easily
treated by the finite difference method [4].
C

A

E
V1

D

Slip surface for multiple block failure mechanism

F

Fig. 6 shows the collapse mechanism of
ABCDE including two rigid blocks ABC and
BCDE, which are subjected to velocities (V 01 ,ω 1 )
and (V 02 ,ω 2 ), respectively. The first block (block1) is assumed to rotate about point O 1 and thesecond one (block 2) about point O 2 .

∆θ = θ2 − θ1
B

O

V0

y02

Fig. 4 Determination of the new slip surface
equation

O2
2ω

x02
E

According to triangles ODE and DEF yields:

B

Y

A
V01

X
V02
D

EF = (r1 sin∆θ)tan(λ + Δθ − π/2)

Block 1

(1)

C

x01

Block 2
1ωAt limit, where ∆θ→0 , ED becomes tangent tothe slip line at point D and makes following theassociated flow rule, angle φ with V 1 ,EF→dr. It
follows that:

dr = (r1dθ) tan (α + ϕ − π/2)

y01

O1

Fig. 6: Slip surface between two rigid blocks withrotational and translational movements(2)
To define the equation of velocity discontinuity
between two blocks, BC, it is more convenient touse local Cartesian coordinates (x 1 , y 1 ) and (x 2 , y 2 )assigned to block 1 and block 2, respectively as
shown in Fig. 7.

In Eq. (2), angle α needs to be determined.
By considering the velocity diagram at an
optional point I on the slip line (Fig. 5) andsignifying the angle between rω and the resultant
velocity, V, by γ, the equation of α can be obtained.

O Y





Vo
α = arc cos .sin(π − θ V + θ) 
 V 2 + (r ω) 2 + 2rωr o cos(π − θ + θ)

o
V



X

(3)

r2

Block1V12

Block2

O2

y2

x2

M
r1
y1
O1
x1

V1
V0

I

Fig. 7 Relative velocity on optional point
Referring to the associated flow rule (normality
condition) the equation of slip surface between two
blocks can be derived:
V0

 
 
T . V12 = T . V12 . cos(ϕ )O(4)where T is the tangential vector of the discontinuity
surface at point "M" and V 12 is relative velocity
between two blocks.
As indicated by substituting the local Cartesian
coordination in Eq. (4) the final equation can beobtained as follow:

Fig. 5 Velocity Diagram at the point I in slip line
AB
Since α is a non-linear function of variables rand θ, obtained differential equation (Eq. 3) cannot

675

GEOMATE-Nagoya, Nov.13-15, 2013
2
2 )
(V12y
tan 2 ϕ − V12xdY 2 + 2 V12x V12y sec2 ϕ dX dY +
2
2 )
(V12x
tan 2 ϕ − V12ydX 2 = 0collapse mechanism. As it shown on Fig. 9 thebearing capacity stays steady after a particulardepth. It means that beyond the special depth theeffect of substratum layer is neglected on bearing
capacity of overlaying soil layer. In the present
study, this depth is called “the effective depth”. In
the perfectly rough interface, due to inclination of
the collapse mechanism to extend the substratum
interface, the effective depth is greater than thecompletely smooth interface when the otherparameters are same.

(5)
Complete details of all above equations can befound in [1].
Modified Failure Mechanism
As explained by slip surface introduction, a newcollapse mechanism based on upper bound solution
can be carried out. Fig. 8 demonstrates theevaluated failure mechanism which can endure theeccentric and inclined applied load. In order toachieve the ultimate upper bound bearing capacity,
the internal energy dissipation rate should be equal
to the rate of work done by traction and body forces[3].
For minimising obtained ultimate load, requires
to use an algorithm by which optimises the variablefactors that are affected in bearing capacity. Hence,
Generic Algorithms (GAs) [5] is used in the current
study.

Fig. 8 A schematic diagram indicating the proposed
modified collapse mechanism
RESULTS AND DISCUSSIONS
For a comprehensive survey, achieved results
are shown as graphical charts. By using this type ofchart, the effects of each spectacular parameter canbe seen separately. One of the most importantparameters is the (H/B) ratio that is the rigid base’s
depth function. The ultimate applied load indicatesas a non-dimensional ratio q u /C (C is the soil
cohesion), although values of N factors can beseparately indicated as a result. Eccentricity (e) andinclination (α) of applied load are two significant
factors on the bearing capacity of foundation that
influence the depth of the failure mechanism. Fig. 9
represents a typical graph that illustrates thebearing capacity results.
The parametric study is more applicable forengineering goals; therefore it needs to identify the
specific depth of bed rock which can limit theFig. 9 Practical design graphs for bearing capacityof eccentrically and inclined loaded foundation(perfectly rough interface)
The other significant depth value is the turning
point on the bearing capacity of foundation in
perfectly smooth interface case. The bearing
capacity tends to increase by confining theformation of the failure mechanism, although thelack of shear strength of interface turns to decrease
the bearing capacity. The interaction between these
two opposing factors causes unsteady raise in the
bearing capacity of shallow foundations so that itreaches a minimum value, even less than theamount of bearing capacity in the absence of a rigid
base. This specific depth is named “the criticaldepth”.

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GEOMATE-Nagoya, Nov.13-15, 2013

capacity of foundation and the consequence of bed
rock presence on bearing capacity simultaneously.

The inclination of applied load can reduce thebearing capacity. In the current research theinclined load shrinks the depth of the failure
mechanism. It causes to vanish the effect of bed
rock in a reduced amount of H/B ratio.

VERIFICATION
However, a lack of investigation in this specificfield of bearing capacity of foundation iscompletely obvious, the few previously mentioned
examples of technical literature that were used forverification. In addition, particular cases [7]-[8][9], in the bearing capacity of foundation on twolayer soil in which the failure mechanism becauseof rigidness of beneath layer is restricted to beyond
layer and the layer interface give a goodverification in this case.
Comparative results are tabulated in Table 1.
According to Table 1 the current study results arecompared with the two previous investigations thatwere mentioned before.
Table 1 Comparison of different methods forcalculating the bearing capacity factor (N c ) for
vertical loaded foundation on an undrained soil
layer (φ=0°), confined by a rigid base.
Perfectly Smooth Interface

Fig. 10 Practical design graphs for bearing capacityof eccentrically and inclined loaded foundation(perfectly rough interface)
In Fig. 10 the drop of effective depth, incomparison with Fig. 9, is obviously seen with only
the angle of inclination increasing. In particularcase the increment of α from 10° to 20° decreases
the effective depth ratio from 1.5 to 1. The twogroups of graphs depict a very similar situation
with the single exception being the increase in theangle of inclination.
The factor of presence inclined load on bearing
capacity has been considered by previous studies.
Hansen introduced inclination factor that was very
conservative then it was modified by Vesic [2]Nevertheless the inclination of applied load has
rarely been studied on bearing capacity of soil layer
overlying a rigid base the current research presents
the applied graphs for evaluating the bearing

[4]

[6]

Current
Study

H/B

Nc

Nc

Nc

0.10

6.40

6.01

7.12

0.12

6.18

5.50

6.33

0.16

5.27

4.96

5.35

0.20

4.83

4.72

4.80

0.25

4.42

4.42

4.39

0.33

4.11

4.15

4.05

0.50

3.97

3.99

3.75

1.00

4.44

4.43

4.21

2.00

5.17

5.14

5.17

3.00

5.17

5.14

5.17

For further proof, a specific case is investigatedin the bearing capacity of a strip footing resting on
a two-layer foundation soil sand/clay by akinematical approach in limit analysis which wasintroduce by Soubra et al [8]. The collapse
mechanism is entirely contained in the sand layer

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GEOMATE-Nagoya, Nov.13-15, 2013
ACKNOWLEDGMENT

for high inclination. In that case, a sliding along theclay-sand interface is observed [8].
The verification of current study can be
possible with the particular case in Soubra’s
collapse mechanism [8]. The calculations are
performed for a value of load inclination when φ =30° C d =17 kPa, B=1m, φ d =0° γ=17 kN/m3
H/B=0.5 α=20° and the results are presented inTable 2.

The authors would like sincerely toacknowledge the guidance and technical advice
provided by Dr Orang Farzaneh, the academic staff
member of the University of Tehran, and Dr
Farajollah Askari, the academic staff member of
the International Institute of Earthquake
Engineering and Seismology, Iran.
REFERENCES[1] Afshar-Mazandaran R, “Bearing Capacity of
Soil Layers on Rigid Base by Upper Bound
Method of Limit Analysis”, Submitted as aM.sc Thesis, University of Tehran, Iran, 2010

Table 2 The current study result in comparison to[8] and [4] for a specific case

P/γ.B

[8]

[4]

2. 4502. 462Current
Study
2.701

[2] Bowles JE, “Foundation Analysis and Design”,
McGraw-Hill, 1996, ch. 4.
[3] Chen WF & Liu XL, “Limit Analysis in Soil
Mechanics”, Elsevier Science Publishers B.V.
1990.

The main purpose of introducing the modified
slip surface is development of Farzaneh et al.
collapse mechanism. By combining the original
and modified slip surfaces, four collapse
mechanisms are presented which only two of them
have been explained in this paper. The answer
optimization is carried out by choosing theminimum answer of each of them.
CONCLUSIONS[4] Farzaneh O, Ganjian N, Askari F, “RotationTranslation Mechanism for Upper-Bound
Solution of Bearing Capacity Problems”,
Computers and Geotechnics, Vol. 37, 2010, pp.
449-455.
[5] Gen M, Cheng R,“Genetic Algorithms andEngineering Optimization”, Wiley, 2000.

The ultimate bearing capacity of shallow
foundations overlaying a soil layer restricted by arigid base has been investigated using a revised
formulation based on the limit state theorem.
Rigorous solutions for a wide range of shear
strength and geometry parameters of soil and sub
stratum interface have been obtained.
The effects of depth of rigid base on the bearing
capacity, inclination and eccentricity of the applied
load have been studied. For each kind of situation,
there exists a “critical depth” where the appearanceof rigid base vanishes on bearing capacity offoundation completely. Finally the results obtained
have been demonstrated in terms of bearing
capacity factors such as N c and N γ in a graphicalform to be applicable in solving practicalfoundation design problems. The modified upperbound can optimise the prior failure mechanism,
which was presented by Farzaneh et al [4].

[6] Mandel J & Salencon J, “Force Portante d’unsol Suruneassiserigide (Etude theorique)”, Geotechnique, Vol. 22(1), 1972, pp. 79-93.
[7] Merifield RS, Sloan SW & Yu HS, “Rigorous
Plasticity Solutions for the Bearing Capacity of
Two-Layered Clays”, Geotechnique, Vol. 49,
No.4, 1999, pp. 471-490.
[8] Soubra AH, Abdel Massih DY & El-Hecham E,“Bearing Capacity of Eccentrically and/or
Obliquely Loaded Strip Footing over TwoLayer Foundation Soil by a Kinematical
Approach”, VIII International Conference on
Computational Plasticity, Barcelona, 2005.
[9] Zhu M, “Bearing Capacity of Strip Footing on
Two-Layer Clay Soil by Finite Element
Method”, ABAQUS Users, Conference, 2004.

678

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SOME THOUGHTS ON THE ULTIMATE RESISTANCE OF PILES
Stephen Buttling1
GHD Geotechnics, Australia

1

ABSTRACT
Australia was one of the first countries to establish a standard for pile design using Limit State principles.
This has since been revised, and the current version is AS 2159-2009. After about 25 years of effort, theEuropeans finally produced EN 1997-1 in 2004, and it is apparently slowly gaining acceptance. Japan, Canada,
and the USA have also been using limit state, or load and resistance factor, design codes for some time. One ofthe problems is the confusion surrounding the definition of ultimate pile resistance, or capacity, and this getshighlighted when international competitions are held to predict the outcome of static load tests. In order to try tominimize this confusion, three compatible definitions are proposed, in the hope that this will add clarity.
Keywords: Piling, Ultimate Pile Resistance
INTRODUCTION

consideration”, in this case the ultimate limit state.
These parameters might also be considered as“characteristic strength parameters”, and their use
will therefore lead to determination of acharacteristic strength, so in this case:

When using a limit state design code such as AS
2159 [1] it is important to understand the principles
of limit state design in which, when considering the
Ultimate Limit State, a design action consisting ofloads or deflections which have been factored up toachieve a magnitude which is unlikely to be
exceeded, must be less than a capacity which has
been factored down such that the actual capacity is
unlikely to be less. This ensures that “failure” will
not occur. We express this mathematically as:
,

(2)

,

This is really the only design method
contemplated by AS 2159 [1], although otherstandards encompass other methods. For example,
the European Standard, EC7 [2], allows a number ofdesigns to be produced, one for each borehole on a
project. Each one of these is then referred to as aprofile or “model pile”, and each will produce anultimate geotechnical pile capacity, Rd,ug. A numberof possible values of capacity therefore exist, and thecharacteristic value can be found by dividing themean value by a factor (ξ3) or the minimum value by
a different factor (ξ4), and using the lower of the twovalues calculated. This still satisfies therequirements of AS 2159 [1] in so far as Rug isestimated by calculation from Rd,ug. Guidance on thefactors to be used are given in a table in Annex A to
the standard, or in a “National annex” which allows
each European country to choose their own, but are
in any event dependent on the number of profiles ormodel piles available, i.e. the number of boreholes.
The suggested values from Annex A are shown in
Table 1, which illustrates how the “characteristic”(1)

where Ed = design action effect, and Rd,g = design
geotechnical resistance.
Characteristic strength
This design geotechnical resistance is factored
down by taking account of uncertainty, from what
AS 2159 [1] refers to as “the ultimate geotechnicalstrength of a pile”, Rug, defined in clause 1.3.37 but
hardly used in the body of the standard. It is actually
only a theoretical value, and is probably the same aswhat might otherwise be termed the “characteristic
ultimate geotechnical strength or capacity” of a pile.
This term is used elsewhere around the world, andmeans the ultimate geotechnical strength which a
proportion, typically 95%, of a collection ofidentical piles would be expected to be stronger
than. This is alluded to in the definitions in Table 1.1of the standard, when it says that Rug “is estimatedeither by calculation (Rd,ug) or by testing (Rt,ug)”.
Considering first design by calculation, it may be
assumed that a number of boreholes are reviewed, ageotechnical model produced, and design parameters
selected which are “a conservative estimate of thevalue likely to occur at the limit state under

Table 1: Factors to be applied to minimum andmean pile load test results, from EC7 [2]ξ for n =
ξ3
ξ4
679

1
1.40
1.40

2
1.35
1.27

3
1.33
1.23

4
1.31
1.20

5
1.29
1.15

7
1.27
1.12

10
1.25
1.08

GEOMATE-Nagoya, Nov.13-15, 2013

value is produced from a collection of values, thespread of which is taken into account by applying
different factors to the mean and the minimum

3,200 kN for static load tests and 3,655 kN for
dynamic load tests, or a mean design ultimate
geotechnical strength of 3,490 kN for static load
tests and 3,990 kN for dynamic load tests, whicheveris the more critical.

Geotechnical strength reduction factor
It is not being suggested that these factors should
be used in a pile design under AS 2159 [1], since apart of these factors is associated with variability ofgeotechnical parameters across a site, and this is also
assessed within the geotechnical strength reduction
factor. Nevertheless the principle still applies, that acharacteristic value of the ultimate geotechnicalstrength can be calculated, either by using
characteristic strength parameters, or by applying
factors to a collection of individual capacity values.
Once this characteristic geotechnical strength has
been determined, then the geotechnical design
strength can be found by reducing the characteristic
strength by the geotechnical strength reduction
factor, φg, and this involves a risk analysis. As
explained in detail by Chambers and Lehane [3], theamount of testing proposed has a significant impact
on the value of φg, but this is applied to the ultimate
design geotechnical strength, and not to the test
value.
It is perhaps easiest to see how this works with ahypothetical case. Taking the example from Figure 1(a) of Chambers and Lehane [3], a project using 300
driven prestressed precast concrete piles is
considered, each with an Ed = 2,000 kN. It is further
assumed that there are four boreholes, and that these
are used to produce a geotechnical model withstrength parameters which are a cautious estimate of
the strength which will apply at the ultimate limit
state. Thus the design geotechnical strength, Rd,g, isgiven by:,,

Use of pile test results
In this, “conventional” use of pile design andtesting, the geotechnical parameters are used to carryout a design on paper, and the testing is used toconfirm the design. Thus if the design ultimate
geotechnical strength is 2,855 kN, any static load
test result above this value confirms the design. On
the other hand, if the model pile method has been
used, then any static load test result above 2,665 kN
confirms the design.
As opposed to a conventional calculation, somedesigners may choose to actually carry out thedesign on the basis of pile tests. This appears to becontemplated by AS 2159 [1], since it states in Table
1.1 that the characteristic ultimate geotechnicalstrength, Rug can be “estimated from ….. Rt,ug”,
although it gives no guidance as to how this estimate
is to be made. Again this issue has been addressed in
EC7 [2], which proposes that:
;

;

;

;

(4)

Here the subscript m means measured, and hence
for comparison with AS 2159 [1]:
;

≡

(5)

;

The correlation factors ξ to derive characteristic
values from static pile load test results (n – thenumber of tested piles) are given in Table 2.

(3)

Table 2. Factors to be applied to static load test
results, after EC7 [2]If it is assumed that 6 tests are carried out (2%),
and that the basic geotechnical strength reduction
factor, φgb = 0.5, then this will give φg = 0.7 forstatic load tests and φg = 0.61 for dynamic load tests.
Therefore the paper design, using the characteristic
strength parameters, must produce a design ultimate
geotechnical strength, Rd,ug, of 2,855 kN if staticload tests are used, or 3,300 kN for dynamic tests.
For comparison, the model pile method could be
used but, as stated above, care must be taken not tomake double allowance for soil variability risk. One
way to assess this is to check the effect on φg ofchanging the site risk ratings from 1 to 5. This isseen to decrease φg by 0.05, and applying this extra
factor to the values for static load tests leads to Rd,ug= 2,665 kN and for dynamic load tests to Rd,ug =
3,045 kN. On the basis of 4 boreholes this meansthat each individual model pile must have aminimum design ultimate geotechnical strength ofξ for n =
ξ1
ξ2

1
1.40
1.40

2
1.30
1.20

3
1.20
1.05

4
1.10
1.00

≥5
1.00
1.00

This method is obviously particularly relevant todriven piling and where a significant amount of
testing is utilised. Although conventional design
methods may be used to estimate the length of piles
and the driveability, it is possible to rely mainly on
PDA testing as the means of “designing” the piles.
In the hypothetical case referred to above there
were 300 piles on the project, and it was proposed totest 2% of them, so we have 6 test results and 6
values of Rt,ug. Again Rug is the characteristic
ultimate geotechnical strength which it could
reasonably be expected that all piles would exceed,
680

GEOMATE-Nagoya, Nov.13-15, 2013

if all of them were tested. Since only 6 piles are to
be tested, there is clearly a risk that other piles could
have lower Rt,ug values if they were tested, so somemargin for variability of soil within the site needs tobe made. As with the model pile case, care is needed
not to make double allowance for this risk, since a
φg factor will still be applied. Again the factors
proposed in Annex A to EC7 [2] may be used as a
guideline.
The correlation factors ξ to derive characteristic
values from dynamic impact test results a, b, c, d, e, (n –the number of tested piles) are given in Table 3.

arisen, and not least of these is the definition of thelimit states, particularly the ultimate limit state, orULS. AS 2159 [1] defines the ultimate geotechnicalstrength as “the resistance developed by an axiallyor laterally loaded pile or pile group at which static
equilibrium is lost or at which the supporting groundfails”. This definition accords with common
definitions of ultimate geotechnical capacity, being aload at which deformations continue without
increase in load, i.e. the supporting ground fails.
However, AS 2159 [1] also defines the ultimate limit
state as a “condition for which a system is designed,
beyond which it ceases to fulfill its intended
function and becomes unfit for use. (Note: There arerecognized limit states, e.g. for fire, serviceability,
stability and strength.)” Unfortunately a piled
foundation can become “unfit for use” to support a
structure long before “the supporting ground fails”.
AS 1170 [4], wherein the structural design actions
are defined, also defines limit states as “states
beyond which the structure no longer satisfies thedesign criteria”, and ultimate limit states as “states
associated with collapse, or with other similar formsof structural failure. (Note: this generally
corresponds to the maximum load-carrying
resistance of a structure or structural element but, insome cases, to the maximum applicable strain or
deformation.)” This would also appear to allow that
ultimate limit states are associated with collapse, i.e.
including foundation failure, but also that they could
include states where the design criteria are no longer
satisfied, for example as a result of excessive strain
or deformation. When we consider piled
foundations, particularly single piles which, whentested, tend to increase in capacity, even slowly, as
settlement increases, we clearly have difficulty indefining a settlement at which we will say that theultimate resistance has been achieved. If we cannot
define a settlement, then defining the ultimate
resistance becomes even more difficult.

Table 3. Factors to be applied to dynamic pile test
results, after EC7 [2]ξ for n =
≥2
1.60
1.50

ξ5
ξ6

≥5
1.50
1.35

≥ 10
1.45
1.30

≥ 15
1.42
1.25

≥ 20
1.40
1.25

a

The ξ-values in the table are valid for dynamic impact
testsb
The ξ-values may be multiplied with a model factor of
0.85 when using dynamic impact tests with signal
matchingc
The ξ-values should be multiplied with a model factorof 1.10 when using a pile driving formula withmeasurement of the quasi-elastic pile head displacement
during the impactdThe ξ-values shall be multiplied with a model factor of
1.20 when using a pile driving formula without
measurement of the quasi-elastic pile head displacement
during the impacte
If different types of piles exist in the foundation,groups of similar piles should be considered separately
when selecting the number n of test piles

Therefore, given 6 dynamic pile test results withsignal matching on a selection from 300 piles, usedas the principal method of design, the minimum total
pile capacity must be:
,

,

.

.

Ultimate geotechnical resistance by design
This leads directly to the question of thedefinition of the ultimate geotechnical strength of apile. Is it the strength at which the supporting groundfails? This definition would be compatible with apaper design, in which the strength of the soil isestimated, usually layer by layer, and from this thetwo components of pile resistance, shaft friction andend-bearing are determined. Typically the shaft
friction will be calculated by some sort of adhesion
factor times the local strength, whether in total stressor effective stress terms, and the end-bearing will befound by applying a traditional bearing capacity
theory to the base. By adding these components
together we are implicitly assuming that all the soils
are elastic/perfectly plastic, and so are not subject tobrittle behaviour with post-peak strengths less thanthe peak, and that the pile is pushed far enough that(6)and the mean of the results must be:
,

,

.

.

(7)

whichever is the more critical.
LIMIT STATESOne of the intentions of introducing limit state
design methods into geotechnical engineering was torationalise the differences which occurred when
limit state design methods were being used forstructural design, and working stress designs werebeing used for foundations. It was probably also
hoped that this might lead to some simplifications in
the processes. However, other complications have681

GEOMATE-Nagoya, Nov.13-15, 2013

all elements have reached their peak strength. Thisultimate capacity will be called Qu3. If thesestrengths are the characteristic strengths of eachelement, then the calculated pile resistance will also
be the characteristic resistance, which is represented
by the brown line in the figure below, which we willcall Qu3,k. In this analysis no consideration is given
to settlement.

will be assumed that the ultimate resistance has beenreached. However, it may be that a pump with ahigher discharge capacity could achieve moreincrements. This concept is embraced by the Brinch
Hansen [7] failure criterion, which defined thefailure load of the pile as the load at which thesettlement is 4 times the settlement at 80% of that
load. In other words, it is defining a point at which
the load/settlement curve has become very steep, but
not vertical. This will produce an ultimate resistancewhich is less than that produced by Chin’s
hyperbolic extrapolation, and will be referred to as
Qu2.
A definition commonly used in the UK andEurope, where piles are generally founded onmaterials which can be described as soil, is that theultimate resistance is given by the load at which
settlement continues without increase in load. It has
also been found, in practice, that piles in granularmaterials may continue to increase in capacity, even
if only slowly, with increasing settlement. This has
led to definitions which limit the settlement to 10%of the pile diameter, as in EC7 [2], and this has
seemed to produce loads and deflections at ultimate
capacity, Qu2, for piles in fine grained and in
granular soils which are compatible. Fellenius [8]has stated that “the concept of bearing capacity does
not apply to a pile toe”, and that “toe resistance does
not exhibit an ultimate value but continues toincrease with increasing toe movement.”

Ultimate geotechnical resistance by test
A number of complications arise as soon as wetry to introduce real physical conditions in a load
test. The work of Chin [5, 6] showed that, towards
the later part of a static load test, the relationshipbetween load and settlement was hyperbolic, withthe load asymptotically approaching the ultimate
value. If this is the case then, in theory, the load will
only reach the ultimate value at an infinite
settlement, which means that this is only ahypothetical value, higher than other more usefulestimates of ultimate resistance, and probably
compatible with the design value referred to above.
It will therefore also be referred to as Qu3. In fact, if
a large number of piles are constructed inhomogeneous soil conditions, to the same geometry
and design, and subsequently tested and the ultimate
resistance determined using the Chin method, thenthe individual values of Qu3 might be expected to be
distributed normally about the mean, as shown by
the blue line in Fig. 6, with the characteristic
resistance at 1.96 times the standard deviation below
the mean. In this example the mean is 1000 kN, thestandard deviation 150 kN, and the characteristic
resistance Qu3,k = 706 kN.

Settlement at ultimate geotechnical resistanceTo this debate over ultimate strength the questionof what settlement should be used to define theultimate geotechnical strength on a load-settlement
chart needs to be added. As mentioned above, forsoils in the UK a settlement of 10% of the pile
diameter is often taken as defining ultimate endbearing pressure, and therefore ultimate geotechnicalstrength, Qu2, since the ultimate shaft friction isusually achieved at much smaller settlements, suchas 0.5 to 2% of pile diameter (Fleming et al [9]).
However, others have proposed much lower
settlement figures, and one of the better known is theDavisson Offset Limit from Davisson [10]. In thiscriterion the toe settlement is considered to belimited to a fixed amount plus an amount which
varies with pile diameter. These were chosen by
Davisson [10] as 0.15 inches (4mm) and 1/120 of
the pile diameter respectively. These two numbers
are added together and applied as an “offset” to thesettlement. The remaining component is an elastic
component, assuming that all of the load at the pilehead is transmitted to the pile toe. This produces aline, drawn from the offset value, for the increasing
shortening with increasing load, which has a
gradient of L/AE, where L = pile length, A = crosssectional area, and E = elastic modulus of pilematerial. The Davisson Offset Limit will generally

0.0 030.0 025

0.0 020.0 015

0.0 01

0.0 005

00

Fig. 6

500
1000
1500
Pile resistance (kN)

2000

Distribution of ultimate pile resistance, Qu3

In practice, other than in Constant Rate of
Penetration tests, the load in a static load test isapplied in small, finite, increments. At some stage,as the ultimate resistance is approached, it may bethat the rate at which the pile is settling, multipliedby the area of the hydraulic jack or jacks, is greaterthan the pump discharge capacity. In this case it will
not be possible to reach the next load stage, and it
682

GEOMATE-Nagoya, Nov.13-15, 2013

produce a lower ultimate resistance, Qu1, than theother criteria, but it is especially popular because of
its use in dynamic pile testing. Because it considers
the ultimate resistance at a relatively small toe
displacement, it is more compatible with dynamic
pile testing, with toe quakes in the order of 5 to 10
mm, than other methods where total settlements of
10% of pile diameter are considered.
Nevertheless, there is clearly no agreement on
what settlement relates to ultimate pile resistance,
and therefore at what point on a load/settlement
curve the ultimate resistance can be defined. Thishas been very well illustrated by Fellenius [11] in hissummary of the contributions to a pile prediction
event which he organised in 2011, for a CFA pile
formed in glacial till near Edmonton, Alberta,
Canada. Figure 8 shows the results of predictions by
41 different people from 15 countries and mostcontinents and, while there is clearly a wide scatterin the predicted performance, the main purpose ofincluding this chart is to show the range of values ofsettlement at which the ultimate capacity of this 406
mm diameter CFA pile was selected. It appears to befrom about 5 to 220 mm.

The results are not yet published, but those who
made predictions have been sent an initial summaryof the results, and Fig. 9, Fig. 10 and Fig. 11 show
the same effect for test piles TP1, TP2 and TP3
respectively.

Fig 8. Predicted
ultimate
resistancesandsettlements for a 500 mm diameter pile in glacial till,after Fellenius [11]Fig.11 Predicted
ultimate
resistancesandsettlements for TP3, a 450 mm diameter auger
displacement pile with an expander body in sand in
Bolivia, after Fellenius [12]Fig.10 Predicted
ultimate
resistancesandsettlements for TP2, a 450 mm diameter auger
displacement pile in sand in Bolivia, after Fellenius[12]

Fellenius has continued his interest in this aspectof foundation engineering, and carried out anotherprediction exercise in 2013, based on 4 piles insandy soil in Bolivia.

Again the only aspect of these charts which is
being considered here is the range of settlements at
which the ultimate pile resistance has been selected,
for TP1 this would appear to be about 2 to 260 mm,
for TP2 about 5 to 95 mm, and for TP3 about 5 to
106 mm. TP1 was 400 mm in diameter, and piles
TP2 and TP3 were both 360 mm diameter. This
seems to demonstrate that there are very widelydiffering views on the settlement at which theultimate pile resistance should be measured. As
stated at the beginning of this section, if there is sucha wide disagreement on settlement, then there can be
no hope of agreeing on an ultimate pile resistance. It
is therefore proposed that three separate definitionsof ultimate pile resistance are considered, being Qu1,
Qu2 and Qu3 in order of increasing numerical value.
Qu1 is based on the Davisson Offset Limit, Qu2 on
the load at a settlement of 10% of the pile diameteror the Brinch Hansen criterion, and Qu3 as the paper

Fig. 9 Predicted
ultimate
capacities
andsettlements for TP1, a 450 mm diameter bored pilein sand in Bolivia, after Fellenius [12]683GEOMATE-Nagoya, Nov.13-15, 2013

REFERENCES

design value or that produced by a Chinextrapolation of a static load test load/settlement
curve. It is believed that clear use of these threedefinitions will enable better comparison between
test and analysis methods. When compared to AS
2159, it should be noted that:[1] AS 2159-2009, “Australian Standard: Piling –Design and Installation”. Sydney: Standards
Australia, 2009.
[2] EC7, “Eurocode 7: Geotechnical design – Part
1: General rules”. BS EN 1997-1:2004. London:
BSI, 2004.
[3] Chambers H and Lehane BM, “An assessmentof the geotechnical strength reduction factors
specified in the new Australian PilingStandard”, Australian Geomechanics, Vol 46
No 4, December 2011, pp. 71-78.
[4] AS 1170.0:2002, “Structural design actions”.
Sydney: Standards Australia, 2002.
[5] Chin FK, “Estimation of the ultimate load ofpiles not carried to failure”, Proc. 2nd South East
Asian Conference on Soil Engineering, 1970, pp.
81-90.
[6] Chin FK, “Discussion on pile test, Arkansas
River Project”. ASCE, J. for Soil Mechanics
and Foundation Engineering, Vol 97, SM6, pp.
930-932.
[7] Hansen J B, “Discussion on hyperbolic stressstrain response – cohesive soils. ASCE, J. of
Soil Mechanics and Foundation Engineering,
Vol 89, SM4, 1963, pp. 241-242.
[8] Fellenius BH, “Recent advances in the design ofpiles for axial loads, dragloads, downdrag, andsettlement”. Proc. Seminar by ASCE and Portof New York and New Jersey, 1998, 19p.
[9] Fleming W G K, Weltman A J, Randolph M F
and Elson W K, “Piling Engineering”, 3rd
Edition, Spon, 2006.
[10] Davisson MT, “High capacity piles”, Proc.
Lecture Series on Innovations in Foundation
Construction. ASCE, Illinois Section, Chicago,
1972, pp. 81-112.
[11] Fellenius B H, “Capacity and load-movement of
a CFA pile: A prediction event”, ASCE
GeoInstitute
Geocongress,
San
Diego,
Foundation Engineeering in the face of
uncertainty, ASCE, Reston, VA, 2013, pp. 707719.
[12] Fellenius B H and Terceros M, “Pile prediction
event in sands in Bolivia”, to be published.

(8),

and that, if characteristic strengths are used in thedesign, then:,(9)

Similarly:,(10)

CONCLUSIONS
1. It is noted that there are numerous
definitions of ultimate pile resistance(capacity) in use in different parts of theworld, and that these can lead to confusion
when working across national borders.
2. It is also noted that, apart from at sometheoretical infinite displacement, there is arelationship between load and displacementof a pile, such that the ultimate pile
resistance (capacity) corresponds to aprescribed displacement.
3. It is proposed that three ultimate pile
resistances(capacities)
bedefined,corresponding
tothreedifferent
displacements. These are:a. The ultimate pile resistance at apile head settlement defined by theDavisson Offset Limit Criterion.
b. The ultimate pile resistance at apile head settlement equal to 10%of the pile diameter, or by the
Brinch Hansen Criterion.
c. The ultimate pile resistancedefined by a calculation based on
ultimate shaft adhesion andultimate end-bearing capacity
regardless of displacement, or by
the Chin Hyperbolic extrapolationof a static load test.
4. Each of these three values will also have a
sub-value,
being
the
associatedcharacteristic value from a number of tests.
5. Most existing definitions fit within one ofthese three, but it is the acknowledgementthat the other values are also relevant, andmay be used by others, which is important.

684

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

WIRELESS SENSOR NETWORK FOR LANDSLIDE MONITORING
S. M. A. Motakabber, M. I. Ibrahimy and F. Anwar
Faculty of Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia

ABSTRACT
Every year all over the world many lives and properties are lost due to many geological catastrophes like,landslide or landslip. Manual and electronic monitoring systems are used for predicting the landslide. The
manual monitoring system is laborious and not practical. And most of the electronic systems are complex and
expensive. A wireless sensor network in conjunction with an underground pretension cable with a strain gage
sensor attached at one end is proposed for a simple landslide monitoring system. A mathematical model has beendeveloped for the system and the model is verified by simulation. The result shows that an early prediction of thelandslide is possible by using the developed system.
Keywords: Wireless Sensor Network, Landslide, Automated Monitoring System, Strain Gage Sensor, Geological
Catastrophe

wireless sensor network arrangements [3], [4] aremainly data collection networks. The wireless sensor
network recurrently collects the respective data andcollaboratively processes the measurements from thefield under study before forwarding them to thecentral monitoring station. The central monitoring
station executes more computationally-intensivealgorithms such as finite element modeling andparameter identification [5], [6] and acts as theexpert interface to the system. A wirelesscommunication system can be used to transmit thesensors sampled data and relevant information to a
distant central database server computer for analysis
purpose. The instant conveyed information would
allow us to implement instant disaster rescue
measures and to notify the land user to protect thepeople’s lives and properties.

INTRODUCTION
Worldwide, landslides cause about 1,000 deaths
per year and property damage of approximately US$
4 billion [1]. Existing manual solution is insufficientand sometimes it is costly for landslide prediction
and detection. Installing a single sensor formonitoring a wide hilly target area is not sufficient.
Most of the cases, the property of the hill is changed
in about every 10-15 meters distance. Wiring withmultiple sensors to a central data logger is also notreliable and practical as well since it requires
frequent maintenance. Therefore, wireless sensor
network system is used for real-time landslide
monitoring. Thin film strain gage pressure sensor
with high accuracy pressure measurement is clamedin the system [2]. A simple pretension undergroundcable attached with a strain gage at one end can beeasily used to measure the pressure of the soil asshown in Fig. 1.

SENSOR MODELING
A simplified force diagram of the proposedlandslide pressure sensor that is, pretension cablewith strain gage is shown in Fig. 2. Assume that a
pre tensioned still cable length of L is attached attwo end supports under the soil. If the linear
expansion coefficient of the cable is α L and thesurrounding temperature of the cable is changed ∆T
degree Kelvin then the change of cable length ∆L T
can be calculated as follows:

Fig. 1 Basic arrangements of the proposed wirelesssensor network system for landslide monitoring.
The measured pressure can be used to calculate
the landslide prediction and detection. A number ofsame kinds of sensor setup can be used formonitoring a wide land area. In this case, eachsensor is defined by a unique number within awireless network. This ID number can be easily used
to locate the landslip zone. A majority of theFig. 2 Simplified force diagram of the proposedlandslide pressure sensor.
685

GEOMATE-Nagoya, Nov.13-15, 2013

substrate is E S then at force equilibrium condition,

𝟏𝟏 ∆𝐋𝐋𝐓𝐓
𝛂𝛂𝐋𝐋 =
𝐋𝐋 ∆𝐓𝐓(𝟏𝟏)

𝐎𝐎𝐎𝐎, ∆𝐋𝐋𝐓𝐓 = 𝛂𝛂𝐋𝐋 𝐋𝐋∆𝐓𝐓𝑭𝑭𝑺𝑺𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺 ∆𝑳𝑳𝑺𝑺
=
(𝟗𝟗)
𝑳𝑳𝑺𝑺
Where, A S and L S are the cross section area andlength of the substrate respectively. F S is the force
on the substrate and ∆L S is the change in length of
the substrate due to force.

(𝟐𝟐)

When the land is slightly moved S distance fromits initial position then it creates a force F on force
plate as well as on the cable. If the Yang’s modulusof the cable is E then at force equilibrium condition,

From Eq. (9),

𝐅𝐅/𝐀𝐀
𝐄𝐄 =
∆𝐋𝐋/𝐋𝐋(𝟑𝟑)

𝑼𝑼𝑺𝑺 = �

𝟎𝟎

Where, A is the cross section area of the cableand ∆L is the change in length of the cable due toforce.

𝐎𝐎𝐎𝐎,

By considering the temperature effect, Eq. (3)can be rewritten as,
𝐅𝐅(𝐋𝐋 + ∆𝐋𝐋𝐓𝐓 )
𝐄𝐄𝐄𝐄

∆𝐋𝐋 =

𝑼𝑼𝑺𝑺 =

𝐎𝐎𝐎𝐎,
∆𝑳𝑳𝑺𝑺
𝑳𝑳𝑺𝑺

(𝟓𝟓)

The potential energy U W stored in the cable canbe calculated as follows:∆𝑳𝑳

From Eq. (4) and Eq. (6),𝑼𝑼𝑾𝑾 = �

∆𝑳𝑳

𝟎𝟎

𝐎𝐎𝐎𝐎,

𝑼𝑼𝑾𝑾 =

𝑬𝑬𝑬𝑬∆𝑳𝑳(𝑳𝑳 + ∆𝑳𝑳𝑻𝑻 )𝑬𝑬𝑬𝑬∆𝑳𝑳

=�

(𝟔𝟔)

𝟎𝟎

𝟐𝟐

𝟐𝟐(𝑳𝑳 + ∆𝑳𝑳𝑻𝑻 )
∆𝑳𝑳𝑳𝑳
=
𝟐𝟐

𝐎𝐎𝐎𝐎,

𝑼𝑼𝑺𝑺 = 𝑭𝑭 �𝑺𝑺

−

∆𝑳𝑳
�
𝟐𝟐

(𝟏𝟏𝟏𝟏)∆𝑳𝑳
𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺 ∆𝑳𝑳𝟐𝟐𝑺𝑺
�=
𝟐𝟐𝑳𝑳𝑺𝑺
𝟐𝟐

𝟐𝟐𝟐𝟐∆𝑳𝑳�𝑺𝑺 − �𝑳𝑳𝑮𝑮𝑮𝑮 𝑬𝑬𝑮𝑮𝑮𝑮 𝑨𝑨𝑮𝑮𝑮𝑮
𝟐𝟐(𝟏𝟏𝟏𝟏)

If the gage factor and the temperature coefficientof the strain gage are G and α respectively then thechange of resistance ∆R of the strain gage withrespect to the initial resistance R is calculated asfollows:

𝒅𝒅∆𝑳𝑳

∆𝑹𝑹

= 𝑹𝑹 �

𝑮𝑮∆𝑳𝑳𝑺𝑺𝑳𝑳𝑺𝑺+ 𝜶𝜶𝜶𝜶�(𝟕𝟕)

By combining Eq. (11) and Eq. (12)From Eq. (5) and Eq. (7), the potential energy U S
stored in strain gage substrate is calculated asfollows:
𝑼𝑼𝑺𝑺 = 𝑼𝑼𝑬𝑬 − 𝑼𝑼𝑾𝑾 = 𝑭𝑭𝑭𝑭 −𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺 ∆𝑳𝑳𝟐𝟐𝑺𝑺
𝟐𝟐𝑳𝑳𝑺𝑺𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺 ∆𝑳𝑳𝟐𝟐𝑺𝑺=
𝟐𝟐

𝑭𝑭 �𝑺𝑺 −The work U E done by the soil movement can becalculated by Eq. (5).

𝑼𝑼𝑾𝑾 = � 𝑭𝑭 𝒅𝒅∆𝑳𝑳

𝑭𝑭𝑺𝑺 𝒅𝒅∆𝑳𝑳𝑺𝑺

By combining Eq. (8) and Eq. (10)(𝟒𝟒)

𝑼𝑼𝑬𝑬 = 𝑭𝑭𝑭𝑭∆𝑳𝑳𝑺𝑺

∆𝑹𝑹 = 𝑹𝑹 �𝑮𝑮�

∆𝑳𝑳𝑳𝑳
𝟐𝟐

𝟐𝟐𝟐𝟐
∆𝑳𝑳
�𝑺𝑺 − �𝑳𝑳𝑺𝑺 𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺
𝟐𝟐
+ 𝜶𝜶𝜶𝜶�(𝟏𝟏𝟏𝟏)(𝟏𝟏𝟏𝟏)

From Eq. (4), if the Yang’s modulus E of thecable is very large then ∆T≈ 0 and Eq. (13) can be
rewritten as Eq. (14).

(𝟖𝟖)

Again, if the Yang’s modulus of the strain gage686

GEOMATE-Nagoya, Nov.13-15, 2013

∆𝑹𝑹 = 𝑹𝑹 �𝑮𝑮�𝟐𝟐𝟐𝟐𝟐𝟐
𝑳𝑳𝑺𝑺 𝑬𝑬𝑺𝑺 𝑨𝑨𝑺𝑺

+ 𝜶𝜶𝜶𝜶�

to measure the exact value of the force ordisplacement of the soil. This principle can help todevelop a simple and low cost real-time landslide orlandslip monitoring system. According to themathematical model, Eq. (13), for an efficientsystem, the Yang’s modulus of the cable must bevery large. Since, the still and carbon fiber cablehave very large Yang’s modulus; they can be used inthis development.

(𝟏𝟏𝟏𝟏)

Eq. (14) indicates that the change of strain gageresistance is directly proportional to the squire rootof the force and displacement of the land.

REFERENCESRESULT AND DISCUSSION[1] Lee S and Pradhan B, “Landslide hazard
mapping at Selangor, Malaysia using frequency
ratio and logistic regression models”,
Landslides, Vol. 4, No. 1, 2007, pp. 33-41.
[2] Hongye W, Kun L, Zhichou A, Xu W and Xun
H, “Ion-beam sputtered thin-film strain-gagepressure transducers”, Sensors and Actuators A:
Physical, Vol. 35, Issue 3, 1993, pp. 265-268.
[3] Szewczyk R, Polastre J, Mainwaring A andCuller D, “Lessons from a sensor network
expedition”, in proceedings of the 1st European
Workshop on Sensor Networks, January 2004.
[4] Xu N, Rangwala S, Chintalapudi KK, Ganesan
D, Broad A, Govindan R and Estrin D, “A
wireless sensor network for structuralmonitoring”, in proceedings of the 2ndinternational
conferenceon
Embedded
Networked Sensor Systems, pp. 13–24, USA,2004.
[5] Kuppusamy T, Sheng J, Parker JC and Lenhard
RJ, “Finite-element analysis of multiphase
immiscible flow through soils”, Water
Resources Research, Vol. 23, Issue 4, 1987, pp.
625-631.
[6] Hoshiya M and Sutoh A, “Kalman Filter-Finite
Element Method in Identification”, J. Eng.
Mech., Vol. 119, Issue 2, 1993, pp. 197–210.

A PSPICE simulation is studied for the proposedlandslide sensor for monitoring system. The result isshown in Fig. 3. In this simulation, it is consideredthat the Yang’s modulus E of the cable is infinity
and the temperature coefficient of the strain gage isvery low. In Fig. 3, it is noticed that a very slow
landslide effect is present at the beginning and aboutfour months later, the effect is more visible. The
sensor ID number 001 shows that its resistance ischanging exponentially; it means a massive
landslide would be happened within short time in theregion under the sensor.

Fig. 3 Change of strain gage resistance with time.
CONCLUSION
A pretension cable and a strain gage sensor canbe used for landslide prediction and detection
purpose. The change of strain gage resistance is adirect indication of the landslide effect and no need

687

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

INFLUENCE OF THE SOIL-STRUCTURE INTERACTION ON THE
SEISMIC BEHAVIOR OF BUILDINGS ON SHALLOW FOUNDATIONS
Z. Benadla, K. Hamdaoui, S. Aissaoui and A. Baouch
Department of Civil Engineering, Faculty of Technology, University of Tlemcen, Algeria

ABSTRACTThe objective of this work is to study the mobility of shallow foundations relative to the subgrade byconsidering two cases. In the first, the structure is fixed at its base, as classic cases. For the second, thefoundation is replaced by hinges and springs, where their stiffnesses are expressed in terms of the geometry of
the foundation and soil shear strength. The comparison is made on a dynamic model when the two tested cases
are confronted. Thereafter, a parametric study is considered to see the effect of all the parameters that can play a
key role in the structural response. Then, these results will be validated on real structure cases, by considering
important Algerian earthquakes: (i) the one of Aïn Témouchent in 1999 and (ii) the earthquake of Boumerdès in2003. The extracted results will permit to make the point on all the elements that may influence the seismic
response of buildings while considering the interface soil-foundation-structure.
Keywords: Dynamic Analysis, Shallow Foundations, Soil Structure Interaction, Shear Velocity.

and a beam representing the floor, is considered(Fig. 1). The SSI phenomenon is carried bymodeling the whole soil-foundation with 6 springs: 3
translations and 3 rotations. This model has been
proposed by many authors, as Parmelee in 1967,
Veletsos et al. in 1974, 1975, 1977, Jennings etBielak in 1973, Wolf in 1985 and Aviles et al [4]. in
1996, 1998. The results of this analysis will becompared to those found in another model in which
the base is considered as fixed.

INTRODUCTION
The design of a structure in a seismic zone ishighly dependent on the knowledge of seating
elements, namely soil and foundations. These latterare the interface between the soil with which they
move, and the superstructure that undergoes inertial
forces. In addition to the vertical loads that they
ordinarily transmit, the horizontal earthquake actionis added. The soil itself is susceptible to deform oreven lose its cohesion. Geotechnicians describe theexpected behavior of soils, when shaken by
deformations, settlements or landslides, or an
amplification of waves of certain frequencies.
Engineers, in their turn, take this into account for the
project in general and the foundations in particular.
For the public authority, it takes this into account forplanning regulations that prohibit the construction incertain sites or require special foundations.
However, most structural studies do not take into
account the foundations mobility relative to thesubgrade. Indeed, the building design considers thesuperstructure fixed on the ground. However, thisassumption is not always justified, given that the
behavior of a building that is supposed to be fixed in
the ground is not the same when the fixed joint is
replaced by hinges with springs that schematize thefreedom of movement of foundations. In someseismic regulations, such as the Algerian earthquake
regulation (RPA 99 V2003, [6]) this matter is notaddressed.
In the present work, analyses of the influence ofSoil-Structure Interaction (SSI) on the fundamental
frequency of building structures are proposed. A
model of a simple frame, composed of two columns

SYSTEM MODEL AND FORMULATION
The fundamental frequency of building typestructures constitutes an essential parameter in thedesign and the structural analysis in the seismic
zone. This parameter is usually calculated by using
empirical formulas provided by the seismic
regulations that generally neglect the SSI. However,this interaction can have a significant influence on
the fundamental frequency, and thus, can lead towrong structural design. Indeed, some authors(Gazetas and Mylonakis 1998, 2000, [2], [3])showed that the post-seismic observations revealed
that the SSI can have a detrimental effect on the
structures. Additionally, numerical simulations,carried out by Boris et al. (2004) [1], showed that
the SSI can have advantageous or harmful effects on
the structural behavior, according to thecharacteristics of soil and those of the seismic
loading [4].
The springs’ stiffnesses (translation and rotation)
are determined using formulas that are available inliterature. The formulas of (Newmark andRosemblueth 1971, [5]) express the stiffness in
688

GEOMATE-Nagoya, Nov.13-15, 2013

terms of the soil mechanical characteristics, namely
the shear modulus G s and Poisson’s ratio ν. Also, in
terms of the geometrical characteristics of thefoundation:

Kv =

Gs
β A
(1 +ν ) z

PARAMETRIC STUDY
Modal dynamic analyses of the studied frame
were carried out for different structuralconfigurations by varying the parameters affecting
the fundamental frequency, particularly, the basic
parameters relative to the soil and the structure.
The objective is to determine the relationshipbetween the modal fundamental frequency of the
fixed model (Ffix) and the one of the same model
when the SSI is considered (FSSI). The obtained
results will permit to bring out the influence of SSI
on the fundamental frequency of the buildings.
It should be noted that this can be expressed
according to (Vs, Ep, IP, Nb, No, H, L, A). Where Vs isthe soil’s shear velocities waves, Ep and IP arerespectively, the Young modulus and the moment ofinertia of the columns, H is the height of floor, L isthe span, and A is the foundation area. Ne is thenumber of floors, Nb and No are the building’s
openings number in the longitudinal and thetransversal directions, respectively.
Initially, the analysis is carried out for a simple
frame comprising one floor and one opening.In thiscase, the fundamental frequency of the frame isexpressed only according to Vs, Ep, IP, H, L, andA.The considered values in this parametric study aresummarized in table 2. The soil’s shear velocities aretaken from the RPA 99 (V2003) [6] regulation fordifferent types of soils: very friable, friable, firm,very firm and rock.

(1)

K h = 2(1 + ν )Gs β x A
1 +ν
Kθ =
Gs β x (a 2 + b ) A
4

(2)
(3)

Kv, Kh et Kθ represent respectively the vertical,
the horizontal and the rotational translational
stiffnensses, and A is the foundation area, A= a*b.
The parameters βx and βz are two entities
depending on the a/b ratio. For the case of a square
foundation of 2*2 m2, βx= 1 et βz= 2.18 [7].

Table 2 Considered parameters values
Fig. 1

Reference model

The mechanical characteristics of the usedmaterials are given in the table 1

Vs (m/s)

Table 1 Mechanical characteristics of the studied
systemEp (MPa)
Density γ(KN/m3)
Soil
structure20
24.5

Elastic
modulus E
(MPa)
52
32000

Poisson’sratio
Ip (m4)

0.3
0.2

The modal analysis of the selected frame wascarried out. The different fundamental modes of thetwo cases (fixed and by considering the SSI) wereextracted. In the first case, the fundamental
frequency is found equal to 8.13Hz, where in thesecond; it is equal to 5.53Hz. Therefore, a reductionof 32% in the fundamental frequency when
considering the SSI is seen. The found fundamental
mode represents a translation in X direction
whatever the treated case is.

H (m)Acolumn(cm²)

689

100 (Very friable)
150 (Very friable)
200 (Friable)
400 (Firm)
800 (Rock)
20000
32000
42000
0.000325
0.00125
0.003420.007620.01490.0341
2.00
4.00
6.00
8.00
10.00
25x25
35x35
45x45
55x55
65x65
80x80

GEOMATE-Nagoya, Nov.13-15, 2013

ResultsFigs.2 to 5 show the parametric study results fordifferent configurations. The different elements are
represented according to the FSSI /Ffix frequency ratio.
In the case of the Vs influence, this ratio is stabilized
for velocities greater than 400m/s. For less resistantsoil, the effect of the SSI remains very visible.

Fig.2

Fig.4

Influence of H on the frequencies ratio

Fig.5

Influence of Ep

Influence of Vs on the frequencies ratio

The inertia variation of columns influences
considerably on the FSSI/Ffix ratio (Fig. 3). Indeed,for velocities Vs lower than 400m/s, the reduction of
the frequency FSSI can reach the 70%, compared tothe case of the fixed structure. It is shown also that
more the inertia of columns increases, more it
becomes judiciable to considerer the SSI effect.

Finally, one can note that for someconfigurations (stiff structures on soft soil), the
FSSI/Ffix ratio can reach low values, close to 0.3,
thing that means that the SSI lead to a reduction of
about 70% of the fundamental frequency of theframe. This confirms the need to consider the SSI
for the determination of the fundamental frequency
for this type of structures.
SSI CONSIDERATION METHOD

Fig.3

A non-dimensional parameter was proposed by
Khalil [4], noted KSS, in order to express relative
stiffness of soil-structure. This one can be
determined according to the parameters used in theprevious paragraph: Vs, H, Ep and IP, determined by
Eq. 4.

Influence of Ip on the frequencies ratio

The fundamental frequency is affected also by
the building’s height variation as shown in fig. 4. In
the cases where the height H is lower than 8.00m,
the variation between the two frequencies FSSI and
Ffix, and for the same velocities, are not significant.
However, the difference becomes clear whenH≥8.00m.The rigidity of columns does not have agreat influence, since the variation of FSSI/Ffix has
practically the same curve shape for different Youngmodulus (Fig. 5).

N o ⋅ N b ⋅ ρ ⋅ Vs ⋅ H 3 ⋅2

K SS =Ne ⋅ E p ⋅ I p

0 , 75A
A0(4)

Where A0 is a referential area (equal to1m²), ρ isthe soil density and A is the foundation area.
Different configuration cases made possible totrace the abacus of the fig. 6. The found results
indicate that for a calculated KSS according to abuilding data, a corresponding FSSI/Ffix ratio will be
got.

690

GEOMATE-Nagoya, Nov.13-15, 2013

In order to check the proposed abacus, two casesof constructions implemented in the region ofTlemcen, west of Algeria, are studied. This zone isclassified as low seismicity zone (Zone I).
The first is a five story building, with 4 openings
in the longitudinal direction and 3 in the transverse
one. The second example is a seven story building,with 5 openings in the longitudinal direction and 3 in
the transverse one. The case of a five story
construction was selected to be based on isolated
footings, and the other one (building with sevenfloors), built on continuous footings. The parameter
KSS was calculated according to the data of the twobuildings and the result permit to plot the curves ofthe fig. 6.

Fig. 6

Figures 8 and 9 represent the accelerograms of thetwo studied cases.

Fig.7

Numerical built model

Fig.8

Aïn Témouchent Accelerogram

Fig.9

Boumerdès Accelerogram

Relative stiffness influence KSS on the
structure frequency in the two buildings

According to the obtained results, we note thatthe suggested parameter KSS represents well the twobuildings cases based on the two types of shallow
foundations.
SEISMIC STUDY
In this part, the influence of the SSI on the
dynamic response of the structure will be seen. For
this effect, the building already studied in theprevious paragraph (Case 2) is selected . In thatstructure, shear walls are added to its frame system.
These walls are modelled as SHELL elements type.
The numerical model is presented in fig. 7.
Two important Algerian earthquake cases wereconcidered. The first, touched the region of Aïn
Témouchent in 1999 (west of Algeria) and thesecond (Boumerdès) has caused enormous humanand material damages in 2003 (north-east region of
the country). This earthquake of 6.8 of magnitude
was felt for a long distance from the epicentre(Majorque to approximately 300km). The
Boumerdès earthquake occurred in a zone where theseismic activity was regarded as moderate.
The zone of Tlemcen, being described as low
seismicity compared to the one of Boumerdès,enabled us to consider only one the third (1/3) of theaccelerogram recorded at the Keddara station.

As results, we presented the obtained
accelerations by considering the structure as fixedand considering the spring elements modeling themobility of the foundations relative to soil, and thedisplacements of the node at the highest point ofconstruction.
For Aïn Témouchent earthquake, the accelerationgraph is composed of two sections (Fig. 10). The
first varies from 0 to 10 seconds, where the values
are not comparable. They are very significant from691

GEOMATE-Nagoya, Nov.13-15, 2013

the first moments of the excitation, whereas in thecase of the fixed structure, those are minimal. After
that, the second interval comes where the values are
similar with small differences.
Horizontal displacements are represented in fig.
11. The maximum displacement is seen in the firstsection (from 0 to 10s), it is equal to 6.74cm in thecase of the SSI, whereas in the fixed structure case,this phase illustrates a minimal displacement. Its
maximum comes only to after 12.54 seconds fromthe beginning of the excitation; its value is around1.66cm.Also, at the end of the excitation, the case of
the SSI needs more time to be damped, since thedisplacement is not vanished, contrary to the fixed
structure case.

displacement passes from 2.5cm in the fixed
structure case to more than 7.5cm in the SSI case;that is 5cm of difference.

Fig.12The SSI effect on the
Boumerdès earthquake.

acceleration,

Fig.10 The SSI effect on the acceleration, AïnTémouchent earthquake

Fig.13 The SSI effect on the horizontal
displacement, Boumerdès earthquake.
CONCLUSION
This paper comprised the study of the influenceof the soil-structure interaction on building typestructures with shallow foundations, using a
numerical modeling, and based on the finite element
method.
The structure was modeled by beam elements,
where the soil-foundation unit was modeled using 6
springs: 3 in translation and 3 in rotation. Their
stiffnesses were determined from suggested
expressions, available in the literature.
The study on the influence of the soil-structureinteraction on the fundamental frequency of thestructures showed that this one can reduce verysignificantly the first frequency of the structures.
The parametric analysis permit the determinationof the expression of a non-dimensional parameter,
called relative stiffness of soil-structure (KSS),
allowing to take into account the influence of the
SSI in the calculation of the fundamental frequencyof the buildings and this was shown by the treatmentof two cases of real buildings.

Fig.11 The SSI effect on the horizontal
displacement, Aïn Témouchent earthquake.
For the earthquake of Boumerdès, the first noted
remark concerns the maximum acceleration thatexceeds the 0.33g in the case of the SSI. Indeed, thisvalue exceeds the 0.5g, and it is reached before theone obtained in the fixed case with a gap of around
0.6 seconds (Fig. 12). Furthermore, at the beginningof the excitation, the acceleration is much moresignificant in the case of the SSI compared to case of
fixed structure.
For the displacements (Fig. 13), it is noted thatthe values are much more significant in the case of
the SSI than in the fixed case. The maximum692

GEOMATE-Nagoya, Nov.13-15, 2013

The study of the seismic response of thebuildings was carried out by using two real seismic
recordings. It was shown that the fact of considering
the effect of the soil-structure interaction increases
considerably the acceleration as well as thedisplacements of last floor of the building. These
values seem critical especially at the beginning of
the excitation.

detrimental”, Journal Earthquake Engineering,
V04, N° 3, 2000, pp. 277-301.
[4] Khalil L., “Influence de l'interaction solstructure sur le comportement sismique desbâtiments, analyse dans les domaines linéaire etnon linéaire”, PhD Thesis, Civil Engineering
Department, University Science & Technology
of Lille, 2009.
[5] Newmark N.M. and Rosemblueth E.,“Fundamentals
Earthquake
Engineerinig”,
Prentice-Hall, 1971.
[6] Règles Parasismiques Algériennes “RPA 99”,
document technique réglémentaire, DTR B C 2
48,version 2003.
[7] Tamahoult M and Branci T., “Influence del'interaction sol-structure sur la réponse
dynamique des structures des bâtiments”, Civil
Engineering Department, Sc. & Sc.Ing. Faculty,
University of Chlef, 5ème SymposiumInternational sur la Construction en Zone
Sismique. SICZS_2010, 2010.

REFERENCES[1] Boris J., Shashi K. and X. Feng “Influence ofSoil-Foundation-Structureinteractiononseismic response of the I-880 Viaduct” J. Struc.
Engineering, Vol. 26, 2004, pp. 391-402.
[2] Gazetas G. and Mylonakis G. Seismic SoilStructure Interaction: New Evidence andEmerging Issues, Emerging Issues paper,
Geotechnical Special publication N°75, ASCE
Vol. III,.1998, pp. 1119-1174.
[3] Gazetas G. and Mylonakis G. “Seismic SoilStructureInteraction:
Beneficial
or693

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

NUMERICAL STUDY OF PLASTICITY-BASED CONSTITUTIVEMODELS FOR SOIL IN SIMULATION OF BRACED EXCAVATION
Samuel J. Verghese1, Ha H. Bui1
Department of Civil Engineering, Monash University, Australia

1

ABSTRACT
Numerical modelling continues to play a unique and intrinsic role in the process of geotechnical design. Of
greatest concern are soil constitutive models that are employed within finite element software to predict soil
behaviour. The objective of this paper is to provide a numerical study of the Mohr-Coulomb and Hardening Soilconstitutive models in simulation of a braced excavation. The Taipei National Enterprise Centre (TNEC)
basement construction process was well documented and the commercial finite element code, Plaxis, wasselected for this numerical comparative study. It was found that the Mohr-Coulomb soil model, a first orderapproximation, produced an underestimation of the diaphragm wall deflection, whilst the Hardening Soil model
provided a good prediction of the observed in-situ diaphragm wall deflections.
Keywords: Constitutive Soil Models, Plasticity Theory, Finite Element Method, Numerical Modellinguser-friendly computer software and consequently
fail to comprehend the fundamental theories,
principles and assumptions built within.
FE analysis is built upon the concept ofcontinuum mechanics and constitutively models asoil system from its stress-strain characteristics.
Various constitutive models have been proposed inliterature to capture the properties and features ofnumerous soil types and model its responses tosurface loading, displacements, excavation, slope
stability and many other geotechnical actions.
This paper seeks to provide a brief overview into
the fundamental principles, which directly influence
the level of accuracy and prediction the MC, andHardening Soil (HS) constitutive models offer.
The Mohr-Coulomb (MC) linear elastic soilmodel is an example of a commonly used
constitutive relationship utilised in industry. Thisparticular model provides a first orderapproximation helpful in providing a preliminary
analysis to the problem. However, for an effective
analysis to be carried out, it is imperative for theuser to recognise the uncertainties and limitations
each model has to offer, and consequently make a
judgement between the reliability of the numericalresults and the uncertainty therein.
A braced excavation simulation of the Taipei
National Enterprise Centre (TNEC) has beenmodelled using the FE software package Plaxis.
Stage by stage construction procedures have been
replicated in order to simulate in-situ conditions
recorded on site. The diaphragm wall deformations
obtained from field data history have been evaluatedwith respect to numerically computed wall
deformations. Both the MC and HS constitutive
models have been selected for this numericalcomparative study.

INTRODUCTION
The behaviour of soil varies all over the world
and continues to present a unique challenge to
geotechnical engineers in professional practice on adaily basis. As a result, numerous soil theorists haveemerged attempting to explain the exciting
phenomenon observed under various in-situ site
conditions. The fundamental knowledge an engineer
employs when analysing an engineering system
directly correlates to the success, safety, andprecision of results.
On April 20th 2004, a 30m deep excavationadjacent to the Nicoll Highway in Singapore
collapsed during construction. The transport
authorities were constructing an undergroundrailway tunnel when the braced excavation support
failed, initiating rapid collapse of the diaphragmwalls leaving a collapse zone which was 150m wide,
100m long and 30m deep. This tragedy took the
lives of two workers, an engineer and a site foreman.
Furthermore, economic losses were substantial withdelays contributing to part of the US$4.14 billion
subway project [1]. Upon post failure investigation,
it was noted that certain errors in the input data of
the original constitutive model used in design
ultimately led to incorrect assumptions andunderestimated calculations [1]; resulting incatastrophic failure.
In recent times, theoretical developments havesignificantly grown and with the advance ofcomputer technology and software programming,
Finite Element (FE) methods are readily available toassist geotechnical engineers in the interpretation,modelling and design of complex soil systems.
Unfortunately, a minority of modern day
geotechnical engineers have become accustomed to694

GEOMATE-Nagoya, Nov.13-15, 2013

loading combinations for a perfectly plastic material
remains fixed and does not move in principal stressspace. Hill [9] states that plastic strain rates areproportional to the derivative of the yield function
with respect to the stresses. This notion provides thebasis upon which plastic deformation can be
determined once the stress point (p-q) reaches theyield surface.

NUMERICAL APPROACH
Stress State and Equilibrium
Continuum theory considers solids, in this casesoil particles, and fluids to behave as a continuous
media. Equations of equilibrium and compatibility
are independent of a material’s physical properties,
and thus form the basis of numerical modelling.
There are three normal stress rates (𝝈𝝈̇ xx , 𝝈𝝈̇ yy, 𝝈𝝈̇ zz ) andthree shear stress rates (𝝈𝝈̇ xy , 𝝈𝝈̇ yz, 𝝈𝝈̇ xz ). The spatial
derivatives of the aforementioned stress rates arethen assembled in a vector denoted 𝝈𝝈 and combinedwith the body force components, X, Y and Z
assembled in a vector b. This presents the static
equilibrium of a continuum [18].
R

R

𝐿𝐿𝑇𝑇 ∙ 𝝈𝝈 + 𝒃𝒃 = 0RR𝜺𝜺𝒑𝒑̇ = 𝜆𝜆

R

R

𝜕𝜕𝝈𝝈̇

(4)

Experimental data indicates that plastic strain rates
are not always orthogonal to the yield surface andhence cannot be accommodated under the coaxial
assumption. Therefore, the plastic potential function
has been derived to model this type of plastic strain
rate behaviour and considers the dilatancy angle, ψ,
where φ ≠ ψ, to avoid the previous overestimation ofdilatancy under the normality rule.

(1)

where 𝐿𝐿𝑇𝑇 is the transpose matrix of a differential
operator [18]. Similarly, the kinematic relationshipbetween stress and strain can be formulated
accordingly and is referred to as a constitutive
relationship seen in Eq. 2 below.
𝝈𝝈̇ = 𝑀𝑀𝜺𝜺̇𝜕𝜕𝜕𝜕

Mohr-Coulomb Soil Model
The MC model in Plaxis captures the linear
elastic perfectly plastic stress-strain behaviour of asoil element when considered in its general stressstate, and all deformations are fully recoverable
upon unloading. Once the stress point (p-q) is loaded
past the model’s elastic limits, φ and cohesion, c,
define a fixed shear failure surface upon which thestress point (p-q) is assumed to follow.

(2)

where 𝝈𝝈̇ and 𝜺𝜺̇ is the stress and strain tensor
respectively and 𝑴𝑴 is the material stiffness matrix.
CONSTITUTIVE THEORY′
𝑡𝑡𝑡𝑡𝑡𝑡(𝜑𝜑′) + 𝑐𝑐′
𝜏𝜏 = 𝜎𝜎𝑚𝑚

The constitutive relationship for a material
depends on the homogeneity, isotropy and continuityof the body material, as well as its response to cyclicloading, and the rate and magnitude of the applied
load [5]. General techniques have been developed tocharacterise soil as elastic, plastic, or viscous innature to consequently conduct constitutive
analyses.

(5)

The above failure criterion produces a linear failureenvelope for a two-dimensional analysis. As thedevelopment of plastic strains occur, the yieldsurface does not admit changes of expansion orcontraction and hence is considered a fixed yieldsurface (perfectly plastic).
Hardening Soil Model

Theory of Plasticity
The HS model in Plaxis is a second orderconstitutive relationship that seeks to describe thenon-linear behaviour of soil upon yielding and isderived from the hyperbolic model of Duncan andChang [8]. The term hardening within this context
defines the various changes, in size, location or
shape, of the yield surface and is directly related to
the loading history measured by a form of plastic
deformation [21]. Note, the Plaxis HS model
considers isotropic hardening only.
Isotropic hardening is governed by theassumption that expansion or contraction about thecentre of the yield surface is uniform, whilst theshape, centre and orientation of the yield surface
remain unchanged. Fundamentally this type of
hardening behaviour can be characterised into two

Classical theory developed by Hill [9] seeks to
explain the stress and strain behaviour of plastically
deformed solids and is fundamentally analogous toHooke’s law which stipulates the relationshipbetween stress and strain governed by the material’s
modulus. It is important to note that a material’s
total strain rate is controlled by an elastic and plastic
rate component.
𝝈𝝈̇ = 𝑀𝑀(𝜺𝜺𝒆𝒆̇ + 𝜺𝜺𝒑𝒑̇ )(3)

The yield limit of an elastic soil material is definedby a yield function, denoted f, and is a function of
the stress components, friction angle, φ andcohesion, c. The failure limit under all deviatoric695

GEOMATE-Nagoya, Nov.13-15, 2013

components: shear hardening and compression
hardening. When a soil body is subjected to primarydeviatoric loading, plastic axial strains develop as
observed in a triaxial test. These irreversible strainsare consequently accounted for by the shear
hardening component of the HS model.
Furthermore, compression hardening is used tomodel the irreversible plastic volumetric strains due
to primary compression in oedometer loading andisotropic loading. Careful consideration to stressdependent stiffness is a fundamental element of theHS model and is associated with a power law value,m. This power value equates to 1 when a linear
analysis is assumed and is typically taken as 0.5(recommended for hard soils) when attempting tomodel hyperbolic stress-strain behavior.
This model requires three input stiffness
parameters, namely: E 50 , E oed , and E ur . E 50 is theconfining stress dependent stiffness modulus forprimary loading and is described by Eq. (6).
𝒓𝒓𝒓𝒓𝒓𝒓

𝑬𝑬𝟓𝟓𝟓𝟓 = 𝑬𝑬𝟓𝟓𝟓𝟓 �𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝝈𝝈𝟑𝟑 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝒑𝒑𝒓𝒓𝒓𝒓𝒓𝒓 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

�𝒎𝒎Fig. 1For hard soils, plastic volume changes tend to be𝒑𝒑
relatively small and hence 𝜺𝜺𝒗𝒗 can be assumed toequal 0 (hard soils only). Hence, the combination of
Eq. 10 and Eq. 11 produces multiple yield surfaces
with increasing values of 𝜸𝜸𝒑𝒑 as seen in Fig 1.
The second type of hardening mechanism isplastic volumetric strain. As an element of soil
undergoes compressive loading, a stress point
asymptotically follows the yield locus respective toits strain hardening parameter, thus the induction ofa yield surface limits the elastic region upon which
the stress point is asymptotically moving, based on a𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓direct relationship between 𝑬𝑬𝟓𝟓𝟓𝟓 and 𝑬𝑬𝒐𝒐𝒐𝒐𝒐𝒐 . Hence,the shear yield surface is controlled by the triaxial
modulus and the cap yield surface by the oedometer
modulus respectively [18]. The reader is suggested
to make reference to Schanz et al. [19] publishedpaper entitled, “The Hardening Soil Model:
Formulation and Verification” for the mathematicalderivations of the yield cap surface.

(6)

For unloading and reloading elastic stiffness, E ur isdefined as follows:
𝒓𝒓𝒓𝒓𝒓𝒓𝑬𝑬𝒖𝒖𝒖𝒖 = 𝑬𝑬𝒖𝒖𝒖𝒖 �𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝝈𝝈𝟑𝟑 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝒑𝒑𝒓𝒓𝒓𝒓𝒓𝒓 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

�

𝒎𝒎

(7)

The oedometer stiffness modulus, E oed for primary
compression is:
𝒓𝒓𝒓𝒓𝒓𝒓𝑬𝑬𝒐𝒐𝒐𝒐𝒐𝒐 = 𝑬𝑬𝒐𝒐𝒐𝒐𝒐𝒐 �𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝝈𝝈𝟑𝟑 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

𝒄𝒄 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄−𝒑𝒑𝒓𝒓𝒓𝒓𝒓𝒓 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔

�

𝒎𝒎

(8)

Note, pref is defined as the reference pressure and istaken as 100 kN/m2 within the Plaxis FEM software𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟[18]. 𝐸𝐸50 , 𝐸𝐸𝑢𝑢𝑢𝑢 , and 𝐸𝐸𝑜𝑜𝑜𝑜𝑜𝑜 are the respective
stiffness moduli corresponding to pref.
The first type of hardening, shear hardening has
a linear flow relationship and is characterised by thedevelopment of plastic strains when mobilising thesoil’s material strength, or increasing the soil’s
preconsolidation stress, commonly referred to ascompaction hardening. The fundamental shear
hardening yield function is given by [18]:𝒇𝒇 = 𝒇𝒇 − 𝜸𝜸𝒑𝒑

TNEC CASE STUDYThe Taipei National Enterprise Centre (TNEC) isthe chosen case study for this paper due to readily
available documentation of construction procedures
and in-situ conditions released by Ou et al. [15]. The
TNEC building was built in 1991 and comprises of
18 storeys and 5 basement levels. The TNEC was
excavated to a depth of 19.7m using the top-down
construction method and a retaining wall measuring
90cm thick and 35m deep was elected to besupported by a series of temporary steel struts andconcrete floor slabs. According to site investigation
data, the soil located within the Taipei basin
consisted of six layers of alternating silty clay andsilty sand deposits overlying a thick gravel
formation. The groundwater level was observed at a
depth of 2m below the ground surface, withincremental dewatering corresponding to excavation
depth. General phreatic level conditions were

(9)

where 𝑓𝑓 is a function of stress and 𝛾𝛾 𝑝𝑝 is the strain
hardening parameter and is expressed as a functionof plastic strains [18]:
𝒇𝒇 =

𝟐𝟐

𝒒𝒒

𝒒𝒒
𝒒𝒒𝒂𝒂

𝟐𝟐𝑬𝑬𝟓𝟓𝟓𝟓 𝟏𝟏−

𝒑𝒑

−

𝟐𝟐𝟐𝟐

(10)

𝒑𝒑

(11)

𝑬𝑬𝒖𝒖𝒖𝒖𝜸𝜸𝒑𝒑 = −(𝟐𝟐𝜺𝜺𝟏𝟏 − 𝜺𝜺𝒗𝒗 )Yield loci for varying constant values of the𝜸𝜸𝒑𝒑 parameter696

GEOMATE-Nagoya, Nov.13-15, 2013

Table 4 Input parameters for MC modelType GLγtϕ'νsuFig. 2TNEC excavation cross-section
relevant dimensions in metres [15].

withassumed, generating hydrostatic pore pressure
distribution. Soil-water coupling was not consideredsince the CL soil layers were analysed as undrained.
Fig. 2 depicts the excavation cross-section.
Numerical parameters are as follows.

-m

3

kN/m

°

CL

2

18.25

34

CL

5.6

18.25

SM

8

CL

E

kPa

kN/m2

0.5

5

2500

34

0.5

30

15000

18.93

31

0.3

-

56471

13

18.15

29

0.5

45

22500

CL

18

18.15

29

0.5

35

17500

CL

23

18.15

29

0.5

50

25000

CL

28

18.15

29

0.5

75

37500

CL

33

18.15

29

0.5

100

50000

SM

35

19.62

31

0.3

-

173620

CL

37.5

19.13

0

0.5

125

62500

SM

46

19.62

32

0.3

-

192571

Table 1 Input parameters of struts and slabs [17]Strut
Behaviour
EA
Ls
(kN)
(m)
H300
Elastic
19548108H400

Elastic

35690213

B1F

Elastic

3690000

1

B2F

Elastic

3690000

1

B3F

Elastic

3690000

1

B4F

Elastic

3690000

1

B5F

Elastic

3690000

1

Fig. 3

RESULTS AND DISCUSSION
Figure 3 shows the finite element mesh of the
TNEC model used for Plaxis modelling. Lateralboundaries have been assumed free-rollers, while thebottom boundary is fixed. In-situ soil parameters
were obtained from Ou et al. [15] and Hui & Hie[10]. In the analysis, construction stages were
performed by deactivating FE elements inaccordance with construction procedures. Withconsideration to consistency between MC and HS
simulations, the drained layers, represented as SM
were modelled using MC parameters during the HS
simulation. The drained layers consisted of silty
sand and hence the MC model provided an accurate
representation for those respective layers. It can beseen in Fig. 4 that the MC model underestimated theobserved deflections of the diaphragm wall quite
significantly. The maximum deflection value
predicted by this model was approximately 7.0cm incomparison to the maximum observed deflection of
9.95cm. In contrast, the HS constitutive model
provided a much better prediction of the excavation
process and slightly overestimated the maximum
deflection of the wall by approximately 0.35cm.

Table 2 Input parameters of diaphragm wall [17]Parameter

Abbr.

Value

Unit

Axial Stiffness

EA

22140000kN/m

Flexural Rigidity

EI

1494450kN/m2/mWall Thickness

d

0.9

m

Weightw

21.6

kN/m/mPoisson's ratio

v

0.15

-

Table 3 Input parameters for HS modelType GLmv
Eref 50
Eref ur
2
-m
kN/m
kN/m2

Eref oed
kN/m2

CL

5.6

0.5

0.2

3531

10594

4414

SM

8

0.3

-

-

-

CL

33

0.5

0.2

36022

108067

45028

SM

35

0.3

-

-

-

CL

37.5

0.5

0.2

65236

195709

81545

SM

46

-

0.3

-

-

-

Finite element mesh of the TNEC

697

GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 4Comparison of observed diaphragm wall
deflections with MC and HS soil models.

Fig. 5Comparison of MC and HS simulations.

observed in soils before yielding. This type of
hardening mechanism behaviour is referred to as
deviatoric hardening, and has been introduced earlier
in this paper. When a triaxial test is performed on asoil sample, the shear hardening phenomenon isobserved due to the development of shear strains
under confining stress conditions. This type ofconfining stress state is generally experienced by asoil element located behind a retaining wall, where
the lateral resistance of the diaphragm wall, coupledwith lateral soil pressure induces a deviatoric stress.
As the development of plastic deformation increases,
the degradation of soil stiffness occurs, thus
resulting in considerable diaphragm wall deflection
and surface settlement. The MC model is unable toexplain this type of behaviour due to its elastic
framework which restricts the modelling of plastic
shear strain influence.
In addition, the HS model takes into account thestress dependent stiffness of soil. Upon loading, asoil’s stiffness is expected to increase due to thedensification of soil particles, resulting in a lower
volume of voids. This phenomenon is observed
when plastic deformation begins to occur, i.e. thepermanent rearrangement of the soil’s lattice
structure. Similarly, when a soil is subject tounloading, exemplary of an excavation scenario, theincreasing levels of strain significantly reduce thesoil’s stiffness attributed by the decrease inconfining stress. This highlights the co-dependent
relationship between stress and stiffness which theMC model fails to account for. Due to thisfundamental behavioural characteristic of soil,
constant stiffness cannot be assumed, especiallywhen considering a soil body in undrained
conditions. Due to the limitations of the MC model,
primary compression stiffness, E oed , is automaticallyassumed to equal the soil’s initial modulus, E o , andconstant elastic stiffness is assumed as a result. This
inevitably overestimates the soil body’s ability toremain rigid upon unloading as it is unable toaccount for the softening effect of the soil, thus
resulting in the significant underestimation of wall
deflection. By alternatively incorporating the three
input stiffness parameters into the HS model, E 50 ,E ur , and E oed , this permits the scale of soil
deformations to be modelled much more precisely as
it takes into account the stiffness variation of soil
with loading. Furthermore, this model is able toexpress a reduction of mean effective stressobserved in soft soils when operating in undrained
conditions.
The secondary hardening mechanism of the HS
model, volumetric hardening, provides an elastic
deviatoric hardening limit and when reached plastic
volumetric strains are seen to develop. This is
another key difference between the MC and HS
models, since the MC model is unable to distinguishvolumetric strain from shear strain. Thus, when aFirstly, the MC model provides a first order
prediction of the excavation procedure andconsequently assumes linear elastic behaviour
during the excavation process. Within the strain
range of 10-3-10-6, it is common for soils to exhibit
non-linear stress-strain behaviour where thevariability of stiffness is readily observed. This does
not indicate the soil has fully yielded, since the soil
is able to almost recover initial stiffness upon
unloading, it does however behave differently to the
MC assumption of linear elasticity. This directly
results in the underestimation of horizontal
displacements occurring behind the retaining wall
since the soil stress path remains in the linear elastic
domain and the development of plastic shear strainsare erroneously overlooked. A key feature of the HS
model is its capability to capture the elastic nonlinear stress-strain relationship that is typically698

GEOMATE-Nagoya, Nov.13-15, 2013

soil body is loaded past its preconsolidationpressure, p o the soil’s modulus is typicallyoverestimated. The HS model however derives a cap
yield surface based on p o , which delineates the
beginning of plastic volumetric failure, thus
avoiding the overestimation of a normallyconsolidated soil’s stiffness. Since the yield surfaceof the MC model is based upon φ and c, thedevelopment of plastic strains do not expand or
contract the failure surface accordingly. Hence, theyield surface of the MC is fixed. The HS modelaccommodates the expansion or contraction of theshear yield surface and introduces an additional
volumetric cap yield surface which induces the
reduction of soil stiffness as a result of highamplitude strain.

[7] Drucker DC, Gibson RE and Henkel D J, “Soilmechanics and work hardening theories ofplasticity”, Transactions of the American Soc.
of Civ. Eng., ASCE, Vol. 122, 1957, pp. 338346.
[8] Duncan JM and Chang CY, “Nonlinear analysisof stress and strain in soils”, J. of the Soil
Mechanics and Foundations Div., ASCE, Vol.
96, 1970, pp. 637-659.
[9] Hill R, The Mathematical Theory of Plasticity.
Oxford: Clarendon Press. 1950.
[10] Hui X and Hie VAS, “Evaluation of modulus ofsubgrade reaction for analysis of deep
excavation”. Ph.D. Thesis, 2007, Dep. of Const.
Eng., National Taiwan University of Scienceand Technology, Taipei.
[11] Jumikis AR, Theoretical Soil Mechanics. USA:
American Book Company, 1969.
[12] Lim A, Ou C-Y and Hsieh P-G, “Evaluation ofclay constitutive models for analysis of deep
excavation under undrained conditions”, J. of
GeoEng., Vol. 5, 2010, pp. 9-20.
[13] Osouli A, Hashash YMA and Song H,“Interplay between field measurements and soil
behavior for capturing supported excavation
response”. J. of Geotech. and Geoenv. Eng.,
Vol. 136, 2010, pp. 69-84.
[14] Ou C-Y, Deep Excavation - Theory andPractice. London: Taylor and Francis Group,
2006.
[15] Ou C-Y, Liao J-T and Lin H-D, “Performanceof diaphragm wall constructed using top-down
method”, J. of Geotech. and Geoenv. Eng., Vol.
124, 1998, pp. 798-808.
[16] Ou C-Y, Shiau BY and Wang IW, “Threedimensional deformation behavior of the Taipei
National Enterprise Center (TNEC) excavationcase history”, Canadian Geotech. J., Vol. 37,
2000, pp. 438-448.
[17] Phuoc DH, “Excavation behavior and adjacentbuilding response analysis using user definedsoil models in PLAXIS” Ph.D. Thesis, 2009,
Dep. of Cons. Eng., National Taiwan Universityof Science and Technology, Taipei.
[18] Plaxis 2012. Material Models Manual.
[19] Schanz T, Vermeer PA and Bonnier PG, The
hardening soil model: Formulation andverification. Beyond 2000 in Computational
Geotechnics – 10 years PLAXIS. Balkema:
Rotterdam, 1999.
[20] Woo SM and Moh ZC, 1990. “Geotechnicalcharacteristics of soils in the Taipei Basin”, 10th
Southeast Asian Geotech. Conf., Taipei, 1990,
Vol. 2, pp. 51-65.
[21] Yu H-S, Plasticity and Geotechnics. USA:
Springer Science and Business Media, 2006.

CONCLUSIONThe TNEC braced excavation case study is one
example of the reliability and realistic prediction ofsoil deformation associated with the application of
non-linear elastic constitutive models. The HS
model provided a competent result in comparison toobserved diaphragm deflections. This was directly
due to the model’s incorporation of deviatoric andvolumetric hardening mechanisms, stress-path
dependent stiffness, soil dilatancy and the expansion
or contraction of the yield surface with respect toplastic straining. In contrast, the MC model assumed
linear elastic perfectly plastic behaviour, i.e. a fixedyield surface, which significantly underestimated thediaphragm wall deflections.
REFERENCES[1] Artola J, “A solution to the braced excavation
collapse in Singapore” Ph.D. Thesis, 2005, Dep.
of Civ. and Env. Eng., Massachusetts Instituteof Technology, Cambridge.
[2] Bishop JFW and Hill R, “A theory of the plastic
distortion of a polycrystalline aggregate under
combined stresses”, Phil. Mag., Vol. 42, 1951,
pp. 414-427.
[3] Calvello M, “Inverse analysis of a supported
excavation through Chicago glacial clays” Ph.D.
Thesis, 2002, Dep. of Civ. Eng., North Western
University, Illinois.
[4] Chakrabarty J, Theory of Plasticity, 3rd Ed.
Texas: Elsevier Butterworth- Heinemann, 2006.
[5] Chen WF and Baladi GY, Developments inGeotechnical Engineering- Soil Plasticity.
Amsterdam: Elsevier, 1985.
[6] Clough GW and Reed MW, “Measured
behavior of braced wall in very soft clay”, J. of
Geotech. Eng., Vol. 110, 1984, pp. 1-19.

699

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

A NUMERICAL MODEL TO PREDICT SETTLEMENT OFCHEMICALLY STABILISED LANDFILL

1,2

Behnam Fatahi1, Hadi Khabbaz2
School of Civil and Environmental Engineering, University of Technology Sydney (UTS), NSW, Australia,
ABSTRACTThis paper presents the findings of numerical analyses to predict the vertical and horizontal displacements ofclosed landfills under surcharge load with and without treatment by chemical admixtures. The finite element
program, PLAXIS version 9, has been used to evaluate the settlement of a landfill model. The soft soil creep
model is used for this analysis. Five layers of solid waste are considered for the landfill to evaluate the effect of
depth of stabilisation on settlement of landfill model. Treated and untreated municipal solid waste (MSW)parameters are obtained from the results of the extensive laboratory program performed on MSW samples in thisresearch. The settlement of the landfill model 10 and 20 years after applying the surcharge load for different fly
ash-quicklime contents and various depths of improvement is estimated. Results indicate that treatment of MSW
reduces the vertical displacement of the landfill model under surcharge load significantly. This reduction is morewith higher depths of improvement.
Keywords: Landfill, SettlementT, Fly ash, Plaxis
Their results indicated that the depth of
improvement is smaller in MSW compared tocohesionless soils. In addition, the settlement causedby DDC depends on the applied energy and it is in
the range of 5% to 25% of the MSW thickness. With
deep dynamic compaction large voids reduce andafterward other technique such as fly ash-lime
grouting can further reduce the remaining smaller
voids. Moreover, the lime/fly ash slurry injection has
significant effects on protecting groundwater,
neutralising leachate, and for placing curtain walls toprevent leachate migration. Replacement of cementwith by-product materials such as fly ash candecrease the stabilisation expenses. Many
researchers reported the application of fly ash in
geotechnical projects (e.g. [2]-[4]). According to [5],from an economic and environmental viewpoint,rich materials in slaked lime (Ca(OH)2, calcium
hydroxide), can be treated together with pozzolanicmaterials, such as fly ash, to develop a cementitious
material.

INTRODUCTION
Landfill design and construction technology has
progressed rapidly during the past two decades inreaction to more strict controlling requirement anddemands. However before any construction on topof landfills, properties of decomposed wastematerials should be improved as required. Whether
immediately or long time after construction, damage
and cracks in structures are a challenging issue fororganisation that design and construct foundations
on improved landfill sites. Generally, clients requirea maximum post construction settlement less than acertain value over the structure’s life-time, and limit
the differential settlement to a certain change in thegrade.
IMPROVEMENT TECHNIQUESThe stabilisation of landfills and waste disposalsites for structural and environmental purposes has
been performed through the application of current
soil stabilisation and ground improvement
techniques. The deep dynamic compaction (DDC)
technique is a common ground improvement
technique due to its relatively economical and easy
application. The deep dynamic compaction
technique has been carried out with success in alarge range of soils including MSW. Reference [1]reviewed 64 case histories regarding theeffectiveness of the DDC on MSW landfill sites.

ACTIVATION OF FLY ASH WITH LIME
The reaction of fly ash (FA) with lime results in
an immediate improvement of the soil’s mechanicalproperties during stabilsation. It reduces the
moisture content of the soil, which has a faststabilising effect, increases soil pH, preparing a
condition for secondary pozzolanic reactions andalso it produces heat, which accelerates the chemical
700

GEOMATE-Nagoya, Nov.13-15, 2013

reactions [6]. Many activation methods have beensuggested by researchers to treat unstable soils withfly ash. The main purpose of these efforts was toimprove the reactivity of the pozzolan, in order toenhance the mechanical and stability characteristicsof the mixed product. Extended grinding proposedby [7], curing at high temperatures suggested by [8],alkali activation considered by [9] and [10] andchemical activation procedures presented by [11] aresome approaches, which have been practiced toattain that goal.

interpolation for displacements and the numericalintegration involves twelve stress points. The
powerful 15-node element provides an accurate
calculation of stresses and failure loads. The twovertical boundaries on both sides are free to move invertical direction, whereas the horizontal boundary
at the base is considered to be fixed in both verticaland horizontal directions as presented in Fig 1. The
foundation soil was considered to be stiff soil and its
stability and deformation were not considereddirectly in this analysis. Cross-sections of generated
mesh have been shown in Fig. 4.

FINITE ELEMENT MODELINGThe finite element program PLAXIS version 9
has been used to evaluate the settlement of stabilised
landfill. The cross-section utilised for the numericalanalysis is presented in Fig. 1. Five layers of solid
waste were considered for the landfill to estimate theeffect of depth of stabilisation on landfill settlement.
All the dimensions for model are given in Fig. 2.
Accordingly, the solid waste properties need to be
adjusted to consider various improvement options.
The landfill is modeled as a two dimensional planestrain model.

Fig. 3 15-nodded triangle element used in modeling.

6m

B
11 m

3m

C

3m
3m
3m

24 m

Fig. 4 Cross-section of generated mesh.

12 m

B

30 m

36 m

30 m

ADOPTED MATERIAL MODELS
Fig. 1 Dimensions of the model.
MESH GENERATION AND BOUNDARYCONDITIONS
The 15 nodded triangle elements were employedin the modeling as shown in Fig. 3 and the meshgeneration algorithm of PLAXIS version 9.0 wasused in this study. It provides a fourth order

All soils exhibit some creep, and primary
compression is thus always followed by a certain
amount of secondary compression. The secondary
compression (for instance during a period of 10 or
30 years) can be a certain percentage of the primary
compression. This is for instance the case whenconstructing embankments over closed landfill sites.
Indeed, the primary settlement of footings andembankments are usually followed by a substantial

Fig. 2 Cross-section of the numerical model.
701

GEOMATE-Nagoya, Nov.13-15, 2013

Moreover, from consolidation test performed it
has been demonstrated that the value of Cc decreasedby 30%, when the fly ash-quicklime content
increased from 0 to 26.7%. By increasing the fly
ash-quicklime content, the treated specimens
indicated more resistance against the compressive
loading and less compressibility characteristics.
Furthermore, the creep results clearly shows that thevalue of the secondary compression index, Cα, for
MSW specimens decreased from 0.052 to 0.033,
while fly ash-quicklime content increased from 0 to
26.7%. This means that, for any given time period,
the volume change during secondary compression ismore for untreated specimens than treated with fly
ash-quicklime. Hence, fly ash-quicklime admixture
is effective in reducing the volume change during
the primary consolidation as well as the secondary
consolidation. The corresponding values for thecompression index and the secondary compression
index are also reported in Table 1.

creep settlement in later years. In such cases it isdesirable to estimate the creep from FEMcomputations. The soft soil creep model was used
for this analysis due to several characteristics suchas:
 Stress-dependent stiffness
 Distinction between primary loading andunloading-reloading Secondary compression
 Memory of pre-consolidation stress Failure behaviour according to the Mohr-Culomb
criterion
Material Parameters
Municipal solid waste parameters used in FEM
analysis for different contents of stabiliser arepresented in Table 1. In addition, parameters used
for compacted clay as a cover layer of closed landfill
model and road embankment are summarised inTable 2.
Some of the important waste properties required
for the analyses are the unit weight, the shear
strength, the permeability, the primary compression
index and the secondary compression index. These
parameters were obtained from the results of theextensive laboratory program performed on the
MSW samples.
The unit weight of solid waste is an important factor
in evaluating the settlement of landfills. The unit
weight values of MSW specimens changed slightly
for specimens mixed with different fly ashquicklime (QL) contents.
The results obtained from consolidated drained(CD) triaxial tests confirmed that the shear strengthparameters are strongly influenced by the fly ashquicklime content mixed with MSW. The shear
strength parameters of solid waste estimated in thisstudy at different fly ash-quicklime content alsopresented in Table 1. It reveals that c and  values of
MSW specimens increased with increasing the fly
ash-quicklime content to MSW specimens.
In addition, the results from permeability tests
indicated that with an increase in fly ash-quicklime
content in the MSW specimen, the coefficient of
permeability reduced. The corresponding numberspresented in Table 1.

ANALYSIS TYPE
The settlement of proposed landfill model in
PLAXIS was computed using ‘consolidation
analysis’ as a calculation type and ‘staged
construction’ as a loading input. Based on Table 3
the effects of various fly ash-quicklime contents anddifferent depths of improvement were examined.
The model presents 30 years old closed landfill andselected MSW materials are decomposed waste. In
the first stage of modelling, the filling process oflandfill was completed in 4 stages (each stage
consisted of 4 metres over 30 days). After filling thesite with decomposed waste material, in landfill
model, the waste was then covered with a 0.5m layerof compacted clay. After this the model evaluatedthe settlement of the landfill after 30 years of self
weight of MSW. In the next stage a 1m thick roadembankment was constructed on the closed landfill
model over a 6 month period, and then a trafficloading of 20 kPa with a reduction factor of 0.5 wasapplied on to the road embankment. In the final step,
the vertical and horizontal displacement of thelandfill model 10 and 20 years after applying thetraffic load for different amounts of fly ashquicklime and various depths of improvement were
calculated.

Table 1 Parameters for soft soil creep model in FEM analysis
FA-QL
Content%
0%-0%
5%-1.7%
10%-3.3%
15%-5%
20%-6.7%

Unit
weight
γsat
kN/m3
14.6
14.8
15
15.2
15.4

Void
ratio
e0
0.63
0.61
0.59
0.57
0.56

CohesionC
kN/m2

Frictionabgle
φºpermeability
K
m/day

Recompression
index
cr

Compression
index
cc

11
20
26
29
30

29
33
36
38
39

0.012
0.00920.00880.00880.0082

0.075
0.07
0.068
0.064
0.061

0.33
0.29
0.28
0.24
0.23

702

Secondarycompression
index
cα
0.052
0.045
0.04
0.036
0.033

GEOMATE-Nagoya, Nov.13-15, 2013

on the vertical displacement versus time for 3m and
9m improvement depths at the midpoint below theembankment. These figures clearly indicated that
increasing the amount of fly ash-quicklime reduced
vertical settlement to a large extent. It can also be
inferred that increasing the depth of improvement
significantly decreases vertical settlement in thelandfill model.

RESULTS AND DISCUSSION
Vertical Settlement 10 Years after Applying
Traffic Load
The results of the numerical predictions of themodel were estimated in PLAXIS. Table 3 presents
the vertical displacements of the landfill model 10
years after applying the traffic load at the midpoint
below the embankment. These numbers reported
based on different depths of treatment and various
fly ash-quicklime contents.
The results predicted that the vertical settlementof untreated landfill model is about 370 mm 10 years
after applying traffic load. In addition, the result
illustrated that treating MSW with fly ash-quicklime
reduced the vertical displacement of the modelsignificantly. This reduction is more with higher
depths of improvement. It revealed that for 3m
improved landfill with 26.7% fly ash-quicklime thevertical settlement reduced 20% (from 370 mm to
296 mm) and this reduction for 6m, 9m, 12m and
24m improved landfill was 32%, 40%, 46% and58%, respectively.

Table 3 Vertical displacement of the landfill model
10 years after applying traffic load.
Vertical displacement forvarious treatment depth (mm)Table 2 Model parameters used for cover layer androad embankment.
ID

γt

c

φ

o

ψ

o

E

Treatment
Depth(m)
FA-QL (%)

3

6

9

12

24

Untreated

370

370

370

370

370

5%FA+1.7% QL

328

309

283

271

248

10%FA+3.3% QL

312

277

255

239

207

15%FA+5% QL

301

258

232

213

172

20%FA+6.7% QL

296

251

221

201

154

ν

3
kN/m

kPa

Cover

17.5

10

25

0

2.5E4

0.35

Road

18

5

30

5

6.5E4

0.3

kPa

Table 4 Vertical displacements of the landfill model,
20 years after applying the traffic load.
Vertical displacement forvarious treatment depth (mm)Vertical Settlement 20 Years after Applying theTraffic Load:
The outcomes of the numerical estimation of themodel are predicted in PLAXIS. Table 4 shows thevertical displacement of the landfill model 20 years
after applying the traffic load at the midpoint below
the embankment. These numbers are based on
different depths of treatment and various amounts of
fly ash-quicklime. The results showed that thesettlement of the untreated landfill model is about
536 mm 20 years after applying traffic load.
Moreover, these result indicated that treatment of
MSW with fly ash-quicklime reduced verticaldisplacement of the model significantly, and thisreduction was more for higher depths ofimprovement. It showed that 20 years after applying
traffic load on 3m improved landfill with 26.7% fly
ash-quicklime the vertical settlement reduced by
19% (from 536 mm to 444 mm) and this reduction
for 6m, 9m, 12m, and 24m improved landfill is 29%,
37%, 43%, and 55%, respectively.
Furthermore, Fig. 5 and Fig. 6 indicate theeffects that the amounts of fly ash-quicklime have

Treatment
Depth(m)
FA-QL (%)

3

6

9

12

24

Untreated

536

536

536

536

536

5%FA+1.7%QL

486

451

426

408

372

10%FA+3.3%QL

466

419

387

363

311

15%FA+5% QL

451

394

356

327

262

20%FA+6.7%QL

444

383

339

308

244

Horizontal Displacement 10 Years after Applying
the Traffic Load
The result showed that the treatment of MSW
with fly ash-quicklime reduced the maximum
horizontal displacement of the model, and this703

GEOMATE-Nagoya, Nov.13-15, 2013

reduction was more for higher depths ofimprovement. Figure 7 shows the horizontal
displacement versus depth for landfill treated with26.7% fly ash-quicklime with various depths ofimprovement in a section below the toe ofembankment. It can be seen that at any specificdepth below the toe of embankment, with increasing
depth of improvement, the horizontal displacement
was reduced and maximum horizontal displacement
occurred at higher depths. Moreover, Fig. 8 shows
the horizontal displacement versus depth for 9m
improved landfill treated with various amounts of fly
ash-quicklime below the toe of embankment. This
proves that increasing the amount of fly ashquicklime reduced the horizontal displacement at
any specific depth, and also that maximum
horizontal displacement occurred at higher depths.

010Horizontal displacement (mm)
20
30

40

0

Depth (m)

-5

-10

-15

20% fly ash-6.7quicklime
untreated
3-m Improvement
6-m Improvement
9-m Improvement
12-m Improvement24-m Improvement

-20

-25

Fig. 7 Horizontal displacement versus depth for thelandfill treated with 26.7% fly ash-quicklime
content.
Horizontal displacement (mm)110Time (Days)
100

0.00

0

1,000

Depth (m)Settlement (m)

-0.15
-0.20

-20

-0.35

3-m Improvement-0.40

20% fly ash- 6.7% quicklime
15% fly ash- 5% quicklime
10% fly ash- 3.3% quicklime
5% fly ash- 1.7% quicklime
Untreated landfill

-0.45
-0.50

-0.55
-0.60

-25

VALIDATION
Finite element results are validated based on resultsof triaxial tests conducted in the laboratory on thetreated MSW. Finite element analysis of triaxial
model (for treated MSW treated with 15% fly
ash+5% quicklime and dimensions of 100 mm
height and 50 mm diameter) was carried out using
PLAXIS 2D. The problem was considered as an
axisymmetry model and the nodes on left verticalboundary was restricted to displace horizontally(horizontal fixity) but allowed to undergo verticaldisplacement whereas all the displacements of thenodes at the bottom surface was arrested (total
fixity). A typical axisymmetric model under triaxial
loading condition is shown in Fig. 9. The treated
MSW material was simulated with soft soil creep
model with 15 node triangular elements. The
material properties used in the finite element
analysis are given in Table 1.
Figure 10 shows the comparison between thelaboratory measurement and finite element
predictions. As indicated the selected soft soil creep
model (which is based on modified cam-clay model)

Time (Days)
1

10

100

1,000

10,0000.00
10 years-0.05

20 years

-0.10
-0.15
-0.20
-0.25
-0.30

-0.45
-0.50
-0.55
-0.60

9-m Improvement
untreated
5% fly ash- 1.7% quicklime
10% fly ash- 3.3% quicklime
15% fly ash- 5% quicklime
20% fly ash-6.7% quicklime

Fig. 8 Horizontal displacement versus depth for 9-m
improved landfill.

Fig. 5 Vertical settlement versus time for 3-m
improved landfill.

Settlement (m)

-10

-0.30

-0.40

40

-15

-0.25

-0.35

30

-5

20 years

-0.10

20

0

10,00010 years

-0.05

10

9-m Improvement
20% fly ash- 6.7% quicklime
15% fly ash- 5% quicklime
10% fly ash- 3.3% quicklime
5% fly ash- 1.7% quicklime
Untreated landfill

Fig 6 Vertical settlement versus time for 9-m
improved landfill.

704

GEOMATE-Nagoya, Nov.13-15, 2013

significantly reduced. These reductions in verticaland horizontal displacement were greater withhigher depths of improvement. For 3m improved
landfill with 26.7% fly ash-quicklime, the verticalsettlement 10 years after applying traffic load below
the embankment was reduced 20% (from 370 mm to
296 mm) and this reduction for 6m, 9m, 12m and
24m improved landfill was 32%, 40%, 46% and58%, respectively.

incorporated in the finite element solution, results inreasonable agreement between the measurements
and predictions.

REFERENCES[1] Zekkos D, Flanagan M (2011) Case Historiesbased Evaluation of the Deep Dynamic
Compaction Technique on Municipal Solid
Waste Sites. Geo-Frontiers, pp 529-538[2] Kawasaki T, Niina A, Saitoh S, Suzuki Y,
Honjo Y (1981) Deep mixing method using
cement hardening agent. Proc 10th Int Conf on
Soil Mechanics and Foundation Engineering,Southeast Asian Geotechnical Soc Bangkok, pp
721–724[3] Kitazume M, Yamazaki H, Tsuchida T (2000)
Recent soil admixture stabilization techniques
for port and harbor constructions in Japan—
deep mixing method, premix method, lightweight method. Proc Int Seminar on
Geotechnics in Kochi, ISGK 2000, Kochi,
Japan, pp 23–40[4] Kehew EA (1995) Geology for engineers andenvironmental scientists,2nd edn. Prentice
Hall, Englewood Cliffs, pp 295–302[5] Horpibulsuk S, Phetchuay C, Chinkulkijniwat
A (2012) Soil stabilization by calcium carbide
residue and fly Ash. J Mater Civil Eng
24(2):184-193[6] Janz M. Johansson S (2002) The function ofdifferent binding agents in deep Stabilization.
Svensk djupstabilisering Report 9[7] Bouzoubaa N, Zhang MH, Bilodeau A,
Malhotra VM (1997) The effect of grinding on
the physical properties of fly ashes and a
Portland cement clinker. Cem Concr Res
27(12):1861–1874[8] Shi C, Day RL (1993) Acceleration of strength
gain of lime-pozzolan cements by thermal
activation. Cem Concr Res 23(4):824–832[9] Palomo A, Grutzeck MW, Blanco MT (1999)
Alkali-activated fly ashes; a cement for the
future. Cem Concr Res 29 (8):1323–1329[10] Xie Z, Xi Y (2001) Hardening mechanisms ofan alkaline-activated class F fly ash. Cem
Concr Res 31(9):1245–1249[11] Shi C, Day RL (1995) Acceleration of thereactivity of fly ash by chemical activation.
Cem
Concr
Res
25(1):15–21

Fig. 9 Typical axisymmetric geometry model

Principal Stress Difference (kPa)

1200

Effective confining pressure 200 kPa
Laboratory

1000

PLAXIS
800

600
400
200
MSW treated with 15% fly ash + 5% quick lime
0
0

2

4
6
Axial Strain (%)

810

Fig. 10 Comparison between the laboratory
measurements and finite element predictions
CONCLUSIONS
A finite element program, PLAXIS version 9,
was used to evaluate the settlement of the landfill
model under traffic load, with and without treatment
by fly ash-quicklime. The soft soil creep model wasused for this analysis. Five layers of solid waste
were used for the landfill model to evaluate how thedepth of stabilisation affected the vertical andhorizontal displacement of the model. Treated anduntreated MSW parameters used for the model wereobtained from the results of the extensive laboratory
program performed on treated and untreated MSW
samples. The vertical and horizontal displacement of
the landfill model 10 and 20 years after applying thetraffic load, and with different amounts of fly ashquicklime and various depths of improvement, were
estimated. The results of the model analyses with
PLAXIS showed that treating MSW with fly ashquicklime reduced the vertical displacement under
traffic load at the midpoint below the embankment.
Horizontal displacement of the landfill model at a
specific depth in a section below the toe of theembankment under traffic load was also705

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SHEAR PROPERTIES OF HIGH-DENSITY BENTONITE-SAND
MIXTURE UNDER UNSATURATED AND SATURATED CONDITIONS
Takeshi Kodaka1, Ying Cui1 and Hidenori Takada1
Department of Civil Engineering, Meijo University, Japan

1

ABSTRACTThe use of high-density bentonite–sand mixtures as buffer and sealing materials at the disposal sites ofradioactive waste is expected. Although the bentonite–sand mixtures at disposal sites will be in an unsaturated
condition during the construction period, they will gradually become saturated by reflooding in the ground water
after the service commencement. In the present paper, a series of unexhaust–undrained triaxial tests is performed
to study the shear properties of a high-density bentonite–sand mixture. A double cell-type triaxial apparatus has
been newly developed to observe the dilatancy behavior of the bentonite–sand mixture with various degrees ofsaturation. As a result, in the case of a low degree of saturation, the shear strength is relatively large andvolumetric expansion is observed. However, in the case of a high degree of saturation, the shear strength is small
and volumetric compression is observed. These results suggest that the mechanical properties of high-density
bentonite rapidly change with an increasing degree of saturation.
Keywords: Bentonite-sand mixture, Triaxial test, Unsaturated soil, Dilatancy, Buffer material
an unsaturated bentonite–sand mixture, with various
degrees of saturation, is performed under an
unexhaust –undrained condition. A double cell-type
triaxial apparatus has been newly developed for thisstudy to observe the dilatancy behavior of the highdensity bentonite–sand mixture during shearing.

INTRODUCTION
High-density bentonite–sand mixtures areplanned for use as buffer materials in the geologicaldisposal of high-level radioactive waste. Their use as
buffer and sealing materials at disposal sites of lowlevel radioactive waste is also expected. Since highdensity bentonite–sand mixtures are produced fromcrushed bentonite power and dry silica sand underan unsaturated condition, the mixtures are thought toremain in an unsaturated condition until refloodingin the ground water after the service commencement.
It will take a long time for the mixtures to gradually
become saturated due to their extremely low
permeability [1]-[2]. It is important, therefore, tostudy the shear and deformation properties ofbentonite-sand mixtures under both saturated andunsaturated conditions in order to design disposalsites.
Triaxial tests on saturated bentonite–sandmixtures have been performed by many otherresearch groups, e.g. [3], [4]. Only a few studies,
however, have been done on the mechanicalproperties of unsaturated bentonite–sand mixtures.
Kodaka and Teramoto [2] and Kodaka et al. [5]performed a series of direct shear box tests on
unsaturated bentonite–sand mixtures using a highpressure direct shear box apparatus. They showedthat the shear properties of unsaturated and saturated
bentonite–sand mixtures are quite different fromeach other. However, the direct shear box test is not
an element test, and thus, it is difficult to use theobtained test results for considering the constitutive
equation.
In the present study, a series of triaxial tests on

TESTING PROCEDURE
Testing Sample and Specimen Preparation
Specimens used in this study were prepared by
the following method: Powder bentonite (70% wt)
and silica sand (30% wt) were mixed well and thendistilled water was added to the mixed sample tocreate a specified moisture content. The mixed wet
sample was then put in a rigid cylindrical steel moldand one-dimensionally compressed by a hydraulicjack to become a cylindrical high-density specimen,
which has a prescribed dry density and degree ofsaturation. After the compressed specimen was takenout of the steel mold, about 5 mm were removed
from the top and bottom ends of the specimen, since
the ends of the specimen are apt to be
inhomogeneous due to compression. The specimens
prepared in the above manner are 30 mm in diameterand 70 mm in height. The dry density of thecompressed specimens is 1.60 Mg/m3.
Three types of specimens, based on degrees ofsaturation, are adopted. The first type consists ofinitial moist specimens into which no additional
water is added to the mixed sample, except for thewater initially contained in the bentonite powder.
The second type consists of quasi-saturated
specimens, whose degrees of saturation are over706

GEOMATE-Nagoya, Nov.13-15, 2013

90%. And the third type consists of various moist
specimens, which are adjusted by adding water.

A triaxial specimen is set in the inner pressure
cell and then isotropically compressed under anundrained–unexhaust condition. Confining pressurelevels of 0.1 and 0.5 MPa are adopted here. Triaxial
compression is conducted up to the axial strain of
15% under an undrained–unexhaust condition withan axial loading rate of 0.5%/min. The undrained–
unexhaust condition is thought to be most suitablefor grasping the shear properties of the unsaturated
bentonite–sand mixture just at its respective degrees
of saturation. Table 1 lists the test cases.

Triaxial Test Apparatus and Testing Conditions
The triaxial test apparatus used in this study is adouble cell-type, which has an inner pressure cell aswell as an ordinary outer pressure cell. An overview
of the apparatus and an enlarged photo of the innercell are shown in Figs. 1(a) and (b), respectively.
Figure 2 gives a schematic view of the apparatus. In
order to grasp the changes in volume of theunsaturated specimen, the drainage which goes inand out of the inner pressure cell is measured.

Table 1 Testing cases
Initial moist specimens
S r (%)σ 3 (MPa)
IM1-1
32
0.1
IM1-2
34
0.1
IM5-1
34
0.5
IM5-2
34
0.5
Quasi-saturated specimens
S r (%)σ 3 (MPa)
QS1-1
92
0.1
QS1-2
90
0.1
QS5-1
91
0.5
QS5-2
91
0.5
Various moist specimens
S r (%)σ 3 (MPa)
VM1-1
42
0.1
VM1-2
63
0.1
VM1-3
77
0.1
VM1-4
88
0.1
VM5-1
44
0.5
VM5-2
63
0.5
VM5-3
73
0.5
VM5-4
87
0.5
Note: S r and σ 3 express the degree of saturation of
the specimens and the adopted confining pressures,
respectively.

(a) Overview of triaxial test apparatus

TESTING RESULTS
Test Results of the Initial Moist Specimens(b) Specimen set in inner pressure cell

Figure 3 shows the undrained–unexhaust test
results for the initial moist specimens. In this case,exactly the same experiments were conducted twice
for each confining pressure to check the accuracy
and reproducibility. In the deviator stress – axial
strain relations, shown in Fig. 3(a), the apparent
peak strength, the subsequent strain softening andthe residual strength can be seen. The maximum
values for the deviator stress in this case are verylarge compared to those of the cases of a low degreeof saturation. This tendency shows the typical shear
characteristics of stiff and brittle geomaterials. Clear
shear bands and cracks were observed in thespecimens at the final stage of shearing.
The volumetric strain – axial strain relations areillustrated in Fig. 3(b). Since positive values for thevolumetric strain express the volumetric compression of the specimens, volumetric expansion

Fig.1 Triaxial test apparatus developed for this study.

Fig.2 Schematic view of the test apparatus.
707

GEOMATE-Nagoya, Nov.13-15, 2013

5.0

0.4

IM5-1

2.0

IM1-2

1.0
0.0
0

QS5-2
QS5-1

0.3

IM5-2

3.0

q [MPa]q [MPa]

4.0

QS1-1
QS1-2

0.2
0.1

IM1-1

3

6

9

12

εa [%]

15

0.0
0

3

6

(a) Deviator stress – axial strain relations

9εa [%]

1215(a) Deviator stress – axial strain relations

2

2.0
QS1-2

1.5

IM5-1

QS1-1

IM5-2

-2

εv [%]

εv [%]

0

IM1-1

-4
-6
0

IM1-2

3

6

9

15

0.0
0

(b) Volumetric strain – axial strain relations
φu=42.3°
cu=0.5 [MPa]

3

6

9

εa [%]

12

15

2.0

0.5
0.4

τ [MPa]τ [MPa]QS5-2(b) Volumetric strain – axial strain relations

3.0

1.0
0.0
0.0

QS5-1

0.5

12

εa [%]

1.0

1.0

2.0

3.0 4.0
σ [MPa]

5.0

6.0

0.3

φu=6.1°
cu=0.12 [MPa]

0.2
0.1
0.0
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
σ [MPa](c) Mohr’s stress circles and failure criteria(c) Mohr’s stress circles and failure criteria
Fig. 3 Test results of the initial moist specimens.
Fig. 4 Test results of the quasi-saturated specimens.
occurs at the state of post-peak and the following
residual state. This dilatancy behavior of theunsaturated specimens can be measured using the
double cell-type triaxial apparatus.
Figure 3(c) shows the Mohr’s stress circles andMohr-Coulomb failure criteria. A very large internal
friction angle is determined from this figure.

near saturation, relatively small volumetriccompression occurs during the undrained–unexhaust
shearing. In the case of larger confining pressure, theobserved volumetric compression becomes smaller.
As shown in Fig. 4(c), the internal friction angle
for the quasi-saturated specimens is very small.
However, this angle would be zero if the specimens
were fully saturated.

Test Results of the Quasi-saturated Specimens
Figure 4 shows the undrained–unexhaust test
results for the quasi-saturated specimens. This case
was also conducted using the same two specimens
for each confining pressure. In all cases, the deviator
stress monotonously increases and the maximum
values for the deviator stress are very small
compared with the peak strengths of the initial moist
specimens. Although the specimens for this case are

Test Results of Various Moist Specimens
Figure 5 shows the undrained–unexhaust test
results for the various moist specimens. Four stagesof saturation are adopted, which are covered fromlow S r near the initial moist specimens to high S rnear the quasi-saturated specimens. As illustrated in
the stress-strain relations for the 0.1 MPa confining
708

[%]

GEOMATE-Nagoya, Nov.13-15, 2013

VM1-1
0 VM5-1

VM1-3
VM5-3

VM1-2
VM5-2

The dilatancy characteristics shown in Fig. 5(b)are directly related to the results of the abovementioned stress-strain relations. Namely, although
the apparent changes in dilatancy characteristics
with different degrees of saturation can be observedin the lower confining pressure case of VM1-1~4, noclear difference is confirmed in the higher confiningpressure case of VM5-1~4.
Figure 5(c) shows that the internal friction anglesof the unsaturated specimens are more than 26
degrees, except for the high S r cases, i.e., VM1-4
and VM5-4. In these cases, the internal friction
angle slightly decreases with an increasing degree ofsaturation. However, there is a gap in the internal
friction angles between 87% and 75%.

VM1-4
VM5-4

2.5

q [MPa]

2.0
1.5
1.0
0.5
0.0
0

3

6

9

12

εa [%]

15(a) Deviator stress – axial strain relations

Effects of Degree of Saturation on Mechanical
Properties of Bentonite-sand Mixture32εv [%]

1
0

-1
-2
-3
-4
0

3

6

9

12

εa [%]15(b) Volumetric strain – axial strain relations
VM1-1, VM5-1
c=0.37MPa，φ u=26.7°

VM1-3, VM5-3
c=0.30MPa，φ u=26.0°

1.5

τ [MPa]VM2-1, VM5-2
c=0.27MPa，φ u=30.7°

1.0

VM1-4, VM5-4
c=0.20MPa，φ u=7.2°

0.5
0.0
0.0

0.5

1.0

1.5 2.0
σ [MPa]2.5

3.0(c) Mohr’s stress circles and failure criteria
Fig. 5 Test results of the various moist specimens.
pressure case, i.e., VM1-1~4, the tendency of theshear properties dramatically changes with thechanging degree of saturation. Typical strain
softening behavior is observed in the case of a lower
degree of saturation. The degree of strain softening,e.g., the difference between the peak strength andthe residual strength, gradually decreases with anincreasing degree of saturation. On the other hand,the deviator stress monotonously increases during
shearing in all specimens of 0.5 MPa.

709

The over-all test results for the cases of confiningpressures of 0.1 MPa and 0.5 MPa are shown in Figs.
6 and 7, respectively. There is a large difference inshear strength between the initial moist specimens
and the quasi-saturated specimens. The former
specimens have quite a high maximum deviator
stress and strain softening behavior, while the latter
specimens show a very low maximum deviator
stress and strain hardening behavior. The dilatancy
properties of the two kinds of specimens also show
the opposite tendency. Hence, the volumetric strainsat the shearing of the former and the latter specimens
develop dilatively and contractively, respectively.
The various moist specimens interpolate between
the initial moist specimens and the quasi-saturated
specimens. The stress – strain curves of the various
moist specimens are placed in between the curves of
those two types of specimens, as shown in Figs. 6(a)and 7(a). Therefore, the shear properties of thebentonite-sand mixture depend on the degree ofsaturation of the specimen. The maximum deviator
stress and the internal friction angle decrease with anincreasing degree of saturation. There is a gap
between VM1-3 (VM5-3) and VM1-4 (VM5-4).
This result suggests that the mechanical properties
rapidly change at relatively high degrees ofsaturation.
The supposed saturation process of thebentonite–sand mixture at real disposal sites is thatthe high–density bentonite-sand mixture isconstructed under the condition of a low degree ofsaturation and then the mixture is gradually saturated.
In this study, however, water is added to the granularmaterial mixed with bentonite powder and sandunder an unconfined condition and then compacted
to be of high-density. Thus, it should be noted thatthe saturation process of the mixture may bedifferent from the actual condition.

GEOMATE-Nagoya, Nov.13-15, 2013

VM1-1
VM1-4

VM1-2
QS1-2

IM5-1
VM5-3

2.5

5.0

2.0

4.0

q [MPa]q [MPa]

IM1-2
VM1-3

1.5
1.0

3

6

ε

9
a [%]

12

12

2.0

3

6

15

(a) Deviator stress – axial strain relations
2.0
1.5
1.0
0.5
0.0
-0.5
-1.0
-1.5
-2.0
0

2
1

εv [%]

0εv [%]

εa [%]9

3.0

0.0
0

15

(a) Deviator stress – axial strain relations

-1
-2
-3
-4
-5
0

VM5-2
QS5-1

1.0

0.5
0.0
0

VM5-1
VM5-4

3

6

εa [%]9

12

15

3

6

εa [%]91215(b) Volumetric strain – axial strain relations(b) Volumetric strain – axial strain relations
Fig. 6 Test results in the low σ3 case.

Fig. 7 Test results in the high σ3 case.

CONCLUSIONREFERENCES

A series of unexhaust–undrained triaxial tests
was performed to study the shear properties of ahigh-density bentonite–sand mixture. From the test
results of this study, in the case of a low degree ofsaturation, the shear strength is relatively large andvolumetric expansion is observed. However, in thecase of a high degree of saturation, the shear
strength is small and volumetric compression isobserved. These results suggest that the mechanicalproperties of high-density bentonite rapidly changewith an increasing degree of saturation.

[1] Komine K and Ogata N, “Experimental study
on swelling characteristics of sand-bentonite
mixture for nu-clear waste disposal” Soils andFoundations, Vol.39, No.2, 1999, pp83-97.
[2] Kodaka T and Teramoto Y, “Shear Failure
Behavior of Compacted Bentonite” in Proc. Int.
Symp. on Prediction and Simulation Methods
for Geohazard Mitigation, IS-Kyoto 2009,
pp.331-337.
[3] Namikawa T and Sugano T, “Shear propertiesof buffer material 1”, Technical Report ofPower Reacter and Nuclear Fuel Development
Corporation, PNC TN8410 97-074, 1997 (inJapanese).
[4] Takaji K and Suzuki H, “Static mechanicalproperties of buffer material”, Technical Reportof Japan Nuclear Cycle Development Institute,
JNC TN8400 99-041, 1999 (in Japanese).
[5] Kodaka T, Teramoto Y, Hirate T and
Motoyama Y, “Density changes and sealing
performance of damaged compacted bentonite”
in Proc. 14ARC, 2011, Paper ID:197.

ACKNOWLEDGEMENTS
The authors wish to express their sincere
appreciation to Dr. Kawaguchi of Kitami Institute ofTechnology for his great support regarding the
manufacture of the testing apparatus. Financial
support for this study has been provided by the
Kajima Foundation, Japan.

710

Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

ENVIRONMENTAL CONDITION INDEX FOR ESTIMATION ON
EUTROPHIC STATE OF ENCLOSED AQUIFER ECOSYSTEM

1

Kazuhito Murakami1, Michio Gomyo1, Saki Agatsuma1 and Yoshimasa Amano2
Department of Life and Environmental Sciences, Chiba Institute of Technology, Japan; 2Department ofApplied Chemistry and Biotechnology, Chiba University, Japan

ABSTRACTTo evaluate the effect of sediment treatment on aquifer ecosystem, a new ecological index that is composedof water quality, sediment quality and biota quantity was proposed in this study. According to ECI(Environmental Condition Index), DAF treatment (Dissolved Air Flotation) + MgO sprinkling was assessed as
the most efficiency method for improvement of eutrophicated ecosystem, that is, this method can make theorganic matter quantity in aquatic ecosystem minimum level in comparison with other sediment treatment
method. Also, for application of this method to real field remediation such as eutrophicated lake, marsh,
reservoir and so on, more detailed analysis for treatment function and optimum condition of sediment treatment
was considered to be necessary.
Keywords: Environmental condition index, Aquifer ecosystem, COD, IL, Chl.a, Eutrophicated lake

For evaluation and/or assessment of anenvironment, a variety of index, such as diversity
index for biota (for example, Shannon index,
Simpson’s index, and so on), has been proposed andapplied. Most of these indexes are based on biotic
diversity, because biota, whether fauna or flora,indicates synthetic results of environmental
fluctuations, that is, water and sediment condition
are reflected to biota. Although the biotic index canbe recognized as one of the most essential indexes toevaluate the environmental condition, it is notenough to indicate the water/sediment condition. It
is recognized that water and/or sediment condition is
not reflected perfectly to biotic index, and thesethree elements, i.e. water, sediment and biota, arerelated with one another in multiplication [2].
In this study, a new ecological index forindicating the environmental condition was
calculated using the data that is obtained from theresults of microcosm experiment.
The environmental condition index (ECI) was
calculated by the equation (1) as described below;

INTRODUCTION
The countermeasure to the nutrient elution fromeutrophicated sediment is necessary to be conductedwith the cut of the inflow loading of nutrient from abasin area of eutrophicated lake and marsh.
Furthermore, it is reported that the eluted nutrient
loading from the accumulated sediment reaches 5-10
times of the inflow loading. This constanteutrophication problem is in the point that organic
polluted mud is accumulated to the inflow rivers andthe lake itself, it is necessary that the organic
sediment, which is over quality for water quality andwater livings, is taken away from the inside to theoutside of the ecosystem [1]. However, the direct
removal methods such as digging / boring have arisk, which disturb the lake ecosystem, and someorganic matter and nutrient should be left in thesediment to preserve macrobenthos and so on. In thiscase, water quality purification will be expected byprevention of nutrient elution from the sediment.
In present study, DAF (Dissolved Air Flotation)
treatment, MgO sprinkling and CaO sprinkling as
CRM (Chemical Remediation Materials) treatment
were conducted, and the effect of these treatment
methods on the lake ecosystem was evaluated fromthe viewpoint of ecological influence. Furthermore,a new index that indicating synthetic state of
ecosystem was proposed and the effect of sediment
treatment on the lake ecosystem was evaluated using
this index.
PROPOSALOFCONDITION INDEXECI = 3 C (COD ) × C ( IL ) × C (Chl .a )(1)

Where,C (COD ) = ∑ LCOD , i / CODmean,
C ( IL ) = ∑ LIL , i / ILmean
C ( Chl .a ) = ∑ LChl .a , i / Chl.amean .

,and

ENVIRONMENTAL
This index has no mathematical dimension. L COD,i,
L IL,i and L Chl.a,i mean the existed quantity of COD,

711

GEOMATE-Nagoya, Nov.13-15, 2013

IL and Chl.a in microcosm during the incubation
period, respectively. COD mean , IL mean and Chl.a mean
mean the average concentration of COD, IL and
Chl.a in microcosm. This index means watercondition by COD (Chemical Oxygen Demand)
concentration, sediment condition by IL (Ignition
Loss) concentration, and phytoplankton quantity by
Chl.a (Chlorophyll a) concentration. When ECI is
low value, the quantity of organic matters in theenvironment is low level, and when ECI is highvalue, the quantity of organic matters is high level inthe opposite direction. The concept of ECI isindicated in Fig.1. The organic matters arerecognized in general as one of main pollutant foraquatic ecosystem. This ECI can indicate thepollution level of organic matters in aquatic
ecosystem, such as lake, marsh, reservoir, river, sea,
and so on.

CRM treatment was conducted as follows; MgO
and CaO were prepared to sprinkle on the surface of
sediment in experimental microcosm. Thesechemical agents are expected to control the elutionof nutrient salts from sediment layer [4], [5].
Microcosm Culture
The microcosm experiment was conducted using
470ml volume glass vessel, and with 4 series
culturing. Those are,Run 1：untreated sediment 100g(w.w.) + Lake Tegawater 380mL,
Run 2：DAF treated sediment 100g(w.w.) + Lake
Tega water 380mL,
Run 3：DAF treated sediment 100g(w.w.) + MgO
400g/m2 + Lake Tega water 380mL,
Run 4：DAF treated sediment 100g(w.w.) + CaO
100g/m2 + Lake Tega water 380mL.

EXPERIMENTAL PROCEDURES
Water and sediment were collected from Lake
Tega that locates in the northwest area of Chiba
prefecture in east Japan and is well known as one of
the most polluted enclosed aquifer.

As described above, experimental microcosm inthis study consisted of water and sediment, likenatural lake ecosystem. Thus, system has acharacteristic that stability and sustainability of thisecosystem are very high [6], [7]. All grass vessels
were sealed up and cultured under unstirring, 20℃,
bright (20,000lux) and/or dark condition. Samplingfrom a boundary between sediment and water was
conducted at intervals of 2 days after the cultivation
started. The experimental condition of microcosm
culture was shown in Fig.2.

Sediment Treatment
DAF treatment was conducted as follows; 50L ofwater was poured into 80L volume reactor, then
7kg(w.w.) of sediment was innoculated. Microbubble was continuously injected under the sedimentto water, and the poly ferric sulfate as coagulant (4Lof 200mg/L) was added. Sediment with muchorganic matter can be divided into froth and treatedsediment in this process [3], [4].

Parameters for Evaluation
COD, IL and Chl.a concentrations were
measured to calculate ECI. COD is for water quality,
IL is for sediment quality and Chl.a is for biota
quantity, and ECI was calculated to evaluate theeffect of sediment treatment to the lake ecosystem.
In addition, phytoplanktonic flora, one of biotic
indexes to assess the environmental condition [8],was also analyzed by microscopically observation tocompare with ECI.

Biota
（Chl.a）

RESULTS AND DISCUSSIONS
Water Quality Assessment

ECI
Water
（COD）

Total COD quantity in each culture series were;694.8mg/L/28days in Run 1, 480.5mg/L/28days in
Run 2, 361.4mg/L/28days in Run 3, and886.6mg/L/28days in Run 4, respectively. As shownin Fig.3, COD value increased from 3rd day after thecultivation started, and indicated the maximum value
in 10th day, and decreased with gentle slope. This isbecause removal by DAF treatment and restraint by
MgO sprinkling for the elution of nutrient salts from

Sediment（I.L.）

Fig.1 Concept of Environmental Condition Index
(ECI)
712

GEOMATE-Nagoya, Nov.13-15, 2013

Fig.2 Experimental Condition of Microcosm Culture
the sediment layer lead low growth of phytoplankton
and low COD concentration in Run 3. On the other
hand, CaO sprinkling made phytoplanktonic growthand COD increasing in Run 4, because of its
characteristics, i.e. washing out effect of NH 4 -Nfrom the sediment layer [9]. In comparison with thetotal COD quantity in Run 1 that is set to value
100%, 69.2% in Run 2, 52.4% in Run 3 and 127.6%
in Run 4. Quantity of COD is considered asindicator of water quality, that is quantity of organic
matter. From these results, Run 3, that is, DAF
treated sediment + MgO sprinkling, was assessed as
the most effective improvement method.

in Run 4. In comparison with the total IL quantity inRun 1, that was set to value 100%, 91.9% in Run 2,
110.6% in Run 3 and 97.9% in Run 4 wererecognized. Quantity of IL is considered as indicatorof sediment quality as quantity of organic matter.
From these results, Run 2, that is, DAF treatedsediment, was assessed as the most effective
improvement method.
Biota Quantity Assessment
Total Chl.a quantity in each culture series were0.512mg/L/28days in Run 1, 0.192mg/L/28days in
Run 2, 0.088mg/L/28days in Run 3, and
0.222mg/L/28days in Run 4. Succession of Chl.a
concentration in each culture series was shown in
Fig.5. The dominant species in each microcosm
cultureserieswere
cyanophyceae
andbacillariophyceae in Run 1, bacillariophyceae in Run
2,bacillariophyceae,
chlorophyceae
andphytoflagellata in Run 3, and bacillariophyceae in
Run 4. This is because these sediment treatments
lead the difference of T-N/T-P mass ratio in water.
Composition of phytoplanktonic flora is mucheffected by T-N/T-P mass ratio in water [10]. DAF
treatment removes nitrogen peculiarly, and T-N/T-P
mass ratio becomes lower, where cyanophyceae
cannot grow in Run 2. MgO sprinkling leads higher

Sediment Quality Assessment
Total IL quantity in each culture series were
996mg/g/28days in Run 1, 916mg/g/28days in Run 2,
1,102mg/g/28days in Run 3, and 975mg/g/28days in
Run 4. As shown in Fig.4, IL value indicated the
maximum value in 1st day, and decreased withgentle slope. This is because DAF treatment
removed organic matters from the sediment layer in
Run 2, and MgO sprinkling restrained the elution ofnutrient salts which introduced bacterial growth insediment layer, that means IL increasing in Run 3.
CaO sprinkling made NH 4 -N washed out and leadbacterial growth under nitrogen-limiting condition
713

GEOMATE-Nagoya, Nov.13-15, 2013

COD(mg/L)

50
40

Run 1
Run 2
Run 3
Run 4

30
20
10
0
0

20

10

30

cultivation time (day)Fig.1Fig.3
Successionof COD concentrationin water on each experimental
Successionof COD concentrationin water series

concentration, and hybrid treatment of DAF
treatment and CaO sprinkling introduce high T-N/TP mass ratio to an extreme. In comparison with thetotal Chl.a quantity in Run 1, that was set to value
100%, 37.6% in Run 2, 17.2% in Run 3 and 43.3%
in Run 4 were recognized. Quantity of Chl.a isconsidered as indicator of biological quantity, i.e.
quantity of phytoplankton. From these results, Run 3,
that is, DAF treated sediment + MgO sprinkling,
was assessed as the most effective improvement
method.

5
IL(g/100g)

4Ecological Estimation
Condition Index (ECI)

Run 1
Run 2
Run 3
Run 4

3
2
1
0
0

10

20

30

cultivation time (day)Fig.2

Successionof IL concentration
sediment layer on eachexperimental series
Fig.4
Successionof ILinconcentrationin sedimentChl.a(μg/L)

30
Run 1
Run 2
Run 3
Run 4

20
10
0
0

10

20

30

cultivation time (day)Fig.3

Succesion of Chl.a concentration in water in each experimental series

Fig.5 Succession of Chl.a concentration in phyto-plankton

T-N/T-P mass ratio, because it has effect to restrain
phosphorus. From this, the hybrid treatment of DAF
treatment and MgO sprinkling can make nutrient
salts concentration lower with keeping T-N/T-P mass
ratio properly, like Run 3. CaO sprinkling lead muchhigher T-N/T-P mass ratio because of its washing out
effect on NH 4 -N, even after DAF treatment in Run 4.
Concluding these characteristics, DAF treatment
lead lower T-N/T-P mass ratio, hybrid treatment,
DAF treatment and MgO sprinkling keep proper TN/T-P mass ratio with low nutrient salts

fromEnvironmental

ECI value in each culture series were 1.69 in
Run 1, 1.22 in Run 2, 0.87 in Run 3, and 1.45 in Run
4. From these results, Run 3, that is, DAF treatedsediment + MgO sprinkling, was assessed as themost effective improvement method. Comparison ofeach index in experimental culture was shown in
Table 1.
In comparison with an analysis of phytoplanktonic
flora as biotic indicator using microscopic
observation, ECI can explain the difference ofphytoplanktonic succession in each culture series.
Biomass rate of each phytoplankton species, i.e.
cyanophyceae, bacillariophyceae, chlorophyceae andphytoflagellata in each treatment condition wereshown in Fig.6. The dominant species ofphytoplankton in each culture series wereMicrocystis aeruginosa, Anabaena spiroides(cyanophyceae)
andMelosira
granulata(bacillariophyceae) in Run 1, M.granulata andNitzschia acicularis (bacillariophyceae) in Run 2,
M.granulata (bacillariophyceae),
Scenedesmus
quadricauda (chlorophyceae) and Chlamydomonas
spp. (phytoflagellata) in Run 3, and M.granulata andN.acicularis (bacillriophyceae) in Run 4. These
species are recognized as biotic indicator for
eutrophication and organic pollution of water
environment [11]. According to the Saprophilous
classification, Run 1, Run 2, Run 3 and Run 4 areunder the state of ps, β-ms, os and α-ms respectively.
This means Run 1 is the most polluted /eutrophicated state and Run 3 is the most purified /oligotrophic state.

Table 1 Comparison of each index in each experimental series
Run No.

Sediment

total

treatment

COD

total IL

total

ECI

Chl.a

Saprobic

dominant species of phytoplankton

index

Run 1

no treat

100

100

100

1.69

ps

cyanophyceae, bacillariophyceae

Run 2

DAF

69.2

91.9

37.6

1.22

ms

bacillariophyceae

Run 3

DAF + MgO

52.1

110.6

17.2

0.87

os

bacillariophyceae, chlorophyceae

Run 4

DAF + CaO

127.6

97.9

43.3

1.45

ms

bacillariophyceae714

GEOMATE-Nagoya, Nov.13-15, 2013

Run 1 (control)
Biomass rate

Biomass rate

100%

100%

80%

80%

60%

60%

40%

40%

20%

20%

0%

Run 2 (DAF treatment)

0%
0

1

3

5

7

10

14

21

30

days

0

Run 3 (hybrid treatment (DAF + MgO))

1

3

5

7

10

14

21

30

days

Run 4 (hybrid treatment (DAF + CaO))

Biomass rate

Biomass rate

100%

100%

80%

80%

60%

60%

40%

40%

20%

20%

0%

0%
0

1

3

5

7

cyanophyceae

10

14

21

30

days

0

chlorophyceae

13bacillariophyceae

5

7

10

14

21

30

days

phytoflagellata

Fig.6 Biomass rate of each phytoplankton species on each experimental series
The experimental results from batch culturing
series, were considered to satisfy the theologicalhypothesis that the hybrid treatment can control
nutrient elution from the sediment more effective
than DAF and/or no treatment, because water bloom
which observed generally in Lake Tega in summer
was not observed in grass vessel. Thus, efficiency ofthis hybrid treatment system of DAF treatment andMgO sprinkling for sediment remediation,
possibility of artificial control on phytoplanktonic
flora and necessity to establish environmental
assessment method on ecosystem level such as ECI
proposed in this study were indicated. And to makethese treatment methods be applied to real field suchas eutrophicated lake and marsh, more detailed
analysis for treatment function and optimum
condition of sediment treatment was considered tobe necessary.

make the organic matter quantity in aquatic
ecosystem minimum level in comparison with othersediment treatment method. More detailed analysis
for treatment function and optimum condition of
sediment treatment was considered to be necessary
to make these treatment methods be applied to real
field remediation such as eutrophicated lake, marsh,
reservoir and so on.
ACKNOWLEDGEMENTS
This work is partially supported by the Grant-inAid for Scientific Research (24651029) of Japan
Society for the Promotion of Science (JSPS).
REFERENCES[1] Inamori Y, Jin X, Park J, and Xu K, Guideline on
the Management for Establishment of EcoSound Watershed Environment of Lakes andMarshes. Tokyo: The Industrial Water Institute,
2007.
[2] Wetzel RG, Limnology, Third Edition: Lake andRiver Ecosystems, Academic Press, 2001.
[3] Agatsuma S, Murakami K, Gomyo M and
Amano Y, “Shell Fragment Application as
Regional Unused Resources for Nutrients
Elution Control from Eutophicated Sediment”, in

CONCLUSIONS
To evaluate the effect of sediment treatment on
aquifer ecosystem, a new ecological index that iscomposed of water quality, sediment quality andbiota quantity was proposed in this study. According
to this ECI (Environmental Condition Index), DAF
treatment + MgO sprinkling was assessed as themost efficiency method, that is, this method can
715

GEOMATE-Nagoya, Nov.13-15, 2013

Proc. 5th IWA-ASPIRE Conf. Exhib., 2013, CDROM.
[4] Agatsuma S, Murakami K, Gomyo M and
Amano Y, “Water Quality Purification in the
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Regional Unused Resources”, in Proc. Wat.
Environ. Technol. Conf. 2013 (WET2013), 2013.
[5] Amano Y, Taki K, Murakami K, Ishii T and
Matsushima H, “Sediment Remediation for
Ecosystem in Eutrophicated Lakes”, The
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[7] Beyers R J, and Odum H T, Ecological
Microcosms, New York: Springer-Verlag, 1993.
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Treatment in Eutrophicated Lakes using
Experimental Mesocosm System”, Papers on

Environmental Information Science, No.22,
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[9] Muto T, Saito T, Matsushima H, Tanaka K,
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2000, CD-ROM.
[10] Fujimoto N, Fukushima T, Inamori Y, Sudo R,“Analytical Evaluation of Relationship between
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Environmental Factors in Japanese Lakes”, J. of
Wat. Environ., Vol.18, No.11, 1995, pp.901-908.
[11] Watanabe T, Asai K, Houki A, Tanaka S, andHizuka T, “Saprophilous and Eurysaprobic
Diatom Taxa to Organic Water Pollution andDiatom Assemblage Index (DAIpo)”, Diatom,
Vol.2, 1986, pp.23-73.

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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

SHALE FAILURE AND CRACKING IN A SEMI-ARID AREA

Muawia Dafalla1, Mutaz, E2. , Mansour Al humimidi3, Loni Allafouza Oumar3 and Mosleh Al Shamrani4
1, 2, 4
Civil Engineering, King Saud University, Saudi Arabia
3
King Abdulaziz City for Science and Technology, Saudi Arabia

ABSTRACTA semi-arid shale formation in the northern and central part of Saudi Arabia showed frequent near surface
cracks and distress at several sites. This phenomenon was found to be of a serious risk to structures founded onor near cracks or failure zones. This study was carried out for an area where several centimeters wide groundcracks extending over more than one kilometer distance across a populated area in Saudi Arabia. The dominantsubsurface formation in the area is reddish brown stiff to hard silty to clayey shale underlain by sandstone
formation. The subsurface material was explored and clayey shale samples were extracted. The study included
borehole drilling and test pit excavations. Soil classification and consistency tests were performed. A series ofphysical and chemical testing confirmed the expansive nature of the shale. The possible causes of cracks and themechanisms of failure in semi-arid shale were covered and discussed in sufficient details. Engineering guides forbuildings and construction in typical zones were presented.
Keywords: Shale; Expansive; Clay; Cracking; Semi-arid.

INTRODUCTION
The shale is encountered in many parts of Saudi
Arabia covering major zones of the central, northand north-western parts of the country. Clayey
shales and silty shales were reported in Al Ghatt,Tabuk, Tayma and Aljoaf. Reference [1] highlighted
the presence and expansive nature of clay shale in
Tabuk. In recent years some ground cracks appearedin several locations causing concerns to municipal
authorities. The phenomenon is only associated withshale zones and happened to affect existing
structures. Reference [2] presented works covering
an area in Madraj near Buraida town in central Saudi
Arabia. Earthquake and seismic activities were
excluded of being the reason behind thisphenomenon as the area does not have any history of
tectonic activities and classified within zones ofnegligible acceleration. This work is part of thestudies to investigate the physical and geotechnicalnature of the shale where these cracks appeared.
Deeda, a small village within the central province
was chosen as the study area. Figure 1 presents thegeographical location. The area geology belong toSudair formation consisting of shale, silt, claystoneand sandstone. These quaternary deposits areunderlained by limestone formation of Triassic age.
Cracks in the ground affected several structures anda major mosque had to be removed as a result ofexcessive distortion. Cracks extended over morethan one kilometer causing damage to asphalt roads
and other light structures.

Fig. 1 Study region in Central Saudi Arabia

Fig.2 Typical ground cracks reported in shale
formation.

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GEOMATE-Nagoya, Nov.13-15, 2013

tube core barrel. Sound and intact rock cores wereextracted and transported to the laboratory forfurther testing. As a part of this investigation seismic
explorations were also conducted. Two seismic lines
passing through the boreholes were tested. The
geotechnical soil profile was constructed based on
the outcome of boreholes, seismic data andlaboratory tests.

GEOLOGY AND GEOENVIRONMENT
The local geology of area consists of recent
deposits of sand, silt and clay with occasional
gravels of variable sizes. This is underlain by clayey
shale material. Reference [3] presented a geologicalmap for Deeda describing the underlying dolomitic
sandstone as belonging to JILH formation

Fig. 5 Drilling Plant on site.
Fig. 3 Geologic map of Deeda Area [3].

The expansive shale like other fat clays is very
sensitive to moisture conditions. Drying and wetting
are associated with shrinkage and expansion. The
temperature range of Al Qassim region vary from -2
degrees in winter to 49 in summer. The annual
rainfall varies from year to year with a minimum of
25mm and a maximum of 230mm. Figure 4
presents change of annual precipitation over 60
years.
250
200

Fig. 6 Typical Shale section from the study area.

150

RESULTS AND DISCUSSION

100
50

The boreholes revealed that the site is overlain
by a top soil consisting of brown to reddish brownclayey sand followed by hard sandy clay. The
plasticity of clay is increasing with depth. The soil
below the level of 3 to 7.5 m is classified within the
CH group and this was found extending to a depth of
22.5 m. No open cavities were reported. The drilling
fluid used was water. No water loss reported during
drilling activities. The sandstone underlying shale
formation is weakly cemented on top. The sandstone
cementation is improved with depth. Recovery ofsoils and rock varied from zero to 100% and RQD(rock quality designation factor) varied from zero to95%. Ground water was encountered at a depth of
24.5 m below ground level. This level is fluctuating

0
1960

1970

1980

1990

2000

2010

Fig. 4 Annual precipitation changes over 60 years.
EXPLORATION ACTIVITIESThe site was explored by advancing twoboreholes within the zones of cracking down to 25
depths. Two test pits were excavated to 3m depth
below ground level. Wash boring technique was
employed and standard penetration tests werecarried out at intervals of 1.5m. On encountering
hard formation drilling was continued using double
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GEOMATE-Nagoya, Nov.13-15, 2013

during different season times of the year.
Engineering property tests indicated SC (clayey sandsoil followed by CL (clay) and CH. The finematerial passing sieve number 200 varied from 25%
to 94%. The liquid limit varied from 50 to 95 andthe plasticity index from 30 to 48. Soil classification,
modified proctor and standard penetration tests werecarried out in accordance with American standard
testing methods [4], [5] and [6].

Testing Methods (ASTM) for one-dimensional
consolidation properties of soils using incrementalloading was used [7]. Swelling pressure tests using
odometers indicated swelling pressure of the orderof 700 to 800 kPa. This figure is obtained in thelaboratory for a confined small sample. The actualswelling pressure in field is far less and can be taken
as one third of this value [8]. The swell pressure fornon-confined field condition of 250 kPa can be
adopted. The overburden pressure for 2.5m is
estimated at 50 kPa.

The seismic profile for borehole (1) indicated
two main layers of sediments followed by sandstone.
The top layer indicated an average depth of 3m
while the second layer extended beyond 18 meters.
The seismic profile for borehole 2 yielded the same
but indicating 5m thickness for top soil and morethan 20 m for shale or claystone.

The chemical tests carried out for a sample takenfrom TP 1 indicated elements as listed in Table 1.
Table 1 Elements concentration in Deeda clay
Elements
Al
Ca
Fe
Mg
Si
Na
K

Percentage %
5.2
14.4
4
0.6
33.0
14.4
6.5

Quartz and calcium are dominant. Alminium,
Calcium and Magnisium are basic components ofsmectite clay minerals that are associated withexpansive clays.
Fig. 7 Travel time and distance profile for line
across BH1.

Structures founded on typical soils shall be
designed following all instructions listed in Chapter
9 of the Saudi Building Code SBC 303[9]. However,for certain structure it might be feasible to consider
pile foundations and transfer the superstructure
stresses down to the sandstone formation. Light
structures shall have their foundations placed at aminimum depth of 2.5m below ground level and thesame time contact pressures from dead loads shall bein the order of 200kN/m2. It is also recommended to
avoid placing the foundations right on the groundcrack lines. A 50m distance away from the cracks
will be sufficient to avoid distress and unexpected
settlement. Excavations shall extend beyond thebottom level of cracks and careful inspection must
be carried out prior to placing footings within thecracks zone.

Fig. 8 Geological section derived from seismic lineat BH 1.

CONCLUSION

The engineering properties indicated that thesubsurface material belongs to expansive clay group.
The cracks can form as a result of drying andshrinkage. The cracks did not show a relative
vertical movement that reflects deep failure or any
signs of tectonic damage. American Standard

The shale can be subjected to serious shrinkage
on drying and can introduce ground cracks. Volume
changes in shale can be very serious for light
structures. All foundations placed on typical material
shall consider all precautions for expansive soils as
set in international standards. Special reference is719

GEOMATE-Nagoya, Nov.13-15, 2013

made to the Saudi Building Code Chapter 9.
Foundations placed on expansive soils shall be basedon sizing the footing dimensions in sucharrangements that contact pressure due to deadloads between concrete and soil is in excess of theswelling pressure. A 200 kN/m2 is suggested as adesign value for this particular area.

[3] Robelin, C., Al-Muallem, M.S., Brosse, J.-M.,
Fourniguet, J., Garcin, M., Gouyet, J.-F.,
Halawani, M.A., Janjou, D., Le Nindre, Y.-M.,
1994. Geologic map of the Qibah Quadrangle;
Sheet 27-G, Scale 1:250,000, Kingdom of Saudi
Arabia. Saudi Arabian Ministry of Petroleum
and Mineral Resources, Jeddah, Geoscience
Map GM-136.

ACKNOWLEDGEMENTS[4] American Standard Testing Methods (ASTM).
American Society for Testing and Material.
(ASTM D 2487).
[5] American Standard Testing Methods (ASTM).
American Society for Testing and Material.
(ASTM D1557)[6] American Standard Testing Methods (ASTM).
American Society for Testing and Material.
(ASTM D 1586)[7] American Standard Testing Methods ( ASTM)
for One-Dimensional Consolidation Propertiesof Soils Using Incremental Loading (ASTM
D2435 – 04)

This research is part of a project funded by King
Abdul-Aziz City for Science and Technology,
Project Number 542. Authors would like to thankgeotechnical and geophysical teams participated inthis work.
REFERENCES[1] Dhowian, A.W. (1984). Characteristics ofExpansive Clay-Shale in the Northern Region of
Saudi Arabia. Proc. of 5th Int. Conf. on
Expansive Soils, Adelaide, South Australia,
pp.316-320.

[8] Al-Shamrani, M. A. and Dhowian A. W
(2003). Experimental study of lateral restraint
effects on the potential heave. Engineering
Geology 69 (2003) pp. 63–81[2] Alfozan, F and Dafalla, M (2013). Study ofcracks and fissure phenomenon in central Saudi
Arabia by applying geotechnical andgeophysical techniques. Arab J Geosci. DOI 10,
1007/s12517-013-0884-7.

[9] Saudi Building Code (SBC 303).

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GEOMATE-Nagoya,Nov.13-15, 2013
Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

EARTH MASONRY UNIT: SUSTAINABLE CMU ALTERNATIVE
Joseph Dahmen1, Jose F. Muñoz2
School of Architecture and Landscape Architecture, University of British Columbia, Canada;
2
Watershed Materials LLC, US.

1

ABSTRACTThis paper provides a justification for a masonry building block fabricated from soil materials that could
radically improve the environmental profile of one of the most common construction materials on the planet.
Typical concrete masonry units depend on the reaction of ordinary Portland cement to provide strength anddurability. While effective at meeting structural requirements, a study has shown that production of ordinary
Portland cement causes 6-7% of global greenhouse gas emissions [1]. In contrast, the principal component ofstabilized earth mix designs is soil, a ubiquitous, innocuous, and almost unlimited resource that offers thepotential of sustainable cradle-to-cradle environmental performance over a full life cycle of products. The paper
presents research investigating the characteristics of a range engineered soil blends and natural soil sources. The
research is applied toward the production of an environmentally sustainable stabilized earth masonry building
block capable of meeting current ASTM concrete block performance specifications while reducing embodied
energy by as much as 50% due to the reduction of energy-intensive Portland cement binders, dramaticallyreducing CO2 emissions of this common construction material
Keywords: Sustainable Construction Materials, Concrete Masonry Unit, Green Building, Green Materials,
Nanotechnology

atmosphere [2] and a study has shown that
production of cement causes 6-7% of global
greenhouse gas emissions [3]. CMUs, the technicalterm for common concrete masonry blocks used inconstruction, are ubiquitous unitized building
materials that contain between 10-16% cement by
weight. In 2007, 8 billion CMUs were produced in
the US, requiring the use of approximately 15.2
million metric tons (MMT) of cement. The
manufacture of this cement released approximately
13.7 MMT of CO2 into the atmosphere. This
represents approximately .25% of the 6,000 MMT
of CO2 emissions resulting from energy andindustry overall in the US during the same year [4].
The standard CMU is a rectangular
200x200x400 mm (8x8x16-inch) unit comprised ofordinary Portland cement (OPC), gravel, sand, andwater. The concrete mixture may also containingredients such as supplementary cementitious
materials (SCMs), accelerators, retarders, andplasticizers governing setting time and workability,
air-entraining agents, coloring pigment, and water
repelling admixtures. During the conventional
CMU manufacturing process, a machine molds
moist, low-slump concrete into the desired shapes,
which undergo accelerated curing at elevatedtemperatures inside a semi-enclosed curing
chamber. This is generally followed by a drying
and storage phase. The manufacture of CMUs has
been characterized by modest, incremental
improvement since its introduction over one
hundred years ago.

INTRODUCTION
This paper presents a vision and justification fordeveloping a reduced cement structural masonrybuilding block fabricated primarily from soilmaterials that could reduce a significant amount ofgreen house gas emissions, radically improve theenvironmental profile of one of the most common
construction materials on the planet. The paper
discusses existing concrete masonry unit (CMU)
manufacturing practices and their associatedimpacts, as well as come techniques currently in
use to incrementally improve environmental
impacts. These conventional practices offer abackdrop against which as radical cement-freeblock is proposed that would make use of advancesin nanotechnology and geopolymerization. The
paper briefly describes the current masonrymarketplace in the US, identifying the commercial
potential of a cement-free masonry building block,and sketches a development pathway to takeadvantage of the opportunity. These arguments
provide justification for the development of astructural masonry building block fabricated fromengineered soil materials.
BACKGROUND AND CONTEXT
Concrete is the most voluminous manufactured
product in the world, with annual consumption
approaching 20,000 million metric tons (MMT).
The production of each metric ton of cement resultsin roughly 900 KG of CO2 released into the721

GEOMATE-Nagoya, Nov.13-15, 2013

Environmental Impacts
Concrete Masonry Unitsofconventional SCMs in proximity to areas
demonstrating the greatest demand for cement
presents another problem. In 2010, the annual
global demand of cement was close to 3,300
million tons [11], while the global combined
production of fly ash, iron and steel slag, and silica
fume accounted for 750 million tons [12,13,14],much of it highly toxic and potentially unusable.

Conventional

A cradle to gate LCA study conducted by thePortland Cement Association in 2007 indicates that
91% of the GHG released by the manufacture of
CMUs are attributable to the OPC constituent used
as a binder [5]. This is mainly due to the intenseheat required for cement manufacture, together with
the CO2 released during the calcination phase, inwhich the raw limestone is converted to calciumoxide and CO2 [6]. It follows that reducing thecement content of a CMU will significantly reduce
its overall environmental impact.
Currently, the leading method for reducing theenvironmental impact of concrete is to replace a
portion of OPC binder constituent with SCMs. This
class of materials includes fly ash, silica fume,metakaolin and natural pozzolans. In practice, themost commonly used SCMs are industrial byproducts such as fly ash and ground granulated
blast furnace slag, due to their low cost and generalavailability. When added to concrete mixes, it has
been demonstrated that these materials can reduce
the need for OPC binders significantly [7],effectively reducing GHG emissions with only
small reductions of strength and durability.
However, despite widespread use of fly ash andother SCMs derived from industrial byproducts as ameans to reduce embodied energy in the
manufacture of concrete, recent research suggeststhat their use may be limited by geographicalavailability, and that these materials may also
contain significant hazards to human health.
Toxicity is the most pressing issue with respect
to SCMs derived from industrial byproducts. The
composition of fly ash, one of the most plentiful
and widely-used OPC substitutes, varies widelywith fuel source, and has been shown to containsuch highly toxic elements such as arsenic,
beryllium, cadmium, chromium and lead, among
others, along with dioxins and polycyclic aromatichydrocarbons compounds in concentrations that canbe up to several percent of the total material [8].
Questions remain as to whether the hydration
reaction of fly ash and cement is capable ofsufficiently immobilizing the toxic elements in fly
ash and leaching of heavy metals, which is of
special concern where concrete comes into contact
with water [8,9,10]. Past experiences with leadpaint, asbestos and arsenic-treated wood should
prevent from a widespread use of a product without
a full understanding of the impacts on human health[7], and additional research is needed to assure thenon-toxicity of concrete incorporating significant
amounts of fly ash and other SCMs over the life of
the material, particularly where residential
construction is concerned.
Issues of toxicity aside, inadequate supply ofFig. 1

Evolution of SCM production and cement
consumption in U.S. [10-12]

As shown in Figure 1, between 2000 and 2010,
fly ash accounted for approximately 80% of the
production of these SCMs in the U.S. Life cycle
analysis shows that transporting fly ash more than
50 miles from its origin dramatically increases its
environmental impacts, reducing its viability as a
cement replacement [15]. Fly ash and othercombustion co-products must be produced in
proximity to cement production sites to ensure theireconomic and environmental viability as asustainable cement substitutes.

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GEOMATE-Nagoya, Nov.13-15, 2013

Fig. 2industrial
byproducts,
properly
engineered
stabilized soils have the capacity to radicallytransform traditional concrete-based masonry
products at a global scale. Soil, the principal
component of stabilized earth materials, is aubiquitous, innocuous and almost unlimited
resource that promises the possibility of sustainablecradle-to-cradle life cycle performance. CMUs
typically contain between 10-16% OPC by weight.
In contrast, masonry blocks made with minimallyprocessed engineered soil blends are capable offulfillingthemechanicalanddurability
requirementsofcontemporary
structural
applications with as little as 5% OPC content andno additional SCMs, significantly reducing
environmental impacts without sacrificing strengthand durability. However, challenges must be met
before reduced-OPC masonry blocks composed ofengineered soil materials will be capable of meetingthe structural requirements of CMUs without
resorting to the use of conventional SCMs.

Cement consumption and fly ash
production by US regions in 2007 [11,16].
Fly ash production is estimated from coalconsumption data, assuming that 10 tonsof coal produce 1 ton of coal combustion
products (CCP) [16] and approximately
70% by weight of the total CCP
corresponds to fly ash [12]Earth masonry materials: opportunities andlimitations
Earth-based masonry building materials havebeen used extensively over the last half-century incivil engineering projects, but poor durability due
to the ingress of water [18] has limited their broader
acceptance as a replacement for conventional
concrete and masonry products. However, researchsuggests that key aspects of the earth materials suchas packing density, soil mineralogy, and type ofchemical binder can be manipulated to improveoverall durability, suggesting new uses andapplications.

Cost-effective fly ash availability around thecountry corresponds to the pattern of coal-fired
plant distribution from which it is derived, resulting
in uneven geographical availability, as portrayed in
Figure 2. For example, in the North, South East
Central, and West North Central regions, fly ash
production exceeds cement demand. In contrast,
other regions such as the Northeast and West Coast
US produce insufficient amounts of fly ash to
maintain pace with demand, limiting its use as a
viable sustainable cement replacement in theseareas. Even where fly ash is available in significant
quantities, as fly ash is transformed from a liability
to a co-product that can be sold at a profit, its
widespread utilization as an OPC substitute could
subsidize coal-fired electricity generation, which iscurrently responsible for 20% of the world’s total
GHG emissions [17].
Despite their growing popularity, theincorporation of conventional SCMs are at best apartial solution to reduce the environmental impactsof cement, and in some cases can even have theopposite effect. The toxicity of the many SCMs
discourages their widespread use, particularly inresidential applications and where concretes comein contact with moisture. Finally, transporting
SCMs long distances required by geographically
uneven supply limits their effectiveness as
sustainable cement alternatives.

Packing Density
The pore structure of the mixes is the major
factor controlling the durability of the material. The
size and the pore connectivity in the stabilized earthsystem are linked to the pressure applied, thepacking efficiency, and the moisture content. An
optimization of the gradation ensures a better
packing of the particles and therefore less interparticle space [19]. The results are mixtures withhigh density, and lower water and binder demand.
Therefore, these mixes will have higher resistanceto freeze-thaw damage.
Quantity and Type of Microfines
The amount of microfines (P200 material),
together with their mineralogy, is another importantfactor with direct impact on the durability of theearth masonry materials. Different soils exhibit
diverse mineralogies depending on their geographic
location, but a common attribute of soils suitable

EARTH MASONRY UNITS
In contrast to the incremental environmental
gains offered by conventional SCMs derived from723

GEOMATE-Nagoya, Nov.13-15, 2013of above factors. Research conducted to date has
established positive results designing sizeengineered mixtures of soil and aggregate byproduct stabilized with 6% Portland cement by
weight to produce a reduced-cement earth masonrybuilding units that meets the compressive strength,water absorption and wet-dry durability of the
ASTM C90 Standard Specification for Loadbearing
Concrete Masonry Units and ASTM D559 Standard
Specification for Wetting and Drying Compacted
Soil-Cement Mixtures. These results alreadyrepresent a 40% reduction in cement from a
conventional CMU.
While significant challenge remain to be solved,
packing density, microfine ratios, and careful
control over chemical binders have the capacity totransform traditional concrete-based masonry
products at a global scale.

for stabilization is the presence of clay minerals.
The presence of clay minerals plays an importantrole in the durability of the overall material due totheir water absorption demand. The effects ofquantity and type of P200 material on dry density
and water absorption of soil-cement are illustrated
in Figure 3. Increasing content of P200 materials
with significant content of clays reduces packing
efficiency (low dry density) causing an increase in
overall porosity and water absorption.

NANOTECHNOLOGY IN EARTH
MATERIALS

Fig. 3

The application of advances in nanotechnology
is another approach that offers great promise inaddressing the lack of durability in conventional
earth masonry products. It is instructive to look at
the evolution from regular to high-performance
concrete in this regard. Continuous refinement of
the particle size of the additives played an
important role in making the transition to highstrength concretes as illustrated in Figure 4. Similar
understanding of characteristics at the nano scale
can be applied to earth masonry to increase its
strength and durability.

Effect of varying P200 content andplasticity index (P.I.) on dry density andwater absorption of soil-cement materials.
Note: 1 pcf is equivalent to 10.018 Kg/m3

Different strategies based on the nature of theclay minerals can be adopted to mitigate the clay
mineral water demand. These strategies can beclassified as traditional and non-traditional
techniques. The use of cement, lime, fly ash, andbituminous products are considered traditional
techniques. Other less conventional methods are theuse of ionic stabilizer, lignosulfonates, salts, or
enzymes. The objective of these two types of
products is to impair the water demand of the clay
minerals. This is achieved through a variety ofmechanisms such as cation exchange, flocculation
and agglomeration, pozzolanic reaction, and basal
charge destabilization, among others. These
treatments have shown to be effective on thestabilization of pavement subgrades [20, 21]. The
type of clay mineral to be stabilized dictates thesuitability of each particular treatment.

Fig. 4 Particle Size vs. Specific Surface Area ofPrincipal Components and SCMs ofConcrete Materials [22]Chemical Binder

In earth materials, the specific surface area ofthe microfine fraction can be modified to influence
the void fraction and the capillarity suction ofstabilized earth materials [23, 24]. Currently, theaggregate industry offers a wide selection ofmineral products and by-products that can be used
to engineer the soil’s finer fraction from 150

Finally, the type and amount of chemical binder
is another factor with a high degree of influence on
the final performance of the product. Portland
cement is the most widely used binder on stabilized
earth materials. However, the cement content canbe drastically reduced with adequate optimization
724

GEOMATE-Nagoya, Nov.13-15, 2013

microns down to nanoscale. This enables
significant
enhancements
totheoverall
performance of the material and, more precisely,
the durability of the finished product.
Current scientific advances in nanomaterials
may further reduce the energy-intensive cement
content in earth masonry building blocks in the
future. As an example, the precipitation reaction of
the Portland cement binder can be improved by theaddition of nano-size materials, which is known as
nano-seeding effect. This approach has been proved
to be successful to accelerate the hydration reactionof Portland cement and its degree of hydration [25,26].
The characterization of amorphous hydrationgels responsible for the cohesiveness and strengthof cementitious materials is another promising area.
Thanks to the progress in analytical technique, thestructure of these gels can be characterized down tonanoscale, and correlations have been establishedwith mechanical performance at the microscale.
The structure of calcium silicate hydrated gel (C-SH) formed during the hydration of Portland cement
has been well studied [27, 28]. Significantly, recent
studies have indicated that calcium aluminumsilicate gels [29-30] and minerals [31] could
achieve even better performance than C-S-H.
It is hypothesized that smaller amount of thesegels would need to be nucleated to improve thedurability in earth masonry than in cement-basedmaterials. Earth masonry products are dense
systems characterized by aggregates with a highdegree of connectivity. It is therefor logical toassume that slight chemical reactions at theirsurface might potentiate the formation of new
amorphous phases. The new-formed phases willreinforce the connectivity between particles throughdirect chemical bond or through cohesivenessattractions (Van der Waals forces).
Thisconnectivity among aggregates is capable ofcreating a rigid skeleton inside the matrix of theearth specimens, contributing to the overall
improvement of the integrity and durability of thesystem.
Applying current advances in nanotechnology
offers great promise in generating a new class ofearth masonry materials capable of delivering
structural performance with significantly reduced
environmental impacts.

$96–140 billion market by 2014$14.3B (12% of total) of this will be spent
on masonry materials

The authors have co-founded a company
dedicated to the development of a new class ofdurable sustainable masonry building blocks called
Earth Masonry Units (EMUs) capable of offering
reliable structural performance with reduced OPC
binder content. To date the company has developed
an environmentally sustainable masonry building
block with recycled aggregates and 50% lesscement than conventional CMUs that meets
standard CMU specifications. The company has
constructed two demonstration houses utilizing
over 13,000 of these blocks, marketed under thename of E-CMUs. The company will continue tocapitalize on its existing product line of E-CMU
during the development of the transformational
zero-cement EMUs. This phased market entry
strategy will generate early revenue for thecompany that will defray development efforts forthe future range of radically sustainable masonrymaterials and products.

Fig. 5

Watershed Materials' demonstration house
under construction in the Bay Area of
California. Photo by David Easton

CONCLUSION
This paper presents a vision for developing a
structural masonry building block fabricated fromsoil materials. The development of the block could
eliminate the need for 15.2 million metric tons
(MMT) of cement and the release of 13.7 MMT of
CO2 into the atmosphere. Moreover, soil-based
masonry building block could represent a viablebusiness opportunity. Existing CMU manufacturing
practices are ripe for transformative change that aradical cement-free masonry block could provide.
Such an effort could make use of existing
manufacturing capability and distribution networks
on the way to developing the commercial potential

MASONRY MATERIALS MARKETPLACE
The green building industry currently represents
a US$49B market in the US and is the fastest
growing segment of the construction market. It ischaracterized by the following attributes:
 280% growth in 5 years, from $17B in2005 to $49B in 2010
 Green Building market is projected to be
725

GEOMATE-Nagoya, Nov.13-15, 2013

Leaching Tests”. ACI Materials Journal, 98(2): 126-136.
[11] U.S. Geological Survey, January 2012.
“Cement”, Mineral Commodity Summaries.
[12] American Coal Ash Association, 2010. “CoalCombustion Product (CCP) Production & Use
Survey Report”.
[13] World Steel Association, 2010. “Steel Industry
By-Products Fact Sheet.”[14] ACI Committee 234, 2006. “Guide for the Useof Silica Fume in Concrete”, ACI 234R-06.
[15] Babbitt C.W., Lindner A.S., 2008. “A life
cycle comparison of disposal and beneficial
use of coal combustion products in Florida;
Part 1: Methodology and inventory of material,
energy, and emissions. International Journal ofLife Cycle Assessment 13(3): 202-211.
[16] U.S. Energy Information Administration, 2008.
“Annual Coal Report”.
[17] Jos G.J. Olivier, Greet Janssens-Maenhout,
Jeroen A.H.W. Peters, 2012. “Trends in global
CO2emissions”,
PBL
Netherlands
Environmental Assessment Agency.
[18] Kerali,
A.G.
(2001).
“DurabilityofCompressed and Cement-stabilized Building
Blocks.” PhD Thesis, University of Warwick,
School of Engineering.
[19] Houben, H. and Guillaud, H., 1994 "Earth
Construction: A Comprehensive Guide,"Intermediate Technology Publications, London.
[20] Prusinski, J.R. and Bhattacharja, S., 1999,"Effectiveness of Portland Cement and Lime in
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of cement-free masonry building block. Thesearguments provide justification for the developmentof a structural masonry building block fabricatedfrom engineered soil materials.
ACKNOWLEDGEMENTS
The authors would like to thank David Eastonof Rammed Earth Works for his role in thedevelopment of the ideas in this paper.
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14/3, Zurich, Intl. Assoc. of Bridge andStructural Engineers, August 2004, 198-200.
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2009. “Emissions of Greenhouse Gases in the
United States 2008” retrieved Nov. 2012 fromhttp://www.eia.gov/oiaf/1605/ggrpt/carbon.html[3] Chaturvedi, S. and Ochsendorf, J., "Global
Environmental Impacts Due to Concrete andSteel," Structural Engineering International,
14/3, Zurich, Intl. Assoc. of Bridge andStructural Engineers, August 2004, 198-200.
[4] US Energy Information Administration (EIA),
2009. “Emissions of Greenhouse Gases in the
United States 2008” retrieved Nov. 2012 fromhttp://www.eia.gov/oiaf/1605/ggrpt/carbon.html[5] Marceau, M., Nisbet, M. and VanGeem, M.,
2007. "Life Cycle Inventory of Portland
CementConcrete".
PortlandCementAssociation.
[6] Worrell, E., Price, L, Martin, N, Hendriks, C. ,and Meida, L.., 2001. “Carbon Dioxide
Emissions from the Global Cement Industry”
Annual Review of Energy Environment, 26:
303–29.
[7] Glazer B., Graber C., Roose C., Syrett P.,
Youssef C., and Farrah K. 2011. “Fly Ash inConcrete”, Perkins and Will.
[8] Qijun Yu, S. Nagataki, Jinmei Lin, T. Saeki, M.
Hisada, 2005. “The leachability of heavymetals
in hardened flyash cement and cementsolidified fly ash”, Cement and Concrete
Research, 35(6): 1056–1063[9] R.H. Rankers, I. Hohberg, 1991. “Leaching
Tests for Concrete Containing Fly ash Evaluation and Mechanism”. Studies inEnvironmental Science, 48: 275–282[10] Min-Hong Zhang, Marcia C. Blanchette, and V.
Mohan Malhotra, 2001. “Leachability of Trace
Metal Elements from Fly Ash Concrete:
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Ceramic Society, 95 (3): 1128-1137.
[30] Hong S and Glasser FP., 2002 Alkali Sorption
by C-S-H and C-A-S-H gels. Part II: Role ofAlumina. Cement and Concrete Research, 32(7): 1101-1111.
[31] Jackson, M. D., Moon, J., Gotti, E., Taylor, R.,
Chae, S. R., Kunz, M., and Monteiro, P. J.,
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Tobermorite in Ancient Roman Seawater
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[26] Sanchez, F., and Sobolev, K., 2010.
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[27] Constantinides, G., and Ulm, F. J., 2007. The
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[28] Jennings, H. M., 2008. Refinements to colloid
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Third International Conference on Geotechnique, Construction Materials andEnvironment, Nagoya, Japan, Nov. 13-15, 2013, ISBN: 978-4-9905958-2-1 C3051

CONSTRUCTION AND MAINTENANCE OF EMBANKMENTS USINGHIGHLY ERODIBLE SOILS IN THE PILBARA, NORTH-WESTERN
AUSTRALIA
J.V. Smith1 and L.A. Sullivan 2
School of Civil, Environmental and Chemical Engineering, RMIT University, Australia; 2 Southern Cross
Geosciences, Australia

1

ABSTRACT
Many soils and sediments in the Pilbara region of north-western Australia are highly susceptible to erosion.
Large quantities of construction materials are required as iron ore mining and the extensive railway lines used totransport ore to port continue to be developed in the region. Simply avoiding the use of highly erodible materials
is often considered to be too high a cost where alternatives are scarce. Constructing embankments to survive thecyclonic wet season from material highly susceptible to erosion, is a major challenge. Highly erodible materials
encountered in the Pilbara include some bedrock shales, dispersive alluvial silts and sands and slaking clays andmudstones. Dispersive materials can erode internally by the formation of pipes or tunnels. Piping erosion canbe difficult to detect and can cause severe internal damage to embankments before being detected. Similarly,
slaking material can undergo compaction during wetting and drying cycles resulting in unexpectedly large
settlements. The effect of erosion, in general, is controlled by appropriate embankment design and construction,in particular compaction standards. Erosion controls include sacrificial batters, surface protection, encapsulationand stabilisation. For many mining projects achieving short-term construction deadlines is a high priority andadding erosion control measures after construction may be preferred. Predicting the time by which erosion
control needs to be installed or rehabilitated should be a part of the embankment design process. Material
selection has direct implications for the on-going asset management of embankment structures.
Keywords: Embankment, Erosion, Dispersion, Slaking, Pilbara

erosion control measures and maintenance after
construction is often preferred. Predicting the timeby which erosion control needs to be installed or
rehabilitated should be a part of the embankment
design process. Material selection has direct
implications for the on-going asset management ofembankment structures. Field observations andlaboratory tests show that the coastal and fluvial
sediments, dominated by the silty ‘Pindan’ sand,contain dispersive clays, which are prone to erosion
even where clay content and sodicity is low.
Conventional lime stabilisation would be impededby the alkaline condition of the soil. In contrast,
tests show gypsum can achieve 0% Exchangeable
Sodium Percentage (ESP) with applications less than
100 grams per ton of soil. The use of gypsum inembankment stabilisation is novel and requires
further investigation. In agricultural applications
gypsum provides a permanent control on dispersion
by the replacement of sodium and magnesium withcalcium and also has a temporary ‘electrolyte effectwhich may last from two to five years depending onwater movement. The ‘electrolyte effect’ istemporary which is not normally acceptable in civilengineering projects. However, the very low initial
ESP of these materials indicates permanent
stabilisation will be achieved by additions of even

INTRODUCTION
Many soils and sediments in the Pilbara region ofnorth-western Australia are highly susceptible toerosion. Large quantities of construction materials
are required as iron ore mining and the extensive
railway lines used to transport ore to port continue tobe developed in the region. Constructing
embankments to survive the cyclonic wet seasonfrom material highly susceptible to erosion, is amajor challenge. Simply avoiding the use of highly
erodible materials is often considered to be too higha cost as alternatives are scarce.
Highly erodible materials encountered in the Pilbara
include some bedrock shales, dispersive alluvial silts
and
sands
and
slakingclays
andmudstones. Dispersive materials can erodeinternally by the formation of pipes ortunnels. Piping erosion can be difficult to detect andcan cause severe damage to embankments before
being detected.
The effect of erosion can becontrolled by appropriate embankment design,
construction and maintenance. Erosion controls
include sacrificial batters, surface protection,
encapsulation and stabilisation.
For many mining projects achieving short-term
construction deadlines is a high priority and adding
728

GEOMATE-Nagoya, Nov.13-15, 2013minimal quantities of gypsum. The dynamic natureof mining infrastructure projects means that gaining
an additional life prior to rehabilitation works canrepresent a significant financial incentive.
The Pilbara region is undergoing rapid expansion ofrailways and other transport infrastructure to link theinland mines with ports to the north. The Economic
Regulation Authority [1], the independent economic
regulator for Western Australia, has factored in a
100 year life when estimating the asset value of forrailway earthworks, including some in the Pilbara.
Meanwhile, construction is occurring at record rates
with an emphasis on low cost construction. From anasset management viewpoint, there is inevitably a
trade-off between up-front construction costs andon-going maintenance costs which should be madeexplicit during the design process [2].
A detailed understanding of soil behaviour isfundamental to predicting the durability ofembankments constructed from soils and sedimentsof the Pilbara region.

the yellow coloured sands are sometimes called“wodgil”.
Investigations for the Broome Airport [6] described
the pindan sand as a collapsible silty-sand or clayeysand soil, typically red in colour. Pindan sand isusually considered deleterious, but may display aself-cementation property upon dry-back during
construction. The substantial strength gain upondrying, which is lost upon re-wetting, was thought tobe due to the bridging effect of clay in the pindan
sand. Previous work also attributed the effect to ironoxide, and further evidence from the laboratory
testing has suggested that the bridges also form fromFe-kaolinite which contains both iron andaluminium (hydr)oxides. Suction testing suggeststhat the strength gain of the pindan upon dry-back is
not just due to the cementing action of the bridges,
but is also due to increased suction from the changed
void geometry after the bridges have formed.
A review of approximately 50 laboratory tests ofpindan sand material from south of Port Hedland forthis study found that gradings were consistent but
Atterberg limits were variable with most samples
exceeding the recommended value (Table 1).

MATERIAL TYPESThe geology of the Pilbara region comprises bedrockof banded iron formation (BIF), consisting ofalternating layers of chert, siltstone, mudstone andhaematite in varying proportions, shale (referring
generally to interbedded fine sandstones, laminatedsiltstones and mudstones), dolomite, and thicksequences of basic and acidic igneous rocks.
According to a regional study, formations in the
Pilbara prone to erosion include the Weeli Wolli
Dolerite, Mt McRae Shale, Mt Sylvia Formation
shales, Bee Gorge Member shales, and various othergranites and basalts [3]. The implications of theerodible nature of these materials on borrow pit
stability has been investigated [4].
Materials overlying bedrock include alluvial gravels,
sands, silts and clays in fans, channels or on flood
plains. Colluvial and taluvial sands, gravels andboulders occur on slopes. In the northwest part ofWestern Australia, scree gravel slopes comprised ofmaterials useful for construction purposes can be
expected near outcrops of chert, quartzite andbanded ironstone, whereas, deposits of gravel on
slopes over dolerite, basalt and other dark igneousrock should be treated with caution because ofhighly active (montmorillonitic) clays which, theystate, almost always occur in the gravel fines oroverburden [5]. Weathering profiles developed on
bedrock and unconsolidated sediments can be clayrich or have siliceous or ferruginous duricrusts.
According to the Department of Main Roads ofWestern Australia [5], well graded sand with small
amounts of clay has been extensively used asbasecourse in the northwest of the State. The red
coloured sands are often referred to as “pindan” andEMBANKMENT CONSTRUCTION IN THE
PILBARAA review of the construction of railway
embankments in the Pilbara [3], describedembankments up to 45 m high constructed of
rockfill typically compacted in lifts of 750–1000 mm
thickness with about 10% by weight of water added
during placement. The design slopes of these highrockfill embankments are typically based on
precedent with angles of 1.5 horizontal to 1 vertical,
that is, 34o. A settlement value of 1% for theembankment height has been considered appropriate
and is allowed for by cambering and by increasing
the crest width so that an increased thickness ofballast can be applied to compensate for long-term
settlement [3].
When durable and non-durable (slaking) rocks inembankments are subjected to compressive contact
forces in the presence of water, the non-durable rockfragments are converted to soil that moves into thespace between the durable rock fragments causing
the settlement of the embankment [7]. Their study
calculated the amount of settlement experienced by a
mixture of non-durable shale with durable rockfragments subjected to embankment loads. The
amount of settlement varied with the percentage by
weight of the shale in the mixtures. The greatest
settlements were recorded in 100% shale.
It has been observed that shortfalls in suitableborrow material commonly occur in railway
construction projects in the Pilbara [3]. Thissituation is due to variations in overburden depth,
incursions of unsuitable materials and environmental
729

GEOMATE-Nagoya, Nov.13-15, 2013

constraints such as a need to keep borrow pits
shallow to allow drainage and prevent water
ponding.

often concealed until the collapse of pipes or tunnels
which have formed below the surface.
Figure 1A shows an embankment constructed fromgravelly soil with deep surface scouring. Bridges ofsoil are present over some of the scours indicatingthat erosion is, at least in part, a sub-surface process.
The scouring is concentrated in a band
approximately 1.5 m above the base of theembankment suggesting that either the material typeor the construction method at that level was thecause of the erosion.
Figure 1B shows an embankment constructed ofsilty sands with narrow surface scours. Local
erosion of the embankment toe by surface water has
revealed that open channels of piping erosion 250
mm across had formed within the embankment.
Embankment slope design should not only take into
account stability against slumping but also the rolethat the slope angle plays in controlling erosion.
Slopes of 1.5 horizontal to 1 vertical (34o) may be
too steep for embankments constructed of noncohesive silty sands as this angle can be expected to
be close to the friction angle of such sands.
The role of vegetation in embankment stabilisation
has been considered elsewhere [8] but will not be
considered here due to the climatic limitations onvegetation growth in the Pilbara region.

Table 1: Test results reviewed for this study(approximately 50) relative to published pindan
sand recommended interim criteria for use as a
sub-base or selected subgrade in a semi-arid orarid climate [6].

Test

Criteria

Proportionof samples
meeting
criteria

Sub-base DCP-CBR>40
59%
after dry-backSelect subgrade
DCP-CBR after>20
74%
dry-backSub-base
Compaction
95%
Not tested
density (Modified
MDD)
Select subgrade
Compaction
93%
Not tested
density (Modified
MDD)
Grading %passing
30-10098%
425µm sieve
Grading %passing
15? – 4092%
(1)75µm sieve
PI x %passing 75µm
> 150
87%
sieve
Liquid limit %<25
51%
Plasticity index %4-12
32%
MDD modified t/m3
>2.0
Not tested
OMC %
5-10
Not tested
Al2O3 + Fe2O3 %>8
Not tested
1. The lower limit is not known. Some of thebetter performing pindan sand had %passing
75µm sieve >25, and this may be a guide for subbase quality. However it is suggested that thecharacterisation of suitable pindan should bedone by strength testing or the use of PI x
%passing 75µm sieve rather than grading alone[6].

SACRIFICIAL BATTERS
A commonly applied approach to the use of highly
erodible materials is to add additional mass toembankments to delay the impact of erosion on thecritical part of the embankment. The additional
mass may be in the form of flatter batters or wider
crests. Ideally, this approach should incorporate an
estimated erosion rate and a predicted lifetime atwhich rehabilitation is expected to be required.
There should also be survey-based monitoring of theactual erosion losses so that predicted performancecan be validated. The occurrence of piping erosion,in particular, can occur without equivalent surface
scouring being visible.
Figure 2A shows an eroding embankment being
managed by the construction of a buttressembankment constructed to approximately half theheight of the existing embankment. The width of thebuttress is determined by the need to accommodate
construction equipment and greatly exceeds thewidth necessary to provide erosion control.
However, the same construction material is being
used and the buttress should be considered sacrificial
as it is expected to develop similar erosional
problems.

EROSION OF EMBANKMENTS
Appropriate material selection and compaction isintended to protect embankments from scouring
erosion from the wash of surface water during heavy
rainfall. Armouring around bridge abutments andculverts is typically installed to protect
embankments from sheet flow and flooding.
Erosional processes which can be more difficult tocontrol are those which occur by internal erosion offine particles by water infiltrating through theembankment. Evidence of this type of erosion is

SURFACE PROTECTION
Surface protection can be applied at the time of
construction or later as rehabilitation. Figure 2B
730

GEOMATE-Nagoya, Nov.13-15, 2013

A

shows the application of geotextile with a physicaland ultraviolet barrier of rock rip-rap. In this case,the surface protection is a rehabilitation measure notanticipated in the original project. Figure 3 shows
an example drawing of such surface protection
works.

A

B

B

C

D
Figure 1. Piping-type erosion on embankments in
the Pilbara. A) Concentration of piping
erosion at a horizon within the embankment
constructed of weathered granite. An A4
size folder shows the scale and highlights
the presence of soil bridges in the deeply
eroded part of the embankment. B) Finesurface runnels approximately 300 mm
apart overlie erosion pipes in an
embankment constructed of alluvial sands.
Figure 2. Post-construction rehabilitation of eroded
embankments. A) Extending the width ofthe earth embankment to control
embankment erosion. B) Placement ofgeotextile and rip-rap. C) Excess blast spoil
dozed against embankment face to control
embankment erosion. D) Fines appear toreadily migrate through the improvised riprap shown in photograph C.

Figure 2C shows surface protection which has been
applied in a more ad hoc manner by dozing of
blasting spoil against eroding batters. Figure 2D
shows that in the absence of geotextile or where theapplied materials are uniformly coarse, fine soil inthe embankment readily washes through this type ofprotection.

731

GEOMATE-Nagoya, Nov.13-15, 2013crusting and erosion. These findings indicate that thesoils are likely to be prone to dispersive erosion even
if their clay content and sodicity are low.
Stabilisation of embankment soils with mineral
additives may provide significant improvements inerosion susceptibility.
Conventional lime
stabilisation can be impeded by the alkalinecondition of the soil which inhibit the release of
calcium from the lime. Alternatively, gypsum
releases calcium more readily in alkaline conditions.
Gypsum is typically only used to control dispersionof soil in agricultural practice due to the anticipatedshort-term effect [12]-[15], however, the use of
gypsum in embankment construction has been
proposed [16].
Tests at Southern Cross Geosciences on dispersive
soils from the Pilbara found that an Exchangeable
Sodium Percentage of near 0% could be achievablewith extremely low applications of less than 100
grams of gypsum per ton of soil. The use of gypsum
in embankment stabilisation is novel and requires
further investigation. In agricultural applications
gypsum provides a permanent control on clay
dispersion by the gradual exchange on the clay of
the two ‘dispersion causing’ cations sodium andmagnesium, with the more stable calcium cation
derived from gypsum dissolution. In addition,
gypsum provides a fast acting, but temporary,control on dispersion via the ‘electrolyte effect’.
The electrolyte effect is due to the flocculating effectof the higher salinity in water caused by gypsum
dissolution and may last from two to five years
depending on water movement. The electrolyte
effect, being temporary, is not normally acceptablein civil engineering projects, but this effect serves toprovide effective control during the period of cationexchange that leads to permanent dispersion control.
Of course, the dynamic nature of mining
infrastructure projects means that gaining even an
additional 2-5 years of life prior to rehabilitation
works can represent a very significant financial
incentive.

Figure 3. Example detail of recommended geotextile
and rip rap protection on erodible
embankments.
ENCAPSULATION
In a review of engineering geology for railway
construction in the Pilbara [3], it was recommended
that weathered shale or dolerite bedrock which canbe prone to erosion should be encapsulated by 2 mof non-erodible soil. Encapsulation introduces thepotential problem of differential settlement acrossembankments and requires significant material
investigations and trials to be conducted.
STABILISATION
Stabilisation of low plasticity soils with agents suchas lime and cement is well documented [9]. Soil
stabilisation has been used in the Pilbara on various
projects. For example, the stabilisation of highly
reactive clay soil known as gilgai soil for the
Karratha to Tom Price road [10]. In that study,
hydrated lime and a combination of lime and cement
were found to have a significant effect inimprovement of California Bearing Ratio,
unconfined compressive strength and shrink andswell characteristics of the reactive subgrade
material.
A case of study ground improvement wasundertaken at the stockyard berms of a large iron ore
handling facility located in the Pilbara region [11].
The stabilisation involved addition of 3% cement tothe berm materials carried out in situ using a Bomag
stabiliser machine. Plate load tests were undertaken
to assess degree of ground improvement of theclayey gravels. Cement not only provides physicalstrengthening of a soil but also contributes calcium
to the chemical balance in the embankment which
can exchange for sodium on clay and thereby
influence erodibility of dispersive soils. The role ofcement as a chemical stabiliser requires further
investigation.
Tests conducted at the Southern Cross GeoSciencelaboratory have shown that some of the silty pindan
sands of the Pilbara contain dispersive clays. The
tests indicated that this soil must be managed
carefully to avoid structural problems such as

CONCLUSIONSThe use of highly erodible material to constructembankments is generally discouraged so thatembankments are of high quality and longevity.
However, the demand for short construction times
means that the most abundant materials at hand willoften be used in construction. Consequently, someform of erosion control will be required during orsoon after construction. Erosion control may be in
the form of surface protection, encapsulation or
stabilisation. Surface protection can be conducted aspart of the original construction or as later
rehabilitation. Encapsulation requires good quality
material to be available or stabilisation of material
for the outer part of embankments. Stabilisation has
732

GEOMATE-Nagoya, Nov.13-15, 2013

been applied on some previous projects in the region
and further investigations are required.

pressures and native vegetation in rail trackstabilisation (Technical report)”. Transport
Engineering in Australia. 12.1, 2009, p25.
[9] Szymkiewicz, F, Guimond-Barrett, A, Le Kouby,
A, Reiffsteck, P & Fanelli S “Strength and Agingof Cement Treated Low Plastic Soils” Int. J. of
GEOMATE, Vol. 4, No. 1, 2013, pp. 490-494.
[10] Cocks, G, Clayton, R, Hu, Y Han, G, &Chakrabarti, S “Treatment of Reactive Soil
Subgrade for Pavement Construction inWestern Australia” 24th ARRB Conference –Building on 50 years of road and transport
research, Melbourne, Australia, 2010.
[11] Chakrabarti, S, Tabucanon, J, “Improvement ofiron ore stockyard berms using cementitious
stabilization” Australian Geomechanics 45,
2010, 53-64.
[12] Sullivan, LA, & Fosbery, G, “Gypsum
improves soil stability” Farmnote 32/85
Western Australian Department of Agriculture,
1984.
[13] Moore, G, (Editor) “Soil Guide: A Handbook
for Understanding and Managing Agricultural
Soils” Agriculture Western Australia Bull.
4343, 2001.
[14] Davies S, & Lacey, A, Identifying Dispersive
Soils, Farmnote 386. Western Australian
Department of Agriculture and Food, 2009.
[15] Davies S, & Lacey, A, “Managing Dispersive
Soils” Farmnote 387. Western Australian
Department of Agriculture and Food, 2010.
[16] Biggs AJW, & Mahony KM, “Is Soil Science
Relevant To Road Infrastructure?” Conserving
Soil and Water for Society: Sharing Solutions
13th International Soil Conservation
Organisation Conference – Brisbane, July
2004.

Summary of erosion controls for
Table 1:embankment construction
Control
Sacrificial flanks
Encapsulation
Stabilisation
Surface Protection

Duringconstruction
Yes
Yes
Yes
Yes

Rehabilitation
Possible
Possible
Possible
Yes

Given the need for many projects to achieve shortterm deadlines for construction, it is likely that asignificant amount of highly erodible materials willcontinue to be used in embankment construction.
Erosion control and/or embankment rehabilitation
will continue to be an integral part of infrastructure
management in the Pilbara region.
ACKNOWLEDGEMENTS
Discussions with colleagues at Coffey geotechnicalconsultants were much appreciated.
REFERENCES[1] www.erawa.com.au/ accessed December 2011.
[2] Sloan, A, Garland, R, & Lloyd, J, “Towards anasset management system for railway
embankments and cuttings”, Proceedings of theRailway Infrastructure Conference, Railway
Engineering, London, Engineering Technics
Press. 2000, pp. 9.
[3] Baynes, FJ, Fookes, PG, & Kennedy, JF, “The
total engineering geology approach applied torailways in the Pilbara” Western Australia Bull
Eng Geol Environ 64, 2005, 67–94.
[4] Smith, JV & Sullivan, LA, “Long-Term
Environmental Stability of Borrow Pits in Highly
Erodible Soils in the Pilbara” International
Conference on Ground Improvement and Ground
Control, Wollonging, NSW. 2012, pp. 1729-1734.
[5] Butkus, F, “Gravel Search Manual” Pavements
Engineering Report No. 2001-6M, Main Roads
Western Australia, 2003, pp. 104.
[6] Emery, S.J, Masterson, S, & Caplehorn, MW,“Sand-clay Pindan material in pavements as astructural layer” In Proceedings 21st AustralianRoad Research Board Conference, Cairns,
2003, 15pp.
[7] Vallejo LE, & Pappas D, Effect of Nondurable
Material on Settlement of Embankments.
Transportation Research Record, 2170, 2010,
84-89.
[8] Indraratna, B, Rujikiatkamjorn, C, Vinod,
J, Khabbaz, H, “A review of ballast
characteristics, geosynthetics, confining733

Authors Index Volume 3(2)A. Baouch

688

K. Hamdaoui

688

A. Beck

642

K.E. Chua

631

A. H. M. Zahirul Alam

664

Kazuhiro Oda

592

A. K. Alzo’ubi

658

Kazuhito Murakami

711

Achmad Fauzi

637

Keiko Okada

604

Ahmad Safuan A Rashid

625

L.A. Sullivan

728

Aniza Ibrahim

575

Loni Allafouza Oumar

717

Annan Zhou

652

M. I. Ibrahimy

664, 685

Atefeh Asoudeh

608

Mansour Al humimidi

717

Behnam Fatahi

700

Masyhur Irsyam

637

C.Y. Tan

631

Michio Gomyo

711

D. Gallagher

642

Mohamed M. Shahin

667

Erwin Oh

608

Mosleh Al Shamrani

717

F. Anwar

685

Muawia Dafalla

717

Fengzhi DAI

604

Muhammad Addifa Yulman

637

Greg Hackney

580

Muhammad Mukhlisin

575

H.B. Ng

642

Mutaz, E.

717

H.M. Yim

631

Nozomu Hirose

604

Ha H. Bui

694

Othman Jaafar

575

Hadi Khabbaz

673

Peijun Guo

619

Hadi Khabbaz

700

Reza Afshar-mazandaran

673

Harry Poulos

580

S. Aissaoui

688

Helen Fairweather

586

S. M. A. Motakabber

664, 685

Hidenori Takada

706

S.H. Chew

631

Ivan Sandi Darma

646

S.Y. Kee

631

J.V. Smith

728

Saki Agatsuma

711

Ja Naw

631

Samuel J. Verghese

694John Yeaman

586

Shohei Ikeda

646

Jonathan A Black

625

Shuhei Takegawa

592Jose F. Muñoz

721

Stephen Buttling

679

Joseph Dahmen

721

Surendra Bahadur Tamrakar

613

Junichi KOSEKI

598

T.K. Khoo

631

Authors Index Volume 3(2)T.Y. Yap

631

Takafumi Sugiyama

646

Takeshi Kodaka

706

Thayalan Nall

580

Tomoyoshi Nishmura

598

Toshiyuki Mitachi

613

Usama Juniansyah Fauzi

637

Yang-Ping Yao

652

Ying Cui

706

Yoshimasa Amano

711

Z. Benadla

688

ISBN978-4-9905-9580-1
C3051 \5000E
9784990595821
定価 （本体5０００＋税）
1923051050000

The “International Journal of
GEOMATE” is a Scientific
Journal the GEOMATEInternational Society thatencompasses a broad area inGeotechnique, Construction
Materials and Environment.
The key objective of thisjournal is to promoteinterdisciplinary research fromvarious regions of the globe.
The editorial board of thejournal is comprised ofextensively qualified
researchers, academicians,
scientists from Japan andother countries of the world.
It is peer-reviewed journal thatis published quarterly. All
articles published in thisjournal are available on line.
For more details, please visit:
http://www.gi-j.com/

Fourth International Conference on
Geotechnique, Construction Materials & Environment
University of Southern Queensland, Springfield Campus, Brisbane, Australia