SEE 2020, KYOTO, JAPANSTRUCTURE, ENGINEERING AND ENVIRONMENTiPROCEEDINGS OF SIXTH INTERNAONAL CONFERENCE – SEE 2020
STRUCTURE, ENGINEERING & ENVIRONMENT KYOTO, JAPAN 18-20 NOVEMBER, 2020

Structure, Engineeringand Environment
Edited byProf. Zakaria Hossain
Graduate School of Bioresources
Mie University, JapanTHE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2020 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: society@geomate.org
http://www.geomate.org/

ISBN Number: 978-4-909106056 C3051

iii

Sixth International Conference on Structure, Engineering & Environment,
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

Table of Contents

ID

Prefaceviii

Organizationix

Technical Papers

1

Structure

26153

DEFECT DETECTION ON ASPHALT PAVEMENT BY DEEP LEARNING
Jonpaul Nnamdi Opara, Aunt Bo Bo Thein, Shota Izumi, Hideaki Yasuhara and Pang-Jo Chun

3

6167

NONLINEAR SECTIONAL ANALYSIS OF STRUCTURAL CONCRETE MEMBERS OF ARBITRARY SHAPE
UNDER CYCLIC LOADING
Ahmed Alkhairo, Nazar Oukaili, and Riadh Al-Mahaidi

9

6228

QUANTITATIVE EVALIATION OF BUCKLING STRENGTH OF DAMAGED PLATES
Hani Doummar and Yoshitaka Suetake

17

6267

PERFORMANCE LEVEL PREDICTION OF STRUCTURE BUILDING USING LOGSIGMOID METHODS
Muhammad Gala Garcya, Reni Suryanita, Zulfikar Djauhari and Harnedi Maizir

23

6287

PERFORMANCE ANALYSIS OF LIGHTWEIGHT CONCRETE BRICKS DUE TOEXPOSURE HIGH TEMPERATURE USING EXPERIMENTAL STUDY
Reni Suryanita, Yohannes Firzal, Harnedi Maizir, Imam Mustafa, Mohd Fadzil Bin Arshad

28

ID
6125

Engineering
EVALUATION OF RECOVERY OF DEBRIS FLOW CONTROL BY CHECK DAMS AFTER REMOVINGDEBRIS BASED ON NUMERICAL SIMULATION
Naomasa Honda

34

35

6107

EFFECT OF TEMPERATURES MALTODEXTRIN ON PHYSICAL PROPERTIES OF DATE PALM POWDERBY SPRAY DRYING
Wattana Wirivutthikorn

43

6126

PARTIAL REPLACEMENNT OF CEMENT WITH FLY ASH AND FGD GYPSUM TO DEVELOP STRENGTH
OF SUBBASE
Pisut Rodvinij and Chotikan Ratchakrom

49

6130

THE VARIATIONAL ITERATION METHOD FOR SOLVING VOLTERRA INTEGRAL EQUATION OF THE
SECOND KIND USING MAPLE
Dalal Adnan Maturi

55

6171

EFFECT OF DEGREE OF SATURATION ON PARTICLE BREAKAGE OF RECYCLED CONCRETE
AGGREGATE UNDER CYCLIC LOADING
Syed Kamran Hussain Shah, Junaid Qayyum Kayani, Taro Uchimura and Ken Kawamoto

60

6184

INVESTIGATION ON RUPTURE OF GROUND ANCHORS DUE TO LANDSLIDE FLUCTUATIONS
Yoshihiro Tsunekawa, Toshinori Sakai

66

iv

6193

EXAMINATION OF APPLICABILITY OF DYNAMIC LOAD TEST AND HILEY FORMULA TO SMALL
DIAMETER STEEL PILE
Takaaki Ariki

72

6208

ASSESSING FACTORS INFLUENCING ROUTE CHOICE: A CASE STUDY OF TERPEKA TOLL ROAD,
INDONESIA
Aleksander Purba, Darmawan Adi Susanto, Rosalia Dwi Werena and Tiara

78

6214

DEVELOPING NUMERICAL MODEL FOR LIQUEFACTIONINDUCED LATERAL DEFORMATION USING
SPH
Erly Bahsan, Budi Susilo Soepandji, Dwinanti Rika Marthanty and Widjojo Adi Prakoso

84

6221

STUDY ON ADSORPTION OF HEAVY METALS BY RICE HUSK AND EXTRACTION OF HEAVYMETALS ADSORBED IN RICE HUSK
Ayane Yanaka, Keiichiro Shibata, Naomichi Matsumoto and Hidenori Yoshida

89

6222

STUDY ON REMOVAL OF CESIUM FROM CONTAMINATED SOIL BY ELECTROPHORESIS USINGPOTASSIUM ACETATE AS ELECTROLYTE
Ayane Yanaka, Keiichiro Shibata, Naomichi Matsumoto and Hidenori Yoshida

94

6227

EFFECT OF WATER HYACINTH FIBER ON STRENGTH AND DURABILITY OF ADOBE BRICKS
Chotikan Ratchakrom, Pisut Rodvinij

99

6234

A NEW TYPE OF ACTUATOR FOR APPEARANCE INSPECTION OF IRON STRUCTURE
Hiroyuki Yaguchi

105

6236

VIBRATION ANALYSIS OF A GASOLINE-ENGINE CAR DRIVING UPON THREE TYPES OF ROADSSuphattharachai Chomphan

112

6259

STUDY ON RIVER PATROL USING IMAGES CAPTURED BY DRONES AND MACHINELEARNING
Ryo Yahara, Koki Sakita, Satoshi Nishiyama, Tomohiro Shimono, Michinari Fujiki and
Tatsuya Chigira

118

6262

VERIFY THE PREDICTION OF SLOPE FAILURE BY SOIL CREEP WITH LABORATORY EXPERIMENTS
Makoto Fukuhara, Taro Uchimura and Shanging Tao

124

ARCHITECTURAL PHOTOGRAMMETRY: A LOW-COST IMAGE ACQUISITION METHOD IN
DOCUMENTING BUILT ENVIRONMENT
Yohannes Firzail

130

EVALUATION LIQUEFACTION AND LATERAL FLOW ON THE PALU MW 7.5 EARTHQUAKE 2018
USING STANDARD PENETRATION TEST AT LOLU VILLAGE SITE
Dandung Sri Harninto and Widjoyo A. Prakoso

134

6291

STRESS ANALYSIS IN AUXETIC TWO-DIMENSION MATERIAL WITH MODIFIED PEANUT PATTERN
Boonthum Wongchai

143

6298

STUDY ON THE BEHAVIOR OF SANDBAR IN A RIVER CHANNEL AT THE BABAMEGAWA RIVER
Junya Taniguchi, Kazuya Watanabe, Noritoshi Saito and Naoya Fujisawa

149

6305

PASSIVE BASE ISOLATOR FOR VERTICAL DIRECTION USING A POST-BUCKLED SHAPE MEMORYALLOY BEAM AND ITS DYNAMIC PROPERTY
Atsushi Urakawa , Takumi Sasaki and Hiroki Cho

155

6313

MRT JAKARTA: A SHORT EVALUATION AFTER 1 YEAR OF OPERATION
Aleksander Purba

161

6314

LABORATORY OBSERVATION ON DESICCATION CRACKING OF THIN CLAY LAYER
Fauzilah Ismail, Ahmad Kamil Arshad, Nadiah Shaari, Nursafiah Khalid, Muhammad Haniff
Asmuni, Muhammad Haziq Shuib and Ekarizan Shaffie

167

6263

6269

v

6330

STATIC PILE LOAD TESTS: CONTRIBUTION OF THE MEASUREMENT OF STRAINS BY OPTICAL FIBER
Fabien Szymkiewicz, Carlos Minatchy and Philippe Reiffsteck

172

ID

Environment

179

6131

SPATIAL DISTRIBUTIONS IN GROUNDWATER DISCHARGE ON VARIOUS TIDAL FLATS IN A SMALL ANDSTEEP ISLAND, WESTERN JAPAN
Shingo Nozaki ,Shin-ichi Onodera, Yusuke Tomozawa, Mitsuyo Saito

180

6108

ASSESSMENT ON MICROPLASTICS CONTAMINATION IN FRESHWATER FISH: A CASE STUDY OF THEUBOLRATANA RESERVOIR, THAILAND
Pattira Kasamesiri, Charumas Meksumpun, Shettapong Meksumpun and Chakhrit Ruengsorn

186

CHARACTERISTICS OF CULTURAL LANDSCAPE AS STREETSCAPE IN KUDOYAMA TOWN
Tomoko Miyagawa, Rena Ozaki, Kyota Matsuyama, Shinpei Yamamoto and Masahiro Takasago

192

6135

UTILIZATION OF ACTIVATED CARBON FROM PALM KERNEL SHELLS AS THE BIOADSORBENT OF
LEAD WASTE
Muhammad Faisal, Asri Gani, Zahrul Fuadi

198

6150

EFFECT OF BIOAUGMENTATION AND PHYTOREMEDIATION ON DEGRADATION OF PARAQUAT IN
CONTAMINATED SOIL
Mullika Teerakun, Pensri Plangklang, Koson Rueangsan Piyachat Wiriyaampaiwong and Piyawadee
Sarapirom

204

6154

CHARACTERISTIC OF LIQUID SMOKE PRODUCED FROM SLOW PYROLYSIS OF CACAO POD SHELLS(THEOBROMA CACAO L)
Hera Desvita, Muhammad. Faisal, Mahidin, and Suhendrayatna

210

6155

A NUMERICAL SIMULATION OF DISASTER WASTE DISPOSAL IN WAKAYAMA CITY BY USING
DHT MODEL
Soichiro ASAI, Tatsuya AKIYAMA, Hiroto TANOUCHI, and Nobuyuki EGUSA

216

6160

ENERGY POLICY, CORPORATE STRATEGY, AND CONSUMER BEHAVIOUR IN JAPAN
Hisatoshi Tanaka, Atsushi Nakashima and Nabil Maghrebi

222

6166

IMPACT OF CITRUS AGRICULTURE ON THE QUALITY OF WATER RESOURCE IN A SMALLSTEEP ISLAND, SETO INLAND SEA, JAPANSharon Bih Kimbi , Shinjo Nozaki, Shin-ichi Onodera, Yusuke Tomozawa, Kungyang Wang,
Anna Rusydi, Mitsuyo Saito Eungpinichpong

226

6199

ECOSYSTEM-LEVEL WET TEST OF CAFETERIA DRAINAGE USING MICROCOSM SYSTEM
Kazuhito Murakami, Kakeru Ruike, Tomomi Tsuchiya,, Kazuhi Obata, Ryuhei Inamori
and Yuhei Inamori

234

6200

RIVER ENVIRONMENT EVALUATION BY WATER QUALITY, ATTACHED DIATOM AND
MACROBENTHOS IN BOSO PENINSULA, JAPANKazuhito Murakami, Haruna Niida,Tsuyoshi Doyama and Kenji Watanabe

240

6201

IDENTIFYING IMPACTS OF DENSITY-DRIVEN FLUCTUATION TO GROUNDWATER CAUSEDBY SALTWATER INTRUSION
Theara Seng, Junichiro Takeuchi and Masayuki Fujihara

246

6134

6209

6211

6215

CHARACTERIZATION OF GROUNDWATER POLLUTION SOURCES BY KRIGING BASED LINKEDSIMULATION OPTIMIZATION
Anirban Chakraborty and Om Prakash
THE KUMAMOTO EARTHQUAKE’S CREATIVE RECONSTRUCTION EFFORT LED BY A DIVERSE RANGEOF ORGANIZATIONS
Reiko Machida, Eri Otsu , Hiroko Shima, Hitomi YaGI ,Katusunori Mochizuki Junya Machida,Hijiri
Shimojima and Naomasa Honda
ASSESSMENT OF HABITAT SUITABILITY AREA OF ENDANGERED SPECIES USING MAXENT BY LANDUSE CHANGE IN FUKUSHIMA PREFECTURE, JAPAN
Hideyuki Ito, Hiromu Tomita, Makoto Ooba and Takahiro Fujii

vi

252

258

264

6241

HEAVY METALS EXPOSURE AND RISK ASSESSMENT OF COOKED RICE FROM THE FIELD NEAR THE
OLD DUMPSITE IN INDONESIA
Fajri Mulya Iresha, Suphia Rahmawati, Dhandhun Wacano, Kasam, Ratna Kartika Sari, Minoru
Yoneda270

6251

DEVELOPMENT OF AN INTERACTIVE AND VISUALIZATION SYSTEM FOR DETERMINING
CLIMATE RISK
Makoto Ooba, Takuya Togawa, Ronald Canero Estoque, Shogo Nakamura, Takashi Tsuji,
Akira Yoshioka and Yasuaki Hijioka

276

6255

MEASURING TOD READINESS OF THE BANDAR LAMPUNG CITY
Aleksander Purba, Aken Andha Runiawan, Rahayu Sulistyorini, Shahnaz Nabila Fuady, Lusmeilia
Afriani, Dikpride Despa, Ratna Widyawati, and Rosalia Dwi Werena

280

6264

SPATIAL VARIATIONS OF WATER QUALITY IN ACIDIC RIVER BASINS OF NORTHEAST JAPANTakeshi Saito and Naoki Watanabe

287

6268

6271

OIL/WATER SEPARATION TECHNIQUES USING HYDROPHOBIZED/OLEOPHILIZED GRAINS: A REVIEWOF RECENT STUDIES
Akihiro Matsuno, Zafar Muhammad Junaid, Takeshi Saito, Huyen Thi Thanh Dang, Pham Thanh
Huyen, Tran Thi Viet Nga and Ken Kawamoto
HEAVY METAL CHARACTERISTICS OF WASTEWATER FROM BATIK INDUSTRY IN YOGYAKARTA
AREA, INDONESIA
Any Juliani, Suphia Rahmawati and Minoru Yoneda

292

298

6282

CONSUMER REVIEW WEBSITE-BASED APPLICATION TO DETERMINE POPULARITY INDEXAND SPATIAL DISTRIBUTION OF RESTAURANTS IN BANDUNG
Dewi Susiloningtyas, Syarifah Salma A’idah, Febiana Nur Azizah, and Iqbal Putut Ash Shidiq

304

6296

COMPARATIVE STUDY ON KOREA AND JAPAN URBAN PARKS CONCERNING THE DEVELOPMENTPOLITICS AND THE TRANSITION OF SYSTEM
Shinya Tsukada, Sangbok Yoon, Yeongha Kim, Tetsuo Morita and Hiroshi Sugita

311

6311
6141
6165

6245

6266
6306

6334

THERMAL ENERGY EVALUATION OF THE INCINERATOR WASTE
Kantayut Trebooniti
RESEARCH ON THE DURABILITY OF RECYCLED AGGREGATE CONCRETE INCORPORATING HIGH
VOLUMES OF BLAST FURNACE SLAG
Chung-Hao Wu and Shu-Ken Lin
NITROGEN FLOW ANALYSIS FROM DIFFERENT LAND-USE OF THE CHI RIVER BASIN(MAHA SARAKHAM REGION, THAILAND)
Nida Chaimoon
EVALUATION OF ENVIRONMENTAL ENGINEERING EDUCATION PROGRAM FOR STUDENTS FROM
SOUTHEAST ASIA TO HIGH SCHOOL IN JAPANKenji Arai, Tetsuo Morita and Toshikazu Nishio
CAUSAL RELATIONSHIP MODEL OF PROBLEMS IN PUBLIC SECTOR PROCUREMENT
Tanayut Chaitongrat, Surapong Liwthaisong, Preenithi Aksorn, Wuttipong Kusonkhum,
Narong Leungbootnak, and Korb Srinavin
MOLECULAR IDENTIFICATION OF A CARBONIC ANHYDRASE-PRODUCING BACTERIUM ISOLATEDFROM A NATTO IN INDONESIA TO BE USED IN BIOCONCRETE DEVELOPMENT
Tomone Ikai, Masahide Uomi, Diana Waturangi, Hiroshi Yonemitsu, Masa-aki Yoshida, Januarti J.
Ekaputri, Davin H. E. Setiamarga
INFLUENCE OF RICE HUSK ASH WASTE ON COMPACTABILITY OF SOIL
Sayful Kabir Khan, Najmun Nahar, Zakaria Hossain , Noma Tamaki

vii

317
321
326

332

339
346

353

Sixth International Conference on Structure, Engineering & Environment,
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

PrefaceOn behalf of the SEE 2020 Organizing Committee, it is our great pleasure to welcome you to the Sixth
International Conference on Structure, Engineering & Environment, held at Kyoto Research Park, Kyoto,
Japan organized in conjunction with Mie University Research Center for Environmental Load
Reduction, The GEOMATE International Society, Useful Plant Spread Society, Glorious International, AOIEngineering, HOJUN, JCK, CosmoWinds and Beppu Construction, Japan.
The conference covers three major themes with many specific themes including:
Advances in Building Structure
Advances in Infrastructures
Advances in Civil Engineering
Advances in Structural Engineering
Advances in Geological Engineering
Advances in Geometics Engineering
Advances in Chemical Engineering
Advances in Environmental Engineering
Advances in Geotechnical Engineering
Advances in Architectural Engineering
Advances in Industrial Engineering
Advances in Manufacturing Engineering
Advances in Materials Engineering

Advances in Mechanical Engineering
Advances in Petroleum Engineering
Advances in Process Engineering
Advances in Environmental Technology
Advances in Geophysics
Advances in Hydrology
Advances in Recycle Solid Wastes
Advances in Use of reclaimed Waters
Advances in Water Distribution
Advances in Water Treatment
Advances in Irrigation and Drainage
Advances in Farm Structures

Due to COVID-19, this year we have received less submissions from different countries all over the world.
The technical papers were selected from the vast number of contributions submitted after a review of theabstracts. The final papers in the proceedings have been peer reviewed rigorously and revised asnecessary by the authors. It relies on the solid 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 their contribution to SEE 2020. We hope you enjoy theconference o n s i t e a n d Z O O M o n l i n e and find this experience inspiring and helpful in yourprofessional field. We look forward to seeing you at our upcoming conference next year.
Best regards,
Prof. Dr. Zakaria Hossain, Chairmanviii

Sixth International Conference on Structure, Engineering & Environment,
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

Organization
Scientific Committees:
Honorary Chairman: Dr. Sohji Inoue, E/Prof. Mie University, Japan
Conference Chairman: Dr. Zakaria Hossain, Prof. Mie University, Japan
Conference Organizing Committee:
Dr. Zakaria Hossain, Prof. Mie University, Japan (Chair)Dr. Satoshi Kaneco, Prof., Mie University, Japan (Co-Chair)Dr. Sohji Inoue, E/Prof. Mie University, Japan (Co-Chair) Dr.
Toshinori Sakai, Prof. Mie University, Japan (Co-Chair) Dr.
Takamitsu Kajisa, Prof. Mie University, Japan (Co-Chair)Dr. Masaaki Kondo, A/Prof. Mie University, Japan (Co-Chair)
National & International Advisory Committee:
Dr. Fumio Tatsuoka, Prof., Tokyo University of Science, Japan
Dr. Junichiro Takeuchi, Prof., Kyoto University, Japan
Dr. Kingshuk Roy, Prof., Nihon University, Japan
Dr. Nakib Dan Khan, A/Prof. Mie University, Japan
Dr. Sai Vanapalli, Prof., University of Ottawa, Canada
Dr. Musharraf Zaman, Prof. Univ. of Oklahama, USA
Dr. Rafiqul Tarefder, Prof. University of New Mexico, USA
Dr. M. Bouassida, Prof., National Sch. of Engg. of Tunis Dr.
L.R. Austriaco, Prof., Angles Univ. Found., Philippines Dr.
A.S.M. Abdul Awal, Prof., Univ. Technology Malaysia
Dr. M. Ibn Ibrahimy, Prof., Int. Islamic Univ., Malaysia
Dr. Mohammad Shariful Islam, Prof., BUET, Bangladesh.
Dr. Bujang B.K. Huat, Prof., Univ. Putra Malaysia
Dr. Nemy Banthia, Prof., UBC, Canada
Dr. Ian Jefferson, Prof., Univ. of Birmingham, UK
Dr. John Bolander, Prof., Univ. of California, USA
Dr. Shamsul Chowdhury, Prof., Roosevelt Univ., USA
Dr. Isabel Pinto, Prof., University of Coimbra, Portugal
Dr. Mark Jaksa, Prof., University of Adelaide, Australia
Dr. Jim Shiau, A/Prof., USQ, Australia
Dr. Hj. Ramli Bin Hj. Nazir, A/Prof., UTM, Malaysia
Dr. H.M. Shahin, Prof., Islamic University of Technology, Bangladesh
Dr. Md. Ariful Islam, A/Prof. Dhaka University, Bangladesh
Dr. Md. Nurul Amin, Prof. Dhaka University, Bangladesh
Dr. D.K. Chauhan, Prof. Noida International Univ., India
Dr. Chan Chee-Ming, A/Prof. Universiti Tun Hussein Onn Malaysia
Dr. Ahmed H. A. Dabwan, A/Prof. TATI Univ. College, MalaysiaixInternational Technical Program Committee:
Prof. Adolf Heinrich Horn, Geological Institute - Federa University of Minas Gerais, Brazil
Prof. Bang-Fuh Chen, National Sun Yat-sen University, Taiwan
Prof. Bindeshwar Singh, Kamla Nehru Institute of Technology, India
Prof. Catherine Mulligan, Concordia Institute of Water, Energy and Sustainable Systems, Canada
Prof. Chi-Min Liu Chienkuo Technology University, Taiwan
Prof. Daffalla Rabih, Kenana Sugar Company, Sudan
Prof. Essaid Bilal, Ecole Nationale Superieure Des Mines De Saint Etienne, France
Prof. Hakan Caliskan, Usak University, Faculty of Engineering, Turkey
Prof. Ibrahim Maiyza, National Institute of Oceanography & Fisheries, Egypt
Prof. Loc Nguyen, Sunflower Soft Company, Vietnam
Prof. Marilia Hagen, Indiana University, United States
Prof. Md Najib bin Ibrahim, Universiti Teknologi MARA, Malaysia
Prof. Md. Abdul Baset Mia, BSMR Agri. Univ., Bangladesh
Prof. Mihaela Popescu, University of Craiova, Romania
Prof. Mohamed Abdou, Faculty of Education Department of Mathematics, Egypt
Prof. Mohamed Tahiri, Présidnce de l'Université Hassan II de Casablanca, MoroccoProf. Nazar Oukaili, University of Baghdad, Iraq
Prof. Radim Cajka, Technical University Ostrava, Faculty of Civil Engineering, Czech RepublicProf. Rajaraman Jambunathan, AMET University, India
Prof. Saad Farhan Ibrahim Alabdullah, University of Almustansiriyah, Iraq
Prof. Salem Alsanusi, Benghazi, Libya
Prof. Sudhir Kumar Das, Retired Senior Project Manager of Indian Railways, India
Prof. Zachary Senwo, Alabama A&M University, United States
Prof. Imed Jabri, University of Tunis, Tunisia
A/Prof. Bindeshwar Singh Kamla Nehru Institute of Technology, India
A/Prof. Hasi Rani Barai, Yeungnam University, South Korea
A/Prof. Jamaluddin Mahmud, Universiti Teknologi MARA, Malaysia
A/Prof. Mohamed Ramadan, University of Hail, Saudi Arabia
A/Prof. Najam Hasan, Dhofar University, Oman
A/Prof. Nosina Krishna Chaitanya, Jawaharlal Nehru Technological University, India
A/Prof. Nurbek Saparkhojayev, Almaty Management University, Kazakhstan
A/Prof. Pandian Vasant, Universiti Teknologi Petronas, Malaysia
A/Prof. Teodor Lucian Grigorie, University of Craiova, Romania
A/Prof. Zawawi Daud, Universiti Tun Hussein Onn Malaysia
A/Prof. Abdull Halim Abdul, OIl and Gas department, Malaysia
A/Prof. Baoping Cai, China University of Petroleum, China
A/Prof. Dariusz Jakóbczak, Koszalin University of Technology, Poland
A/Prof. Edgar Allan Mendoza, University of the Philippines
A/Prof. Lakhveer Singh, Universiti Malaysia Pahang (UMP) Malaysia, Malaysia
A/Prof. Lidia Sas Paszt, Research Institute of Pomology, Poland
A/Prof. Mahmood Barbooti, University of Yechnology, Iraq
A/Prof. Majid Mirzaei, Universiti Tunku Abdul Rahman, Malaysia
A/Prof. Najeh Lakhoua, University of Carthage, Tunisia
A/Prof. Ryan Joseph Calinao, Lyceum of the Philippines University-Laguna
A/Prof. Sarawut Thepanondh, Mahidol University, Thailand
A/Prof. Yasir Al Hussein, Jerash University, Faculty of Engineering, Jordan
A/Prof. Grigorie Teodor Lucian, University of Craiova, Romania
A/Prof. Hêriş Golpîra, Islamic Azad University, Sanandaj, Iran
A/Prof. Muhammad Aslam, King Abdulaziz University, Saudi Arabia
A/Prof. Tomasz Plech, Medical University of Lublin, Poland
A/Prof. Fellah Mamoun, Abbes laghrour University, Algeria
A/Prof. R. S. Ajin, GeoVin Solutions Pvt. Ltd., India
A/Prof. Roman Szewczyk, Industrial Research Institute for Automation and Measurements, PolandxDr. Abolghasem Akbari, University Malaysia Pahang, Malaysia
Dr. Ahmad Safuan A Rashid, Universiti Teknologi Malaysia, Malaysia
Dr. Akinola Johnson Olarewaju, Federal Polytechnic Ilaro, Ogun State, Nigeria
Dr. Alexandre Costa, Federal University of the valleys of Jequitinhonha and Mucuri, Brazil
Dr. Angelo Gallone, Scotland’s Rural College (SRUC), United Kingdom
Dr. Azizul Azhar Ramli, Universiti Tun Hussein Onn Malaysia
Dr. Bashir Dar, University of kashmir Delina Baramulla J&K India, India
Dr. Bassam Abdellatif, National Authority for Remote Sensing and Space Sciences, Egypt
Dr. Binh Phu Nguyen, National University of Singapore, Singapore
Dr. Cazacu Gabriela, S.C. Geotech Dobrogea, Romania
Dr. Chengen Yang, Intel Corporation, United States
Dr. Dayang Norulfairuz Abang Zaidel, Universiti Teknologi Malaysia
Dr. Evgeni Starikov, KIT, Karlsruhe, Germany; Chalmers, Gothenburg Sweden, Germany
Dr. Fatma Khanchel, University of Tunis El Manar, Tunisia
Dr. Hamidreza Khataee, Griffith University, Australia
Dr. Hêriş Golpîra, Islamic Azad University, IranDr. Iskhaq Iskandar, Dept. Physics, University of Sriwijaya, Indonesia
Dr. Jingwei Zhao, University of Wollongong, Australia
Dr. Jitendra Agrawal, Rajiv Gandhi Proudyogiki Vishwavidyalaya, India
Dr. Liza Patacsil, Malayan Colleges Laguna, Philippines
Dr. Mohamed Amine, Ferrag Guelma University, Algeria
Dr. Mohd Afendi Rojan, Universiti Malaysia Perlis, Malaysia
Dr. Mohd Altaf, University of kashmir Delina Baramulla J&K India, India
Dr. Mohd Hairy Ibrahim, Sultan Idris Education University, Malaysia
Dr. Mostafa Khater, Egypt - El sharqia - Zagazig, Egypt
Dr. Najam Hasan, Dhofar University, Oman
Dr. Namir Alkawaaz, University of Almustansiriyah, Iraq
Dr. Nashrul Fazli Mohd Nasir, Universiti Malaysia Perlis, Malaysia
Dr. NaufaL Mansor Kampus Uniciti Alam, Universiti Malaysia Perlis (UniMAP), Malaysia
Dr. Obed Majeed Ali, Northern Technical University, Iraq
Dr. Piyapong Janmaimool, King Mongkhut' University of Technology, Thailand
Dr. Po-Sheng Chiu, National Cheng Kung University, Taiwan
Dr. Prabu Mohandas, Adhiyamaan College of Engineering, India
Dr. Raman Kumar, D A V Institute of Engineering and Technology, India
Dr. Riccardo Colella, University of Salento, Italy
Dr. Rolando Javellonar, Romblon State University, Philippines
Dr. Shikha Agrawal, Rajeev Gandhi Technical University, India
Dr. Stefania Tomasiello CORISA, University of Salerno, Italy
Dr. Sumiyyah Sabar, Universiti Sains Malaysia, Malaysia
Dr. Suphaphat Kwonpongsagoon, Mahidol University, Thailand
Dr. Wei Hong Tan, Universiti Malaysia Perlis, Malaysia
Dr. Yoshiro Fujii, Shin Kobe Dental Clinic, Japan
Dr. Yuk Feng Huang, Universiti Tunku Abdul Rahman (UTAR), Malaysia
Dr. Zongyan Zhou, Monsh University, Australia
Dr. Purnanand Savoikar, Goa Engineering College, India
Dr. Ahmed Toaha Mobashsher, University of Queensland, Australia
Dr. Chupong Pakpum, Maejo University
Dr. Emanuele Quaranta, Politecnico di Torino, Italy
Dr. Jiangling Yin, Apple Inc., Cupertino, CA, United States
Dr. Khor Shing Fhan, Universiti Malaysia Perlis, Malaysia
Dr. Mario Chauca, Ricardo Palma University, Peru
Dr. Santosh Gaikwad, Model College, Ghansawangi, India
Dr. Tse Guan Tan, Universiti Malaysia Kelantan
Dr. Vikas Panthi, National Institute of Technology, India
Dr. Watoo Phrompittayarat, Naresuan University, ThailandxiDr. Hamidreza Namazi, Nanyang Technological University, Singapore
Dr. Parichat Phumkhachorn, Ubon Ratchathani University, Thailand
Dr. Subhasis Roy, University of Calcutta, India
Conference Correspondence:Prof. Dr. Zakaria Hossain (Director)
Dept. of Environmental Science and Technology, Mie University, Japan
Mr. Md. Aminul Islam (Secretary)Dept. of Environmental Science and Technology, Mie University, Japan
E-mail: conference@geomate.org
Tel & Fax: +81-59-231-9578
Editorial and Executive Committee:
Prof. Dr. Zakaria Hossain
Engr. Alex Otieno Owino
Engr. Md. Aminul Islam
Ms. Najmun Nahar
Mr. Sayful Kabir Khan
Mr. Jamie Ovia

xii

Technical Papers

1Structure2

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

DEFECT DETECTION ON ASPHALT PAVEMENT BY DEEPLEARNING
Jonpaul Nnamdi Opara1, Aunt Bo Bo Thein2, Shota Izumi3, Hideaki Yasuhara4 and Pang-Jo Chun5
Graduate School of Science and Engineering, Ehime University, Japan; 5 School of Engineering, The
University of Tokyo, Japan

1,2,3,4

ABSTRACTThe importance of road infrastructure to the economy of any nation cannot be overemphasized, however, it is
not easy to maintain it properly. Since the inspection of pavements is particularly difficult, an efficient inspection
method is required. In this study, a method for detecting damage in asphalt pavements was developed using oneof the deep learning techniques, YOLOv3. YOLOv3 is a method for detecting the position and type of an object
from an input image, which fits the purpose of this study. The developed method can distinguish between
longitudinal crack, transverse crack, alligator crack and pothole. In order to confirm the accuracy of the developed
method, images of pavements acquired on National Route 4 in Japan are analyzed. From the analysis, it is foundthat the precision value is 0.7 and average IoU is 50.39%. From the visualization of the analysis results, it was
found that this method based on YOLOv3 was able to detect the damage with good accuracy.
Keywords: Asphalt pavement, Deep learning, YOLOv3, Crack detection, Potholehuman expert and it is a process that always involves acertain degree of subjective judgment. In order tominimize the subjectivity, save time and labour cost, a
computerized system for analysis that automaticallyevaluates the condition of pavement is desired. Manysuch studies have been conducted to automaticallydetect cracks in asphalt pavements (e.g. [5-11]). If we
include the detection of damages in concrete or steel
structure, there are many papers on this subject including
author’s researches (e.g. [12-20]). However, consideringthat almost all of the methods have not yet been put topractical use, we still need to accumulate more researchdevelopments. Therefore, in this study, we developed amethod for detecting cracks using YOLOv3 [21], which
is a deep learning technique to detect the position andtype of an object from an input image. Then, images ofpavements acquired on National Route 4 in Japan are
analyzed to confirm the accuracy of the developed
method. We will discuss these in the following chapters.

INTRODUCTION
The importance of road infrastructure to theeconomy of any nation cannot be overemphasized [1].
Roads are the arteries through which the economy
pulses. By linking producers to markets, workers tojobs, students to school, and the sick to hospitals,
roads are vital to any development agenda. Countries
all over the world are currently finding the path
towards attaining the Sustainable Development Goal
9 (SDG9), efficient transportation services are key
drivers of economic development [2]. The importanceof roads is infinite, but most importantly is how safe
the road is and the ease of maintenance. No matter theamount of road constructed, proper maintenance isessential in order for the road to continue to serve its
design purpose. In order to achieve this, a robust roadmanagement system has become a necessity. Road
inspection is one of key processes of a pavement
management system, whose function is to examineand describe the road infrastructure condition [3]. If
done right, will provide adequate information
required to implement a robust and all-encompassing
road policy and maintenance schedule.
In Japan for instance, amid the aging of
infrastructures, the increase in maintenance and repair
expenditures are topics of concern. In a 2016 survey,
the total length of road in Japan is about 1,210,000
kilometers and the number of roads that needs
maintenance is constantly on the increase [4]. Among
those, 77.3% of the total road length is in asphalt
concrete structure. It means the inspection andmaintenance processes must be cost effective andefficient. In this study, we focus on inspection.
Traditional evaluation method is usually done by a

LITERATURE REVIEWWith a lot of research in developing defectdetection and inspection system from the survey
database images. Deep learning and AI applications
has become vital for maintenance infrastructure
management. And lots of advancement is been madein this area especially with the application ofcomputer vision techniques. [22] Identified Faster
R-CNN as a better algorithm in terms of speed andproposed a solution to detect road potholes, deep
ridges and speed breakers with an R-CNN basedmodel. The proposed approach used the custom-built
Bumpy Dataset which was created, both trainedmodel and the dataset used to develop the model3

SEE - Kyoto, Japan, Nov.18-20, 2020

could easily be integrated into an assistive driving
technology.[23] made comparative study on
automatic asphalt pavement cracks recognition basedon image processing and machine learning
approaches. Six machine learning approaches, Na¨ıveBayesian Classifer (NBC), Classifcation Tree (CT),
Backpropagation Artifcial Neural Network (BPANN),
Radial Basis Function Neural Network (RBFNN),
Support Vector Machine (SVM), and Least Squares
Support Vector Machine (LSSVM), have been
employed. Additionally, Median Filter (MF),
Steerable Filter (SF), and Projective Integral (PI)have been used to extract useful features frompavement image.
The findings showed that input pattern including
the diagonal PIs enhances the classifcation
performance significantly by creating more
informative features. LSSVM had the highest
classification accuracy, which indicates that machine
leaning can in understanding pavement condition
properly. Although in this research we dived indeeper, works like this set the bases for more research.
In [24] the authors narrowed down to crack
defects on pavement and propose the CrackSeg—an
end-to-end trainable deep C-NN for pavement crack
detection, that has proven to be effective in achieving
pixel-level, and automated detection via high-levelfeatures. Novel multiscale dilated convolutional
module that can learn rich deep convolutionalfeatures was introduced, making the crack featuresacquired under a complex background more
discriminant. Using their own custom CrackDataset
to train and evaluate the CrackSeg net theexperimental results showed that the CrackSeg canachieve high performance with a precision of 98.00%,
recall of 97.85%, F-score of 97.92%, and a mIoU of
73.53%. Comparing this with other state-of-the-art
methods, the CrackSeg performs more efficiently,
and robustly for automated pavement crack detection
and could be deployed for other forms of pavement
defects detection.

Longitudinal CrackTransverse Crack

Alligator Crack

PotholeFig.1 Classes of asphalt pavement defects

Fig.2 Example of annotation with LabelImg
The structure of YOLOv3 is complicated. YOLOv3
uses Residual Blocks which consists of several
convolutional layers and shortcut paths for featurelearning. It is difficult to train in very deep neuralnetworks because of the vanishing and exploding
gradients types of problems. Residual networks
known as ResNet which is famous for its short cut
connection which is basically the feeding (bysummation) of the features from the preceding layers
to the next level layers are built by residual blocks.
The accuracy of YOLOv3 making use of the residual
blocks and ResNet is known to be high. See [21] fora detailed structure and explanation.
In this study, we aimed to detect four types ofdefects: longitudinal crack, transverse crack, alligatorcrack and pothole. Examples of each are shown in Fig.
1. YOLOv3 is classified as supervised machinelearning, which is a procedure for predicting an
output corresponding to a new input based on priortraining that uses manually prepared inputs andoutputs. In other words, to train the YOLOv3, the

CRACK DETECTION METHOD
In recent years, many deep learning techniques
have been developed. Among them, YOLOv3 ispositioned as extremely fast and accurate object
detection algorithm. YOLOv3 makes use only
features learned by a deep convolutional neuralnetwork to detect an object, making it a fully
convolutional network (FCN), the algorithm can not
only classify objects into a category, but it can also
detect multiple objects within an image outputting the
4-coordinate of the bounding boxes for each object.

4

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 1 The number of images obtained for eachclass

training dataset is required. In this study, the training
dataset were made using the annotation tools
LabelImg [25]. An example of annotation is shown in
Fig.2.

Defect class
Transverse crack
Longitudinal crack
Alligator crack
PotholeNo crack

Hyperparameters

The number of pictures
1,035
1,676
672
11
1,968

Hyperparameters are the variable which control
the network architecture and training process of
YOLOv3. Hyperparameter can be changed according
to the own network architecture. In our defects
detection model the hyperparameters are set as below.
In this research, we use the network size of 448 x
448 with 3 channels. The momentum and decay rate
are set to 0.9 and 0.005 respectively. Saturation andExposure are set to 1.5. Learning rate of the YOLOv3
network is set to 0.001 burning in at 1000 training
steps. Policy is set up to do in step by step. As ourcrack detection network has 4 classes, we use the
YOLOv3 layers with 27 filters using linear activation
function. Ignore threshold is set to 0.7. We use 9anchors cluster for the network which is calculated byusing computing function presented in latest
YOLOv3 repository. We adjust the anchors value andtest the training. Maximum iteration is set to 20000
iteration. Usually sufficient 2000 iterations for eachclass (object), but not less than number of training
images and not less than 6000 iterations in total. As
our network has 4 classes, we only need about 8000
iteration. However, for the better performance and forthe research, we train up to 20000 iteration.

Table 1 shows the number of images obtained foreach class. Although the number of pot holes is small,
it is inevitable because pot holes are quickly repairedin Japan. In the future, more pothole images are
required to improve the detection performance of
pothole, but the methodology is still underconsideration.

DATA COLLECTIONCRACK DETECTION BY YOLOV3

Fig.4 Definition of TP, TN, FP, FN.

In this research, survey data were taken by survey
vehicle called RIM (Road space Information
Management system), owned by Obayashi Road
Cooperation (Fig. 3). It is a vehicle mounted with the
GPS instruments with mobile mapping system MMS
with surface recording cameras which collect the roadsurface information up to mm units in threedimensional perspective. The RIM vehicles enables
highly detailed mapping of roads and high accuracy
and excellent positioning, within a short period oftime while minimizing nuisance to traffic and risks ofaccidents. The image data taken by RIM vehicle are2400 x 2000 pixels images and the light content
measurement is in RGB. In this study, the survey data
is taken along the Nation Highway Road No.4 inside
Tochigi Prefecture.

Training YOLOv3
In this chapter, we train YOLOv3 using the datacollected in the previous chapter. In this study, theratio of training, validation and test was 7:2:1. Inorder to prevent overfitting, the training was
conducted to the extent that the accuracy of the
training dataset and the accuracy of the validation
dataset did not deviate.
During the training process, precision, recall, andF1 value of validation dataset are obtained. These
indices are defined by the following equations.

Precision =TP
TP + FPTP
TP + FN
2Recall × Precision
F1 value =Recall + Precision
Recall =

(1)
(2)
(3)

where TP, TN, FP, FN are defined as like in Fig.4.
Fig. 5 shows the changes in these indices with theFig.3 RIM vehicle owned by Obayashi Road
Cooperation
5

SEE - Kyoto, Japan, Nov.18-20, 2020

cracks and alligator cracks are also accurately

Precision, Recall, F1 value

1.0

0.8

0.6

0.4

Precision
Recall
F1 value

0.2

0.0

0

5000

10000

15000

20000

The number of iterations

Fig.5 Changes in precision, recall, F1 value.

Fig.7 Detection results of longitudinal crack.

Fig.6 Detection results of transverse crack
number of iteration increases.
According to the results, the maximum value of
precision is at iteration 2000 and 7000, that of recall
is at iteration 18000, and that of F1 value is almost at
iteration 10000, 18000, and 19000. Considering theabove, we decided to adopt the model using theresults of iteration 18000 as the analysis model.
Analyzing test images
Fig. 6 illustrates some examples of the detection
results of transverse crack obtained by applying the
proposed method. As in the figures, the transverse
cracks are accurately detected. Similarly, longitudinal

Fig.8 Detection results of alligator crack.
detected as in Fig. 7 and Fig.8, respectively. As for6

SEE - Kyoto, Japan, Nov.18-20, 2020

the pothole, because there was only one test image, it
is difficult to say that the accuracy is confirmed.
However, the pothole was properly detected on one

image as in Fig.9. However, it is needed to examine
again after the number of images including potholeincreases in future study. Fig. 10 shows an exampleof the detection results when several types of cracks
are present in the same image. The top and middle
pictures were properly detected, but the bottom
picture was confused between alligator crack andtransverse crack. We would like to solve this problem
by increasing the amount of data. Nevertheless, thisis not a bad result in terms of the detection of cracks.
Considering the results from Fig.6 to Fig.9, it can besaid that the effectiveness of this method has been
proved.
CONCLUSIONSThis study uses YOLOv3, one of the deeplearning techniques, to detect cracks in pavements
automatically. In addition, the pavement of the
National Road was photographed using RIM andanalyzed by YOLOv3 to examine the crack detection
performance. As a result, it became clear that thecrack could be detected with very high accuracy as
shown in Figs. 6 to 10.
Future problems are described below. When
there are multiple types of cracks in one image, as
shown in the bottom figure in Fig. 10, there is a casein which the exact answer cannot always be obtained.
This can be solved by increasing the number oftraining data. It is also necessary to increase thenumber of images for the pothole. However, it isgenerally appropriate as a technique, and it isconsidered to be one step forward for the practical use.

Fig.9 Detection results of pothole.

ACKNOWLEDGMENTS
We would like to take this opportunity to thankObayashi Road Corporation for taking the image with
their RIM.
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[2] Claudia B., Uwe D., and Harris S., How roads
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[3] Staniek M., Detection of cracks in asphalt
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[4] Ministry of Land, Infrastructure, Transport andTourism, The maintenance of national road
network in Japan, https://www.mlit.go.jp/road/road_e/03key_challenges/1-2-2.pdf (accessed Jun.

Fig.10 Detection results when multiple types ofcracks are in one image.

7

SEE - Kyoto, Japan, Nov.18-20, 202029, 2020).
[5] Hoang N. D. and Nguyen Q. L., A novel method
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[6] Zhang A., Wang K.C., Fei Y., Liu Y., Chen C.,
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Engineering, Vol. 34, Issue 3, pp.213-229, 2019.
[7] Nhat-Duc H., Nguyen Q.L., and Tran V.D.,
Automatic recognition of asphalt pavement cracks
using metaheuristic optimized edge detection
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Automation in Construction, Vol. 94, pp.203-213,
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[8] Zhang D., Li Q., Chen Y., Cao M., He L., andZhang B., An efficient and reliable coarse-to-fineapproach for asphalt pavement crack detection.
Image and Vision Computing, Vol. 57, pp.130146, 2017.
[9] Zhang L., Yang F., Zhang Y.D., and Zhu Y.J.,
Road crack detection using deep convolutional
neural network. In 2016 IEEE international
conference on image processing (ICIP), pp.37083712, 2016.
[10] Chun P., Hashimoto K., Kataoka N., KuramotoN., and Ohga M., Asphalt pavement crack
detection using image processing and naive bayes
based machine learning approach. Journal ofJapan Society of Civil Engineers, Ser. E1(Pavement Engineering), Vol. 70, No. 3, pp.I_1I_8, 2015.
[11] Saar T., and Talvik O., Automatic asphalt
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[12] Zou Q., Zhang Z., Li Q., Qi X., Wang Q., andWang S., Deepcrack: Learning hierarchicalconvolutional features for crack detection. IEEE
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[13] Chun P., Izumi S., and Yamane T., Automatic
detection method of cracks from concrete surface
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[14] Park S., Ahmad, S., Yun, C. B., and Roh, Y. ,Multiple crack detection of concrete structuresusing
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structural
healthmonitoring techniques. Experimental Mechanics,
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[15] Sohn, H. G., Lim, Y. M., Yun, K. H., and Kim,

G. H., Monitoring crack changes in concrete
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[16] Chun, P., Ujike, I., Mishima, K., Kusumoto, M.,
and Okazaki, S., Random Forest-based evaluation
technique for internal damage in reinforced
concrete featuring multiple nondestructive testing
results. Construction and Building Materials,
Vol.253, 119238, 2020.
[17] Okazaki, Y., Okazaki, S., Asamoto, S., and Chun,
P., Applicability of machine learning to a crackmodel in concrete bridges. Computer ‐ Aided
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[18] Chun, P., Yamane, T., Izumi, S., and Kameda, T. ,Evaluation of tensile performance of steel
members by analysis of corroded steel surface
using deep learning. Metals, Vol. 9, Issue 12,
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[19] Chun, P., Tsukada, K., Kusumoto, M., andOkubo, K., Investigation and repair plan for
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[20] Chun, P., Yamane, T., Izumi, S., and Kuramoto,N., Development of a Machine Learning-Based
Damage Identification Method Using Multi-Point
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[21] Redmon, J., and Farhadi, A., Yolov3: An
incremental improvement. arXiv preprint
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[22] Zahid H., Samsoon N., Tasmia R. and Shahnewaz
S., Pothole and Speed Breaker Detection Using
Smartphone Cameras and Convolutional Neural
Networks 2020 IEEE Region 10 Symposium(TENSYMP), 5-7 June 2020, Dhaka, Bangladesh[23] Nhat-Duc H. and Quoc-Lam N., Automatic
Recognition of Asphalt Pavement Cracks Based on
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Approaches: A Comparative Study on Classifier
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[24] Weidong S., Guohui J., Hong Zhu , Di J., and Lin
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[25] LabelImg, https://github.com/tzutalin/labelImg(accessed Jun. 29, 2020).

86th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

NONLINEAR SECTIONAL ANALYSIS OF STRUCTURAL CONCRETE
MEMBERS OF ARBITRARY SHAPE UNDER CYCLIC LOADING
Ahmed Alkhairo1, Nazar Oukaili2, and Riadh Al-Mahaidi3
University of Baghdad, Iraq; 2University of Baghdad, Iraq;3Swinburne University of Technology, Australia.

1

ABSTRACTThis paper presents a new numerical methodology for the analysis of the sectional behaviour of structuralconcrete members with arbitrary cross-sectional configurations under repeated loading. The proposed
methodology is accompanied by computer software written in the Python language to perform the sectional
analysis at different loading stages from serviceability to ultimate limit conditions. The software uses a meshgenerator to discretise sections of arbitrary shapes, a combination of polygons and circles, into infinitesimal
triangles. The contribution of each mesh element is then determined based on the stiffness and the concrete secant
modulus of elasticity of that element. The stress-strain concrete model under repeated loading proposed by
Karpenko et al. [1] is adopted to calculate the concrete secant modulus of elasticity of each mesh element
independently based on the level of stress attained at the start of the unloading and reloading stages. The change
in the concrete secant modulus of elasticity is reduced for each cycle until stabilisation is achieved. After eachcycle, the deformation (strain and curvature) is calculated. The software is also capable of analysing the beamcolumn section under biaxial bending moment combined with normal force. It outputs the results in a video format
containing all steps of the loading behaviour and plots the moment-curvature relation and the bending-axial force
interaction diagram.
Keywords: Stiffness matrix, Constitutive relationship, Strain vector, Secant modulus, Residual strain

developed by Karpenko et al. [1] to involve the cyclic
behaviour of concrete material using linear unloading
and reloading relationships. The research reported inthis paper investigates the implementation of therepeated loading effect in the sectional analysis ofdifferent structural concrete members, including
reinforced and prestressed concrete members.

INTRODUCTION
Concrete sections are designed to withstand static
external loads. Although structural elements, such as
bridge girders, most often undergo subsequentloading and unloading stages, most design standards
exaggerate the estimated external static loads toaccount for the repeated load effect. As a result, thecyclic effect may be under-estimated, which in turncauses excessive deformation during service life, orover-estimated, which increases the cost of
construction. Therefore, the cyclic effect of structuralelements has recently attracted the attention ofresearchers.
Traditional design methods were developed for
manual calculations. However, with current
technologies and computer power, more accurate
results can be obtained using sophisticated analyticalmodels and repetitive calculation procedures.
Although discretised section analysis was developedin the late nineteenth century, it has only been used inrecent years due to its long and tedious calculations.
A nonlinear stress-strain relationship developedby Karpenko et al.[2], [3] is adopted in this research.
Karpenko et al.’s model can be used to simulate any
nonlinear material behaviour by changing specificparameters.
Consequently,
thestress-strain
behaviours of both concrete and steel have been
produced using just one pattern with input data
specific to each material. The model was further

THEORETICAL BACKGROUND
The concept of sectional analysis is mainly
dependent on Bernoulli-Navier’s assumption that aplane section before deformation remains plane after
deformation [4]. Hence, the strain (𝜀𝜀) at any point
over the beam section can be expressed by a linear
relationship:𝜀𝜀 = 𝜀𝜀𝑜𝑜 + 𝜓𝜓𝑥𝑥 × 𝑦𝑦 + 𝜓𝜓𝑦𝑦 × 𝑥𝑥

(1)

where
𝜀𝜀𝑜𝑜 : the axial strain magnitude at the reference point,𝜓𝜓𝑥𝑥 , 𝜓𝜓𝑦𝑦 : biaxial bending curvatures, and𝑥𝑥, 𝑦𝑦 : the coordinates of the corresponding point
relative to the global coordinates.

For any material, the constitutive relationship canbe presented by the modulus of elasticity (𝐸𝐸), where:
𝐸𝐸 =
9

𝜎𝜎
𝜀𝜀

⇒

𝜎𝜎 = 𝐸𝐸 × 𝜀𝜀(2)

SEE - Kyoto, Japan, Nov.18-20, 2020

The three equations of classical beam theory canbe rewritten in a matrix form as follows [5]:⎡ � 𝜎𝜎 𝑑𝑑𝑑𝑑 ⎤𝑁𝑁⎢⎥
�𝑀𝑀𝑥𝑥 � = ⎢� 𝜎𝜎 × 𝑦𝑦 𝑑𝑑𝑑𝑑⎥
⎢
⎥
𝑀𝑀𝑦𝑦
⎢
⎥
� 𝜎𝜎 × 𝑥𝑥 𝑑𝑑𝑑𝑑
⎣
⎦

(3)

{𝐹𝐹} = [𝑪𝑪] × {𝜀𝜀}(4)calculating the failure load vector by predicting avertex in the cross-section of the beam which will failfirst, depending on the orientation of the externallyapplied moment and the location of the plastic
centroid. Solving for the failure load vector is thenachieved based on the knowledge that the strain inthat vertex is the maximum strain defined by thematerial stress-strain diagram. Furthermore, thedescending part of the moment-curvature diagram
can be obtained by increasing the strain vector
beyond the maximum strain specified by the material
properties. On the other hand, the second approach ismore convenient for the analysis of beams under agiven load vector, and it satisfies the requirement of
Karpenko et al.’s [1] concrete cyclic behaviour model.
Furthermore, the computational algorithm is lesscomplicated and leads to fewer errors. The failureload vector can still be determined using the bisection
method by increasing the external load vector until an
acceptable tolerance is reached while checking if thestrain has exceeded the ultimate strain in any vertex
in the cross-section for each increment.

Substituting Eq. (1) and Eq. (2) into Eq. (3) andsolving the integration by numerical summation
results in:

1𝑁𝑁�𝑀𝑀𝑥𝑥 � = � �𝐸𝐸 × �𝑦𝑦
𝑀𝑀𝑦𝑦
𝑥𝑥

𝑦𝑦
𝑦𝑦 2
𝑥𝑥𝑥𝑥

𝜀𝜀𝑜𝑜
𝑥𝑥
𝑥𝑥𝑥𝑥� × 𝐴𝐴� �𝜓𝜓𝑥𝑥 �
𝜓𝜓𝑦𝑦
𝑥𝑥 2

(5)

where 𝐴𝐴 corresponds to the cross-sectional area ofan elementary unit in the section which has a specificmaterial type and (𝐸𝐸) is the secant modulus of thatmaterial at the given strain vector.
Several models and algorithms have beendeveloped to perform sectional analysis of arbitrary
shapes utilising Eq. (5). However, two main
approaches have been investigated in the literature,
either solving for the load vector or solving for thestrain vector. The first approach [6]-[8] involves agiven strain magnitude at the reference point and an
iterative procedure to calculate the biaxial curvaturecaused by a given biaxial moment ratio. Therefore,
the load vector can be easily obtained from Eq. (5).
On the other hand, the second approach [5], [9] adopts
an iterative procedure using the Newton-Raphson
technique to calculate the strain vector at a given load
vector such that:{𝜀𝜀}𝑖𝑖 = [𝑪𝑪({𝜀𝜀}𝑖𝑖−1 )]−1 × {𝐹𝐹}

MATERIAL MODELS
Equation (2) requires a function to determine thesecant modulus at a specific strain magnitude. It canbe calculated for any material model such that stressis a function of strain. The nonlinear stress-strainmodel for both concrete and steel proposed by
Karpenko et al.[2], [3] is adopted for this research.
The model was developed based on the coefficient ofchange of the secant modulus (𝜈𝜈), Thus:(8)
𝐸𝐸 = 𝐸𝐸𝑖𝑖 × 𝜈𝜈𝜈𝜈 = 𝜈𝜈̂ + (𝜈𝜈𝑜𝑜 − 𝜈𝜈̂ )�1 − 𝜔𝜔 × 𝜂𝜂 − (1 − 𝜔𝜔) × 𝜂𝜂2 (9)𝜎𝜎 − 𝜎𝜎𝑒𝑒𝑒𝑒
(10)
𝜂𝜂 =
𝜎𝜎� − 𝜎𝜎𝑒𝑒𝑒𝑒

where,𝐸𝐸𝑖𝑖 : the initial modulus of elasticity,𝜈𝜈𝑜𝑜 : the coefficient of change of the secant modulus at
the start of the (𝜎𝜎 − 𝜀𝜀) diagram,𝜈𝜈̂ : the coefficient of change of the secant modulus at
the peak of the (𝜎𝜎 − 𝜀𝜀) diagram,𝜔𝜔: the (𝜎𝜎 − 𝜀𝜀) diagram curvature parameter,𝜂𝜂: relative stress level, ( 0 ≤ 𝜂𝜂 ≤ 1 ),𝜎𝜎𝑒𝑒𝑒𝑒 : the elastic stress limit, and𝜎𝜎�: the stress at the peak of the (𝜎𝜎 − 𝜀𝜀) diagram.

(6)

For a given load vector, Eq. (6) can be solved todetermine the corresponding strain vector. This
calculation requires a repetitive process to find thestiffness matrix of each mesh element based on astrain vector from the previous iteration andnumerically summed over all elements. Hence,
accurate results depend mainly on the number ofmesh elements used to discretise the section. The
iterative process continues until an acceptable
tolerance of the strain vector between two successive
iterations is achieved, as shown in Eq. (7). After
convergence is reached, the stress and strain at any
point can be calculated using Eqs. (1) and (2).

|𝜀𝜀𝑖𝑖 − 𝜀𝜀𝑖𝑖−1 | ≤ 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡

Any parameter designated with a hat (^)
corresponds to the point of peak stress in the stressstrain diagram. Now, substitution Eq. (2) and Eq. (10)into Eq. (9) and re-arrangement into a quadratic form
leads to Eq. (11):(7)

𝑎𝑎 × 𝜈𝜈 2 + 𝑏𝑏 × 𝜈𝜈 + 𝑐𝑐 = 0

The first approach is recommended when

where,

10(11)

SEE - Kyoto, Japan, Nov.18-20, 2020𝑎𝑎 = (1 − 𝜔𝜔) × (𝜈𝜈𝑜𝑜 − 𝜈𝜈̂ )2 × 𝜀𝜀 2 + (𝜈𝜈̂ × 𝜀𝜀 − 𝜀𝜀𝑒𝑒𝑒𝑒 )2 ,𝑏𝑏 = (𝜈𝜈𝑜𝑜 − 𝜈𝜈̂ )2 × 𝜀𝜀 × [𝜔𝜔 × (𝜈𝜈̂ × 𝜀𝜀̂ − 𝜀𝜀𝑒𝑒𝑒𝑒 ) − 2 × 𝜀𝜀𝑒𝑒𝑒𝑒 ×(1 − 𝜔𝜔)] − 2 × 𝜈𝜈̂ ∗ (𝜈𝜈̂ × 𝜀𝜀̂ − 𝜀𝜀𝑒𝑒𝑒𝑒 )2 , and
𝑐𝑐 = (𝜈𝜈𝑜𝑜 − 𝜈𝜈̂ )2 × 𝜀𝜀𝑒𝑒𝑒𝑒 × [(1 − 𝜔𝜔) × 𝜀𝜀𝑒𝑒𝑒𝑒 − 𝜔𝜔 × (𝜈𝜈̂ ×𝜀𝜀̂ − 𝜀𝜀𝑒𝑒𝑒𝑒 )] + (𝜈𝜈̂ × 𝜀𝜀̂ − 𝜀𝜀𝑒𝑒𝑒𝑒 )2 × (2 × 𝜈𝜈̂ − 𝑣𝑣𝑜𝑜 ) × 𝜈𝜈𝑜𝑜

experimental data with an acceptable error level.
Therefore, the present research implements the cyclic
model at the section level.
The model is developed for a constant stressamplitude for all cycles and full unloading in eachcycle. The parameters corresponding to the points of
unloading in the stress-strain diagram are designatedwith the tilde (~) (i.e. 𝜎𝜎�, 𝜀𝜀̃, 𝜂𝜂�). The stabilised concrete
stress-strain relationship proposed by Karpenko et al.
[1] depends on reducing the peak stress (𝜎𝜎�) and theinitial modulus of elasticity (𝐸𝐸𝑖𝑖 ) of the initial diagramby 17% and 10%, respectively. Therefore:

The roots of Eq. (11) involve two solutions.
However, the value of 𝜈𝜈 should be selected such that(0 < 𝜈𝜈 ≤ 1). Equation (11) can be solved for any
material for which the constant input data are thecoordinates of the start and peak points and the elastic
properties. The only variable is the strain of the point
under consideration. Figures (1) and (2) demonstrate
the stress-strain relationship of concrete material andmild steel, respectively, generated by solving Eq. (11)for all values of strain (𝜀𝜀) for each material. The input
data were extracted from [10].

𝜎𝜎�𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = 0.83 × 𝜎𝜎�𝐸𝐸𝑖𝑖,𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 = 0.90 × 𝐸𝐸𝑖𝑖

(12)

The number of cycles required to achieve
stabilisation, 𝑁𝑁𝑐𝑐 , at any stress level (𝜂𝜂� ≤ 0.83) can becalculated using Eq. (13), where (𝜂𝜂𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 ) is a constantvalue assumed to be 0.83 as shown in Eq. (12). Basedon the experimental data reported by Karpenko et al.
[1], the number of cycles required to achieve� ), at a stress level corresponding tostabilisation, (𝑁𝑁𝜂𝜂𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 equals 50 cycles. Accordingly, the predicted
number of cycles (𝑁𝑁𝑓𝑓 ) required to reach the failure
stress at any stress level (𝜂𝜂� > 0.83) can be calculatedusing Eq. (14) [1].
1 − 𝜂𝜂𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 2
� , 0 < 𝜂𝜂𝑐𝑐 ≤ 𝜂𝜂𝑐𝑐,𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠
1 − 𝜂𝜂�
� × �1 − 𝜂𝜂� ,𝑁𝑁𝑓𝑓 = 𝑁𝑁𝜂𝜂𝑐𝑐 > 𝜂𝜂𝑐𝑐,𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠

Fig.1

Stress-strain diagram for concrete

�×�
𝑁𝑁𝑐𝑐 = 𝑁𝑁

Fig.2

Stress-strain diagram for mild steel

Fig. 3CYCLIC ANALYSIS MODEL

(13)

(14)

Initial vs stabilised concrete stress-strain
diagrams

The strain of the stabilised diagram ( 𝜀𝜀̃𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 )corresponding to unloading stress (𝜎𝜎�) can be easily
calculated using Eq. (9) with (𝜈𝜈̂ ) being replaced by(𝜈𝜈̂ 𝑠𝑠𝑠𝑠𝑎𝑎𝑎𝑎 ). The residual strain (𝜀𝜀 𝑜𝑜 ) in the first cycle (𝜀𝜀1𝑜𝑜 )𝑜𝑜) can be calculated using Eq.
and the last cycle (𝜀𝜀𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠(15), in which ( 𝜀𝜀̃, 𝜎𝜎� ) are the coordinates of theunloading point of the cycle under consideration, and(𝐸𝐸𝑢𝑢 ) is the unloading modulus, which represents theslope of the unloading line in the diagram. Figure (3)illustrates the difference between the stress-strain

The nonlinear stress-strain relationship is further
investigated in [1] to involve the behaviour ofconcrete material under repeated load. The concept of
the proposed Karpenko et al.’s model involves linear
unloading and reloading paths with strength
degradation in each cycle until stabilisation isreached, in which subsequent unloading andreloading stages follow one linear path. The model isdeveloped in the material level and verified by
11

SEE - Kyoto, Japan, Nov.18-20, 2020

relationship before the start of the cyclic load andafter stabilisation.
𝜎𝜎�
𝐸𝐸𝑢𝑢
√𝜈𝜈�
× 𝐸𝐸𝑖𝑖𝐸𝐸𝑢𝑢 =
0.95

𝜀𝜀 𝑜𝑜 = 𝜀𝜀̃ −However, it can be extended by using the unloading
modulus technique for ( 𝜀𝜀̃ ≥ 𝜀𝜀̂ ) while keeping thestress-strain relationship after the cyclic pathunchanged. In the present study, for simplicity, thetension phase under cyclic loading would have
similar treatment following the same procedure
adopted for cyclic loading in compression.

(15)

(16)

The residual strain ( 𝜀𝜀𝑘𝑘𝑜𝑜 ) and the strain at theunloading point ( 𝜀𝜀̃𝑘𝑘 ) for the subsequent cycles
between first unloading and stabilisation aredetermined using Eqs. (17) and (18) in which (𝛽𝛽𝑘𝑘 )represents the ratio of the change in strain between
the current cycle (𝑘𝑘) and the stabilisation cycle (𝑁𝑁𝑐𝑐 ),where (𝑘𝑘 = 2,3, … , 𝑁𝑁𝑐𝑐 ).
𝜀𝜀̃𝑘𝑘 = 𝜀𝜀̃1 + 𝛽𝛽𝑘𝑘 × (𝜀𝜀̃𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠 − 𝜀𝜀̃1 )𝑜𝑜− 𝜀𝜀1𝑜𝑜 )𝜀𝜀𝑘𝑘𝑜𝑜 = 𝜀𝜀1𝑜𝑜 + 𝛽𝛽𝑘𝑘 × (𝜀𝜀𝑠𝑠𝑠𝑠𝑠𝑠𝑠𝑠
0.2
𝑁𝑁𝑐𝑐
𝛽𝛽𝑘𝑘 = 1 − 2 × ln � � , (0 ≤ 𝛽𝛽𝑘𝑘 ≤ 1)
𝑘𝑘
𝜂𝜂�

(17)
(18)
(19)

Fig.4

Now, the stress-strain relationship in cyclic modecan be obtained for any element with known first
unload strain ( 𝜀𝜀̃1 ) and cycle number ( 𝑘𝑘 ) underconsideration. However, the stress-strain relationshipafter the linear, cyclic path when stabilisation is notreached yet is not investigated in [1].
The present study suggests the application of the(𝛽𝛽𝑘𝑘 ) factor in Eq. (12) as shown in Eq. (20). Solving
Eq. (9) for (𝐸𝐸𝑖𝑖,𝑘𝑘 ) of the kth cycle to obtain the fullstress-strain relationship by substituting thecoordinates of the two known points ( 𝜀𝜀̃𝑘𝑘 , 𝜎𝜎� ) and(𝜀𝜀̂, 𝜎𝜎�𝑘𝑘 ). The diagram curvature parameter of concrete,𝜔𝜔, is assumed to be a linear relationship, as shown in
Eq. (21) where 𝜁𝜁 and 𝜆𝜆 are the linear coefficients.
Therefore, Eq. (9) is rearranged into cubic form, as
shown in Eq. (22).

Concrete cyclic stress-strain diagram

Implementing the cyclic model into Eq. (5)requires the calculation of secant modulus (𝐸𝐸) being
performed independently for each elementary area inthe section because each element is undergoing cyclicloading at different stress amplitudes, due to thelocation of the element relative to the adopted global
axes and the load vector being applied. Hence, it isnecessary to achieve this programmatically byassigning a different material object for each elementin the section.
PROGRAMMING INTERFACE
Previous studies conducted by Oukaili [5]involved the development of a program using Fortran.
The program was built to perform sectional analysisof structural concrete members with a general crosssectionofrectangular-shaped
components
undergoing static loads and detect the failure load
vector and the flexural crack depth across the section
at different loading stages [11], [12]. The present
research involves rebuilding a new software package
written in Python [13] and named SectionPy. It wasdeveloped using an object-oriented programming
concept by distributing the code into reusable
modules and classes. The software consists of eight
modules named as following: material, mesh,element, section, load, solver, postprocessor, andmiscellaneous functions. The material module
generates the stress-strain diagram from the nonlinear
relationship by computing the corresponding stress ofa massive number of strain ordinates (i.e. more than
1000 points), which is then used to calculate thesecant modulus of elasticity at given strain values bylinear interpolation. This method adds flexibility forthe implementation of any material model. However,(20)
𝜎𝜎�𝑘𝑘 = (1 − 0.17 × 𝛽𝛽𝑘𝑘 ) × 𝜎𝜎�1𝜔𝜔 = 𝜁𝜁 + 𝜆𝜆 × 𝜈𝜈̂(21)
3
2+ 𝑏𝑏 × 𝐸𝐸�𝑘𝑘 × 𝐸𝐸𝑖𝑖,𝑘𝑘+ 𝑐𝑐 × 𝐸𝐸�𝑘𝑘2 × 𝐸𝐸𝑖𝑖,𝑘𝑘 + 𝑑𝑑 × 𝐸𝐸�𝑘𝑘3
𝑎𝑎 × 𝐸𝐸𝑖𝑖,𝑘𝑘=0(22)

where,
𝑎𝑎 = (1 − 𝜁𝜁) × 𝜂𝜂2 + 𝜁𝜁 × 𝜂𝜂 − 1,𝑏𝑏 = (2 × 𝜁𝜁 − 2 + 𝜆𝜆) × 𝜂𝜂2 + (𝜆𝜆 − 2 × 𝜁𝜁) × 𝜂𝜂 + 2,
𝑐𝑐 = (1 − 𝜁𝜁 + 2 × 𝜆𝜆) × 𝜂𝜂2 − (𝜁𝜁 + 2 × 𝜆𝜆) × 𝜂𝜂 − 1
2
𝐸𝐸�𝑘𝑘
+ �1 − � , and𝐸𝐸�𝑘𝑘
𝑑𝑑 = 𝜆𝜆 × (𝜂𝜂 − 𝜂𝜂 2 )Although Eq. (22) involves three mathematicalsolutions, the only correct solution should be verified
such that (𝐸𝐸𝑖𝑖,𝑘𝑘 ≥ 𝐸𝐸𝑘𝑘 ). The plots of the stress-strain
diagram for the initial, intermediate and stabilisation
cycles are presented in Fig. (4). This model isdeveloped for compression only and with (𝜀𝜀̃ < 𝜀𝜀̂ ).
12

SEE - Kyoto, Japan, Nov.18-20, 2020

the software currently adopts Karpenko models forboth steel and concrete when generating stress-strain
coordinates. The mesh module is used to discretisethe section being analysed using the Gmsh software[14], which enables the software to analyse sectionsof arbitrary shapes including polygons, circles, and a
combination of both. Moreover, sections with voids
can also be discretised using Boolean operations suchas the hollow-core slab section shown in Fig. (5). The
section can be discretised as structured rectangles,
right triangles, and non-structured triangles.

Fig.5

behaviour of the section between two load vectors.
The determination of the failure load vector requires
an incremental load vector that represents theorientation of the applied load. Therefore, the static
analysis is carried out by multiplying the specified
incremental load vector by a factor until the failureload vector is determined and convergence isachieved. The failure load vector represents the load
vector that results in an unsolvable singular stiffness
matrix or produces a strain at any vertex of the beam
section that exceeds the maximum strain defined in
the material instance of that element. Finally, thepostprocessor is used to visualise the output steps
from solvers into the desired form, such as the stressstrain curve at a specific point, or a biaxial momentcurvature diagram. The stress-strain curve along a
specific line and the stress-strain map can begenerated in a video format that shows the behaviourof the beam between two load vectors.

Hollow-core slab section mesh

COMPUTATIONAL EXAMPLE

The element module includes Subsection andWire classes. Subsection represents a 2-D solid
element with specific material properties. It takes amesh object and material object as an input andcalculates areas and centroids for all mesh elements.
It is worth mentioning that the calculation is
performed at an array level using the NumPy library[15], which enhances the performance of calculationcompared to Python for-loop. Cells areas arecomputed using the shoelace technique based on cell
vertices regardless of the shape of the mesh element.
The wire element represents a reinforcing bar or aprestressing strand in which area, location, andprestressing value are provided as an input.
Both elements accept initial strain either in vector
form or as a number. Initial strain represents theinitial condition corresponding to a zero externallyapplied load vector (i.e. dead or live load) such as
initial strain in concrete and non-prestress steel due toelastic shortening, creep and shrinkage, and pre-strain
in prestressing strands. The primary function of theelement module is to calculate the stiffness matrix at
the strain vector provided.
The section module represents a collection ofelements where solving the matrix is conducted bysumming up all elements: subsections and wires.
Although the software is used to analyse composite
sections with different materials, such an analysis
assumes a full bond between all elements andimplements fictitious strain for nonhomogeneousmaterials. The load module is a small module used to
calculate the load vector for any load type. Currently,
it consists of force, moment, and a combination offorces and moments.
The solver module consists of special analysis
procedures used to calculate the required data byimplementing the above modules. One of the solvers
is the static analysis solver which calculates thefailure load vector using the bisection method and the

A beam with a tee-shaped section is adopted todemonstrate the output of the developed program.
The general section is defined as two rectangles (200mm * 300 mm) for the web and (100 mm * 500 mm)
for the flange using the input data in Table 1. A
reference point located in the middle of the soffit of
the beam is adopted as the origin of the global
coordinate system. A structured mesh 10 mm in size
is nominated. The concrete material stress-strain
profile shown in Fig. (1) is assigned for the subsection
instance. The rebars used are three (𝜙𝜙20 mm) placedat the bottom and four (𝜙𝜙10 mm) distributed at the
top of the beam. The bars are placed such that a 30
mm cover to the rebar edge is achieved. The input
data on the reinforcement bars, including the area andlocation relative to the reference point, are listed inTable 2. The steel material stress-strain relationshipused for all rebars is shown in Fig. (2). Figure (6)shows the final section plot generated by the software.
Table 1 Concrete subsection input data
Items
web
flange

Type
Rect.
Rect.

X
-100
-250

Y
0
300

Width
200
500

Height300
100

Table 2 Reinforcement detailing input data
Items
B1
B2
B3
T1
T2
T3
T4
13

X, mm
-57.5
0
57.5
-215
-65
65
215

Y, mm
42.5
42.5
42.5
365
365
365
365

Area, mm2
314
314
314
78.5
78.5
78.5
78.5

SEE - Kyoto, Japan, Nov.18-20, 2020

modification as a starting point.

Fig.6

T-beam section and discretisation used in theanalysis

The applied load vector is then defined as a
moment instance in the software. A 10 kN.m moment
about the x-axis is used as an incremental load vector.
The maximum bending moment about the x-axis
before tensile steel starts to yield is expected to
exceed 130 kN.m, while, the load vector which causes
complete failure can reach up to 190 kN.m. After
determining the failure load vector, the momentcurvature diagram can be plotted from the successful
steps between the initial and failure load vectors.
Figure (7) illustrates the moment-curvature diagram
about the x-axis generated by the software.

Fig.7

Fig.8

Curvature in x-axis during the cyclic
analysis

Moment-curvature about x-axis

After finishing the static analysis, it is necessary
to select a load vector to be used for the cyclic
analysis. The selected load vector represents the load
amplitude of the cyclic analysis. 25, 75 and 125 kN.m
are adopted for this example to demonstrate theresults at different loading stages. After initiating thecyclic solver, the material stress-strain diagram ismodified for each element in the mesh according totheir stress level and the cycle number provided. Aftermodification, the section analysis is repeated for thesame load vector but with modified material
properties. The calculation of secant modulus (𝐸𝐸) in
Eq. (5) requires a strain vector from the previous
iteration. However, starting with a zero strain vector
results in an infinite solution because the modified
material stress-strain diagram no longer passes
through (0,0). Therefore, overcoming this issue canbe accomplished by using the strain vector before

Fig.9

Stress-strain diagrams across the depth of
the beam
Stabilisation is achieved after 46, 15 and 41
cycles, respectively. The strain vector is calculated ineach cycle, and curvature about the x-axis is noted.
Figure (8) shows the change in curvature over eachcycle up to stabilisation. The strain diagram of the14

SEE - Kyoto, Japan, Nov.18-20, 2020

initial, second cycle, tenth cycle, and stabilised cycle
accompanied by the stress diagram of the initial cycle
across the depth of the concrete beam are plotted inFig. (9). The sign convention used assumes thatcompression is positive, and tension is negative. The
strain diagram in Fig. (9) is shifted upward in eachcycle since the stress level in the tension zone ishigher than that in the compression zone. Hence, the𝛽𝛽𝑘𝑘 of cells in tension is higher.

the section after full unloading and verify the resultswith experimental data. Finally, the presented cyclic
model can be developed to simulate cyclic loading
accompanied by a sustained dead load which conflicts
with the full unload assumption currently used in thisstudy.
REFERENCES[1] Karpenko N. I., Eryshev V. A., and Latysheva E.
V., Stress-Strain Diagrams of Concrete Under
Repeated Loads with Compressive Stresses.
Procedia Eng., 111, 2015, pp. 371-377.
[2] Karpenko N. I., Mukhamediev T. A., and Petrov
A. N., The Initial and Transformed Stress-Strain
Diagrams of Steel and Concrete, Special
Publication,
Stress-Strain
Conditionfor
Reinforced Concrete Construction, Reinforced
Concrete Research Center, Moscow, 1986, pp. 725.
[3] Karpenko N. I., Mukhamediev T. A., and Petrov
A. N., The Use of Transformed Concrete StressStrain Diagrams in Construction Design, Special
Publication, The Limit State of Concrete andReinforced
Concrete
Construction,
Energyatomizdat, Leningrad, 1986, pp. 170-180.
[4] Alameh A. S. and Harajli M. H., Deflection of
Progressively Cracking Partially Prestressed
Concrete Flexural Members, PCI Journal, Vol. 34,
Issue 3, 1989, pp. 94-128.
[5] Oukaili N. K., Moment Capacity and Strength ofReinforced Concrete Members Using StressStrain Diagrams of Concrete and Steel, Journal ofKing Saud University, Engineering Sciences (2),Vol. 10, 1998, pp. 23-44.
[6] Rodriguez J. A. and Aristizabal-Ochoa J. D.,
Biaxial Interaction Diagrams for Short RC
Columns of Any Cross Section, Journal of
Structural Engineering, Vol. 125, No. 6, 1999, pp.
672-683.
[7] Charalampakis A. E. and Koumousis V. K.,
Ultimate Strength Analysis of Composite
Sections Under Biaxial Bending and Axial Load,
Advances in Engineering Software, Vol. 39, Issue
11, 2008, pp. 923-936.
[8] Chiorean C. G., A Computer Method for MomentCurvature Analysis of Composite Steel-Concrete
Cross-Sections of Arbitrary Shape, Engineering
Structures and Technologies, Vol. 9, Issue 1, 2017,
pp. 25-40.
[9] Kwak H. G. and Kim S. P., Nonlinear Analysis of
RC Beams Based On Moment-Curvature Relation,
Computers and Structures, Vol. 80, 2002, pp. 615628.
[10] Oukaili N.K., Strength of Partially Prestressed
Concrete Elements with Mixed Reinforcement by
Highly Strength Strands and Steel Bars, PhD
Thesis, Moscow Civil Engineering University,
Russia, 1991.

DISCUSSION

The present study demonstrates a promising
methodology for calculating the effect of repeatedloading on structural concrete sections. Sectional
analysis is a versatile technique for simulating beam
deformation under different types of loading.
Therefore, the development of this technique forcyclic loading will improve its accuracy. Although
the proposed method does not consider the frequency
of cyclic loading, a wide range of applications canemploy this technique. The proposed method can beeffectively used for simulating structural concrete
sections with prestressing strands [16]. For instance,
during the release of pre-tensioned steel, concreteelements near strands are compressed due to thetransfer of loading from strands. Therefore, theapplication of external load will eventually cause
unloading of the concrete elements in that zone. As aresult, traditional static sectional analysis overestimates beam capacity when using the stress-strain
relationship of static elements. This techniquerequires an improvement when the stress levelexceeds 0.83 of peak stress (𝜂𝜂 > 0.83). However,current results at a low-stress level are quite
encouraging.
CONCLUSIONSThis paper presents an analytical methodology
for the analysis of structural concrete sections undercyclic loading. Karpenko et al.’s cyclic model [1] isemployed to simulate the stress-strain relationship ofconcrete elements under repeated loads. Furthermore,
the Bernoulli–Navier assumption is utilised toperform sectional analysis of finite discretised
concrete sections of arbitrary shape. A software
package developed to perform the proposed analysis
is also presented. Finally, a tee-shaped beam section
is implemented to illustrate the output. The momentcurvature diagram is generated and the strain vector
observed at different cycles. The analysis results
show an increase in the curvature during each cycle.
After cracking, the change in curvature follows abilinear relationship because the increase in curvaturein the subsequent cycles is vanished rapidly due to thelow-stress amplitude of the cells in compression.
Further research could be conducted to upgrade thepresent methodology to consider the residual strain in
15

SEE - Kyoto, Japan, Nov.18-20, 2020[11] Oukaili N. K., Model for Predicting the Cracking
Moment in Structural Concrete Members, Abhath
Al-Yarmouk Basic Science & Engineering –AYBSE, Vol. 8, Issue 2, 1999, pp. 9-39.
[12] Oukaili N. K. and Al-Shawi I. N., Strengthening
and Closing Cracks for Existing Reinforced
Concrete Girders Using Externally PostTensioned Tendons, Journal of Engineering,
University of Baghdad, Vol. 19, 2013, pp. 13541374.
[13] Python Language Documentation, V. 3.8.2,

https://docs.python.org/3/.
[14] Gmsh
documentation,V.
4.5.6,
http://gmsh.info/doc/texinfo/gmsh.html.
[15] NumPy Package Documentation, V. 1.18.1,
https://numpy.org/doc/.
[16] Peera I. and Oukaili N., Methodology for
Monitoring the Flexural Behavior of Structural
Concrete Members with Unbonded Internal Steel,International Journal of GEOMATE, Vol.18,
Issue 69, 2020, pp. 9-17.

16

6th Int. Conf. on Geotechnique, Construction Materials and Environment,
Kyoto, Japan, 18-20 November 2020, ISBN: 978-4-909106049 C3051

QUANTITATIVE EVALIATION OF BUCKLING STRENGTHOF DAMAGED PLATES
Hani Doummar and Yoshitaka Suetake
Civil engineering, Ashikaga University, Japan.

ABSTRACTThe main aim of this paper is to investigate an approach to evaluate buckling strength of plates that have achange in their thickness. In general, all structural members can have a change in cross section for several reasons.
For example, architectural esthetic reasons, necessity to serve the design, and changes either by slow damage
factors due to severe service environment or sudden damage like accident or explosion in case of war. In case ofdamaged members, it is required that the plate members maintain their original performance as much as possible.
This goal can be achieved by estimate the level of damage that happens to the cross section of members after theincident. In this research, we deal with damaged plates which are subjected to a partial loss in cross sections. The
damage is represented by step-formed change in cross section due to reduction of plate thickness at the area of thedamage. A criterion is needed to evaluate this state of change. In the present investigation Damage Index is
introduced by using critical loads of the plate buckling. Many numerical examples are demonstrated, in which
thickness and area of the damaged parts are changed in wide range. The damage level, in which plate members areusable, can be evaluated from the results of the damage index.

Keywords: Plate, Buckling load, Damage index, Variation in thickness.
is based on the change of stiffness before and after theoccur of damage as a status quo.

INTRODUCTION
In the recent decades, after the worldwide
expansion in the sector of infrastructures andstructural construction. The managers of thesestructures face a major problem represented by
specify the criteria to evaluate the amount ofdepreciation, that was exposed to during its period ofservice and affect directly the decision tacked byrenovation or replacement and reflect directly on the
final cost. This challenge encourage the researcher
to study in deep several kinds of deterioration factors
under its related service circumstances that cause thelost in cross section.
The damage can be classified by the duration of
exposure, as sudden damages in structures provokedby sudden short-term incidents for example
earthquakes [1] and fire, or long term effects that thestructure is undergoing during its life service-circle
like chemical deterioration, loading history [2] static
steady or repeating cycles accompanied with overloading.
Recently, the studies distinguish between theassessment the amount of damage that structures as
whole and specific structural elements in precise toevaluate the usefulness of the remain section by
develop several kinds of indices depending onparameters that contribute in the sustain of thesubjected element.
In this paper, in-plane buckling strength ofdamaged plates is dealt with, in which all sides of aplate are simply supported. The factor chosen toevaluate the damage called the damage index DI that

METHODOLOGY
It is substantial to clarify the methodology
adopted in this paper. By using the energy method, it
is possible to obtain the magnitude of the bucklingload, K, for the plate of both the original and thedamaged state under the uniaxial buckling load.
Subsequently, the levels of damage to the plate are
evaluated by applying the damage index.
Energy method
To specify the critical load of plates. This paper
employ the principle of energy method [3] that isdenoted by the following equation∆𝐔𝐔 = ∆𝐓𝐓

(1)

where ∆𝐔𝐔 is defined as the strain energy and ∆𝐓𝐓 is
the potential energy of load.
In case of a rectangular plate with constant
thickness, all edges are simply supported, thedeflection surface can be represented by the double
trigonometric series, so called double Fourier series,
determined by the Eq. (2) [3]∞𝛚𝛚 = ∑∞
𝐦𝐦=𝟏𝟏 ∑𝐧𝐧=𝟏𝟏 𝐚𝐚𝐦𝐦𝐦𝐦 𝐬𝐬𝐬𝐬𝐬𝐬

17

𝐦𝐦𝐦𝐦𝐦𝐦𝐚𝐚

𝐬𝐬𝐬𝐬𝐬𝐬𝐧𝐧𝐧𝐧𝐧𝐧𝐛𝐛(2)

SEE - Kyoto, Japan, Nov.18-20, 2020

where 𝐚𝐚𝐦𝐦𝐦𝐦 is the maximum deflection which remains
indefinite provided we consider it small and neglect
stretching the middle plane of the plate during
buckling. This series expression satisfies theboundary conditions of the simply supported plates.
For simplification, we set the width of plate b isconstant as a result n=1. In this case, the relation
becomes the following:𝛚𝛚 = 𝐚𝐚𝐦𝐦𝐦𝐦 𝐬𝐬𝐬𝐬𝐬𝐬

𝐦𝐦𝐦𝐦𝐦𝐦𝐚𝐚

𝐬𝐬𝐬𝐬𝐬𝐬𝛑𝛑𝛑𝛑which the number of the half-wave of the bucklingmode is changed from m=1 to m=5.
Figure 1 obtained by [3] represents the relation
between a/b and K. It can be seen from Fig. 1 that all
curves for different values of the half-wave number
m have the minimum value K=4. In later sections, thisvalue of K=4 is employed as 𝐊𝐊 𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 .

𝐛𝐛

8This means that the plate buckles in such a way that
there can be several half-wave in length direction and
one half-wave in width direction.
The strain energy ∆𝐔𝐔 is given by:

6

K

𝟐𝟐

𝐚𝐚 𝐛𝐛
𝟏𝟏
𝛛𝛛𝟐𝟐 𝛚𝛚 𝛛𝛛𝟐𝟐 𝛚𝛚
𝐃𝐃 � � �� 𝟐𝟐 + 𝟐𝟐 �
𝟐𝟐 𝟎𝟎 𝟎𝟎
𝛛𝛛 𝐱𝐱 𝛛𝛛 𝐲𝐲∆𝐔𝐔 =𝛛𝛛𝟐𝟐 𝛚𝛚 𝛛𝛛𝟐𝟐 𝛚𝛚− 𝟐𝟐(𝟏𝟏 − 𝐯𝐯) � 𝟐𝟐

𝛛𝛛 𝐱𝐱 𝛛𝛛𝟐𝟐 𝐲𝐲

m=1
m=2
m=3
m=4
m=5

10

(3)

−�

𝛛𝛛𝟐𝟐 𝛚𝛚

20𝟐𝟐

� � 𝐝𝐝𝐝𝐝𝐝𝐝𝐝𝐝�

𝛛𝛛𝛛𝛛𝛛𝛛𝛛𝛛

4

(4)

0

After substituting of Eq. (2) into Eq. (4), we have∆𝐔𝐔 =𝐃𝐃 𝛑𝛑𝟒𝟒 𝐦𝐦𝟐𝟐 𝐚𝐚

𝐦𝐦𝐦𝐦

𝐚𝐚𝟑𝟑 𝐛𝐛 𝟑𝟑

𝟖𝟖

𝟐𝟐

�𝐛𝐛𝟐𝟐 +

𝟐𝟐
𝐚𝐚𝟐𝟐
𝐦𝐦

�

𝟐𝟐

𝛛𝛛𝟐𝟐 𝛚𝛚
𝛛𝛛𝟐𝟐 𝛚𝛚
𝟏𝟏 𝐚𝐚 𝐛𝐛
∆𝐓𝐓 = � � �𝐍𝐍𝐱𝐱 � 𝟐𝟐 � + 𝐍𝐍𝐲𝐲 � 𝟐𝟐 �
𝛛𝛛 𝐱𝐱
𝛛𝛛 𝐱𝐱
𝟐𝟐 𝟎𝟎 𝟎𝟎
+𝟐𝟐𝐍𝐍𝐱𝐱𝐱𝐱 �𝛛𝛛𝛛𝛛 𝛛𝛛𝛛𝛛
𝛛𝛛𝛛𝛛 𝛛𝛛𝛛𝛛� � 𝐝𝐝𝐝𝐝𝐝𝐝𝐝𝐝

𝟏𝟏𝐚𝐚𝛛𝛛𝟐𝟐 𝛚𝛚

𝐛𝐛

𝟐𝟐

𝟐𝟐

𝐃𝐃 =

𝛑𝛑𝟐𝟐 𝐛𝐛
𝟖𝟖 𝐚𝐚

𝐃𝐃𝐃𝐃 = 𝟏𝟏 −

(8)

𝟐𝟐

𝐛𝐛

𝐚𝐚

𝐦𝐦𝐦𝐦

𝟐𝟐

(9)

This equation also can be represented:
𝟐𝟐

� 𝐗𝐗 = 𝐊𝐊 𝛑𝛑 𝟐𝟐𝐃𝐃 ; 𝐊𝐊 = �𝐦𝐦𝐦𝐦 + 𝟏𝟏 �
𝐍𝐍
𝐛𝐛

𝐦𝐦𝐦𝐦

𝟐𝟐

, 𝛄𝛄 =

𝐚𝐚

𝐛𝐛

(11)

𝐊𝐊𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟

𝐊𝐊𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢(12)

where 𝐊𝐊 𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟𝐟 represents the stiffness of the damaged
element, the 𝐊𝐊 𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢𝐢 is the original stiffness (initialslope of behavior) of the element before incident.
The previous shape of DI in Eq. (12) can be� 𝐗𝐗 obtained from theobtained easily using the 𝐍𝐍�energy method [3] and 𝐍𝐍𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 derived later for
one change and two changes in cross-section.

Substituting the results into Eq. (1), we obtain the� 𝐗𝐗 as shown the following equation:
critical load 𝐍𝐍
� 𝐗𝐗 = 𝛑𝛑 𝟐𝟐𝐃𝐃 �𝐦𝐦𝐦𝐦 + 𝐚𝐚 �𝐍𝐍

6

The index that will be used in this study is the
response-based damage index so-called Damage
Index or shortly DI. DI can be distinguished into threesorts according to the factors that it considers: (a)maximum deformation. (b) cumulative damage. (c)maximum deformation and cumulative damage.
The damage index [1] that fit with the requires ofthis study, it defined by:

(7)

� 𝐗𝐗
𝐦𝐦𝟐𝟐 𝐚𝐚𝐦𝐦𝐦𝐦 𝟐𝟐 𝐍𝐍

𝐄𝐄𝐡𝐡𝟑𝟑𝟏𝟏𝟏𝟏(𝟏𝟏−𝛎𝛎)

The damage index:(6)

Therefore, we have
∆𝐓𝐓 =

4

When the buckling load was determined, the value ofPoisson’s ratio set as 𝜈𝜈 =0.3. And the flexural rigidity
D is defined by the Eq. (11) [4].

In this study, the loading is apply in the x direction
only, therefore 𝐍𝐍𝐱𝐱 ≠ 𝟎𝟎 but both 𝐍𝐍𝐲𝐲 = 𝐍𝐍𝐱𝐱𝐱𝐱 = 𝟎𝟎.
∆𝐓𝐓 = ∫𝟎𝟎 ∫𝟎𝟎 �𝐍𝐍𝐱𝐱 � 𝟐𝟐 � � 𝐝𝐝𝐝𝐝𝐝𝐝𝐝𝐝
𝟐𝟐
𝛛𝛛 𝐱𝐱

a/b

Fig.1 Curves of factor K.

(5)

The potential energy ∆𝐓𝐓 is given by:2

� 𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃
𝐍𝐍

𝐃𝐃𝐃𝐃 = 𝟏𝟏 − �(10)𝐍𝐍𝐗𝐗 𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒(13)

� 𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 represents the critical load of thewhere 𝐍𝐍� 𝐗𝐗 𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 is the critical load ofdamaged plate and 𝐍𝐍
the plate in the original state before the incident.

The factor K represents the magnitude of the bucklingload. Curves of the factor K are drawn in Fig. 1, in

18

SEE - Kyoto, Japan, Nov.18-20, 2020

𝟏𝟏
𝐚𝐚𝟏𝟏
𝟐𝟐𝟐𝟐𝟏𝟏−
𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 ��
��
𝐚𝐚
𝐚𝐚
𝐦𝐦𝐦𝐦
1
a1
t 2 3 a − 2a1+�sin �2mπ ����+� � �
t1
aamπ

The physical interpretation of this index presented
by [5] is clarified in Table 1.
Table 1 The physical interpretation of DI.
Degree ofDamageCollapse
SevereModerate
SlightDamage Index,
DI
𝐃𝐃𝐃𝐃 > 𝟏𝟏
𝟏𝟏 > 𝐃𝐃𝐃𝐃 > 𝟎𝟎. 𝟒𝟒
𝐃𝐃𝐃𝐃 < 𝟎𝟎. 𝟒𝟒
𝐃𝐃𝐃𝐃 < 𝟎𝟎. 𝟐𝟐

+

State
Loss of building
Beyond repair
Reparable

𝐦𝐦𝐦𝐦

𝐭𝐭

𝟑𝟑

𝐚𝐚

�𝟏𝟏 − � 𝟐𝟐 � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟏𝟏��
𝐭𝐭 𝟏𝟏

(14)

𝐚𝐚

By substituting ∆𝐔𝐔 the in Eq. (1) the critical load� 𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 is denoted as 𝐍𝐍
� 𝐗𝐗 𝐃𝐃 in the following relation𝐍𝐍
𝛑𝛑𝟐𝟐 𝐃𝐃𝟏𝟏𝟏𝟏 𝟐𝟐 𝐭𝐭 𝟐𝟐 𝟑𝟑
��𝐦𝐦𝐦𝐦 +� �� �
𝟐𝟐
𝐛𝐛
𝐭𝐭 𝟏𝟏
𝛄𝛄𝛄𝛄
𝟑𝟑
𝟐𝟐𝟐𝟐𝟏𝟏
𝟏𝟏
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐
−
𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 ���+ �𝟏𝟏 − � � � �
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐚𝐚
𝐦𝐦𝐦𝐦

� 𝐗𝐗 𝐃𝐃 =𝐍𝐍

THE STUDIED CASES:

This paper studies two cases of change in crosssection due to happening damage, for one or twochanges in thickness, by applying the same boundaryand loading conditions for simply supported
rectangular plate, subjected in the middle plane byforces uniformly distributed along the sides x=0 and
x=a [3]. As numerical models, two types of damaged
plates were adopted. The first is a two-steps model asshown in Fig. 2 (Model A); the second is a three-steps
model as shown in Fig. 3 (Model B).

+

a1

t1

t2

t1

𝟑𝟑

𝐭𝐭

𝐚𝐚

�𝟏𝟏 − � 𝟐𝟐� � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟏𝟏��
𝐭𝐭 𝟏𝟏

(15)

𝐚𝐚

𝟏𝟏 𝟐𝟐 𝐭𝐭 𝟐𝟐 𝟑𝟑
� �� �
𝐭𝐭 𝟏𝟏𝛄𝛄𝛄𝛄
𝐭𝐭 𝟐𝟐 𝟑𝟑 𝟐𝟐𝟐𝟐𝟏𝟏
𝟏𝟏
𝐚𝐚𝟏𝟏+ �𝟏𝟏 − � � � �−𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 ���
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐚𝐚
𝐦𝐦𝐦𝐦
+

𝟒𝟒(𝟏𝟏−𝐯𝐯)
𝐦𝐦𝐦𝐦

𝐭𝐭

𝟑𝟑

𝐚𝐚

�𝟏𝟏 − � 𝟐𝟐� � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟏𝟏��
𝐭𝐭 𝟏𝟏

𝐚𝐚

(16)

After the substitution of 𝐊𝐊 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 and 𝐊𝐊 𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 in
the relation of DI can be represented in Eq. 17.
𝐭𝐭 𝟐𝟐 𝟑𝟑
𝐃𝐃𝐃𝐃 = 𝟏𝟏 − ��� �
𝐭𝐭 𝟏𝟏
𝟏𝟏
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑 𝟐𝟐𝟐𝟐𝟏𝟏−
𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 ���+ �𝟏𝟏 − � � � �
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐚𝐚
𝐦𝐦𝐦𝐦

a
a2

𝐦𝐦𝐦𝐦

𝐊𝐊 𝐃𝐃 = ��𝐦𝐦𝐦𝐦 +This applied change in the internal part wherein
the plate is symmetric about a plane at its half-length.
Fig. 2 shows the dimensions of parts of a damaged
plate in case of one change in thickness.
a1

𝟒𝟒(𝟏𝟏−𝐯𝐯)

� 𝐗𝐗 in Eq. 15 with the relation
By comparing the 𝐍𝐍�of the 𝐍𝐍𝐗𝐗 in Eq. 10, the value of K in case of one
change in thickness is shown in the Eq. 16.

One change in thickness

X

+

Z

𝟒𝟒(𝟏𝟏−𝐯𝐯)

𝐦𝐦𝐦𝐦�𝐦𝐦𝐦𝐦+

𝟏𝟏 𝟐𝟐
�
𝛄𝛄𝛄𝛄

𝐭𝐭

𝟑𝟑

𝐚𝐚

�𝟏𝟏 − � 𝟐𝟐� � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟏𝟏��
𝐭𝐭 𝟏𝟏

(17)

𝐚𝐚

Two changes in thickness

Fig. 2 Plate with one change in thickness.

In this case, the applied change in thickness in theinternal zone where the plate is symmetric about aplane at the half-length of the plate. The first changeof the plate thickness is t 2 , applied on length a 2 , will
be calculated for each of the following cases t 2 /t 1 are
20%, 40%, 60%, 80% separately and the middle part
percentage of change in thickness t 3 /t 1 = 0.5 t 2 /t 1 isthe half of each of the previous percentage
respectively, applied on length a 3 .

Figure 2 shows a longitudinal section in
simply supported plate symmetric about aplane normal on the mid-plane of the plate. The
original thickness of the plate is t 1 and t 2 is the
thickness of the plate after the damage
happens. The calculated proportions t 2 /t 1 were20%, 40%, 60%, 80% of the original thickness.
In this case, a 1 defined as the non-damaged length
on both opposite sides near the supports of the plate.
a 2 is the length of the middle damaged part. The
length ratios of Model A are as follows: (A1)a1/a=0.1, (A2) a1/a=0.2, (A3) a1/a=0.3, and (A4)a1/a=0.4.
By using the energy method, the internal energy
can be represented in the following equation.
∆𝐔𝐔 =𝟒𝟒(𝟏𝟏−𝛝𝛝)𝐃𝐃𝟏𝟏𝐦𝐦𝟐𝟐 𝛑𝛑𝟒𝟒 𝐦𝐦𝐦𝐦
𝐚𝐚 𝟐𝟐
𝐚𝐚𝐦𝐦𝐦𝐦 𝟐𝟐 𝟐𝟐 𝟐𝟐 ��
+
�
𝟖𝟖
𝐚𝐚 𝐛𝐛
𝐚𝐚
𝐦𝐦𝐦𝐦

a1

a2

a
a3

a2

a1

t1

t2

t3

t2

t1

X

Z

Fig. 3 Plate with two changes in thickness.
19

SEE - Kyoto, Japan, Nov.18-20, 2020

This figure shows the change in thickness and thelengths of these changes that is symmetrical about aplane normal on the middle plane of plate. And thelength ratios of Model B: (B1) (a1/a, a2/a) = (0.1,0.1),(B2)(a1/a, a2/a)=(0.1,0.2), (B3) (a1/a, a2/a)=(0.1,0.3),(B4) (a1/a,a2/a)=(0.2,0.1), (B5) (a1/a, a2/a)=(0.2,0.2),
and (B6) (a1/a, a2/a)=(0.3,0.1).
Using the energy method, the internal energy canbe represented in the following equation

those curves obtained from the present numericalcalculations in the group (A2) when t1/t=0.2.
5
4

K 3
2
1

𝐦𝐦𝟐𝟐 𝛑𝛑𝟒𝟒 𝐦𝐦𝐦𝐦
𝐃𝐃𝟏𝟏
𝐚𝐚 𝟐𝟐 𝐚𝐚𝟏𝟏
𝐚𝐚𝟐𝟐 𝐭𝐭 𝟐𝟐 𝟑𝟑
𝐚𝐚𝐦𝐦𝐦𝐦 𝟐𝟐+
� �𝟐𝟐 +𝟐𝟐 � �
��
𝟖𝟖
𝐚𝐚𝐚𝐚
𝐚𝐚
𝐚𝐚 𝐭𝐭 𝟏𝟏𝐚𝐚
𝐦𝐦𝐦𝐦
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏 𝐭𝐭 𝟑𝟑 𝟑𝟑+ �𝟏𝟏 − 𝟐𝟐
�� �
𝐚𝐚
𝐭𝐭 𝟏𝟏
𝟏𝟏
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑−
��𝟏𝟏 − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 �
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐦𝐦𝐦𝐦

∆𝐔𝐔 =

𝟒𝟒(𝟏𝟏−𝐯𝐯)
𝐦𝐦𝐦𝐦

𝐚𝐚

𝐭𝐭

𝐚𝐚 +𝐚𝐚𝟏𝟏+ 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟐𝟐

𝐚𝐚

𝐚𝐚

𝐭𝐭

𝐭𝐭 𝟏𝟏
𝐭𝐭 𝟑𝟑

𝟑𝟑

� �� 𝟐𝟐 � − � 𝟑𝟑 � ���
𝐭𝐭 𝟏𝟏

𝐭𝐭 𝟏𝟏

(18)

𝛑𝛑𝟐𝟐 𝐃𝐃𝟏𝟏 𝐦𝐦𝐦𝐦
𝐚𝐚 𝟐𝟐 𝐚𝐚𝟏𝟏
𝐚𝐚𝟐𝟐 𝐭𝐭 𝟐𝟐 𝟑𝟑+
� �𝟐𝟐 +𝟐𝟐 � �
��
𝐛𝐛 𝟐𝟐
𝐚𝐚
𝐚𝐚 𝐭𝐭 𝟏𝟏𝐚𝐚
𝐦𝐦𝐦𝐦
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏 𝐭𝐭 𝟑𝟑 𝟑𝟑+ �𝟏𝟏 − 𝟐𝟐
�� �
𝐚𝐚
𝐭𝐭 𝟏𝟏
𝟏𝟏
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑−
��𝟏𝟏 − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 �
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐦𝐦𝐦𝐦

� 𝐗𝐗 𝐃𝐃 =𝐍𝐍+ 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐

𝐚𝐚𝟐𝟐 +𝐚𝐚𝟏𝟏
𝐚𝐚

𝐭𝐭 𝟐𝟐 𝟑𝟑

𝐭𝐭 𝟑𝟑 𝟑𝟑� �� � − � � ���
𝐭𝐭 𝟏𝟏

𝐭𝐭 𝟏𝟏

DI

𝐚𝐚

𝐭𝐭

𝟑𝟑

𝐭𝐭

𝟑𝟑

� �� 𝟐𝟐 � − � 𝟑𝟑 � ���
𝐭𝐭 𝟏𝟏

𝐭𝐭 𝟏𝟏

NUMERICAL RESULTS

m=4

0.70
0.60
0.50

(19)

0.40

0.2

m=1

𝐦𝐦𝐦𝐦
𝐚𝐚 𝟐𝟐 𝐚𝐚𝟏𝟏
𝐚𝐚𝟐𝟐 𝐭𝐭 𝟐𝟐 𝟑𝟑
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏 𝐭𝐭 𝟑𝟑 𝟑𝟑+
� �𝟐𝟐 +𝟐𝟐 � � + �𝟏𝟏 − 𝟐𝟐
�� �
𝐚𝐚
𝐦𝐦𝐦𝐦
𝐚𝐚
𝐚𝐚 𝐭𝐭 𝟏𝟏𝐚𝐚
𝐭𝐭 𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑𝐚𝐚𝟏𝟏
𝟏𝟏
��𝟏𝟏 − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 �
−
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐦𝐦𝐦𝐦

𝐚𝐚 +𝐚𝐚𝟏𝟏

m=3

0.80

0.4 t2/t1
m=2

0.6

0.8

m=3

m=4

Fig. 5 DI of group (A1) with one step.

𝐊𝐊𝐃𝐃 = ��+ 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟐𝟐

m=2

8

0.90

� 𝐗𝐗 inComparing with relation of the shape the 𝐍𝐍
Eq. 10, the value of K in case of two change inthickness is shown in the Eq. (20).

𝐭𝐭 𝟑𝟑 𝟑𝟑
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑���+ �� � − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐
𝐭𝐭 𝟏𝟏
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑
𝟒𝟒(𝟏𝟏 − 𝐯𝐯)
��𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 � �𝟏𝟏 − � � ��
+
𝐦𝐦𝐦𝐦
𝐚𝐚
𝐭𝐭 𝟏𝟏

6

a/b

Notably, that the minimum values of curves differ
following the diverse of m. This tendency is different
from the result in Fig. 1, which is the case ofundamaged plate obtained in [3]. This behavior issimilar in all studied cases.
The next figures of DI, Fig. 5 to 8, for one change
in thickness are classified using the proportion of
non-damaged length a 1 /a into four groups.

By substituting ∆𝐔𝐔 the in Eq. (1) the critical load� 𝐗𝐗 𝐃𝐃 = 𝐍𝐍� 𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃� 𝐗𝐗 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 .Where 𝐍𝐍
is 𝐍𝐍

𝐭𝐭 𝟐𝟐 𝟑𝟑
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏
𝐭𝐭 𝟑𝟑 𝟑𝟑
+ �� � − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐
���
𝐭𝐭 𝟏𝟏
𝐭𝐭 𝟏𝟏
𝐚𝐚
𝟒𝟒(𝟏𝟏 − 𝐯𝐯)
𝐚𝐚𝟏𝟏
𝐭𝐭 𝟐𝟐 𝟑𝟑+
��𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 � �𝟏𝟏 − � � ��
𝐚𝐚
𝐭𝐭 𝟏𝟏
𝐦𝐦𝐦𝐦

4

Fig. 4 Curves of factor K for (A4), t 2 /t 1 =0.2.

𝟑𝟑��𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐 𝟏𝟏 � �𝟏𝟏 − � 𝟐𝟐 � ��2
m=1

𝐭𝐭 𝟐𝟐 𝟑𝟑
𝐚𝐚𝟐𝟐 + 𝐚𝐚𝟏𝟏
𝐭𝐭 𝟑𝟑 𝟑𝟑
+ �� � − � � � 𝐬𝐬𝐬𝐬𝐬𝐬 �𝟐𝟐𝟐𝟐𝟐𝟐
���
𝐭𝐭 𝟏𝟏
𝐭𝐭 𝟏𝟏
𝐚𝐚
+

0

0.8
0.7
0.6

DI 0.5

(20)

0.4
0.3
0.2

In this section, the numerical values of K and DI
are calculated for both cases of change in thickness.

0.2

0.4

m=1

m=2

t2/t1

0.6

0.8

m=3

m=4

One change in thickness
Fig. 6 DI of group (A2) with one step

The curves of factor K are classified into 4 cases
corresponding to m values. Figure 4 is an example of20

SEE - Kyoto, Japan, Nov.18-20, 2020

2.0

0.5
0.4

DI

0.3

1.0

0.2

K

0.1

0.0

0

0.2

0.4

0.6

0.8

m=1

m=2

m=3

m=4

t2/t1

0

2
m=1

4

6

8

m=3

m=4

a/b
m=2

Fig .9 Curves of K for (B1), t2/t1=0.8.
Fig. 7 DI of group (A3) with one step.
Figure 9 shows that in two changes in thickness theminimum value of each curve differs in case with thechange of m, while in case of the non-damaged
minimum K=4 for all m curves [3].
The next figures of DI, Fig. 10 to 15, for twochanges in thickness classified into six groups using
the proportion combination of lengths (a 1 /a, a 2 /a).

0.25
0.2

DI 0.15
0.1
0.05

0.9
0.85
0.2

0.4

m=1

m=2

t2/t1

0.6

0.8

m=3

m=4

0.8

DI 0.75
0.7
0.65
0.6

Fig. 8 DI of group (A4) with one step.

0.2
m=1

Referring to Table 1, we can find the physicalinterpretation of DI in each group. In Fig. 5 to Fig. 8,
no case is classified into “Collapse.” The damage
indices, DI, decrease with the increase of t 2 /t 1 . In allgroups, the most dangerous cases are when m=1.
Most cases of the group (A1) and 75% of the group(A2) are classified into “Sever.” In groups of (A2)and (A3), “Moderate” cases are observed. While only
two “Slight” cases appear in the group (A3), 11“Slight” cases can be found in the group (A4).

0.4 t2/t1

0.6

0.8

m=2

m=3

m=4

Fig. 10 DI of group (B1) Plate with Two steps.
0.9
0.8

DI 0.7
0.6

Two changes in thickness

0.5

The curves of the factor K and DI classified into
six groups defined previously by the proportion of
non-damaged length a 1 /a and a 2 /a.
As an example of K curves for two changes inthickness, the result of the case (B2), (a1/a, a2/a) =(0.1,0.2), is shown in Fig. 9.

0.2

0.4

0.6

0.8

m=1

m=2

m=3

m=4

t2/t1

Fig. 11 DI of group (B2) Plate with Two steps.

21

SEE - Kyoto, Japan, Nov.18-20, 2020

DI

0.9

0.5

0.8

0.45
0.4

0.7

DI 0.35

0.6

0.3

0.5
0.4

0.25
0.2
0.2

0.4

0.6

0.8

m=3

m=4

t2/t1
m=1

m=2

0.2
m=1

0.4 t2/t1 0.6
m=2
m=3

0.8
m=4

Fig. 15 DI of group (B6) Plate with Two steps.
Fig. 12 DI of group (B3) Plate with Two steps.

0.75
0.7
0.65
0.6
DI
0.55
0.5
0.45
0.4

In Fig. 15, half of cases are classified under a “severe
damage” case. The most dangerous cases occur whenm=1. And half of the Group (B6) is “Moderate.”
CONCLUSIONS

0.2

0.4

0.6

0.8

m=3

m=4

1) The introduced index DI for the damaged plates
under critical buckling loads is a useful
numerical evaluation to repair the damage. The
highest level of damage is “Severe” which means
all cases are repairable by different levels
2) The minimum curves values of the magnitude of
the buckling load K for specific number halfwave in damaged plate decreases with theincrease of the damage in both model.
3) In case of one change in thickness, the occurred
level of damage varied from “Severe” till “slight”
damage with the decrease of damage.
4) The dominant level of damage in the case of twochanges in thickness is “Severe” in all groups.
But cases of “Moderate” appear in (B5) and (B6)
in which the length of the damaged part isrelatively shorter and the reside section bigger.

t2/t1
m=1

m=2

Fig. 13 DI of group (B4) Plate with Two steps.

0.75
0.7
0.65
0.6
0.55
DI 0.5
0.45
0.4
0.35
0.3

REFERENCES

0.2

0.4 t2/t1

m=1

m=2

0.6

0.8

m=3

m=4

[1] Ghobarah A., Abou-Elfath, and Biddah A.
(1999). ” Response-based damage assessment ofstructures”, Earthquake Engineering andStructural Dynamics 28,79-104.
[2] ChungY.,MeyerC.
andShinozuka
M.(1987).”Seismic damage assessment ofreinforced concrete members”. Technical Report
NCEER-87-0022.Columbia University, USA.
[3] Timoshenko S. and Gere J. (1989).” Theory ofelastic stability”. Dover Publications, Inc. New
York, USA
[4] Yu, Chen. (2003). “Buckling of rectangular plates
under intermediate and end loads”. Master thesis,
National university of Singapore, Singapore.
[5] Park YJ, Ang AH, Wen YK, Damage-limiting aseismic design of buildings. Earthquake Spectra3(1);1-26.

Fig. 14 DI of group (B5) Plate with Two steps.
In Fig. 10 to Fig. 14, most cases are classified into
“severe” damage the highest when m=1. It is
notifiable that three “Moderate” damage cases inGroup (B5). There is no case classified under “Slight”
damage.

22

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

PERFORMANCE LEVEL PREDICTION OF STRUCTURE BUILDINGUSING LOG-SIGMOID METHODS
Muhammad Gala Garcya1, *Reni Suryanita2, Zulfikar Djauhari3 and Harnedi Maizir4
1,2,3
Civil Engineering Department, University of Riau, Indonesia;
4
Civil Engineering Department, Sekolah Tinggi Teknologi Pekanbaru*Corresponding Author
ABSTRACT
Earthquake is one of the biggest threats towards the building, so it needs to be designed with calculating theearthquake loads that happened. The finite elements can obtain the structure response such as displacement,
velocity, and acceleration that happened because of an earthquake. The study aims to predict structural damage
using structure response data with short relative analysis time than analyzing by each. The research used 5 (five)earthquake data with different high-intensity magnitude. The finite element generated ANN data is 14534 data. In
this research, the composition used for training, validating, and testing is 60%,15%, and 25% by each. The input
data consist of time, acceleration in x and y directions, velocity in x and y directions, and also displacement in x
and y directions. Meanwhile, the target data are structure performance determined by FEMA 356 and story drift
for x and y directions. The result indicated the regression value by ANN analysis reached 97,379%. Evaluation
results by ANN show that Log-sigmoid transfer functions are small enough and show the smallest error value(MSE) approximately 3,9774 E-07. Therefore, ANN analysis with the Log-Sigmoid transfer function can be used
to predict the performance level of the structure appropriately and accurately. The method can be recommended
tools for structural engineers and building designers in designing earthquake-resistant buildings.
Keywords: Structure Response, Structure damage, Log-Sigmoid Transfer Function, Mean Square Error (MSE)INTRODUCTION

saved.
ANN works by studying previous patterns topredict data later. ANN works like the human brain,
and the more practice makes the ability will increase
as well too. So, the more data are used, the level ofaccuracy generated by the ANN in predicting will
also be higher as well. Otherwise, getting a bit of data
will make the accuracy of the ANN will be lower.
ANN can predict many models, such as towers,
bridges, roads, and even road damage. And the main
target ANN utilization is to simplify and save time indesigning the structure for the future of mankind.

The development of human life was increased
rapidly and made the use of technology that aims tofacilitate human life from how to communicate until
to fulfil any daily needs. It can solve all kinds ofproblems and can be solved better and faster. Now,
the era of humans has entered the era of the Industrial
Revolution 4.0, where humans have solved the
problems of life only by utilizing technology, whichis to fulfil all kinds of problems by not needing towaste a lot of time but only in a very short time.
In the development of technology, there is a term
known as AI (Artificial Intelligence). AI has enteredinto human life in various forms and functions. One
product of AI is very useful in human life in terms ofdisaster mitigation, namely as Artificial Neural
Network (ANN). ANN is one of the AI products thatcan be used to predict building damage that occurs
due to natural disasters, which is one of them is anearthquake. Earthquakes are one of the biggest threatsthat occur in human life because earthquakes cannot
be predicted how long the intensity and duration up
to how much impact damage they cause. By using
ANN in predicting building damage index towards anearthquake, the condition of the building can be
known more quickly, and disaster evacuation will befaster to minimize the number of lives that are not

LITERATURE STUDIES
Modal Analysis
Variance analysis or commonly known as themodal analysis is an analysis that determines the
motion of the structure under the free vibration
conditions, where the motion is only influenced by
the initial conditions. This analysis is very importantbecause this analysis provides the dynamic nature
response of the most important in the structuraldesign is a natural period and mode shapes.
Free vibrations are vibrations that occur due to theoperation of forces on the structure itself without theforces occurring. The force acting on free vibration is
the weight of the structure itself. From this vibration
23

SEE - Kyoto, Japan, Nov.18-20, 2020

can be seen in the large frequency of a structure. The
natural frequency is very important to be taken into
account in the planning of the structure because thenatural frequency of the structure which is the sameas the external force (resonance) will be dangerous
for the structure that causes a collapse in the structure.
In SNI 1726-2019, a value of participating mass
ratio requirement has been set, which is a value that
explains the amount of participation of structuralcomponents to hold external forces. The value of themass participation ratio must be greater than 90%.
Time History Analysis
Earthquake analysis is divided into 2 (two)methods, which is a static analysis and dynamic
analysis (Chopra, 1995). In a structural analysis needs
to be done more thoroughly to obtain an economical
design. Generally, analysis of the structure of theearthquake is divided into 2 (two) types, namely:
In general, structural analysis of earthquakes isdivided into two types, namely:
1. Static analysis is an analysis where the effect ofan earthquake on a structure is considered as ahorizontal static load was obtained by only
calculating the natural frequency and period in thefirst shape mode.
2. Dynamic analysis is an analysis of the structure inwhich the division of earthquake shear forces at
all levels is obtained by taking into account the
dynamic influence of ground motion on the
structure. Dynamic analysis is divided into 2 (two)types, which are spectrum response analysis andtime history analysis.
In the time history analysis, the earthquake load
included in the loading of the structure is in the formof recorded ground motion data from the earthquakethat occurred. Dynamic analysis is used to obtain amore accurate evaluation of earthquake and structural
behaviour. Dynamic time history analysis is divided
into 2 (two) types, namely:
1. Dynamic analysis of linear time history
Dynamic analysis of linear time history is ananalysis of the dynamic response history of a 3dimensional building structure that behaves fully
elastic to the planned earthquake load.
2. Dynamic analysis of non-linear time history
Dynamic analysis of non-linear time history is ananalysis in which the dynamic response of 3dimensional building structures behaves in full elastic(linear) and elastoplastic (non-linear) behavior
against ground motion due to designed earthquake
loads.
Dynamic loads give responses that change withtime, therefore the structure will also vibrating or
moving when it occurred. Apart from that time,
history analysis can also cause deformation in the
structure as well as other burdens. The one thing that
can happen is the deviation between floors (story

drift). In SNI 1726-2019 article 7.12.1 concerninginter-floor level intersections have been regulated andcan be seen in the following Table 1.
Table 1 Allowed Story Drift, ∆aRisk Category
Structure
I or II
III
IV
Structure, apart from
the
shear
wall
structure brick, 4level, or less with theinterior
walls,
0,020 hsx
0,015 hsx
partitions, ceilings, 0,025 hsx
and exterior wall
systems that havebeen designed tofacilitate floor-level
drift.
Brick
cantilevered
0,010 hsx
0,010 hsx
0,010 hsx
shear wall structure.
Othercantilevered
0,007 hsx
0,007 hsx
0,007 hsx
shear wall structure.
All other structures.
0,020 hsx
0,015 hsx
0,010 hsx
Artificial Neural Networks
An artificial neural network or known as ANN isa system that has a way of working as the human brain,
this system can be modelled to predict complex things
between inputs and outputs to determine a specificpattern. The use of ANN produces a good approachin spectrum response analysis. So ANN is a tool thatcan recognize patterns and produce output based on
network weights in the training process.
In terms of function, ANN was created to design
a computer, which can be used to carry out theprocess of learning from an example of an event.
ANN has many methods for predicting values, one of
them
is
the
Backpropagation
method.
Backpropagation methods can estimate errors withgradient values for each network in the ANN
architecture. MATLAB Backpropagation is known asa feed-forward backpropagation because this method
learning data from the past to predict the value for the
future. This method has been widely used in
predicting such as flood discharge, water level, up to
the performance of a structure. So that the predicted
results that will affect the pattern that will occur.
The output generated by the function is activatedand calculated the number of errors generated. If theerror value has not reached the specified target, thenit needs to estimating by error square function or
known as Mean Square Error (MSE). MSE is a costfunction that forms quadratic parabolic shapes.
Activation
characteristics
functionofbackpropagation ANN must be continuous,
24

SEE - Kyoto, Japan, Nov.18-20, 2020

distinguishable, and monotonous does not go down.
In the backpropagation, the ANN calculation process,there are three counting processes, namely forward
calculation, backpropagation, and weight and bias
changes.
RESEARCH METHODOLOGY
Loads
Based on SNI 1727-2019, loads that used for thisbuilding divide into 2 (two) types, that are dead andlive loads. In this research using 1,92 kN/m2
distributed loads for dead and live loads on the firstfloor until the top of this building.

Fig. 2 Floor Plan Top View
Artificial Neural Network Steps

Modal Analysis Steps

ANN is a tool that used to calculating as biology
process like human brains. Human brains have many
neural networks and connect to each other. Thisalgorithm architecture has 3 (three) layers consistingof input, hidden, and output.
Other research illustrating networks give input
patterns as training patterns; the patterns lead tohidden layer units and be forwarded to output layers.
After this process, output layers will give a response
named as output networks when output did not
generate expected output, it will spread back to thehidden layer and forwarding to input layers. That’s
why this mechanism named as backpropagation
training.
Structure Response such as displacement,
velocity, and acceleration are collected will be used
as input data. Meanwhile, target data that will be usedis performance level data generated by finite element
software that used performance level based on FEMA
356. Nntool from licensed MATLAB is helping inpredicting the performance level of the building
without running all earthquake data one by one fromthe beginning. Output data generated from ANN
processed data will be plotted in the graph and shows
how much MSE data and R2 generated by the
networks. Furthermore, the result can be comparedwith the result from finite element software.

Modal analysis is needed to design the structureof the building. With modal analysis, the building
response towards external forces that happened canbe seen and characteristic of the building based on its
frequency and natural periods.
Time History Analysis StepsIn this analysis steps, it needs to design the
structure formerly with the standard that defined startfrom materials data, beam and column profiles, untilslab that strong against modal loads. After getting an
optimal dimension of the structure, earthquake data
were inputted into programs, and time history
analysis begins to start, but before these steps begin
to run, it needs to defined hinges value first. The value
needs to be inputted are IO = 0,003, Ls=0,012, and
CP=0,015. Time history analysis generated
performance level from the structure of the building
after earthquake loads from PEER were inputted. The
performance level of structure building and story driftthat happened needs to collect to be target data inneural network tools (nntool) from licensed
MATLAB.
Meanwhile, story drift that being an objective getsfrom calculating 2 (two) on the top of the building thatcan be seen in Figures 1 and 2 below.

RESULT AND DISCUSSIONS
Modal Analysis
Modal analysis means analyzing the structurefrom itself weight before external forces such as live
loads, dead loads, up to dynamics loads were
inputted. In this analysis can be seen how thestructure reacts when it holding of its own weight.
This analysis of the frequency and the natural periods
generated by the structure can be used in designing
the building. And furthermore, this analysis canprovide a capability percentage of the structuralelements that participating withstand external forces

Fig. 1 Building Side View
25

SEE - Kyoto, Japan, Nov.18-20, 2020

known as Mass Participation Ratio.
In this modal analysis can be seen how thestructure deformed starting from rotation, translation,
up to torsion. In first mode shapes that generated by
the software can be seen in Figure 3 below.

Time History Analysis
Time history analysis in this research is analyzing
the structure in linear and non-linear using earthquake
record data. From time history analysis results it
generated structure response value such as
acceleration, velocity, and displacement that
happened because earthquake data that were inputted.
Meanwhile, non-linear analysis can generate aperformance level of the structure that has been
regulated by FEMA 356 as a condition level value ofthe building. It is just from finite element software
only shows the joint that sustains damage against load
based on the criteria points that have been set.
Time history analysis can show performance levelfrom the that modeled structures. In this research,level observed every 0,01 seconds, it means theperformance of the structure being observed every
0,01 seconds is it has been damaged or yet because ofan earthquake. Time history analysis utilizing ahinges to determine damage index that tolerated by
FEMA 356 based on used materials. Acceptancecriteria used in this research can be seen in the
research methodology in the time history analysis
steps above. The output from time history analysis
can be seen in Figure 4 below.

Fig. 3 First Mode Shapes generated by Modal
AnalysisWith 12 mode shapes is done at first mode with
3,882 cycle/sec frequency and 0,257 seconds natural
periods were obtained. So the conclusion that can betaken is the structure need 0,257 second to dotranslation. For other frequency and periods values,
can be seen in Table 2 below.
Table 2 Result of Natural Periods and Frequency
Mode
Frequency
Periods
Shapes(cyc/sec)(sec)
10.25754
3.882835
20.26965
3.708535
3
0.302
3.31120740.89595
1.1161450.89827
1.113253
60.96005
1.041608
7
1.47850.676378
1.48750.672252
9
1.5847
0.6310310
2.02130.494734
11
2.0362
0.491121
12
2.16290.462342

Fig. 4 Performance level result using time history
analysis
FEMA 356 has assigned a damage index valuethat is tolerated in some categories, that is IO, LS, CP.
This analysis shows the joint that was damaged by theearthquake loads. This analysis shows theperformance levels such as the damage index by
FEMA 356 and the story drift that happened.
The data shows that the building suffered different
damage each earthquake that occurred, but from thevarious earthquake data entered no story drift
exceeded the specified limit that is less than 0,100 m(0,025 hsx).

In SNI 1726-2019 mass participation ratio is notallowed below 90%, and this analysis has reachedmore that requirement value, which means more than
90% of the structure element has participating
withstand external forces. The value generated by thisanalysis can be seen in Table 3 below.
Table 3 Result of Mass Participation Ratio
Modal Analysis
StaticDynamic
Direction
Percent
Percent
UX
99.991799.2717UY
99.991799.2903
UZ
0.00140.00007043

ANN with Log-Sigmoid
Log-sigmoid running with calculating an output
layer from its input itself. This function carrying input
26

SEE - Kyoto, Japan, Nov.18-20, 2020

value to output by log-sigmoid calculation. This
analysis generates MSE value of 3,9774 E-07 so theanalysis being stopped because the analysis result hasreached defined parameters.
In figure 5 below can be seen that training data
generated by 97,681%, testing data of 95,153%,
validating data of 97,591% and for all is 97,379%.
This analysis can be concluded that data have reliablevalue and fairly accuracy that is 90%, and regression
line data approached the desirable line so prediction
value by using the log-sigmoid function is credible.
The result generated by this analysis can be seen in
the graph in Figure 5 below.

The original and predicted value of the structure
performance level used in ANN analysis didn't showmuch difference.
CONCLUSION
Based on the analysis that has been done, here thefollowing conclusions below.
1. Modal analysis, from this analysis frequency
generated by the software, is 0,257 cycle/seconds
and periods of 3,882 seconds. Meanwhile, themass participation ratio has reached a defined
standard by that is SNI 1726-2019 is more than90%.
2. Time history analysis that has been done, someearthquake data shows damage structure up to
more than collapse prevention (CP) index levels.
3. Story drift that occurred by the analysis, nothingis exceeded defined value by the SNI 1726-2019
that is 0,100 m (0,025 hsx).
4. ANN analysis using Log-sigmoid analysis shows
97,379% regression value (R2) and 3,9774 E-07
MSE, it means analyze using Log-Sigmoid
function generated reliable data.
REFERENCES[1] Adnan, A., Suryanita, R. (2012). Intelligent
Monitoring System on Prediction of Building
DamageIndex
using
Neural-Network.
TELKOMNIKA, 10(1). 155-164[2] American Society of Civil Engineers (ASCE);
Federal Emergency Management Agency(FEMA). (2000). FEMA 356 Prestandard.
[3] Chopra, A.K. (2012). Dynamics of Structures.
University of California at Berkeley.
[4] Indonesian National Standard 03-1727-2013.
(2013). Minimum for the Design of Buildings
and others structure.
[5] Indonesian National Standard 03-2847-2013.
(2013). Structural Concrete Requirements for
Buildings.
[6] Indonesian National Standard 03-1726-2019.
(2019). Earthquake resistant design proceduresfor building and nonbuilding structures.
[7] Inel, M. (2007). Modeling ultimate deformation
capacity of RC columns using artificial neuralnetworks. 29, 329–335.
[8] Richard, O., Lautour, D., & Omenzetter, P.
(2009). Prediction of seismic-induced structural
damage using artificial neural networks.
Engineering Structures, 31(2), 600–606.
[9] Vazirizade, S. M., Nozhati, S., & Zadeh, M. A.
(2017). Seismic reliability assessment ofstructures using artificial neural network.
Journal of Building Engineering, 11(November2016), 230–235.

Fig. 5 Result of Log-Sigmoid Analysis
Regression Graph Plots
From the analysis can be seen comparison of story
drift value predicted by the ANN and the original dataas can be seen in Figure 6 and 7 below.

Fig. 6 Story drift Originals vs Log-Sigmoid
Predict X direction

Fig. 7 Story drift Originals vs Log-Sigmoid
Predict Y direction
27

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

PERFORMANCE ANALYSIS OF LIGHTWEIGHT CONCRETE
BRICKS DUE TO EXPOSURE HIGH TEMPERATURE USING
EXPERIMENTAL STUDY
Reni Suryanita1, Yohannes Firzal2, Harnedi Maizir3, Imam Mustafa4, Mohd Fadzil Bin Arshad5
Civil Engineering Department, University of Riau, Kampus Binawidya Jl. HR Soebrantas KM 12,5, Pekanbaru,
28000, Indonesia
2
Architecture Department, University of Riau, Kampus Binawidya Jl. HR Soebrantas KM 12,5, Pekanbaru,
28000, Indonesia
3
Civil Engineering Department, Sekolah Tinggi Teknologi Pekanbaru, Jl. Dirgantara No.4, Pekanbaru, 28000,
Indonesia
4Civil Engineering Department, University of Riau, Kampus Binawidya Jl. HR Soebrantas KM 12,5, Pekanbaru,
28000, Indonesia
5
Faculty of Civil Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia
1

ABSTRACT
Generally, the effort to make the building load lighter is to use Cellular Lightweight Concrete bricks (CLC) on
wall components. CLC bricks contain pores, so the weight is less than red-bricks. Changes in temperature due tobuilding fires have an impact on the characteristics and performance of CLC bricks, especially in density,
compressive strength and visual shape of the brick. The research aims to analyse the performance of CLC bricks;
compressive strength and appearance of brick surfaces after exposure to high temperatures. The CLC brick model
size was 60 cm length, 10 cm width, and 20 cm height. Variation of temperature exposure time is 10 minutes, 20
minutes, 30 minutes and 40 minutes. CLC bricks are placed close to conventional brick kilns with an averagesurface temperature of 370 degrees Celsius along 40 minutes of combustion. The value of the CLC brickcompressive strength test due to exposure to high temperatures for 40 minutes is 0.39 MPa. The compressive
strength value decreases 38% from the value at room temperature without temperature exposure. Whereas, thevisual form on the surface of the CLC brick gives rise to a blackish grey colour resulting from exposure to hightemperatures. The results of this study indicate that the dry and cracked surface texture on CLC brick has caused
a decrease in the performance includes density and compressive strength of CLC bricks. Therefore, CLC bricks
need to be repaired after being exposed to high temperatures.
Keywords: CLC brick, conventional brick, compressive strength, high temperaturestable, and no chemical reactions occur during thematerial mixing process [3]-[6].
CLC brick has low strength and density index thatcan be used as partition walls, acoustic and thermal
insulation materials [7]-[8]. CLC brick contains fine
air cavity due to the addition of foam to the mass ofthe mortar, which aims to reduce the value of volume
weight [9]. The advantages of CLC bricks make it aviable alternative to wall partitioning compared to red
clay bricks.
Increased temperature due to heat exposure froma burning building or direct sunlight can affect theproperties of CLC bricks, such as mechanicalproperties. In the previous study [10], the authors
have studied the mechanical properties of CLC bricks
such as deformation, tensile strength, compressive
strength, and shear strength in various sand andcement ratio. In addition to influencing themechanical properties of lightweight bricks, the effectof heat transfer also affects the physical properties of
CLC bricks [11]. The CLC brick physical properties
are measured without changing their original identity

INTRODUCTION
Red-brick is one of the most widely used
construction materials in Indonesia. This brick is
made by using clay as a primary material in its
manufacture conventionally. An excellent red brickhas the characteristics of a rough surface, not cracked,
not easily broken, a deep red uniform colour, both on
the inside or outside of the brick which indicates thatthe brick is ripe [1]. Nowadays, the development ofconstruction technology is increasing. The impact oftechnological developments in the field ofconstruction is the discovery of new construction
materials such as Cellular Lightweight Concrete(CLC) and Autoclaved Aerated Concrete (AAC).
AAC brick is a cellular concrete with air bubbles
produced from the chemical reaction of aluminium
powder or aluminium paste as a mixture developer[2]. In comparison, CLC bricks are cellular bricks that
undergo natural treatment processes. The CLC
brickwork process uses organic foam which is very

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SEE - Kyoto, Japan, Nov.18-20, 2020

[4],[12]-[13]. One example of material properties is acolour change.
Testing mechanical properties, especiallycompressive strength testing can be done with several
methods including tests that are non-destructive(Non-Destructive Test), and tests that are destructive
to all parts of the CLC brick (Destructive Test). In thatstudy, the compressive strength of CLC bricks wasproduced through destructive testing using a load cellmounted on a steel frame.
The fundamental problem of CLC bricks exposed
to high temperatures is how to estimate thecompressive strength and what happens to the surfaceof the CLC bricks after the temperature rise.
Therefore, the study aims to identify changes visually
and analyse the compressive strength of CLC bricks
after exposure to high temperatures. Therefore, thewalls of buildings were made of CLC bricks exposed
to high temperatures can be anticipated withimprovements so that the walls are still suitable foruse.

for use in tall buildings. In addition, CLC bricks arealso suitable for use in building walls of soft soil areas,
because they can reduce the load on the foundation.
Another advantage of CLC bricks is in terms of
dimensions. CLC bricks have larger dimensions thanconventional bricks. Fig. 2 shows the difference indimensions of conventional brick (red-brick) and
CLC bricks. In-wall installation, every 1 m2 requires
8.3 CLC bricks, whereas for conventional bricks 125
bricks are needed
Conventional Brick

CLC Brick

THEORETICAL BACKGROUND

Fig. 2 Dimension of conventional and CellularLightweight Concrete (CLC)

Red-brick, natural stone, brick, wood, plywood,asbestos are materials commonly used in wallconstruction. Today, the development of thesematerials is replaced by renewable materials such as
Cellular Lightweight Concrete (CLC) brick, as shownin Fig. 1.

According to [6] foam stability is very critical forachieving the optimal density of the CLC mix and forhaving a closed pore structure. Hydrolysed protein
foaming agents impart the desired properties to the
produced foam. Commercially available foaming
agent called Sunlite Foam SF-30 SPL was used forthis analysis. The foaming agent and water werecombined in a ratio of 1:40 and fed into the foam
generator to achieve a preformed foam density of 70
g/litre. The volume fraction of the mixture of foam is
16 per cent of the overall volume.
The material used in making CLC brick is cement,water, fine aggregate and foaming agent [5], [16]. The
composition of the mixture greatly influences thequality of CLC. Cement water factor is essential in
making lightweight bricks. Based on research
conducted by [6]-[7], [17]-[18], by varying thecement water factor in making concrete, thecompressive strength value of the concrete decreases
due to an increase in the cement water factor. The
selection of aggregates is essential in making CLC
bricks. The use of coarse aggregate tends to bedifficult during the lightweight brick mixing process
because the aggregate will settle to the bottom so thatthe lightweight brick is not mixed evenly.
The necessary ingredients of foam agents consistof synthetic materials and protein components.
Synthetic based foam has a density of around 40 kg/
m3 and can expand about 25 times the initial volume.

(a)(b)
Fig. 1 (a) The Cellular Lightweight Concrete(CLC) brick, (b) and the texture of CLC brick [10].
CLC brick is considered more economicalcompared to conventional red-brick. Also, therelatively larger form of CLC bricks can shorten thewall working time. CLC bricks are made from a
mixture of cement, water, sand and foam to produce
a mix of mortar that is ready to be poured on a CLC
brick mould [5]. The most critical aspect in planning
CLC bricks is how to create lightweight andeconomic bricks, without ignoring the strength ofthese lightweight bricks [13]-[15].
The advantages of CLC bricks compared toconventional bricks and concrete bricks are low cost,time-saving, comfortable to work, soundproof, andlightweight so that it does not overload the underlying
structure [5]. Therefore, CLC bricks are very suitable
29

SEE - Kyoto, Japan, Nov.18-20, 2020

This type of foaming agent is very stable for CLC
bricks with masses above 1000 kg / m3. The ratio of
foam and water used is 1:19. The solution of 20 litresof foam can expand into about 500 litres of foam witha weight of about 40 kg / m3.
In comparison, protein-based foam obtained fromnatural materials weighs around 80 kg /m3 and can
expand about 12.5 times the original volume. Thisfoam is relatively more stable and has a higher
strength compared to synthetic foam. But this foam
can only last up to 12 months in an open state. The
ratio of foam and water is 1:33 to 1:39. For a solutionof 40 litres of foam can expand into about 500 litresof stable foam weighing around 80 kg /m3 [10].
High temperature is very influential on CLC
bricks. Light bricks exposed to high temperatures canexperience colour changes such as in concrete.
According to [8] and [19], the colour change of thephysical properties of post-burnt concrete is very
influential on the temperature during combustion.
Discolouration of the concrete begins to appear at atemperature of 500 oC, which is greyish brown. The
condition occurred because of the presence of ironsalt compounds in the aggregate or concrete sand thatcauses the concrete to change colour. For
temperatures reaching 750 oC, brick can create acarbonation process that is formed of Calcium
Carbonate (CaCO3), which is whitish in colour. So
the brick becomes brighter. Based on research
conducted by [9], [20], the higher the combustion
temperature of the concrete, the higher the damage tothe concrete.

Table 1. Plan for mortar mixture
Specimen
CodeMaterial
Cement
(kg)

Sand
(kg)

W/C
ratio

Sikamen(ml)

Variation
(1)

100

200

0.5

200

Variation
(2)

100

150

0.5

200

Compressive strength testing is carried out in the
structure laboratory to obtain the strength of the CLC
brick using a loading frame. Compressive strength
testing is carried out after 28 days since CLC bricks
are made and heated in a brick kiln on the temperature
465 oC as shown in Fig 3.

Fig. 3 The process of heating CLC bricks in a furnace.
The test equipment is worked until the full loadwhen the experiment was a collapse is collected. The
value of the compressive strength of lightweight brickhas been reported using a data logger. Fig. 4 displays
the full image of the instrumentation.

RESEARCH METHODOLOGYThis work used two different mass-ratio cement
and sand compositions. The first composition iscalled Variation 1, with the cement-sand ratio being
1:2, and the second composition is called Variation 2,
with the cement-sand ratio being 2:3. Table 1
describes the variable composition of the CLC bricks.
The research has tested 24 specimens to getlightweight brick strength and density: the foaming
agent and water-mass ratio of 1:30 and Sikamen
addictive. The CLC paste was made with cement towater ratio (W/C) of 0.5.
The material consists of cement, sand, water andfoam agent. At the same time, the leading equipmentused in this research included foam generator with acapacity of 200 litres per minute and a capacity of 100
kN compression test machine.

Fig. 4 Instrumentation setting out

30

SEE - Kyoto, Japan, Nov.18-20, 2020

condition shows that increased use of cement in
Variation 2 has caused the mixing foam concrete toincrease mixed density.
Experimental research shows specimens failure at
the bottom at the age of 28 days. The broken texture
shows itself around the surface of the CLC brick. Test
colours for 28 days, Variation 1 showed the specimen
is brighter than Variation 2, as shown in Fig 6 and Fig
7.

RESULT AND DISCUSSION
Table 2 shows the results of the fine-aggregate test
suggested the amount of mud on the fine aggregatesused in this study met condition according to ASTM
C-33 [21], and the fine aggregates provided a medium
sand group with a fineness modulus of 2.04. The fineaggregates mud average is 4.87 per cent. The fine sum
has an apparent absolute gravity of 2.65. The findingsof the sieve review on fine aggregates showed thatfine aggregates were based on Indonesian Standard
SNI 03-2828-2011 [22] in Specification No. 4, whichnotes fine aggregates are fine grading. The value ofthe fine modulus is an indication that the amount of
the fine aggregate is in the mortar.
Table 2. Fine Aggregate Characteristic
No

Testing item1
2

Mud rate (%)
4.87
Specific Gravity
a. Apparent Specific 2.65
Gravityb. Bulk Specific
2.28
Gravity on Dryc. Bulk Specific
2.40
Gravity on SSD
d. Absorption (%)
5.49
Water content (%)
3.73
Volumeweight(gr/cm3)
a. Solid condition
1787.77b. Dry condition
1297.74
Rate of Organic
No. 2
Fine-Modulus
2.04

3
4

5
6

ResultStandard
Range<5

Fig. 5. Compressive strength of The CLC brick2.58-2.83

Table 3. The Compressive strength with the variationof composition cement and sand2.58-2.83

VariationNo.

2.58-2.83

Cement: Sand

2.0 – 7.0
3–5

1400-1900
1400-1900
Max No. 3
1.5-3.8

Fig. 5 and Table 3 display the effect of thecontents of variation composition on the compressive
intensity of the CLC brick. Variation 2 with higher
cement content demonstrates higher compressive
strength at 3, 7, 14, and 28 days of age than Variation
1.
The research resulted in the various compositional
effects, including density and compressive strength,of the physical and mechanical properties of CLC
brick. In Variation 1 and Variation 2, the use of sandconsumption in 1 m3 of mixing concrete was 200 kg
and 150 kg, respectively, when the cement
consumption was 100 kg for both variations.
Therefore, the use of sand consumption in a fixed
quantity for 1 m3 of concrete mixture in Variation 1
and Variation 2 resulted in decreased cement use in
Variation 2 instead of Variation 1. The researchaffects the mean foam concrete density at the age of
28 days, as shown in Table 3. Variation 2 indicates ahigher value for density than Variation 1. The

Compressive Strength
(MPa)
3
days

7
days

14
days

28
days

1

1:2

0.18

0.28

0.41

0.52

2

2:3

0.22

0.35

0.52

0.68

Fig 6. The compressive test on specimen Variation 1
age 28 days.
The increased density allowed the addition of
cement to the lightweight mixture of concrete. Hence
Variation 2 power is higher than Variation 1.
Nevertheless, due to small additions (low strength)
the increase in force generated is not large. While thefindings of this study are similar to studies publishedin the literature, such as [4] and [5], so reducing thesize of sand particles will lead to increased foam
concrete resistance. Replacing sand with materials

31

SEE - Kyoto, Japan, Nov.18-20, 2020

such as fly ash might lead to greater strength, and fineaggregate fillers could also produce higher strengthand density ratios.

Fig. 9 The CLC brick pores after exposed hightemperature.

Fig 7. The compressive test on specimen Variation 2
age 28 days

Based on the results of the compressive strength
test on 28 days CLC bricks before exposure to hightemperatures has a density value 0.850 grams/cm3.
Exposure to high temperatures for 10, 20, and 30
minutes, has led to a decrease in the weight of thevolume of CLC bricks respectively to 0.833
grams/cm3, 0.811 grams/cm3 and 0.808 gram/cm3.
Finally, at 40 minutes exposed to high temperature,
there was a decrease to 0.803 gram/cm3. Figure 10
shows the relationship between density andcompressive strength during high temperature
exposure.

Based on visual observations of brick CLC due toexposure to high temperatures, several changes suchas CLC brick colour changes and changes in pore size
have occurred. Colour-changes in the CLC brickbegan to be seen since the CLC brick was exposed for
30 minutes. The exposed brick surface has turnedbrownish. Table 4. shows the exposure temperatureof CLC bricks in parts directly exposed to hightemperatures.
Table 4. The temperature of CLC brick exposure

0,9

0,85

0,833

0,8
0,7

0,811

0,808

0,803

0,63

0,6

0,51

0,5

0,45

0,44

20 minutes

30 minutes

0,4

0,39

0,3
0,2
0,1

In addition to changes in colour, due to exposure
to high temperatures also cause changes in pore sizeof the lightweight brick. Pores that have initially beensmall in size, as shown in Fig 8, due to exposure tohigh temperatures caused the size of the brick pores
to become enlarged, as shown in Fig 9.

00 minutes

10 minutes

Density (gr/cm3)

40 minutes

Compressive strength (Mpa)

Fig. 10 The performance of CLC brick before andafter exposed high temperature

CONCLUSION
Based on the research that has been done, thefollowing conclusions can be drawn:
1. Exposure to high temperatures in CLC bricks cancause discolouration, change in pore size, change
in volume weight, and change in compressive
strength of the bricks.
2. CLC bricks exposed to high temperatures for 40
minutes have caused a decrease in volume weightfrom the original 0.85 gram/cm3 to 0.803 gram/cm3. In addition to the reduction in density, thecompressive strength test results of the CLC brickFig. 8 The CLC brick pores before exposure hightemperature
32

SEE - Kyoto, Japan, Nov.18-20, 2020

show the compressive strength of the CLC bricks
changed from 0.63 MPa to 0.39 MPa.
ACKNOWLEDGMENTS[11]
The author would like to thank the financial
support from the University of Riau for funding thisresearch under the AKSI project through the PNBP
Grant for the International Research Collaboration
2020 scheme.

[12]

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M. A. Rasheed and S. S. Prakash, “Behaviorof Hibrid-Synthetic Fiber Rereinforced
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[8]
M. R. Ahmad, B. Chen, and S. Farasat Ali
Shah, “Investigate the influence of expanded
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[9]
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properties of silica-fume based foams,”
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H. Maizir, R. Suryanita, and R. Arditama,

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A. Thongtha, S. Ketchaona, J. Wattana, andT. Patanin, “Influence of portland cement on
physical, mechanical and thermal propertiesof cellular lightweight concrete,” Key Eng.
Mater., vol. 751 KEM, pp. 532–537, 2017.
Z. Liu, K. Zhao, C. Hu, and Y. Tang, “Effectof Water-Cement Ratio on Pore Structure andStrength of Foam Concrete,” Adv. Mater. Sci.
Eng., vol. 2016, 2016.
F.
K.
Alqahtani
andI.
Zafar,“Characterization of processed lightweightaggregate and its effect on physical propertiesof concrete,” Constr. Build. Mater., vol. 230,
p. 116992, 2020.
T. J. Chandni and K. B. Anand, “Utilizationof recycled waste as filler in foam concrete,”
J. Build. Eng., vol. 19, pp. 154–160, 2018.
Z. Zhang and H. Wang, “The porecharacteristics of geopolymer foam concreteand their impact on the compressive strengthand modulus,” Front. Mater., vol. 3, no.
August, pp. 1–10, 2016.
L. Chica and A. Alzate, “Cellular concrete
review: New trends for application inconstruction,” Constr. Build. Mater., vol.
200, pp. 637–647, 2019.
H. S. Gökçe, D. Hatungimana, and K.
Ramyar, “Effect of fly ash and silica fume on
hardened properties of foam concrete,”
Constr. Build. Mater., vol. 194, pp. 1–11,
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Korjakins, “Durability Properties of High
Performance Foamed Concrete,” Procedia
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151–163, 2017.
R. Suryanita, H. Maizir, Ismeddiyanto, R.
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Engineering34

6th Int. Conf. on Structure, Engineering & Environment (SEE)
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106032 C3051

EVALUATION OF RECOVERY OF DEBRIS FLOW CONTROLBY CHECK DAMS AFTER REMOVING DEBRISBASED ON NUMERICAL SIMULATION
Naomasa Honda1
1Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
ABSTRACTThe present paper evaluated the recovery of a debris flow control by check dams after removing debris fromcheck storage areas based on the numerical results of both a model and an actual torrent. A one-dimensional
numerical simulation is conducted to investigate the variations in the debris flow characteristics along a river reachwith check dams. In the calculation, the check storage area was either filled with sediment or emptied by removing
debris. The analytical results show that check dams effectively reduced the sediment transport when the initial bed
slope of the deposition area at the dam’s upstream region is gentler than the equilibrium slope of the debris flow,even if the area is filled with sediment. Removing debris from the check storage area is much more effective forcontrolling the debris flow, but a priority ranking for removing the works of a number of check dams must be
carefully determined when considering the sediment runoff process and its characteristics throughout a torrent.
Keywords: Check dam, Check storage area, Removing debris, Debris flow control, Numerical simulation

INTRODUCTION

debris from the check storage area based on the
numerical analysis results of virtual and actual
torrents.
A one-dimensional numerical simulation, which iscomprised of mass and momentum conservation
equations for debris flow and erosion velocity
formula on debris from riverbeds, is conducted toinvestigate the variations in the debris flow
characteristics along a river that reaches the checkdams. In the calculation, the check storage area waseither filled with sediment or emptied by removing
the debris. Such debris flow characteristics assediment discharge and sediment flux concentration
can be predicted to estimate the recovery of thedebris flow control by check dams after removing thedebris.

A check dam basically controls sediment runoff
based on its storage volume [1], [2]. It can control
the debris flow with a change of the deposition
gradient at the check storage area even if it is filledwith sediment. Since check dams, which wereconstructed a long time ago, have check storage
areas that are filled with sediment, their ability must
be restored to control the debris flow by removing
debris from them. But no debris has been removed,
and as alternative facilities, new check dams havebeen constructed, because removing debris faces thefollowing difficulties:
・Securing such sites as approach paths to dams andthe stock yards of removed debris:
・Disposal and recycling methods of the removed
debris:・Influence on neighboring environments

METHOD AND PROCEDURE FOR STUDY
Characteristics of check storage areaθeｃ

Since appropriate places at which to build new
check dams are limited, they must be restored thecheck storage ability to control debris flow by
removing debris. In addition, in an actual torrent, therecovery of debris flow control by check dams thatremoved the debris should be evaluated as a groupof dams, not as individual structures, because theactual bed slope and the width irregularly changes in
the river, and strongly influences the debris flow
characteristics and the storage’s ability to check theflow.
The present paper evaluates the recovery of thedebris flow control by check dams after removing

Ve

V
θ

L = H cotθFig. 1 Check storage area
35

H

SEE - Kyoto, Japan, Nov. 18-20, 2020

5.03

σ = 2.65g/cm

Ve / V4.0

c = 0.50

ρ = 1.00g/cm3
φ s = 40°c = 0.40

3.0
c = 0.30

2.0εch 1 εcBvh
+
=E
t
B x

(4)

where t is the time, x is the coordinate axis along theflow, h is the flow depth, B is the flow width, v is theflow velocity, E is the erosion velocity (its negativevalue designates the deposition), ε is the correction
factor (Egashira et al. [6], εc = ct , ct is the sediment
flux concentration), and c* is the sedimentconcentration of the bed layer. The following is themomentum conservation equation:

1.0
0.0
5.0

10.0

15.0

20.0
θ ( °)

25.0

30.0

Fig. 2 Relationship among θ, c, and Ve /V: Flowwidth is constant in all section.
Figure 1 shows a schematic diagram of the checkstorage area of a check dam, where θis the bed
slope, c is the sediment concentration by volume,θe is the equilibrium bed slope that correspond to
the sediment concentration, H is the check dam’sheight, V is the deposited amount of sediment to H
( θ e.= 0), and Ve is the additional deposition
amount of sediment withθ e , defined by Eq. (1)[3]: ( /  − 1) ctan  s 
(
)

/

−
1
c
+
1



 e = tan −1 τv
v
1 P vE+ v = g sin θ −
−
− b
t
x
ρm h x c* h ρm h

 m = ( −  )c + (1)・When θ is constant, Ve is large and c is large(therefore, θe is large, as shown in Eq. (1)).
・When c is constant (therefore, θe is a constant
shown in Eq. (1)), Ve is large, and θ is small.

cos sin  esin ( −  e )

(6)

Z b
E
=−
t
c* cos (7) Z 
 = sin −1  − b  x 

(8)

where Zb is the bed elevation, and θis expressed by
Eq. (6). As mentioned above, even though E andτbplay an important role in the governing equations, nogeneral formulas have been developed for them. In
this study, the formulas for E [4] and τ b [7]developed by Egashira et al. are used
Erosion velocity E is the as following:

When the flow width is constant in all the sections,the following is the relationship between Ve and V:=(5)

The second term on the right-hand side of Eq. (5) is
the pressure gradient, and the third term is theresistance due to the sediment erosion. g is thegravity acceleration, P is the pressure, τb is the bed
shear stress, and ρm is the mass density of the flow
mixture defined in Eq. (6). The mass conservation
equation of the bed sediment takes the following
form:

where σ is the mass density of the gravel, ρ is themass density of the water, and φ s is the internal
friction angle of the sediment.
The following is the relationship among θ, c, and
V e:

V

(3)

c = 0.20
c = 0.10Veh 1 Bvh E+=
t B xc*(2)E= c* tan(θ − θe )v

Figure 2 shows Eq. (2) as a horizontal axis in θ.
Generally, in actual torrents, their flow width and thestorage area’s width irregularly change, but Fig. 2
directly shows the relationship among θ, c, and Ve.

(9)

The following is bed shear stress τb: b = y+ fv 2

Governing equations for debris flow

(10)

15

c
 y=    (  − 1)cgh cos  tan  s c* 

To analyze the sediment transport in a river reach[4], [5], the one-dimensional equations developed by
Egashira et al. [4] is used. The following are themass conservation equations for the flow mixture
and the sediment alone:

25  (1 − c )
k f
4 
c2 3

53

f =

36

+ kg

 h  −2
(
1 − e 2 )c 2 3   d 

(11)(12)

SEE - Kyoto, Japan, Nov. 18-20, 2020

In Eq. (10), τy is the yield stress caused by theparticle to particle contacts defined in Eq. (11), and fis the friction factor defined as Eq. (12), where e isthe restitution coefficient, d is the reference grain size,
and kf and kg are coefficients: kf =0.16, kg =0.0828.

Actual torrent’s caseOhzedani River, a tributary of the Sendai River in
Tottori Prefecture, flows into the Japan Sea (Figs.
4(a) and (b)). It has drainage of 3.2km2 and a river
reach of 4.1km. Its mean bed slope is 10.8degrees,
and its width changes irregularly (Figs. 4(c) and (d)).
During drainage, the mountain slope is steep, andweathering granite rock, which is very susceptible toerosion, is widely distributed on the mountainside.
Unstable sediment is often produced during drainage.
This torrent is defined as a river’s stream that poses
the risk of a debris flow.
In this basin, a very active sediment runoff wascaused in September 1961 by the Second Muroto
typhoon. Debris flow arrived at the lowest stream
reach near Kofune Village (Fig. 4(b)). However, thetorrent did not overflow its banks because a checkdam (No. 3 dam in Fig. 4(c)) and channel works,
constructed at a village located downstream of theriver’s reach (Fig. 4(b)), effectively reduced thesediment transport and controlled the debris flow [8].
After the disaster, two check dams were constructed
as countermeasures against sediment-related
disaster's hazards: No. 2 and No. 3 dams in Fig. 4(c).
In this paper, the following are the actual
torrent's conditions:
・This study analyzed a 3,200m long river reach 380
to 990m above sea level from the point where thebed slope changes suddenly to a confluence of the
Ochiori River.
・The bed and width profiles are shown in Figs.
4(c) and (d).
・Three dams are shown in Fig. 4(c). No. 1 dam's
height is H1=5.2m, and its width is B1=25.0m; No.
2 dam's height is H2=8.8m, and its width is
B2=42.0m; No. 3 dam's height is H3=5.5m, and its
width is B3=53.0m. The storage areas of all threedams are filled with sediment.
・This study assumed that the sediment was mainly
supplied by bed erosion and estimate that thecritical erosion depth of the bed material equaled
2.5m based on previous study's results [8].
・The maximum hourly precipitation was 58.0mm
in the September 1961 debris flow hazard. The
rainfall intensity of this value is chosen, whichyields 0.50m3/sec at the reach’s upstream end,using a rational formula with a drainage area of
0.05km2 and a runoff coefficient of 0.60. Such an
inflow water discharge is supplied constantly, andfor convenience sediment concentration cin isassumed to be 5% by volume.

Examination cases and calculation conditions
In actual torrents, the flow width and the bed
slope change irregularly, and the sediment that
becomes the constitution materials of the debris flow
is partly distributed on the bed. These geographicalconditions greatly influence the calculation results ofsuch debris flow characteristics as h, c, and v. They
also influence both the sediment and the flow
discharges, which closely affect the debris flow
characteristics of check dam's storage.
In this study, the following two torrents are set:
the virtual torrent with a constant width, the actual
torrent whose width irregularly changes.
Virtual torrent’s case
Figure 3 shows a river-bed profile of the virtual
torrent. The following is its conditions:

Bed elevetion Zb (altitude : m )・Total river length; L=900m (horizontal distance=985m, relative height=187m);
・Flow width; B =constant=20m (in all sections);
・ Bed inclines are 18degrees, 12degrees, and 6
degrees every 300m from the upper reaches.
・Three dams exist from Nos.1 to 3 at the change
points of the bed incline. No.1 dam's height is
H1=3.0m, No.2 dam's height is H2=4.0m, andNo.3 dam's height is H3=5.0m. But the storage
areas of all three dams are filled with sediment.
・ The sediment has eroded and exists fat athickness of 2.0m (the critical erosion depth of the
bed material) on the bed.
・ If just a little water is supplied, and the bed
sediment begins to move in a saturated soil state,
it is adequate in a numerical simulation.
Therefore, an inflow water discharge is constantly
supplied 0.10m3/sec at the upstream boundary, andfor convenience assumed sediment concentration cin
by volume.
300
250
No.1
200
No.2
150

No.3

Conditions shared by two cases

100
50
0

300

600

The storage area's state before and after removing
the debris and the conditions of the check dam’s
storage area are set in the numerical simulation(Fig.5, Table 1).

900

Distance x (m )Fig. 3 Bed profile of virtual torrent
37

SEE - Kyoto, Japan, Nov. 18-20, 2020

Japan Sea

Fig.5 Schematic diagram of dam’s storage area
in numerical simulation

Tottori Prefecture

Table 1 Conditions of check dam’s storage area
in numerical simulation(a) Location of Tottori Prefecture in JapanThe Japan Sea

Sediment storage conditions of dams
Case. ●：Being filled up ○：after removing

Ohzedani River
The drainage
divideR. Sendai

1
2
3
4
5
6
7
8

Kofunevillage

No.1

No.2

No.3

●
●
●
●
○
○
○
○

●
●
○
○
●
●
○
○

●
○
●
○
●
○
●
○

R. Ochiori
R. Hattoh(b) Schematic diagram of Ohzedani River basin
t +1

1200

Bed elevetion Zb (altitude : m )

t

1000

○ the unknown pointt -1● the known point

No.1 dam
800
No.2 dam
600

n -1

No.3 damnn +1

Fig.6 Schematic diagram of leap-frog scheme

400(Ochiori River junction)

The following parameters are required forcomputation: σ= 2.70g/cm3, φ s = 39.0degrees, d=
5.0cm, and c*= 0.50, respectively.
Fine sand concentration in water cs, is the closely
related to a rise in the water’s density (muddy water).
Because such a rise increases buoyancy, the analysis
cannot ignore its influence [9], [10]. When it isassumed that cs equals 10%, ρ is calculated by Eq.
(8) as follows: ρ=1.17g/cm3 (cs = 10%)In this study, the finite difference method is used(leap-frog scheme in Fig. 6). The time and distanceare discriminated as Δt=0.025 seconds and Δx=5.0 m,
respectively.

200
0

500

1000

1500

2000

2500

3000

2500

3000

Distance x (m )(c) Bed profile of Ohzedani River

River-width B (m )

15.0

10.0

5.0

RESULTS AND DISCUSSIONS

0.0
0

500

1000

1500

2000

Virtual torrent’s caseDistance x (m )(d) Width of Ohzedani River

Figures 7(a), (b), and (c) show the temporalchanges of the bed elevation near three check dams
after 300 seconds with their water supply as an

Fig. 4 Outline of actual torrent: Ohzedani River
38

SEE - Kyoto, Japan, Nov. 18-20, 2020

240

After 300 seconds

220

No.1 dam200

0 sec(Initial bed)

180

160
200

250

300

350

Removing the debris from the check storage of No.1
dam (from Cases 5 to 8) is generally affective for thecomprehensive evaluation shown as ∑Qs. But after
removing debris from the check storage of No. 1, its
sediment discharge downstream is larger than the
upstream value, because the bed erosion
immediately downstream of the check dams
occurred due to the dam’s overflow.
After carefully removing the debris from thecheck storage of No. 2 dam, the ∑Qs of Case 3,
which only removed the debris from No. 2, is larger
than Case 1, where all three check storages are filledwith sediment (▲ in Table 2). This is because thecheck storage slope of No. 2 (after removing debris)
became steeper than before removing it and bed
erosion was accelerated.
In Table 2, note that the ∑Qs of Case 6 (No. 1
and No. 3 dams are removed the debris, and No. 2
dam isn’t removed). Case 6 is smaller and more
effective for the debris flow control than Case 8,
which removed debris from all three check storages
and is the smallest and most effective case.

180

Bed elevetion Zb (altitude : m )Bed elevetion Zb (altitude : m )Bed elevetion Zb (altitude : m )example (all three check dam’s storage areas arefilled with sediment, i.e., Case 1 in Table 1). All thecheck dams deposited sediment at their storage areasand controlled the debris flow’s power by changing
of the check storage gradient. The bed erosion
immediately downstream of the check dams wascaused by overflow from the dam.
Figures 8(a) and (b) show the temporal changes ofsediment flux concentration c and sediment discharge
Qs at the cross-sections: x=200m and 300m (upstream
and downstream of No. 1 dam), x=500 and 600m
(upstream and downstream of No. 2 dam), x=800m
and 900m (upstream and downstream of No. 3 dam)as an example (Case 1 in Table 1). In these figures,the debris flow control with every check dam can beevaluated by the peak cut value, i.e., comparing twovalues between check dam’s upstream anddownstream. Similarly, the debris flow control as acheck dam group can be estimated by the maximum
values of c and Qs and total sediment volume ∑Qs at
the downstream end (x=900m).
Table 2 shows the numerical results based on theconditions of the check dam’s storage area in Table 1.

After 300 seconds
160

No.2 dam140

0 sec(Initial bed)

120

100
450

400

500

550

600

650

130

After 300 seconds
120

No.3 dam
110

100

0 sec
(Initial bed)

90
700

750

800

850

Distance x (m )Distance x (m )Distance x (m )(a) Near No. 1 dam(b) Near No. 2 dam(c) Near No. 3 dam

900

Sediment flux concentration ct

150
x =500m
x =200m

3

Sediment discharge Q s (m /sec )Fig. 7 Temporal changes of bed elevations near check dams in virtual torrent(Case 1 in Table 1: all three check dam’s storage areas are filled up with sediment.)

x =600m100
x =800m

x =300m50

x =900m
0
0

60

120

180

240

0.6
x =200m

0.5

x =500m

0.4
x =600m
0.3
0.2
x =900m

0.1

x =800m

00300

x =300m

60

120

180

240

Time t (sec )Time t (sec )(a) Sediment discharge(b) Sediment flux concentration

Fig.8 Temporal changes of debris flow characteristics as an example in virtual torrent(Case 1 in Table 1: all three check dam’s storage areas are filled up with sediment.)
39

300

SEE - Kyoto, Japan, Nov. 18-20, 2020

Table 2 Debris flow runoff control by check dams evaluated by peak cut quantity of sediment discharge Qs
in the virtual torrent
Sediment storage
conditions of dams●：Being filled up○：after removing

No.1 dam (x =285m)

1

●

●

●

2

●

●

○

3

●

○

●

4

●

○

○

5

○

●

●

6

○

●

○

7

○

○

●

8

○

○

○

Upstream(x =200m)

Downstream(x =300m)

No.2 dam (x =578m)

Peak cut3(m /sec)

26.52

Downstream(x =600m)

Peak cut

132.60

84.18

48.43

128.51

82.08

46.43

131.44

72.77

58.67

3

(m /sec)

38.56

65.08

107.31

No.3 dam (x =878m)

Upstream(x =500m)-42.23124.95

69.76

55.19

Upstream(x =800m)

Downstream(x =900m)

Peak cut

45.41

27.85

17.56

96.72

20.05

76.67

48.44

27.76

20.68

88.15

26.74

61.40

59.35

20.95

38.40

101.97

13.14

88.82

41.39

22.98

18.41

85.50

11.51

73.99

With Based on economic and feasibility reason,
intensively removing debris from the check storageof No. 3, which is the most downstream (debris flow
deposition area) location, is the most effective for thedebris flow control shown Case 2 in Table 2.

0 sec(Initia bed)

580
560
540
600sec後

520
1400

1500

1600

1700

1800

Bed elevetion Zb (altitude : m )Bed elevetion Zb (altitude : m )Figures 9(a), (b), and (c) show the temporalchanges of the bed elevation near the check dams
after 600 seconds with their water supply as an
example (all three check dam’s storage areas arefilled with sediment, i.e. Case 1 in Table 1). All thecheck dams deposited sediment in their storage areasand controlled the debris flow’s power by the checkstorage width and the changes of the check storage
gradient. Bed erosion immediately downstream of thecheck dams was caused by overflow from the dam.
Figures 10(a) and (b) show the temporal changesof sediment flux concentration ct and sediment
discharge Qs at the cross-sections: x=400m (debris
flow occurrence area), x=1,500m and 1,700m(upstream and downstream of No. 1 dam), x=2,300m
and 2,500m (upstream and downstream of No. 2 dam),

No.1 dam

500

460

3

ΣQs (m3)

Ratewith Case.1

132.60(x =500m)

27.85

1430.23

1.00

20.05

965.970.68

3128.51(x =500m)

27.76

1496.26

1.05

▲

26.74

1174.120.82

131.44(x =500m)

20.95

1040.40

0.73

13.14

594.550.42

124.95(x =500m)

22.98

1025.73

0.72

11.51

662.890.46

After 600 seconds

440
No.2 dam

420
2100

2200

Comprehensive
Evaluation（m /sec）

0sec(Initial bed)

480

ΣQs

Qs max12

x=2,800m and 3,000m (upstream and downstream of
No. 3 dam) as an example (Case 1 in Table 1).
Tables 3(a) and (b) show the numerical results
based on the conditions of the check dam’s storage
area in Table 1. By scrutinizing the No. 1 and No. 2
dams in Table 3(a), it can be confirmed the peak cut
of ct from Cases 1 to 6. The reason is because thecheck dams changed the sediment transport modes
based on their check storage width even if the checkstorage areas were filled with sediment. On the other
hand, focusing on No. 3 dam, there are cases when ct
increases downstream of No.3 (Cases 1, 2, 5, 6, and 7
in Table 3(a)) because the sediment was deposited in
the channel works downstream of No. 3.
Focusing on Cases 2, 3, and 5 in Table 3(b), whichshow debris that was separately removed, Case 2
removes the debris from the check storage of the No.
2 dam, which is the most effective decision for debris
flow control of all the three cases as shown Qsmax and∑Qs at the downstream end. The reason is because
the check storage volume of No. 2 is the largest of all
three dams and Qsmax occurs near No. 2 shown inCase 1 in Table 3(b).
Focusing on Cases 4, 6, and 7 in Table 3(b), whichremoved debris from two check storages, Cases 4 and 7,

Actual torrent’s case

600

3(m /sec)

Downstream end (x =900m)

Qs max(m3/sec)(x =500m)

Bed elevetion Zb (altitude : m )Case
No.1 No.2 No.3

Debris flow runoff control using three check dams
evaluated by peak cut quantity of sediment dischaerge Qs

Peak cut quantity of sediment discharge Qs using several dams

2300

2400

Distance x (m )Distance x (m )(a) Near No. 1 dam(b) Near No. 2 dam

2500

Fig. 9 Temporal changes of bed elevations near check dams in actual torrent(Case 1: all three check dam’s storage areas are filled up with sediment.)
40

440
After 600 seconds
420
No.3 dam
400
0sec(Initial bed)

380
360
2700

2800

2900

3000

Distance x (m )(c) Near No. 3 dam

3100

0.5

x =400m

0.4

x =3100m
x =2800m

x =1500m
x =1700m

0.3

x =2300m
x =2500m

0.2
0.1
0
0

120

240

360

200

Sedimen discharge Qs (m3/sec )Sediment flux concentration ct

SEE - Kyoto, Japan, Nov. 18-20, 2020

480

x =1700m
150

x =1500m

x =2500m

x =400m

x =2300m

100

x =2800m
x =3100m

50
0

600

0

120

240

Time t (sec )

360

480

Time t (sec )(b) Sediment discharge(a) Sediment flux concentration

Fig. 10 Temporal changes of debris flow characteristics as an example in actual torrent(Case 1: all three check dam’s storage areas are filled up with sediment.)
Table 3 Debris flow runoff control by check dams evaluated by peak cut quantity in actual torrent(a) Sediment flux concentration

Case

Sediment storage
conditions of dams●：Being filled up○：after removing

flux concentration c t
No.1 dam (x =1,605m)

No.1

No.2

No.3

1

●

●

●

2

●

●

○

3

●

○

●

4

●

○

○

5

○

●

●

6

○

●

○

7

○

○

●

8

○

○

○

Debris flow runoff control
using three check dams
evaluated by peak cut quantity of sediment

Peak cut quantity of sediment flux concentration c t using several dams

Upstream Downstream(x =1,500m) (x =1,700m)

Peak cut

No.2 dam (x =2,410m)
Upstream Downstream(x =2,300m) (x =2,500m)

0.21
0.16

0.07

Peak cut

0.14

0.11
0.29

0.23

0.06

0.27
0.17
0.21

0.04

0.13

0.06
0.18

0.12

0.06

c t maxNo.3 dam (x =2,925m)
Upstream Downstream(x =2,800m) (x =3,100m)

Peak cut

Debris flow
occurrence(x =400m)

Downstream
end(x =3,200m)

Comprehensive
Evaluation

0.08

0.17

-0.09

0.13

0.09

0.16

-0.07

0.13

0.17

0.15

0.02

0.22

0.12

0.10

0.05

0.14

-0.09

0.08

0.15

-0.07

0.13

0.09

0.14

-0.05

0.12

3

0.19

0.08

0.11

0.05

1

0.13
0.09

0.44

2

0.13

(b) Sediment discharge
Sediment storage
conditions of dams●：Being filled up○：after removing
Case

No.1 dam (x =1,605m)
No.1 No.2 No.3

1

●

●

●

2

●

●

○

3

●

○

●

4

●

○

○

5

○

●

●

6

○

●

○

7

○

○

●

8

○

○

○

Debris flow runoff control using three check dams
evaluated by peak cut quantity of sediment discharge Qs

Peak cut quantity of sediment discharge Qs using several dams

Upstream Downstream(x =1,500m) (x =1,700m)

Peak cut

No.2 dam (x =2,410m)
Upstream

58.91
44.34

Downstream3(m /sec) (x =2,300m) (x =2,500m)

200.74

Peak cutDownstream

Peak cut3(m /sec) (x =2,800m) (x =3,100m)(m /sec)

65.20

23.20

42.00

109.14

14.42

94.72

24.83

5.23

19.60

38.76

2.54

36.22

48.91

12.82

36.09

81.45

6.30

75.15

10.95

2.15

8.80

15.73

0.91

14.82

-141.83

57.53
77.94

81.85

-3.91

101.87
32.49
64.92

49.05

-16.56

36.95
64.13

57.48

No.3 dam (x =2,925m)

6.65

Upstreamwhich always removed debris from the checkstorage of No. 2, are equally effective for the debris
flow control shown by Qsmax and ∑ Qs at thedownstream end. Removing debris from the checkstorage of No. 2 is the most effective strategy.
Focusing on Cases 4, 7, and 8 in Tables 3(a) and(b), where debris flow is always removed from thecheck storage of No. 2, Case 8 removed the debris

3

Downstream end (x =3,200m)
Qs max(m3/sec)

ΣQs

Qs maxComprehensive
Evaluation（m /sec）

ΣQs (m )Ratewith Case.1

200.74(x =2,500m)

20.68

1742.46

1.00

10.82

891.160.51

101.87(x =1,500m)

5.13

675.380.39

1.99

226.59

0.13

11.64

1060.16

0.61

5.47

460.870.26

2.06

238.76

0.14

3

0.77

78.81

0.05

1

101.87(x =1,500m)

3

3

2

from all three check storages and is the mosteffective choice for debris flow control for thecomprehensive evaluation shown by ctmas , Qsmax and∑Qs at the downstream end
But No. 1 dam changes the sediment transportmodes even if its check storage areas are filled withsediment (Cases 1, 2, 3, and 4 in Tables 3(a) and (b)).
Therefore, based on economic and feasibility
41

SEE - Kyoto, Japan, Nov. 18-20, 2020

concerns, the check storage of the No. 1 dam locatedupstream should not remove any debris. Thoroughly.
removing debris from the check storage dams No. 2
and No. 3 located midstream and downstream is themost effective option for debris flow control (Case 4
in Table 3(b)).

[2] Egashira S. and Honda N., Debris Flow Control
with Sabo Dams. The 10th APD-IAHR
Congress, Vol. 2, 1998, pp.180-187.
[3] Takahashi T., A Mechanism of Occurrence of
Mud-Debris Flow and Their Characteristics in
Motion. Annuals of Disaster Prevention
Research Institute, Kyoto University, Vol. 20,
Issue B-2, 1977, pp.405-435 (in Japanese).
[4] Egashira S., Ashida K., Yajima H., andTakahama J., Constitutive Equations of Debris
Flow. Annuals of Disaster Prevention ResearchInstitute, Kyoto University, Vol. 32, Issue B-2,
1989, pp.487-501 (in Japanese with English
abstract).
[5] Suzuki T. and Hotta N., Coupling of particle
and grid-based methods for debris flow
simulation. Journal of the Japan Society of
Erosion Control Engineering, Vol. 71(2), 2018,
pp. 13-21 (in Japanese with English abstract).
[6] Egashira S., Itoh T., Miyamato K., and Honda
N., Importance of Correction Factor Associatedwith Sediment Concentration Profile in Debris
Flow Simulation. 2th International Symposiumon Flood Defence 2002, Vol.2, 2002, pp.16581666.
[7] Egashira, S., Miyamoto K., and Itoh T.,
Constitutive Equations of Debris Flow andTheirApplicability.
1st
International
Conference on DFHM, American Society of
Civil Engineering, 1997, pp. 340-349.
[8] Honda N., Evaluation Debris Flow Using Sabo
Facilities Based on Numerical Simulations. 9thInternational Conference on GEOMATE, 2019,
pp.75-81.
[9] Egashira, S., N. Honda and K. Miyamoto,
Numerical simulation of debris flow at the
Gamaharazawa in the Hime River basin.
Annuals of Hydraulic Engineers, Japan Societyof Civil Engineering, Vol.42, 1998, pp. 919924(in Japanese with English abstract).
[10] Nakatani K., Furuya T., Hasegawa Y., Kosugi
K., and Satofuka Y., Study on fine sedimentphase change factors and on influence on debris
flow behavior. Journal of the Japan Society of
Erosion Control Engineering, Vol. 70(6), 2018,
pp. 3-11 (in Japanese with English abstract).

CONCLUSIONSThe present paper evaluated the recovery ofdebris flow control by check dams after removing
debris from check storage areas based on the results
a numerical analysis of a virtual and an actual torrent.
Then this study obtained the following results.
1) A check dam effectively reduced sedimenttransport when the initial bed slope of the depositionarea upstream of the dam is milder than theequilibrium slope of the debris flow, even if the area
is filled with sediment.
2) With economy and possibility of works, a checkdam, which is located upstream whose check storage
area is filled with sediment, should not aggressively
remove debris or expect a function that changes
sediment transport modes.
3) On the other hand, a check dam, locatedmidstream and downstream, should aggressively
remove debris and maintain its storage volume fordebris flow control.
4) Removing debris from check storage areas ismuch more effective for controlling the debris flow,
but the priority ranking for removing works for anumber of check dams must be carefully determinedwhen considering the sediment runoff process andits characteristics throughout a torrent.
ACKNOWLEDGEMENTS
Part of the present study was supported by theStrategic Research Project from Tokyo University ofAgriculture.
REFERENCES[1] Honda N. and Egashira S., Prediction of Debris
Flow Characteristics in Mountain Torrents. The
1st International Conference on DFHM,
American Society of Civil Engineering, 1997,
pp. 707-716.

42

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EFFECT OF TEMPERATURES MALTODEXTRIN ON PHYSICALPROPERTIES OF DATE PALM POWDER BY SPRAY DRYING
Wattana Wirivutthikorn1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi (RMUTT)
2 Phaholyothin 87 Soi 2 Phaholyothin Road Thanyaburi Pathumthani 12130 Thailand

1

ABSTRACT
Fruit juices have tendency to loose nutrients during processing when subjected for heating. Fruit juices
could be preserved by several drying methods. Spray drying has been one of the most a well-known method ofparticle production which comprises the transformation of a liquid material into dried particles. The advantagesof this method is a rapid, continuous, cost-effective and reproducible. The objective of this research was todetermine the suitable spray drying conditions and the date palm powder qualities. The maltodextrin atconcentrations of 20, 25, and 30 percent were added in finished palm date juice. Three of the inlet and fixed theoutlet temperatures as 130, 140, 150 and 90ºc, respectively were performed. The physico chemical properties aswater activity (a w ), moisture, brightness (L*), redness (+a*), yellowness (+b*) and solubility values wereanalyzed. As a result, the maltodextrin concentrations at 30 percent provided good characteristics of date palm
powder with high powder recovery and low water activity and moisture content. It appeared that the inlet
temperature of 150°c was more appropriate than 130°c and 140°c because it concerned higher powder recovery,
low water activity of 0.15, and low moisture of 2.15 percent, but gave the low solubility of 13.85 percent. Fromthe information obtained, describes the most outstanding advantages of the spray drying method for the
production of food particles and the potential of this technique and the more advanced equipment to develop
processes and industrial scale processes that are essential to the bench-to-bedside translation of innovative
instant powdered fruit beverage products.
Keywords: Date palm, Powder, Temperature, Spray drying, Maltodextrin
methods including drum drying, freeze drying hot
air oven, tray drying, spray drying is one of the mosttechnique applied to efficiently dehydrate sugar andacid-rich fruit juice by using different drying agents
under optimal processing conditions to obtainpowdered foods with advantages of heat shortcontact time, microbial growth inhibition, andstorage stability [2]. The spray drying parameterssuch as drying air temperature and feed rate areinfluential to the attributes of spray-dried food suchas particle size, bulk density, moisture content,
average time of wettability and insoluble solids. The
carrier substances normally used in the spray dryingof fruit juice is maltodextin due to its high solubility
and low viscosity which is important conditions forthe spray drying method [3]. Date palm powder is aninteresting product because of its long shelf life atambient temperature, convenience to consume andlow transportation expenditure. Date palm powder
can be consumed as an instant juice powder or aflavoring agent. Some researchers reviewed thatdrying of fruit juice could produce the fruit powderthat reconstituted rapidly to a fine productresembling the original juice. It is because theproduct temperature is rarely raised above 100°c
during drying process. However, there are somedifficulties in drying techniques the date palm juicewith high sugar content, the sticky behavior of sugar
and acid rich materials such as fructose, glucose,

INTRODUCTION
Date palm is a kind of fruit as sweet taste andabundant in many essential and essential nutrients
including vitamins, minerals and dietary fiber, whichhave antioxidant effects. It has a long shelf life, andmany varieties, including the common Deglet Noor, are often sold dried and processed. Although
this fruit is small. In which one weight is about 7.5
grams and 100 grams of body gives 314 kilocalories
of energy and provides up to 10 minerals such ascopper, potassium, magnesium, selenium and etc. inamounts greater than 15 percent of the amountrecommended for each day. Polyphenol compoundthat helps prevent health problems caused by thedegeneration of the body, such as protecting cells
and tissues from being destroyed by free radicals. It
is also rich in vitamin C, vitamin B, vitamin K, ironand fiber. As a results, the date palm is a fruit thattastes good, quenches thirst, and has an easy form of
consumption. However, it can be processed into fruit
juice, which, when exposed to heat, causes physicaland chemical changes, such as the loss of smell,taste, easily during storage. There are also
limitations in storage area, temperature, humidity,
storage space and transportation costs. In order toenhance the nutritional quality of processed datepalm juice, the processing techniques must be
carefully selected [1]. Various drying processing
43

SEE - Kyoto, Japan, Nov.18-20, 2020

sucrose and organic acid such as citric acid, malic
acid and tartaric acid due to their thermoplasticity
and hygroscopicity at high temperatures andhumidities causing their packaging and utilization introuble. Jittanit et al 2010 has investigated that fresh
pineapple juices were added with maltodextrin at 15,
20 and 25 percent by spray drying before exposing
to the drying temperatures at 130, 150 and 170°c
with the feed rate 0.020, 0.022 and 0.035 litre perminute respectively. Then, the qualities of pineapple
powders and reconstituted pineapple powders were
investigated in the aspects of moisture content,solubility, color, pH and the consumer acceptance.
The results indicated that the pineapple juice should
be added with maltodextrin at 15 percent and driedat 150°c. Furthermore, the moisture content andsolubility of the pineapple powder produced under
this condition were 5.1 percent and 6.2 minutes
respectively while its solution had the lightness 58.8,
redness 5.2, yellowness 25.1 and pH 3.5 [4]. The
next research concluded that to determine thesuitable spray-drying conditions and the inulin
powder qualities. The inulin extracts at
concentrations of 10, 20, and 30 ºBrix were spraydried using the inlet/outlet drying temperatures at
150/90ºc. As a result, the feed material at 30 ºBrix
provided good characteristics of inulin powder withhigh powder recovery and low moisture content.
Then the drying experiments were conducted at inlet
air temperatures of 150, 170, and 190ºc whereas theoutlet air temperature and the JA extract
concentration were fixed at 90ºc and 30 ºBrix. It
appeared that the drying temperature of 190°c wasmore appropriate than 150°c and 170°c because it
provided higher powder recovery, lower moisture
content, better solubility and absorptivity, and morestability of powder. The SEM micrographs showedthat the inulin powders produced by the spray-drying
temperatures at 150°c and 170°c had more sphereshaped and had attached particles than those at
190°c [5]. The last research concerned about todevelop lime powder products with 20 percent of
combined maltodextrin and gum arabic at a ratio of
4:1. A high shear homogenization was applied toencapsulate phytochemical compounds before spraydrying with the purpose of protecting bioactive
compounds from thermal degradation. The particle
size, morphology, moisture content, color, solubility,
hygroscopicity, ascorbic acid, total polyphenol andflavonoid contents, antioxidant activity of the spraydried powder undergoing the homogenization werecompared with those of the non-homogenized
powder. The higher yield (30 percent) was obtainedin the homogenized powder compared with thecontrol (28 percent) with no significant difference.
The average particle diameter of the homogenized
powder was 0.1-4.0 micrometers, smaller than 18-26
micrometers of the untreated powder. Morphologicalstudy revealed that the powder without

homogenization was densely packed compared withthe homogenized powder. Moisture content ofhomogenized powder and that of the particles
without homogenization were 3.91 percent and 5.42
percent, respectively. Higher solubility and lesshygroscopicity values and color after spray drying
were observed in reconstituted lime powder withhigh shear homogenization [4]. However, due to theknowledge and technique about the production ofdate palm powder is still limited knowledge. This
study from finished date palm juice and it was thenspray dried into a powder form. The main factor
aims of this study were to determine the suitable
spray drying conditions and the date palm powder
characteristic as physico chemical qualities in termsof water activity, water solubility capability
percentage, brightness and color (L, a* and b*
values) moisture content and powder recovery
percentage of date palm powder.
METHODOLOGY
The research was carried out at the Division ofFood Science and Technology, Faculty ofAgricultural Technology, Rajamangala University ofTechnology Thanyaburi (RMUTT) Pathum Thani
Province Thailand.
Raw Material Preparation
The finished date palm juice was purchased by
the factory (In one date palm Brand) in
Kanchanaburi Province, Thailand. The preparedmixtures were diluted and filtered to remove
insoluble solids before spray drying [6].
The maltodextrin DE 10-12 was supplied from
Chemical Bangkok Co., Ltd in Bangkok, Thailand[6].
Determination of Suitable Spray Drying
Temperature for Date Palm Powder Production
The samples prepared by the proceduredescribed in the previous section (2.1) were dried ina Lab Plant Spray Dryer Model SD-Basic (Fig. 1).
The amounts of maltodextrin filled into the hotwater in order to provide maltodextrin content 20, 25
and 30 percent of the combination of hot water. The
maltodextrin content 20, 25 and 30 percent of thefeed mixture can be approximately converted to be
the ratios of date palm juice (based on total soluble
solids) until dissolved homogenous aliquot. The
drying experiments were carried out using threemaltodextrin content levels (20, 25 and 30 percent)and three inlet temperatures (130, 140 and 150°c) inorder to keep the temperature of the outlet drying air
at approximately 90°c. At the end of drying, the datepalm powders were collected, weighed, and kept in
the sealed container for the physico chemical quality
determination. The total weight value of powder
44

SEE - Kyoto, Japan, Nov.18-20, 2020

collected from each drying run was used for the
calculation of powder recovery percentage [6].

divided by the standard state partial vapor pressureof water. In the field of food science, the standard
state is most often defined as the partial vapor
pressure of pure water at the same temperature. Most
foods have a water activity above 0.95 and that will
provide sufficient moisture to support the growth ofbacteria, yeast, mold [6], [10]–[11]. The analysis of
the Water solubility capability of date palm
powdered showed in Table 2. In regard to the watersolubility capability, it showed that the amount ofsolubility of instantized powdered date palm. When
comparing the solubility of powder palm water at
the inlet air temperature of 130, 140 and 150°c, thevalue at the inlet air temperature at 150°c andmaltodextrin at 20, 25 and 30 percent, respectively,
had the capability to dissolve of 18.75, 16.51 and13.85 percent, respectively, and the inlet temperatureof hot air 140°c at 20 percent. Maltodextrin had thewater capability to dissolve of 19.24 percent and theinlet temperature of 130°c at 20 percent maltodextrin
had a solubility of 23.45 percent. Therefore, when
the inlet temperature was higher, resulted in a worse
solubility and absorptivity of the powder. This was
because the higher drying temperature caused ahigher drying rate leading to a less porous structureof the date powder [6], [10]–[12]. It was found thatthe amount of maltodextrin and the outlet hot air
temperature had no effect on solubility [6], [10]–[12]. Furthermore, the moisture content of thepowder sample produced from maltodextrin
concentration 30 percent was significantly lower
than those of 25 percent and 20 percent,respectively. This may be due to the fact that theincrease in solid contents of feed material led to the
reduction of water proportion in the feed. As aconsequence, when applying the same drying
temperature, the moisture content of date palm
powder was less than those of 25 and 20 percent
counterparts. The condition in which the product has
the most moisture is the condition with thetemperature of hot air inlet temperature 130°c andthe amount of maltodextrin 20 percent with moisture
content 4.03 percent and the condition with the least
moisture was the condition that has. The temperatureof hot air inlet temperature 150°c and the amount ofmaltodextrin 30 percent had a moisture of 2.15
percent. Because the increase in the temperature of
the hot air (inlet temperature) causes the moisture
content of reduced product. As higher temperaturescause the water in the product to evaporate more
quickly and more than the lower inlet temperature.
By considering the influence of inlet temperaturefound that the temperature rises, humidity
percentage will decrease. This is because when thetemperature rises, the water in the productevaporates more quickly and more than thetemperature of the hot air inlet is lower. At the sametime, it was found that when the amount ofmaltodextrin was increased, the moisture content of

Physico Chemical Quality of Date Palm
PowderSpray-dried date palm powder was analyzed formoisture content following by infrared method [7].
Brightness and color of the samples determinedusing a Hunter Laboratory Mini Scan XE
colorimeter (Hunter Associates, Reston, VA) in the
L*, a*, b* scale. L* represents lightness (0 ≤ L ≤100), while a*(+), a*(-), b*(+) and b*(-) represent
redness, greenness, yellowness, and blueness,
respectively [7]. Water activity (a w ) was measured
and recorded as values according to [7]. The
solubility of the powder (water solubility capability)
was evaluated according to the method described byadaptation [8]. The solubility was calculated using
the equation below:% solubility =weight of supernatant after drying x 100 (1)weight of sample

The powder recovery percentage of each spraydrying experiment was calculated applying theequation (2) [5].
% powder recovery =solid weight of powder after spray drying
x 100
total solid weight in raw material before spray drying(2)

Recording of Data
Data from experiments (three replications) werecollected and recorded numerical and statisticalanalysis. The Experimental design for physico
chemical quality analysis were evaluated by using a
Factorial Completely Randomized Design (CRD).
Analysis of variance and the mean differences ofexperiments was performed using Duncan’s new
multiple range test [9].
RESULTS AND DISCUSSION
The physical appearance of the date palm powder
spraydryingexperimentsusingvariousconcentrations of maltodextrin were illustrated in(Fig 2). Table 1 showed that as the inlet temperatureof the hot air increased, resulting in the value ofwater activity decreasing by the inlet temperature
150°c at 30 percent maltodextrin was as low as 0.15
and inlet temperature at 130°c at 20 percent
maltodextrin was the highest values which obtained
value of 0.32. Because the addition of maltodextrin
has an effect on increasing solid content andmaltodextrin binds with the water part, whichcorresponded in decreasing of water activity. Water
activity is the partial vapor pressure of in a substance45

SEE - Kyoto, Japan, Nov.18-20, 2020

the product will tend to decrease. This is because
maltodextrin has main properties as a drying aid. It
will reduce the moisture absorption characteristics
towards date palm powder products by using 30
percent maltodextrin have a lower moisture content
than 20 percent and 25 percent of maltodextrin,
respectively [6], [10]–[13]. Regarding the brightness(L*) and color (a* and b*) values, they revealed thatthe brightness of the solutions of date palm powders
were significantly different (P≤0.05) but except forredness and yellowness. In general, the solutions had
the more brightness than the redness and yellowness
were higher. The cause of the lower brightness wasthat a small proportion of powder could not dissolve
completely in the solution. As the temperature rises,
it results in a brown reaction causing the powder
palm water at the inlet temperature of 150°c toproduce less brightness than using the inlet
temperature at 130 and 140°c [6], [10]–[14]. The
another reason for the brightness decrease could be
the non enzymatic browning reactions occurring
during the spray drying [6], [10]–[15]. For thehigher redness and yellowness of the solutions, it
may be also as a result of some non-enzymaticbrowning reactions such as caramelization and
Maillard reactions happening during the drying
process. These reactions could take place because of
the high sugar content in the finished date palm juice
and heat supplied to the juice in the drying chamber[6], [10]–[16]. Maltodextrin has a white powder,when using higher maltodextrin concentration, thedate palm increased the brightness. Furthermore, themaltodextrin concentration is another cause of thecolor difference between the fresh, finished and thereconstituted date palm juices. However, the color
difference among reconstituted samples did not haveobvious trend because for these samples the spraydried powders were diluted in distilled water before
analysis. Moreover, the effect of drying temperatureon the product color was not apparent because thefeed rates were also increased at higher drying
temperature [6], [10]–[17]. The powder recovery as
percent values showed in Table 7. It indicated thatall drying conditions provided high powder recovery
in the range 15.87-25.02 percent. Although, thesevalues were very low, they were revealed that theconcentration of maltodextrin at 30 percent provided
a significantly higher powder recovery percentage
than those of 10 and 20 percent. Low powder
recovery values were due to the addition of
malodextrin contents greater than 20 percent that
resulted in the non-sticky products and subsequently
low amount of product sized in the drying chamberand cyclone [6], [17]–[19]. Besides, there was atrend of better powder recovery along the increasing
maltodextrin concentrations. This occurrence might
be explained by the method applied for the powder
collection. In this study, all the powder (eachtreatment) was collected at the cyclone; nonetheless,the drying chamber was periodically knocked by the
hard-rubber hammer during the experiment in orderto keep the remaining powder on the drying chamber
surface and its accessories as minimum as possible.
As a result, although the powder recovery
percentage was very low for every drying run, there
were higher amount of powder stuck in the drying
system for the drying conditions that had more totalsoluble solids in the inlet feed (added higher
maltodextrin concentration) because of the limitation
using of the hammer force applied in this powder
collection method [6], [17]–[20]. On the other hand,
if at the end of drying run, all the powder on thedrying chamber surface was manually swept andcombined with those collected at the cyclone, thetrend of powder recovery percentage might change
from the original characteristic [6], [17]–[21].
Table 1 Water activity of instantized date palm
powder by variation of 3 inlet temperature.
Maltodextrin(%)

Water activity
Inlet temperature (°c)*
130°c
140°c
150°c
20
0.32a
0.31a
0.26a
b
b
25
0.27
0.24
0.24b
30
0.25b
0.18c
0.15c
Note: *a-d The different letters in the same column
mean significant difference (P < 0.05)
Table 2 Water solubility capability of instantized
date palm powder by variation of 3 inlet
temperature.
Maltodextrin(%)

Water solubility capability (%)
Inlet temperature (°c)ns

130°c
140°c
20
23.45
19.24
25
21.89
26.21
30
22.84
18.70
Note: ns = non-significant difference

150°c
18.75
16.51
15.33

Table 3 Moisture content of instantized date palm
powder by variation of 3 inlet temperature.
Maltodextrin(%)

Moisture content (%)
Inlet temperature (°c)*
130°c
140°c
150°c
a
a
20
4.03
3.84
2.88a
b
b
25
3.52
3.29
2.39b
30
3.21c
2.39c
2.15c
Note: *a-d The different letters in the same column
mean significant difference (P < 0.05)

46

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 4 Brightness of instantized date palm powder
by variation of 3 inlet temperature.
Maltodextrin(%)

Brightness
Inlet temperature (°c)*
130°c
140°c
150°c
20
55.99b52.86c52.01c25
56.39b56.26b55.97b
a
ab
30
59.21
58.38
58.63abNote: *a-d The different letters in the same column
mean significant difference (P < 0.05)
Table 5 Redness of instantized date palm powder byvariation of 3 inlet temperature.
Maltodextrin
(%)
20
25
30

Redness
Inlet temperature (°c)ns
130°c
140°c
150°c
0.52
0.81
1.26
1.23
0.56
1.12
1.26
0.81
1.16

Fig. 2 Physical appearance of date palm powder
after spray drying.
CONCLUSION
1. The results showed that the practicability of
producing the date palm powders from finished datepalm juice and the aliquots of maltodextrin by
applying the spray drying method. After
reconstituting the date palm powder in the distilledwater,
themostappropriate
maltodextrin
concentration for spray drying was 30 percent, while
the inlet temperature of 150°c was more appropriate
for date palm production than 130°c and 140°c.
Because, it provided a higher powder recovery,
lower moisture content, better solubility andabsorptivity, and more stability of powder.
2. There are useful for the fruit powder producers
and researchers., the researchers will be able tolaunch new products in the future by selecting theappropriate other Thai local fruits and vegetables
that develop processes and industrial scale processes
that are essential to the bench-to-bedside translationof innovative instant powdered fruit and vegetable
beverage products.

Note: ns = non-significant difference
Table 6 Yellowness of instantized date palm powder
by variation of 3 inlet temperature.
Maltodextrin(%)

Yellowness
Inlet temperature (°c)ns
130°c
140°c
150°c
20
33.48
32.23
32.44
25
34.25
33.31
33.14
30
32.50
32.18
32.92
Note: ns = non-significant difference
Table 7 Powder recovery of instantized date palm
powder by variation of 3 inlet temperature.
Maltodextrin(%)

Powder recovery (%)
Inlet temperature (°c)*
130°c
140°c
150°c
20
15.87a18.23a19.76a25
16.78ab20.42b
23.87b
b
c
30
22.12
23.12
25.02cNote: *a-d The different letters in the same column
mean significant difference (P < 0.05)

ACKNOWLEDGMENTS
The researchers would like to thank the 4 th gradestudents and officials of the Division of Food
Science and Technology, the Faculty of Agricultural
Technology Rajamangala University of Technology
Thanyaburi (RMUTT), Pathum Thani Thailand that
contributed some parts in the research. The Facultyof Agricultural Technology provided support
facilities and budgets on our research and travel
expense for this conference.
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Fig. 1 Lab Plant Spray Dryer Model SD-Basic.

47

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uses, and cultivation, HORTSCIENCE, Vol. 42,
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[4] Jittanit W., Niti-Att S., and Techanuntachaikul
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[5] Jirayucharoensak1 R., Jittanit W., andSirisansaneeyakul S., Spray drying for Inulin
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[6] Tiyakulpanich K., and Kongratch A.,
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[7] AOAC, Official method of analysis, Verginia:
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[8] Cano-chauca M., Stringheta P.C., Sardagna,
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[9] Damnum A., Statistical analysis and data
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[10] Kha T.C., Nguyen M.H., and Roach P.D.,
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the Gac (Momordica cochinchinensis) fruit aril
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No. 3, 2010, pp.385-392.
[11] Sawaya W., Miski A., Khalil J., Khatchadourian
H. and Mashadi A., Physical and chemical
characterization of the major date varieties
grown in Saudi Arabia: I Morphologicalmeasurements, proximate and mineral analyses,
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[12] Peighambardoust S.H., Golshan Tafti A., andHesari J., Application of spray drying forpreservation of lactic acid starter cultures: A
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[13] Adhikari B., Howes T., Bhandari B.R., andTroung V., Characterization of the surface
stickiness of fructose-maltodextrin solutions
during drying, Dry. Technol, Vol. 21, No. 1,
2003, pp.17-34.
[14] Adhikari B., Howes T., Bhandari B.R., andTroung V., Effect of addition of maltodextrin on
drying kinetics and stickiness of sugar and acidrichfoods
duringconvective
dryingexperiments and modeling, J. Food Eng, Vol. 62,
No. 1, 2004, pp.53-68.
[15] Sinija V.R., Mishra H.N., and Bal S., Process
technology for production of soluble tea powder,
J. Food Eng, Vol. 82, No. 1, 2007, pp.276-283.
[16] Grabowski J.A., Truong V.D., and Daubert C.
R., Spray drying of amylase hydrolyzed
sweetpotato puree and physicochemical
properties of powder, Journal of Food Science,Vol. 71, No. 1, 2006, pp.E209-E217.
[17] Finney J., Buffo R., and Reineccius G.A.,
Effects of type of atomization and processing
temperatures on the physical properties andstability of spray-dried flavors, Journal of Food
Science, Vol. 67, No. 3, 2002, pp.1108-1114.
[18] Jaya S., and Das H., Effect of maltodextrin,
glycerol mono stearate and tricalcium phosphate
on vacuum dried powder properties, Journal of
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[19] Bhandari B.R., Snoussi A., Dumoulin E.D., andLebert A., Spray drying of concentrated fruit
juices, Dry Technol, Vol. 11, No. 5, 1993,
pp.1081-1092.
[20] Fazaeli M., Djomeh Z.E., Ashtari A.K., andOmid M., Effect of spray drying conditions andfeed composition on the physical properties of
black mulberry juice powder, J. of Food andBioproducts Processing, Vol. 90, No. 1, 2012,
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[21] Sarabandi K., Peighambardoust S.H., andShirmohammadi M., Physical properties ofspray dried grape syrup as affected by drying
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48

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

PARTIAL REPLACEMENNT OF CEMENT WITH FLY ASH AND FGD
GYPSUM TO DEVELOP STRENGTH OF SUBBASE
Pisut Rodvinij1 and Chotikan Ratchakrom2
Faculty of Engineering, Rajamangala University of Technology Lanna, Thailand; 2Faculty of Industrial
Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage, Thailand

1

ABSTRACT
Portland cement is used as an admixture to improve the strength of poor subbase. However, this induced a highcost for the road construction. The replacement of cement with by-product materials from Mae Moh power plantin the admixture is a good alternative to reduce the amount of cement and reduce the cost for subbase improvement.
Therefore, this study focused on fly ash, and FGD gypsum replaced cement in the admixture. The soil samples
mixed with the admixture at 3% were conducted on unconfined compressive strength test to determine the strengthof soil improvement. The results demonstrated that soil mixed with cement at 1%, fly ash 1.5%, and FGD gypsum
0.5% can develop the compressive strength more than the requirements recommended by the Thailand Departmentof Highways. The compressive strength of soil improvement was 702 kPa. This admixture can develop the strengthof soil 384 kPa from the non-improvement soil. Moreover, the strength of soil mixed with cement at 1.5%, fly ash
1%, and FGD gypsum 0.5% can reach 90% of the soil mixed with cement at 3%. The results showed that thestrength of soil improvement tended to increase with an incremental amount of fly ash. However, the strength ofsoil improvement decreased with the increased FGD gypsum in the admixture. In conclusion, the partial
replacement of cement by fly ash and FGD gypsum can develop the strength of soils and reduce the amount of
cement in the admixture.
Keywords: Fly ash, FGD gypsum, Soil improvement, Compressive strength, Subbase

strength and high-performance concrete. ASTM
broadly classifies fly ash two classes, Class F andClass C. Class F fly ash is normally produced byburning anthracite or bituminous coal and has
pozzolanic properties only. While Class C fly ash isnormally produced by burning lignite or subbituminous coal and can possess pozzolanic as wellas cementitious properties [3]. Mae Moh lignite fly
ash is a Class C type. The chemical composition of
fly ash includes 30.1% CaO, 20.6% SiO 2 , 16.1%
Al 2 O 3 , 6.1% SO 3 , 12.0% Fe 2 O 3 , 1.9% MgO, 1.7%
Na 2 O, 2.2% k 2 O, 1.0% TiO 2 , 8.3% etc. Fly ash has
all the quality of being a pozzolan material [4]. In the
cement hydration development, the calcium silicate
hydrate (C-S-H) and calcium hydroxide (Ca (OH) 2 ,or CH) are released within the hydration of two main
components of cement namely tricalcium silicate(C 3 S) and dicalcium silicate (C 2 S) where C, S
represent CaO and SiO 2 . The C-S-H gel is generated
by the hydration of C 3 S and C 2 S. This is the mainstrengthening constituent [5]. It is known that byadding pozzolanic material to the mortar of concretemix, the pozzolanic reaction will only start when CH
is released/CH interaction exit. In the pozzolan-lime
reaction, OH- and Ca2+ react with the SiO 2 or Al 2 O 3 SiO 2 framework to form calcium silicate hydrate (CS-H), calcium aluminate hydrate (C-A-H) andcalcium aluminate ferrite hydrate [6]. Normally, fly
ash is used as a pozzolanic material in the concrete
industry. The partial replacement of Portland cementwith fly ash reduces the heat of hydration and

INTRODUCTION
The lateritic soil has been used in the road
construction of Thailand and widespread in the ruralarea. Subbase of the road in Thailand was constructedby lateritic soil. However, it becomes the realize
problem because of the low compressive strength ofthe poor lateritic soil and poor durability. The bearing
capacity of poor subbase was lower than theminimum requirement for the road construction.
Moreover, the rain infiltration or the water inundatesof the subbase can be causing road damage [1].
The most commonly used additive for soil
stabilization is ordinary Portland cement. To build a
subbase with cement stabilized ash alone is not yet
common, but this is one of the high volume ash
applications being promoted by ash producers [2].
The use of ash or the pozzolanic materials combinedwith cement to improve the strength of soil can reducethe cost of soil stabilization. Therefore, this study
investigated the replacement of cement with fly ash
and FGD gypsum to improve the strength of poor
subbase.
Mae Moh power plant produces three types oflignite by-products from the lignite-fired power
generation include fly ash, bottom ash, and FGD
gypsum. Fly ash is the most widely used pozzolanicmaterial all over the world. In recent times, theimportance and use of fly ash in concrete have grownso much that it has almost become a common
ingredient in concrete, particularly for making high49

SEE - Kyoto, Japan, Nov.18-20, 2020

improves the strength and durability of concrete [7],[8].
SO 2 is one of the major environmental
contaminations generated from coal-burning power
stations and heating plants. It is very important todevelop flue gas desulphurization (FGD)
technologies to remove SO 2 for FGD clean coal
combustion. Although FGD technology is successful
in reducing SO 2 discharge, it generates a large
quantity of FGD gypsum at the same time. FGD
gypsum from Mae Moh power plant is shown in
Figure 1. The chemical composition of FGD gypsum
includes 37.7% CaO, 4.0% SiO 2 , 2.0% Al 2 O 3 , 54.1%
SO 3 , 0.5% FeO 3 , 1.6% MgO, 0% Na 2 O, 0.1 k 2 O, 0%
TiO 2 [9]. Normally, FGD gypsum contains in the
mixture of mortar can increase the durability andcompressive strength [10], [11]. FGD gypsum iseffective in providing the additional calcium andsulfate required to activate the clinker to form
ettringite. The compressive strength produces highearly strength than ordinary Portland cement.
Additional long-term strength is possible provided byhydration of dicalcium silicate (C 2 S) within theclinker [12]. However, the excessive amount of FGD
gypsum can decrease the workability and the strengthof mortar [13].

gypsum were used as an admixture to improve thestrength of soil. Fly ash and FGD gypsum wereobtained from Mae Moh power plant. All admixtures
stored in plastic bags to maintain their dry condition.
The soil samples were mixed with cement, fly ash,and FGD gypsum in the ratio according to Table 1.
The amount of admixture mixed with the soil samples
was 3% by weight. Table 1 shows the mixture codeof C, D, and E was fly ash, and FGD gypsum replace
cement in the mixture.
Table 1 The mixture ratio of the admixture forstabilized the soil samples
Mixture
code
A
B1
B2
C1
C2
C3
C4
C5
D1
D3
D4

Cement
(%)
1.5
3.0
0.5
0.5
0.5
0.5
0.5
1.0
1.0
1.0

Fly Ash
(%)
0.5
1.0
1.5
2.0
1.0
1.5

FGD
Gypsum (%)
2.5
2.0
1.5
1.0
0.5
2.0
1.0
0.5

E1
E2
E3

1.5
1.5
1.5

0.5
1.0

1.5
1.0
0.5

This study investigated on the partial replacementof cement with fly ash and FGD gypsum to develop
the strength of poor subbase. The mixture code ingroup A presented the non-improvement soil samples.
The mixture code in group B presented soil mixed
with cement at 1.5-3.0%. Whereas, the mixture ingroup C represented the soil samples mixed withcement at 0.5%, fly ash 0-2.0%, and FGD gypsum
0.5-2.5%. The mixture code in group D presented thesoil samples mixed with cement at 1.0%, fly ash 01.5%, and FGD gypsum 0.5-2.0%. The mixture codein group E presented the soil samples mixed withcement at 1.5%, fly ash 0-1.0%, and FGD gypsum
0.5-1.5%. The combination of cement, fly ash, and
FGD gypsum of the admixture in groups C, D, and E
was 3%.
The soil samples mixed with the admixture in theratio according to Table 1 were compacted by themodified compaction test method. The moisture usedin the compaction method was the optimum moisture
content (OMC) of soil. The samples were manuallycompacted in five equal layers using the modified
compaction effort. After completing the compaction
process, each sample was extruded from thecompaction mold and then cured in the plastic bag for
3, 5, and 7 days. Following the curing process, thesamples were soaked in water for 2 hours, and thenFig. 1 FGD gypsum obtained from Mae Moh power
plant.
Therefore, the objective of this study is toinvestigate the utilization of fly ash and FGD gypsum
to improve the strength of lateritic soil and reduce thecost of soil improvement. The target strength of thesoil improvement is 689 kPa. This target strength isrecommended by the Thailand Department ofHighways.
MATERIALS PREPARATION AND MIXTURE
OF SOIL IMPROVEMENT
The poor quality of lateritic soil was used in thisexperiment. The strength of the soil samples was lessthan the requirement of the Thailand Department ofHighways. The soil samples were conducted on
Atterberg limits test and sieve analysis test to
determine the properties and classification of thesamples. Portland cement type 1, fly ash, and FGD
50

SEE - Kyoto, Japan, Nov.18-20, 2020

compressed the samples by the compression machine,
as shown in Fig.2. The compressive strength values
for each mixture are the average of three specimens.

100
90

Size Distribution of Soil Samples

80

Percent Finer (%)

70
60
50
40
30
20
10
0
0.01

1

0.1

10

Particle Size (mm)Fig. 3 Particle size distribution of the soil samples.

2000

Dry Density (kg/m3)

1950

Fig. 2 The samples conducted on unconfinedcompressive strength tests.

1900
1850
1800
1750
1700
1650

The results can represent the possibility to use byproduct materials replace cement in the admixture.
However, the Thailand Department of highways
suggested that the unconfined compressive strengthof subbase improvement should be more than 689 kPa
at the curing time of 7 days. Therefore, the optimum
content of fly ash and FGD gypsum replaced cementin the admixture to improve the strength of soil canbe determined.

1600
6

7

8

9
10
Moisture Content (%)

11

12

13

Fig. 4 The relation between dry density and moisture
content of the soil samples.
Unconfined Compressive
Improvement

Strengthof

Soil

The unconfined compressive strength of the nonimprovement soil (A) was 318 kPa. The results
illustrated that the strength of the soil samples
increased when the soil mixed with an admixture. The
unconfined compressive strength of the soil mixed
with the admixture in group C is shown in Fig 5. The
results demonstrated that the strength of C5 washigher than the soil mixed with cement at 1.5% andgave the highest strength in group C. The
compressive strength of C5 was 471 kPa, while thecompressive strength of B1 was 456 kPa at the curing
time of 7 days. The compressive strength of C5
increased by 3% from B1. However, by-productmaterials can develop the compressive strength of C5
by approximately 10% from B1 at the curing time of
3 days. Moreover, the compressive strength of C4
was near the samples B1 at the curing time of 5 days
and 7 days. Nevertheless, the compressive strength of
C4 increased by 5% from B1 at the curing time of 3days. Therefore, this result represented that the
replacement of cement with fly ash and FGD gypsum
efficient to develop the strength of soil, especially at
3 days. Nevertheless, the compressive strength of soil
improvement with the admixture in group C was
lower than the suggestion of the Thailand Departmentof highways.

RESULTS AND DISCUSSIONSEngineering Properties of Lateritic Soil
The soil samples were conducted on Atterberg
limits test, sieve analysis test, and modified
compaction test to determine the engineering
properties of the soil samples. The results
demonstrated that the liquid limit, plastic limit, andplasticity index of the soil samples was 27%, 17%,and 10%, respectively. Fig. 3 shows the particle size
distribution of the soil samples in this study.
According to the AASHTO classification system, thesoil samples were A-2-4. The gradation of the soil
sample is excellent or good for subgrade materials
when considered on the general subgrade rating of
AASHTO. Moreover, the results of modified
compaction tests are shown in Fig.4. The results
demonstrated the maximum dry density of the soil
samples was approximately 1,978 kg/m3, andoptimum moisture content was 10.9%.

51

SEE - Kyoto, Japan, Nov.18-20, 2020

admixture in group E was less than B2, approximately
10-15% at the curing time of 7 days. Therefore, theresults demonstrated that the replacement of cementwith fly ash and FGD gypsum can develop earlystrength. FGD gypsum consists of SO 3 approximately
54.1%. SO 3 seems to be responsible for the higher
early compressive strength. However, the later
strength is controlled mainly by calcium silicate
hydrate [14]. Fly ash affects the early strength gainprobably due to the free lime that is still reacting
during the curing process [3].
Moreover, the samples in group E can develop
compressive strength higher than the samples B1.
While the mixture in group E and B1 used a similar
amount of cement at 1.5%. However, the admixture
in group E added fly ash at 0-1.0% and FGD gypsum
at 0.5-1.5%. The results illustrated the strength of thesamples in group E was higher than the samples ingroup B1 approximately, 58-77%, 67-74%, and 6476% at the curing time of 3 days, 5 days, and 7 days,
respectively. Therefore, the results verified the
addition of fly ash and FGD gypsum in the admixture
can develop the strength of soil.
Consideration of the compressive strength of soil
improvement at the curing time of 7 days, the results
demonstrated that the strength in this group was
higher than the requirement at 689 kPa. The
compressive strength of E1, E2, and E3 at the curing
time of 7 days was 748 kPa, 768 kPa, and 804 kPa,
respectively.

480

Compressive Strength (kPa)

460
440
420
400
380
360
B1
C2
C4

340
320

C1
C3
C5

300
3

4

5

6

7

Curing Time (Days)

Fig. 5 Unconfined compressive strength of the soil
mixed with an admixture in group C.
The results of the soil samples mixed with
admixture in group D are shown in Fig. 6. Cement
content of the admixture in group D was 1%. Fig.6
shows the strength of the soil samples mixed with theadmixture in group D can reach 70-92% and 66-78%of the samples B2 at 5 days and 7 days, respectively.
The compressive strength of D1, D2, D3, and D4 atthe curing time of 7 days was 589 kPa, 599 kPa, 625
kPa, and 702 kPa, respectively. D4 has the highest
compressive strength of the mixture in this group.
Moreover, the results demonstrated the compressive
strength of soil mixed with admixture D4 was higher
than B1, approximately 51-54%. While the samples
D4 used cement less than B1 at 0.5%. Therefore, thisresult can verify the replacement of by-productmaterials in the admixture to develop the compressive
strength of soils. Moreover, the strength of D4 wasnear B2 at 3 days. The compressive strength of D4 at
3 days was 579 kPa. However, the compressive
strength of D4 less than B2 at 5 days and 7 days.

Compressive Strength (kPa)

1000

Compressive Strength (kPa)

1000
900
800

B1

B2

D1

D2

D3

D4

B1
E1
E3

900

B2
E2

800
700
600
500
400

700
300

600

3

4

5

6

7

Curing Time (Days)

500

Fig. 7 Unconfined compressive strength of the soil
mixed with an admixture in group E.

400
300
3

4

5

6

7

Curing Time (Days)

Effect of Fly Ash and FGD Gypsum on Strengthof Soil Improvement

Fig. 6 Unconfined compressive strength of the soil
mixed with an admixture in group D.

The effect of fly ash and FGD gypsum on thecompressive strength of soil improvement is shown in
Fig. 8, Fig. 9, and Fig. 10. The results demonstrated
that the strength of soil improvement tended toincrease with fly ash increment. However, thecompressive strength of soil improvement was
decreased by the increase of FGD gypsum in the
admixture.
Fig. 8 shows the relation between the compressive
strength, amount of fly ash, and FGD gypsum in theFig. 7 shows the compressive strength of thesamples mixed with the admixture in group E. The
results demonstrated that the strength of soil mixed
with the admixture in group E was higher than B2,
approximately 5-17% at the curing time of 3 days.
Moreover, the samples mixed with the admixture inthis group can develop the strength of 2-6% from B2
at the curing time of 5 days. However, thecompressive strength of the soil mixed with the52

SEE - Kyoto, Japan, Nov.18-20, 2020

admixture group C. The results demonstrated thestrength increased by approximately 12-18% when
fly ash increased from 0% to 2.0% and FGD gypsum
reduced from 2.5% remaining to 0.5%.

2

FGD Gypsum (%)
1.5

1

0.5

Compressive Strength (kPa)

490
470

1

0.5

850
Compressive Strength (kPa)

2.5

FGD Gypsum (%)
1.5

Cement 0.5 %450

Cement 1.5 %

800
750
700
650

3 days600

5 days550

7 days

500
430

0

0.5

410

1

Fly Ash (%)
3 days390

5 days370

Fig. 10 Relation between the compressive strength,
fly ash, and FGD gypsum in the admixture group E.

7 days

350
0

0.5

1

1.5

2

Strength Requirement for Subbase Improvement

Fly Ash (%)

Fig. 8 Relation between the compressive strength, flyash, and FGD gypsum in the admixture group C.

The unconfined compressive strength of subbase
improvement suggested by the Thailand Departmentof Highways was 689 kPa. Fig. 11 shows the strengthof soil mixed with an admixture at the curing time of
7 days. The results demonstrated that the samples
passed the requirement include B2, D4, E1, E2, andE3. The unconfined compressive strength of B2, D4,
E1, E2, and E3 was 889 kPa, 702 kPa, 748 kPa, 768
kPa, and 804 kPa, respectively.

Fig. 9 shows the relation between the compressive
strength, amount of fly ash, and FGD gypsum in the
admixture group D. The results demonstrated that thecompressive strength increased 20-31% when fly ash
increased from 0% to 1.5%, and FGD gypsum
reduced from 2.0% remaining to 0.5%. The strength
rapidly increased when fly ash increased from 1.0%
to 1.5%, and FGD gypsum decreased from 1.0%
remaining to 0.5%.

1000
Target900
889

FGD Gypsum (%)
1.5
1

2

Compressive Strength (kPa)

800

0.5

Compressive Strength (kPa)

750
700

Cement 1 %

650
600
550
500

3 days450

5 days400

7 days
0.5

1

768

804

702

600
589

599

625

500
400

456

420

425

440

461

471

300
200
100
0

B1 B2 C1 C2 C3 C4 C5 D1 D2 D3 D4 E1 E2 E3

350
0

748

700

Fig. 11 Unconfined compressive strength of the soil
improvement at the curing time of 7 days.

1.5

Fly Ash (%)

Fig. 12 shows the relation between thecompressive strength and cement content in the
admixture. The results demonstrated that the strengthof soil tended to increase with cement increment. The
mixture D4 can develop the strength higher than therequirement. Whereas the cement content of D4 lessthan B2 and the admixture group E at 2% and 0.5%,
respectively. Moreover, the strength of D4 can reach
79% of B2, while D4 used cement only 33% of B2.
The results presented that E3 used cement content,
only 50% of B2. However, the compressive strengthof E3 can reach 90% of B2. Therefore, the use of
admixture D4 and E3 to improve the strength of soil
can reduce the cost for construction approximately

Fig. 9 Relation between the compressive strength, flyash, and FGD gypsum in the admixture group D.
Fig. 10 shows the relation between thecompressive strength, amount of fly ash, and FGD
gypsum in the admixture group E. The results
demonstrated that the compressive strength increased
5-12% when fly ash increased from 0% to 1.0%, and
FGD gypsum decreased from 1.5% remaining to
0.5%. The results presented the strength of soil
samples mixed with admixture groups C, D, and E
tended to increase with fly ash increment and the
reduction in FGD gypsum.

53

SEE - Kyoto, Japan, Nov.18-20, 202067% and 50%, respectively.
3

3
Cement Content

Target

900
889

2.5

Compressive Strength (kPa)

800
700

702

804

768

748

2

600
1.5

500

1.5

1.5

1.5

400
1

1

300
200

Cement Content (%)

1000

Chiang Mai University, Doctoral Thesis, 2019.
[5] Omotosoa O. E., Ivey D.G., and Milulab R.,
Characterization of Chromium Doped Tricalcium
Silicate Using SEM/EDS, XRD and FTIR,
Journal of Hazardous Materials, 1995, pp.87-102.
[6] Villar C. E., Valencia M. E., Gonzalez R. R., andHarnandez R. J., Kinetics of the Pozzolanic
Reaction between Lime and Sugar Cane Straw
Ash by Electrical Conductivity Measurement: A
Kinetic-Diffusive Model, Cement Concrete
Research, 2003, pp.517-524.
[7] Chindaprasirt P., Jaturapitakkul C., Chalee W.,
and Rattanasak U., Comparative Study on The
Characteristics of Fly Ash and Bottom Ash
Geopolymers, Waste Management, Vol. 29, 2008,
pp. 539-543.
[8] Englehardt J. D., and Peng C., Pozzolanic
Filtration/Solidification of Radionuclides in
Nuclear Reactor Cooling Water, Waste
Management, 1995, pp. 585-592.
[9] Boonserm k., Sata V., Pimraksa k., andChindaprasirt P., Improved Geopolymerization of
Bottom Ash by Incorporating Fly Ash and Using
Waste Gypsum as Additive, Cement Concrete
Composites, Vol. 34, 2012, pp. 819-824.
[10] Guo X. L., and Shi H. S., Thermal Treatment andUtilization of Flue Gas Desulphurization Gypsum
as An Admixture in Cement and Concrete,
Construction and Building Materials, Vol. 22,
2008, pp. 1471-1476.
[11] Guo X. L., Shi H. S., and Liu H. Y., Effects ofCombined Admixture of Slag Powder and
Thermally Treated Flue Gas Desulphurization(FGD) Gypsum on The Compressive Strength andDurability of Concrete, Materials and Structures,Vol. 42, 2009, pp. 263-270.
[12] Jewell R. B., Rath R. F., Duvallet T.Y., Robl T.
l., and Mahboub K. C., Fabrication and Testing of
Low-Energy Calcium Sulfoaluminate-Bilite
Cements that Utilize Circulating Fluidized Bed
Combustion By-Products, Coal Combustion and
Gasification Products, 2015, pp. 9-18.
[13] Rodvinij P., Wattanachai P., and Chaiwithee S.,
The Effect of FGD Gypsum Addition in The
Mixture of Shotcrete Used Bottom Ash as Fine
Aggregate, International Journal of GEOMATE,
Vol. 16, Issue 57, 2019, pp. 1-8.
[14] Agabaglou A. M., Boyaci O. C., Hosseinnezhad
H., Felekoglu B., and Ramyar K., Effect ofGypsum Type on Properties of Cementitious
Materials Containing High Range Water
Reducing Admixture, Cement and Concrete
Composites, Vol. 68, 2016, pp. 15-26.

0.5

100
0

0
B2

D4

E1

E2

E3

Fig. 12 Relation between compressive strength andcement content.
CONCLUSIONS
Based on the results obtained from this study, thefollowing conclusion was made:1. The replacement of cement with fly ash and
FGD gypsum can increase the strength of poor
subbase and reduce cement content in the admixture.
2. The strength of subbase improvement bycement at 1.5%, fly ash 1.0%, and FGD gypsum 0.5%
can reach 90% of the soil mixed with cement at 3%.
This result shows the replacement of cement with fly
ash and FGD gypsum can develop the strength ofsubbase.
3. The compressive strength of soil improvement
tended to increase with incremental fly ash in the
admixture. However, the compressive strength of soil
improvement decreased with the incremental FGD
gypsum.
4. The replacement of cement with fly ash at 1.5%
and FGD gypsum at 0.5% was the optimum content
to replace cement in the admixture. This mixture candevelop the strength of soil more than the requirementof the Thailand Department of Highways, and it can
reduce costs by approximately 67%.
REFERENCES[1] Ratchakrom C., The Effect of Bottom Ash andKaolin on The Strength of Poor Subbase,
International Journal of GEOMATE, Vol. 16,
Issue 57, 2019, pp. 76-81.
[2] Hausmann M. R., Modification by admixture,Engineering Principles of Ground Modification,
International Edition, McGraw-Hill Publishing
Company, 1990, pp. 302-324.
[3] Bendapudi S. C. K., and Saha, P., Contribution of
Fly Ash to The Properties of Mortar and Concrete,
International Journal of Earth Science andEngineering, Vol 04, 2011, pp. 1017-1023.
[4] Rodvinij P., Slope Stability Improvement ofClaystone Backfill by Rock Bund and Shotcrete
Mixed with By-Product Materials from Mae Moh
Power Plant, Department of Civil Engineering,54

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

THE VARIATIONAL ITERATION METHOD FOR SOLVING
VOLTERRA INTEGRAL EQUATION OF THE SECOND KIND USING
MAPLE
Dalal Adnan Maturi 1
1

Departement of Mathematics, Faculty of Science, King Abdulaziz University, P.O.Box 42664,Jeddah 21551,
Saudi Arabia
ABSTRACTIn this paper, the Variational Iteration Method (VIM) is applied to obtain an approximate solution to linear
and non-linear Volterra equations. The Volterra integral equation in mathematics is a special case of integral
equations. Volterra integral equations have applications in demographics as well as the study of viscous elastic
materials as well as in risk mathematics through the theory of regeneration in probability theory. By means of thismethod an algorithm Maple is successfully established for solving Volterra integral equation of the second kind.
Finally, several examples are presented to illustrate the application of the algorithm. The study revealed that the
Variational iteration method are effective methods for solving the Volterra integral equation of the second type.
And, the results demonstrate great potential and potential for methods as algorithms in order to obtain the exact
solution of Volterra integral equation of the second kind and the results demonstrate great potential and potential
for methods as algorithms using Maple18 in order to obtain the exact solution of Volterra integral equation of thesecond kind.
Keywords: Volterra Integral Equation Of The Second Kind, Variational Iteration Method, Maple18 .

INTRODUCTION𝑳𝑳𝑳𝑳 + 𝑵𝑵𝑵𝑵 = 𝒈𝒈(𝒙𝒙),In this paper, we consider the Volterra integral
equation of the second kind [ 1,2,3,17,18,21,28,31]𝒙𝒙

𝒖𝒖(𝒙𝒙) = 𝒇𝒇(𝒙𝒙) + 𝝀𝝀 ∫𝟎𝟎 𝑲𝑲(𝒙𝒙, 𝒕𝒕)𝒖𝒖(𝒕𝒕)𝒅𝒅𝒅𝒅(2)

where L and N are linear and nonlinear operators
respectively, and g(x) is the inhomogeneous source
term. The variational iteration method admits the useof a correction functional for Equation (2) in the
form

(1)

The unknown function 𝒖𝒖(𝒙𝒙),The kernel 𝑲𝑲(𝒙𝒙, 𝒕𝒕) andthe function 𝒇𝒇(𝒙𝒙) are given real-valued functions,and 𝝀𝝀 is a parameter.
Volterra integral equation has many scientificapplications, and many numerical and analyticalmethods can also be applied to Volterra integral
equation from [4-32]. Also, The variational iteration
method; a reliable tool for solving linear andnonlinear wave equations [1] , and the variational
iteration method for solving the Volterra integrodifferential forms of the lane-Emden and the EmdenFowler problems with initial and boundary value
conditions [3], the modified decomposition method
for solving Volterra integral equation of the second
kind using Maple [28], the modified decomposition
method for solving Volterra Fredholm integrodfferential equation using Maple [31].

𝒙𝒙�𝒏𝒏 (𝒕𝒕) −𝒖𝒖𝒏𝒏+𝟏𝟏 (𝒙𝒙) = 𝒖𝒖𝒏𝒏 (𝒙𝒙) + ∫𝟎𝟎 𝝀𝝀(𝒕𝒕) �𝑳𝑳𝒖𝒖𝒏𝒏 (𝒕𝒕) + 𝑵𝑵𝒖𝒖
𝒈𝒈(𝒕𝒕)�𝒅𝒅𝒅𝒅,(3)

where 𝝀𝝀 is a general Lagrange’s multiplier, which
can be identified optimally via the variational
theory, and ˜un is a restricted variation which means�𝒏𝒏 = 𝟎𝟎. The Lagrange multiplier 𝝀𝝀 is crucial and𝜹𝜹𝒖𝒖
critical in the method, and it can be a constant or afunction. Having 𝝀𝝀 determined, an iteration formula
should be used for the determination of thesuccessive approximations 𝒖𝒖𝒏𝒏+𝟏𝟏 (𝒙𝒙), 𝒏𝒏 ≥ 𝟎𝟎 of thesolution u(x). The initial approximation u0 can be
any selective function. However, the initial values𝒖𝒖(𝟎𝟎), 𝒖𝒖′(𝟎𝟎) and 𝒖𝒖′′(𝟎𝟎) are preferably used for theselective zeroth approximation u0 as will be seen
later. Consequently, the solution is given by

In this paper, we present paper is to study thesolution of Volterra integral equation of thesecond kind using algorithm Maple18.

𝒖𝒖(𝒙𝒙) = 𝐥𝐥𝐥𝐥𝐥𝐥 𝒖𝒖𝒏𝒏 (𝒙𝒙)𝒏𝒏→∞

THE VARIATIONAL ITERATION METHOD(VIM)Consider the differential equation [3]55(4)

It is interesting to point out that the distinct forms of
the Lagrange multipliers 𝝀𝝀 were formally derived inSEE - Kyoto, Japan, Nov.18-20, 2020[2], hence we skip the details. It suffices to present a
brief summary of such results: For firrst order ODEof the form
𝒖𝒖′ + 𝒑𝒑(𝒙𝒙)𝒖𝒖 = 𝒒𝒒(𝒙𝒙), 𝒖𝒖(𝟎𝟎) = 𝜶𝜶
it was found that 𝝀𝝀 = −𝟏𝟏, and the correction
functional gives the iteration formula

(5)

𝒙𝒙

𝒖𝒖𝒏𝒏+𝟏𝟏 (𝒙𝒙) = 𝒖𝒖𝒏𝒏 (𝒙𝒙) − ∫𝟎𝟎 ( 𝒖𝒖′𝒏𝒏 (𝒕𝒕) + 𝒑𝒑(𝒕𝒕)𝒖𝒖𝒏𝒏 (𝒕𝒕) −𝒒𝒒(𝒕𝒕))𝒅𝒅𝒅𝒅.
(6)
Generally, for the nth-order ODE

𝒖𝒖(𝒏𝒏) + 𝒇𝒇�𝒖𝒖, 𝒖𝒖′ , 𝒖𝒖′′ , ⋯ 𝒖𝒖(𝒏𝒏−𝟏𝟏) � = 𝒈𝒈(𝒙𝒙), 𝒖𝒖(𝟎𝟎) = 𝜶𝜶𝟎𝟎 ,𝒖𝒖′ (𝟎𝟎) = 𝜶𝜶𝟏𝟏 , ⋯ , 𝒖𝒖(𝒏𝒏−𝟏𝟏) (𝟎𝟎) = 𝜶𝜶𝒏𝒏−𝟏𝟏(7)(−𝟏𝟏)𝒏𝒏

we found that 𝝀𝝀 = (𝒏𝒏−𝟏𝟏)! (𝒕𝒕 − 𝒙𝒙)𝒏𝒏−𝟏𝟏 , and theiteration formula takes the form(−𝟏𝟏)𝒏𝒏

Fig.1 Plot 2D of the exact solutions result Of
Volterra integral equation of the second kind forexample 1.

𝒙𝒙

𝒖𝒖𝒏𝒏+𝟏𝟏 (𝒙𝒙) = 𝒖𝒖𝒏𝒏 (𝒙𝒙) + (𝒏𝒏−𝟏𝟏)! ∫𝟎𝟎 (𝒕𝒕 − 𝒙𝒙)𝒏𝒏−𝟏𝟏 �𝒖𝒖(𝒏𝒏) +𝒇𝒇�𝒖𝒖, 𝒖𝒖′ , 𝒖𝒖′′ , ⋯ , 𝒖𝒖(𝒏𝒏−𝟏𝟏) � − 𝒈𝒈(𝒕𝒕)� 𝒅𝒅𝒅𝒅.

(8)

Example2. Consider the Volterra integral equationof second kind

The successive approximations 𝒖𝒖𝒏𝒏+𝟏𝟏 , 𝒏𝒏 ≥ 𝟎𝟎 of thesolution u(x) will be readily obtained upon using any
selective function u0(x).

𝒙𝒙

𝒖𝒖(𝒙𝒙) = 𝒙𝒙 + �(𝒙𝒙 − 𝒕𝒕) 𝒖𝒖(𝒕𝒕)𝒅𝒅𝒅𝒅, 𝒖𝒖(𝟎𝟎) = 𝟎𝟎,

SEVERAL EXAMPLE

𝟎𝟎

Example1. Consider the Volterra integral equationof the second kind

Applying the Variational Iteration Method
using Maple, we find𝒙𝒙

𝒖𝒖(𝒙𝒙) = 𝟏𝟏 + � 𝒖𝒖(𝒕𝒕)𝒅𝒅𝒅𝒅,

Table 2 Numerical results and exact solution of
Volterra integral equation of the second kindfor example 2.

𝟎𝟎

𝒖𝒖(𝟎𝟎) = 𝟏𝟏
Applying the Variational Iteration Method
using Maple, we find𝒙𝒙

Table 1 Numerical results and exact solution of
Volterra integral equation of the second kindfor example 1𝒙𝒙0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

𝒖𝒖(𝒙𝒙)

1.1051709
1.2214028
1.3498588
1.4918247
1.6487213
1.8221188
2.0137527
2.2255409
2.4596031
2.7182818

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬= 𝒆𝒆𝒙𝒙1.1051709
1.2214028
1.3498588
1.4918244
1.6487196
1.8221128
2.0137348
2.2254948
2.4594964
2.7180556

𝒖𝒖′(𝟎𝟎) = 𝟏𝟏0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬

0.0000000
0.0000000
0.0000000
0.0000003
0.0000017
0.0000060
0.0000179
0.0000462
0.0001067
0.0002263

56

𝒖𝒖(𝒙𝒙)

0.1001668
0.2013360
0.3045203
0.4107523
0.5210953
0.6366536
0.7585837
0.8881060
1.0265167
1.1752012

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬= 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔(𝒙𝒙)0.1001668
0.2013360
0.3045203
0.4107523
0.5210953
0.6366536
0.7585837
0.8881060
1.0265167
1.1752012

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬

0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000

SEE - Kyoto, Japan, Nov.18-20, 2020

Fig.3 Plot 2D of the exact solutions result Of
Volterra integral equation of the second kind forexample 3.

Fig.2 Plot 2D of the exact solutions result Of
Volterra integral equation of the second kind forexample 2.

CONCLUSION
Example3. Consider the Volterra integral equationof second kind𝒖𝒖(𝒙𝒙) = 𝟏𝟏 + 𝒙𝒙 +In this paper, the Variational iteration method isused to solve the Volterra integral equation of thesecond type using Maple 18. By presenting andinterpreting the method on a number of examples, theresults are shown through examples and it is shownthat this method is very effective and the process offinding results from the tables and drawings very
easily and clearly The approximate solution is very
close to the exact solution.

𝒙𝒙

𝟏𝟏 𝟑𝟑
𝒙𝒙 − �(𝒙𝒙 − 𝒕𝒕) 𝒖𝒖(𝒕𝒕)𝒅𝒅𝒅𝒅,
𝟑𝟑!
𝟎𝟎

𝒖𝒖(𝟎𝟎) = 𝟏𝟏, 𝒖𝒖′(𝟎𝟎) = 𝟏𝟏

Applying the Variational Iteration Method
using Maple, we findTable 3 Numerical results and exact solution of
Volterra integral equation of the second kindfor example 3.
𝒙𝒙

𝒖𝒖(𝒙𝒙)

0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

1.0950042
1.1800666
1.2553365
1.3210610
1.3775826
1.4253356
1.4648422
1.4967067
1.5216100
1.5403023

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬= 𝒙𝒙+ 𝒄𝒄𝒄𝒄𝒄𝒄(𝒙𝒙)1.0950042
1.1800666
1.2553365
1.3210610
1.3775826
1.4253356
1.4648422
1.4967067
1.5216100
1.5403023

ACKNOWLEDGMENTS
This paper was supported by the Deanship ofScientific Research (DSR), King Abdulaziz
University, Jeddah.

𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬

REFERENCES

0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000[1] A.M. Wazwaz, The variational iteration method;a reliable tool for solving linear and nonlinear
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Journal of Science and Engineering, Vol9, No.2,
pp.1-9,2014.

[13] R.L. Burden and J. Douglas Faires, Numerical
Analysis, 8th ed., Thomson Brooks/Cole,
Belmont, CA, 2005.
[14] T. A. Burton, Volterra Integral and Differential
Equations, 2nd ed., Mathematics in Science &Engineering, 202, Elsevier, 2005.

[26] H.H. Sorkun, S. Yalcinbas, Approximate
solutions of linear Volterra integral equation
systems with variable coefficients, Applied
Mathematical Modeling, 34(2010) 3451-3464.

[15] M.I. Berenguer, D. Gamez, A. I. GarraldaGuillem, M. Ruiz Galan, and M.C. Serrano
Perez, Biorthogonal Systems for Solving
Volterra Integral equation Systems of the Second
Kind, Journal of Computional and Applied
Mathematics,235(7)(2011),1875-1883.

[27] Dalal A. Maturi, Honaida M. Malaikah,
Numerical Solution of System of Three
Nonlinear Volterra Integral Equation Using
Implicit Trapezoial, Journal of Mathematics
Research; Vol. 10, No. 1; February 2018,ISSN
1916-9795
E-ISSN
1916-9809,
doi:10.5539/jmr.v10n1p44URL:
https://doi.org/10.5539/jmr.v10n1p44.

[16] J. Biazar and M. Eslami, Modified HPM for
Solving Systems of Volterra Integral Equation of
the Second Kind, Journal of King Saud
University-Science, 23(1) (2011),35-39.
[17] P. Linz, Analytical and Numerical Methods for
Volterra Equations, Studies in Applied
Mathematics 7, SIAM, Philadelphia, 1985.

[28] Dalal
Adnan
Maturi,The
Modified
Decomposition Method For Solving Volterra
Integral Equation Of The Second Kind Using
Maple, International Journal of GEOMATE,
Oct., 2019 Vol.17, Issue 62, pp. 23-28.

[18] P. Linz, A simple approximation method forsolving Volterra integro-differential equations of
the first kind, J. Inst. Math. Appl., 14 (1974)
211–215.

58

SEE - Kyoto, Japan, Nov.18-20, 2020[31] Dalal Adnan Maturi, Eman Ahmed M. Simbawa,
The Modified Decomposition Method For
Solving Volterra Fredholm Integro-Differential
Equation Using Maple, International Journal of
GEOMATE, March 2020 Vol.18, Issue 67, pp.
84-89.

[29] Dalal Adnan Maturi, Amal Ibrahim Aljedani,
Eman Salem Alaidarous, Finite Difference
Method For Solving Heat Conduction Equation
Of The Granite, International Journal of
GEOMATE, Sept., 2019 Vol.17, Issue 61, pp.
135 -140 . ISSN: 2186-2982 (P), 2186-2990 (O),Japan.
[30] Dalal Adnan Maturi, Finite Difference Method
For Solving Heat Conduction Equation Of The
Brick, International Journal of GEOMATE,
April, 2020 Vol.18, Issue 68, pp. 114-119.

59

6th

Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EFFECT OF DEGREE OF SATURATION ON
PARTICLE BREAKAGE OF RECYCLED CONCRETE AGGREGATEUNDER CYCLIC LOADING
Syed Kamran Hussain Shah1, Junaid Qayyum Kayani1,2, Taro Uchimura1 and Ken Kawamoto1
1
Department of Civil and Environmental Engineering, Saitama University, Saitama, Japan
2
Neelum Jhelum Hydropower Company, Muzaffarabad, Azad Jammu Kashmir, Pakistan

ABSTRACTThe recycled concrete aggregates (RCA) are extracted from construction and demolition waste. If it meets all
the engineering aspects of the material, then its use not only decreases the exhaustion of natural resources but also
effectively help to utilize the waste. The use of recycled concrete aggregate (RCA) as a granular material highly
depends upon its performance under actual field loading conditions and environmental factors it may undergo.
The particle breakage is one of the important factors that affect the performance of recycled concrete aggregate,especially in the long-term pavement performance under different environmental conditions. The present study
focuses on the particle breakage of recycled concrete aggregate with the variation in the degree of saturation during
cyclic loading through triaxial testing. The test results indicated that breakage of particles decreases with anincrease in saturation under cyclic loading. The particles more prone to breakage can be identified through coloring
technique.
Keywords: Saturation, Breakage, Recycled Concrete Aggregate, Cyclic Triaxial

demolition waste, especially recycled concrete
aggregates (RCA) in geotechnical applications, isincreasing [4].
Alongside the long-term durability of the material,
particle breakage is a critical aspect exposed to
dynamic loading. That is why it has drawn theattention of past researches focused on the long-term
durability of aggregates and breakage behavior. To
understand the impact of particle breakage on
strength and deformation behavior several studies
have been done using different laboratory tests
including
triaxial
test
andnumerical
methods [5]. Studies found out that particle breakage
influences the shear strength of granular materials andinduce more irrecoverable deformation [6]. Other
than mechanical factors influencing the breakage
behavior, physical characteristics of the granularmaterials were also reported in the literature that
affects the breakage extent, for example increasing
coefficient of uniformity decreases particle breakage
with similar relative density [7]. Comprehensive
laboratory assessment of physical and strengthcharacteristics has been established for the utilizationof recycled aggregates [8]. However, the effect ofvariation in the degree of saturation on the breakage
behavior of RCA was not conclusive. Therefore, it isimportant to study the influence of the degree ofsaturation on breakage behavior of RCA to assess thelong-term durability as pavement base material.

INTRODUCTION
After the demolition of existing infrastructure or
the occurrence of natural disasters in recent times, alarge amount of construction waste is being produced.
This construction waste material mostly containing
demolished concrete from roads and buildings, isoften dumped as waste causing a disposal problem. It
is difficult to handle a large quantity of constructionwaste materials in designated landfill sites due to theshortage of land with an increasing population and anincrease in public confrontation. Solving the problem
of utilization of construction waste materials mixed
with industrial by-products such as wastewater sludge
and incineration ash in the construction industry is
also gaining attention [1].
History of utilizing recycled materials inconstruction leads back to the end of World War II
when the extensive demolition of infrastructure
occurred and high demand to both get rid of the wastematerial and rebuild ruined countries. In the 70s, theUnited States introduced the use of RCA in nonstructural uses, such as fill material, foundations, andbase course material [2]. Since then, researchers
became interested in how to utilize RCA is as an
option to replace natural aggregate (NA) in
construction activities to protect the natural
resources [3].
The increase in demand and use of NA is causing
depletion of natural resources, as for large
construction projects a big amount of material isrequired. Therefore, more use of construction and

MATERIAL PROPERTIES

60

SEE - Kyoto, Japan, Nov.18-20, 2020

Recycled concrete aggregate (RCA) collectedfrom a recycling plant in Japan is used in theseexperiments as shown in Fig. 1.

Fig. 1

Cylindrical RCA specimen of 75 mm diameter and
150 mm height was used in the study. The confiningpressure was applied by pressurizing the air in the celland distributed through water and it was continuously
monitored by a transducer connected to the cell.

Recycled Concrete Aggregate (RCA) gradedin accordance with RM-30 (2010).

The specific gravity of RCA use is 2.59.
Absorption of particles > 2.36 mm is 5.9% andparticles < 2.36 mm is 15.7%. Maximum dry densityof RCA is 1.89 g/cm3 with optimum moisture content(OMC) of approximately 10% with corresponding
degree of saturation 67.2 %.
This material was sieved and adjusted from 19.0
mm to 0.075 mm in accordance with RM – 30
gradation [9] suggested by Japan Road Association(2010), refer Fig. 2.

Fig. 3The cyclic loading was applied using double
action pressure cylinder mounted on top of the system.
EP transducer was used to convert signal into
pressure given from function generator. The verticaldeformation of the specimen was calculated by themeasurements provided by linear variable differential
transformer (LVDT) attached to the vertical shaft on
top of triaxial cell. Whereas volumetric deformation
was measured by low capacity displacementtransducer (LCDPT) by measuring the difference ofwater level in double cell. Cell pressure transducers
and the load cell were connected to a data logging
system which collected the responses of thetransducers at specified time intervals.
The test conditions used in cyclic triaxial tests areshown in Table 1.

100

Percentage Passing (%)

80

60

40

20

0
0.01

0.1

1

10

100

Table 1

Particle Size (mm)Lower_Limit

Fig. 2Upper_Limit

SETUP

Test conditions

Gradation_Used

Test Conditions
Compaction Energy [kJ/m3]
2700
Degree of Saturation [%]30, 40, 60, 80
Frequency [Hz]0.2
Number of Cycles [Nos.]
2000, 4000
Confining Pressure [kPa]70
Max. Cyclic Deviatoric Stress [kPa]590
Min. Cyclic Deviatoric Stress [kPa]59

Gradation curves of the RCA samples withupper and lower limit curves of RM-30
suggested by Japan Road Association (2010)

EXPERIMENTAL
CONDITIONS

Schematic diagram of cyclic triaxial system.

AND

TESTING

The performance of recycled concrete aggregate(RCA) was determined by conducting a series ofstatic and cyclic triaxial tests on the compacted
specimens at different degrees of saturation andselected stress conditions. The schematic of triaxial
system used in these experiments is shown in Fig. 3.

Sample Preparation and Placing

61

SEE - Kyoto, Japan, Nov.18-20, 2020

For evaluating the strength and deformation
characteristics of RCA, samples were compacted at
optimum moisture content with energy equivalent tomodified proctor energy (2700 kJ/m3).
To assess the particle breakage of RCA undercyclic loading, coarse content of the material ranging
from 19.0 mm to 4.75 mm was painted. The color
codes used for these particle ranges is illustrated inFig. 4. Whereas the fine content is kept in its originalcolor due to difficulty in coloring. Sample was thenmixed with pre-determined water content for target
degree of saturation. The sample is then compacted in
the mold in three layers with specified compactionenergy of 2700 kJ/m3.
Compacted specimen is then enclosed in rubber
membrane and placed on the pedestal of triaxial cell.
The specimen is sealed by O-rings at the top and thebottom. Inner and outer cells were installed. After
filling the water in both cells to the required level,
predetermined cell pressure (σ3) was applied and thesample was allowed to consolidate.

Fig. 4

between load assembly and specimen. Under constantconfining pressure, 2000 and 4000 repeated load
cycles were applied. After completing the desired
cycles, sample was retrieved carefully, oven dried andsieved to evaluate the breakage.
The results were analyzed to study the particle
breakage behavior by using the data acquired throughdata acquisition system, sieving analysis and particle
segregation based on color schemes used.
RESULTS AND DISCUSSION
Static Triaxial Test
Prior to evaluating the performance of RCA
during cyclic loading, static triaxial tests were
performed. The test results are shown in Fig. 5. At theconfining pressure (σ3) of 70 kPa, the peak strengthachieved by sample compacted at optimum moisture
content is approximately 900 kPa. The sample failed
after gaining slightly over 3% axial strain value. The
peak strength achieved is used to fix the maximum
and minimum cyclic deviatoric stress values to assess
the long-term performance of RCA during cyclic
triaxial tests.
The most distinctive feature of RCA is mortar
layer surrounding the thick core particles, whichmight affect initial stiffness and volumetric strain
characteristic.
The results show that when recycled concrete iswell compacted it showed good strength, otherresearchers also concluded that when well compacted,
recycled concrete aggregates can exhibit strength andstiffness even higher than those of selected wellgraded gravelly soil [10]. When subjected to triaxial
compression loading, some crushing of mortar takes
place at inter-particle contact points, resulting in a
low initial stiffness. Then a better inter-particle
contact condition between adjacent stiff cores of theaggregate develops resulting in increase of tangent
stiffness and ultimately a high compressive strength.
The negative effects of mortar layer on thecompressive strength of RCA can be eliminated bybetter compaction [11].

Color scheme of each particle size range.

Loading and Data Acquisition
Static triaxial test
Strain controlled static triaxial tests were
performed in drained condition, to get the strengthand deformation characteristics of RCA samples.

1000

Deviatoric Stress, q (kPa)

900

Cyclic triaxial test
Stress controlled cyclic triaxial tests were
performed to study performance of RCA. Verticalaxial load (σ1) corresponding to selected maximum
and minimum deviatoric stress (q) was applied as a
waveform by generating the signal through function
generator and EP transducer.
Tests were conducted under drained conditions.
Constant contact stress (10% of maximum deviatoricstress) was applied to ensure the constant contact

800
700
600
500
400
300
200
100

Confining Pressure = 70kPa

0
0

1

2

3

4

5

6

Axial Strain, εa (%)

Fig. 5 Strength of RCA during static triaxial test.
Cyclic Triaxial Test

62

SEE - Kyoto, Japan, Nov.18-20, 2020

Two series of cyclic triaxial tests wereconducted to evaluate the long-term performance andbreakage behavior of RCA with variation in degree ofsaturation.
Figure 6 shows the maximum and minimum valueof cyclic deviatoric stress used in cyclic triaxial test.
The maximum deviatoric stress is taken
approximately 65% of the maximum stress achievedin the static triaxial test 10% of the maximum
deviatoric stress was taken as the contact stress inorder to ensure constant contact between loading rod,
top cap and sample [12].

permanent axial strain with increasing degree ofsaturation, but RCA sample did not collapse undercyclic loading albeit the strain values were high at
saturation over the optimum value of RCA samples.
It seems to be a significant performance characteristicof RCA which demonstrates resistance against plastic
deformation at high water contents without collapse
which establishes its capacity for load bearing and its
suitability as a high-quality granular pavement
material. This is in accordance to the natural behavior
to many conventional pavement materials which
exhibit increase in plastic strain with increase in thewater content [14].
Permanent Axial Strain,εap (%)

Deviatoric Stress, q (kPa)

600
500
400
300
200
100
0
1300

5
4
3
2
1

2000 Cycles

0
0

1320

1340

1360

1380

1000

500

1400

1500

2000

Number of Cycles (Nos.)

Time (Sec)Maximum and minimum cyclic deviatoricstress.

Perm._Axial_Strain_60%

Perm._Axial_Strain_40%

Perm._Axial_Strain_30%

5Permanent Axial Strain,εap (%)

Fig. 6

Perm._Axial_Strain_80%

Accumulation of axial permanent strain of the
RCA specimens with number of load cycles is shownin Fig. 7 for 2000 and 4000 cycles. This figure
illustrates the effect of degree of saturation on theaccumulated axial strain at a constant σ3 of 70 kPa.
The figure illustrates the increase of plastic strain
with number of load cycles at various values ofdegree of saturation.
The higher the saturation value, the higher thepermanent axial strain.
The rate of increase of permanent axial strain
slows down as the number of load cycles increased atconstant maximum value of deviatoric stress (σd) andconfining stress (σ3). The curves show a tendency
towards attaining a steady state of plastic response at
the end of the test, especially, at the low values ofdegree of saturation i.e., 30 and 40 % in comparison
to higher degrees of saturation. This behavior
indicates the state of energy absorption by RCA oneach stress-strain loop and its ability to resist aftergaining minor permanent deformations. Decrease in
the permanent axial strain over the number of loading
cycles in RCA sample indicates a state of plastic
shakedown limit [13]. This behavior of accumulated
permanent axial strain of RCA sample at lower
degrees of saturation suggests illustrates its approachto plastic limit. However, enough volume of water onlower side of optimum value of the RCA positively
affected the strength and stiffness of the RCA sample
compacted at modified proctor energy and reduced
the rate of permanent deformation.
Moreover, results in Fig. 7 show the rise of

4
3
2
1

4000 Cycles
0
0

1000

2000

3000

4000

Number of Cycles (Nos.)

Fig. 7

Perm._Axial_Strain_80%

Perm._Axial_Strain_60%

Perm._Axial_Strain_40%

Perm._Axial_Strain_30%

Permanent axial strain with loading cycles.

Particle Breakage Analysis
To assess the effect of degree of saturation on
particle breakage of RCA under cyclic loading,following methods were adopted for analysis in thisstudy.
Marsal’s breakage ratio (Bg)
To quantify the extent of particle breakage, mostcommon method, the Marsal’s breakage ratio (Bg)
was used [15]. It is a quantitative breakage index andis defined as the percentage by weight of the solid
phase that has broken. It measures the percentage
increase in mass of particles that pass through eachsieve size as expressed in Eq. (1) and (2).

63

Bg = Σ (ΔWk > 0)

(1)

ΔWk = Wki -Wkf

(2)

SEE - Kyoto, Japan, Nov.18-20, 2020

Wherein, Wki is the percentage of sample weightretained before test in each sieve size and Wkf is thepercentage of sample weight retained after test ineach sieve size respectively.
Marsal’s breakage ratio is shown in Fig. 8 asfunction of degree of saturation. Solid line represents
the data obtained in tests where RCA sample wassubjected to 2000 loading cycles and dotted line for4000 load cycles. Results depict that there is a minor
shift in the curve upwards with increase in number ofcycles from 2000 to 4000.
An almost linear decreasing trend can be observedin Marsal’s breakage ratio with increasing degree ofsaturation until 60% degree of saturation value whichis in close range to corresponding optimum moisturevalue. However, a slight increase was observed at
higher degree of saturation in both the cases. Overall
trend suggests that with increase in moisture particle
breakage in the sample reduces.
It is presumed that with the increase in degree ofsaturation, water provides a cushion and/or slippage
surface around the particles which result in lessbreakage of particles.

Fig. 9The mass reduction percentage is described as;
Mass Reduction/Accumulation (%) =[(Initial Mass – Final Mass)/Initial Mass x 100)]
The finer particles (2.36 ~ 0.075 mm) didn’t show
considerable breakage but their final mass increased
due to the accumulation from top sizes of coarse
fraction (19.0, 9.5 and 4.75 mm). Particularly particle
size range 9.5~4.75 mm of the coarse fraction showshigher mass reduction as compared to 19.0~9.5 and4.75~2.36 mm size ranges at both 2000 and 4000
cycles.

4000 Cycles
4
20

40

60

80

100

Degree of Saturation, Sr (%)

30

9.5~4.75 mm

25
20
15

OMC

2000 Cycles[Coarse Content]

Mass Reduction (%)

8

OMC

Marsal's Breakage Ratio, Br

106Each particle size fraction after test.

10
5
0
20

Fig. 8

30

40

50

60

70

80

90

Degree of Saturation, Sr (%)

Marsal’s breakage ratio as function ofdegree of saturation.

Coloring technique
To assess that which fraction of the material ismore prone to breakage or more influenced by thetesting conditions assumed, coloring technique isadopted in this study.
Material after the test was sieved. Then coarse
fraction which was colored is segregated and particles
which shifted from one color scheme to another color
scheme were picked up by color identification andweighed as shown in Fig. 9. With this methodology,
it can be observed that the fraction size which has
moved to the next size range and actual breakage ormass reduction/accumulation can be calculated.
The results shown in Fig. 10 indicated coarser
fraction such as 19.0 mm, 9.5 mm and 4.75 mm broke
and this breakage decrease with increase in moisture
content.

19~9.5_2000 Cycles

9.5~4.75_2000 Cycles

4.75~2.36_2000 Cycles

19~9.5_4000 Cycles

9.5~4.75_4000 Cycles

4.75~2.36_4000 Cycles

25
20
15

OMC

[Fine Content]

Mass Accumulation (%)

30

10
5
0
20

30

40

50

60

70

80

Degree of Saturation, Sr (%)
2.36~0.075_2000 Cycles

Fig. 10Mass reduction and accumulation.

CONCLUSIONS

64

2.36~0.075_4000 Cycles

90

SEE - Kyoto, Japan, Nov.18-20, 2020

This study contributes to advancement ingeotechnical engineering in terms of utilization ofrecycled materials. The performance characteristics
of RCA were investigated by conducting a series ofcyclic triaxial tests under different degree ofsaturation and number of load cycles. The following
conclusions were drawn from this study• Permanent axial strain was notably affected byhigh value of degree of saturation of thecompacted RCA which revealed sensitivity RCA
to moisture.
• Accumulation of permanent axial deformation of
RCA move towards plastic state with the increaseof the load cycles, especially at low degrees ofsaturation. This behavior corresponds to thenatural good quality pavement materials.
• Breakage of particles decreases with increase insaturation as evident from the results. Therefore,
it is important to consider the particle breakage of
RCA as an important factor to influence the longterm durability as a pavement material.
• Marsal’s breakage ratio, Bg, showed a decreasing
relationship between overall breakage and degreeof saturation. However there is a slight increase in
breakage ratio at higher saturation.
• The coloring technique introduced in this study iscapable to indicate the particle size more prone tobreakage and particle tracing is possible to track
the particle movement after testing from one size
range to the other especially in coarse fractions.
• 9.5~4.75 mm range of coarse fraction shows more
breakage as compared to other coarse fractions.
Mass accumulation happens in finer content due
to breakage of large particles.
• Along with the traditional breakage indices, thecoloring technique can be used to study thebreakage of particles in long term durability tests.

Aggregates: A Review. International Journal ofConcrete Structures and Materials. Vol. 7, No. 1,
2013, pp. 61-69.
[4] Abukhettala M., Use of Recycled Materials inRoad Construction. Proceedings of the 2nd
International Conference on Civil, Structural andTransportation Engineering, ICCSTE’16, 2016,
Paper No. 138.
[5] Coop M., Sorensen K., Freitas TB., andGeorgoutsos G., Particle Breakage during
Shearing of a Carbonate Sand. Geotechnique,54(3), 2004, pp. 157-163.
[6] Yu F., Characteristics of Particle Breakage of
Sand in Triaxial Shear. Powder Technology, 320,2017a, pp. 656-667.
[7] Sun Y., Zheng C., Breakage and Shape Analysis
of Ballast Aggregates with Different Size
Distributions. Particuology, 35, 2017, pp. 84-92.
[8] Arulrajah A., Disfani M.M., Horpibulsuk S.,
Suksiripattanapong C., and Prongmanee N.,
Physical Properties and Shear Strength Responses
of Recycled Construction and Demolition
Materials in Unbound Pavement Base/Subbase
Applications. Constr. Build. Mater, 58, 2014b, pp.
245-257.
[9] RM-30, Gradation Standard for Recycled
Materials. Japan Road Association (JRA), 2010
(in Japanese).
[10] Aqil U., Tatsuoka F., Uchimura T., Lohani T.N.,
Tomita Y., and Matsushima K., Strength andDeformation Characteristics of Recycled
Concrete Aggregate as a Backfill Material. Soils
and Foundations, 45(4), 2005, pp. 53-72.
[11] Tatsuoka F., Tomita Y., Iguchi Y., and Harikawa
D., Strength and Stiffness of Compacted Crushed
Concrete Aggregate. Soils and Foundations, 53(6),2013, pp. 835-852.
[12] Frost M.W., Fleming P.R., and Rogers C.D.F.,
Threshold Stress and Asymptotic Stiffness of UK
Clays in the Repeated Load Triaxial Test.
Proceedings of the 6th International Conference[13] Cerni G., Cardone F., Virgili A., and Camilli S.,
Characterization of Permanent Deformation
Behavior of Unbound Granular Materials underRepeated Triaxial Loading. Constr. Build. Mater.,
28, 2012, pp. 79–87.
[14] Thom N.H., Brown S.F., Effect of Moisture on
the Structural Performance of a Crushedlimestone Road Base. Transportation Research
Record, 1 12 1, (1987).
[15] Marsal R.J., Large Scale Testing of Rockfill
Materials. Journal of the Soil Mechanics andFoundation Division ASCE, 93(2), 1967, pp. 2743.

ACKNOWLEDGEMENTS
This research was partially supported by JSTJICA, Science and Technology Research Partnershipfor Sustainable Development (SATREPS) project(No. JPMJSA1701).
REFERENCES[1] Iqbal M.R., Hashimoto K., Tachibana S., andKawamoto K.., Geotechnical Properties of Sludge
Blended with Crushed Concrete and Incineration
Ash. International Journal of GEOMATE, Vol. 16,
Issue 57, 2019, pp. 116–123.
[2] Buck A. D., Recycled Concrete as a Source ofAggregate. ACI Journal. 74, 1977, pp. 212–219.
[3] McNeil K., Kang T.H.K., Recycled Concrete65

6th Int. Conf. on Strucrture, Engineering & Environment (SEE),
Kyoto, Nov.18-20, 2020, ISBN: 978-4-909106032 C3051

INVESTIGATION ON RUPTURE OF GROUND ANCHORS DUE TO
LANDSLIDE FLUCTUATIONS
Yoshihiro TSUNEKAWA1, Toshinori SAKAI2,
1
Soai, Japan; 2Mie University, Japan

ABSTRACT
Ground anchors are widely used as landslide prevention measures. In recent years, record heavy rains and huge
earthquakes have occurred frequently, and there is a high likelihood that damage will be caused by external forces
exceeding design conditions. It has been reported that some anchors have experienced tensions exceeding 100 kN
and will be ejected from their installation sites if the anchor breaks. Because some anchors are installed on slopes
facing roads and houses, ensuring safety in the event of damage is important. In this study, a survey was conducted
over a period of five years at a site where anchors have broken due to landslides exceeding the design load of theanchors. It was found that the fracture of the anchors progressed stepwise, and although 42 out of 86 anchors
fractured, the slope in which they were installed did not collapse. It was confirmed that 14 of the fractured anchors
were ejected, and their flight distance reached approximately 100 m.
Keywords: Ground anchor, Landslide, Anchor fracture, Flight distanceblock, and there is a large-scale landslide block thatfluctuates in the upper part. Figure 2 shows the
positions of the anchors in block A-1. The landslide
scale of the A-1 block is approximately 100 m wide,
120 m long, and 15 m deep, and part of the A block
passes through the A-1 block. In 2009, 86 anchors

INTRODUCTION
Ground anchors (hereafter referred to simply asanchors) are widely used for landslide prevention. In
recent years, record heavy rains and huge earthquakes
have frequently occurred, and the possibility thatdamage will occur as a result of external forces
exceeding the anchor design conditions is increasing.
Tensile forces of over 100 kN have been introduced
to anchors, and, as shown in Photo 1, anchors havebeen reported to break out of structures when theyrupture [1]. Anchors may be installed on slopes facing
roads and houses, so it is important to ensure safety
in case of breakage.

Block C
Block B

Block ASURVEY SITE OVERVIEW
Figure 1 shows the landslide block considered inthis study and the survey site. This survey site is
located in the A-1 block at the end of the landslide

Photo by Google Map(2020)

Survey site
Block A-1
100m
Block AFig 1. Landslide positions and survey site

Upper step
Middle step
Lower step
Ground anchors(86 anchors)

Block A-1
20m

Photo by Google Map(2020)

Photo 1. Damage due to anchor rupture

Fig 2. Ground anchors in the A-1 block66

SEE - Kyoto, Nov.18-20, 2020

were constructed to prevent landslides in the A-1
block. The anchor installation angle is 25°, thedesigned load T d is 414.5 kN, and the lock-off load
P t is 207 kN, which is approximately 50% of thedesigned load.
Figure 3 shows a typical anchor countermeasurecross section of block A-1. The anchor fixed lengthl a is 4.5 m, and the anchor free length l f ranges from
5.5 to 29 m. For the free anchor length part, three ∅15mm prestressed concrete (PC) steel stranded wires
were used. These wires have a tendon yield strength
T ys of 666 kN, and a tendon ultimate strength of T us
of 783 kN. Photo 2 shows the configuration of theanchor head. The PC steel stranded wire is fixed witha wedge at the anchor head, and the anchor head is
protected by an aluminum cap containing rustpreventive oil.
Anchor fracture was confirmed in 2014, five years
after construction. Figure 4 shows the distribution of
the anchor load obtained one year before the anchor
rupture occurred. The loads are categorized according
to the soundness categories given in Table 1.
Regarding the change in the anchor load, Figure 4
demonstrates that the landslide displacement of the A
block increases the anchor load only on the A blockside. It has been confirmed in previous studies that ifcontinuous rainfall exceeds 400 mm, anchors loadedwith at least 90% of the yield tensile force will break[2].
Photo 3 shows the condition of a typical fractured
anchor observed in the field. As shown in Photo 3(a),the anchor head and the PC steel stranded wire wereleft protruding by the fracture. In addition, as shownin Photo 3(b), it was confirmed that the broken
portion of the PC steel stranded wire traveled over 30
m when it was ejected from its place of installation.
This photograph shows evidence of the collision of
the broken PC steel stranded wire with a tree andwhere it was left hanging on the tree.
Landslide boundary of Block A
Area of increased load
33 32 31

E+

Upper step

599.4
D+
516.8

30 29 28C+

27 26 25 24 23 22 2120 19 18 17 16 15

14 13

436.8

12 1110 9 8 7 6 5 4 3 2 1B+

Middle step

414.5
A
331.6

23 2221 20 19 18 17 16 15 14

B-

13 12 11 10207.3

9 8 7 6 5 4 3 2 1C-Lower step

41.5
D-

90% of yield load0

Fig. 4. Soundness classification diagram

50 m
Colluvial soil

Integrity

30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1

Ground anchors

FIELD SURVEY
Sandstone
Mudstone
Conglomerate

m
4.5

20m
m
4.5

21m
m
4.5

Table 1. Guidelines for residual tensile load andanchor integrity [3] (Additional writing)

20m

Slide surface(Block A)
Slide surface(Block A-1)
50 m

0 m

Range of residual tensile load Integrity

0 m

0. 9 Tys
1. 1 TaFig 3. Typical anchor countermeasure crossPC steel stranded wiresection in block A-1

Allowable load（Ta）
Design load （Td）
Lock-off Load（Pt）
0. 8 Pt
0. 5 Pt
0. 1 Pt

Situation

E+

Possibility of failure

D+

Possibility of dangerous situation

C+

Beyond toletanceCountermeasure
Emargency countermeasure is necessaryCountermeasure is necessary
Need for countermeasure is examined
after inspection

B+
A+

Sound

A-

Sound
Need for countermeasure is examined
after inspection

BC-

Drastic deterioration of functionD-Non-functional

Countermeasure is necessary

Anchor head
Wedges(a) Installation of PC steel stranded wires(a) Protruding anchor head and PC steel stranded wire

Aluminum cap(b) Filled with corrosion inhibitor(b) Flight of PC steel stranded wire and traces ofcollision
Photo 3. Condition of the ruptured anchor

Photo 2. Configuration of the anchor head
67

SEE - Kyoto, Nov.18-20, 2020

and the flight distances in the case of anchor flight. It
was confirmed that 42 anchors broke, which wasapproximately 80% of the anchors in the area
associated with load increase due to landslide. Of
these, 14 fractured anchors were ejected from theirsites, and it was confirmed that all of the ejectedanchors fractured inside the ground. Furthermore, forthe anchors that broke behind the anchor head, no
anchor flight was observed. Ejected anchors were
found in four areas. PC steel stranded wires wereejected from the anchors that were broken, and aflight distance of up to 120 m was confirmed.
Photo 4 shows the slope condition of the upper
anchor after the anchor fracture. Although slight
displacement was observed in the supporting
structure and water channel, it was confirmed that
there was no collapse at present (five years after thestart of rupture) and that the shape of the slope wasmaintained.
ANCHOR FLIGHT ANALYSIS

A field survey was conducted over the course of
five years from 2014 to 2019, and the progress ofanchor rupture and the condition of anchor pop-out
were confirmed. After heavy rainfalls with a daily
rainfall of 300 mm or more, visual inspection was
conducted, and the progress of the fracture of theanchor was recorded. In addition, regarding the flightof anchors due to fracture, anchors no longer in theirinstallation locations were found by searching the site,
and the length and flight distance of these anchors
were measured. The survey results are presented
below.
Figure 5 shows the daily precipitation [4] and thenumber of newly fractured anchors each year. The
numbers of yearly anchor ruptures from 2014 to 2019were 6, 22, 13, 1, and 1, respectively. It was
confirmed that the fracture of the anchor proceeded instages. Figure 6 shows the anchor fracture locations

Number of broken anchors

50
40
30

22

20

13
6
1

1

10

2019

2018

2017

2016

2015

2014

2013

0

Fig 5. Precipitation and number of broken anchors

Photo 4. Condition of the slope after anchor rupture

2
33 3
0 29
31 3

3
A3-

3
30

2
28

8 27
29 2

72
62

30
A2-

25

42
52

26

22
01
12
91
81
51
61
71
41

A3

0 -14

31
11
21

1
A2-

3

10

09

11

8

9

7

8

6

7

23
A1-

1
A1-

1

8 7

5

6
5

4

6
4

3

5
3

2

4
2

1

3
2
1

1

1

A1-

1

50

4

2

0 9
11 1

3

3 12
5 14 13 12
14 1

Area 1

61
71

6 15
71

81

81

91

91

01
12

1
20
21

22

22

32

32

24 2

23

1

A2-

0
100
200
300
400
500
600
700
800
900
1000

1
A3-

Daily precipitation (mm)Number of broken anchors
Daily precipitaion

Block A-1

Block A

■Rupture inside the ground (With flight)■Rupture at the back of the anchor head (No flight)■Rupture both behind the anchor head and inside the ground■The rupture position is unknown

Area 20
10Area 3
Area 4

Photo by Google Map(2020)

Fig. 6. Locations of anchor rupture and flight distance
68

0
15

m

SEE - Kyoto, Nov.18-20, 2020

where 𝒖𝒖 [kg/m] is the mass per unit length of PC
steel stranded wire and 𝒍𝒍𝒇𝒇 [m] is the wire fracture
length.

To evaluate anchor flight due to fracture, theenergy at the time of ejection was calculated from theflight distance, and a basic study was carried out
regarding measures to prevent this ejection.
The elastic energy U at the fracture of a PC steel
strand is given by the following equation:(1)

𝒗𝒗𝟎𝟎 = �where 𝑼𝑼 [kJ] is the elastic energy of the PC steel
stranded wire, 𝒌𝒌 [N/mm] is the spring coefficient of
the wire, and 𝒙𝒙 [mm] is the displacement of the wire.
The displacement x of the PC steel stranded wire isthen given by
𝒙𝒙 =𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝑷𝑷𝒍𝒍𝒇𝒇，
𝑬𝑬𝒔𝒔 𝑨𝑨𝒔𝒔

The PC steel stranded wire at this survey site has 𝑢𝑢= 1.1 kg/m, 𝐸𝐸𝑠𝑠 = 194 kN/mm2, and 𝐴𝐴𝑠𝑠 = 138.7 mm2.
From the fact that the minimum load to break ananchor is 90% of the yield tension, corresponding to
P = 199.8 kN, the initial velocity of the PC steel wire
would be approximately 37.6 m/s. From this initial
velocity v 0 , the trajectory and flight distance of the
PC steel wire were calculated. Figure 7 shows theestimated flight trajectory and flight distance of thewires in area 4, where the maximum flight distancewas confirmed. The flight distance calculated at afracture load of 199.8 kN was approximately 170 m,
and the actual observed distance was 120 m. Becauseof this discrepancy, the velocity at the time of ejectionthat matches the actual flight distance was calculated.
As shown in Fig. 8, the calculation conditions wereobtained for a trajectory that intersects with the tip ofa tree near the edge of each region. The tree height
was set to 12 m, which is the average tree height inthe surrounding area. From this computation, the(2)where 𝑷𝑷 [kN] is the load of the PC steel stranded wire,𝒍𝒍𝒇𝒇 [m] is the wire fracture length, 𝑬𝑬𝒔𝒔 [kN/mm2] is themodulus of elasticity of the wire, and 𝑨𝑨𝒔𝒔 [mm2] is the
cross-sectional area of the wire.
The relationship between the load and displacementof the PC steel stranded wire is
𝒌𝒌 =

𝑷𝑷
．
𝒙𝒙

(3)

0

0m

-20

25°

25°

-40
-60

Area 1-20-40

Area 2
Area 300mArea 4

50
50

100
100m

-60

150
150

200
200m

Horizontal distance from anchor site (m)

(5)

20

0

0m

-20

25°

25°

where 𝒎𝒎 [kg] is the mass of broken PC steel stranded
wire and 𝒗𝒗 [m/s] is the speed of the wire as it isejected from the site.

20

-40
-60

The mass m of the fractured PC steel stranded wireis given by the following equation:

Area 1-20-40

Area 2
Area 3

0
0m

50
50

Area 4

100
100m

-60

150
150

200
200m

Horizontal distance from anchor site (m)𝒎𝒎 = 𝒖𝒖𝒍𝒍𝒇𝒇 ，(6)Fig. 8. Anchor flight trajectory(Area 4, 𝑙𝑙𝑓𝑓 = 20.1 m, 𝑣𝑣0 = 29 m/s)
69

Vertical distancefrom anchor site (m)Fig. 7. Anchor flight trajectory(Area 4, 𝑙𝑙𝑓𝑓 = 20.1 m, P = 199.8 kN, 𝑣𝑣0 = 36.7 m/s)
25°

𝟏𝟏
𝟏𝟏
𝒎𝒎𝒗𝒗𝟐𝟐，𝟐𝟐𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏

20

25°

(4)

The elastic energy U when a PC strand breaks isdetermined by the load and length at the breaking
point.
Furthermore, the kinetic energy K when the PC steel
stranded wire breaks is expressed by
𝑲𝑲 =

20

Vertical distancefrom anchor site (m)Substituting Equations (2) and (3) into Equation (1)yields the following equation:
𝑷𝑷𝟐𝟐 𝒍𝒍𝒇𝒇
𝑼𝑼 =．
𝟐𝟐𝑬𝑬𝒔𝒔 𝑨𝑨𝒔𝒔

(7)

𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝑷𝑷𝟐𝟐．
𝒖𝒖𝑬𝑬𝒔𝒔 𝑨𝑨𝒔𝒔

12m

𝟏𝟏 𝟐𝟐 𝟏𝟏𝒌𝒌𝒙𝒙，
𝟐𝟐𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏

12m

𝑼𝑼 =

From the law of conservation of energy, Equations(4) and (5) must be equal, i.e., U = K. Substituting
Equation (6) into this gives the initial velocity v 0 of
the PC steel stranded wire at the break point, as

SEE - Kyoto, Nov.18-20, 2020

initial velocity at a flight distance of 120 m wasdetermined to be approximately 29 m/s.
Table 2 lists the calculation results. Area 0 is theplace where there was no flight and the protrusion of
the anchor was 2.5 m. It was confirmed that the initial
velocities of the PC steel strands at ejection werelower than the initial velocities at the time of fracture.
Figure 9 shows the relationship between the fracture
length of the PC steel wire, the elastic energy U at
rupture with a load of 199.8 kN, and the kinetic
energy K at ejection with the initial velocity obtained
from the actual flight distance.
The energy at fracture increased in proportion to thefracture length. The energy at the time of ejection wasapproximately 3 kJ lower than the energy at time ofbreakage, to a fracture length of approximately 20 m.
The energy at the time of ejection reached amaximum of 9 kJ near a fracture length of 20 m, after
which it was confirmed that the energy dropped.
Photo 7 shows the damage to the head cap caused by
the anchor rupture. It can be seen that the head cap isseverely cracked, and the anchor head is rotated andslipping downward. From this, it was considered thatthe cause of the overall energy decrease at the time ofejection was the decrease in energy due to thefrictional resistance of the PC steel wire prior tocomplete ejection. In addition, other factors, such as

Erastic energy at fracture (P=199.8kN)
Kinetic energy at ejection

Energy (kJ)

20
15

10k J

10
5
0
0

5

10

15

20

25

30

Fracture length (m)Fig. 9. Anchor energy and fracture length forejected anchors

Photo 7. Breakage of anchor head by anchor
ruptureTable 2. Measurement results of ejected PC steel strands and calculation results of energy at ejection

Area

0

1

2
3

4

Measured value
PC steel stranded wire
FlightFracture
distance(m)No.
length(m)
Min Max
1
1
2
3
4
5
6
7
8
9
1
2
1
1
2
3
4
5
6
Min
Max

2.5

2.5

30

60

50

70

70

90

85

120

2.5
85

2.5
120

12.7
22.2
21.2
25.4
25.2
25
19.3
24.8
22.4
25.8
15.5
7.5
7.7
20.1
17.6
17
17
11.5
17.8
7.5
25.8

Analysis result
At anchor breakage
At ejection
Breaking
InitialWire
Energy Velocity
Energyload
velocity
mass
𝒗𝒗𝟎𝟎
(m/s)

P
(kN)

199.8

37.6

199.8
199.8

37.6
37.6

70

U
(kJ)
10
16
16
19
19
19
14
18
17
19
11
6
6
15
13
13
13
9
13
6
19

𝒗𝒗𝟎𝟎 (m/s)

21.5
21.5
21.5
21.5
21.5
21.5
21.5
21.5
21.5
23.5
23.5
25.0
29.0
29.0
29.0
29.0
29.0
29.0
21.5
29

m
(kg)
24.4
23.3
27.9
27.7
27.5
21.2
27.3
24.6
28.4
17.1
8.3
8.5
22.1
19.4
18.7
18.7
12.7
19.6
8.3
28.4

K
(kJ)
6
5
6
6
6
5
6
6
7
5
2
3
9
8
8
8
5
8
2
9

SEE - Kyoto, Nov.18-20, 2020

the energy reduction due to the collision of the wirewith the head cap, were considered to also contributeto the lower velocity. It was considered that thereason the energy decreased for fracture lengths of 20
m or more was that a greater fracture length yields agreater influence on the internal friction resistance. In
addition, as shown in Photo 7, it was confirmed that
there were many places where the spirals were broken
one by one rather than the PC steel stranded wire.
These results indicate that it necessary to takemeasures to prevent the ejection of a single PC steel
stranded wire multiple times, even for anchors withthree PC steel stranded wires.
From the above, although a tensile load of several
hundred kilonewtons has been introduced to theanchor, the energy required for countermeasures per
PC stranded wire is approximately 10 kJ or less,which is relatively small in comparison with othernatural events such as rockfall. Furthermore, the massof the PC steel stranded wire is as small as several
tens of kilograms. If the ejection speed can beeffectively reduced, the energy can be greatly
attenuated, and it is possible that effective ejection
protection measures can be implemented.

small. It was confirmed that the energy at ejection
may not increase above a certain level depending on
the fracture length of the anchor and the internal
friction conditions.
In the future, we will continue to conduct fieldsurveys on the fracture of anchors, accumulate data,
and work toward developing slope stabilization
measures that are safe and effective even whenunexpected external forces occur.
ACKNOWLEDGMENTS
In carrying out this survey, the cooperation of the
manager of the landslide countermeasure, Public
Works Research Institute, and Anchor AssetManagement Study Group was kindly provided. This
research was supported in part by the Grant-in-Aid
for Scientific Research Project (Project No.
19K04595). We would like to express our deep
gratitude to all those involved for their cooperation.
REFERENCES[1] Yoshihiro Tsunekawa,Toshinori Sakai,Hiroaki
Miyatake,Masuo Kondoh,and Tomohiro Fujita
Survey on fractures of ground anchors caused
by inland earthquakes, Journal of GeotechnicalSociety, Vol.15 No. 2,2020, pp.339-354.
[2] Toshinori Sakaie, EVALUATION OF SLOPESTABILITY BASED ON MONITORING OF
RESIDUALLOADSONGROUND
ANCHORS USING THE SAAM SYSTEM,
SeventhInternational
Conferenceon
Geotechnique, Construction Materials andEnvironment, Mie, Japan, 2017,pp.10-18[3] Public Works Research Institute,JAPANANCHOR ASSOCIATION, Inspection and
Maintenance
Manualfor
GroundAnchors,2015,pp.58 .
[4] Japan Meteorological Agency: Various data andmaterials，
https://www.data.jma.go.jp/gmd/risk/obsdl/inde
x.php(Confirmed on September 17, 2019)

CONCLUSIONS
At a site where anchors ruptured as a result of alandslide producing a load that exceeded the designload, the rupture conditions of the anchors were
investigated over the course of five years following
the initial anchor fracture. The following observations
were confirmed, although these were obtained underlimited conditions.
It was confirmed that the rupture of the anchor
progressed in stages, and although 42 anchors, which
accounted for approximately 80% of the anchors
within the deformation range, broke, the slope did notcollapse. Of the fractured anchors, 14 were ejectedfrom their installation sites, and a maximum flight
distance of approximately 105 m was confirmed.
The load and kinetic energy when the anchors wereejected were estimated from the flight distance of theanchors, and it was confirmed that the maximum
ejection energy of a PC steel strand of wire wasapproximately 10 kJ or less, which was relatively

71

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EXAMINATION OF APPLICABILITY OF DYNAMIC LOAD TESTAND HILEY FORMULA TO SMALL DIAMETER STEEL PILE
1

Takaaki Ariki1
Ex- General Incorporated Association of Advanced Geotechnical Technology, Japan

ABSTRACTThe purpose of this study was to assess the adequacy of using Hiley formula and the dynamic load test to
estimate the bearing capacity of the steel pile with small diameter and length. The same specification piles wereused and the static and dynamic load tests were performed at the same site, and compared these results. In theexamination, the penetration and the rebound reflected the characteristics of the ground strength both the bearing
pile and the friction pile, and the amount of work obtained by the dynamic load test. Furthermore, it was
revealed that the work calculated from the rebound was directly proportional to the ultimate bearing capacity andthe work calculated from the penetration was inversely proportional to the ultimate bearing capacity in theexamination. These results suggested that Hiley formula was appropriate for the evaluation of the bearing
capacity of the small diameter steel pile. In addition, by back calculating with the known values, the range of thehammer efficiency was obtained and the hammer efficiency could be used to correct the bearing value estimatedby the formula.
Keywords: Small diameter steel pile, Dynamic load test, Hiley formula, Applicability, Hammer efficiency

relation with the variation in the hammer efficiency.
The present study puts its focus on theapplicability of the Hiley formula and the dynamic
load test by the comparison of the test results of thestatic load test and the dynamic load test which were
examined on the same test site using the piles ofsame specifications; limiting the size to small
diameter and length and material to steel.

INTRODUCTION
Hiley pile driving formula [1] is generally used
for the assessment of bearing capacity of driving
piles. This dynamic pile driving formula is stillwidely used. In general, the accuracy of the Hiley
formula decreases with increasing pile length. In
addition, it is also said that the accurate prediction ofpile capacity using this formula is not possible incase of saturated silts, clays, muds, etc. The other
hand, local buckling stress is enough to for the
bearing capacity of the pile. But for the large
diameter steel pile, the impact load/energy applied
during dynamic load test might be larger whereas it
might be smaller in case of small diameter steel piles.
Some studies have claimed that the estimatedbearing capacity by Hiley formula is not accurate
toward the bearing capacity on the static load test.
The Hiley formula was induced assuming thatequilibrium state of the energy. By the way, in thisformula, the hammer efficiency is unknown. Chelis[2] mentions that the hammer efficiency varies from
0.6 to 1.0. And, Cornfield [3] points out that the
Hiley formula is not valid for long pile. Furthermore,
Ryan et al. [4] roused attention in using the averagevalue of the hammer efficiency and showed thehammer efficiency of the actual survey. This
problem might have aroused from the fact that there
is wide variation in the size (e.g., diameter andlength) and the material property (e.g., steel orconcrete) of the pile. Thus, if the variation in the size
and the material property of the pile is limited, thevariation in the bearing capacity can be estimated in

THE STATIC LOAD TEST
For the comparison with the results of the
dynamic load test, the static load test was also
conducted for the pile with same specification asthat used for dynamic load test.
The Specifications of Pile, Installation andCuring of the Pile and Method of the Test
Table 1 shows the specification of the pile, suchas the diameter, thickness and length for each testsite. Figure 1 shows the lid with the digging claw
and the open hole. This lid which has the same
diameter as that of steel pipe, was joined to the tip ofsteel pipe by welding.
The pile was constructed by rotary penetration soas to satisfy the designed length. In the test site V,
the intermediate hard layer, which has SPT value,
N>20, was seen from 2 m to 7 m depths. This layer
was drilled by the same diameter pile before
installing the test pile. At this V test site, one pile
showed shorter length than the design length in thatthe bearing layer appeared to be shallow during the72

SEE - Bangkok, Thailand, Nov.11-13, 2019

ground survey. Such cases are noted on Table 1 with* and ** symbols.
The static load test was examined by the step
loading method until the tip displacement reached to
the 10 % of the pile diameter after about one monthcuring from the construction. During the test, theapplied load for the pile, the displacement of the pilehead and the axial strain of the pile tip were
measured. The ultimate resistance shall be definedas the load where the displacement of pile tip wasreached to 10 % of pile diameter. And, the yielding
resistance shall be defined as the load at the
inflection point that appears clearly in the log P - log
s curve or P - s curve.

Figure 2 (a) shows the relationship obtained
between the yielding displacement and the yielding
or ultimate bearing capacity for three types(diameters) of piles tested. Figure 2 (b) shows therelationship between the elastic rebound and theultimate bearing capacity on the ultimate condition
for same three types (diameters) of piles tested.
As Figure 2 (a) indicates, the yielding
displacement and the yielding or ultimate bearing
capacity are nearly in linear relationship. Also,
Figure 2 (b) indicates, the elastic rebound on
ultimate and the ultimate bearing capacity are nearlyin linear relationship. From these relationships, therelationship between the yielding displacement andthe elastic rebound at ultimate condition is plotted asshown in Figure 3. Here also, linear relationship isobserved.

Lid on tip of the pile

Table 1 Test site and specification of pile
Test
site

DiameterThickness
Lengthof pile (mm) of pile (mm) of pile (m)
114.3
4.5
12.5
I
114.3
4.5
10.5
114.3
4.5
8.25
II
89.1
4.2
6.0
165.2
6.0
8.0
114.3
4.5
6.0
III
114.3
3.5
3.0
89.1
3.2
1.0
165.2
6.0
17.0
89.1
4.2
8.0
89.1
4.2
8.0
IV
89.1
3.2
3.0
89.1
3.2
1.5
89.1
4.2
18.0
165.2
6.0
15.635*, **
165.2
6.0
16.0**
114.3
6.0
13.5**
V
89.1
4.2
4.5
165.2
6.0
21.5**
165.2
6.0
21.5
VI
114.3
4.5
15.0
89.1
3.2
3.0
89.1
4.2
13.25
VII
Note: * Remaining high toward the design length,**: Pre-drilling of intermediate hard layer

350
300

350

Tip of pile
Black: clayey
White: sandy

250
200
150
100
Diameter
89.1mm114.3mm
165.2mm50
00 2 4 6 8 10
Yielding displacement at the head (mm)Ultimate bearing capacity (kN)

Yielding or ultimate bearing capacity (kN)

Fig. 1The Results of the Test(a) Yielding displacement

250
200
150

Tip of pile
Black: clayey
White: sandy

100
50
0

Diameter
89.1mm114.3mm
165.2mm

0 2 4 6 8 10
Elastic rebound on
ultimate condition (mm)(b) Elastic reboundYielding displacement and elastic rebound
Elastic rebound (mm)Fig. 2300

10Diameter
89.1mm114.3mm
165.2mmTip of pile
White: sandy
Black: clayey

5

0
0
5
10
Yielding settlement (mm)Fig. 3

Relations of yielding settlement and elastic
rebound

THE DYNAMIC LOAD TEST
In order to compare the results of the static load
test and examine the applicability of Hiley formulain the dynamic load test, piles of similar
specification as those used in the static load test
were used. Also, the same test sites were used.
73

SEE - Bangkok, Thailand, Nov.11-13, 2019conducted.
The weight and height of the hammer were
determined by checking the local buckling of thesteel pipe by using Equation (1). From the test
results, it is observed that the hammer weight is 1.92
kN or 1.47 kN and the maximum height of thehammer (weight) kept is 2 m.

The Specifications of Pile, Installation andCuring of the Pile and Method of the Test
The test sites, specification and installation of thepile for the dynamic load test are same as that used
for the static load test (Table 1). Also, the curing
period after installation of pile is same as for thestatic load test. As explained earlier, Figure 1 shows
the lid to be connected at the pile tip. Two open
holes are provided in that lid to reduce the effect ofexcess pore water pressure which is generated
during dynamic loading [5].

E
2 gH ⋅10 −3  ⋅ e −788A W
C

σ2 = 

(1)

Where,

σ2: the impact stress in N/mm2.
E: the young’s modulus of the steel pilein N/mm2.
C: the velocity of elastic wave of the steel
pile in m/sec.
g: the acceleration of gravity in m/sec2.
H: the height of the free fall of hammer inm.
A: the cross-sectional area of the steel
pipe in m2.
W: the weight of the hammer in kN.
(a) Set of the heightFig. 4(b) Record

The Results of the Test

A situation sample of dynamic load test
3rd blow

2nd blow

Figure 6 shows the relationship between thepenetration and the rebound. It shows that with theincrease in penetration, there is decrease in therebound amount.

1st blow

Penetration
per blow

Fig. 5

Rebound (mm)Rebound per blow

15

Total penetration
per blow

Tip of pile
Sandy
Clayey10
50
0

A sample record of dynamic load test

5

10

15

20

25

30

35

40

45

Penetration (mm)In Figures 4 (a) and 4 (b), test set up height andrecording process are shown. The hammer isallowed to free fall from the height of the set to thecap with of the pile. A rubber plate of 2 cm thick is
kept on the pile cap and displacement of the pile perblow after each free fall of the hammer on the pile
cap was recorded. One of the test records of hammer
impact and penetration amount is shown in Figure 5.
The penetration per blow, rebound per blow andtotal penetration are shown in Figure 5. During the
dynamic load test, the pile is impacted (hammered) 3
times by the same hammer (weight) by allowing it tofree fall from the same hammer height. Finally thepenetration per blow and rebound per blow wereadded. Then the average penetration and reboundwere calculated for each case.
In addition, the tests were also done by varying
the impact energy to check the hammer efficiency.
The test sites and test pile specifications were sameas those used earlier. In total, 53 tests were

Fig. 6

Relations of the penetration and thereboundFigure 7 shows the relationship between the
ground strength (in terms of N’ value), thepenetration, and the rebound/length or the elasticstrain of the pile in regard with the pile tip. Figure 8
shows the relationship of the ground strength (interms of N’ value), the penetration, and therebound/length or the elastic strain in regard with thepile side. Here, the ground strength is shown interms of N’ value. The Swedish weight sounding canconduct a consecutive investigation in the ground.
The N’ value is the converted value of Swedishweight sounding method in terms of N value of theStandard Penetration Test (SPT). It is observed thatthe averaged N’ value on the pile tip is calculated in
the range of 3 times of the pile diameter from thepile tip, and the averaged N’ value on the pile side is74

SEE - Bangkok, Thailand, Nov.11-13, 2019

Penetration "S" (mm)

0.001
0

10 20 30 40 50 60
Average N' value on tip of pile

70

Penetration, rebound and elastic strain ofground toward the N’ value on tip of pile

45
40
35
30
25
20
15
10
5
0

Tip of pile
Black: sandy
White: clayey

1
S
K/l

εg

0.1

0.01

5
Average N' value on side of pile

0.1

0.01

0.001
5

10
15
20
Length of pile (m)25Penetration, rebound, elastic strain ofground and elastic strain of pile toward thelength of pile10

Tip of pile

5

Sandy

Clayey

0
0

5

10

15

20

25

30

35

40

Total penetration on dynamic load test (mm)Fig. 10 Comparison total penetration and yielding
displacement
The Comparison the Results of the Dynamic
Load Test and the Results of the Static Load Test
Figure 10 shows the relationship of the total
penetration of the dynamic load test and the yielding
displacement of the static load test. The total
penetration included all deformation by the dynamic
load test. As shown in Figure 10, the total
penetration was nearly larger than the yielding
displacement. Therefore, it is considered that the
ground has reached to the yielding condition by this

0.001
0

K/l
εg

Rebound/Length "K/l",
Elastic strain of pile "εs",Penetration "S" (mm)Fig. 9

1
S
εs

1:
1

0.01

Tip of pile
Black: sandy
White: clayey0

Yielding displacement
on static load test (mm)

εg

0.1

Fig. 7

Fig. 81S
K/l

Rebound/Length "K/l",
Elastic strain of pile "εs" (%)

Tip of pile
Black: sandy
White: clayey

Rebound/Length "K/l",
Elastic strain of pile "εs" (%)

Penetration "S" (mm)

45
40
35
30
25
20
15
10
5
0

45
40
35
30
25
20
15
10
5
0

Elastic strain of ground "εg" (%)

Figure 9 shows the relationship between the pilelength and the penetration, the rebound, the elasticstrain of the ground and the elastic strain of the steel
pipe. As shown in Figure 9, the penetration amountis dependent on the pile length clearly. And, when
the pile length is more than 15 m, the penetration
amount is almost 0. This relationship agrees withindication given by Cornfield [3] that the Hiley
formula is not valid for the longer pile. However,this relation is not influenced by the Hiley formulain that the impact energy is limited by the local
buckling stress. Thus, it is considered that thisrelation is attributed to the relations of the impact
energy and the local buckling stress.
Therefore, the penetration and the rebound arereflecting the ground properties, but the upper limit
by this test device which the ground strength can bereflecting exists, because of the upper limit of the
impact energy.

calculated in the range of pile length. Where, therebound was shown in the elastic strain by dividing
by the pile length for comparing to the elastic strainof the ground. And, the elastic strain of the steel pipecaused the impact stress of Equation (1) is obtainedby subtracting the elastic strain of the rebound andelastic deformation of cap from the total elasticstrain of the ground. Here, elastic deformation of thecap is not considered.
As shown in Figure 7, when the averaged N’value on the pile tip is smaller than 10, thepenetration, the rebound and the elastic strain ofground decreases. When the averaged N’ value ismore than 10, the penetration, the rebound and theelastic strain of the ground remains nearly constant.
Therefore, these values are dependent on the groundstrength on tip of pile, and these values are reflecting
the ground properties on tip of the pile.
In Figure 8, a trend of decrease in the value ofthe penetration, the rebound and the elastic strain ofground when the averaged N’ value on the pile sideis smaller than 5. Also, the figure shows that when
the averaged N’ value is more than 5, the penetration,
the rebound and the elastic strain of the ground isnearly constant. Therefore, these values are
depending on the ground strength on side of pile,and these values are reflecting the ground properties
on side of the pile.

10

Penetration, rebound and elastic strain ofground toward the N’ value on side of pile75

SEE - Bangkok, Thailand, Nov.11-13, 2019

relationship. The product of the impact energy andthe penetration, the product of the impact energy andthe rebound are showing the work done by the
impact energy on the dynamic load test.

Tip of pile
Sandy
Clayey10

Ultimate bearing capacity
on static load test (kN)

350

250
200
150
100

Tip of pile
Sandy
Clayey

50
0.01

0.02

0.03

0.04

0.05
2

The product of impact energy and rebound (kNm )Fig. 13 Relations of the product of the impact
energy and the rebound and the ultimate
bearing capacity
In Figure 12, the ultimate bearing capacity islarge when the penetration is small on the same
impact energy where the work done by thepenetration is inversely proportional to the ultimate
bearing capacity. And, in Figure 13, the ultimate
bearing capacity is larger when the rebound is large
on the same impact energy in that the work done by
the rebound is proportional to the ultimate bearing
capacity. Therefore, the penetration and the reboundwere depending on the ground strength, these results
enable the penetration and the rebound to assume theground strength on the same impact energy, but as
Figures 7 and 8 indicated, this assumption has an
upper limit.

5

0
0

300

0
0.00

1:
1

Elastic rebound on
static load test (mm)dynamic load test. But, when the total penetration
was nearly less than 10 mm, the total penetration
was smaller than the yielding displacement.
Figure 11 shows the relations of the rebound of
the dynamic load test and the elastic rebound of thestatic load test. As Figure 11 indicates, when theelastic rebound increased, the rebound also increased,
and the rebound was bigger than the elastic rebound.
By the way, the impact stress on the dynamic load
test which is calculated by the Equation (1) is nearlylarger than the ultimate stress on the static load testof which the ultimate bearing capacity is divided by
the cross section of the steel pipe, such as shown in
Figure 14, and as Figure 2 indicated, the yielding
displacement and the elastic rebound increased
linearly when the loading weight increased on thestatic load test.
Because of the foregoing reasons, as the total
penetration and the rebound were nearly bigger than
the yielding displacement and the elastic rebound. Itshows that the ground was reached to the yielding
condition by this dynamic load test.

5
10
Rebound on dynamic
load test (mm)Fig. 11 Comparison rebound and elastic reboundUltimate bearing capacity
on static load test (kN)350

EXAMINATION IN THE APPLICABLITY
AND RANGE OF THE DYNAMIC LOAD TEST

Tip of pile
Sandy
Clayey300
250

Because the equilibrium condition of the work
done by both the penetration and the rebound whichreflected the ground strength from the bearing pile tothe friction pile on the dynamic load test was
confirmed in the foregoing chapter and sections, theapplicability of the dynamic load test and the Hiley
formula is high. What is the noted is the range of theapplication will have the upper limit, like a situationthat the total penetration was equal to the rebound.
Thus, it can be presumed that the foregoing situationis the upper limit of the range of the application ofusing this test device. As the situation indicated in
Figure 9, when the pile length is 15 m, the reboundand the elastic strain of the steel pipe are same as
0.07 %., then the calculated bearing capacity is
about 400 kN. In this dynamic load test, the upper
limit of the application range is enough is that thedesigned ultimate bearing capacity is almost samefor the small diameter pile.

200
150
100
50
0
0.00

0.01

0.02

0.03

0.04

0.05
2

The product of impact energy and penetration (kNm )Fig. 12 Relations of the product of the impact
energy and the penetration and the ultimate
bearing capacity
Next, Figure 12 shows the relations of the
product of the impact energy and penetration and theultimate bearing capacity. Figure 13 shows therelations of the product of the impact energy andrebound and the ultimate bearing capacity
76

SEE - Bangkok, Thailand, Nov.11-13, 2019

HAMMERFORMULAEFFICIENCYON

It is considered that this result can be applied tothe calibration of the estimated bearing capacity by
the Hiley formula. And, when the designed ultimate
bearing capacity is known, the impact energy should
not be larger than the ultimate resistance necessarily
if the range of the application is shown clearly.

HILEY

Equation (2) shows the Hiley formula. The
penetration, the rebound, the weight of the hammer
and the height of the free fall of hammer are known
in this dynamic load test. Generally, the ultimate
bearing resistance is estimated from the Equation (2).
Where, it is same as the ultimate bearing capacity inthe static load test. Then, the hammer efficiency wasback calculated using these known values.

Rd u =ehWH
S+K 2

CONCLUTION
The present study puts its focus on theapplicability of the Hiley formula and the dynamic
load test by the comparison of the test results of thestatic load test and the dynamic load test which were
examined on the same test site used by the same
specification of pile, when the applied range of thesteel pipe pile is limited to the small diameter andlength.
The fact that the equilibrium condition of thework done by both the penetration and the reboundwhich reflected the ground strength from the bearing
pile to the friction pile on the dynamic load test was
confirmed by the following relations reveals that theapplicability of the dynamic load test and the Hiley
formula is high. The confirmed relations are therelations with the ground strength and thepenetration or the rebound, and the relations with theultimate bearing capacity and the work done by thepenetration or the rebound. In addition, the upper
limit of the application range of this dynamic load
test is enough in that the maximum designed
ultimate bearing capacity is almost same for thesmall diameter pile.
Furthermore, an existing range of the hammer
efficiency calculated back using known values in the
Hiley formula was shown. It is considered that thisresult can be applied to the calibration of theestimated bearing capacity by the Hiley formula.
And, when the designed ultimate bearing capacity is
known, the impact energy should not be bigger thanthe ultimate resistance necessarily if the range of theapplication is shown clearly.

(2)

Where,
Rdu : the ultimate driving resistance in kN.
eh : the hammer efficiency.
W : the weight of the hammer in kN.
H : the height of the free fall of the hammer inm.
S: the penetration by the dynamic load test inm.
K: the rebound by the dynamic load test in m.
Figure 14 shows the relationship of the impact
stress per the ultimate stress and the hammer
efficiency relationship. The value that the ultimate
bearing capacity is divided by the cross section of
the steel pipe was defined as the ultimate stress. As
shown in Figure 14, the hammer efficiency varies
from 0.2 to 0.5, when the impact stress per theultimate stress is larger than 1. When the impact
stress per the ultimate stress is less than 1, theimpact stress per the ultimate stress decreased. At
the same point, the hammer efficiency was increased.
Therefore, when the impact weight is enough tothe ultimate bearing capacity, the hammer efficiency
is almost same. In contrary, when the impact weightis less than the ultimate bearing capacity, thehammer efficiency was increased.

REFERENCES[1] Hiley, A., A rational pile-driving formula and its
application in piling practice explained,
Engineering, 119, pp.657 and 721, 1925.
[2] Chelis, R.D., Pile foundations, McGraw Hill,
pp.29-31, 1961.
[3] Cornfield, G.M., Discussion on “Pile-driving
analysis by the wave equation”, J. Soil Mech.
Found. Div., ASCE 87, No.SM1, pp.63-75, 1961.
[4] Ryan Allin, Garland Likins, Jon Honeycutt, Pile
Driving Formulas Revised, Proceedings of theinternationalfoundations
congress
andequipment expo, ASCE, 2015.
[5] Randolph, M. F., Carter, J. P. and Worth, P. C. :Driven piles in clay – the effects of installationand subsequent consolidation, Geotechnique,Vol.29, No.4, pp.361-393, 1979.

1.2

Hammer efficiency

1.0
0.8
0.6
0.4
0.2
0.0
0.1

Tip of pile
Sandy
Clayey1
Impact stress divided by ulimate stress10

Fig. 14 Relations of the impact stress divided byultimate stress and the hammer efficiency
77

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ASSESSING FACTORS INFLUENCING ROUTE CHOICE
A CASE STUDY OF TERPEKA TOLL ROAD, INDONESIA
Aleksander Purba1, Darmawan Adi Susanto2, Rosalia Dwi Werena3 and Tiara4
1,3,4Engineering Faculty, the University of Lampung, Indonesia
2
Post Graduate Program, Civil Engineering, the University of Lampung, Indonesia

ABSTRACTTERPEKA is part of the Trans Sumatera toll road network that is planned to connect the northern part of
Sumatera to the southern part and will link the province of Nanggroe Aceh Darussalam with Lampung. The
TERPEKA section is located in the Lampung and South Sumatera provinces with a total length of 189 km andexpected to increase accessibility to and from regions located in close proximity to the toll road and to stimulate
economic growth, particularly in palm oil and rubber sectors. A total of 190 respondents were collected in the rest
area of KM 234A and KM 215B on end year vacation of 2019. Respondents in the age range of 26 to 55 years
who were in the productive age category had a percentage of 84%, and age range of 36 to 45 years was recorded
as 32% which included the most productive age category. These figures indicate that Indonesia is enjoying ademographic bonus. The most significant factor influencing route choice when deciding to determine to travelusing toll road is income followed by spending for transport attribute. The equation of Y = -1.711 – 0.00000921X 1+ 0.186X 2 + 0.446X 4 is differences in the utility related to the attributes or characteristics of TERPEKA routewhich was analyzed. With the correlation coefficient, the income level and time saving variables are thosevariables that most influence the TERPEKA’s toll road users. Instead, increase in toll fares reduces vehicle use.
Keywords: TERPEKA, Fare, Income, Spending for transport, Indonesia

starting point of Terbanggi Besar to the end point of
the segment in Kayu Agung or Rp902/km.
Generally, the determination of toll fares is decided
by considering the financial condition of thegovernment, investors and road users and fares mustmeet user benefits and meet environmental
requirements [3]. Toll road financing is allocated forconstruction, operation and maintenance. Toll fareand the number of users are the two main factors
affecting revenue, investment and development oftoll roads. Travel demand depend on the number andtype of trips to be selected by individuals undercertain conditions. Factors that influence travel
demand in general are demographic, geographic andeconomic factors, which the available space canexceed capacity faster than the predicted as found by
Selmoune et. al in many cities such as Singapore,
Stockholm, and London [4]. Demographic factors
are the individual preference of road users andeconomic factors usually related to travel expenses.
Travel expenses include fares, additional travel time,
inconvenience and risks. Modeling the relationshipfactors will be useful in estimating the trip behavior
and future transport policy strategies. Changes infares can affect the frequency, route, mode, anddestination of the trip and their impact can be known
through measuring price impacts [5] and change ofutility function [6]. Study area in China has foundthe travel cost and travel time have a significantly
negative impact on the utilities [7]. The purpose of

INTRODUCTION
A Terbanggi Besar–Pematang Panggang–Kayu
Agung (TERPEKA) along 189 km is part of theplanned development of 2,974 km of Trans Sumatra
toll road. The construction of this toll road is one ofthe packages of a national strategic project initiatedby the central government. At the beginning ofdevelopment, the TERPEKA toll road segment was
declared economically feasible but financially
unfeasible, so the central government assigned astate owned company to build it. According to thefeasibility study document, the total volume oftraffic of TERPEKA is 14,000 vehicles per day andsegments that are considered financially viable areusually with total volume more than 20,000 vehicles
per day. Such conditions are not only phenomena indeveloping country such as Indonesia but also in thedeveloped country, since costs derived from throughtraffic would also not be covered by the fees, but thisissue may be moot, as most through traffic uses
arterials that are funded by higher levels ofgovernment [1].
Hence, through Presidential Regulation No.
117/2015 jo. No.100/2014 the central government
assigned PT Hutama Karya (Persero) to implement
the acceleration of development of Trans Sumatera
toll road [2]. After constructed around two years, in
mid-November 2019 the TERPEKA segment began
operating with toll fares of Rp170,500 from the78

SEE - Kyoto, Japan, Nov.18-20, 2020

the study is to model user preference on the selectionof routes between toll roads or non-toll road.

section is a combination of the Terbanggi Besar –Pematang Panggang (100 km) section which wasbuilt and operated first and Pematang Panggang Kayu Agung (89 km) section which was operated
later as shown in Fig. 1.
As part of the main network of the island of
Sumatra, this section is important to support thetransportation of goods and people from the
Bakauheni port and is expected to be able to open
access to the surrounding areas and support
economic growth, especially natural resources of oilpalm and rubber plantations. In addition, one of thevital roles expected is to reduce travel time andreduce logistics costs from the Bakauheni port toSouth Sumatera and surrounding areas [8].

MATERIAL AND METHOD
Study Area
TERPEKA is part of the Trans Sumatra toll roadwhich is planned to link from the north of the islandof Sumatra to the south and connects the province ofNangroe Aceh Darussalam to Lampung province.
This section is located in Lampung and South
Sumatra provinces and is divided into three sections
namely section 1 Terbanggi Besar - Menggala,section 2 Menggala - Simpang Pematang and section
3 Simpang Pematang - Kayu Agung. So that thisFig. 1 A section of TERPEKA toll roadprovided as conducted by Saeed & Majid [9]. An
example of a choice not revealed on the market is thecase of choosing a route between using a toll road or
non-toll road. In this case study condition, there is no
specific information or data that can be processedwith statistics to get the desired route choice. With
the stated preference technique, researchers can fully
control the factors that exist in a hypotheticalsituation. In the case of choosing a route between aStated Preference Techniques
The stated preference (SP) technique is widelyused in research and practice in travel behavior.
Generally, this method is applied to identify
behavioral responses to selected situations that are
not or have not yet been fully revealed in the market.
In practice the SP method is modified in such a way
as to the importance of the attributes in the choices

79

SEE - Kyoto, Japan, Nov.18-20, 2020

toll road and a non-toll road, alternative options aredesigned that show variations in toll fares and timesaving (compared to non-toll routes). Individuals
will state their response to these alternatives. Thenthe data is processed using statistical software to
determine the choice of the route by considering thefactors of toll fare and time saving variations.

9%

govt officer
26%

student
private/SOE

RESULT AND DISCUSSION

49%

businessman/farmerothers13%

3%

Field Survey
A total of 190 respondents were collected in therest area of KM 234A and KM 215B of TERPEKA
on December 26 and 27, 2019 between 9am and6pm. It is important to note that the number of
respondent is not large enough compared to about
18,000 vehicles per day of TERPEKA at the time thesurvey was conducted, as is also stated by Xiao et. al[10], biases may occur in the process ofcharacterizing the population by using samples [11],each person has a characteristic daily motif [12], andthe underestimation of the relatively high mobility at
the city scale [13]. The socioeconomic
characteristics of respondent are described below:
they are age group, education level, job, monthly
income range, spending for transport, annual travel
frequency, trip purpose, and reason for using tollroad, respectively.

Fig. 4 Job
3%
8%

30%

29%

Fig. 5 Income range
15%27%

17 - 25
28%

24%

<1M
1M - 2M
2M - 4M
4M - 6M
6M - 8M
8M - 10M
>10M

13%

6%

10%

11%

6%

26 - 35<0.5M

0.5M - 1M

36 - 45
46 - 55
2M - 3M

≥56
58%
32%

Fig. 6 Spending for transport

Fig. 2 Age group
1%

2%
6%

8%

<3 times

9%

42%

─high
schooldiploma

3 - 6 times
6 - 12 times
12 - 18 times

18%
undergradpostgrad42%

64%

18 - 24 times>24 times

8%

Fig. 7 Annual travel frequency

Fig. 3 Education level

80

SEE - Kyoto, Japan, Nov.18-20, 2020

business/publicaffairs

19%

24%

Here are the four most important factors
influencing preferences (Fig. 10). First, respondent
characteristics that influence the route choice are
education, income and spending for transport,
respectively. Second, the correlation coefficient
related to education factor for route choice using tollroad is 0.237 (low correlation). The sign (+)
indicates a positive correlation, meaning that thehigher education, the higher tendency of respondents
to choose toll road. Third, the correlation coefficientin terms of income related to route choice of
TERPEKA is 0.851 (very strong). This figure
indicates that the income factor is the mostinfluential factor comparing to other characteristic
factors while determining the option of using tollroads. The sign (+) indicates a positive correlation,
meaning that the higher income the higher tendency
to determine to travel using toll road. Fourth, thecorrelation coefficient associated with spending fortransport over route choice of toll road is 0443
(moderate). The sign (+) indicates a positive
correlation, which means the higher spending fortransport the more people use toll road.

school/college
10%leisureothers47%

Fig. 8 Trip purpose
3%

3% 3%

cutting travel
time
Safer
more
convenient
others91%

Route Choice Probability
Based on the toll fare variables, the respondent's
largest preference for "may be not use toll" if the fareincrease amounted to Rp50,200 was 20.50% forincome group of 2M to 4M. These income groups
have the potential to switch for choosing non-tollroad if toll fares increased more than Rp50,200. The
respondent preference on the route choice can beseen in the following Table 1.

Fig. 9 Reason for using toll road

Correlation Analysis
Correlation
analysisof
respondent
characteristics was conducted to determine theinfluence of a number of socioeconomic factors indetermining route choice. The correlation coefficientof variables
expressing
therespondents'characteristics is shown in Figure 10 below. The
figures of correlation coefficient were obtained fromthe correlation analysis by using statistical software.
The significance test of the correlation coefficient isconducted based on probability with a confidence
level of 95%.

Table 1. Income group, fare, and route choice
Income
2M-4M
4M-6M
1M-2M
6M-8M

Δ-Fare50,20025,200

%
20.50
17.89

80,200

10.53

9,200

6.32

In terms of time saving variable, the respondent’s
largest preference for "may be not use toll" if thetime saving range is only two hours with apercentage of 11.58% for income group of 2M to
4M.
These income groups have the potential to switch
for choosing non-toll roads if time saving is less than
two hours. Route choice preferences for various
income group categories and time saving ranges isshown in Table 2.
Furthermore, based on the results of the
respondent's preference, an equation approach canbe made to predict the binary logit model of route
choice between toll roads and non-toll roads.

1
0.8
Correlation coeff.

Preference
May be not use toll
May use toll
Definitely not use
toll
Definitely use toll

0.6
0.4
0.2
0
-0.2
Factor influencing preferences

Fig. 10 Correlation coefficient of toll user
characteristics

81

SEE - Kyoto, Japan, Nov.18-20, 2020

highest percentage of 47% and the respondents
determined a toll road with a percentage of 91% dueto the reason would cutting travel time. The mostsignificant factor influencing route choice when
deciding to determine to travel using toll road isincome with a correlation coefficient of (+) 0.851.
This figure indicates that the higher income thehigher tendency to determine to travel using tollroad. Findings on this research are not muchdifferent compared to respondent behavior of other
cities as expressed by Atlanta [15, 16] and Abu
Dhabi [17]. Attribute related to spending fortransport is quite influential on the route choice fordetermining toll roads with a correlation coefficientof (+) 0,443. It means the higher spending fortransport of respondents, they have tendency todetermine for using toll road compared to non-tollroad. The equation of Y = -1.711 – 0.00000921X 1 +0.186X 2 + 0.446X 4 is differences in the utility
related to the attributes or characteristics of
TERPEKA route which was analyzed. Route choiceprobability between the toll roads and non-toll roads
is represented by attributes of toll fares, time saving
and income level and its differences in utility would
maximized by respondents according to his/hercharacteristics individually in deciding of available
options. With the correlation coefficient, the income
level and time saving variables are those variables
that most influence the TERPEKA’s toll road users.
Instead, increase in toll fares reduces vehicle use.

Table 2 Income group, time-saving, and route choice
Income
2M-4M
4M-6M
2M-4M
1M-2M

Preference
May not use toll
May use toll
May not use toll
Definitely not use
toll

Δ-t-save
2
3
1

%
11.58
8.95
7.89

1

7.37

The model is to specify differences in the utility
associated with both available routes. Hence,equation (U toll - U non-toll ) is the difference in theutility of toll road route and non-toll road route. The
general form of a multiple linear regression analysis
formed is as follows:
Y = a + b 1 (X 1toll – X 1non-toll ) + b 2 (X 2toll – X 2non-toll ) +(1)…. + b n (X ntoll – X nnon-toll )Furthermore, the model with the best
performance on the backward elimination validation
set is selected as below:
𝑌𝑌 = −1.711 – 0.00000921𝑋𝑋1 + 0.186𝑋𝑋2 + 0.446𝑋𝑋4

with,
X 1 : toll fares
X 2 : time saving
X 4 : income level

With the correlation coefficient, the variables X 4 andX 2 are those variables that most influence the
TERPEKA’s toll road users. Instead, increase in toll
fares reduces vehicle use.

ACKNOWLEDGEMENT
Authors thank DIPA Engineering Faculty the
University of Lampung to support research project
and the people who have helped field survey and also
the reviewers for all useful and helpful comments on
our manuscript.

CONCLUSION
Respondents in the age range of 26 to 55 years
who were in the productive age category had apercentage of 84%, and age range of 36 to 45 years
was recorded as 32% which included the mostproductive age category. This figure is almost threetimes higher compared to the HOT and HOV – HOTmarkets of the USA which is only 12% [14]. Thesefindings indicate that Indonesia is enjoying ademographic bonus, which are shown through a highpercentage of the age range of productive categories
and also the most productive age range, which ismuch higher compared to developed countries suchas the USA. Respondents with education level ofhigh school and diploma have the largest percentage
of 42%. In terms of job, respondents with selfemployed/farmers had the highest percentage of
49%. According to monthly income, respondents
with 2M to 4M income range had the highest
percentage of 30%. Respondents with a spending fortransport of 0.5 M to 1M were recorded at 58% andrespondents with the annual travel frequency lessthan three times had the highest percentage of 64%.
Respondents with trip purpose for leisure have the

REFERENCES[1] Junge, J. R., and Levinson, D., Prospects fortransportation utility fees, J. of Transport andLand Use, Vol. 5, No. 1, 2012, pp. 33-47.
[2] Retrieved
from
http://www.jdih.kemenkeu.go.id/fullText/201
5/117TAHUN2015PERPRES.pdf,(In
Indonesian)[3] Yusuf, J. E. (Wie)., O'Connell, L., and Anuar,
K. A., For Whom the Tunnel Be Tolled: A
Four-Factor
Model
for
Explaining
Willingness-to-Pay Tolls, School of PublicService Faculty Publications, Vol. 1, 2014,
pp.1-28.
[4] Aya, S., Qixiu, C., Lumeng, W., and Zhiyuan,
L., Influencing Factors in Congestion Pricing
Acceptability: A Literature Review, J. of
Advanced Transportation, Vol. 2020, 2020, pp.
1-11.

82

SEE - Kyoto, Japan, Nov.18-20, 2020

[5] Litman, T., Understanding Transport Demands
and Elasticities How Prices and Other Factors
Affect Travel Behavior, Victoria Transport
Policy Institute, 2019, pp. 1-79.
[6] Saeed, A. B., Mitra, H., Madjid, T., and Debora
C., A logit-based model for measuring theeffects of transportation infrastructure on land
value, J. of Transportation Planning andTechnology, Vol. 40, No. 2, 2017, pp. 143–
166.
[7] Xiaomei, L., Yusak, O. S., Chunfu, S., andChengxi, L., The Implication of Road Toll
Discount for Mode Choice: Intercity Travel
during the Chinese Spring Festival Holiday, J.
of Sustainability, Vol. 10, No. 2700, 2018, pp.
1-16.
[8] Retrieved from https://kppip.go.id/en/priorityprojects/road/15-sections-of-the-sumatera-tollroad/[9] Saeed, A. B., and Majid S., A modern
congestion pricing policy for urban traffic:
subsidy
plus
toll,
J.
of
ModernTransportation, Vol. 25, 2017, pp. 133–149.
[10] Xiao, Y. Y., Wen, X. W., Zi, Y. G., and Ying,
C. L., Universal model of individual andpopulation mobility on diverse spatial scales, J.
of Nature Communications, Vol. 8, No. 1639,
2017, pp. 1-9.
[11] Zhengbing, H., Spatial-temporal fractal ofurban agglomeration travel demand, J. of
Physica A: Statistical Mechanics and its
Applications, Vol. 549, 2020, pp. 1-11.

[12] Christian, M. S., Vitaly, B., Thomas C.,
Zbigniew, S., and Marta, C. G., Unravelling
daily human mobility motifs, J. of Royal
Society Interface, Vol. 10, No. 84, 2013, pp. 18.
[13] Xiao, Y. Y., Chen, Z., Ying, F., Zengru, D., andWen, X. W., Universal predictability ofmobility patterns in cities, J. of Royal SocietyInterface 11(100), 2014, pp. 1-7.
[14] Sara, K., and Randall, G., Socioeconomic
Assessment: Conversion of I-85 HighOccupancy Vehicle to High-Occupancy Toll in
Atlanta, Georgia, Transportation Research
Record: Journal of the Transportation Research
Board, No. 2450, 2014, pp. 52–61.
[15] Randall, G., Joonho, K., Daejin, K., Sara, K.,
Adnan, S., and Yanzhi, X., Factors affecting
Atlanta commuters’ high occupancy toll lane
and carpool choices, International Journal of
Sustainable Transportation, 2019, pp. 1-12.
[16] Adnan, S., Aditi, M., and Randall, G., HighOccupancy Toll Lane Decision Making:
Income Effects on I-85 Express Lanes, Atlanta,
Georgia, Transportation Research Record:
Journal of the Transportation Research Board,
No. 2531, 2015, pp. 45–53.
[17] Ammar, A., and Zaidan, Analysis of factors
affecting willingness to pay for highoccupancy-toll lanes: Results from statedpreference survey of travelers, J. of Transport
Geography, Vol. 66, 2018, pp. 91-105.

83

6th

Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

DEVELOPING NUMERICAL MODEL FOR LIQUEFACTIONINDUCED LATERAL DEFORMATION USING SPH

Erly Bahsan1, Budi Susilo Soepandji1, Dwinanti Rika Marthanty1 and Widjojo Adi Prakoso1
1
Department of Civil Engineering, University of Indonesia
ABSTRACT
Numerical simulation on lateral displacement after liquefaction has been a focus for the latest studies ingeomechanics. However, the use of finite element and finite different as the most popular numerical methods ingeomechanics has some limitations in representing such large failure. As an alternative, the smoothed particle
hydrodynamics (SPH) has been used for this purpose. This recent study tries to apply the SPH to simulate the verylarge lateral displacement following the liquefaction as part of bigger research in studying such phenomenon insome locations near Palu City, Central Sulawesi, Indonesia, after the big earthquake on 28 September 2018. The
SPH model will be developed by assuming the liquefied sand as fluid particles that interacts with pore waterparticles. Some hypotheses regarding the main factors that possibly related to the large displacement will besimulated using the SPH model, which are the effect of the very gentle sloping ground and the effect of water filmthat might be developed during the liquefaction. The outcomes of this recent study were expected to complement
the previous studies regarding the use of SPH for liquefaction and lateral spreading.
Keywords: Smoothed Particle Hydrodynamics, liquefaction, numerical method
INTRODUCTION

method is also applied for geomaterials andgeodisaster models as mentioned by [6]. Examples ofapplications are for dam-break analysis [7], large
deformation and slope failure [8], seepage [9], andliquefaction [10].
This article presents the progress of the on-going
research on the use of SPH model to simulate thelateral deformation after liquefaction. This research isa part of the bigger research to study the mechanismof the phenomenon that occurred in Central Sulawesi.
It is expected that this numerical model could help inunderstanding the factors that caused such thing,hence it will be easier to identify the risk in the future.

The big earthquake in Central Sulawesi, Indonesia,
on 28 September 2018 showed some major impact
such as tsunamis, rockslides and landslides, structural
damages, and liquefactions. Yet, the most notablephenomenon was the large lateral soil deformation
following the liquefactions. According to [1] at least
there were 5 locations near Palu City that experienced
the large lateral displacement after the earthquake:
Petobo, Jono Oge, Lolu Village, Sibalaya, andBalaroa. Those were noted as the largest lateraldisplacement ever recorded [2].
To avoid more damage due to this phenomenon,
it is necessary to study its behavior and theinfluencing factors using numerical models. However,the commonly used numerical methods ingeotechnical studies such as Finite Element and Finite
Difference have difficulties to represent the large
deformation since both methods are grid based. In theother hand, Smoothed Particle Hydrodynamics (SPH)
as a mesh-free numerical method can overcome thislimitation. In SPH, the materials are represented by aset of particles that can freely move and interact witheach other within a range controlled by a weighting
function [3].
Smoothed particle hydrodynamics is a mesh-freeparticle method based on Lagrangian formulation,that was first applied to solve the astrophysicalproblems in open space (e.g., [4], [5]). Recently, thisBASIC CONCEPT OF SPH
The concept of SPH as mentioned by [3] is that astate of system is represented by a set of particles,
which possess the material properties and interact
with each other within a range that controlled by aweight or smoothing function. SPH is built oninterpolation theory with two essential aspects, which
are the kernel approximation and particle
approximation (e.g., [6]). Consider a particle  asshown in Fig. 1, the value of a function at computing
particle  is approximated using the average of thosevalues of the function at all particles in the influence
domain of particle , weighted by the smoothing84

SEE - Kyoto, Japan, Nov.18-20, 2020

function, which is W in Fig. 1. The neighboring
particle is shown as , and the radius of influence
from particle  is h.

type of fluid. The relationships between shear stressand shear strain are shown in Fig. 2, as taken from
Huang et al. (2014).

The kernel approximation can be written as afunction f(x) as the position of vector x:〈𝑓(𝑥)〉 = ∫ 𝑓(𝑥′) 𝑊(𝑥 − 𝑥′, ℎ)𝑑𝑥′(1)where f  is the volume of integral that contains x.
The smoothing function W should satisfy a numberof conditions:
1. the unity or normalization condition:∫ 𝑊(𝑥 − 𝑥′, ℎ) 𝑑𝑥′ = 1(2)

2. delta function property:
𝑙𝑖𝑚 𝑊(𝑥 − 𝑥′, ℎ) = 𝛿(𝑥 − 𝑥′)(3)

3. compact condition
𝑊(𝑥 − 𝑥′, ℎ) = 0 when |𝑥 − 𝑥′| > 𝜅ℎ

(4)

ℎ→

Fig. 2 Relationship between shear strain rate andshear stress (reproduced from [6])Line (a) in Fig. 2 show the characteristic ofNewtonian fluid, where n = 1 and y = 0. Thus 0 as
the gradient represent the viscosity of Newtonian
fluid. For n = 1 and y > 0, this equation represents thecharacteristics of Bingham fluid as shown by line (b)where 0 represents the viscosity after yield. Line (c)represents the pseudoplastic fluid, where y = 0 and n< 1, while line (d) represents the dilatant fluid with y= 0 and n > 1. The Bingham model is suggested by[6] to simulate the large deformation of soil.
The Bingham fluid constitutive should beinterpreted using the equivalent Newtonian viscosity
to be incorporated into an SPH model. The equivalentviscosity derived from Eq. (6) with n = 1 becomes:

where  is a constant related to the smoothing
function for a particle at x, and h defines theeffective (non-zero) area of the smoothing function.

𝜂′ = 𝜂 +̇

(7)Fig. 1 Concept of SPH
The particle approximation can be written as⟨𝑓(𝑥)⟩ = ∑𝑓 𝑥

𝑊 𝑥 − 𝑥 ,ℎ(5)where N is the total number of particles within theinfluence area of the particle at x, and m/ is the ratio
off mass to density of particle j.
In hydrodynamics, the dynamic characteristic of
fluid can be described as:𝜏 = 𝜂 𝛾̇ + 𝜏

Fig. 3 Concept of equivalent viscosity [6](6)The concept of equivalent viscosity (’) is shownin Fig. 3. The solid line is the viscosity after yield that
represents the relationship between shear stress andshear strain rate for the Bingham model (0), whereas

where  is shear stress, 𝛾̇ is the rate of shear strain,and 0, n, and y are material parameters related to the85

SEE - Kyoto, Japan, Nov.18-20, 2020

the dashed lines are the equivalent Newtonianviscosity that represent motion characteristics
expressed by the Bingham model.

The condition of liquefaction will be modeled as
saturated sand, where the particles of sand andparticles of water mixed randomly as shown in Fig. 4.
When the liquefaction happen, the sand usually settle
down due to the dynamic load (from earthquake) andthe pore water will rise to the top, and sometimes
burst up above the surface as shown in Fig. 5.

METHODOLOGYThis study will be conducted in two parts: the firstpart will focus on modelling the process ofliquefaction, while the second part will focus on theinteraction of water and impermeable soil layer thatis suspected as the important factor that affecting thelarge lateral soil displacement following theliquefaction.
All the simulation here are conducted in Fortranlanguage.

Interaction of Water and Impermeable Layer
The second part of this study tries to represent the
behavior of trapped water below the relatively
impermeable soil layer after liquefaction, as mention
in [13] as the water film effect. The model is built byplacing the particles of water below the sets ofparticles of soil that cannot be penetrated by theparticles of water, as shown in Fig. 6.
The impermeability of the particles will be
represented by the coefficient of damping (noted asKd) and coefficient of stiffness (noted as Ks). The
sensitivity analysis will be conducted to check theeffect of those coefficient to the impermeability
behavior.

Sand and Water at Liquefaction
Basic modeling of sand and pore water behaviour
as a dummy fluid-like material with different densityand viscousity (e.g., [10], [11]), continuing the resultsfrom previous study by [12]. Sand as granularmaterial is assumed to have a fluid-like behavior,especially when liquefaction occurs, based on the
study by Hamada and Wakamatsu as mentioned in[11]. It was stated that the physical and mechanicalproperties of liquified sand can be represented byfunction of viscosity.
In this study, the liquefaction phenomenon will beapproached by modeling the behavior of two different
type of particles that have different properties (unitweight and viscosity).

Fig. 6 The model for water trapped below theimpermeable soil layer (top grey circles are theimpermeable soil particles)
The algorithm of the SPH numerical model isdrawn in a flowchart as shown in Fig. 1Fig. 7, where
the particle i is the main particle and particle j is theneighboring particle. The steps are started withdefining the initial conditions for the particles’
parameters and positions, and followed by calculating
the particles’ distances, forces, accelerations, andpositions. The particles’ positions and velocity will be
updated through the simulation time.

Fig. 4 Particles of sand (dark circles) and water(white circles) are placed randomly beforeliquefaction

CURRENT PROGRESS
For the first part of this study, the sensitivity
analysis on the effect of assigned viscosity to changeof unit wight of the particles of sand was conducted.
Some of the results are shown in Fig. 8. It can be seenthat the increase of viscosity value above 1 Pa.s will
result to zero changes on density after certain
simulation time.

Fig. 5 Particles of sand will be compacted down
while the particles of water pushed to the top

86

SEE - Kyoto, Japan, Nov.18-20, 2020

0.002 s0.2 s

1sFig. 7 Flowchart of the SPH simulation

CONCLUSIONSThis paper presents the current proress of an ongoing study about the development of numericalmethod using the Smoothed Praticle Hydrodynamics.
The final target is to model the behavior of large soil
displacement after liquefaction. This initial phase is
aimed to find the suitable parameters to the SPH
particles to behave as the actual materials in the field.

Fig. 8 The effect of different viscosity to density
Table 1 show the current results of visualizationof the simulation results to model the simpleliquefaction process. The initial condition is torepresent the condition as shown in Fig. 4 where thesand and water particles are placed randomly, andduring the liquefaction the sand particles will moveand settled down. The liquefaction is consideredstopped when the particles are positioned unmoved at
the end of simulation time (1 second).

ACKNOWLEDGMENTS
The authors would like to thank to Hana Saffanah,
Hutami Mahardima, and Yudha Wicaksana, thestudents of the Department of Civil Engineering
University of Indonesia who helped the authors indoing this study.
REFERENCES

Table 1 Visualization of the simulation results[1] H. B. Mason et al., “GeotechnicalReconnaissance: The 28 September 2018 M7.5
Palu-Donggala, Indonesia Earthquake,” GEER061, 2019.
[2] I. M. Watkinson and R. Hall, “Impact ofcommunal irrigation on the 2018 Palu
earthquake-triggered landslides,” Nat. Geosci.,
vol.
12,
pp.
940–945,2019,doi:
https://doi.org/10.1038/s41561-019-0448-x.
[3] M. B. Liu and G. R. Liu, “Smoothed Particle
Hydrodynamics (SPH): an Overview and Recent

InitialCondition

87

SEE - Kyoto, Japan, Nov.18-20, 2020

[4]
[5]

[6]
[7]

[8]

[9]

Developments,” Arch. Comput. Methods Eng.,
vol. 17, no. 1, pp. 25–76, 2010.
L. B. Lucy, “A numerical approach to the testingof the fission hypothesis,” Astron. J., vol. 82, no.
12, p. 1013, 1977.
R. A. Gingold and J. J. Monaghan, “Smoothed
particle hydrodynamics: theory and application
to non-spherical stars,” Mon. Not. R. Astron.
Soc., vol. 181, no. 3, pp. 375–389, 1977.
Y. Huang, Z. Dai, and W. Zhang, Geo-disaster
Modeling and Analysis: An SPH-based
Approach. Springer, 2014.
Z. Wang and H. T. Shen, “Lagrangian simulationof one-dimensional dam-break flow,” J.
Hydraul. Eng., vol. 125, no. 11, pp. 1217–1220,
1999.
H. H. Bui, R. Fukagawa, and K. Sako,“Smoothed particle hydrodynamics for soil
mechanics,” in Numerical Methods inGeotechnical Engineering, London: Taylor &Francis Group, 2006.
K. Maeda and M. Sakai, “Development of
seepage failure analysis procedure of granularground with Smoothed Particle Hydrodynamics(SPH) method,” J. Appl. Mech., vol. 7, 2004.

[10] M. Naili, T. Matsushima, and Y. Yamada, “A 2D
Smoothed Particle Hydrodynamics method forliquefaction induced lateral spreading analysis,”
J. Appl. Mech., vol. 8, pp. 591–599, 2005.
[11] J.-I. Hwang, C.-Y. Kim, C.-K. Chung, and M.M. Kim, “Viscous fluid characteristics ofliquefied soils and behavior of piles subjected toflow of liquefied soils,” Soil Dyn. Earthq. Eng.,
vol. 26, pp. 313–323, 2006.
[12] S. Rachman, J. Sjah, R. R. D. R. Marthanty, and
H. Soeryantono, “Fluid-fluid Interaction Studyof Different Density and Viscosity Using
Smoothed Particle Hydrodynamics Method,” in
IOP Conference Series: Materials Science andEngineering, Jakarta, 2018, vol. 453, doi:
10.1088/1757-899X/453/1/012048.
[13] T. Kokusho, “Mechanism for water film
generation and lateral flow in liquefied sandlayer,” Soils Found., vol. 40, no. 5, pp. 99–111,
2000.

88

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STUDY ON ADSORPTION OF HEAVY METALS BY RICE HUSK AND
EXTRACTION OF HEAVY METALS ADSORBED IN RICE HUSK
Ayane Yanaka1, Keiichiro Shibata2, Naomichi Matsumoto3 and Hidenori Yoshida4 1
Graduate School of Engineering, Kagawa University, Japan; 2 Kajima Corporation, Japan, 3 Technical staff,
Kagawa University, Japan; 4 Faculty of Engineering and Design, Kagawa University, Japan
ABSTRACT
Heavy metals with strong toxicity are contained in the mine drainage generated from the suspended or
abandoned mines that once had mining activities. The mine drainage continues to flow semi-permanently. Thus
the treatment of mine drainage must be continued. As the current treatment method for the mine drainage treatment,
the neutralization treatment process utilizing alkali chemicals is mainly conducted. However, few alkali chemicals
satisfy both low cost and high neutralizing ability. In addition, regarding the neutralized deposits generated during
the treatment of mine drainage, it is difficult to secure the disposal sites. Moreover, in recent years, the metal
demand increases by the development of IC chip and electric automobile. In this study, in order to achieve both
low cost and high adsorption performance, focusing on the rice husk which is an industrial waste, the purposes ofthis study are to verify the adsorption performance of rice husks for heavy metals and to verify whether the
extraction of heavy metals from rice husks to which heavy metals are adsorbed is possible or not. From the test
results, it is turned out that the rice husks have a sufficient adsorption performance for zinc, copper and cadmium.
Furthermore, it is proved to be possible to extract them from the rice husks which adsorbs such heavy metals. It isclarified that the utilization of rice husk can be an effective method for removing heavy metals in mine drainage.
Keywords: Mine drainage, Rice husk, Adsorbent, Heavy metals, Extraction

deposits generated during the neutralization treatment
and the security of the disposal site for the deposits.
Furthermore, heavy metals contained in theneutralized sludge may be eluted from the sludge toclarified water when the neutralization treatment bycalcium hydroxide are conducted as in [3]. On theother hand, metals with high resource value such as
zinc (Zn) and copper (Cu) are included in the minedrainage. In recent years, the resource recycling by
the urban mine development is promoted, because themetal demand increases by the development of IC
chip and electric automobile. Therefore, adsorption
treatment is suitable for a simple treatment method
instead of the current neutralization treatment in orderto solve these problems. An adsorbent utilized as themine drainage treatment method is desirable toconsider the following three issues; one is that
adsorbents are inexpensive, another is that heavy
metals adsorbed after adsorption can be recovered,and the other is that the adsorbents after recovering
heavy metals should be recycled. Then, in this study,
in order to achieve both of low cost and highperformance, focusing on the rice husk which is anindustrial waste, the purposes are to verify theadsorption of heavy metals by rice husks and to verify
whether the extraction of heavy metals from ricehusks to which heavy metals are adsorbed is possible
or not.

INTRODUCTION
In recent years, the soil and groundwater pollution
by heavy metals have been frequently confirmed informer factory sites. The purification methods for
those pollutions are complicated, and many of them
are costly as in [1]. The treatment of mine drainage inthe suspended or abandoned mines has a similar
problem. The mining activities are suspended orclosed the suspended or abandoned mines which arescattered all over Japan. Heavy metals with strong
toxicity are contained in the mine drainage generated
from the suspended or abandoned mines. Once themine is operated, the mine drainage continues to flow
semi-permanently. Even if the mine is suspended orclosed, the mine drainage does not stop. If the minedrainage containing harmful substances such as
heavy metals is discharged without any treatment, it
causes pollution to river water and groundwater in thevicinity. Thus the treatment of mine drainage must becontinued. The current treatment method for the minedrainage treatment is mainly the neutralization
treatment method utilizing alkali chemicals such as
slaked lime as in [2]. However, few alkali chemicals
satisfy both low cost and high neutralizing ability. In
addition, the treatment process to purify the minedrainage to the level where it can be released intorivers is complicated, and it seems that the current
treatment method will be costly. Additionally, there
are agendas such as the disposal of neutralized
89

SEE - Kyoto, Japan, Nov.18-20, 2020

ADSORBENT

the initial pH of these solutions is adjusted to 6. Next,
10 mL of the prepared solution is poured into acentrifuge tube to which 20 mg of raw rice husk isadded. Then, 10 mL of solution with 20 mg of raw
rice husk is shaken for 24 hours at 200 revolutions at
a temperature of 20 ° C. After that, the solutions arecentrifuged at 2000 rpm for 3 minutes, and theresidual concentration of heavy metals: Zn, Cu andCd, in the solutions are analyzed by an ICP-AES. In
the study, the adsorption amount per unit mass of theraw rice husks is employed as the evaluation of thetest result. The adsorption amount per unit mass of theraw rice husks is defined by the following equation(1).

Photo. 1 shows the rice husk utilized as anadsorbent in this study. In Japan, about 2 million tonsof rice husks are discharged annually. Rice husks
containing much silica have high hardness, and it isdifficult to process rice husks. Therefore, rice husks
have no use other than simple agricultural materials,
and many of them are discarded. At present, there arefew effective utilization methods for rice husks, andvarious research institutes are actively conducting the
research on utilization methods for rice husks. As one
example, Kobayashi et al. states that the rice husk
charcoal has an adsorption performance for cesium(Cs) and strontium (Sr) in aqueous solution as in [4].
In addition, it is reported that the rice husk ash has anadsorption ability for heavy metals such as lead (Pb),mercury (Hg), zinc (Zn), nickel (Ni) and cadmium(Cd) as in [5], [6]. However, it takes labor and cost toprocess into coal and ash. Additionally, it is difficult
to collect rice husk charcoal and ash after utilized as
an adsorbent. Moreover, there are few studies inwhich the adsorption performance and adsorption
mechanism of raw rice husks for heavy and the reusemethod considering the tight disposal site areinvestigated. In this study, various tests are conductedusing the raw rice husks dried at 100 ° C for 24 hours.

Wi (mg⁄g)=

V(Co -Ci )Mi(1)In the equation (1), “V” is the amount of thesolution, “Co” is the initial concentration of thesolution, “Ci” is the residual concentration(equilibrium concentration) and “Mi” is the mass of
the raw rice husks.
In order to ensure reproducibility, the average
results obtained from the tests conducted three times
are adopted as test results. In addition, the test results
are applied to Langmuir and Freundlich models so as
to clarify the adsorption mechanism of the adsorbent
for the heavy metals. Langmuir and Freundlichmodels are typical adsorption equilibrium equations
in liquid-phase adsorption. Langmuir and Freundlichmodels are defined by the following equation (2) and(3), respectively.
Ci
1
1
=
+
C
Wi aWs Ws i

(2)

1
Freundlich: log Wi = log K F + log Cin(3)Langmuir:

Photo. 1 Raw Rice Husks

In the equation (2), “a” is the adsorption
equilibrium constant, “Ws” is the amount of saturation
adsorption. In the equation (3), “1/n” is the affinity
between adsorbent and adsorbate, “KF” is theadsorption capacity.

TEST METHOD
Since zinc (Zn), copper (Cu), and cadmium (Cd)have been detected in mine drainage water leaked
from many suspended mines, three kinds of heavy
metals are examined in this study.

Extraction Test Of Heavy Metals From The Rice
Husks To Which Heavy Metals Are Adsorbed

Heavy Metals Adsorption Test (Shaking Test)
In order to confirm whether it is possible torecover heavy metals which are valuable resourcesfrom the used rice husks (uRRH) adsorbing heavy
metals, the extraction of heavy metals adsorbed fromuRRH is tried with nitric acid solution.

Based on the adsorption isotherms obtained fromshaking tests for zinc, copper and cadmium, theadsorption performance of raw rice husks (RRH) forthem is evaluated. In the test, three solutions areprepared. One contains zinc nitrate solution, anothercontains copper nitrate solution and the other contains
cadmium nitrate solution. First, seven initialconcentrations (3 ppm, 4 ppm, 5 ppm, 6 ppm, 7 ppm,
30 ppm, 60 ppm) of each solution are prepared andPreparation of the raw rice husks adsorbing heavy
metalsFirst, a solution similar to the shaking test is90

SEE - Kyoto, Japan, Nov.18-20, 2020

the coefficient of determination (R2) is close to 1 inFig. 1, it is indicated that the adsorption mode of theraw rice husks to Cd is likely to be monolayer
adsorption. Fig. 2 shows that the amount of Cd
adsorbed in the low concentration region is not solarge. It is also confirmed that a large amount of Cd
can be adsorbed as the concentration increases. It is
confirmed that the amount of Zn or Cu adsorbed in
the low and high concentration regions is not so large,
and that a large amount of Zn or Cu can be adsorbed
in the medium concentration region. Water molecules
are more abundant than heavy metal ions in the low
concentration region. As described in the reference,liquid phase adsorption is a competitive adsorption ofsolvent and adsorbate on the adsorbent surface. In the
low concentration region, it is considered that it does
not become the adsorption of the logarithmic function
type for either heavy metal, that is, a large amount ofheavy metals are not adsorbed to an adsorbent. The
adsorption mode of the raw rice husks for Cd ismonolayer adsorption, and it seems to be able toadsorb more Cd because of the strong attractive force
between adsorbent surface and adsorbate. On theother hand, with respect to Zn and Cu, it is consideredthat Zn and Cu are further attached on the first layer
on which Zn and Cu have already been adsorbed, thatis, the adsorption mode is likely to be multi-molecularlayer adsorption. It is considered that the adsorption

prepared, and the initial concentration and pH are
adjusted to 5 ppm and 6, respectively. Next, 50mL of
the solution is poured into a centrifuge tube, and 1.0g
of the raw rice husks is added. Then, the prepared
solutions are shaken and centrifuged under the same
conditions as has already mentioned in shaking test.
After that, the raw rice husks which adsorb heavy
metals are separated from the solutions by a filtration
apparatus, and the residual concentration of heavy
metals in the solutions is analyzed by an ICP-AES.
The difference between the initial concentration andthe analyzed one is defined as the concentration ofheavy metals contained in the raw rice husks which
adsorb heavy metals.
Extraction of heavy metals by nitric acid solution
First, 50 mL of a solution of nitric acid(Concentration: 0.1 mol/L) is poured into a centrifuge
tube, and then the raw rice husks to which heavy
metals have been adsorbed are added. Then, thesolutions are shaken at 200 rpm for 6 hours by ashaking apparatus. After that, the solutions arecentrifuged at 2000 rpm for 3 minutes, and theresidual concentration of heavy metals in thesolutions is analyzed in an ICP-AES. In order toensure reproducibility, the average results obtained
from the tests conducted three times are adopted as
test results as mentioned in shaking test.

18
16
14
12
10
8
6
4
2
0

RESULT

C/W

Result Of Adsorption Test For Heavy Metals

Zn/RRH R² = 0.8251
Cu/RRH R² = 0.9878
Cd/RRH R² = 0.9993

The adsorption isotherms obtained in the tests
with the Langmuir model are shown in Fig. 1, andthose with the Freundlich model are shown in Fig. 2.
The horizontal and vertical axes in Fig. 1 are theequilibrium concentration of heavy metals (Zn, Cu
and Cd), and the value obtained by dividing theequilibrium concentration by the adsorption amountof heavy metals (C/W), respectively. The horizontal
and vertical axes in Fig. 2 are the logarithm of theequilibrium concentration of heavy metals (logC) andthe logarithm of the adsorption amount of heavy
metals (logW), respectively. The Langmuir model
suggests whether the adsorption mode is monolayer
adsorption or not. The applicability of the Langmuirmodel depends on whether the linear relationshipbetween the equilibrium concentration of heavy
metals and the value of equilibrium concentration
divided by the adsorption amount of heavy metals
holds or not. When Langmuir model is not applied, it
is possible that the adsorption mode is multimolecular layer adsorption. In addition, Freundlichmodel shows that a large amount of heavy metals areadsorbed in the case of logarithm shape, and theamount of heavy metals are adsorbed is not so large
in the case of exponential shape. Since the value of

0

10

20

30

40

50

60

Equilibrium concentration (mg/L)
Fig. 1

The adsorption isotherm (Langmuir model)
2.5

Zn/RRH
Cu/RRH
Cd/RRH

2

logW

1.5
1
0.5
0
-2

0
-0.5

Fig. 2
91

2

4

6

logC

The adsorption isotherm (Freundlich model)

SEE - Kyoto, Japan, Nov.18-20, 2020

the disposal of neutralized deposits generated during
the neutralization treatment and the security of thedisposal site for the deposits. Moreover, in recent
years, the metal demand increases by thedevelopment of IC chip and electric automobile. As
the simple treatment method to solve these problems,
the adsorption treatment is conducted utilizing theraw rice husks as an adsorbent with focusing on therice husk which is industrial waste. In this study, it isturned out the raw rice husks has the adsorption
performance of heavy metals (Zn, Cu and Cd)
contained in mine drainage. Additionally, it is foundthat it is possible to recover heavy metals from theraw rice husks adsorbed heavy metals by a nitric acid.
As the reuse method of the raw rice husks after theadsorption of heavy metals, in the future, thefollowing are examined: the reuse of raw rice husk
after heavy metal extraction as an adsorbent again or
as a concrete admixture by processing it into rice husk
ash as in [8].

amount of Zn and Cu in the second and subsequent
layers is less than the one of Cd in the first layer, since
the attractive force does not work between
adsorbent.in the adsorption of Zn and Cu.
Result Of The Extraction Test Of Heavy Metals
From The Raw Rice Husks To Which Heavy
Metals Are Adsorbed

Concentration in uRRH (ppm)Fig. 3 shows the concentrations of heavy metals
contained in raw rice husks before and after the
extraction tests with nitric acid solution. “before” and“after” indicate that the concentration of heavy metals
contained in the raw rice husks before and after the
extraction tests. The difference concentration
between “before” and “after” means the extracted
concentration of heavy metals, respectively. From Fig.
3, more than 90% of Zn, about 60% of Cu, and about
90% of Cd are extracted, which indicates that heavy
metals adsorbed on the raw rice husks can beextracted by nitric acid. This is considered to bebecause heavy metals adhering to the surface of
unprocessed rice husks were washed away bybleaching action of acid. The reason why there is thedifference in the extraction concentration by theheavy metal is mainly dependent on whether theadsorption mode is monolayer adsorption or not.
However, there is the difference in the extraction
concentration between Zn and Cu both of which have
similar adsorption mode. This is considered to be dueto the elution of trace element Zn as well as Zn
adsorbed on the raw rice husks.
6.000
5.000

4.774

ACNOWLEDGMENTS
This work was supported by Seeds Development
Research Fund (Emergence type) of Kagawa
University Research Promotion Program 2019
(KURPP) and Japan Society for Promotion of Science(JSPS), the Grants-in-Aid for Scientific Research(KAKENHI) (Grant number: 20K04684, 18J12343).
REFERENCES[1] Daigobo H., Nishikawa K., Mihara K., Inoue Y.
and Fujimoto H., Countermeasures for the Soil
Environmental Problems, Sumitomi Chemical,
Technical report 2003-1, 2003, pp. 13-23[2] Japan Oil Gas and Metals National Corporation(JOGMEC), The Principle of an acid minedrainage treatment, 2006, pp. 13-24[3] Sato D. and Tazaki K., Mineralization andHeavy Metal Interaction after Lime Treatmentof Mine Drainage, Journal of the Clay Science
Society of Japan, Vol. 40, No. 4, 2001, pp. 218228[4] Kobayashi S., Noda K., Shibata H., Matsubara
S., Kawamura N., Nonami T., Adsorption
Properties of Rice Hull Charcoal for Cesium andStrontium in Aqueous Solution, Journal of theSociety of Materials Science, Japan, Vol. 67, No.
10, 2018, pp. 898-903[5] Feng Q., Lin Q, Gong F., Sugita S. and Shoya
M., Adsorption of lead and mercury by rice husk
ash, Journal of Colloid and Interface Science,Vol. 278, No. 1, 2004, pp. 1-8[6] Srivastava C. V., Mall D. I. and Mishra M. I.,
Characterization of mesoporous rice husk ash(RHA) and adsorption kinetics of metal ionsaqueous solution onto RHA, Journal ofHazardous Materials, Vol. 134, No. 1-3, 2006,

before
after
4.813

4.269

4.000
3.000
1.940

2.000
1.000

0.447

0.279

0.000
Zn

Fig. 3Cu

Cd

The result of extraction test (by HNO3 aq)

CONCLUSIONSAs a current treatment method of mine drainage,
the neutralization treatment process is frequently
conducted utilizing alkali chemicals. However, few
alkali chemicals satisfy both low cost and neutralizing
ability. In addition, there are agendas such as thecomplication of the neutralization treatment process,92

SEE - Kyoto, Japan, Nov.18-20, 2020

Property of Concrete with Non-crushed Rice
Husk Ash, Concrete Research and Technology,
Vol. 28, 2017, pp. 1-13

pp. 257-267[7] Chikazawa M. and Tajima K., Interface
Chemistry, Maruzen Publication, 2001, pp. 108117[8] Kajiwara N., Uehara T. and Saito K.,
Fundamental Study of Fresh and Hardening

93

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STUDY ON REMOVAL OF CESIUM FROM CONTAMINATED SOIL
BY ELECTROPHORESIS USING POTASSIUM ACETATEAS ELECTROLYTE
Ayane Yanaka1, Keiichiro Shibata2, Naomichi Matsumoto3 and Hidenori Yoshida4
1

Graduate School of Engineering, Kagawa University, Japan; 2 Kajima Corporation, Japan, 3 Technical staff,
Kagawa University, Japan; 4 Faculty of Engineering and Design, Kagawa University, Japan
ABSTRACT

9 years have passed since a large amount of radioactive materials were diffused by the nuclear accident at the
Fukushima Daiichi Nuclear Power Station of Tokyo Electric Power Company. The decontamination works havealmost been completed, and some of the contaminated soil whose topsoil was stripped and collected wastransported to the intermediate storage and incineration facilities. However, the contaminated soil containing theradioactive cesium stored in the temporary storage place has not decreased significantly. Additionally, thetransportation of the intermediate storage and incineration facilities have an agenda from the viewpoint of cost.
Therefore, it is needed to investigate the method of decontamination by which the radiation dose of contaminatedsoil can be reduced below 8000 Bq/kg at the temporary storage place. Considering the decontamination in theactual temporary storage place, electrophoresis is the simple method as a decontamination method, and it isdesirable to utilize zeolite with ion-exchange property as an inexpensive adsorbent. Ammonium acetate has been
considered to be effective as an electrolyte because it has ammonium ion that has high ion-exchange reaction withcesium ion. However, an efficient decontamination cannot be achieved since the adsorption of cesium ions tozeolite is inhibited by ammonium ions. The purpose of this study is to discuss the efficient removal of cesium byusing zeolite as an adsorbent and potassium acetate as an electrolyte through the electrophoresis test. From the test
results, it is turned out that potassium acetate is suitable to extract cesium efficiently in electrophoresis.
Keywords: Radioactive materials, Cesium, Zeolite, Electrophoresis, Extraction

have been transported to the intermediate storage
facilities in Fukushima Prefecture successively since2015. However, the contaminated soil containing theradioactive cesium of about 6.67 million m3 remains
to be stored in the temporary storage place.
Furthermore, the contaminated soil transported to anintermediate storage facility is sorted through sieves,and incinerated at a high temperature above 800 ° C
or higher as in [3]. Therefore, it is expected that not
only the transportation cost of a large amount ofcontaminated soil but also the incineration cost will
be enormous. According to the basic policy by the
Ministry of the Environment, since it is shown thatthe contaminated soil with radiation dose below 8000
Bq/kg is reused as construction materials as in [4], thereuse of low dose of soil as construction materials can
reduce the volume of contaminated soil. To achieve
the volume reduction of the contaminated soil, it isdesired to reduce the dose to 8000 Bq/kg or less by
the partial removal of the radiation cesium for t thecontaminated soil exceeding 8000 Bq/kg at present. It
is necessary to remove only radioactive cesium
efficiently in order to reduce the dose of soil in theflexible container bag stored in the temporary storage
place. As one of the means for efficiently realizing theremoval of only the radioactive cesium, the techniqueusing the electrophoresis is mentioned as a candidate.

INTRODUCTION
The nuclear accident at the Fukushima Daiichi
Nuclear Power Station of Tokyo Electric Power
Company occurred due to the effect of the hugetsunami by the Great East Japan Earthquake, and alarge amount of radioactive materials were diffused
extensively widely around Fukushima Prefecture.
Most of the released radioactive materials wereradioactive cesium. Radioactive cesium has a long
half-life and affects over a long period of time as in[1]. Vermiculite is widely distributed in soils inFukushima Prefecture and has interlayers calledfrayed edge. Since radioactive cesium is selectively
fixed to the interlayers of mineral particles such asvermiculite, it is difficult to extract cesium which isonce fixed. Since most of the accumulated radioactive
cesium exists in the surface soil of the contaminatedsoil as in [2], the surface decontamination work has
been carried out by stripping the surface soil. The
contaminated soil collected by the stripping of the
topsoil is enclosed in a flexible container bag andtemporarily stored in the temporary storage place. At
present, 9 years have passed since the occurrence of
the accident, the decontamination works have almostb een co mp l eted. Ad ditionally, so me o f thecontaminated soil enclosed in flexible container bags
94

SEE - Kyoto, Japan, Nov.18-20, 2020

By using this method, cesium ions, which are cations,can be extracted from the soil using a solution which
also serves as an electrolyte and an extract, andtransferred to the cathode by electric force.
Ammonium or potassium salts are necessary for the
extraction of cesium ions in soil, and ammonium
acetate is known to have relatively higher extraction
performance than potassium acetate as in [5].
Therefore, ammonium acetate with ammonium ion
which has high ion exchange reactivity with cesium
ion seems to be effective as an electrolyte for theelectrophoresis. However, it is reported that theadsorption of cesium ions on zeolite is inhibited by
the presence of ammonium ions when zeolite is used
as an adsorbent as in [6]. Potassium acetate is slightly
inferior in the extraction performance, but from theviewpoint of the cesium adsorption ability of zeolite
and the volume reduction of contaminated soil
containing radioactive cesium, it is expected that thecesium adsorption capacity of zeolite can beincreased by using potassium acetate as an electrolyte
and extraction solution. The purpose of this study is
to discuss the efficient extraction and adsorption ofcesium by using zeolite as an adsorbent andpotassium acetate as an electrolyte through theelectrophoresis test.

occupy the six-membered ring because an abundanceof potassium ion in the soil is overwhelmingly large(see Fig. 1). Potassium ions are released by the fray atthe end of the layer in clay minerals accompanied bysoil weathering (see Fig. 2). As a result, a region inwhich other cations can penetrate is formed. This iscalled frayed edges. It is difficult that cesium ion
fixed in the frayed edge is displaced by other cations
as in [8].

Fig. 1 The 2: 1 layered silicate

THE BEHAVIOR OF CESIUM IN SOIL
Cesium exists as monovalent cation in soil and isadsorbed to the soil particles which carry a negative
charge in soil. Cesium selectively adheres to soil
composed of clay minerals mainly of 2: 1 type layered
silicate among the minerals constituting clay minerals.
The 2: 1 type layered silicate is a generic name ofminerals having a 2: 1 relationship between thelamination of silicon tetrahedral sheets and thelamination of aluminum octahedral sheets. A silicontetrahedron sheet is a tetrahedron formed bysurrounding silicon atoms with four oxygen atoms,
and an aluminum octahedron sheet is a tetrahedron
formed by surrounding aluminum atoms with six
oxygen atoms in two dimensions. In a silicontetrahedral sheet or an aluminum octahedral sheet,when some silicon or aluminum elements are
replaced by other elements having a small amount of
positive charge, the amount of positive charge is not
sufficient in either sheet or both sheets as in [7]. After
that, negative charge appears due to lack of positive
charge, and the interlayers are neutralized by theadsorption of cations. The interlayer charge showshigh adsorption selectivity for cesium ions. This isbecause the size of the cavity called six-memberedring formed by oxygen atom on the basal surface of asilicon tetrahedral sheet is approximately equal to theionic radius of cesium ions. As the hydration energy
decreases, the binding force to the six-membered ringincreases, and in particular, the cesium ion has thehighest binding force. However, potassium ionsFig. 2 Frayed edge
TEST METHODElectrophoresis
In the electrolyte used in electrophoresis, charged
particles in the solvent move under the electric field
generated by the application. In the electric field,
cations and anions transfer to the cathode side and theanode side, respectively. Cesium ions, which arecations, are transferred to the cathode side by utilizing
the electrophoretic phenomenon, and the transferredcesium ions are adsorbed on zeolite which is placed
between the soil and the cathode.
95

SEE - Kyoto, Japan, Nov.18-20, 2020

acrylic container bag to maintain the lowest possible
voltage during the test. After energization, using
potassium acetate solution as an extraction cleaning
solution, the soil is stirred and washed by using astirring device. Moreover, the concentration ofcesium contained in the filtered and separated
solution is analyzed by an atomic absorption
spectrometer. The extraction ratio is defined by thefollowing equation (1).

Electrophoresis test
Electrophoresis test is conducted using potassium
acetate aqueous as an electrolyte and extraction
solution. Electrolyte and extract solutions areprepared at three different concentrations (1.0%,
1.5%, 3.0%). Electrophoretic tests are carried out at
each concentration, and the amount of Cesium
remaining in the soil is measured. According to theobtained results, the extraction and adsorption at eachconcentration are discussed. As a test equipment, asimulated flexible container bag is prepared (seePhoto. 1). First, a simulated contaminated soil isprepared. 114g of standard sand and 6g of vermiculite
are mixed, and 36mL of pure water is poured into themixed sand in order to adjust the 30% of moisture
content. 1 mL of cesium chloride solution is added tothe soil, and the test sample is cured for 168 hours.
Next, the simulated soil is put into an acrylic
container bag, a carbon rod to (15mm of diameter,
40mm of length) as an anode is placed
perpendicularly to the center of the soil. In this stage,a 35 μm opening bolting cloth is laid on the inside of
the acrylic container bag, and then a simulated
contaminated soil is put there so as to prevent mixing
with zeolite and the test sample. In addition, 60 - 70
mL of potassium acetate solution, which is anelectrolyte solution, is put into the acrylic container
bag, and the simulated contaminated soil is immersedin the electrolyte. An aluminum plate as a cathode isplaced so as to surround the simulated contaminatedsoil, and 10g of zeolite is installed between thebolting cloth and the aluminum plate. In theelectrophoresis test, a constant current of 50 mA is
applied for 48 hours with a voltage value of 40 V as
an upper limit. In conducting electrophoretic tests,
potassium acetate solution is sequentially put into theExtraction ratio (%)
Extracted amount (mg)=
Added amount (mg)
× 100

(1)

In order to ensure reproducibility, the average
results obtained from the tests conducted three times
are adopted as test results.
RESULT OF ELECTROPHORESIS TEST
Fig. 3 shows the extraction rate of cesium undervarious concentrations of potassium acetate solution.
The horizontal and vertical axes are the concentrationof potassium acetate solution and the extraction
ratio of cesium, respectively. The difference between
the extraction rate of cesium with zeolite and thatwithout zeolite is interpreted as the adsorption rate ofcesium adsorbed on zeolite. Fig. 3 suggests that theextraction ratio of cesium from the soil increases as
the concentration of potassium acetate solution
decreases. It is also found that the highest
concentration of 3.0% potassium acetate solution
results in the lowest rate of cesium extraction fromthe soil. In the electrophoresis, due to the electrolysis
reaction of water with the application of voltage,hydrogen ions and hydroxide ions are generated at an
anode and a cathode, respectively as in [9]. Therefore,
the solution near an anode and a cathode indicates
acidity and basicity, respectively. In the case of thehighest concentration of potassium acetate solution(3.0%), the pH of the solution near an aluminum plate
as a cathode indicates a high value (pH over 10). For
aluminum, corrosion occurs at pH outside the rangeof 4 to 8. In the case of the high concentration ofpotassium acetate solution, it is considered that theelectrophoresis is inhibited by the corrosion of analuminum plate, and as a result, the extraction ratio of
cesium decreases. Judging comprehensively from theextraction and adsorption ratios of cesium, it is foundthat potassium acetate has the highest performancefor extraction and ion transport at the lowest
concentration of 1.0% of potassium acetate solution.
The concentration of potassium acetate solution as theelectrolyte becomes lower, as the voltage is increased.
Then, the potassium acetate solution is sequentially
put into the acrylic container bag from the viewpoint

Photo. 1 A simulated flexible container bag(test equipment)
96

SEE - Kyoto, Japan, Nov.18-20, 202050

potassium acetate solution show neutrality andweakly basicity, respectively. When the pH falls
below the zero charge point, it is possible that theelectroosmotic flow reverses due to the changes of thesurface electric charge of the soil from a negative
charge to a positive one as in [10]. It is consideredthat the flow of cesium ions to a cathode is inhibitedby the back run of the electroosmotic flow because
the pH of the ammonium acetate solution is less thanthat of the potassium acetate solution. It seems thatthe pH of an electrolyte and extraction solutions
affects the extraction ratio of cesium.

No zeolite
Use zeolite

40
30Extraction ratio of Cs (%)

Extraction ratio of Cs (%)

of ensuring the safety. A lot of potassium ions are
required to extract cesium ions. It is considered thatthe potassium ions necessary for the extraction ofcesium can be supplied more efficiently by
sequentially adding a low concentration of potassium
acetate solution as an extraction and electrolyte forthe electrophoresis than by using a high concentrationof potassium acetate solution.

20
10
0
1.0

1.5

3.0

Potassium acetate aq (%)

Fig. 3 The extraction ratio of cesium by potassium
acetate solution

50

No zeolite
Use zeolite

40
30
20
10
0
1.0

1.5

3.0

4.5

Ammonium acetate aq (%)

Incidentally, it is generally known ammonium
acetate has a higher extraction capacity thanpotassium acetate in order to extract cesium fixed toclay minerals. For the reason, in regard to theextraction from the soil and the adsorption on zeolite,
the result of the electrophoresis test utilizing
ammonium acetate as extraction solutions andelectrolytes is compared to that utilized potassium
acetate as extraction solutions and electrolytes. Fig. 4
shows the extraction ratio cesium under various
concentrations of ammonium acetate solution. Fig. 4
shows The horizontal and vertical axes are theconcentration of ammonium acetate solution, and theextraction ratio of cesium. As with Fig. 3, thedifference between the extraction rate of cesium withzeolite and that without zeolite is interpreted as theadsorption rate of cesium adsorbed on zeolite. In theelectrophoretic test using ammonium acetate solution
as an extraction and electrolyte solution, not only abolting cloth but also a filter paper is laid on the insideof an acrylic container bag to prevent mixing ofzeolite and the specimen. Then, the simulated
contaminated soil is put into the acrylic container bag.
Except this condition, all the conditions for theelectrophoretic test using ammonium acetate solution
as an extraction and electrolyte solution are the sameas those for the electrophoretic test using potassium
acetate solution as an extraction and electrolyte
solution. As compared to Fig. 3 with Fig. 4, whether
or not filter paper is used, it is indicated that theadsorption ratio of cesium by a potassium acetate
solution is more than that by an ammonium acetate
solution in the lowest concentration of the electrolyte
and extraction solution (1.0%). Ammonium andFig. 4 The extraction ratio of cesium by ammonium
acetate solution
CONCLUSION
9 years have passed since a large amount ofradioactive materials were diffused due to theaccident at the Fukushima Daiichi Nuclear Power
Station of Tokyo Electric Power Company. At
present, the decontamination work by stripping of the
topsoil soil has almost been completed. However, alarge amount of the contaminated soil containing theradioactive cesium remains to be stored in thetemporary storage place. Considering the agendas oftransportation to an intermediate storage facility anddisposal in an incineration facility, it is desirable toreuse materials that can be used as construction
materials instead of bringing all contaminated soil in
an intermediate storage facility into an incineration
facility. It is desirable to remove only radioactive
cesium efficiently in the flexible container bag inorder to reduce the dose of contaminated soil in a
flexible container bag stored in a temporary storage
place by decontamination below 8000 Bq/kg. As oneof the methods which efficiently realize the removalof only the radioactive cesium, the technique using
the electrophoresis is employed. Adsorption to zeolite
is inhibited by the presence of ammonium ion when
an electrophoretic test is conducted using ammonium
acetate as an electrolyte and extract solution andzeolite as an adsorbent. Therefore, the electrophoretic
tests are conducted by changing the electrolyte andextract solution from ammonium acetate to potassium
97

SEE - Kyoto, Japan, Nov.18-20, 2020

Environmental Technology Research Institute
Report, No. 34, 2015, pp. 29-32[6] Igawa M., Doi R., Ikai Y. and Matsuno C.,
Volume reduction of decontaminated waste
using electrophoresis and cesium ion adsorbent,
The 8th Workshop of Remediation ofRadioactive Contamination in Environment, S81, 2019, p. 40[7] Nakano A.: Cesium Adsorption and Fixation on
Soils, Trends in the Sciences, Vol. 17, No. 10,
2012, pp. 40-45[8] Yamaguchi N.: Adsorption mechanism ofradiocesium on soil, Journal of the JapaneseSociety of Soil Physics, No. 126, 2014, pp. 1121
[9] Tanaka S. and Akemoto Y.: Soil and related
interfacial electric phenomena. 6. Remediationof contaminated soil by electrokinetic process,Japanese Journal of Soil Science and Plant
Nutrition, Vol. 86, No. 1, 2015, pp. 48-53[10] Miura T., Kabir M., Suzuki M., Nakajima S. andMori S.: Effect of Organic Acids on Cesium
Removal from Contaminated Soil by
Electrokinetic Remediation, Journal of theInstitute of Electrostatics Japan, Vol. 40, No. 1,
2016, pp. 14-19

acetate. In this study, it is demonstrated that cesium
can be removed efficiently by the low concentrationof the potassium acetate solution in electrophoresis. It
is necessary to clarify the relationship between the pHof the contaminated soil and the extraction ratio of
cesium in the future.
ACNOWLEDGMENT
This work was supported by Seeds Development
Research Fund (Emergence type) of Kagawa
University Research Promotion Program 2019
(KURPP) and Japan Society for Promotion of Science(JSPS), the Grants-in-Aid for Scientific Research(KAKENHI) (Grant number: 20K04684, 18J12343).
REFERENCES[1] Ministry of the Environment: Unified basic dataon health effects from radiation, 2019, p. 11[2] Kato H., Onda Y. and Teramage M.: Depth
distribution of 137Cs, 134Cs, and 131I in soil
profile after Fukushima Dai-ichi Nuclear Power
Plant Accident, Journal of Environmental
Radioactivity, Vol. 111, 2012, pp. 59-64[3] National Institute for Environmental Studies,
Proper treatment of wastes contaminated byradioactive materials, 2014, pp. 1-20
[4] Ministry of the Environment: Policy for disposalof disaster waste in Fukushima Prefecture, 2011,
pp. 1-13[5] Yamaguchi N., Eguchi S., Ikeba M., Fujiwara E.,
Makino T. and Taniyama I.: Radiocesium
extraction from arable soils at the initial stage
after deposition of radionuclides, Agricultural98

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EFFECT OF WATER HYACINTH FIBER ON STRENGTH AND
DURABILITY OF ADOBE BRICKS
1

Chotikan Ratchakrom1, Pisut Rodvinij2
Faculty of Industrial Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage,
Thailand; 2Faculty of Engineering, Rajamangala University of Technology Lanna, Thailand

ABSTRACTThis study focused on the development of the strength and durability of adobe bricks by used water hyacinth
as fiber reinforcement. The mixture of adobe bricks was a combination of clay and sand in the ratio of 1:1. Cement
at 5% added in the mixture of adobe bricks. Water hyacinth at the length of 3 cm, 5 cm, and 7 cm was mixed withsoil samples at 0.5% by weight. The results demonstrated that the adobe bricks reinforced with water hyacinth
reduced the shrinkage approximately 31-34%. Moreover, the flexural strength of adobe bricks reinforced withwater hyacinth can reach 61-74% of the compressive strength. While the flexural strength of non-reinforced adobe
bricks can reach only 17% of the compressive strength. The results presented that the alteration in the length ofwater hyacinth slightly affected the strength of adobe bricks. Moreover, the addition of water hyacinth in the adobe
bricks can decrease the unit weight by approximately 20%. However, the compressive strength of adobe bricks
reinforced with water hyacinth decreased by approximately 35-42%. The compressive strength tended to decrease
with the reduction in the unit weight of adobe bricks. The results of the capillary rise test demonstrated that nonreinforced samples broke down after soaked in the water for 24 hours. However, water hyacinth fiber can maintainthe characteristic of adobe bricks. Therefore, water hyacinth fiber can use as reinforcement materials to increase
the flexural strength, durability, and reduce the shrinkage of adobe bricks.
Keywords: Water Hyacinth, Fiber Reinforcement, Flexural Strength, Durability[8], [9]. Thus, this paper investigated the effect ofwater hyacinth fiber on the volume change, strength,and durability of adobe bricks.
Water hyacinth is a free-floating perennial plant.
The water hyacinth plant is easily spread over thewater. It grows over a variety of wetland types fromlakes, ponds, streams, ditches, waterways, and black
water areas. The plant height may vary from few
inches. It may rise above the water surface as muchas 1 meter in height. The leaves are 10-20 cm indiameter which float above the water surface. The
plant can produce thousands of seeds each year andthese seeds can remain viable for more than 28 years.
The common water hyacinth is double its populationin two weeks [10]. Thailand is facing serious waterpollution problems, especially in natural water
sources such as rivers and canals. One of the main
reasons is the widespread water hyacinth plant. Since
it can grow and reproduce very fast, it covers thewater surface in natural water sources. This prevents
oxygen from penetrating and dissolving into thewater. A water source can be considered polluted
when the dissolved oxygen in the water is lower thana standard limit [11]. Therefore, the utilization ofwater hyacinth as construction materials can be analternative to reduce the environmental problem inThailand. Moreover, the improvement of adobe brickcan increase durability, and reduce unit weight. The
use of water hyacinth may reduce the unit weight ofadobe bricks more than the other type of natural

INTRODUCTION
Adobe, Earth building is the oldest building
material. It is most commonly used in the current.
Nearly 30% of the total population of the world still
resides in a mud house [1], [2]. Brick is the mostcommonly used building. Adobe (sun-dried) bricks
were used in ancient times during the Sumerian andHarappan civilizations. The utilization of the adobe
as a building material in the construction industry is
an alternative [3]. Sun-dried adobe bricks are simply
made with low energy consumption and locallyavailable materials such as cohesive soil and straw[4]. The properties of bricks depend upon soil
selection and the process of brick making to obtain
the desired strength. The suitable soil required formaking adobe brick should contain adequate clay,
silt, and sand. The soil is mixed with the water until
plastic consistency is obtained. Mainly the adobe
construction is vulnerable to water absorption [5].
Some of the problems of the adobe construction are
erosion of earth walls, shrinkage, cracking, andfrequent maintenance of the structure [3].
Therefore, this study focused on the improvementof the mixture of adobe bricks by ordinary Portland
cement and water hyacinth fiber. Literature reviews
demonstrated that brick reinforced with natural fibers
are feasible to be used as a building material. The
presence of fibers in brick reduces brick density andshrinkage, prevents deformation and crack [6], [7],99SEE - Kyoto, Japan, Nov.18-20, 2020

fibers. This is because of the high pores in water
hyacinths. Therefore, this can result in increased useof adobe brick in house construction.

MixtureClay:
CementLength
Code
Sand
(%)
of Fiber
S1
1:1
0
S1C
1:1
5
S1CW3
1:1
5
3
S1CW5
1:1
5
5
S1CW7
1:1
5
7
Note: Water at liquid limit of the soil samples wasused in the mixing procedure.

MATERIALS PREPARATION
Normally, a combination of clay and sand wasused as adobe bricks materials. Clay soils from
Pathum Thani Province, Thailand were used in thisstudy. The consistency limit of clay samples includes
a liquid limit, plastic limit, and shrinkage limit wasinvestigated. The liquid limit was 45.0%, the plastic
limit was 27.7%, the shrinkage limit was 12.6%, andthe plastic index was 17.3%. The soil was classified
as low plasticity clay, according to the Unified Soil
Classification System (USCS). Fine sand collectedfrom the river. Dried sand passed sieve #10 was usedin this test. The soil samples for build up the adobe
bricks were a combination of clay and fine sand in aratio of 1:1. Atterberg’s limit value of the soil samples
reduced from clay. Liquid limit, plastic limit, plastic
index, and shrinkage limit of the soil samples was
21.1%, 10.8%, 10.3%, and 8.8%, respectively.
Moreover, Portland cement type 1 used as a
cementitious material. Portland cement was mixed
with the soil samples at 5% by weight.
This study focused on the use of water hyacinth asfiber reinforcement in the adobe bricks. The water
hyacinth fiber was dried in the air for 2 weeks before
mixed with the soil samples, as shown in Fig. 1. The
effect of water hyacinth on the volume change, thecompressive strength, the flexural strength, and the
durability of adobe bricks have been investigated.
Water hyacinth at the length of 3 cm, 5 cm, and 7 cm
was mixed with the soil samples at 0.5% by weight.
Table 1 shows the mixture of adobe bricks reinforced
with water hyacinth in this study.

MECHANICAL PROPERTIES OF ADOBEBRICKS
The compressive strength, flexural strength, anddurability of adobe bricks reinforced with water
hyacinth have investigated by the unconfinedcompressive strength tests, flexural strength tests, andcapillary rise tests, respectively.
Compressive Strength Tests
The soil samples mixed with water, cement, andwater hyacinth, according to Table 1 were used in thetest. The samples were compacted in the mold at
10×10×10 cm, as shown in Fig. 2. After the samples
dried in the air for 1 day, the samples were extruded
from the mold and curing in the dried air for 14 days.
Then the samples were conducted on an unconfinedcompressive strength test. The compressive strength
values for each mixture are the average of fivespecimens.

Fig. 2 The samples prepared for unconfinedcompressive strength tests.
Flexural Strength Tests
The soil samples mixed with water, cement, andwater hyacinth according to Table 1 were used in thistest. The samples were compacted in the mold at
4×4×16 cm. After the samples dried in the air for 1day, the samples were extruded from the mold andcuring in the dried air for 14 days. The simple beam

Fig. 1 Water hyacinth fiber dried in the air.
Table 1 Mixture of adobe bricks
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SEE - Kyoto, Japan, Nov.18-20, 2020

with center-point loading was used in the test, asshown in Fig. 3. Turn the test specimen on its side
concerning its position as molded and center it on the
support blocks. Center the loading system to theapplied force. Bring the load-applying block incontact with the surface of the specimen at the center.
The load shall be applied at the constant rate to thebreaking point (ASTM, C293). The flexural strength
values for each mixture are the average of three
specimens.

Volume Change and Density
The volume change was investigated bymeasuring the width, length, and height of specimens
by Vernier Caliper at the curing time of 1, 3, 7, 14,
and 21 days, as shown in Fig. 5. The volume changeof adobe bricks for each mixture is shown in Fig. 6.
The initial volume of the specimens was 1,000 cm3.
The results demonstrated that the volume of
specimens tends to decrease with rising time. The
results showed the volume of the sample S1 rapidly
decreased in 3 days followed by slightly decreased.
The remaining volume of S1 was 721 cm3 at 21 days.
The reduction in the volume of S1 was approximately
28%. However, the addition cement at 5% in the
mixture can reduce the shrinkage of the specimens, as
shown in the results of S1C. The volume of S1C
decreased by only 13% by the remaining volume of
S1C was 872 cm3. Moreover, the volume of thesamples mixed with cement and reinforced by water
hyacinth decreased by approximately 5-7%. The
volume of S1CW3, S1CW5, and S1CW7 was 934
cm3, 951 cm3, and 926 cm3, respectively at the curing
time of 21 days. Therefore, the results demonstrated
that the water hyacinth reinforced in the bricks can
reduce the shrinkage of adobe bricks. Moreover, theresults illustrated that the length of water hyacinth
slightly affected the shrinkage of adobe bricks.

Fig. 3 Flexural strength test of the specimen.
CAPILLARY RISE AND DURABILITY TESTSThe soil samples mixed with water, cement, andwater hyacinth according to Table 1 were used in thistest. Capillary rise and durability cube specimens,
10×10×10 cm was compacted in the mold and curedin the dried air for 14 days in the same condition as
unconfined compressive strength specimens. Three
specimens were prepared for each mixture. After the
curing process, the specimens were placed in a tray
with water level maintained at 10 mm and room
temperature of 25±2 °C [12], as shown in Fig. 4. The
average level of rising water measured from the baseof the specimens.

Fig. 5 The specimen volume measurement.
1100
S1

S1C

S1CW5

S1CW7

S1CW3

1050
1000

Volume (cm3)

950
900
850
800
750

Fig. 4 The specimens conducted on capillary rise
tests.

700
650
600
0

In order to investigate the durability of adobe
bricks reinforced by water hyacinth, the specimens
through the capillary rise tests at 7 days wereconducted on unconfined compressive strength tests.
The results can demonstrate the reduction in thecompressive strength of adobe bricks due to theincreased moisture.
RESULTS AND DISCUSSION

5

10

15

20

Period of time (days)

Fig. 6 Relation between volume change and period oftime.
Consideration of the density of the specimens foreach mixture, the density of the specimens tended todecrease with the rising time, as shown in Fig. 7. The
results demonstrated that the density of S1 was higher
101

SEE - Kyoto, Japan, Nov.18-20, 2020

than S1C approximately 13-17%. Moreover, thespecimens reinforced with water hyacinth can reducethe density of approximately 5-11% from S1C. The
density of the specimens reinforced with water
hyacinth was between 1,422-1,452 kg/m3 at thecuring time of 21 days. The results illustrated that thechanging length of water hyacinth was not affecting
the density of adobe bricks, as shown in Fig. 7. The
density of the reinforcement samples reduced 19-23%
from S1.
2000

S1

S1CW3

S1CW5

S1CW7

S1C
Density (kg/m3 )

1900
1800
1700
1600
1500
1400
1

6

11

16

21

Period of time (days)

Fig. 7 The relation between density of adobe bricks
and period of time.
The low density of the reinforcement samples canbe described by the relation between the alteration involume and weight of the sample for each mixture, as
shown in Fig. 8. It shows the results of the samples atthe curing time of 21 days. The results illustrated thatthe weight of the sample for each mixture slightly
different, as shown the weight was between 1.31-1.38
kg. However, the volume of S1and S1C less than
S1Cw3, S1CW5, and S1CW7 due to the highshrinkage of the samples. Therefore, this result shows
the water hyacinth fiber can assist to maintain thevolume of adobe bricks. This induced the density of
the reinforcement specimens less than the specimens
without reinforcement.
Weight1.5

16Compressive strength (ksc)14

Volume (cm3)Weight (kg)

2.91

3.05

3.25

900
700
500

S1C

S1CW3

S1CW5

S1CW7

The flexural strength of the samples for each
mixture is shown in Fig. 10. The results demonstrated
that the flexural strength of the samples for each
mixture slightly different. The flexural strength of S1,
S1C, S1CW3, S1CW5, and S1CW7 was 2.3 ksc, 2.3
ksc, 2.2 ksc, 2.0 ksc, and 2.0 ksc, respectively. The
results illustrated that the flexural strength of S1
extremely decreased from the compressive strength.
The flexural strength can reach only 17% of thecompressive strength. However, the addition of
cement at 5% can enhance the flexural strength of thesamples. The flexural strength of S1C can reach 46%
of compressive strength. Moreover, the flexural

500
S1CW5

1100

4.97

Flexural Strength

600

S1CW3

6

Fig. 9 Relation between compressive strength anddensity of the samples for each mixture.

700

S1C

1300

8

S1

0.5

S1

1500

10

0

900

0

1700

Density

12

2

1000

800

Compressive strength4Volume

1

1900

13.68

Density (kg/cm3)

2100

The compressive strength of the specimens foreach mixture is shown in Fig. 9. The results
demonstrated that S1 gave the highest strength. The
compressive strength of S1 was 13.68 ksc. However,
the addition of cement at 5% in the soil samples
decreased the compressive strength by approximately
64% from S1. The compressive strength of S1C was
4.97 ksc. Moreover, the specimens reinforced bywater hyacinth have the lowest compressive strength.
The compressive strength of S1CW3, S1CW5, andS1CW7 was 2.91 ksc, 3.05 ksc, and 3.25 ksc,
respectively. The results illustrated that thecompressive strength of the samples reinforced bywater hyacinth tended to increase with the additional
length of the fiber.
The reduction in the compressive strength can
describe by the density of the samples for each
mixture. The results illustrated that the compressive
strength tended to decrease with the reduction indensity. This phenomenon causes the shrinkage of thesamples. The high shrinkage of S1 induced the highdensity and low porosity of the specimen. However,the samples S1C, S1CW3, S1CW5, and S1CW7
shrink less than S1. This induced low density andhigh porosity. Therefore, the high porosity is thecauses of the compressive strength of S1CW3,
S1CW5, and S1CW7 decreased 35-42% from S1C.

S1CW7

Fig. 8 Relation between the alteration in weight andvolume of the specimens for each mixture.
Compressive Strength
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SEE - Kyoto, Japan, Nov.18-20, 2020

strength of the samples reinforced with water
hyacinth can reach 61-74% of the compressive
strength. Therefore, the results illustrated thereinforcement of water hyacinth can enhance theflexural of adobe bricks approximately 15-28% fromthe non-reinforced adobe bricks.
15

Density (kg/m3)

2000

1500

1427.00

1768.421766.371470.00

1450.00

Before Test

1000

After Test

500

13.68
Flexural strength0Compressive strength
Strength (ksc)1790.13

S1CW3

S1CW5

S1CW7

10

Fig. 12 Density of the reinforced samples after 7 daysof capillary rise tests.

4.97

5
2.3

2.91

2.3

2.2

S1C

S1CW3

2.0

3.25

3.05

The samples S1C3, S1CW5, and S1CW7 after
through the capillary rise tests were conducted on theunconfined compressive tests to investigate thedurability of adobe bricks. The results of the
durability test are shown in Fig. 13. The compressive
strength of S1CW3, S1CW5, and S1CW7 after
soaked in the water for 7 days was 1.03 ksc, 1.08 ksc,
and 1.09 ksc, respectively. The compressive strength
decreased approximately 65% from the dry samples.
However, the samples S1 cannot conduct on theunconfined compressive strength tests due to thesamples broke down after soaking in the water for 24hours. Therefore, the results of capillary rise tests andunconfined compressive strength tests demonstrated
the water hyacinth fiber can increase the durability of
adobe bricks.

2.0

0
S1

S1CW5

S1CW7

Fig. 10 Flexural strength of the samples for each
mixture.
Capillary Rise and Durability
The results of capillary rise tests demonstrated
that the samples S1 heavily of capillary rise after 24hours. S1 samples broke down, as shown in Fig. 11.
This is due to the high amount of clay in the soil
samples. Therefore, it induced high water pressure in
the samples and broke down the samples. However,the samples mixed with cement at 5% and reinforced
by water hyacinth can maintain the characteristics ofthe specimens during soaked in the water for 7 days.

Compressive strength (ksc)

4.5
4
3.5
3

3.25

3.05

2.91

Unsoaked
Soaked

2.5
2
1.5

1.03

1.08

1.09

S1CW3

S1CW5

S1CW7

1
0.5
0

Fig. 13 Compressive strength of the reinforced
specimens after soaked in the water.
Fig. 11 The samples without reinforcement after
soaked in the water for 24 hours.

CONCLUSIONS

Moreover, the results illustrated that the density of
S1CW3, S1CW5, and S1CW7 tended to increase
after soaked in the water for 7 days, as shown in Fig.
12. The density of S1CW3, S1CW5, S1CW7 after
soaked in the water for 7 days increased
approximately 20-25%.

Based on the results obtained from this study, thefollowing conclusion was made:1. Water hyacinth can reduce the drying shrinkageof adobe bricks approximately 31-34%, and decrease
the density of adobe bricks approximately 20%.
2. The compressive strength of adobe bricks
reinforced with water hyacinth decreased byapproximately 35-42% from the non-reinforced
bricks.
103

SEE - Kyoto, Japan, Nov.18-20, 2020

3. The flexural strength of adobe bricks reinforced
with water hyacinth can reach 61-74% of thecompressive strength. However, the flexural strengthof non-reinforced adobe bricks can reach only 17% of
the compressive strength.
4. The non-reinforced adobe bricks broke down
after soaking in the water for 24 hours. However,water hyacinth fiber can maintain the characteristic ofadobe bricks.
5. Water hyacinth fiber can increase the flexuralstrength, durability, and reduce the shrinkage ofadobe bricks.

[6] Binichi, H., Aksogan, O., and Shah, T.,
Investigation of Fibre Reinforced Mud Brick as A
Building Material., Construction and Building
Materials, Vol. 19, 2005, 313-318.
[7] Ananth, C., A Brief Outline on Microwave
Semiconductor Devices, RF & Microwave
Engineering Book 4, Kindle Edition, Vol. 11,
2017, 129-192.
[8] Ghavami, K., Filho, R, D, T., and Barbosac, N, P.,
Behavior of Composite Soil, Reinforced with
Natural Fibres, Cement and Concrete Composites,
Vol. 21, 1999, 39-48.
[9] Ngowi, A, B., Improving the international Earth
Construction: A Case of Botswana, Construction
and Building Materials, Vol. 11, 1997, 1-7.
[10] Punitha, S., Sangeetha, K., and Bhuvaneshwari,
M., Processing of Water Hyacinth Fiber to
Improve Its Absorbency, International Journal ofAdvanced Research, Vol. 3, Issue 8, 2015, 290294.
[11] Potiyaraj, P., Panchaipech., and Chuayjuljt, S.,
Using Water-Hyacinth Fiber as Filler in Natural
Rubber, Journal of Scientific Research
Chulalongkorn University, Vol. 26, No.1, 2001,
12-19.
[12] Ferdrigo, W., Nunez, W, P., Kleinert, T, R.,
Matuella, M, F., and Ceratti, J, A, P., Strength,
Shrinkage, Erodibility, and Capillary Flow
Characteristics of Cement-Treated Recycled
Pavement Materials, International Journal ofPavement Research and Technology, 10, 2017,393-402.

REFERENCES[1] Detheir, J., Des Architectures De Terre, Edition
De Centre Pompidou, 1986, Paris.
[2] Coffman, R., Agnew, N., Auiston, G., Doehne, E.,
Adobe Mineralogy: Characterization of The
Conservation of Adobes from Around The World,
6th International Conference on The Conservationof Earthen Architectures, Las Cruces, NM, 1990,
14-19.
[3] Prakash, V., Raj, A., Aravind, S., Mathew, B., andSumith, V. R., Studies on Stabilized Mud Blockas A Construction Material, International Journalof Innovative Research in Advanced Engineering,Vol. 3, No. 1, 2016, 19-24.
[4] Banjonkliang, E., Capability of Rain Washing
Resistance Improvement of External Rubber-Clay
Plaster for Adobe Walls, Doctor Thesis, Chiang
Mai University, 2015.
[5] Monika,
H.,
andUnnikrishnan,
S.,
Characterisation of Jute Fibre Reinforced Adobe
Brick and Brick Masonry, International Journal ofAdvanced Research Trends in Engineering andTechnology, Vol. 4, Issue 22, 2017, 16-21.

104

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

A NEW TYPE OF ACTUATOR FOR APPEARANCE INSPECTION OF
IRON STRUCTURE
1Hiroyuki Yaguchi1
Faculty of Engineering, Tohoku Gakuin University, Japan

ABSTRACTDue to economic development, many types of social infrastructure, such as various large structures, arebeing constructed around the world. Inspection and maintenance of social infrastructure, such as large bridges
and tanks, are extremely important. In the present study, a new vibration actuator that extends the principle ofoperation proposed by the authors was proposed and tested. The experimental results indicate that reciprocating
motion can be realized by controlling the phase of the vibration displacement of two vibration components.
Experimental results reveal that this vibration actuator was able to pull a load mass of 190 g and that the
maximum efficiency of the actuator was approximately 12.5% for the own-weight case. The actuator was
confirmed to be able to easily control the direction of movement with a two-channel function generator and apower amplifier.
Keywords: vibration, actuator, phase difference, electromagnetic force, inertial force.
limited to one direction.
In the present study, a new vibration actuatorthat extends the principle of operation is proposed.
The vibration actuator, in which two vibration
components with the same specifications arearranged orthogonally, was prototyped. The
experimental results indicate that reciprocating
motion can be realized by controlling the phase of
the vibration displacement of the two vibration
components. It was confirmed through actualmachine tests that the maximum propulsion force forthis actuator was 1.9 N and the maximum efficiency
was approximately 12.5%. In addition, the vibration
actuator was found to be able to easily control the
direction of movement with a two-channel function
generator and a power amplifier.

INTRODUCTION
Due to economic development, many types ofsocial infrastructure, such as various large structures,are being constructed around the world. The safetyof large structures constructed in recent years is
ensured by design standards. On the other hand,older social infrastructure can collapse because of
low design standards. In addition, the number ofendangered structures has increased due to damage
and deterioration as a result of aging. For this reason,
inspection and maintenance of social infrastructure,such as large bridges and tanks, is extremely
important. However, inspection of such structures isvery difficult due to site conditions. For this reason,
inspection robots have been developed in order toensure worker safety and reduce costs.
Robots with various movement principles havebeen proposed for the inspection of structures.
Previously proposed operating principles are as
follows: a permanent magnetic adhesion system
coupled with a tracked locomotion mechanism [1],the adhesive force of a suction cup manufactured
from a sponge [2] or flexible rubber [3-5], control of
the attractive force of an electromagnet inserted
therein [6], a permanent magnet and an iron wheel[7, 8], negative pressure generated by a pump [9],the wind force produced by a propeller [10],vibration of the many caps of a sucker to obtain
mobile power [11], a claw gripper [12,13], andadhesive materials [14].
In such mobile robots, the moving speed is low
as a result of the problem of controllability and theincrease in the weight of the actuator due to its
complex structure. The authors previously proposeda lightweight actuator with excellent operability[15]. However, movement of this actuator was

STEUCTURE OF THE VIBRATIONACTUATOR OPERATING INERTIA FORCE
Fig.1 shows a vibration actuator capable ofmovement on a magnetic substance proposed by theauthors. This vibration actuator is composed of a
Vibration

Cylindical
permanent
magnetN
S

Electromagnet
Iron core

Vibration
component

Springα
Rubberpermanent
magnetN
S

Triangular
frame
Attractive
force(a) Front view

Magnetic
substance

Attractive
force(b) Side viewFig. 1. Structure of the vibration actuator.
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SEE - Kyoto, Japan, Nov.18-20, 2020

Frictional
force

Attractive force F(a) Sliding(b) No sliding

Fig. 2. Principle of locomotion.
permanent magnet, a coil spring, an electromagnet, atriangular acrylic frame, and a rubber permanent
magnet. When the diagonally mounted vibration
component is excited by the electromagnet, an
inertial force is generated in the diagonal direction.
The angle α of the vibration component was set to
60 degrees based on the results obtained in aprevious study [15]. The attractive force generated
by the rubber magnet attached at the support partacts on the vibration actuator when it is placed on amagnetic substance, as shown in Fig. 2. The
frictional force between the rubber magnet and themagnetic substance alternates periodically during
one cycle of vibration. Since the horizontal
component of the inertial force exceeds the frictional
force, the vibration actuator is propelled by thedifference between the frictional forces in theforward and backward directions acting on therubber magnet in the support, as shown in a previous
study [15]. This vibration actuator has a very simple
structure and can generate propulsion equivalent toapproximately 10 times its own weight. However,
the movement direction is limited to only onedirectional movement from the principle ofoperation.

Acrylic plate
Vibration
component A
Vibration
component B
Permanent
rubbermagnet(Secondary)

STRUCTURE OF THE NEW VIBRATIONACTUATOR
Fig. 3 shows the new vibration actuator capable ofreciprocating movement. It is composed of two
vibration components, A and B, having the same
specifications, an acrylic frame and plate, and two
rubber permanent magnets. Vibration components A
and B are orthogonally arranged on the acrylic
frame. The vibration components are composed of acoil spring, a ring-type permanent magnet, and anelectromagnet having a bobbin-type iron core
proposed in the previous paper [16]. The magnetic
field generated by an electromagnet can beconverted to an electromagnetic force with highefficiency. Details of the vibration component andthe bobbin-type iron core are shown in Fig. 4. The
coil spring is a compression coil spring with a free

Acrylic frame

Magnetic substance

Permanent
rubbermagnet(Main)

Fig. 3. Structure of the new vibration actuatorcapable of reversible motion.
D

12 mm

h

Attractive force F

Bobbin-typeiron core

9 mmRing-typepermanent magnet
Electromagnet

Coil

d

H

Horizontal
component

Coil springhFrictional
force

Verticalcomponent

32 mm

Verticalcomponent

Horizontal
component

length of 25 mm, an outer diameter of 12 mm, and aspring constant k = 2,689 N/m. The ring-type
permanent magnet is an NdFeB magnet with anouter diameter of 12 mm, an inner diameter of 9mm, a thickness of 8 mm, and is magnetized in theheight direction. For the electromagnet, theexperimental results for the optimization of thebobbin-type iron core shape and the number of turns
obtained in the previous study [16] were applied. As
shown in Fig. 3, for the iron disk, the diameter is D
= 8 mm and the thickness is h = 1 mm. In addition,
the shaft diameter is d = 3 mm, and the length is H =26 mm. The electromagnet was produced bywinding a copper wire having an outer diameter of
0.14 mm around a bobbin-type iron core of 1,200
turns.
Two vibration components are glued to theacrylic frame, and two rubber permanent magnets
are attached to the bottom of the acrylic frame inorder to hold the actuator against the magnetic
substance. One is the main rubber permanent magnet
for holding the actuator against a magnetic
substance. Another secondary rubber permanent
magnet was attached in order to achieve stablestraight movement. This main rubber magnet has alength of 13 mm, a width of 15 mm, and a thicknessof 3 mm. The average surface magnetic flux
density measured using a tesla meter was 128 mT.
The secondary rubber magnet has a length of 6 mm,
a width of 15 mm, and a thickness of 3 mm. The
average surface magnetic flux density was 121 mT.
When the vibration actuator is set on an ironstructure, the attractive forces of the main andsecondary permanent magnets are Fs = 5.2 N and Fm

Displacementof mass

Direction ofinertia force

24 mm

Displacementof mass

12 mm

Electromagnet

Fig. 4. Vibration components and electromagnet.
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SEE - Kyoto, Japan, Nov.18-20, 2020

= 0.5 N, respectively. The vibration actuator has aheight of 43 mm, a length of 58 mm, a width of 20mm, and a total mass Ma of 39 g.

F = Fm + Fs —IB sin ω t ( 0 < t < π/ω) , Ff = μ F

where t is time, and μ is the friction coefficient.
When component A is displaced in the +x directionin the same phase while vibration component B isdisplaced in the +y direction, the vibration actuator
easily slides in the +x direction. As shown in thefollowing equation, when the inertial force IA of thepermanent magnet in vibration component A
exceeds the friction force Ff, the actuator can movein the +x direction:

PRINCIPLE OF OPERATION FOR THE NEW
VIBRATION ACTUATOR
As shown in Fig. 3, when two vibration
components, A and B, are arranged orthogonally, themovement direction of the actuator can be changed
by controlling the phase of the vibration
displacement in each component. The cases ofdisplacement in the horizontal and vertical directions
are referred to as vibration components A and B,
respectively. The displacement coordinates x and yfor vibration components A and B are determined, as
shown in Fig. 5.
When the vibration actuator is set on a magnetic
substance, the frame of this actuator is held by themain and secondary rubber permanent magnets withattractive forces of Fm and Fs. Due to this reaction,
the vibration component can be displaced. The
vibration components A and B were assumed tovibrate at an angular frequency ω. First, as shown in
Fig. 5(a), consider the case in which the phasedifference for displacement between vibration
components A and B is 0 degrees (in-phase).
Focusing on one cycle of the displacement (ω/2π) in
the vibration component B, the holding force F andthe frictional force Ff of the support part for theactuator change periodically, as shown inEquation(1), due to the inertial force IB by thepermanent magnet of the vibration component B:
IB

IA

IB

IA

y
x

x

Movement
direction

Frictional Frictional
force Ff force Ff

IA > Ff

Attractive force F

Attractive force Fm(Main)

Attractive force Fs(Secondary)IB

Attractive force F(a) Sliding

IB

F = Fm + Fs + IB sin ω t (π/ω < t < 2π/ω) , Ff = μ F---------- (3)Even if the component A is displaced in the -ydirection in opposite phase, the inertial force IA
cannot exceed the friction force Ff. Therefore, theactuator cannot move, as shown in the following
equation:I A < FfyAttractive force Fm(Main)(b) No sliding

IB

BASIC CHARACTERISTICS OF THE NEW
VIBRATION ACTUATOR
Fig. 7 shows an outline of the experimental
apparatus used to determine the basic characteristics.
In the experiment, two vibration components were
driven resonantly by a two-channel signaltransmitter and amplifier. The resonance frequency
was 128 Hz. The voltage, current, and power input
to the electromagnet for the vibration component
were measured by a power analyzer. As themagnetic substance, an iron rail having a width of 50mm, a thickness of 50 mm, and a length of 500 mm
was used. In the measurement, the vibration actuator
was set on a horizontal plane. As described above,

IB

IA

y

y
x

x
Movement
direction

Frictional
force Ff

Frictional
force Ff
Attractive force Fm Attractive force Fs(Secondary)(Main)
IB
Attractive force F
Attractive force F

Attractive force Fs(Secondary)(a) Sliding(4)

The actuator can move in one direction by changing
the frictional force of the rubber permanent magnet
attached to the frame.
Fig. 6 shows a case in which the phasedifference of the displacement between vibration
components A and B is 180 degrees (opposite
phase). The actuator can move in the -x direction
according to the principle of movement by thefrictional force and the inertial force describedabove. Accordingly, the actuator can change
between forward and backward motion bycontrolling the phase of displacement of the two
vibration components.

Fig. 5. Principle of reversible motion (in-phase).
IB(2)

On the other hand, as shown in Fig. 5(b), when
vibration component B is displaced in the -ydirection, the holding force F and the frictional force
Ff increase as shown in the following equation, due
to the inertial force IB by the permanent magnet:

Movement
direction

Attractive force Fs(Secondary)(1)

Attractive force Fm(Main)IB(b) No sliding

Fig. 6. Principle of reversible motion (out-of-phase).
107

SEE - Kyoto, Japan, Nov.18-20, 2020

the attractive forces produced by the main and sub
rubber permanent magnets are Fs = 5.2 N and Fm =0.5 N, respectively. The coefficient of friction
between the rubber permanent magnet and the ironrail is 0.84. The directions of movement of theactuator are defined as shown in Fig. 7. Fig. 8 showsa photograph of the vibration actuator.
Fig. 9 shows the relationship between the input
current to each electromagnet and the displacement
amplitude in vibration components A and B. Usingan acrylic stopper, the state in which the vibration
actuator is freely held was set. For the measurementof the displacement amplitude, a laser displacement
meter and an FFT analyzer were used as shown in
Fig. 7. For both vibration components, thedisplacement amplitude increases approximately
linearly with an increase in the input current.
Therefore, the displacement amplitude in each
vibration component can be estimated by measuring
the input current.
The input current to the electromagnet forvibration component B is set to 50 mA, and Fig. 10shows the relationship between the amplitude ofvibration component A and the speed of movement
for the vibration actuator. In this case, the twoacrylic stoppers were removed. As shown in Fig. 7,
Direction A (Forward) is a case in which the phasedifference of displacement between the vibration
components is 0 degrees, and Direction B(Backward) is a case in which the phase difference is
180 degrees. The movement speed varies greatly
depending on the movement direction. This is due tothe attractive force of the secondary rubber
permanent magnet attached to the support part of the
FFTanalyzer

actuator. However, as described above, themovement speed of the actuator depends
approximately on the displacement amplitude. By
controlling the input current to the electromagnet,
the movement speed in both directions can be
adjusted to be the same.
The input current to the electromagnet forvibration component A at 50 mA was set, and Fig. 11
shows the relationship between the vibration
amplitude of vibration component B and the
movement speed of the vibration actuator in two
directions. As the input current to vibration
component B increases, the holding force of theactuator increases. Due to the increase in the holding
force, the amplitude of the two vibration
components increases, so that the movement speed
increases. For the reasons described above, adifference in speed occurs depending on the
movement direction.
Fig. 12 shows the relationship between thedisplacement phase difference for vibration
components A and B and the movement speed. The
input current to the electromagnet for both vibration
components was varied as 50, 60, and 70 mA. In thiscase, the frequency of vibration components A and
B was 128 Hz, and the phase of component A waschanged from -180 degrees to 180 degrees using the

Amplitude (mm)

3

Laser
displacement
meter
Power
analyzer(2 channels)

Direction B

Laser
displacement
meter

Direction A

1〇 : Direction A△ : Direction B

0

50
100
Input current (mA)

Fig. 9. Relationship between input current andamplitude.

Amplifier(2 channels)
Function
generator(2 channels)

60
50

Speed (mm/s)

Acrylic
stopper2

Fig. 7. Experimental apparatus.

〇 : Direction A△ : Direction B

40
30
20
10
0

1

1.5
2
Amplitude (mm)2.5

Fig. 10. Relationship between amplitude and speed.

Fig. 8. Photograph of vibration actuator.
108

SEE - Kyoto, Japan, Nov.18-20, 2020

100

Dir
ect
ion
A

Speed (mm/s)

80

Dir
ect
ion
B

〇 : Direction A△ : Direction B

60
40
20
0

β1
1

1.5
2
Amplitude (mm)

2.5

β2

Fig. 13. Vibration actuator moving on iron railwith tilt angle.

Fig. 11. Relationship between amplitude and speed.
8030〇 : 50 mA△ : 60 mA□ : 70 mA

Speed (mm/s)

Speed (mm/s)

40

20〇 : 50 mA△ : 60 mA□ : 70 mA

60
40
20

10
0
-180 -120 -60
060 120Phase difference (degrees)

0
-90

-60

180

-30
0
30
60
Tilt angle β1 (degrees)

90

Fig. 14. Relationship between tilt angle and speed.

Fig. 12. Relationship between phase difference andspeed.

80

Speed (mm/s)

phase adjustment of the two -channel signal
generator. The movement speed shows a maximum
value when the phase difference of the displacement
is 0 degrees and 180 degrees. In these cases, themovement speed of the actuator is approximately 30
mm/s. When the phase difference is -90 degrees or
90 degrees, the vibration actuator cannot move dueto the movement principle.

40
20
0
-90

MOVEMENT CHARACTERISTICS OF THE
VIBRATION ACTUATOR
As shown in Fig. 13, the tilt angle of the iron rail
was set to β1 and β2, and the movement
characteristics of the vibration actuator were
measured. In the experiment, the phase difference of
displacement in each vibration component was set to
0 degrees and 180 degrees.
Figs 14 and 15 show the relationship between
the tilt angles β1 and β2 of the iron rail and the speed
for Direction A ( for war d) and Directio n B(backward) of the vibration actuator by changing the
input current to the electromagnet for each vibration
component. In the figure, -90 degrees indicatesvertical downward movement, 0 degrees indicateshorizontal movement, and 90 degrees indicatesvertical upward movement. As the tilt angle of theiron rail increases, the movement speed of theactuator decreases. This is due to the weight of the〇 : 50 mA△ : 60 mA□ : 70 mA

60

-60

-30
0
30
60
Tilt angle β2 (degrees)

90

Fig. 15. Relationship between tilt angle and speed.
actuator itself. The actuator can move withapproximately the same amount in the forward andbackward directions.
A load mass was attached to the frame of theactuator using a string. The tilt angle of the iron rail
was set to 90 degrees.
Figs 16 and 17 show the relationship between theload mass mounted on the actuator and the vertical
upward speed when the actuator moves in theforward and backward directions. The input current
to the electromagnet for each vibration component
was changed from 50 mA to 110 mA. As shown in
the figure, the maximum pulling force of theactuator in the case of forward movement is 1.9 N,
while that in the case of backward movement is only109Vertical upward speed (mm/s)

SEE - Kyoto, Japan, Nov.18-20, 2020

60
50
40

 %  M a  M m  v up g  100 PI〇 : 50 mA△ : 70 mA□ : 90 mA

30

where Ma is the total mass of the actuator, Mm is theload mass, vup is the vertical speed, g is theacceleration due to gravity, and PI is the input power.
The solid line indicates the results for Direction A(forward) for the actuator pulling its own weight,
and the dashed line indicates the results for
Direction B (backward). The maximum efficiency of
the actuator was approximately 12.5 % for the caseof direction A.

StringLoad mass

20
10
0

100
Load mass (g)200

Vertical upward speed (mm/s)

Fig. 16. Relationship between load mass andvertical speed.

CONCLUSION
A new type of a vibration actuator that is
capable of reciprocating movement by means of adisplacement phase difference between two
vibration components has been proposed and tested.
The experimental results reveal that this vibration
actuator is able to pull a load mass of 190 g. The
maximum efficiency of the vibration actuator wasapproximately 12.5 % for the own-weight case. By
setting the phase difference of the displacement
between the vibration components to 0 and 180
degrees, the vibration actuator can perform
reciprocating movement at maximum speed. Thisvibration actuator was confirmed through actual
tests to be able to easily control the direction of
movement with a two-channel function generator
and a power amplifier. In the future, by mounting a
CCD camera on the frame of the actuator, it
becomes possible to inspect the appearance of theiron structure.

60
50
40

〇 : 50 mA△ : 70 mA□ : 90 mA

30String20

Load mass

10
0

50
100
Load mass (g)150

Fig. 17. Relationship between load mass andvertical speed.

Efficiency (%)

15

ACKNOWLEDGEMENTS
I would like to thank the students of Yaguchi
Laboratory and the staff of the machine factory of
Tohoku Gakuin University for their involvement inthis research.

105〇 : 90 mA (Direction A)△ : 90 mA (Direction B)

0100
Load mass (g)

(5)

200

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Fig. 18. Relationship between load mass andefficiency.
1.3 N. As described above, this is because theattractive force of the secondary rubber permanent
magnet has an effect. The presence of the attractive
force asymmetric with respect to vibration
component B degrades the movement characteristicsof the actuator. However, the secondary rubber
permanent magnet is needed to drive the actuatorstraight.
Fig. 18 shows the relationship between the load
mass and the efficiency of the vibration actuator.
The efficiency  is expressed as follows:
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Hyun, “Micro aerial vehicle type wall-climbing
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［12］F. Xu, X. Wang and G. Jiang, “Design andAnalysis of a Wall-Climbing Robot Based on a
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［15］H. Yaguchi and S. Sakuma : Vibration
Actuator Capable of Movement on Magnetic
Substance Based on New Motion Principle,
Journal of Vibroengineering, Vol. 19, Issue 3,
pp. 1494 - 1508 (2017).
［16］H. Yaguchi and T. Izumikawa : Wireless InPiping Actuator Capable of High-Speed
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［5］M. Akhtaruzzaman, N. Samsuddin, N. Umar
and M. Rahman, “Design and Development ofa Wall Climbing Robot and its Control System”,
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［6］M. Suzuki and S. Hirose, “Proposal of
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Anchor Climber and Development of
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［7］N. Khirade, R. Sanghi and D. Tidke,“Magnetic Wall Climbing Devices - A
Review”, in Proc., International Conference on
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［8］J. H. Kim, S. M. Park, J. H. Kim and J. Y.
Lee, “Design and Experimental Implementationof Easily Detachable Permanent Magnet
Reluctance Wheel for Wall-Climbing Mobile
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［9］A. Subramanyam, Y. Mallikarjuna, S. Suneel
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111

6

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106032 C3051

VIBRATION ANALYSIS OF A GASOLINE-ENGINE CAR DRIVING
UPON THREE TYPES OF ROADSSuphattharachai Chomphan
Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACTThis paper presents a problematic analysis of vibration signals inside a personal gasoline-engine car whiledriving upon three types of roads including paved road, concrete road, and gravel road. The vibration sensors areallocated over three positions inside the passenger room; the right-front (driver’s) seat surface, the left-front seatsurface, and the rear seat surface. A couple of purposes of this study are to compare the vibration affecting fromdriving upon three types of roads, and to compare the vibration at three different areas of sensor allocations. The
proposed signal analysis technique is Fast Fourier Transform (FFT), the output spectrum are used to extract thedominant peaks. The averaged values for six engine speeds ranging from 0-30 km/h are conducted. The averaging
calculations are based on 50 five-second-length samples of vibration signals. As for the first purpose, theexperimental results confirm that the highest peak values are mostly of the gravel road, meanwhile the lowest peakvalues are of the paved road. As for the second purpose, the evident results can be strongly concluded as follows.
In case of paved road, the highest peak values are at the rear seat surface, moreover in case of concrete road, thehighest peak values are at the left-front seat surface. Last but not least, in case of gravel road, the highest peakvalues are at the rear seat surface. All in all, this study confirmed that the proposed approach can be used todifferentiate the signal features of all scenarios.
Keywords: Fast Fourier transform, Vibration analysis of gasoline engine, Paved road, Concrete road, Gravel
road

durability simulation. Six different kinds of test roadsurfaces are conducted in the simulation, it has beenconcluded that the explicit–implicit co-simulation
techniques are efficient and accurate enough forengineering purposes [2].
The interaction between the type and technicalcondition of road surfaces, dynamic vehicle loads,
and the level of vibration propagated to theenvironment has been introduced by Czech [3]. It has
been insisted that the type of road surface and thetechnical condition and varied dynamic vehicle loads
are affecting the level of vibration propagated to theenvironment explicitly.
Since the vibration is one of the main
environmental stress in vehicles. A study of the
discomfort caused by vibration for three models of
micro commercial vehicles running in four types ofroad conditions has been performed by Huang and Li[4]. Noise is also investigated in the study. Moreover,
Litak et al., investigated the chaotic vibration which
was the effect of critical Melnikov amplitude of theroad surface profile to a quarter car model [5].
Blekhman and Kremer also conducted a study of theeffect of road unevenness on the dynamics of theaveraged longitudinal motion of a vehicle [6]. In the
aspects of detection and diagnosis of the faults inrotating machinery, a number of the mechanical

INTRODUCTION
Nowadays, land transportation are playing many
important roles in our daily lives. Especially in the
newly-developed or developing countries, trailers,
trucks, pick-up trucks, or cars, have been used totransport products, raw materials, tools, andequipment. Not only the non-living things but also theliving things are carried upon automobile on land.
Therefore the effects of the road surface type andcondition are very dominant factors on the vibrationand sound within the transportation vehicles.
A study of the effects of the road surface typeand condition on the traffic flows management modein case of directive management has been explored by
Novikov et al., [1]. Its focus is the method ofassessment of effect of the road surface type andcondition on the capacity rate of the signalized area
and therefore its effects on the traffic flow
management mode. It has been concluded that there
is a correlation between the friction coefficient andthe capacity of the managed area resulting in thechange of the traffic lights cycle, which is also
corroborated by the conducted field experiment on asignalized intersection.
In the vehicle durability aspect, Hu and Zhong
applied a conventional finite element model for linear
and nonlinear analysis for multibody full-vehicle112

SEE - USQ, Kyoto, Japan, Nov.18-20, 2020

Almost all road surfaces in Thailand include
three main types of paved road, concrete road, andgravel road. Their attributes are concluded as follows.

vibration-based studies have been tremendously
pursued [7]-[9].
Investigating the associated signal processing
for machine diagnosis, several research of signal
processing adaptation have been investigated for fault

1. Gravel Road, this type of road surface isabundant in rural areas of the Thailand. It does not
require frequent maintenance as long as its surface isstill smooth. However, its major disadvantage is thediagnosis [8]. The discrete wavelet transform in
temporal and spatial domain was successfully appliedwith the vibration signal for the engine fault diagnosis

Experimental
designData preparationof the diesel engine and the gearbox [8], [9]. The
power spectrum analysis with high order, cepstrum
analysis, and neural network approach were utilized
for fault diagnosis and indication of some of theExperimental
setup

Measurement ofvibration signal
for gravel road

Measurement ofvibration signal
for concrete road

Measurement ofvibration signal
for paved road

Signalpreparation andcollection withthree sensor
positions

Signalpreparation andcollection withthree sensor
positions

Signalpreparation andcollection withthree sensor
positions

element bearings [12]. The problems of gasolinesubstitution with LPG boiling system installation
cause some significant variation in vibration andVibration signal
databasefor gravel roadVibration signal
databasefor concrete roadVibration signal
databasefor paved roadsound signals of the modified engines [13]-[16].
Thereafter some analysis techniques of the vibrationand sound signals were developed to differentiate

Featureextraction

Featureextraction

Featureextraction

specific induction motors [10]. The power of signal
analysis with less time consumption and low
computational cost was conducted in a comparative
study of LPG-modified engine and normal oil-usageengine [11], and also in a fault diagnosis of rolling

between the LPG-modified engine and theconventional gasoline engine, subsequently somesignificant attributes were used to indicate theComparative
analysis
Signal processing

irregularities of the corresponding engines [17], [18].
Another study of vibration and sound signal analysis
for a gasoline engine with LPG-installation and some

Discusstion

Fig. 1 Experimental Procedure.

specified fault simulations was investigated, LPGinstallation and the specified faults concretely

existing dust that occurs during its usage.

affected the engine efficiency degradations [19]-[21].
This study proposed an approach of vibration
signal analysis for a personal gasoline-engine
automobile while driving upon three types of roadsurfaces including paved road, concrete road, andgravel road as mentioned in the previous related
studies [4]-[6]. Two core purposes are to compare thevibration affecting from driving upon three types ofroads, and then to compare the vibration at threedifferent areas of sensor positions. The Fast Fourier
Transform is adopted to extract the signal spectrum
and the corresponding features [11], [20]-[22].

2. Concrete Road, this type of road takes a longtime to build and has high construction costs withhigh durability.
3. Paved road, this type of road is considered aroad that has both advantages and disadvantages.
Asphalt is commonly used in this road type
construction. Its advantage is its inexpensive quicktime construction, however some disadvantages arestill existing. For example, spray water asphalt to coat
the road surface is needed while broken surface is
detected.

MATERIAL AND METHODS

Experimental Procedure

In this section, the road surface types selected in
the experiment has been explained. The experimental
procedure has been illustrated step by step. Finally theexperimental setups have been therefore presented.

In this study, the experiment procedurecomprises of data preparation and signal processing
sub-procedures as illustrated in Fig. 1. At the datapreparation stage, the experimental setup has been
conducted at the beginning. Thereafter, themeasurement of vibration signal of the experimentautomobile for all three types of road surfaces has

Road Surface Types

113

SEE - USQ, Kyoto, Japan, Nov.18-20, 2020

been performed. Subsequently, the signal preparationand collection has been conducted to construct thesignal database for three positions of sensors inside
the passenger room; the right-front seat surface, theleft-front seat surface, and the rear seat surface. The
signal database consists of all scenarios of car speeds
including 0, 10, 15, 20, 25, and 20 km/h, respectively.
At the data preparation stage, signal feature
extraction has been inaugurated. Fast Fouriertransform of the initially-provided signal has been
applied to obtain its corresponding frequency
spectrum. Monitoring the frequency spectrum brings
about some frequencies at the dominant peak points
and their corresponding amplitudes. These highest
peaks are assumed to represent the importantcomponents of the vibration signal inherited frommovement of the automobile. These features areaveraged among all collected samples and therefore
analyzed comparatively. At the end of this stage, thediscussion of this study has been done andsummarized.

(c)

(d)

Fig. 2 Experimental setups: (a) interface of NI9234
card, and installation locations of vibration
sensors; (b) the left-front seat surface, (c) theright-front seat surface, and (d) the rear seatsurface.

Magnitude of peak (m/s²)

Paved road

Gravel road

0.35
0.3
0.25
0.2
0.15
0.1
0.05
0

0

5

10

15

20

25

30

Engine speed (km/h)

Fig. 3 The averaged magnitude of emerging peak offrequency spectrum of the vibration signal
measured at the left-front seat surface at
different engine speeds.

Experimental Setups
In the experiments, the specimen automobile isa personal gasoline engine car of Mazda-2 model with
1,499-cc cylinder volume, Skyactiv-D, 4 cylinders,and 16 valves. The vibration sensors and theircomplementary parts, NI9234 card for interfacingwith computer, and a computer for signal processing
are provided. The interface of NI9234 card, andinstallation locations of vibration sensors areillustrated in Fig. 2.

Magnitude of peak (m/s²)

Paved road

EXPERIMENTAL RESULTS

0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0

0

5

Concrete road

10

15

Gravel road

20

25

30

Engine speed (km/h)

In the signal analysis, FFT the efficient tool offrequency spectrum extraction has been selected todetermine frequency components of the collectedvibration signals in the databases. The most dominantfrequencies emerging peak along the frequency
spectrum at six different engine speeds are extracted.

Fig. 4 The averaged magnitude of emerging peak offrequency spectrum of the vibration signal
measured at the left-front seat surface at
different engine speeds.

Magnitude of peak (m/s²)

Paved road(a)Concrete road

(b)

0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0

0

5

Concrete road

10

15

Gravel road

20

25

30

Engine speed (km/h)

Fig. 5 The averaged magnitude of emerging peak offrequency spectrum of the vibration signal
114

SEE - USQ, Kyoto, Japan, Nov.18-20, 2020

measured at the rear seat surface at different
engine speeds.

Magnitude of peak (m/s²)

Left-front seat
0.5
0.4
0.3
0.2
0.1
0

0

Right-front seat

10

15

20

frequency spectrum of the vibration signal increases
while the engine speed is being raised. The gravel
road reflects the highest impact to the averaged
magnitude when comparing with the others,
meanwhile the paved road shows the least vibration
magnitude. Furthermore, it can be observed that themagnitudes of the FFT for all road surface scenarios
at the low engine speeds of 0 and 10 km/h are quite
not different.
From Fig. 4 with focusing at the right-front seat,
the averaged magnitude of emerging peak offrequency spectrum of the vibration signal increases
while the engine speed is being raised as same as thatof the left-front seat depicted in Fig. 3. The paved
road and the concrete road are quite similar to eachother especially at the engine speed under 15 km/h.
From Fig. 5 with focusing at the rear seat, theaveraged magnitude of emerging peak of frequency
spectrum of the vibration signal has the same
movement along the engine speed axis as those of theleft-front seat surface and the right-front seat surface
illustrated in Figs. 3 and 4, respectively.
From Fig. 6 with focusing the gravel road, theaveraged magnitude of emerging peak of frequency
spectrum of the vibration signal increases while theengine speed is being raised for all of the vibration at
all sensor locations. The rear seat gives the highest
impact to the averaged magnitude when comparing
with the others, meanwhile the right-front seat gives
the least vibration magnitude.
From Fig. 7 with focusing the concrete road, thetrends of all averaged are as same as those of thegravel road in Fig. 6. However it has been noticed thatthe left-front seat rises from the second highest to the
top highest impact for the engine speeds over 20
km/h.
From Fig. 8 with focusing the paved road, thetrends of all averaged are as same as those of thegravel road in Fig. 6.

Rear seat25

30

Engine speed (km/h)

Fig. 6 The averaged magnitude of emerging peak offrequency spectrum of the gravel road atdifferent engine speeds.

Magnitude of peak (m/s²)

Left-front seat

Right-front seat

Rear seat

0.25
0.2
0.15
0.1
0.05
0

0

10

15

20

25

30

Engine speed (km/h)

Fig. 7 The averaged magnitude of emerging peak offrequency spectrum of the concrete road atdifferent engine speeds.

Magnitude of peak (m/s²)

Left-front seat

Right-front seat

Rear seat

0.2
0.15
0.1
0.05
0

CONCLUSIONS
0

10

15

20

25

30

An analysis of vibration signals measured insidea gasoline-engine automobile of Mazda-2 model
driving upon three types of roads has been presented.
The installation of vibration sensors are at the driver’s
seat surface, the left-front seat surface, and the rearseat surface. The frequency spectrum of FFT is used
to extract a number of peaks where the dominantfrequencies is located. The averaged magnitude of
emerging peak for six engine speeds ranging from 030 km/h are calculated. Comparing among three typesof roads, the experimental results confirm that thehighest peak values are mostly of the gravel road,meanwhile the lowest peak values are of the paved
road. Comparing among three locations of vibration
sensors, the explicit results can be strongly concluded
as follows. In cases of paved road and gravel road, thehighest peak values are of the rear seat surface,Engine speed (km/h)

Fig. 8 The averaged magnitude of emerging peak offrequency spectrum of the paved road atdifferent engine speeds.
The plotting of the averaged magnitude of
emerging peak of frequency spectrum has been
performed along the different engine speeds. Threelines in each figure represent the characteristics ofthree types of roads including paved road, concreteroad, and gravel road, respectively. These plots havebeen conducted for all three installation locations ofvibration sensors.
From Fig. 3 with focusing at the left-front seat,
the averaged magnitude of emerging peak of115

SEE - USQ, Kyoto, Japan, Nov.18-20, 2020

moreover in case of concrete road, the highest peakvalues are of the left-front seat surface. Summarily,
this study concludes that the proposed analysis
technique of vibration signals can be used todifferentiate the signal features of all scenarios of apersonal gasoline-engine car while driving upon three
types of roads. In the future study, the otherassociated signal processing techniques should be
developed to approach more efficient identification of
all scenarios or automobile condition diagnosis.

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Yanyang Z., Zhengjia H., Fault feature extractionof gearbox by using over complete rational
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Systems and Signal Processing, Vol. 33, Issue 11,2012, pp. 275–298.
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Mechanical Systems and Signal Processing, Vol.
19, Issue 6, 2005, pp. 1196–1208.
[17] Zbigniew S., Jan W., Application of vibration
signals in the diagnosis of combustion engines –exploitation practices. Journal of KONES
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pp. 405-412.
[18] Carlucci A. P., Chiara F. F., Laforgia D.,
Analysis of the relation between injection
parameter variation and block vibration of aninternal combustion diesel engine. Journal ofSound and Vibration, Vol. 295, Issues 1–2, 2006,
pp. 141–164[19] Boonsit S., Chomphan S., Vibration Signal
Analysis for LPG-modified Engine and Normal
Oil-usage Engine with Different Engine Speeds
and Faults. in Proc. International Congress on
Engineering and Information, 2017, pp. 102-107.
[20] Chomphan S., Vibration Signal Analysis of A

ACKNOWLEDGMENTS
The research was sponsored by Kasetsart
University, Faculty of Engineering at Sriracha. The
instruments were supported by the Mechanical
Syetem and Signal Processing research group.
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K., Chaotic vibration of a quarter-car model
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[6] Blekhman I., Kremer E., Vibrational resistanceto vehicle motion due to road unevenness,
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Motorcycle, International Journal of GEOMATE,
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[21] Chomphan S., Kingrattanaset T., Boonsit S.,
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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STUDY ON RIVER PATROL USING IMAGES CAPTURED BYDRONES AND MACHINE LEARNING
Ryo Yahara1, Koki Sakita2, Satoshi Nishiyama3, Tomohiro Shimono4, Michinari Fujiki5 and Tatsuya
Chigira6
1,2,3
Environmental and Life Science, Okayama University, Japan; 4,5,6 Kokusai Kogyo Co., Ltd., Japan

ABSTRACT
Owing to the frequent occurrence of heavy rainfall in recent years, river patrols are increasingly crucial forevaluating local situations to prevent large-scale disasters, such as bank breaks. Qualitative anomalies are grasped
visually by personnel, and a large amount of effort is spent on patrolling long dikes. In this study, we used aerial
images captured by drones. We aim to quantify abnormalities in rivers during river patrols and reduce the burden
on staff. We also investigated a method that can automatically extract abnormal points from captured images by
object detection using local binary pattern features. The features described in the river patrol could be identified
from the images captured by the drone, enhancing the practicality of river patrols. Regarding automatic extraction,
we were able to sort out the differences in results based on shooting conditions and machine learning process andobtain results for the future for automatic extraction.
Keywords: Machine learning, Object detection, Local binary pattern (LBP), River patrol

In this paper, we analyze the accuracy of thecaptured images depending on the shooting
conditions and the relationship between this feature
amount and the output of machine learning, andconsider the practicality of river patrol using thedrone captured images.

INTRODUCTION
In recent years, occurrence of heavy rainfall andstrong typhoons has become frequent in Japan,
resulting sequential flooding of rivers. Therefore,
river patrol to grasp the local situation is becoming
more important for preventing large-scale disasters
such as bank breaks. However, the inspection method
for river patrols has been carried out as before, andthe qualitative abnormality can be grasped visually by
the patrol staff. In addition, much effort is spent onpatrols of long dikes. Therefore, in this study, we
focused on drones as a measure to reduce the burden
on staff in river patrol operations and to prevent
oversight. Drones are used as an efficiency method in
various fields, such as bridge inspection andcollection of agricultural crop growth information[1]-[5]. However, there is no example that it is applied
to river patrol, and this study verified whether theefficiency improvement of the work by drone can beapplied to river patrol. First, we verified how high theheight of an image taken by a drone equipped with acamera could be to visually confirm the features. In
addition, we also verified the method of automaticallyextracting abnormal points by using object detection
by machine learning. A study on the efficiency ofquality inspection and facility inspection using
machine learning has also been reported [6]-[8].
However, there is no example applied to river patrol
work. LBP features are used as features. The method
proposed by Ojala et. al. [9] has the advantage that itis robust against changes in brightness and requires asmall amount of calculation, and is still widely used
as a feature amount. [10]-[12]RIVER PATROL
In river maintenance, it is very important to detect
abnormal points at an early stage, and it is essential tograsp river conditions on a daily basis. In Japan,“river inspection” and “river patrol” are performed asa means to understand the situation of a river and its
peripheral equipment. River inspections are
conducted approximately twice a year to havedetailed understanding on the conditions of rivers.
Conversely, river patrol, which is the aim of thisresearch to improve the efficiency of this technique,is performed approximately twice a week tounderstand the river situation generally and detect
abnormalities.
According to Standards established by the
Ministry of Land, Infrastructure, Transport andTourism (Ministry of Land, Infrastructure, Transport
and Tourism River Bureau, May 2011), the river
patrol covers the following four topics:(1) Discovery of illegal acts in river areas(2) Grasping the status of river management
facilities and maintenance of permitted works(3) Collecting information on the use of river space

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Object Detection(4) Collecting information regarding the naturalenvironment of rivers.
Currently, river patrols are mainly performed visuallyusing patrol vehicles, and workers monitor and record
the data on field and peruse the acquired data at
offices. Additionally, areas that are difficult forvehicles to enter, such as river banks, are assessed bywalking. Evidently, observing a vast river spacevisually is laborious and time consuming.

We used object detection, which is a part ofmachine learning, as a method for automatic
extraction of abnormal points during a river patrol.
Object detection is a method of automaticallydistinguishing a target object comprised in an image
from a background and categorizing this object.
Further, by using the rectangular search window,
even if the image comprises a plurality of target
objects, their positions can be located and theirclassification can be identified. In this study,“Traincascade,” which is one of the functions in
OpenCV, is used as a method to develop a detector
for object detection. The procedure can be divided
into two phases, learning and recognition phases. In
the learning phase, training data are fed to themachine, and the features are repeatedly learned.
Meanwhile, in the recognition phase, the computer
determines whether the learned object is included in
the input image.

MACHINE LEARNING
Machine learning is a technology that allows acomputer to have a learning mechanism similar tohumans; unknown data can be predicted by learningfeatures, regularity, and patterns from previous data.
With machine learning image recognition, voice
analysis, class classification, regression, clustering,etc., can be realized. In this method, a human mustspecify a feature amount, and the machine must learn
the feature amount.
Deep learning is one of the machine learning
methods (Fig. 1), and it is used in many studies
because of its high performance [13],[14]. Deeplearning technique is based on neural networks,
which are systems that can imitate the mechanism of
human nerve cells. By using neural networks inmultiple layers, the step-by-step features contained in
the data can be learned. When a large amount ofimages, text, and audio data is input into a multilayered neural network, the computer automaticallylearns the features contained in the data in each layer.
One of the merits of deep learning is that the accuracy
is improved by the machine automatically selecting
the feature amount that should be originallyperformed by humans. However, since humans
cannot adjust small parts such as parameter
adjustment, the contents become a black box, and it isdifficult to understand the process leading to theresult. Therefore, in this study, we conducted a study
on machine learning, which is a basic study for deeplearning, and examined how factors such as shooting
conditions and feature quantities affect.

Learning Phase
In the learning phase, the properties andcharacteristics of the target object are learned fromthe pixel data of the image, which is the training data.
Hence, providing assessments based on rules ispossible even for data. In this study, the target object
was manually extracted from the images captured by
the drone at altitudes of 37, 74, and 110 m as training
data, and the machine was made to learn the numberof correct images (i.e., images containing the target
object)(Fig.2). We also verified the difference inaccuracy depending on the number of training data.
The maximum number of learning images is 2000 for
correct images and 2000 for incorrect images (i.e.,
images that do not include the target object).

Fig. 2

Garbage bag training data

Detection Phase
Fig. 1In the recognition phase, a new input image thatis not used in learning is converted into feature
quantity data by using the same procedure used in the

Machine learning conceptual diagram

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learning phase. The target area is identified based on
characteristics that have been input and learned, andthe judgment criteria on whether the target area is thedetection target or the non-detection target (Fig.3).

LBP Feature Process
The specific method for extracting LBP features
is as follows. First, the image given as training data isconverted into gray scale and the image is segmented.
One part of the image is taken, paying attention to 3
× 3 pixels (Fig.5).

Fig. 5
Fig. 3The central pixel of this local area is converted
into binary form. The difference between that pixel
value and the surrounding eight pixels is considered.
If the brightness value of the surrounding pixels ishigher (if the difference in the brightness values ispositive), then the value of the surrounding pixels is
set to 1, and if it is low (if the difference is negative),then the value of the surrounding pixels is set to 0. In
this manner, when 8 pixels surrounding the central
pixel are selected as peripheral pixels, the LBP valueof the central pixel is represented by 8 bits. A weightof 2i (i = 0,...,7) is assigned in a clockwise direction
from the upper left side of the center pixel(Fig.6).

Search in object detection

Learning Algorithm
The learning algorithm is a type of ensemble
learning called “AdaBoost.” In summary, ensemble
learning is a method of taking a majority vote. And It
is a method for improving the prediction ability for
unlearned data by merging those learned as separate
learners. is there. In AdaBoost, multiple weakclassifiers are sequentially applied to the training data,and it is determined whether or not each iscorrect.(Fig.4) At this time, it is a mechanism formaking adjustment by increasing the weight for theincorrectly classified sample or, conversely, reducing
the weight for the correct sample.

Fig. 6
Fig. 4Extraction of local pixels

Convert to binary

If this calculation is performed for the complete
mesh, a collection of one block of binary data is
obtained. This collection of binary data is a histogramof one part.
When this operation is performed for all pixels, acollection of histograms is obtained, which is the LBP
feature quantity (Fig.7).

Theory of Adaboost

LOCAL BINARY PATTERN FEATURESIn the learning phase, it is necessary for themachine to learn a large number of images. However,as the images are fed to the machine as a sequence of
meaningless numbers, they should be converted intomeaningful data representing the features of theimage and then extracted. Therefore, in this study,
local binary pattern (LBP) features are adopted as theones to be converted. LBP features are the local
representation of the image, and each pixel iscompared with the surrounding neighboring pixels.
They are composed of relative values and has thecharacteristics of low calculation cost and robustness
against changes in terms of image brightness.

Fig. 7120

LBP feature extraction

SEE - Kyoto, Japan, Nov.18-20, 2020

bat were placed in the river as objects to be
photographed. Figure 8 is an example of an image ofa garbage bag. As shown in the figure, the feature
amount of the subject in the image changes dependingon the altitude and illuminance.
In this study, we examined the practicality of river
patrolling via drone photography by organizing thedifferences in feature quantities depending on theshooting conditions of these images and therelationship between this feature quantity and theoutput of machine learning.

EVALUATION METHOD
The detection accuracy is evaluated using three
indices: recall rate, precision rate and F value. Eachevaluation method will be described using thefollowing four types of detection patterns.
(1) TP: The number of objects that actually exist andcorrectly judged by the detector(2) FP: The number of objects mistakenly determined
to be an object other than the object(3) FN: The number of objects that the detector
mistakenly determined not to be the object although
it is actually the object(4) TN: The number of objects other than the object
that are judged not to be the object
Recall refers to the ratio of the number ofcorrectly determined objects to the number of actuallyexisting objects. That is, if the recall is low, the rate
at which objects are actually detected but not detected(missing rate) is high. It can be calculated using thefollowing formula:𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫

𝑻𝑻𝑻𝑻
𝑻𝑻𝑻𝑻 + 𝑭𝑭𝑭𝑭

=

Fig.8
(𝟏𝟏)

Precision is an index that evaluates the accuracyof the detector and indicates the ratio of the numberof detection frames that have been judged to becorrect by the detector and are actually judged
correctly to the output detection frames. That is, if thematching rate is low, the rate at which the detector
determines that the target object is included(erroneous detection rate) is high even though it is not
actually the target object. It can be calculated using
the following formula:
𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩 𝐫𝐫𝐚𝐚𝐚𝐚𝐚𝐚=

𝑻𝑻𝑻𝑻
𝑻𝑻𝑻𝑻 + 𝑭𝑭𝑭𝑭

Left: Altitude about 40 m, illuminance
25000 Lux. Right: Altitude about 100 m,
illuminance 25000 Lux

Practicality of Drone Photography for River
PatrolFigure 9 shows a shooting example of thisverification. Each image shows the condition of therevetment, crotovine, and vegetation described in theriver patrol item for each altitude (37m, 74m, 110m).

(𝟐𝟐)

The F value is an index showing the balance between
recall and precision and is a value calculated by the
harmonic mean of recall and precision. It is calculatedusing the following formula:
𝐅𝐅 𝐕𝐕𝐕𝐕𝐕𝐕𝐕𝐕𝐕𝐕 =𝟐𝟐 × 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 × 𝐩𝐩𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫(𝟑𝟑)𝐞𝐞𝐞𝐞𝐞𝐞𝐞𝐞𝐞𝐞 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 + 𝐩𝐩𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫 𝐫𝐫𝐫𝐫𝐫𝐫𝐫𝐫

EXPERIMENTAL OUTLINE AND RESULTThe drone uses a DJI Phantom 4 in terms ofversatility and was installed with a digital camera
with 20 million pixels and an aperture value of 5.6
from altitudes of about 40, 70, and 110 m.
Additionally, to perform verification based on the
difference in illuminance, we changed the shooting
time and shot under an illuminance of approximately
25,000 Lux and 3000 Lux. This study aims to detect
illegally dumped materials in rivers by using drones.
Hence, garbage bags, bicycles, tires, PET bottles andFig. 9 Shooting caseDifference in F Value Owing to the Difference in
the Number of Training data
Figure 10 shows the relationship between thenumber of pieces of training data and the F value.In
this verification, the detection results were compared
between a case where object detection was performed
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using only the learning images that could be collected
in 2 days of image shooting and a case where thenumber of learning images was increased by rotatingor reversing the images. The initial number is thenumber that can be collected in 2 days of image
shooting, and the initial number of each feature isshown in Table 1. The shooting altitude of theverification image is 37 m, and the number ofincorrect images is 2000.

performed at a shooting altitude of 37 m. Regarding
the garbage bags, the F value is 32.77 % at an
illuminance of 25000 Lux and 22.91 % at 3000 Lux.

Fig. 12 Relationship between illuminance and F
value
CONSIDERATION
Fig. 10 Difference in F value owing to the differencein the number of training data
Table 1

In visual confirmation of features from images
taken by drones, if the image is taken at an altitude of
74 m or less, it is possible to check the condition of
the river dike, vegetation, and crotovine described in
the patrol item. It is considered possible to improvethe efficiency of the patrol of the river byappropriately using it according to the managementlevel of the river. As the altitude increases, theshooting range becomes wider (Table 2), which leads
to more efficiency. In the future, it will be necessary
to examine the machine parameters in detail to obtain
results at high altitudes.

Initial value of training data

Difference in F Value Depending on the Shooting
AltitudeFigure 11 shows the F value for eachphotographing altitude. The Value when shooting thedust bag was 19.42% at an altitude of about 40 m and6.70% at an altitude of about 70 m.

Table 2

Relationship between
shooting range

altitudeandWe verified each factor regarding automatic
extraction, and confirmed that the detection accuracy
was improved by increasing the number of training
data for garbage bags, bicycles, and tires. Since thetask of creating training data is also labor-intensive, itwill be necessary to verify the optimum number oftraining data for each objects and improve efficiency
in the future.
Regarding the difference in F-value depending on
the shooting altitude, it is considered that the F-value
decreased due to the decrease in ground resolution
accompanying the increase in altitude. As mentioned
above, the higher the altitude, the more efficient it is.
Therefore, it is necessary to proceed with theverification of the internal factors so that the object
can be detected with high accuracy even with a small
amount of features in the future.
Furthermore, the illuminance at the time ofFig. 11 Difference in F value depending on theshooting altitude
Difference in F value depending on shooting
illuminance
Figure 12 shows the relationship between theshooting illuminance and the F value. The
illuminance when shooting from 8:46 to 8:52 is about
25000 Lux, and the illuminance when shooting from
15:39 to 15:46 is about 3000 Lux. Verification was
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[2] Metni N. Hamel T. and Derkx F., A UAV for
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Optimizing Quality and Outputs by Improving
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UAVs Procedia Computer Science, Vol. 167,
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[5] Wang X. Sun H. Long Y. Zheng L. Liu H. and Li
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shooting had less effect on the F value than the
resolution. As shown in Fig. 13, in the LBP feature
amount, the difference in the brightness is used bycomparison with the surrounding pixels, andtherefore the change in the brightness of the entire
image is unlikely to affect. That is, the obtainedfeature amount data is hardly affected by the shooting
time. Therefore, it is possible to perform river patrol
operations without being bound by the time of day,which is expected to contribute to efficiency
improvement.

Fig. 13 Robustness of LBP
illuminance changes

featuresagainstCONCLUSION
In this study, we aimed to establish a river patrol
method using drone measurement for efficient river
patrol, and attempted automatic detection ofabnormal points using drone image and machinelearning. The results obtained are summarized below.
・If it is 74m or less, We can visually check thefeatures of the river patrol items from the aerial image.
・F-value improves as the number of training data
increases
・F value decreases as altitude increases
・There is little effect of shooting illuminanceIn the future, among the influential factors that areconsidered to affect the detection accuracy, not only
external factors such as the shooting environment but
also internal factors such as the creation method andnumber of training data, learning method, and results
will be considered. We will examine in more detail
how the parameters on the machine learning side,
such as the threshold, affect detection accuracy, andproceed with research toward practical application.
REFERENCES[1] Karim M. M., Dagli C. H., and Qin R., Modelingand Simulation of a Robotic Bridge Inspection
System, Procedia Computer Science, Vol. 168,
2020, pp.177-185.
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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

VERIFY THE PREDICTION OF SLOPE FAILURE BY SOIL CREEPWITH LABORATORY EXPERIMENTS
1,2

Makoto Fukuhara1, Taro Uchimura2 and Shanging Tao3
Saitama University, Japan; 1,3 Chuokaihatsu Corporation, Japan
ABSTRACT

More than a thousand cases of rainfall-induced slope failure occur in Japan every year. Predict the slope
failure is social needs. In this paper, we propose and verify a method to predict the instability of the slope surface
layer by soil creep combined with the creep theory of metallic materials. To investigate the creep theory affectedby soil moisture and deformation and to verify the relationship between creep and soil moisture, deformation,
two kinds of laboratory experiment was conducted to simulate the process of rainfall induce slope failure, thefirst one was multi-layer shear model and the second one was the direct shear test. The soil moisture wascontrolled by artificial rainfall in the multi-layer shear model whereas water infiltrates in the direct shear test.
The inverse number of velocity calculated by Fukuzono's equation and the surface displacement have been
compared, the results show that the tendency of the change of the inverse number of velocity is similar in bothmodel tests. The effect of volumetric water content on the displacement also has been confirmed, when thevolumetric water content increased, the displacement trended to start increasing with an accelerated rate. Fromthese results, the prediction of slope failure time can be improved with higher accuracy.
Keywords: Slope failure, Early warning, Soil creep, Shear deformation
INTRODUCTION
BEHAVIOR DURING SLOPE FAILURE

Rainfall-induced slope failure occurs commonly
in Japan. Before the slope failure, the continuous
slow movement of soil mass has been traditionallyconsidered as soil creep[1]-[2], the time to slope
failure can be predicted from the process of soil
creep. So the prediction of the time to slope failure isvery important for the countermeasures designed to
avoid human losses and reduce the property
damages from slope failure. Nowadays with thedevelopment of the technology, the mass movement
can be easily monitored by means of simple wire
extensometers[3], inclinometers[4], or tilt sensors[5].
Uchimura [6] has proposed a simple monitoring
method for the early warning of rainfall-induced
slope failure, the distinct behaviors of mass
movement expressed by tilting angles at several sites
can be detected in the pre-failure stages. The
methods to predict the time of slope failure had beendeveloped by many researchers [7],[8],[9],[10], they
showed that the behavior of the soil creep is similar
to the metal creep. In this paper, we focus on one of
the methods, the Fukuzono's equation[8], to predict
the instability of the slope surface layer.
To verify the accuracy of the prediction of thetime to slope failure, two kinds of laboratory
experiments were conducted to simulate the processof rainfall-induced slope failure. The inverse numberof velocity calculated by Fukuzono's equation andthe surface displacement have been compared andthe effect of volumetric water content on thedisplacement also has been confirmed.

Deformation until failure
The creep can be explained by the timedependent deformation of solids under constantstress. In general, three creep stages of movement
are included in creep behavior before failure:-Primary: strain rate decreases over time.
-Secondary: strain rate is constant.
-Tertiary: strain rate is rapidly increasing until
failure.
In the case of soil failure (Fig.1), displacement rateincreases at a constant at the secondary creep, andthen increases rapidly at the tertiary creep, finally
failure. The behavior of soil creep varies depending
on conditions such as particle size, soil moisture,and slope angle, etc., the duration of tertiary creep
may be different from sites. Metal creep is shown in
Fig.2. It shows that the behavior of the soil creep(Fig.1) and metal creep is similar.

Fig. 1
124

Example of soil creep in slope failure

Inverse number ofvelocity (1/v)

SEE - Kyoto, Japan, Nov.18-20, 2020

FailureTime (hour)Fig. 2

Metal creep development modelFig. 3The method of failure prediction
Fukuzono[8] found that rapid failure in thetertiary creep base on an experimental study ofsmall scale slope model tests under monotonicallyincreasing load, and proposed the following general
expression:

LABORATORY TEST METHOD
Properties of the test soils
In this study, two types of material were used inlaboratory tests. The first one is mixed sand which iscomprised of Silica sand No4, No5, No7, and No8
mixed with a ratio of 1:1:3:1. The other one is Silica
No.7. The soil property is shown in Table 1 and thegrain size distribution curve is shown in Fig. 4.

【Fukuzono method】
𝑎 𝛼

1

⋅ 𝑡

𝑡

(1)

Where v is the velocity of the slope surface
displacement, t is current time, tr is the estimating time to
failure, a,α:constant.
In the case of α = 2, Eq.1 can be expressed in termsof deformation, proposed by Saito[7]:Table 1 Soil property of material
Soil
Mixed
property
SilicaRelative density(Dr)%50
Dry density(ρd)
g/cm3
1.481
Initial volumetric%7
water content(θ)
StrengthΦ°
43.9
parameters(Φ)
StrengthkN/㎡
7.4
parameters(C)【Saito method】
𝜀𝐶 ⋅ log

Typical figures of the changes of theinverse number of velocity of surface
displacement just before the failure. (after
Fukuzono[8])(2)Where 𝜀 is strain, 𝑡𝑟 is the estimating time to failure, 𝑡0
is hte time at strain = 0, 𝑡 is current time, C isconstant.

Percentage finer by weight (%)

Fig. 3 shows the typical figures of Fukuzono's
method. The changes of the inverse number ofvelocity of surface displacement (1/v) arerepresented by y-axis and the elapsed time isrepresented by the x-axis. The failure time is definedby an intersection point which is extension of thedotted line to the x-axis .
This prediction method is verified by laboratory
experiments that were conducted to simulate theprocess of rainfall-induced slope failure. Even if theresults show complicate behavior of soil creep, but it
is possible to predict the time to failure from thelinear part corresponding to the tertiary creep.

7
37.1
28.6

Grain size distribution curve

100
80
60
40

Mixed silica
Silica No.7

20
0Fig. 4125

Silica
No.7
50
1.340

0.01

0.1

Grain size (mm)1Grain size distribution curve of test soil

10

SEE - Kyoto, Japan, Nov.18-20, 2020

Multi-layer shear model

EFFECT OF DISPLACEMENT RATE ON
PREDICTING THE TIME TO FAILURE

Laboratory experiments were performed using a
multi-shear model to simulate the process of rainfallinduced slope failure. The concept and the detail ofthe multi-shear model were summarized at [11]. It isa model including 20 frames with a total height of
1m. Every frame has a height of 0.05m, length of
0.6m, and width of 0.54m, the soil is filled in theframe. Wheels are setup at every frame to reduce
friction. A constant horizontal force is applied on
every interface between the layers by air cylinders tosimulate the shear force corresponding to the slope
angle. Load cells and displacement meters are also
set at every layer. The artificial rainfall intensity is
60mm/h. Rainwater infiltrates into the top layer anddrains out from the bottom. The volumetric watercontent is measured by the Soil moisture sensor EC5. (Fig.5)

Results of multi-layer shear model test
The method of prediction the time to failure by
the displacement rate has been studied at many slop
surface using extensometers. However, the progressof ground deformation is not constant in the depth
direction. In this study, laboratory experiments using
multi-layer shear model can confirm the detailed
displacements of a part of soil subdivided into manylayers at the depth direction (Fig.7).

Direct shear test
Direct shear tests also are conducted to simulate
the slip surface failure. Two layers are included.
Every layer has a height of 0.035 m, length of 0.31m,
and width of 0.21m. Vertical stress is applied by theupper layer; Constant horizontal force is applied byair cylinders. Water is infiltrated to the soil via
ceramic disks which set up at the bottom (Fig.6).

Fig. 7

Concept of displacement in multi-layer
shear model test

The effect of the displacement rate on the time to
failure was verified by multi-layer shear model tests.
Fig. 8 shows the time history of the displacement in
the test using silica No. 7. Fig. 8 a) shows therelative displacement of layer 19 and layer 18 arelarge, especially the displacement of layer 18
progresses rapidly after 0.1 hours, whereas thedisplacements of the other upper layers are small.
Fig. 8 b) shows the accumulated displacement at to
top layer, layer 19, and layer 18.
Relative disp. (mm)

a)

12

b)
Accumulated disp. (mm)Multi-layer shear model test apparatus

642

Direct shear test apparatus

Fig. 8

126

0.00

0.05

0.10

0.15

0.10

0.15

Time （hr）
12

Top layer
Layer18
Layer19

10
8
6
4
2
0

Fig. 6Layer19

80Fig. 5Layer18

10

0.00

0.05

Time （hr）

Time history of displacement (Silica No. 7)

SEE - Kyoto, Japan, Nov.18-20, 2020

Fig. 10 shows the time history of displacement andthe inverse number of velocity at direct shear test. In
this case, the surface layer progresses slowly
displacement, the time to failure which calculated by
the prediction method was later than the actual time.
Therefore, it is safe to predict the failure time using
the layer which observed fast displacement toprevent damage due to failure.

Application of failure prediction method
To obtain the time to failure, the following data
were calculated by the prediction method (Eq.1).
・ Accumulative displacement at the top layer(corresponding to the bottom layer).
・ Relative displacement near the bottom(layer18 and 19) which shows particularly
remarkable changes.
Fig. 9 shows the results of the time history of
displacement and the inverse number of velocity at
the multi-layer shear model. The time to failure
obtained from the accumulative displacement of the
top layer is 0.126 hour. The time calculated from therelative displacement is different, 0.122 hour at
layer 18 and 0.144 hour at layer 19. The inverse
number of velocity at layer 18 gradually increased
from 0.1 hours, whereas at layer 19 did not change
so much but increased rapidly before failure. It isobserved that the inverse number of velocity at the
top layer is the sum of the layer 18 and layer 19, so
it is considered that the time to failure is thefollowing relationship of the prediction method.

Disp (mm)

5

0
0.00

6

0.06

4

0.04

2

0.02

Time （hr）

0.15

0.06

4

0.04

2

0.02

0.15

Time （hr）

1/v (hr/mm)

0.12

Disp
1/V

Relative disp. of layer 18

0.10

Reciprocal of Disp rate
1/v (hr/mm)

Disp (mm)

0.00

0.144

12
10
8

0.08

6

0.06

4

0.04

2

0.02

0

0.00

Fig. 90.05

0.10

Time （hr）

FailureTop layer(A+B)
Layer A
Layer B200

Tr calculated fromtop layer data

150
100

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

The method of prediction the time to failure is
performed by the tertiary creep. The time to failure
is obtained by plotting the time and the inverse
number of velocity. In the secondary creep stage, theinverse number of velocity shows a large value
because the displacement proceeds at a constantsmall speed. During the tertiary creep stage, thedisplacement increases at an accelerating rate, so theinverse number of velocity gradually decreases. In
particular, when α = 2, the inverse number ofvelocity becomes linear as shown in fig.3.
In this study, the effect of the displacement ratechange in the tertiary creep stage was verified bydirect shear test and multi-layer shear model test.

0.10
0.08

0.10

0.40

Test results for each method

Reciprocal of Disp rate
1/v (hr/mm)

Disp (mm)Relative disp. of layer 19

0.05

0.35

CHANGEINDISPLACEMENTRATE
DURING THE TERTIARY CREEP STAGE

0.126

6

0.00

0.30

Fig. 10 Displacement and the inverse number ofvelocity at direct shear test

8

0

0.25

50

0.12

Disp
1/V

0.20

250

0.00

12
10

0.15

0.10
0.08

0.10

0.10

300

Reciprocal of Disp rate
1/v (hr/mm)

Disp (mm)

Accumulated disp. of top layer

0.05

0.05

Time (hr)

0.12

0.00

10

Time (hr)

8

0

15

0
0.00

12
Disp
1/V

Top layer(A+B)
Layer A
Layer B

20

[Early][Late]
Layer 18 → Surface layer → Layer 19

10

Failure25

0.15

Results of direct shear test
Direct shear test was performed using the mixed
Silica sand under the conditions shown in Table 2.
Fig. 11 shows the time history of the displacement
and the corresponding inverse number of velocity.
According to the test results of case 1, the tertiary
creep stage starts from 0.4 hour, the inverse numberof velocity decreases from 0.4 hour and thenaccelerates from 0.6 hour, finally failure at 0.82 hour.
In case 2, the tertiary creep stage starts from 0.3

0.00

0.122

Time history of displacement and theinverse number of velocity(Silica No. 7)

127

SEE - Kyoto, Japan, Nov.18-20, 2020

hour, the inverse number of velocity decreases from
0.3 hour and then accelerate from 0.4 hour, finally
failure at 0.55 hour.

of velocity(1/v) tended to increase rapidly when thewater content rose high. This phenomenon may beconsidered that the increase of soil moisture leads toa decrease in soil matric suction, resulting in theweakening of soil strength.
In the direct shear test, the changes of inverse
number of velocity(1/v) in the tertiary creep stage
have been confirmed that it is the same results withthe previous research [6]. Considering the uniformof the soil and the various physical properties ofstrata, it is possible to predict the time to failure
more accurately by understanding not only theground surface but also the deformation in ground.

Results of multi-layer shear model test
Multi-layer shear model test (10 layers) was
conducted using the mixed Silica sand, Fig. 12shows the relationship of displacement and theinverse number of velocity in time series. the inverse
number of velocity decreases from 2.4 hours, andaccelerate decreases from 3 hours, showing the sametendency as the result of the direct shear test.
The effect of volumetric water content on
displacement

Table 2 Test conditions of direct shear test
Vertical Horizontal Water
pressure pressure
injection
(kPa)
(kPa)
pressure
(kPa)
7
6.7
0.3
7
7.5
0.15

1
2

Case1

12

Disp (mm)

1.2

Disp
1/v

10

direct shear test
Fig.13 shows the relationship of the volumetricwater content and the inverse number ofvelocity(1/v) in time series in the direct shear test.
starts to increase at a constant rate after the supply ofwater from the time history. At the same timing thatthe volumetric water content starts to increase at anaccelerated rate, the inverse number of velocity(1/v)
also starts to decrease quickly.

1.0

8

0.8

6

0.6

4

0.4

2

0.2

0

0.0

0.2

0.4

0.6

0.8

Time （hr）

0.0

1.2

Disp
1/v

10

Disp (mm)

1.0

0.82

Case2

12

multi-layer shear model test (10 layers)
Fig. 14 summarizes the results of multi-layer
shear test. In this test, the volumetric water content
at each layer was different depending on the time forwater infiltration from the upper layer. The
volumetric water content began to increase with theinfiltration of rainwater from the upper layer, andchanged at a constant rate from 1.4 hours, increased
again from 2.6 hours. The slope of the inverse
number of velocity(1/v) changed from 3 hours. Thechange timing is different from the result of thedirect shear test. However, the timing of theaccelerate of the inverse number of velocity(1/v) is
the same when the volumetric water content
increases to over 0.25.

Water
injection
speed(%/min)
0.41
0.59

1.0

8

0.8

6

0.6

4

0.4

2

0.2

0

0.0

Reciprocal of Disp rate
1/v (hr/mm)

Case

0.1

0.2

0.3

0.4

0.5

Time （hr）

0.6

Reciprocal of Disp rate
1/v (hr/mm)

The changes of inverse number of velocity(1/v)
in the tertiary creep stage have been confirmed byboth of direct shear test and multi-layer shear model
test. The effect of volumetric water content on soil
creep also has been investigated by both tests. In themulti-layer shear model test, artificial rainfall(60mm/h) was applied, and the rainwater infiltrated
into the top layer. In the direct shear test, water was
injected into soil from mode bottom. The following
results show how volumetric water content affects
the soil creep.

0.0

0.55

Fig. 11 Time history of displacement and theinverse number of velocity (Direct shear test)
12

Disp (mm)10

discussion
Because the speed of water infiltration was
different between the two kinds of laboratory
experiments, the failure time also showed differently.
From these results, it is confirmed that in thetertiary creep stage, the slope of the inverse number

5.0

8

4.0

6

3.0

4

2.0

2

1.0

0

0.0

1.0

2.0

Time （hr）

3.0

4.0
3.37

Reciprocal of Disp rate
1/v (hr/mm)

6.0

Disp
1/v

0.0

Fig. 12 Time history of displacement and theinverse number of velocity (Multi-layer
shear model test(10 layers))
128

SEE - Kyoto, Japan, Nov.18-20, 2020

VWC
1/v

1.0
0.8

0.2

0.6
0.4

0.1
0.0

0.2

0.0

0.2

0.6

1.0

1.0
0.8
0.6
0.4

0.1

0.2

0.0

ACKNOWLEDGMENTS
This research was supported by Grant-in-Aid for
JSPS Scientific Research (B).

1.2

0.2

0.0

0.0

0.82
Average above andbelow the shear plane

VWC
1/v

0.3

0.8

Time （hr）

Case2

0.4

VWC

0.4

Prediction of the time to failure can be possible
to improve more accurately by understanding not
only the ground surface but also the deformation in
ground.

0.1

0.2

0.3

0.4

0.5

Time （hr）

0.6

Reciprocal of Disp rate
1/v (hr/mm)

VWC

0.3

tertiary creep stage has been confirmed that it
was the same results as the previous research.
・ The deformation tended to increase rapidly when
the soil moisture increased to a high level.

1.2

Average above andbelow the shear plane

Reciprocal of Disp rate
1/v (hr/mm)

Case1

0.4

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1969, Mexico, 677–683.
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Failure Caused by Rainfall Using the Inverse Numberof Velocity of Surface Displacement. Landslides 1985,
22, 8-13_1, doi:10.3313/jls1964.22.2_8.
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Deformation Based on Compression Wave Velocities
in a Shallow Slope Surface Layer. Sensors 2019, 19,3406, doi:10.3390/s19153406.

0.0

0.55

Fig. 13 Time history of VWC and displacementrate(1/v) (Direct shear test)
6.0

Disp (mm)

5.0

4.0

4.0

3.0

3.0

2.0

2.0

1.0

1.0

0.0

0.0

1.0

2.0

3.0

Time （hr）
0.6

4.0

Reciprocal of Disp rate
1/v (hr/mm)

6.0

Disp
1/v

5.0

0.0

3.35

VWC

0.5

VWC

0.4
0.3
0.2
0.1
0.0

0.0

1.0

2.0

3.0

4.0

Time （hr）

Fig. 14 Time history of VWC and displacementrate(1/v)(Multi-layer
shear
model(10layers))CONCLUSIONS
Two kinds of laboratory experiments wereconducted to simulate the process of rainfallinduced slope failure. Predicting the time to failureusing the inverse number of velocity calculated by
Fukuzono's equation has been verified. The
conclusion is summated as following:
・ The method of prediction the time to failure timeby the inverse number of velocity(1/v) in the129

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ARCHITECTURAL PHOTOGRAMMETRY: A LOW-COST IMAGE
ACQUISITION METHOD IN DOCUMENTING BUILT ENVIRONMENT
Yohannes FIRZAL
Faculty of Engineering, Universitas Riau, Indonesia

ABSTRACT
Architectural photogrammetry, as a digital survey method requires photographic images that haveproduced by using a precision camera. This method in the particular the close-range photogrammetry has foundmore effectively used compare to other techniques such as laser scanning. This paper has aimed to show that theclose-range photogrammetry is as a practical way and low-cost image acquisition in architectural projects. By
applying a sequential two-step process method, capturing images in the field and using photogrammetry software
has conducted to generate from the point cloud to the architectural model. This model shows at a high level ofaccuracy detail from a part of the Sewu temple Indonesia where this research has conducted. Thus, this researchconcludes that using architectural photogrammetry is not only to obtain accuracy detail of architecture object incomplex nature but also as a low cost and effective methods.
Keywords: Architectural Photogrammetry, Photographic Image, Acquisition, Software

reconstructing of the built form. Therefore,
photogrammetry becomes an effective tool and a lowcost method [15]. Photogrammetry is not to change
the role of an architect, but a means in helping topresent the architecture [16].

INTRODUCTION
Photogrammetry is known as a digital image
processing method in orthoimages and image
mosaics. Photogrammetry has mostly used in the fieldofarchaeology[1].
However,
today’s
photogrammetry has widely recognized as analternative low-cost solution in the image processing[2] compare to laser scanning method [3].
Photogrammetry has applied in various disciplines[4] such as geoscience [5], structural engineering [6],zooarchaeology [7], heritage documentation [8] [9],archaeology [10], buildings inspection [11] andarchitectural representation [12].
There are groups of kinds in photogrammetry.
One of them is known as close-range
photogrammetry (CRP). The CRP has adopted fromthe aerial photogrammetry. This adaptation has aimed
to fit with a specific field such as architecture [13].
The adoption of this CRP gives a new possibility inthe digital image processing by using less equipment.
At least, CRP requires a camera, personal computerand scale bar to obtain a 3D image [14]. The
application of CRP in architecture is a non-intrusivetechnique in documenting and producing a 3D model.
Conventionally, the documenting and 3D image havecollected from 2D technics such as sketch,mechanical drawing that is following up to vector andmassing software.
In contrast, the photogrammetry sequentiallygenerates serial images to points cloud that canconduct in fast and accurate detail of the 3D object.
As digitally formed, a virtual model of CRP
represents not only existing built forms but also
possible used in the process of designing and

METHODS
The method in photogrammetry has organized insequential steps. In this paper, close-range
photogrammetry has conducted in a two-step process.
The first step is capturing photographic images fromvarious angles by using a DSLR camera and Drone.
This step is called the fieldwork phase that hasapplied to collect quality and geometric informationof the images such as position, size, contrast, filteringand shape. This first step has much more relied on theskill of the person who has operated the devices [17].
The second step is to arranged the images by applying
photogrammetry software to generate dense cloud
and texture data. The software is automaticallyinterpreting the semantic information of the image[18]. This computational phase is sequentially run in
the workflow of the software to obtain 3D images atthe end of the process.
RESULT AND DISCUSSION
The field operator must understand several
technical parameters. The most basic setting is multiimage restitution of a block of overlapping images
and collinearity equations [19]. The block images
must be arranged in between 60% to 80% overlaid on
each image. This block means that the degree ofoverlapping is correlating to effects on detail130

SEE - Kyoto, Japan, Nov.18-20, 2020

obtained.
Another fundamental parameter is image
distortion that is caused by reasons such as operator
position, lenses-used, amount of light, the angel of thedevice, and assistive devices. Therefore, in practicalways, the number of technical images captured are
significant not only to reduce the distortion [20][21]but also to contribute in generating the density of thepoints cloud [22].
As using a metric device, DSLR camera withmetric attributes is an ideal tool to produce technicalimages. However, it is necessary to set lenses-used toensure consistency of the focal length. Therefore, themetric camera calibration [23] [24] needs to control
continuously during the process of collecting images.
In practical ways, using the prime lenses or the fixed
lenses can avoid this control (fig. 1 left).
Slightly different on a drone, as having a nonmetrical camera, it is necessary to use a drone with ahigh-quality camera to ensure the image quality
produced [25]. A drone is a useful device to acquire
fast and accurate images that cannot be captured on
certain positions by DSLR camera such as at a highlevel place, large area, delicate angels [26] [27]. In
practical ways, besides numbers and overlapping
images, it is also necessary for a drone operator tohave a correct flight plan in avoiding an images
overabundance (fig. 2 right).

Fig. 2 Aligning Images (left) and Point Cloud Model(right) in Photogrammetry Software
The process has continued to build generating
texture, building tiled model, building digital
elevation model (DEM), and building ortho-mosaic(fig. 3 left). In every phase, the photogrammetry
software shows the preferences dialogue command
before continuing the processing that is giving achance to correct or adjusting during the process (fig.
3 right). The last phase in the photogrammetry
software is exporting the result and making the 3Dmodel available to other software such as BIM
platform [29] [30] [31].

Fig. 3 Ortho-mosaic Images (left) and Point Cloud 3D
Model (right)
From the whole process, this close-range
photogrammetry (CRP) shows more advantageousthan conventional methods. CRP can be conducted inlimited time to obtain a 3D model [32][33]. The
process in photogrammetry also can be accurately
recovered regardless of the size of the object [34].
As a comparison of the result, this research has
also used a laser scanner device on the same research
object (fig. 4 left). The laser scanner can produce asignificant volume of points cloud (fig. 4 right) andgenerates very great detail in fast and precision bothon an object and large area [35]. For this reason, thelaser scanner still the best device in documenting fielddata until today. However, a part of its advantage, theprice of this device is still high, and for maintaining
and routines calibration make laser scanner lesspractical and economical in reason. Therefore, it isnecessary to provide a low-cost alternative method
and also practice in used such as close-range
photogrammetry.

Fig.1 Using DSLR Camera (left) and Drone (right) in
Acquiring Image Mosaics
All images that have been acquired by cameras
then are generated by photogrammetry software.
There are several alternatives software which canprocess the image. The selection of suitable software
which is available both commercial and open-source
options based on computer skills and requirements[28].
This generating process is following the workflow.
The workflow starts with aligning images. In this firstphase, the interface software shows a position andorientation of images and builds a sparse of a point
cloud model. From here, this earliest model displays
two groups of arranged images on the main windows,
and sources images on the bottom pane (fig. 2 left).
The next phases are sequentially building dense point
cloud and building mesh (3D polygonal model) (fig.
2 right).

131

SEE - Kyoto, Japan, Nov.18-20, 2020[6] J. Han, K. Hong, and S. Kim, “Application of a
Photogrammetric System for Monitoring Civil
Engineering Structures,” 2012.
[7] A. Evin et al., “The use of close-range
photogrammetry in zooarchaeology: Creating accurate
3D models of wolf crania to study dog domestication,”
J. Archaeol. Sci. Reports, vol. 9, pp. 87–93, Oct. 2016,
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Fig. 4 Using Laser Scanner Device (left) and Point
Cloud Model (right)
CONCLUSION
The close-range photogrammetry (CRP) overs
architecture not only efficiency in time process, butalso giving alternative and valuable method in
obtaining a 3D model. From this paper, a combinationof DSLR camera, Drone and the photogrammetry
software shows the 3D architectural model produced
can be generated from a natural setting into a hightechnical accuracy detail.
However, due to less familiar with the workflow
of the software, the photogrammetry becomes lessused in the practice of obtaining information inarchitectural objects. The software also requires
mastery of more advanced software to further process
on architectural models that have produced to becompatible with other fields.
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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EVALUATION LIQUEFACTION AND LATERAL FLOWON THE PALU MW 7.5 EARTHQUAKE 2018 USINGSTANDARD PENETRATION TEST AT LOLU VILLAGE SITE
1,2

Dandung Sri Harninto1 and Widjoyo A. Prakoso2
Civil Engineering and Environmental, Indonesia University, Indonesia

ABSTRACT
Palu Mw 7.5 earthquake on 28 September 2018 caused extra ordinary geotechnical event in the world. Not
only building damage, tsunami caused by submarine landslide, but also the most devastating event was extreme
scale of flow liquefaction. In the area studied (Lolu Village), down slope flow movements were more than 150
meters, and in other location events were more than 1,000 meters. This must be extra ordinary phenomena ofliquefaction, which have never happened at other places.
Geological formation of Palu city has been formed from young alluvial fan sourced from mountain at east-westof the city. The formation was dominated by non-cohesive material and fully saturated due to very shallow groundwater table. Several standard penetration tests (SPT) were conducted after the earthquake both inside and outside
area of flow liquefaction. These data can be used to estimate thickness of liquefiable layer, movable soil layer, andsite characterization based on factor of safety against liquefaction used ratio cyclic resistance ratio (CRR) to cyclic
stress ratio (CSR).
This report will also discuss comparison data between inside flow and outside-flow area studied, withappreciation for non-commercial map application which can help to make superimpose before-after earthquake
map with quite good approximate. The report also will discuss site characterization by standard test of SPT
completed by soil gradation test at every layer of soil stratum which prone to highly potential flow liquefaction.
Keywords: Palu earthquake 2018, Liquefaction, Standard penetration test, CRR/CSR

of earthquake magnitude data in table fig. 3 from
BMKG, other ground accelerations record should besignificantly contributed for generating extreme
disaster, especially liquefaction. BMKG web site
(link : http://shakemap.bmkg.go.id) shown spread out
earthquake magnitude data (as table at fig. 3).
Recognize level of catastrophic occurred [2], USGS
reported a much larger peak ground motion
acceleration and reached magnitude of 0.7g and thisvalue might be possible (fig. 2).
Before the Palu 2018 earthquake -such asdevastating liquefaction in Niigata, Japan (1964) andAlaska, USA (1964)-, lateral spreading hadmagnitude of teen meters or even less and prompted
some differential settlement which generated tiltingof buildings or houses. However, Palu earthquake
generated not only common liquefaction occurred,
but also hundred meters either lateral spreading orsoil mass flow which brought all objects moving
downslope. Liquefaction itself so far has never madefatalities, but the liquefaction spawned thousand
fatalities, buried, and revolved them under deposit ofsand which changed from solid transformed to mud(liquid) for some period.
Palu City, Indonesia is located at complex tectonic
formation where collision of three plates comprising
Eurasian, Indo-Australia, and Philippines Sea.
Besides. There were at least three features of Palu city
associated to liquefaction disaster:

BACKGROUND
Mw 7.5 earthquake struck Palu and Donggala City,
Central Sulawesi, Indonesia on 28 September 2018,as consequence of releasing energy of Palu-Kore fault
where aligned west side of Palu City. This event
created several catastrophic disasters, and caused
large number of casualties, destroyed housings,
buildings, and many infrastructures such roads,
power lines, bridges, and water channels, etc.
Tsunami, ground shaking, landslide arrived almost at
the same time and the most extreme liquefaction
disaster ever on earth caused by earthquake.
Indonesia Meteorology, Climatology andGeophysical Agency [4] reported that epicenter of themainshock was about 72 km north of the city withdepth 10 km. Series of significant foreshocks (Mw >4.4) occurred four hours before and main shock
arrived with magnitude Mw 7.5, and it was followed
also by series of aftershocks (Mw >5.7) for the periodof 48 minutes since main shock. Epicenters ofsignificant foreshocks-mainshock-aftershocks were
documented sweep over area Palu City (fig. 1).
BMKG and JICA (Japan International
Corporation Agency) [1] have released time history
data of ground acceleration of mainshock from one
survival seismograph station near Palu City (Balaroa
Station) as fig. 2. Unfortunately, for other shocks
writer have no access to get them. If we studied series
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1. Palu city is just located across Palu-Kora fault,aligned from north to south of the city. This fault has
slip rate around 58 mm/year [13]. This tectonic
landscape will make Palu city become very
susceptible to high earthquake event (fig.4).
2. Palu low land mostly consist of young alluvium
formed by sediment transport from east and west sideof mountains [2]. In general, deposit mostly originate
from boulder, gravel, and sand with loose consistency.
Natural water stream called Palu river divide the city
at centre with slope of valley around 1-6 % (fig. 1).
3. The valley area is located at middle ofmountains; annual rain intensity is extremely low atmost 500-mili meter annually. Conversely, groundwater table was very shallow and there were somewater springs blown up ground surface and possibility
artesian spring. There was unlined water irrigation
canal system at eastern part of the city which has been
operating since 80’ (fig. 4), many experts alleged that
this canal had contributed significantly saturated sanddeposit at east side of Palu.

(figure 5). Sand boil structure is formed by sandejecta from sand deposit of underlayer as releasing
excess pore water pressure which brought somefraction of sand.

Fig.2 Time history of ground acceleration from
BMKG&JICA (2018) [1], [2]Fig.3 Magnitude of foreshock, mainshock andaftershock of Palu earthquake 2018 (BKMG,
2018)
As Bradley [12] reported that mostly downhill
area of unlined canal occurred lateral spreading(figure 4) with variation of magnitude. The crown ofslide was generally along irrigation canal, however,at uphill of canals were still good, no evidence eitherliquefaction or lateral spreading at all. However, inseveral areas such as at Petobo, Lolu Village and JonoOge (Sidera) where occurred in hundred-meter of
spreading and it engendered huge number ofcasualties especially at Petobo area (figure 4).
Basic mechanism could be the same for all
locations -even though the thesis is being still
debatable-. It started with fluidization of certain areaof sand deposit which initiated by liquefaction, withgentle slope of land commenced a long-distancelateral spreading caused by gravitational force. At theupper part of the area started to retrogressive collapse
which caused by lost their counterweight at toe,Fig.1 Geological landscape and epicenter of theearthquake [2].
LIQUEFACTION
Liquefaction is a phenomenon where saturated
soil deposit reduces stiffness and strength due to thegeneration of high excess pore pressures during
earthquake shaking. In certain condition the excess
could be the same with total overburden pressure(r u =1), and then effective pressure practiced zero, itmeans solid soil deposit for the time being behaves asliquid. Evidence of liquefaction in the event had been
onsite, we found number of sand boils footprint
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SEE - Kyoto, Japan, Nov.18-20, 2020

underwent high excess pore water pressure createdwater sprang out (seepage) huge volume of water on
surface and perhaps followed by land subsidence asconsequently of sand deposit contraction process.
Water mixed with fine sand-silt formed mud flow andsparked more destructive process. Finally, all erodedand debris material with very high-water content
glided to downstream or stacked create deposition
fill. The hypothetic mechanism has not firmed yet,many researchers are still working to discoveraccurate one.

spreading. The longest distance was 155-meters(yellow arrow line), and relative long distanceoccurred at northern part of area. At southern part,
displacement distance was average 70-meters. At
eastern part or upper hill, lateral displacement was
average 25-meters. Outside landslide area, many
objects were measured as well where lateral
movement with magnitude less than 10-meters.

Fig.4 Lateral spreading magnitude generated byliquefaction [12] and Disaster footprint
The above mechanism proposed by writer was
similar with Manson [2]. This suggestion is without
any contribution of breakage of confined aquifer.
Since JICA [9] suggested that there was contributedof confined aquifer breakage which maintenanceexcess pore water pressure kept high, this was argued
by Ishihara [11] as well. This hypothesis must bequite difficult to be proven, even though that will bepossibility happened. However, all the above mention
researchers have agreed including Watkinson andHall [5] and Bradley [12] that construction andoperation an unlined agriculture canal (fig. 4) had
played a large role in the slope failure. Yearly water
seepage from the canal increased height of water tableaccordingly saturated the underlaying loose soil layer
and caused of it making them liquefaction prone.
To know magnitude of lateral displacement, we
also have measured magnitude of lateral spreadinguse Google Earth Pro. At time being, we have been
only focusing at Lolu Village site with some reason
which will discuss later. We use figure published by
Bradley [12], to help describe magnitude of lateralFig.5 One of sand boil at Lolu Village site

SOIL INVESTIGATIONSThere must be distinct onsite sand deposit
characteristic to make as discussed above could
happen. Understanding of this mechanism isimportant since the flow liquefaction areas were mostdeadly compare to outside area. It should be valuable
for mitigation hazards purposes for next communal

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We have divided Lolu Village liquefaction area
into two area; called “flow area” and “affected area”.
Flow area is inside blue line (fig. 6) where lateral
spreading generated more than 10-meters till
maximum 153 meter and affected area is outsidewhere less than 10-meter. As discussed above aboutbasic mechanism argued by writer at long direction(east to west), the area has been alienated into several
zones (fig. 7): tension, retrogressive, raft-initiation,
stacking and stopper zone. For each zone, we haveconducted bore hole and taken SPT data to know
underlayer properties of sand deposit. Section BH10BH9 is movement direction (long section) and section
BH3-BH5 is perpendicular movement direction(cross section). For every hole, each 1.0-meter, wehave taken series of disturb sample to know grain size
gradation. This data will be used to recognized kindof soil and to determine fines content to calculate NSPT corrected caused of fine content or N1(60) value
for CRR7.5 calculation.

settlement planning. Lolu Village was exceptionalsite and thought as main mechanism of purely
liquefaction without any involvement from otherforce such as water inundating from breakage of main
water canal. Except Balaroa, other big lateral
spreading including Petobo, Jono Oge and South
Sibalaya, all of them involved huge volume of waterfrom breakage canal since top-crown of landslides
were also started at breakage of canal. Understandingat Lalo Village will be useful to recognize mechanism
for other areas, because magnitude moving objects atground surface were triggered purely by liquefaction.

LIQUEFACTION ANALYSISOther researchers have reported that liquefaction
could be re-occurred at the same location which
activated by different earthquake events Towhata [7].
We conclude that engineering properties of sanddeposit should be unchanged significantly and stillsusceptible to liquefaction if other parameter alsopreserved either magnitude of earthquake orsaturation of sand deposit.

Fig. 6 Distance of lateral spreading at Lolu Village
and Standard penetration test bore location
Point

BH-10

BH-6
BH-3
BH-1 PTPP
BH-4
BH-5

BH-9

stopper zone

stackingzone

raft-initiation zone

retrogressive zone

Fig. 7 Alienation of flow and affected area

Fig. 8 Grain size distribution at cross section area

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SEE - Kyoto, Japan, Nov.18-20, 2020

Fig. 9 Grain Size Distribution at Long Section Area

We will use post-event data to proceed a backanalysis of the event and supposed this method should
be still reliable. We use commercial software to
calculate susceptibility of liquefaction soil deposit
using SPT data called NovoSPT released by
Novotechsoftware, Canada. The software willcalculate safety factor of liquefaction by calculation
ratio cyclic resistance ratio (CRR) to cyclic stressratio (CSR).
This method was originally developed by Seedand Idriss [8] and are used to calculate a soil
resistance to liquefaction during earthquake loading.
The CSR can be defined as the seismic demandplaced on a soil layer by a given earthquake, and the
CRR can be defined as the capacity of the soil to resistliquefaction. The factor of safety, therefore, is equal
to the CRR/CSR ratio. The CRR can be tested either
using laboratory testing, preferably in quality,
undisturbed samples. However as this can sometimes
be difficult and expensive to obtain, it has become
popular to use the SPT, or more recently the CPT.
These are seismic parameter for calculation:
1. Earthquake Magnitude Mw: 7.5
2. Distance from fault (km): 80
3. Peak Ground Acceleration (PGA): 0.4 g
4. Cyclic Stress Ration (CSR): Simplified Seed
& Idriss
For SPT correction, we use as follow method:
1. Depth correction Cn: Liao & Whitman, 1986
2. Hammer energy level (%) Ce: 60
3. Borehole diameter (mm) Cb: 150
4. Sampling method Sc: Standard sampler
5. Rod length method Cr: Cetin et al.
For liquefaction analysis, we adopt ground waterlevel approximately 1-meter below surface, CRR7.5:
NCEER Workshop (1997) & Boulanger & Idriss(2014), Magnitude scaling factor (MSF): Idriss, 1997
(NCEER), Stress Reduction Factor (Rd): NCEER,
1997, Fines content correction for NCEER: Idriss &Seed, 1996 (NCEER Workshop).
We will not discuss regarding method used to
calculate and focus on result and trend of result togenerate some hypothetic mechanism, just selectproposal method which available in the software. The
results of calculation have presented at fig.10 dan fig.
11, for cross section and long section, respectively.
Locations of each bore hole please refer to fig. 6.

DISCUSSION
We have made a hypothetic liquefied/nonliquefied soil layering which interpreted based on SF(safety factor) liquefaction calculation result. Soil
deposit have been differed into two layers namely:liquefied layer and non-liquefied layer. Fig. 12 iscross section profile align north to south at raftinitiation zone, at northern side of flow liquefaction
must the deepest liquefied layer, and this wascorrespondent with the longest distance of lateral
movement (150-meter). Figure 13 is long section at
approximately in centre of longest path of lateral
deformation. Liquefied depth starts to be deeper
between BH#6 and J#07 JICA. This area is started
area for raft zone.
Generally, we found that soil deposits are nothomogeneous, there are some interbedded layers. Theinterlayers are denser than other layers (N-SPT
higher) and calculate as not liquefied layer. On
affected area, liquefied layer is only at upper layer
with thickness approximately 10-meter at most (refer
to BH#10, BH#6, BH#9, BH#3 and BH#5). Insideflow area, liquefied layers are much thicker thanaffected area, please refer to BH#4, BH#1PTPP andJ#7 JICA. BH#4 shows that liquefied layer around17-meter, and two other data show even deeper layer.
At BH#4 location, objects had been moved 80-meter(raft-initiation zone). At BH#1@PTPP: 120-meters(raft-initiation zone), at J#7JICA: 90-meters(retrogressive zone), and BH#4: 10-meters. These
distances were traced from overlay of two google
earth pro data: before (08/18/2018) dan after
earthquake (10/02/2018). Thicker liquefaction layer
has been initiated longer distance of lateral movement.
If at raft-initiation zone resides many objects suchas housing, infrastructure and so on with different
either size or weight, it will produce different
movement magnitude. Raft movement could make anundulance movement, rolling, rotating and generate
catastrophic disaster. From fig. 13 long section of thearea study, we have found something interest thatraft-initiation zone was just located over abandoned
lake-look or deeper valley. Many liquefaction areas
occurred at abandon ancient either lake or river [7].

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BH #4

BH #5

BH#1 PT
PP

BH#3

Fig. 10 Safety Factor Against Liquefaction at Cross Section of Area

BH #9

BH

BH#1 PT
PP

BH#10

J 07 JICA

Fig. 11 Safety Factor Against Liquefaction at Long Section of Area

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SEE - Kyoto, Japan, Nov.18-20, 2020

flow area (350m)
BH #3

Trenching #1

BH #4

BH #2,
PTPP

Trenching #2

BH #5

10 m

10 m

10 m

liquefied layer
10 mN

non-liquefied
layer

S

Fig. 12 Hypothetic Liquefaction Layers at Cross Section of Area
BH #10Flow area (850m)
20 m
BH #01_PTP

BH
#6
J 07
JICA

BH
#9
20 m

20 m
liquefiedW

non-liquefied
layerE
1,600mFig. 13 Hypothetic Liquefaction Layers at Long Section of Area
CONCLUSIONS(2003) which cause soil deposit at certain layers losttheir shear strength during liquefied and generatehuge magnitude of lateral spreading.
3. Even tough area had relatively the same
grade of slope and geological landscape, but in fact
generated different magnitude of lateral deformation
between flow area and affected area. This was caused
by variation formation of underlaying deposit whichcorrespond with thickness of liquefied layer.
4. Either figure 12 cross section or figure 13
long section of the area have studied, we have foundsomething interest related to base elevation ofliquefied layer that flow area was located on top of
look-like an abandoned former lake or water stream
or deep valley. As recorded by Towhata (2014) thatre-liquefaction area could be occurred at abandon
ancient lake or river, and from geological landscapethis hypothetic should be understood since alluvial
fan has formed this area.

We performed soil investigation including SPTgrain size analysis and conducted analysis by using
commercial software available to determine
susceptibility sand deposit at Lolu Village againstliquefaction. As history recorded that liquefaction
could re-occur at the same location, in that case weentitlement that post-event data still can be used forback calculation.
1. Based on standard penetration test (SPT)
post event data, both flow area and affected area wereliquefaction susceptible with variation of depth, byreference safety factor against liquefaction calculated
is less than one.
2. Fine grain contents were significant
according to grain gradation test, possibility that soil
deposits were interbedded between sand and silt-clay.
Existence of such kind of deposit will generate void
redistribution or water film as proposed by Kokusho
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With limited data taken would be too early to haveprecise relation between depth of liquefied layer anddistance of lateral movement. Nevertheless, frominitial data collected and the analysis discussed, we
have suggested basic mechanism and sitecharacteristic which make such a big liquefaction
flow occurred.
For further research, it will need denser bore holeand SPT data, especially inside flow area to havemore accurate of liquefied layer and preferably we areable to produce three-dimensional layering.
Moreover, if we can conduct SPT tests at moved
object track that must be much better, to know
underlayer sand deposit underneath. By this data, weshould be able to purposes a relation between
thickness of liquefied zone against magnitude oflateral spreading.

Agus Himawan, Widodo Yasin (2019), “TheSibalaya flowslide initiated by the 28 September
2018 MW 7.5 Palu-Donggala, Indonesia
earthquake”, Landslides DOI 10.1007/s10346020-01254-1.
[3] H. Benjamin Mason, Aaron P. Gallant, Daniel
Hutabarat, Jack Montgomery, A. Nicole Reed,
Joseph Wartman, Masyhur Irsyam, Widjojo
Prakoso, Didiek Djarwadi, Dandung S. Harninto,
Idrus Alatas, Paulus Rahardjo, Pintor Simatupang,
Aksan Kawanda, Rahma Hanifa (2019),“GeotechnicalReconnaissance:
The
28
September 2018 M7.5 Palu-Donggala, Indonesia
Earthquake Version 1.0”, Geotechnical Extreme
Events Reconnaissance Report.
[4] Indonesia Meteorology, Climatology andGeophysicalAgency,2018
http://shakemap.bmkg.go.id[5] Ian M. Watkinson and Robert Hall (2019),“Impact of Communal Irrigation of the 2018 Palu
Earthquake-triggered
Landslide”,
NatureGeoscience, Article 10.1038/s41561-019-0448-x.
[6] Ikuo Towhata (2008), “Geotechnical Earthquake
Engineering”, Springer.
[7] Ikuo Towhata et. al (2014),”Liquefaction in the
Kanto region during the 2011 off the pacific coastof Tohoku earthquake”, Soil and Foundations
2014, 54(4):859-873.
[8] I.M. Idriss, R.W. Boulanger (2006), “Semiempirical
proceduresforevaluatingliquefactionpotential during earthquakes”, Soil
Dynamics and Earthquake Engineering, 26 : 115130.
[9] JICA Study Team (2019), “Brief Explanation of“Nalodo” Assessment & Mitigation”, Handout
National Workshop on Joint Research, Assesment
Mitigation of Liquefaction Hazards on 9th
October 2019, Indonesia University.
[10] Kenji Ishihara (1993), “Liquefaction and Flow
Failure During Earthquake”, Geotechnique 43,
No.3, 351-415.
[11] Kenji Ishihara (2019), “Site Characterization of
Behavior of Sandy Soils”, Handout National
Workshop on Joint Research, Assesment
Mitigation of Liquefaction Hazards, Indonesia
University.
[12] Kyle Bradley, Rishav Mallick, Harisma
Andikagumi, Judith Hubbard, Ella Meilinda,
Adam Switzer, Nairong Du, Gilles Brocard, Dedy
Alfian, Benazir Benazir, Guangcai Feng, San-Ho
Yun, Jedrzej Majewski, Shengji Wei and Emma
M. Hill (2019), “Earthquake-triggered 2018 Palu

ACKNOWLEDGMENTS
We have many parties to thank for giving
encouragement of this report: our team in University
Indonesia especially Prof. Widjoyo A. Prakoso, Past
immediate Chairman of Indonesia Society for
Geotechnical Engineering (HATTI) Prof Masyhur
Irsyam and team, and GEER (Geotechnical Extreme
Events Reconnaissance), USA team including H. Ben
Banson, Aron P. Gallant, Jack Montgomery, Joe
Wartman, and Daniel Hutabarat for worth moment
along with all them for site reconnaissance joint
survey in Palu. We would like also to thank for many
valuable discussion and lecture from Kenji Ishihara,
Susumu Yasuda, Takeji Kokusho, Ikou Towhata andHisashi Furuichi (JICA) during they visited on site inPalu and series of lecture in Jakarta, Indonesia.

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Hanifa, Andi Kartawiria, Agus Himawan, Requel
Mikhail, Dandung Sri Harninto, Agus Muntohar,
Didiek Djarwadi, Widjoyo Prakoso, D.H.
Natawijaya, Hamzah Latief, M. Asrurifak, L.
Faizal, A. Sabarudin, Sigit Pramono, M. Daryono,
Ramli Nazir (2019), “Geotechnical Overview ofthe 2018 Indonesia Palu Earthquake”, Handout of
VII International Conference on Earthquake
Geotechnical Engineering, Rome, Italy, 17-20
June 2019.
[2] Aaron P. Gallant, Jack Montgomery, H. Benjamin
Mason, Daniel Hutabarat, A. Nicole Reed, Joseph
Wartman, Masyhur Irsyam, Pintor T. Simatupang,
Idrus M. Alatas, Widjojo A. Prakoso, Didiek
Djarwadi, Rahma Hanifa, Paulus Rahardjo, Lutfi
Faizal, Dandung S. Harninto, Aksan Kawanda,
141

SEE - Kyoto, Japan, Nov.18-20, 2020

Valley Landsliders Enabled by Wet Rice
Cultivation”, Nature Geoscience, Article
10.1038/s41561-019-0444-1.
[13] Mudrik
Rahmawan
Daryono(2016),“Paleoseismologi Tropis Indonesia (Dengan Studi
Kasus Di Sesar Sumatra, Sesar Palukoro-Matano,dan Sesar Lembang)”, Disertasi Doktor Program
Studi Sain Kebumian, Institut Teknologi Bandung.
[14] Mitsu Okmura, Kohei Ono, Utari S. Minaka,
Tadahiro Inoue, Ryuji Inaba, Rytaro Tanaka, Adi
Maulana, Ardy, Arsyad, Sabri, Purwanto,
Sukirman Nurdin (2019), “Liquefaction-induced
Large Scale Flowslide in Sibalaya –Investigation
to Underlying Mechanism-“, Handout ofInternational Seminar on Developing Mitigation
Technique for Liquefaction Disasters : Case
Study from Palu Earhquake 7.4Mw Sulawesi
Tengah, Hasanuddin University.
[15] Pepen Supendi, Andri Dian Nugraha, Sri
Widiyantoro, Chalid Idham Abdullah, Nanang T.
Puspito, Kadek Hendrawan Palgunadi, D.
Daryono and Samsul Hadi Wiyono, “Hypocenter
Relocation Of The Aftershocks Of The Mw 7.5
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Swarm Earthquakes Of Mamasa, Sulawesi,
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The Cone Penetration Test”, Canadian
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[17] Ross W. Boulanger and Stephen P. Truman(1996), “Void Redistribution in Sand Under PostEarthquake Loading”, Canadian Geotechnical
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[18] R.W. Boulanger, D.M. Moug, S.K. Munter, A.B.
Price and J.T. DeJong (2016), “Evaluating
Liquefaction and Lateral Spreading inInterbedded Sand, Silt and Slay Deposit Using theCone
Penetrometer”,
GeotechnicalandGeophysicalCharacterisation,
Australian
Geomechanics Society, Sydney, Australia, 81-97.

[19] Susumu Yasuda (2019), “Prediction ofLiquefaction and Countermeasure Against
Liquefaction”, Handout National Workshop on
Joint Research, Assesment Mitigation ofLiquefaction Hazards on 9th October 2019,
Indonesia University.
[20] Takaji Kokusho (2017), “Innovative Earthquake
Soil Dynamics”, Taylor & Francis Gorup.
[21] Takaji Kokusho, M.ASCE, Fumiko Ito, Yohta
Nagao, and A. Russel Green, M. ASCE (2012),“Influence of Non/Low-Plastic Fines andAssociated Aging Effect on Liquefaction
Resistance”, Journal of Geotechnical andGeoenvironmental Engineering ASCE, 138 (6),
747-756.
[22] Takeji Kokusho (1999), “Water Film in Liquefied
Sand and Its Effect on Lateral Spread”, Journal of
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[23] Takeji Kokusho and Tetsuro Kojima (2002),“Mechanism for Postliquefaction Water Film
Generation in Layered Sand”, Journal of
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[24] Takaji Kokusho (2003), “Current State of
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[26] Takeji Kokusho and Katsuhisa Fuji (2001),"Water Films Involved in Post-Liquefaction Flow
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1426th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STRESS ANALYSIS IN AUXETIC TWO-DIMENSION MATERIAL
WITH MODIFIED PEANUT PATTERN
Boonthum Wongchai
Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACT
Auxetic materials with negative Poisson’s ratio are alternatively used in structure engineering. For negative
Poisson’s ratio material, the transverse deformation is different from the conventional materials with positive
Poisson’s ratio. When the tensile force is applied on the axial direction, the transverse deformation of auxetic
material is expand, meanwhile the transverse deformation of conventional material is shrinking. In this research,
the auxetic two-dimension material with modified peanut pattern is used to study the effect of the pattern geometricshape and the equivalent density on the stress. A four-circle punched pattern has been designed with the original
peanut pattern. The equivalent density will be changed by varying their radius lengths. The results show that, thestress can be reduced by increasing the radius length. In the other word, by decreasing the equivalent density, thestress is decreased. The parabolic relationship between the radius length and the stress is found with high R-squarevalue.

Keywords: Auxetic material, Modified peanut pattern, Negative Poisson’s ratio, Stress analysis

shown in Fig. 2 was developed to reduce the stressconcentration at the sharp corner [1], [18].

INTRODUCTION
Auxetic materials with negative Poisson’s ratio
have recently received more attention in engineering
materials. The dominant properties of auxetic
materials differ from conventional materials. For
convention materials, the Poisson’s ratio is positiveand its transverse deformation is decreased byapplying the tensile force in the axial direction,
meanwhile the transverse deformation of auxetic
materials is increased [1]. For engineering advantage,
auxetic materials can be applied with various
engineering properties, such as, increasing of shear
resistance, energy absorption, crashworthiness,
indentation resistance, and energy dissipation ability[2]-[6].
In 1987, the first auxetic foam with negative
Poisson’s ratio was constructed [7]-[9]. Auxetic
materials have been developed by various
manufacturing. Nowadays, 3D printer is powerfuldevice to create the test specimen and the real workpiece. Two-dimensional and three-dimensional
auxetic materials can be manufactured using 3D
printer [10].
Auxetic materials are usually designed with reentrant shape and chiral shape as shown in Fig. 1 [11][15]. Beam members with bending dominatedtopologies are commonly used to analyze the auxetic
microstructures with these shapes [16]-[17]. Highstress concentration at the sharp corners in the reentrant and chiral auxetic microstructures is the main
problem in the axetic microstructure design. The
orthogonal elliptical hole pattern in solid material as

(a)

(b)

Fig. 1

Popular shapes of auxetic materials (a) reentrant shape (b) chiral shape.

Fig. 2The orthogonal elliptical hole pattern insolid material.

However, the elliptical pattern also induces highstress too. Hui et al., designed the peanut pattern as
shown in Fig. 3 with smoothed boundary. By using
143

SEE - Kyoto, Japan, Nov.18-20, 2020

finite element method, it has been found that the
maximum von Mises stress in the peanut pattern islower than the elliptical hole pattern.

L = d + 2r + s − 2 R + 2m

(2).
The area A of each peanut-shaped hole can writtenas
A= 2π r 2 +



ds
d
− 2 R 2 arcsin 2
 2( R + r ) d−2r 2 arccos 

2(
R
+
r
)



(3).

The equivalent density ρ * can be evaluated by

ρ * L2 − 4 A
=
ρs
L2

(4)

where ρ is the density of the base material [1].
The modified peanut pattern
The modified peanut pattern is developed fromthe original peanut pattern with r = 2.7 mm, R = 7.2mm, d = 10 mm, and L = 20 mm. The original peanutlattice is drilled by four-circle holes with radius a asshown in Fig. 4.

Fig. 3The peanut pattern [1].

However, to reduce of the equivalent density, theunit cell of the peanut pattern lattice can be drilledwith four circle holes. This research purposes to study
the effect of the circle hole radius length and theequivalent density of the lattice on the stress.
PATTERN DESIGN

Fig. 4The peanut pattern

The equivalent density of the modified peanut
pattern ρ1* can be written by

For peanut pattern as shown in Fig. 3, the centroid
distance s of the two large circles can be computed by=
ϕd2
s = 2 (r + R) − ,42

The modified peanut pattern.

ρ1* L2 − 4( A + π a 2 )
=
ρs
L2

(5)

where ϕ the equivalent density ratio. In this research,a is varied at seven values of r/4, r/3, r/2, 5r/8, 11r/16,
23r/32, and 3r/4.

(1)
where d is the centroid distance of the two small
circles. It has been assume that the lengths of theligaments separating neighboring holes are equal,m=m=m, and the side lengths, L=
L=
L, are1212also equal, The relation is defined as follows,

STRESS ANALYSIS
Finite element method is used to analyze the stress
144

SEE - Kyoto, Japan, Nov.18-20, 2020

radius a and the normal strain ε y , the maximum vonin the auxetic material. The PE high density is used
for base materials with Young’s modulus of 1.07
GPa, Poisson’s ratio of 0.41, tensile strength of 22.10
MPa, and mass density of 952 kg/m3. The model ofthe modified peanut pattern with 2 × 4 array is
generated using SOLIDWORKS with thickness of 20
mm. The stress in the auxetic material is computed
using SOLIDWORKS Simulation. The boundary
conditions are setting with the displacement u y in yMises stress for all cases are shown in Table 1.

direction at the top edge and fixed at the bottom edge
as shown in Fig. 5. The model is meshed using
triangular shell element with thickness of 20 mm.

Fig. 6The von Mises stress in case of a = r/4 andε y = 8% .

Fig. 7The maximum von Mises stress-strain curve.

Fixed
Fig. 5Boundary conditions.

The maximum von Mises stress σ von ,max iscomputed from the simulation by varying the normal
strain ε y in y direction at 4%, 8%, 12%, 16% and24%. For 2 × 4 unit-cells, the displacement u y can be
determined by

εy =

uy
4L

.

(5)

From Table 1, the σ von ,max and the ε y can be

RESULT AND DISCUSSION

plotted with linear trend line as shown in Fig. 7. For
cases of a > r/2, the results show that the slope of thetrend line less than the original peanut-shaped holepattern (a = 0). In the other word, for a > r/2, theσ von ,max can be reduced by increasing the radius a.

Fig. 6 shows the von Mises stress in the auxetic
material with modified peanut pattern for case of a =r/4 and ε y = 8% . For all cases, the maximum vonMises stress occurs at the top of the lattice as same as
the case of a = r/4 and ε y = 8% . By varying theTable 2 shows the percentage change of the145SEE - Kyoto, Japan, Nov.18-20, 2020

maximum von Mises stress compare with the original

peanut-shaped hole pattern.

Table 1. The maximum von Mises stressεyσ von ,max (MPa)a=0
a = r/4
a = r/3
a = r/2
a = 5r/8
4%
8.91
9.146
9.12
8.991
8.687
8%
18.03
18.47
18.42
18.14
17.5
12%
27.33
27.97
27.88
27.43
26.42
16%
36.81
37.65
37.51
36.87
35.44
20%
46.49
47.49
47.31
46.65
44.56
24%
56.36
57.51
57.27
56.18
53.78
Note: The original peanut-shaped hole pattern has the radius a = 0.

a = 11r/16
8.298
16.69
25.15
33.68
42.27
50.92

a = 23r/32
7.964
16
24.09
32.22
40.39
48.59

a = 3r/4
7.43
14.91
22.41
29.93
37.47
45.02

Table 2. The percentage change of the maximum von Mises stress compare with the original peanut-shaped holepatternεy

The percentage change of the σ von ,max (%)
a = r/4

4%
8%
12%
16%
20%
24%
Average

ϕ = 0.39

ϕ = 0.38

a = r/3

ϕ = 0.35

a = r/2

ϕ = 0.31

a = 5r/8

a = 11r/16
ϕ = 0.30

a = 23r/32
ϕ = 0.29

ϕ = 0.27

a = 3r/4

2.65
2.44
2.34
2.28
2.15
2.04
2.32

2.36
2.16
2.01
1.90
1.76
1.61
1.97

0.91
0.61
0.37
0.16
0.34
-0.32
0.35

-2.50
-2.94
-3.33
-3.72
-4.15
-4.58
-3.54

-6.87
-7.43
-7.98
-8.50
-9.08
-9.65
-8.25

-10.62-11.26-11.86-12.47-13.12-13.79-12.18-16.61-17.30-18.00-18.69-19.40-20.12-18.36

Fig. 8 shows the curve of the %σ von ,max versus the

The relationships between the percentage changeof maximum von Mises stress %σ von ,max and theradius a. All curves can be plotted with the parabolic
curve. The parabolic curves are very closed to theadjacent curves. Thus, the average of the percentagechange of the maximum von Mises stress %σ ave from
Table 2 is presented in Fig. 10.

normal strain in y direction ε y are linear trend linewith negative slope as shown in Fig. 8. By adding thenormal strain in y direction, the percentage change ofmaximum von Mises stress is reduced. The negativevalues of the %σ von ,max are occurred when the radiusa > r/2.

Fig. 9Fig. 8The percentage change of the maximum vonMises stress versus the radius a.

The %σ ave and the radius a can be plotted withthe parabolic equation with high R-square as shownin Fig. 10. When a > 1.46 mm (a > 0.54r), the values

The percentage change of the maximum vonMises stress versus the normal strain in ydirection.
146

SEE - Kyoto, Japan, Nov.18-20, 2020

versus the equivalent density ratio ϕ . The parabolic
curves are very closed to the adjacent curves. Similar
to the curves of the %σ von ,max versus the radius a, theof the %σ ave are negative. The %σ ave is rapidly
reduced by increasing a small value of the radius awhen a > 0.54r. Thus, by comparing with the original
peanut pattern lattice, the maximum von Mises stresswill be reduced when a > 0.54r. By adding the radiusa the maximum von Mises stress is decreased.

parabolic curve of the %σ ave and the equivalentdensity ratio ϕ is presented as shown in Fig. 12. The
values of the %σ ave are negative when ϕ < 0.33 . By
reducing of the equivalent density ratio, the averageof the percentage change of the maximum von Mises
stress is decreased. In the other words, by comparing
with the original peanut pattern lattice, the maximum
von Mises stress will be reduced when ϕ < 0.33 . For
the constant density of the base material, themaximum von Mises stress can be decreased by
reducing the equivalent density of the modified
peanut pattern lattice.
CONCLUSIONS

Fig. 10 The average of the percentage change of the
maximum von Mises stress versus the radiusa.

This study proposes the stress analysis in theauxetic two-dimension material with the modified
peanut pattern. The original peanut pattern is drilledwith four-circles holes. Finite element method is used
to analyze the von Mises stress in the auxetic material
by varying the circle radius and the normal strain in ydirection.
The relationship between the normal strain in ydirection and the maximum von Mises stressprecisely linear. The maximum von Mises stress is
added by increasing the normal strain in y direction
meanwhile the percentage change of the maximum
von Mises stress is decreased.
The average of the percentage change of the
maximum von Mises stress and the circle hole radius
can be plotted with parabolic trend line with high Rsquare. The average of the percentage change of the
maximum von Mises stress is decreased by adding
the circle hole radius. Thus, by increasing the circle
hole radius, the maximum von Mises stress is reduced.
The curve of the average of the percentage changeof the maximum von Mises stress versus theequivalent density ratio of the modified peanut
pattern lattice can be plotted with parabolic trend linewith high R-square. By adding of the equivalentdensity ratio, the average of the percentage change ofthe maximum von Mises stress is increased. For
constant density of the base material, the maximum
von Mises stress is increased by adding the equivalentdensity of the modified peanut pattern lattice.

Fig. 11 The percentage change of the maximum vonMises stress versus the equivalent density
ratio.

Fig. 12 The average of the percentage change of the
maximum von Mises stress versus theequivalent density ratio.

REFERENCES[1] Hui W., Yuxuan Z., Wanqing L., and Qing-Hua
Q., A novel two-dimensional mechanicalFig. 11 shows the parabolic curves of thepercentage change of the maximum von Mises stress147

SEE - Kyoto, Japan, Nov.18-20, 2020

metamaterial with negative Poisson’s ratio.
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148

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STUDY ON THE BEHAVIOR OF SANDBAR IN A RIVER CHANNELAT THE BABAMEGAWA RIVER
Junya Taniguchi1, Kazuya Watanabe2, Noritoshi Saito3 and Naoya Fujisawa4
1,2,3,4
Graduate School of Engineering Science, Akita University, Japan

ABSTRACT
A flood disaster was frequently happened resulting from local heavy rainfall in Japan. Many farmlands andhousing were damaged terribly in 2017 and 2018. High water level was observed in Babamegawa River which
was the largest Class B river. Embankment on the left bank at Babamegawa River was collapsed owing to scouring
was caused by sandbar at the downstream side. Like this, streamflow was greatly influenced by sandbar, so it was
important to understand behavior of sandbar. However, only one percent rivers were conducted Periodic Verticaland Cross-sectional Survey while all Class A river were conducted measurement mainly because there were too
many Class B river to measure. In this study, it was carried out that investigation using UAV to manage rivers
easily. Sandbar was taken the photographs from 150 m above the ground from September in 2017 to November in2018 and Sandbars’ area, length and width were calculated with SfM (Structure from Motion technique). These
data were investigated sharply when water level was decreased below ordinary. Moreover, it was important toremark width of sandbar as contraction of channel and loss of sandbar were needed to grasp for river management.
Keywords: Babamegawa River, sandbar, unmanned aerial vehicle, river management, water level

INTRODUCTION

This study proposed to evaluate quantitatively the
relationship between the behavior of sandbar andwater level using UAV at Babamegawa River.
Generally, behavior of sandbar was surveyed threedimensionally. In this study, surveying was carriedout two-dimensionally for simple river management.
The method will make it possible to examine easierand shorter than cross-sectioning. Firstly, aerial
photographs were taken using UAV. Then, thesephotographs captured SfM (Structure from Motion)technique. Finally, the behavior of the sandbar
grasped by measuring Sandbar area, length, and width.

Local heavy rain was caused flood damage in Julyand August 2017, May 2018 in Akita prefecture. Highwater level was observed in Babamegawa River.
Babamegawa River is the largest Class B rivers in
Alita prefecture. Such flood damage by local heavy
rain was happened in Japan [1]. Left hand side had
erosion due to this damage in Babamegawa River.
Sandbar in Channel was caused meandered flow. And
sandbar was caused transition in channel anddestroyed. It was important to grasp sandbar shapeand channel condition for channel management.
According to research by Ministry of Land,
Infrastructure, Transport and Tourism [2], all class A
rivers were implemented longitudinal and transverse
survey. On the other hand, class B rivers were
implemented only 1 percent of the whole. Because
class B rivers were many in Japan. River patrol
conducted once or nothing per week in class B rivers.
In previous studies, river management method
was proposed that numerical calculation using
universal model [3]. And authors calculated
recurrence calculation at the time of flood [4]. Data
filling was lacking in class B rivers. This study
proposed to maintain channel using UAV (Unmanned
Aerial Vehicle) Babamegawa River to take aerial
photographs. Many studies using UAV were
implemented in Japan. For example, it had surveyed
in inaccessible area using UAV [5]. In the coast, it
conducted nearshore topography monitoring by using
UAV [6]. UAV was also used in river. The method
was maintenance management system [7].

RESEARCH SUBMIT
Babamegawa River is the largest class B rivers.
Figure 1 shows that outline diagram of Babamegawa
Haollow

Fig. 1
149

The outline diagram of Babamegawa River.

SEE - Kyoto, Japan, Nov.18-20, 2020

were takenqFig. 2

State of the target area.

River. Akita It was originated from Babametake in
Gojome Town, Minami-Akita-gun, Akita Prefecture,
combines the surrounding tributaries into the
Hachirogata Reservoir, pours into the Sea of Japanthrough the Funakoshi channel. Drainage area was910.5 km2 and Main line flow path extending was
47.5 km [8].
This target was Bababegawa River at Hiranoshita
area. It was about 300 m length. Figure 2 shows thatstate of entire study area. This river width was about
30 m. The left-hand side was erosion due to heavy
local rain damage July and August 2017. In Figure 2,
there were intake for agricultural work in right handside curved parts. The flow path was narrowed by thecrossing structure so that water could be accumulatedeven at low water level. Therefore, sandbar was
generated near the intake. Even if one year had passed
since this damage, the situation of erosion damage
still could be seen.
Figure 3 was taken at the time of flood. The
revetment had collapsed like a landslide. In this study,
sandbar condition was left-hand side in Figure 2.
Figure 4 shows the situation of sandbar condition.
The water level used data from Kubo station locatedseveral kilometers downstream from the study area
shown in Figure 1.

Fig. 3 Babamegawa River at the flood. (August 28,2017).

Fig. 4RESEARCH MERHOD

Sandbar condition (August 22, 2018).

Were taken. The behavior of the sandbar formation
grasped from the aerial photographs. Sandbar area A,
length L, and width B was measured in this area. L
was maximum length of sandbar parallel to the flow
path. B was maximum length of sandbar
perpendicular to the flow path.

UAV Surveying
At the first, about 30 aerial photographs weretaken along a river from ground to 150 m height. Then,aerial photographs were taken to overlap 80 % of thephotographs horizontally and vertically. It was taken
aerial photographs from September 2017 toNovember 2018. This study was chosen 5 times incase of low water level and high-water level.

RESULT AND CONSIDERATIONS
Relationship between Water Level and Sandbar
condition.

SfM(Structure from Motion) Technique

Sandbar was formed on the river channel. Then,river embankment erosion occurred immediately
after water flow. Therefore, it was important grasping

At the first, it combined the aerial photographs
150

SEE - Kyoto, Japan, Nov.18-20, 20205
conditions

extendedectioning by Ueki and Watanabe in St.1 and St.2
on

4.5
4

η(m)

3.5
3

2.5
2

1.5
1

Figure. 5

2017/9/1

2017/8/1

2017/7/1

2017/6/1

2017/5/1

2017/4/1

2017/3/1

2017/2/1

2017/1/1

2016/12/1

2016/11/1

2016/10/1

0

2016/9/1

0.5

Water level fluctuation from September, 2016 to September, 2017.

5
4.5

4
3.5

η(m)

3
2.5

2
1.5

1

Figure. 6

2018/9/1

2018/8/1

2018/7/1

2018/6/1

2018/5/1

2018/4/1

2018/3/1

2018/2/1

2018/1/1

2017/12/1

2017/11/1

2017/10/1

0

2017/9/1

0.5

Water level fluctuation from September, 2017 to September, 2018.
river spreads so that A extends to 3124.4 m2 and B
extends to 26.3 m, and it occupied most of the flow
path. η was 0.81 m, which was lower than theordinary water level.
Figure 8 shows sandbar condition on August 3,
2018. A was 2947.0 m2 and B was 19.4 m, and from
September 11, 2017, A was 177.4 m2 and B was 6.9
m. η was 0.88 m, which was close to the ordinarywater level in the study area.
Figure 9 shows the condition of the sandbar on
August 22, 2018. The A decreased from 2947.0 m2 to1159.7 m2, and the flow path of the river was aminimum of 18.0 m, extending to about 60 % of theriver width. In addition, η was 1.18 m higher thanordinary water level, and the sandbar became smaller
because the water level rose due to rainfall.
Figure 10 shows the condition of the sandbar on
September 7, 2018. A decreased to 1153.1 m2, Ldecreased 2.0 m, and B decreased 1.5 m. In addition,
since the water level was 1.24 m and the water level
had risen from August 22, sandbar on the water
surface was decreasing. Sandbar on the water surface
decreased because the water level was rising due tothe rainfall on August 15 on August 22 andSeptember 7 when the field observation was

the form of Sandbar [10]. And, the hydrologicalconditions under which the form of sandbar changes
was confirmed by the experiments. It needs toexamine sandbar shape and flow near the flood peak.
Therefore, it was necessary consideration before andafter events such as precipitation. It was considered
the relationship between water level and sandbar
behavior. The water level was measured at Kubo
station. In Figure 5, a maximum of 4.51 m wasobserved on August 25, 2017. In addition, waterlevels exceeding the flood risk water level areobserved because of the effects of torrential rain.
Looking at Figure 6, a maximum water level of 4.63
m was observed on May 18, 2018, far exceeding theflood danger level. In addition, water levels as high as
the flood danger level were observed from August to
September. Akita Prefecture has a feature that thewater level rises from March to April because of theeffect of snowmelt.
UAV Surveying
A, L, and B were derived for the area enclosed by
the broken line shown in Figure 2. Figure 7 shows thecondition of the sandbar on September 11, 2017. The
151

SEE - Kyoto, Japan, Nov.18-20, 2020

examined.September

Fig.7

Sandbar condition (September 11, 2017).

Fig.8

Sandbar condition (August 3, 2018).

Fig.9

Sandbar condition (August 22, 2018).

Fig.10Sandbar condition (September 7, 2018).

50 m

Fig.11

Sandbar condition (November 28, 2018).

Fig.12
152

Sandbar condition (December 13, 2018).

SEE - Kyoto, Japan, Nov.18-20, 2020

examined.
Figure 11 shows the condition of the sandbar on
November 28, 2018. It again narrowed the channel ofthe river. However, A was 1665.2 m2, L was 132 m, B
was 16.7 m, and it was thought that the sandbar has
flowed out, and η was 0.89 m, which was the ordinarywater level.
Figure 12 shows the condition of the sandbar on
December 13, 2018. A, L and B could not be derived
because the sandbars to be observed were removed by
dredging.
Relationship between Water Level and Sandbar
Area
The relationship between sandbar area, length andwidth was examined. Figure 13 shows therelationship between water level and sandbar area.
When the water level was lower than the ordinarywater level (0.89 m), A increased rapidly, but
decreased gradually when the water level rose.
Figure 14 shows the relationship between sandbar
area and width. The B also increased as the A
increased. Therefore, it was considered that the B
greatly affected the A change.
In addition, Figure 15 shows the relationshipamong A, L and B. Compared data on August 3, 2018with November 28, 2018, B was decreased due todecreasing A, while L was unchanged. A was reducedby 1281.8 m2, so it was expected that sandbar was
drained by flood when water level was observed morethan 3.1 m such as August 15 and September 9, 2018.

Fig. 13

Relationship between water level andsandbar area.

Fig. 14

Relationship between sandbar width andarea.

Fig.15

Relationship among sandbar width, lengthand area.

CONCLUSIONS
It would be concluding as follows.
1) It was possible grasping the behavior of thesandbar on the water surface. It was possible tomeasure sandbar area, length, and width.
2) The sandbar was increased sharply when thewater level falls below 0.89 m. The sandbar was
decreased gently when the water level rises due
to rainfall.
3) Evaluation of sandbar width was important tograsp constriction of the channel and erosion ofsandbar in channel management.
UAV surveying has been able to quantitatively
evaluate the area of the sandbar on the water surface.
However, there are still issues such as not being able
to derive the volume of the sandbar and evaluating thesandbar under the water. Therefore, in the future, it isnecessary to understand the behavior of the sandbar
under the water surface by combining the crosssection survey and the UAV survey. In addition, it isimportant to examine the relationship between the
sandbar on the water surface and the sandbar under
the water surface.

ACKNOWLEDGMENTS
The author would like to thank the Akita
prefecture for their contributions to this study.

153

SEE - Kyoto, Japan, Nov.18-20, 2020

REFERENCES

Transactions, Japanese Geomorphological Union,
Vol.35, No.3, 2014, pp.283-294.
[6] Matsuba Y., Sato S. and Hadano K., Applicationof UAV based nearshore topography monitoring
to a sand-bypassed beach on Fukude-asaba coastin Shizuoka prefecture, Japan Society of Civil
Engineers Paper B2 (Coastal Engineering),
Vol.72, No.2, 2016, pp.853-858.
[7] Kawai Y. and Kubota A., Proposal of
maintenance management system for river using
three- dimensional model, IPSJ SIG Technical
Report, Vol.2015-IS-134, No.4, 2015.
[8] Akita Prefecture. Class B river Babame River
water system River maintenance basic policy,<http://www.pref.akita.lg.jp/pages/arghive/10601> (accessed on May 23, 2020).
[9] Kawakami M. and Watanabe Y. Hydraulicexperiments on influence of alternate bars to bankerosion, Japan Society of Civil Engineers Papers
A2 (Applied mechanics), Vol72, No.2(Appliedmechanics papers, Vol.19), 2016, pp.593-600.
[10] Kuwamura T. and Watanabe Y. Behavior of Bars
under flow condition between single-row bars anddouble-row bars, Hokkaido Research Institute ofDevelopment Public Works Monthly Report,
No.602, 2003, pp.3-14[1] Meteorological Agency. Meteorological case thatbrought about disaster (from 1989 to this year),<http://www.datajma.go.jp/obd/stats/data/bosai/r
eport/index_1989.html.> (accessed on May 23,2020).
[2] Ministry of Land, Infrastructure, Transport andTourism. River management status and issues,<https://www.mlit.go.jp/river/shinngikai_blog/s
haseishin/kasenbunkakai/shouiinkai/anzenkakuho/dai01kai/dai01kai_siryou2.pdf> (accessed on
May 23, 2020).
[3] Nomura K., and Watanabe K., Study on rivermanagement method using multipurpose
numerical calculation at small and medium-sized
river, Japan Society of Civil Engineers Papers G(Environment), Vol.70, No.5, 2014, pp.235-240.
[4] Ueki K., and Watanabe K., Study on levee
damage using numerical calculation in Babame
River, Conference of Tohoku Branch of Japan
Society of Civil Engineerings, 2017, (CD-ROM).
[5] Obanawa H., Hayalkawa Y. and Gomez C., 3D
modeling of inaccessible areas using UAV-based
aerial photography and structure from motion,154

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

PASSIVE BASE ISOLATOR FOR VERTICAL DIRECTION USING A
POST-BUCKLED SHAPE MEMORY ALLOY BEAM AND ITS
DYNAMIC PROPERTY

1

Atsushi Urakawa 1, Takumi Sasaki 2 and Hiroki Cho 3
Graduate school of Environmental Engineering, The University of Kitakyushu, Japan;
2,3
The University of Kitakyushu, Japan

ABSTRACT
Recent years, high-performance and compact vibration isolator has been demanded with the advancement ofprecise technology. Among various vibration isolators, a passive vibration isolator is the most commonly adopted
form due to its simplicity, stability and low cost. In the previous studies, the authors have proposed a simple andcompact passive vibration isolator for the vertical direction using a post-buckled shape memory alloy (SMA) beam.
This isolator achieved a low natural frequency assuring high static stiffness by utilizing the negative tangent
stiffness of a post-buckled SMA beam. It is expected that the appearance of the negative stiffness is related withthe phase transformation of a post-buckled SMA beam, however, the fundamental principle of the appearance andthe response for a reciprocating motion (vibration) have not been clarified. In this study, in order to clarify thesecharacteristics, the restoring force of a SMA beam subjected to reciprocating motion in its post-buckled state wasmeasured experimentally and predicted by the Finite Element Analysis in which the phase transformation of the
post-buckled SMA was taken in account. As the result, it was found that the restoring force converged to a certain
force when SMA was subjected to reciprocating motion; the negative tangent stiffness arose when the phase of
SMA transforms from Austenite phase to Martensite phase in compression process; SMA with small hysteretic
property in stress-strain curve is appropriate for an ideal isolation element. In future research, it is necessary tovalidate the performance of the isolator taking in account the phase transformation.
Keywords: Buckling, Shape memory alloy, Base isolation, Passive isolation, Nonlinear isolator

characteristic of a post-buckled tape-shaped Ti-Ni
based shape memory alloy beam (hereafter, called
SMA beam) in the previous study[4]. And also
proposed a passive vibration isolator using a postbuckled SMA beam and investigated its isolation
performance experimentally. In that study, theisolator achieved a low natural frequency of about 3
Hz and exhibited considerable isolation performance.
However, few studies have examined the restoring
force of a post-buckled SMA. Especially, theexpression principle of the negative stiffness, therestoring force of a post-buckled SMA forreciprocating motion, dynamic characteristic of apost-buckled SMA, etc., have not been clarified
although they are important for designing andpredicting the performance of an isolator.
The motivation of the study is to clarify
experimentally and numerically the fundamental
characteristic of a post-buckled SMA beam which isneeded for establishing the design guideline for an
isolator using a post-buckled SMA beam. In thispaper, we focused on following characteristics;(1)The response of a post-buckled SMA forreciprocating motion is experimentally andnumerically investigated and their properties arecompared qualitatively. (2)The expression principleof the negative stiffness is investigated numerically.

INTRODUCTION
For precise equipment, e.g. precision sensors,
precision processing machinery, etc., base isolation is
crucial technology for assuring their performance andreliability. In the base isolation technology, passive
vibration isolators are the most commonly adopted
form due to their simplicity, stability and low cost.
Basically, their effectiveness, i.e., isolation
performance and isolation frequency bandwidth,
relies on being able to achieve a low natural
frequency when supporting an isolated object, and a
low natural frequency can be achieved by supporting
an isolated object by a soft spring element. However,when they were applied to isolation in the verticaldirection, low stiffness can result in impracticallylarge static deflection due to the weight of the isolated
object. Consequently, a key trade-off in the selectionof a spring element for an isolator for verticaldirection is their low dynamic stiffness, which govern
the effectiveness of an isolator, versus their high static
stiffness, which is needed for static load bearing
capacity. In previous studies [1]-[3], in order torealize such stiffness, many nonlinear systems areproposed. One commonly used technique is making
use of nonlinear restoring force of a post-buckled
beam. Authors have detected the negative stiffness155

SEE - Kyoto, Japan, Nov.18-20, 2020

In section 2, the general overview of a passive
isolator, the restoring force of a post-buckled SMA
beam and the conceptual design of an isolator using a
post-buckled SMA beam are described. In section 3,
the restoring force of a post-buckled SMA beam forseveral reciprocating conditions is described. Section
4 concerned with the numerical investigation for the
restoring force of a post-buckled SMA beam, which
was obtained by FE analysis which considers thephase transformation of SMA material, and comparedwith the experimental results qualitatively.

imposed compressive displacement, that is , SMA
exhibits the negative tangent stiffness characteristic.
By utilising this characteristic, authors have proposeda vibration isolator using a post-buckled SMA beam.
The conceptual diagram of an isolator is shown in Fig.
3. This isolator incorporated a post-buckled SMA
beam, a coil spring and constraint elements that
constrained the isolated object to vertical motion.
The SMA beam was oriented vertically with one end
fixed to a base and the weight of the isolated object
acting at the other end. If the weight of the isolated
object is larger than the buckling load of the SMA
beam, the SMA beam will buckle. Then, if the spring
constant of a coil spring, which is installed in parallelto the post-buckled beam, was chosen so as only justto cancels the negative tangent stiffness of the postbuckled SMA beam, in principle, quasi-zero-stiffness(QZS) will be achieved and ideal isolation would be
realized.
For designing and predicting the performance of
this isolator the static and dynamic property of a postbuckled SMA beam is the essential property.
However, studies for these properties is insufficientso far. Then, in the following sections, the restoring
force of SMA beam simulating the deflection when it
is used for the isolator are examined experimentallyand numerically.

OVERVIEW OF A POSSIVE VIBRATIONISOLATOR AND AN ISOLATOR USING A
POST-BUCKLED SMA BEAM
Overview of a Passive Vibration Itolator
Figure 1 shows the most fundamental model of apassive vibration isolator for the vertical direction.
An isolated mass is supported by a linear spring anda linear dashpot. Considering the frequency responseof the vibration transmissibility between an isolated
mass and base vibration for the vertical direction, theeffectiveness of the isolator relies on being able toachieve a low natural frequency. However, low
stiffness can result in impractically large static
deflection due to the weight of the isolated object.
This dilemma can in principle be solved by adopting
a nonlinear isolator that exhibits high stiffness when
loaded statically and low stiffness in relation to small
oscillations about the static equilibrium position. Oneof tequnique to realize such nonlinearity is making
use of nonlinear restoring force of a post-buckled
beam.

22

Static restoring force [N]Compression process

m

20

18

Shape recovery process

16

k

c

0

Fig. 2y(t)Fig. 1

5
10Longitudinal displacement ratio x / L [％]Static restoring force of a post-buckled SMA
beam

The most fundamental model of a passive
vibration isolator for the vertical direction
Constraint
element

Isolated
objectStatic Restoring Force of a Post-Buckled SMA
Beam and Vibration Isolator Using a PostBuckled SMA Beam
Coil spring

Authors have reported that the static restoring
force of a SMA beam, which is subjected tocompressive external displacement at both ends of thebeam for longitudinal direction , exhibits the negative
tangent stiffness in its post-buckled state. Fig. 2
shows one of the measured static restoring force of apost-buckled SMA beam. As shown in the figure, thestatic restoring force decreases by increasing the

BuckledSMA beam

Base
Fig. 3156

Conceptual diagram of a vibration isolator
using a post-buckled SMA beam

SEE - Kyoto, Japan, Nov.18-20, 2020

[Exp. 1]
Impose 9mm longitudinal displacement
firstly, and subsequently impose 10 times
reciprocating displacement of which amplitude wasincreased by 0.2mm per one reciprocation. After thereciprocation, imposed displacement was recovered
to the original position (0mm). By this experiment,
the restoring force behaviour of the SMA beam when
the amplitude of an isolated object was varied could
be simulated.
[Exp. 2]
Impose 10mm longitudinal displacement
firstly, and subsequently let the displacement recoverto (a)3mm, (b)4mm or (c)5mm, and finally impose
500 times reciprocating displacement of which peakto-peak amplitude was 2mm. After the reciprocation,
imposed displacement was recovered to the original
position (0mm). By this experiment, the restoring
force behaviour of the SMA beam after onece large
displacement was imposed.
The solid line in Fig. 4(a) shows the measured
restoring force for Exp. 1. The dashed line in the
figure shows the restoring force for one timereciprocation for comparison. Fig. 4(b) is themagnification of Fig. 4(a). From the figure, it isconfirmed that the magnitude of restoring force drops
drawing a hysteretic loop while the reciprocating
motion was imposed. Also, it is confirmed that themagnitude of hysteretic loop get larger when theamplitude of the reciprocation was large. The lower
limit of the dropping restoring force will beconsidered in the following section.

EXPERIMENTAL INVESTIGATION FOR THE
RESTORING FORCE OF A POST-BUCKLEDSMA BEAM
In order to apply a post-buckled SMA beam to avibration isolator, it is necessary to examine therestoring force property of a post-buckled SMA beam
when it is subjected reciprocal motion. In this section,
the restoring force of a post-buckled SMA beam
when it is subjected reciprocal motion is examined
experimentally.
Figure 3 shows schematic view of theexperimental setup. Titanium-Nickel based SMA
beam, with specifications summarized in Table 1, wasused for the experiment. Both ends of SMA beam
was clamped by stainless steel plate. One end was
fixed to the base rigidly. Another end was supported
by a linear guide and a liear slider which correspondto a constraint element and a device for imposing
longitudinal external displacement, respectively. The
restoring force of the SMA beam for the original
longitudinal direction was measured by a load cell.
Since the moving speed of linear slider was controlled
to 0.1mm/s, quasi-static restoring force was measured.
Stainless plates at both ends had a electrode and the
SMA beam could be heated by Joule heat that was
generated by applying electric current directly to the
SMA beam. The temperature of the SMA beas wasmonitored by a thermocouple set at the middle of the
SMA beam (omitted in Fig. 3) and kept to 30°C by
coutrolling the electric current with a PID control
system.
In order to simulate the restoring force of the
SMA beam when it was used to a base isolation
system, following experiment was conducted.

BuckledSMA beam

Fixed
base
Fig.3

Current
supplyLoadcellLinearguide
Fig.4(a) Measured restoring force of the SMA beamin reciprocating motion [Exp. 1]

Linear slider

Schematic view of the experimental setup

Table 1 Specification
experiment
Material
compositionHeat
treatment
condition
Dimension

of

SMA

used

in

the

Ti-50.2at%Ni
Temperature
Time
Cooling condition
Width
Thickness
Length753 [K]40 [min]Air cooling
5.5 [mm]
0.5 [mm]
110 [mm]Fig.4(b) Magnification of Fig. 4(a)157

SEE - Kyoto, Japan, Nov.18-20, 2020

Figure 5 shows the measured restoring force forExp. 2. Marks of 〇, □ and ◇ represent the restoring
force of shape recover condition of (a)3mm, (b)4mm
and (c)5mm, respectively. The dashed lines show theapproximate line when the restoring force inreciprotating process were approximated by the linear
function. From the figure, it is confirmed that therestoring force in reciprocating motion differeddipending on the start point of recprocating motion,
while the restoring force on compression process andshape recover process of all conditions were the same
except in reciprocal motion. The gradient of thedashed line corresponds to the approximative tangent
stiffness in reciprocating mosion and that of shaperecover doncition (a)3mm, (b)4mm and (c)5mm was
0.175 N/mm, 0.132 N/mm and 0.105 N/mm,
respectively. From the figure it is confirmed that theapproximative tangent stiffness also differeddepending on the start point of recprocating motion
and it didn’t exhibit the negative tangent stiffness but
the positive tangent stiffness. These properties, therestoring force and the tangent stiffness varies
depending on reciprocational condition, areconsidered not to be appropriate for the use for an
isolator, because the isolation performance varies
depending on the vibration condition. However, in alater section, the appropriate material specification
desired for the SMA for an isolator will be clarified.

length and 0.43mm in thickness was used. Both endsof the beam was rigidly fixed except the degree of
freedom for longitudinal direction at one end was set
free. The material property (stress-strain curve) of
SMA was approximated by piecewise linear property
composed of four linear lines as shown by solid line
in Fig.6. The SMA beam was modelled by using
three dimensional laminated solid-shell element inorder to accurately figure out the stress and the phasetransformation of inner part of SMA material.

Fig.6

The effect of phase transformation of SMA beam
on appearance of the negative tangent stiffness in its
post-buckled state was investigated. In this anaysis
two types of material, with specifications summarizedin Table 2, was used, where  1 ,  2 ,  3 and  4 ofmaterial (a) represent the stress at the intersection
point of I, II, III and IV, respectively. E ,  and 
represent the gradient of line (1), the difference ofstrain between intersection point of I and II, and also
III and IV and Poisson’s rat io, respect ively.
Deformation process on the line (1) can be regarded
as deformation process of austenite phase, and that ont he line (2) is deformat ion process of pahsetransformation from austenite phase to martensite
phase. Also, deformation process on the line (3) canbe regarded as elastic deformation of martensite
phase, and that on the line (4) is deformation processof pahse transformation from martensite phase toaustenite phase. Material (a) approximates a

Restoring force [N]16

3–5[mm]
4–6[mm]
5–7[mm]Fig. 55
Displacement [mm]in numerical

Efect of Phase Transformation of SMA on
Appearance of the Negative Tangent Stiffness

18

14
0

Stress-strain curve used
analysis10

Measured restoring force of the SMA beamin reciprocating motion [Exp. 2]

NUMERICAL INVESTIGATION FOR THE
RESTORING FORCE OF A POST-BUCKLEDSMA BEAM

Table 2In this section, the post-buckled properties of
SMA beam is numerically investigated. On the
numerical analysis, Finite Element Analysis was
executed by using ANSYS 19.0.

Specification of SMA material used in the
numerical analysis

Material (a)Material (b)1  2000 [MPa] 2  2800 [MPa] 3  1000 [MPa] 4  50 [MPa]E  20 [GPa],   0.05 ,   0.3

1  200 [MPa] 2  280 [MPa] 3  100 [MPa] 4  5 [MPa]Analytical ModelOn the numerical analysis, the SMA beam ofwhich dimension was 7.2mm in width, 50mm in
158

SEE - Kyoto, Japan, Nov.18-20, 2020

matereial property of Ti-Ni based SMA, whilematerial (b) is the material of which pahsetransformation is suppressed by setting large stressfor  1 .
Figure 7 shows force displacement curve of postbuckled beam when 5mm displacement was imposed
for longitudinal direction. Imposed displacement(horizontal axis) and restoring force (primary verticalaxis) are normalized by the length of the beam and thebuckling load obtained from linear buckling theorem.
The solid line and the dashed line show the restoring
force of material (a) and (b). Marks 〇 and △ show
the volume fraction of martensite phase incompression process of material (a) and (b),respectively, by secondary vertical axis. From thefigure, it is confirmed that the restoring force ofmaterial (a) exhibit negative tangent stiffness in thedisplacement range beyond 4% in compression
process and within 4% in shape recover process. Also,in compression process of material (a), the negative
tangent stiffness appears as phase transformationfrom austenite phase to martensite phase getadvanced, while the restoring force of materical (b)exhibits positive stiffness in all displacement range inthe figure and exhibit no phase transformation. Fromthese results, it is considered that the appearance ofthe negative tangent stiffness deeply related to thephase transformatio of the SMA.

to 0.8mm, and subsequently impose reciprocating
displacement of which amplitude was 0.5mm for 500
times. After the reciprocation, imposed displacement
was recovered to the original position (0mm).
Material (a) in table 2 was used for the analysis.
Figure 8 shows the restoring force obtained inAnalysis 1. Marks ◇, △, 〇 and □ correspond to
the restoring force of reciprocating dondition of (a),(b), (c) and (d). Figure 9 shows the magnisication of
Fig.8 at reciprocating condition (d). From the figure,it is confirmed that the magnitude of restoring force
drops while the reciprocating motion was imposed.
Also, if the number of reciprocating time wasincreased more than 5000 times, it will not lowered
than that of 4999 times.

Restoring force ratio P /Pcr

[–]

1.2

1

0.8
: 10 times reciprocation: 50 times reciprocation: 500 times reciprocation: 4999 times reciprocation
0.6
0Fig. 82
4
6Displacement ratio x/ L [％]8

Restoring force of the beam in reciprocating
motion [Analysis 1]

Restoring force ratio P /Pcr [ – ]

1.02

1

0.98

0.96

Fig. 7Force displacement curve and volume
fraction of martensite phase

6.5

Fig. 9

Restoring Force in Reciprocating Motion

77.5
8Displacement ratio x/ L [％]8.5

Magnification of Fig. 8

Figure 10 shows the restoring force obtained inAnalysis 2. From the figure, it is confirmed that themagnitude of restoring force rises while thereciprocating motion was imposed. Also, if thenumber of reciprocating time was increased morethan 501 times, it will not lowered than that of 500
times.
From these results, it is confirmed that themagnitude of restoring force drops or rises while thereciprocating motion was imposed in compression
process or shape recovery process, respectively, andconverges to a certain force. This phenomenon
qualitatively corresponds to the experimental result

In order to investigate the restoring force inreciprocation motion, following analysis was
executed.
[Analysis 1] Impose 4mm longitudinal displacement
firstly, and subsequently impose reciprocating
displacement of which amplitude was 0.25 mm for(a)10 times, (b)50 times, (c)100 times and (d)4999
times. After the reciprocation, imposed displacement
was recovered to the original position (0mm).
[Analysis 2] Impose 4mm longitudinal displacement
firstly, and subsequently let the displacement recover
159

SEE - Kyoto, Japan, Nov.18-20, 2020

Restoring force ratio P /Pcr [ – ]Restoring force ratio P /Pcr

[–]

1.1

1

0.9

0.8
0

2
4
6
Displacement ratio x / L [％]

1

0.8

0

8

5
10
Displacement ratio x / L [–]Fig. 10 Restoring force in reciprocating motion in
shape recovery process [Analysis 2]

Fig. 11 Restoring force of the beam with small
hysteretic materialrefered in the last section. The restoring force in Fig.8
doesn’t draw loop, which is different fromexperimental result, however this is because that thereciprocating amplitude of numerical analysis was
smaller than the experiment and stress-strain curve
was approximated by piesewise lines.

CONCLUSIONSThis paper has investigated the dynamic property
of a post-buckled SMA beam experimentally andnumerically. The restoring force of Ti-Ni based SMA
beam exhibited negative tangent stiffness for one timebuckling deformation, however, it exhibited positive
stiffness when reciprocal motion was imposed in
post-buckled state. The restoring force varied while
in reciprocation and converged a certain force. The
restoring force of a beam with small hystereticmaterial exhibit almost constant tangent stiffness in
displacement range beyond 5%.
For a highperformance passive isolator, realizing SMA material
which has such small hysteretic property needs to beaddressed in future studies.

Desired specification of the SMA for an isolator
The restoring force characteristics refered inprevious sections were not appropriate for a highperformance isolator due to positive stiffness
characteristic in reciprocating motion.
The
appearance of positive stiffness is thought to be themost likely cause of the difference of the gradient of
restoring force among compression process and shaperecovery process, that is, hysteretic property of SMA.
Then, the restoring force of a beam with small
systeresis material was calculated. The specificationof the material is summarized in table 3.
Figure 11 shows the restoring force of the beamwith material (c). The restoring force exhibits
negative tangent stiffness in the displacement range
beyond 4% and almost constant stiffness (gradient of
the curve) could be obtaind in the displacement range
beyond 5% even in compression process or in shaperecovery process. This kind of property is appropriate
for the system shown in Fig. 3, since desired isolation
performance would be obtained regardless ofvibration condition.

ACKNOWLEDGMENTS
This work was supported by JSPS Grant-in-Aid
for Scientific Research (C) number 18K04025.
REFERENCES[1] Ibrahim R. A., Recent advances in nonlinear
passive vibration isolators, Journal of Sound andVibration, 314, 2008, pp. 371-452.
[2] Sasaki T, Waters T. P., Analysis of a vibration
isolation table comprising post-buckled -shaped
beam isolators, Journal of Physics: Conference
series, Vol. 744, 2016, No. 1: 1-8.
[3] Chiyojima T. and Sasaki T., Development of apassive vibration isolator using a post-buckled shaped beam (Improvement of the isolation
performance by considering mode shapes of a shaped beam), Proc. of Asia Pacific Vibration
Conference 2017, 2017, pp. 11-16.
[4] Sasaki T. and Kimura Y., Experimental Study on
a Passive Vibration Isolator Utilizing Dynamic
Characteristics of a Post-Buckled Shape Memory
Alloy, Proc. of Asia Pacific Vibration Conference
2019, 2019, pp. 1-6.

Table 3 Specification of a material of which
hysteresis in stress-strain curve is small
Material (c) 2  280 [MPa],1  200 [MPa] , 3  275 [MPa] , 4  195 [MPa]E  20 [GPa],   0.05 ,   0.3

160

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

MRT JAKARTA: A SHORT EVALUATION AFTER 1 YEAR OF
OPERATION
Aleksander Purba1
Engineering Faculty, University of Lampung, Indonesia 35145

1

ABSTRACTJakarta has been planning the MRT project since the 1980s, but it has been canceled several times for anumber of reasons, including the economic crisis in 1990s. The implementation of sustainable Jakarta MRT entails
coordination among different sectors and levels of government. An increase in public transport would be more
realistic if accompanied by disincentive mechanisms for users of private vehicles on the one side and incentives
for public transport users on the other. Like it or not, the city’s next job is to change people’s behaviours throughboth educative and repressive measures. Within the framework of an integrated MRT development, thegovernment should start thinking about reliable feeders connecting MRT routes to settlement centres. In addition,pedestrian paths linking shelters to central business districts and offices need also be improved. In the long term,
the growth of settlements and new activity centres in the city’s master plan needs to be integrated into the MRT.
Building affordable apartments downtown to shorten residents’ commuting journeys is unavoidable. As
experienced by such cities, the built environment has significant impacts on the activity-travel behavior of private
housing residents, partly because they could self-select into the types of residential environment matching theirtravel preference.
Keywords: MRT Jakarta, Evaluation, Integrated, Travel behaviorpurchased from the ticketing machines or ticket
offices located at every station. The Jakarta MRT is
expected to stretch across over 108 kilometres,
including 26.9 kilometres for the red line (from Lebak
Bulus to Kota) and 87 kilometres for the yellow line(from Cikarang to Balaraja).
Otherwise, during Covid-19 emergency period
the number of MRT passengers jumped significantly.
Referring to report on Tuesday, March 17, there were
only 32,000 passengers from regularly 100,000 perday. It went further down to 28,000 on Wednesday
and 24,000 on Thursday. The policy limits thenumber of MRT passengers on board of one car for
only 60 people or 360 per train set of six cars or lessthan 30% of capacity. This paper focuses on theevaluation of projected and actual ridership of MRTJakarta after one year of operation and after theheading, respectively.

INTRODUCTION
The year 2019 has been marked by importantmilestones in the modernization of the country’s
railway transportation system with the inaugurationof the first ever rail-based mass rapid transportation
system and the development of the first high-speed
train. On March 23, President Joko “Jokowi” Widodo
inaugurated Jakarta’s MRT system, marking a new
era in Indonesia’s railway transportation system.
After almost a year since it began commerciallyoperating, the Jakarta MRT has become an
importation means of transportation for Jakarta
residents. Phase 1 connects Lebak Bulus to Bundaran
HI along 20.1 kilometres and consists of 13 stations(7 elevated stations and 6 underground stations). The
Indonesian Ministry of Transport approved this planin September 2010 and invited tenders. Construction
began in October 2013. Phase 1 was opened for freeservice on 24 March 2019. Commercial service began
on 1 April 2019. Phase 1 is expected to serve 212,000
passengers per day. This expected capacity may be
maxed out to 960,000 per day. The 20.1 kilometres
distance is covered in under 30 minutes. Within its
first month of operations, 82,000 passengers used theline daily. The charged fare for a trip on the MRT
starts at Rp3,000, increasing by Rp1,000 for every
station passed. A trip spanning the entire existing line
in 2019 would cost a passenger Rp14,000.
A refundable Rp15,000 deposit is required topurchase a single journey ticket, in addition to fares
required for the journey. The Jakarta MRT employs acashless fare payment system. A dedicatedcontactless smart card known as the 'Jelajah' can be

A CASE STUDY: MRT JAKARTA
The Jakarta mass rapid transit (Indonesian: moda raya
terpadu Jakarta or Jakarta MRT is a rapid transit
system in Jakarta, the capital city of Indonesia. The
system is operated by PT MRT Jakarta (Perseroda), amunicipally owned of the city of Jakarta. Jakarta is
the capital city of Indonesia, harbouring 10 million
inhabitants, one-third of the population of Greater
Jakarta. It is estimated that over four million residentsof the surrounding Greater Jakarta area commute to
and from the city each working day. Transport issues
have increasingly begun to attract political attention
and it has been foreseen that without a major
161

SEE - Kyoto, Japan, Nov.18-20, 2020

transportation breakthrough, the city will havecomplete traffic gridlock by 2020, as illustrated inFig. 1.
20,000,000

6,980

18,000,000
6,975
16,000,000
6,970

14,000,000
12,000,000

6,965

10,000,000
6,960

8,000,000
6,000,000

6,955

4,000,000
6,950
2,000,000
0

6,945

2011

2012

2013

road length (km)

2014

2015

2016

2017

registered vehicle (unit)

Fig. 1

Relationship between road length andregistered vehicle
Previously, public transportation now mainly consistsof the TransJakarta bus rapid transit system with alength of 230 kilometers and phase 1 of the MRT
project was funded through a soft loan (Rp 16 trillion)
from JICA with a 30 years tenure and 0.25% interest
per annum. Trial run conducted since December 2018
until February 2019.
Besides serving as trial run and form of machinist
familiarization prior to full operation, the parallel trial
run is also part of the company's campaign toencourage the people of Jakarta to use public
transportation modes in order to reduce congestion.
Key performance and map of the line are shown in
Table 1 and Fig. 2, respectively.

Fig.2

URBAN REGENERATION

Table 1 Key performance of the line
Length network
Number of stations
Distance between
stations
Track width
Travel time
Headway
Operation hours
Targeted no ofpassenger
Number of train
Electricity
Train operation
systemSignaling system
No of employeesLine map of MRT Jakarta

As perform by the MRT operating experience in othercountries -though different in every city and countryMRT Jakarta is also designed to support the region's
economy and improve the quality of life. Table 2
shows several of them, including the ongoing and will
be implemented. Based on long experiences of suchcities, it is undeniable that the development of MRT
will lead to job losses since the city’s transportation
sector is more capital-intensive by nature. Thus thegovernment needs to explore every avenue dealing
with the process of adaptation and the transfer oftransportation sector employers in stages throughcapacity building, capital assistance and provision of
new jobs

20.1 km130.8~2.2 km
1,067 mm
± 30 minutes
5 minutes
05:00~24:00
130,000 person/day
16 (include 2 sets forreserve)
60 MVA
Automatic train operation
Communication based
train control
520 (2018)162

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 2 The city’s potential regeneration

willingness to use the metro is higher than the
gentrifies.
At city level, for the metro to attract more TOD
residents it is necessary to expand the metro influence
area beyond walking distance destinations by
integrating with other existing modes of travel suchas bicycles, IPT and buses [3]. Based on the Regional
Regulation of the DKI Jakarta Provincial
Government No. 9/2018, the Company is granted theright to conduct property development andmanagement at stations, station areas and depots aswell as concession rights to manage and develop land,buildings both underground and above ground in allareas in stations and depots and in outside the stations
and outside the depots in a certain area to becommercialized through ways of being leased or
making cooperation to create potential income otherthan direct income from ticket sales. In accordancewith Governor Regulation No. 140/2017, MRT
Jakarta is assigned as the main operator included
developing TOD along the line with the following
functions: to coordinate land and or building owners
in regional planning and development, to encourage
efforts to accelerate the development of TOD
infrastructure and facilities in accordance with thecity design guidelines, to coordinate the land and or
building owners, tenants and other stakeholders in the
TOD area management, maintenance andsupervision, andto monitor the TOD area
development. Referring to Hong Kong experienced,
the built environment has significant impacts on theactivity-travel behavior of private housing residents,
partly because they could self-select into the types ofresidential environment matching their travel
preference. However, when it comes to public
housing residents, density, accessibility, and selfcontainment have no significant impacts on theiractivity-travel behavior. Because they are not likely
to self-select where to live and daily infrastructuresand services are mandated in public housingdevelopment, the access to these facilities at the local
level helps overcome transportation constraints ofpublic housing residents in low-density (or suburban)
areas. That is, neighborhood planning matters toactivity-travel behavior of public housing residents inHong Kong.

Growth development
10.83 million m2 new mixed development area
Rp242.2 trillion growth of property value related toTOD
153,776 reduced parking lots
Contribution to regional income
Rp742 billion/year from land & building taxes in
TOD area
Rp182 billion/year tax contribution from rental office& retailRp15.4 trillion contribution from buying property
taxes (PJB/BPHTB)
Social & environmental contribution
34,047 units potential development of affordable
housing in TOD area
639,380 employed workers
210,000 m2 area of public activities
739,000 m2 park and public open space
149.1 km development of sidewalk
56,854 m2 riverside area
As development of bicycle line is relatively a new
project in Jakarta, its implementation may take a longtime, such as the experience of other cities. Though
as experienced by Beijing, public bicycle has be
defined as a component of public transit by theauthorities of Beijing. As a continuation of the public
transit, public bicycle is helpful to implement a newtrip mode of ”Public Bicycle + Public Transit + Public
Bicycle” to improve the accessibility of Public
Transit. The new scheme of PBS is operated byprofessional public bicycle rental company, but
funded by a state-owned enterprise under thesupervision of the government.
The main profit point of private company does notrely on rental fees, but on the sale of maturement ofbike rental technological system [1]. More advance,
as performed by Brisbane, there is more scope forinterventions based around the adoption of smart
transport measures to shape attitudes and encouragechanges in travel behaviour.
This work also indicates that both land use planningand complementary transport measures can impact on
travel behavior [2]. Referring to Chava, Newman, andTiwari [3], for increasing sustainable mode shareespecially among new build residents, measures need
to be taken to encourage intensive mixed land use
developments in new TODs like the traditional old
residential area. To encourage walking, cycling andto provide safe access to PT, neighbourhood NMT
infrastructure needs to be improved. In addition, toreap significant metro ridership benefits and to ensuretransit equity, the TOD policy must include
affordable housing policies, to accommodate people
with low income and low vehicle ownership, as their

COMPANY ACHIEVEMENT
After about one year of operation, the financial
performance of the company is shown as following
figures. They are asset, equity, expenditure, income,and total asset and total equity, respectively. It is
important to note that since its establishment until theend of 2018, the company has not yet operated
commercially and has not yet distributed dividends toshareholders. The funding for MRT Jakarta project issourced from the capital investment made by thecompany’s shareholders comprising DKI Jakarta
163

SEE - Kyoto, Japan, Nov.18-20, 2020

Provincial Government, through the Regional Capital
Investment (PMD) scheme. Project construction anddevelopment funders consist of grants (49%) andloans (51%). One of the company's best achievements
is asset growth increased 37%, it was in line with thecompany physical progress at the end of 2018.

tot comp income (loss) for
the year

2018

2017

50,000100,000

other comp income (expense)
income for the year
net other income (expense)
finance expenseother income/(expense)

total assets

gain (loss) on for exch
interest income-150,000

non-current assets-100,000-50,000

0

Fig. 6 Company’s income

2018
current assets

05,000,000

10,000,000

16,000,000

15,000,000

total assets
14,000,000
12,000,000

Fig. 3 Company’s assets

10,000,000
8,000,000
6,000,000

equity-net

4,000,000
2,000,000

other comp income02014
deficit

2015

2016

2017

2018

2018
2017

Fig. 7 Total assets and equity (2014-2018)

other share capital

DISCUSSION
share capital-5,000,000

05,000,000

10,000,000

As experienced in other countries, challenges for the
MRT and public transportation in the new line is toincrease the passenger capacity. While the initial
targeted daily ridership of 130,000 is a good target toaim for in the short term, it requires built environment
characteristics measured in a neighbourhood-based
unit, including residential density, distance to transit
and bus stops within 500 m, significantly affect public
transit behavior including travel distance, travel time
and transit mode choice [4]. It is important to note thatthe number of passengers differs from station tostation. The minimum volume is 964 passengers perday, while the maximum is more than 66,715
passengers per day refers to Metro Stations in
Bangkok. The area around the metro station also
ranges from the lowest population density (1995
population/km2)
tothehighest(19,814
population/km2). The residential area comprises all
metro stations. The station with the lowest density inthe residential area has approximately 420,000 m2 ofresidential floor area units. The highest portion of the

15,000,000

Fig. 4 Company’s equity
total expense
donations & sponsorships
communication, energy &…
licensing fees & meeting costs
depreciation & amortizationtransportation & parking costs
promotions & exhibitions
household needs
office supplies
consultant service fee
office & vehicle rent
training & membership
employee's salaries & welfare
0

2018

2017

50,000 100,000 150,000 200,000 250,000

Fig. 5 Company’s expenditure
164

SEE - Kyoto, Japan, Nov.18-20, 2020

commercial, industrial, and mixed use relative to theresidential area. Most stations are at a distance of lessthan 1 km from municipal public service facilities,
landmarks, and retail services. The average distancefrom the metro stations to these locations is less than
300 m. Access to public transport facilities is foundto vary from station to station [5]. Hong Kong
experiences suggested the built environment has
significant impacts on the activity-travel behavior ofprivate housing residents, partly because they could
self-select into the types of residential environment
matching their travel preference. However, when it
comes to public housing residents, density,
accessibility, and self-containment have nosignificant impacts on their activity-travel behavior.
Because they are not likely to self-select where to live
and daily infrastructures and services are mandated inpublic housing development, the access to thesefacilities at the local level helps overcome
transportation constraints of public housing residents
in low-density (or suburban) areas. That is,neighborhood planning matters to activity-travel
behavior of public housing residents in Hong Kong
[6]. Moreover, the Washington metropolitan area as
the study case: Household car ownership was foundto be significantly associated with residential density,
employment density, land use mix, average block
size, and distance from CBD. The factors ofresidential density, average block size, and distancefrom CBD were found to have significant effects oncommuter’s transit, and walk and bicycling mode
choice. Meanwhile, the mode of walk and bicycling
was also influenced by employment density aroundresidential location. People living in high density
areas may travel less due to increased accessibility
but they can also travel more due to reduced travel
costs [7], [8]. Another cities of the USA are shown
different findings: even classified by its transit
connection, station Park (Salt Lake City region) is
more of a TAD (transit adjacent development) than a
TOD. Huge parking lots dominate the space between
the commuter rail station and other components of thedevelopment [9]. In Los Angeles, Chakrabarti [10]concluded it is unrealistic to expect that transit can
win over auto in a large number of circumstances.
Transit agencies need to invest in better bike-transit
and rideshare- (or car share-) transit integration for
creating truly multi-modal cities, and improving
door-to-door connections via active or shared travelmodes. But most of literatures stated mixed land-use
policies reduce transport energy consumption. Whenmixed-use land also has a good jobs-housing balance,transport efficiency is even greater. Mixed land-use
policies should be encouraged to shape urban
development in more sustainable ways during
China’s ongoing rapid urbanization [11]. Regarding
the costs Zolnik [12] found at the household-level,
private-vehicle commuting costs for the 55-to-64 age
cohort are slightly less than for the 45-to-54 age

cohort. Comparing Whites and Asians, costs arelower for Asians. In the $75,000-to-$99,999 andgreater-than-or-equal to-$100,000 income categories
each spent $0.21 more on the work trip thanrespondents in the $25,000-to-$49,999 income
category. Private-vehicle commuting costs forrespondents in the manufacturing, construction, andmaintenance occupational category are higher thanfor respondents in the professional, managerial, andtechnical occupational category. Costs are also higher
for males than females.
CONCLUSION
The Jakarta MRT has been just a dream the people of
Jakarta have had for equalizing with the advanced
transportation systems present in foreign developed
countries. Referring to financial highlights, the MRT
asset growth increased by 37% during 2017 to 2018
period. It was in line with the company physicalprogress while the company has not operated
commercially due to trial run conducted since
December 2018 until February 2019. MRT Jakarta
announced it has surpassed the target of 65,000
passengers since its first day of commercial
operation. Neighbouring countries such as Malaysia,
Singapore, Thailand and the Philippines have longsince developed MRT systems to cope with traffic
congestion in their respective capital cities. Despite
having smaller populations than Jakarta, Singapore
and Kuala Lumpur have more extensive city rail
networks. Singapore has 129.7 kilometres of MRT
and 28.8 kilometres of feeder LRT (Light RailTransit). Kuala Lumpur has 175 kilometres of citycommuter trains, 56 kilometres of MRT, 57
kilometres of high-speed rail (ERL) and 8.6
kilometres of monorails. All in all, the benefits of
MRT will be fruitless if the city does not draw up
supporting policies as experienced of another city
around the globe.
REFERENCES[1] Liu, Z., Jia, X., and Cheng, W., Solving the Last
Mile Problem: Ensure the Success of Public
Bicycle System in Beijing, Procedia - Social and
Behavioral Sciences, Vol. 43, 2012, pp. 73–78.
[2] Kamruzzaman, M., Shatu, F. M., Hine, J., andTurrell, G., Commuting mode choice in transit
oriented development: Disentangling the effectsof competitive neighbourhoods, travel attitudes,
and self-selection, J. of Transport Policy, Vol.
42, 2015, pp. 187–196.
[3] Chava, J., Newman, P., and Tiwari, R.,
Gentrification of station areas and its impact ontransit ridership, J. of Case Studies on Transport
Policy, Vol. 6, No. 1, 2018, pp. 1–10.
165

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[4] Yu, L., Xie, B., and Chan, E. H. W., Exploring
impacts of the built environment on transit
travel: Distance, time and mode choice, forurban villages in Shenzhen, China, J. of
Transportation Research Part E: Logistics andTransportation Review, Vol. 132, 2019, pp. 57–
71.
[5] Nyunt, K. T. K., and Wongchavalidkul, N.,
Evaluation of Relationships Between Ridership
Demand and Transit-Oriented Development(TOD) Indicators Focused on Land Use
Density, Diversity, and Accessibility: A Case
Study of Existing Metro Stations in Bangkok, J.
of Urban Rail Transit, Vol. 6, No. 1, 2020, pp.
56–70.
[6] Wang, D., and Cao, X., Impacts of the built
environment on activity-travel behavior: Are
there differences between public and private
housing residents in Hong Kong? J. of
Transportation Research Part A: Policy andPractice, Vol. 103, 2017, pp. 25–35.
[7] Ding, C., Wang, Y., Tang, T., Mishra, S., and Liu,C., Joint analysis of the spatial impacts of built
environment on car ownership and travel mode
choice, J. of Transportation Research Part D:
Transport and Environment, Vol. 60, 2018, pp.
28–40.

[8] Hong, J., and Goodchild, A., Land use policies
and transport emissions: Modeling the impact oftrip speed, vehicle characteristics and residential
location, J. of Transportation Research Part D:
Transport and Environment, Vol. 26, 2014, pp.
47–51.
[9] Ewing, R., Tian, G., Park, K., Sabouri, S.,
Stinger, P., and Proffitt, D., Comparative casestudies: trip and parking generation at Orenco
Station TOD, Portland Region and Station Park
TAD, Salt Lake City Region, J. of Cities, Vol.
87, 2019, pp. 48–59.
[10] Chakrabarti, S., How can public transit getpeople out of their cars? An analysis of transit
mode choice for commute trips in Los Angeles,
J. of Transport Policy, Vol. 54, 2017, pp. 80–89.
[11] Zhang, M., and Zhao, P., The impact of landuse mix on residents’ travel energy
consumption: New evidence from Beijing, J of
Transportation Research Part D: Transport andEnvironment, Vol. 57, 2017, pp. 224–236.
[12] Zolnik, E. J., The costs of sprawl for privatevehicle commuters, J. of Transport Geography,
Vol. 20, No. 1, 2012, pp. 23–30.

1666th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

LABORATORY OBSERVATION ON DESICCATION CRACKING OF
THIN CLAY LAYER
Fauzilah Ismail1, Ahmad Kamil Arshad2, Nadiah Shaari3, Nursafiah Khalid1, Muhammad Haniff Asmuni1,
Muhammad Haziq Shuib1 and Ekarizan Shaffie2
1
Faculty of Civil Engineering, Universiti Teknologi MARA Shah Alam, Selangor, Malaysia; 2Institute forInfrastructure Engineering and Sustainable Management (IIESM), Universiti Teknologi MARA Shah Alam,
Selangor, Malaysia; 3Faculty of Civil Engineering, Universiti Teknologi MARA Pasir Gudang, Johor,
Malaysia

ABSTRACT
Desiccation is the state of extreme dryness, or the process of extreme drying. During drying process, clay soil
shrank and developed a tiny crack from the surface. The crack propagation is able to progressed deep into thesoil that can affect the stability and efficiency of the geotechnical structures such as dam failures. A series oflaboratory work was conducted to investigate desiccation cracking of kaolin clay sample of different thickness
placed on three different types of plate – ceramic, wood and steel. The crack propagation and pattern of thesekaolin clay samples placed on ceramic base plates were examined and compared with the samples placed onwood and steel plates. From the test, it was revealed that 10 mm thick kaolin clay sample has the highest crackintensity factor (CIF) with rapid propagation of cracks, while samples that were placed on the steel plateexperienced high rate of drying process as compared to samples put on ceramic and wood plates. It is also
observed that the crack propagation and pattern are also influenced by the thickness of the samples and type ofplates used.
Keywords: Desiccation, Kaolin clay, Crack propagation, Crack pattern, Thickness, Platesof thickness and different base plate materials
utilised for kaolin clay samples, as well as crack
propagations and patterns.

INTRODUCTION
Clay soil usually can be found in many
geotechnical structures such as embankment dam,slope and landfill. Clay soil potentially develops
desiccation cracking during drying that can affectthe stability and efficiency of the geotechnicalstructures such as dam failures [1] and slope failures[2]. Desiccation is the state of extreme dryness, orthe process of extreme drying. During drying
process, clay soil shrank and developed a tiny crackfrom the surface. As moisture content dissipates thecrack opening becomes bigger and deeper.
Laboratory scale (small size) investigations on
desiccation cracks of slurry, clay paste and starchwater mixed cakes have been carried out by several
researchers [3], [4], [5] &[6]. This paper reports theresults of a laboratory work that has been performed
to investigate desiccation cracking of manufactured
kaolin clay paste of different thickness and set on
different base plates made of ceramic, wood andsteel materials. Propagation of cracks and theirpatterns that appeared during the drying process arealso presented herein.

The experimental work was carried out using
manufactured kaolin clay. The basic properties andsoil classification of kaolin clay was acquired using
the Atterberg’s Limit Test.
The samples were prepared in liquid state bymixing dry powder of kaolin with 70% of watercontent. The dry powder was mixed thoroughly with
distilled water and left overnight to allow for thehydration process to take place. Prior to that, themoisture content (w%) of the sample paste wasdetermined before storage. Three alternate layers ofcling film and aluminium foil were used to preserve
the moisture content of samples. These wrappedsamples were then stored in air tight containers andkept away from direct sun light. The moisture
content was checked again the next day for control
purpose before desiccation test is conducted for thekaolin clay samples.

LABORATORY EXPERIMENTS

Test Methodology and Procedure

A series of laboratory testing on desiccation
cracking has been carried out to examine the effect

The Plastic Limit Test and Cone Penetration Test
were done to obtain the plastic limit and liquid limit

Sample Preparation

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SEE - Kyoto, Japan, Nov.18-20, 2020of kaolin clay sample, following the procedure asstated in BS1337:1990 Part 2 – Classification Tests.
The results are tabulated as shown in Table 1. The
sample was classified as clay of high plasticity.

DESICCATION TEST RESULTS
Desiccation test results are examined anddiscussed based on Crack Intensity Factor (CIF),
loss of moisture content and evolution of crack
pattern. The effects of different sample thickness
and different plate material used in the test are also
discussed in the conclusion.

Table 1 Kaolin Clay Properties
Descriptions
Results
Type of soil used
Kaolin Clay
Liquid limit (%)
68
Plastic limit (%)
34
Plasticity index
34
Specific Gravity
2.68
Soil classified as clay of high plasticity

Crack Intensity Factor
Crack Intensity Factor (CIF) is defined as thetime-variable ratio of the surface crack area, A c tothe total dried surface area of the soil, A t [8].
However only cracks formation with more than 2
mm depth are considered for the calculation of CIF[9]. Surface crack area, A c is determined by anapproximate method based on the manual grid
system of size 1.5 cm × 1.5 cm by using tracing
paper as shown in Figure 2. The tracing process wasdone upon completion of the drying process, i.e
constant mass gained and when crack propagationceased. Estimated area of crack (A c ) of related
sample was then summarised manually based on the
tracing drawing obtained using grid system.

Desiccation test was carried out in a room
temperature of an average 30°C. Main equipment
required for the test are desiccation plates made ofsteel, wood and ceramic, camera and weight balance.
A square kaolin paste sample of size 21 mm wasplaced on a desiccation plate. A camera wasclamped at a fixed height of about 600 mm above
the plate. The aerial photo and weight of the sample
were monitored, measured and recorded for every 6hours interval daily. However monitoring scheduled
was lengthen to duration of 12 and 24 hours interval
after the moisture content gradually reduced. Thiswas experiential observed between 5 to 15 days after
desiccation test was started dependent on thesamples thickness.
A grid system of aperture size 1.5 cm × 1.5 cm
was used for the purpose of monitoring the crack
propagation. Figure 1 shows the aerial photo of thewet sample of kaolin paste placed on the ceramic
plate and the grid system. The sample was labelled
as C1-3010, of which C refers to ceramic plate
followed by the number of sample (sample 1), room
temperature (30°C) and thickness of the sample (10mm). For other plates, S and W denote steel andwood, respectively. The monitoring program ended
when the moisture content of sample remained
constant and crack propagation ceased.

Fig. 2

The area of crack traced using grid system.

CIF result for all kaolin samples is tabulated inTable 2 and presented as a chart shown in Figure 3.
Overall result indicates that the evolution of crack ishigh in the thinnest sample (10 mm) regardless ofthe types of base plate used. However, the highest
CIF percentage of 5.02% is obtained fromdesiccation test of kaolin clay placed on steel plate.
Almost similar CIF percentage results were attained
for samples placed on wood and ceramic plates forboth 10 mm and 15 mm thicknesses. For 30 mm
thick kaolin clay the CIF percentage demonstrated aunique trend of no crack sign appearance on all
samples.
Table 2 Crack Intensity Factor (CIF)

Fig. 1 Kaolin paste sample on ceramic plate andgrid system.

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SEE - Kyoto, Japan, Nov.18-20, 2020

slightly slower than that of the first group of
samples. However, the result of second group showsa significant dropped in moisture content for the first
9 days for kaolin clay placed on steel plate. Area ofprimary crack formation is also less than the primarycrack formation area of the first group samples. The
highest CIF calculated for this second group samples
is 3.87% for kaolin clay placed on steel plate.
Different occurrence was observed for kaolin
clay of 30 mm thickness whereby the result shows agradual and steady reduction of moisture content
throughout the drying process. Nearly 24 days
passed by before the moisture content became
constant. However, for kaolin clay placed on woodplate the drying process was prolonged up to 36
days. CIF percentage is zero and no crack formed
for all samples in this third group (S3, W3 and C3).
Nevertheless, the total surface area is reduced due toshrinkage.

Crack
Total area
CIF
Base
Samplearea,of dry soil,
(%)
Plate
No.
Ac
A t (cm2)(cm2)
S1-301021.08
420.27
5.02
SS2-301516.28
420.25
3.87
S3-3030
nil
414.090W1-301019.13
417.38
4.6WW2-3015
3.94
368.55
1.1
W3-3030nil
401.850C1-301017.43
412.09
4.2CC2-3015
4.88
407.25
1.2
C3-3030
nil
407.390Note: S, W and C is refer to steel, wood and ceramicbase plate respectively and whilst nil is denote no
crack occurred.

CIF (%)

5.00

S1

W1
C1

4.00

steel plate,Swood plate,Wceramic plate,C

S2

Moisture Content, w (%)

6.00

3.00
2.00

W2C2

1.00

S3 W3 C3

0.00

10 mm
15 mm
30 mm
Sample thickness (mm)Fig. 3
used.

80
70
60
50
40
30
20
10
0
0 100 200 300 400 500 600 700 800

CIF results for different thickness and plate

C3-3030
C2-3015
C1-3010

Drying time, t (hour)
W3-3030
S3-3030
W2-3015
S2-3015
W1-3010
S1-3010

Moisture Content
Fig. 4 The relationship between moisture content
and drying time.

Desiccation is the process of extreme drying
therefore it is directly related with the loss ofmoisture content. Monitoring program for themeasurement of moisture content is crucial. It must
be done continuously and taken at appropriate
interval until the constant mass achieved. The loss ofmoisture content for all kaolin paste samples areplotted on a graph as shown in Figure 4.
A drastic reduction of moisture content with
rapid crack propagation in the first 5 days of testing
period can be seen for kaolin clay of 10 mmthickness. Primary cracks were formed within thisperiod followed by appearance of secondary cracks
as moisture content gradually decreased till it
remained constant. The monitoring program wasstopped after a few constant readings of moisture
content were recorded.
Overall results show the group of 10 mmthickness samples (S1, W1 and C1) has the highest
CIF percentage as compared to the other groups ofsamples. As for kaolin clay of 15 mm thickness (S2,W2 and C2), the losses of moisture content are

Evolution of Crack Pattern
The geometric features of cracks such as width,
depth and surface area are important parameters
because they influenced both the soil hydraulics andmechanics [8]. It also signifies the evolution of crack
pattern on the surface area. The time-variable aerial
photos were taken for all samples. These photos
display the propagation of cracks and theirformations at the end of the test.
It is evident that the primary cracks meet at aright angle and produce an orthogonal pattern for all
samples of kaolin clay of 10 mm thickness, as
shown in Figure 5. Secondary cracks appeared after
the primary cracks ended and made a narrow
opening. Yet, not much of secondary cracks can beviewed for all desiccation test categories (i.e.
different plate used).

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SEE - Kyoto, Japan, Nov.18-20, 2020

S1-3010

W1-3010

investigated. The results obtained from desiccation
test can be concluded as following:i) Cracks started at the edge of kaolin clay samples
and developed inwards into the inner area.
ii) Secondary cracks appeared after the primarycracks ended and made a narrow opening.
iii) A clear crack propagation and orthogonal pattern
dominated by primary cracks can be viewed on
the thinnest sample.
iv) CIF decreased as the thickness of sample
increased.
v) Rapid loss of moisture content was observed
from the samples placed on steel plate.

C1-3010

Fig. 5 Crack pattern for kaolin clay of 10 mmthickness at the end of the test.
Normally, the progression of crack starts fromthe edge of sample [7] but it is observed that forkaolin clay of 15 mm thickness the propagation of
cracks start from the centre of the sample. It issuspected that a small defect exists on the surface
during sample preparation where this defect can
trigger crack formation due to stress concentrationand shrinkage distortion of surrounding medium [7].
However, for an unknown reason the propagation of
cracks for all kaolin samples of 15 mm thickness
possess similar trait, in which it starts from the
middle of the surface and develops outward to theedges. This is regardless of different types of plateused as shown in Figure 6.

S2-3015

W2-3015ACKNOWLEDGMENTS
This work is supported by Universiti Teknologi
MARA (UiTM), Shah Alam Campus, Selangor,
Malaysia. The contributions of final year project(FYP) students in the collation of experimental data
and related research are gratefully acknowledged
and highly appreciated.

REFERENCES[1] Y. Xu and L.M. Zhang, Breaching parameters ofearth and rockfill dams, J.Geotech. Geoenviron.
Eng., ASCE, Vol. 135, Issue 12, 2009, pp. 19571970.
[2] F.H. Lee, K.W. Lo and S.L. Lee, Tension crackdevelopment in soils, J. Geotech. Eng., 114 (8),1988, pp. 915-929.
[3] K.A. Shorlin, J.R. de Bruyn, M. Graham and
S.W. Morris, Development and geometry of
isotropic and directional shrinkage-crack
patterns, Phys. Rev., E 61 (6), 2000, pp. 69506957.
[4] J.K. Kodikara and X. Choi, A simplified
analytical model for desiccation cracking of clay
layers in laboratory tests, Geotechnical Special
Publication, No. 147, ASCE, Reston, VA, 2006,
pp. 2558-2569.
[5] H. Peron, L. Laloui, T. Hueckel and L. Hu,
Experimental study of desiccation of soil,
Geotechnical Special Publication, No. 147,
ASCE, Reston, VA, 2006, pp. 1073-1084.
[6] J.H. Li, L.B. Guo and C.Z. Cai, Influence ofwater content and soil type on soil cracking,
Advances in Civil, Env. And Material Research(ACEM’ 12), Seoul, Korea, 2012, pp. 15431553.
[7] C.S. Tang, B. Shi, C. Liu, L. Goa and H.I.
Inyang, Experimental investigation of thedesiccation cracking behaviour of soil layers
during drying, J. of Materials in Civil Eng.,
2011, pp. 873-878.
[8] C.J. Miller, H. Mi and N. Yesiller, Experimental
analysis of desiccation crack propagation in clay

C2-3015

Fig. 6 Crack propagation during drying process
for samples of 15 mm thickness.
For kaolin clay of 30 mm thickness, there are no
cracks forming on all samples as shown in Figure 7.
Nevertheless, the total surface area is reduced duringdrying process due to shrinkage. A similar result wasobserved on Indian Head Till clay of 40 mm
thickness as reported by Lau [10].

S3-3030

W3-3030

C3-3030

Fig. 7 No traced of crack occurred for all samplesof 30 mm thickness.
CONCLUSIONS
Desiccation cracking process of kaolin clay
samples of different thickness were thoroughly
monitored and reported. Observation on the effect ofdifferent types of base plate used was also
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SEE - Kyoto, Japan, Nov.18-20, 2020

liners, Journal of American Water Resources
Association (AWRA), 34 (3), 1998, pp. 677-686.
[9] R.M. Al Wahab and M.A. El-Kedrah, Usingfibers to reduce tension crack and shrink/swell incompacted clay, Geoenvironment, 2000, pp. 791805.
[10]J.T.K. Lau, Desiccation cracking of clay soils,
M.Sc. Thesis, Department of Civil Engineering,
University of Saskatchewan, Saskatoon, Canada,
1987.

171

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

STATIC PILE LOAD TESTS: CONTRIBUTION OF THE
MEASUREMENT OF STRAINS BY OPTICAL FIBER
Fabien Szymkiewicz1, Carlos Minatchy2 and Philippe Reiffsteck3
1, 2, 3
Université Paris-Est, France
ABSTRACTThe use of optical fiber for measuring strains and or temperature is increasing in civil engineering. Opticalfiber is known to be relatively cheap, compared to the more traditional sensors commonly used, and can,depending on the chosen technology, give a complete distribution along the instrumented element, which can bevery interesting in case of an element with variable dimensions along the length of said element. Therefore, forstatic pile loading tests, the use of optical fiber should present many advantages, compared to more conventional
methods of measure of the strains. The aim of this publication is to shed new light on the advantages anddisadvantages of using optical fiber for the measurement of deformations along a foundation element. After astate of the art of the methods commonly used, the contribution of the optical fiber for the instrumentation of thefoundation elements is evaluated, by comparing the results obtained by the use of the fiber with those obtained
thanks to more traditional methods, through some examples of full-scale load tests. Finally, somerecommendations are given to maximize the interest of the use of optical fiber in future tests.
Keywords: Deep Foundations, Piles, Load Test, Optical Fiberdetailed test standards [1]. Depending on the
purpose of the test, the pile may or may not be
instrumented. When instrumentation is implemented
inside the pile, the goal of this instrumentation is tomeasure whether forces or strains, which can be thenderived in forces, knowing the geometry of the pileand the apparent modulus of the constitutive
material of the pile. Then, from these forces, forcedepth diagrams can be drawn (Fig. 1).

INTRODUCTION
Static pile load test are usually carried either fordesign purposes, whether it be for control of thisdesign or design by trial, or for constitution of adatabase then used to elaborate design methods.
Therefore, they are critical tests for geotechnicalstructures and shall be thoroughly prepared.
As such, they are covered by complete and wellFig. 1Force distribution along a CFA pile instrumented with a retrievable extensometer

For lateral load tests, the principle is the same,
except that it is p-y curves that are determined.
A number of different solutions exist for themeasurement of these strains, each with its
advantages and disadvantages.
Among these solutions is the optical fiber: sinceapproximately a decade, a number of geotechnicalprojects have included these technologies for

Shaft resistance and base resistance can then be
dissociated, and unit shaft friction can be assessed
for each soil layer encountered, depending on thenumber of measurement points available along thelength of the pile. t-z curves, linking thedevelopment of the unit shaft friction of a segmentof pile to the displacement of this segment, can thenbe drawn, as well as q b -z curves

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SEE - Kyoto, Japan, Nov.18-20, 2020

monitoring, including piles [2]-[3]-[4].
This paper aims to first inventory the mostcommon solutions for the measurement of strains
along the shaft of a pile, listing in the process thepros and cons of these solutions. Then, a focus ismade on the optical fiber and its use for the testingof geotechnical structures, and particularly piles.
The encountered difficulties and the observed clear
benefits of the use of the optical fiber for thispurpose are then highlighted, through practicalfeedback. Conclusions are then drawn, and someinnovative uses of the fiber for the monitoring offoundations are proposed.

-

products, some of them having to be kept
refrigerated, and a clean environment,
Wires and gauges are very small, and may
be damaged during the process of
introducing the reinforcing cage inside theconcrete (for CFA piles or equivalent),
during the concreting phase (for bored piles),or during the driving phase (driven piles).

TRADITIONNAL SOLUTIONS FOR THE
MEASUREMENT OF STRAINS ALONG A
PILE
In this section, the three main solutions for themeasurement of strains along the shaft of a pile aredescribed in details, and their technical, practical andeconomical strengths and weaknesses are listed.

Fig. 2

Naked train gauge bonded to the rebar (a)Vibrating Wire Strain GaugesThis solution is very close to the first one:vibrating wire sensors are attached to the reinforcing
bars of the steel cage at different depths, with one ormore per depth.
The advantages of this solution are as follow:- the sensors are very robust (made of steel),- the sensors are not very intrusive (usual
length is around 150 mm for a diameter of
25 mm, but can go up to 400 mm in lengthfor particular applications),- the sensors need only to be attached to therebars with ducktape or plastic zip ties (Fig.
3a),- the sensors can be bought pre-cabled to theneeded length,- cables are strong enough to resist the tension
during the different phases of manipulation
and realization of the piles.
- The sensors are very quick to fix, even if thelength of the cables (especially whenworking on long and / or heavily reinforced
piles) can hinder the work and make theintervention longer,- each sensor is independent from the others,- each sensor can be compensated intemperature.
On the other hand, this solution presents somedisadvantages:- for piles heavily instrumented, the number
and thickness of the cables can make thissolution intrusive, especially for small
diameter piles (Fig 3b),- it can be expensive, when using a great
number of sensor and instrumenting long
piles, as the cost per sensor and per meter ofcable is not negligible.

Embedded Strain GaugesThis solution is one of the oldest: it consists inplacing, at defined depth, strain gauges that will bebonded to the steel cage reinforcing bars (one ormore per depth) or pipe.
The advantages of this solution are multiple:- this is a proven technology, with whichalmost every actors is familiar,- it is not very intrusive due to the small sizeof the gauges and the wires, which is a good
point for small diameter piles,- it is quite affordable,- each sensor is independent from the others,
which is important when encountering somedamages,- each sensor can be compensated intemperature.
However, there are a number of disadvantages
when using this technology:- It is time consuming to implement, as there
are multiple steps to follow the wholeprocess of preparation and bonding: first,
flat rough surfaces should be grinded on therebars, then should be smoothed using finer
sandpaper. Surface has then to be cleaned of
any impurity using chemical products. The
strain gauge may then be bonded to thesurface (Fig. 2), using another chemical
product, and two layers of protection should
then be added on top of the gauge. If thegauges are not pre-cabled, then an extra step
will be the soldering of the cables to thegauge. Then, if necessary, soldering should
be done for any extra cable length added,- It necessitates multiple tools and chemical
173

SEE - Kyoto, Japan, Nov.18-20, 2020aFig. 3bVibrating wire strain gauge linked to a rebar (a) and cables exiting the top of the steel cages (b)12 segments, which can sometimes not beenough for long piles in a multi-layers
ground,- nitrogen is needed for the use of most ofthese systems,- duration of use is limited in time, as there
may be leaks of nitrogen due to worn-out
valves and connections,- it is quite fragile and needs extra care whenmanipulated,- spare parts are expensive and not always
easily found,- it needs constant maintenance and highly
qualified technicians to maintain it, calibrate
it and keep it ready to use,
- on site preparation takes time,- during on site preparation phase, it
necessitates a lot of space to be deployedsafely.
All these aspects make the use of a retrievable
extensometer expensive, compared to the embedded
solutions.

Retrievable extensometers
This solution is a totally different one. It consists
in a chain of sensors that will have to be inserted
inside the pile after it realization. Technologies usedin retrievable extensometers are usually strain
gauges, vibrating wires strain gauges, LVDT or
potential sensor based.
The principle is as follow: one or morereservations made of PVC or steel (which can besonic tube, for example) are cast in the pile. Just
before the load test begins, the retrievable
extensometer, made of multiple segments whose
lengths can vary to adjust to the geology on site, isinserted inside the pipe [5]. When completely
inserted and correctly positioned, it is locked into
position, using either a pneumatic (with nitrogen
being the gaz expanding the anchors) or amechanical system (Fig. 4).
The advantages of this solution are as follow:- it doesn’t need the intervention of a team ofexternal workers during the realization phase,- the material is not expendable and can be reused for another pile, which can be
economically interesting in case of repeatedtests on the same site,- lengths of segments are adjustable, if needed,- it is particularly well adapted for the
instrumentation of driven piles, as thesensors are not present during the criticalphases and therefore cannot suffer from it.
However, this solution presents some major
disadvantages:- extra pipes should be positioned inside thereinforcing cage, which implicate extra workfor the contractor before the realization of
the pile. These pipes shall also be chosen in
relation to the model of extensometer thatwill be implemented. Particular attention
should be paid to the connection/welding of
the segments of the pipe, to ensure that
nothing obstructs the passage of theextensometer,- it is intrusive, especially for small diameter
piles,- these extensometers are often limited to 8 to

EMBEDDED SENSORS VS RETRIEVABLE
EXTENSOMETERS
While, for practical and economical reasons,the use retrievable extensometer are interesting
when testing multiple piles of comparable size
and/or driven piles, it becomes less competitive forprojects with only a few piles, or with piles withdifferent lengths, for the same reasons.
Furthermore, even if both solutions aim is tomeasure strains along the pile, the measurement may
differs : indeed, while the technologies of thesensors used for one or the other are often the same,the principle of measures differs. The embedded
sensors are measuring the strains over a length equal
to their own length, while the retrievable
extensometers measures strains between two anchors
assumed to be fixed, and moving with the pile itself(Fig. 5) [6], making the strain measurement ‘global’
compared to the ‘local’ measurements achieved withembedded sensors.

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SEE - Kyoto, Japan, Nov.18-20, 2020

Fig. 4operating principle of a retrievable extensometerabFig. 5Comparison of measured strains at different depth (a) and calculated displacements of pile base (b)in a bored pile with a retrievable extensometer and vibrating wire strain gauges
Therefore, the retrievable extensometersintegrate the strains over a longer sample. In
consequence these measured strains are often larger
than the ones achieved with embedded sensors, witha ratio dependent on the strain level (Fig. 5a). The
resulting equivalent moduli derived from thesemeasurements are in turn smaller.
In addition, the analysis of the results achieved
are not as straight-forward as when using embedded
sensors, as it is needed to interpolate results at thelevel of each anchor.
Nevertheless, results achieved with bothmeasuring methods are quite comparable, as can beseen on Fig. 5b for the calculated displacement of
the pile base, on Fig. 6a for the load distribution of agiven load step and on Fig. 6b for the mobilizationof shaft resistance during a static load test [6], andthe utilization of one solution or the other should
therefore be only linked to the context of the project,as it is not a question of accuracy.

CONTRIBUTION OF THE MEASUREMENTOF STRAINS BY OPTICAL FIBER
Implementing optical fiber for the measurementof strains in piles was first done when long termmonitoring of strains and temperatures was needed :therefore, at first, piles instrumented with thesetechnologies were thermo-active piles.
Nowadays, with positive practical feedbacks on
the use of this solution available, it can be used forstandard piles, for control or development purposes,
as it allows measurements all along the fiber, with aresolution up to a few millimeters, depending on thetechnology used (Fig. 7), and measurements
achieved are in excellent concordance withmeaurements achieved with vibrating wire strain
gauges (Fig. 8a).

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SEE - Kyoto, Japan, Nov.18-20, 2020

2

0

500

Load (kN)

1000

1500

2000

strain gauges
Retrievable extensometer

4

Depth (m)

2500

2500

6
8

Shaft Resistance (kN)

0

10

2000
1500

500
0

12
14

a

Pile 2 strain gauges
Pile 2 Retrievable extensometer

1000

0

0,02

0,04

0,06

Mean shaft displacement

0,08

b

Fig. 6Comparison of load distribution for a given load step (a) and shaft resistance mobilization (b) for a
CFA pile: results achieved with strain gauges and retrievable extensometer.
The use of optical fiber for the measurement ofstrains presents some advantages:- implementation, when choosing to simply
link the fiber with ducktape to the rebars,
can be very quick,- it is almost non intrusive, as the fiber isgenerally only a 3 or 4 mm in diameter (Fig.
3b),- it is very interesting for determining
moments and p-y curves, as it provides avery high number of measurements along
the pile,- it can be temperature conpensated,- cost of the fiber in itself is very low andmakes it possible to instrument most rebars.
Optical fiber can also be inserted inside a pipe
if available, and then sealed with grout, allowing fora possibility to monitor a pile if something were togo wrong with the primary instrumentation. Resultsfrom such instrumentation can be seen on Fig. 8b,

where they are compared to results achieved with afiber linked to a rebar : measurements are quite
comparable and therefore this solution can be used if
needed. It is interesting to note that strains presented
on Fig. 7b were also measured through this method,as the timing of the project did not allow for the pile
to be instrumented before being realized.
Furthermore, it also allows to detect layers that
where not detected during the geotechnicalinvestigation, and to observe behaviour that would
not be seen when using a discrete methods ofmeasuring strains.
Figure 9 shows the strains measured with an
optical fiber and vibrating wire strain gauges, on abored pile tubed down to 16m: at the end of the tube,
strains measured by the optical fiber increases, due
to a decreased stifness of the pile, while the strain
gauges, which are discretly distributed along theshaft, do not reflect this local behaviour.

aFig. 7b

Strain distribution for a given load step (a) [2] and for different load steps (b)176

SEE - Kyoto, Japan, Nov.18-20, 2020ab

Fig. 8strain measurements comparison between optical fiber and vibrating wires (a) Strain distribution fora given load step with an embedded fiber and a fiber sealed in pipe (b)
0

-50

-100

-150

-200

-250

-300

-350

-400

-450

-500

Strains (µm/m)

0
2
4

6

most exposed during concreting or insertion
phases (Fig. 10a), and during construction
phases such as lifting, when tensile stressdue to the bending of the cage can exceed
fiber tensile resistance (Fig. 10b), to avoid
any break.
the fiber acting as a chain of sensors, abroken fiber will result in the total loss of
information under the break.

8

Depth (m)10
12
14
16
18
20

a

Fig. 9Strains measurements along a bored
pile: effect of tubingbFig. 10Fiber protection at the pile base (a) andcage lifting phase (b)However, it is important to be aware of the
difficulties / disadvantages of the optical fiber :- while the cost of the fiber in itself is very
low, the interrogator price is usually veryhigh,
- the interrogator are often not so rugged, andcan be damaged during on site monitoring,
due to dust presence mostly. Someinterrogators are very vibration sensitive,- the fiber is also very fragile, and must betreated with extra care during set up (Fig. 9),especially at the pile base, where the fiber isFurthermore, the steps of the realisation of aconection are numerous and tedious. The
environment needs to be very clean, with close onsite activities as low as possible. The apparatus
needed are presented in Fig. 11.
Bad connections result in loss of signal that willin turn result in loss of precision, that will have to be
added to the impact of the deployement method of
the fiber and the pile, a seen on Fig. 12, which
represent the variation of the frequenc.

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SEE - Kyoto, Japan, Nov.18-20, 2020-aFig. 11stagesthe set up, implementation and manipulationof the fiber should be done in a very
controlled environment and with extra care,as it is very fragile.
- while the cost of the fiber is relatively low,
the price of the interrogator, coupled with its
fragility, leads to a certain reluctance todeploy them in dusty environments prone tohazards endangering their integrity and theirproper functioning.
However, further applications like themonitoring of piles at a young age for quality control
purposes (by measuring of temperature inside thepile along the shaft to assess its possible change indiameter) may entice contractors to develop the useof this technology.

bPresentation of the different welding

REFERENCES[1] Szymkiewicz F, Sanagawa T and Nishioka H.,
2020. Static Pile Load Test: International
Practice Review And Discussion About The
European And Japanese Standards, International
Journal of GEOMATE, Vol.18, Issue 66, pp.
76-83.
[2] Soga, K., Kwan, V., Pelecanos, L., Rui, Y.,
Schwamb, T., Seo, H., and Wilcock, M., 2015.
The role of distributed sensing in understanding
the engineering performance of geotechnicalstructures. XVI European Conference on Soil
Mechanics and Structures.
[3] Klar, A., Bennett, P.J., Soga, K., Mair, R.J.,
Tester, P., Fernie, R., St John, H.D., and TorpPeterson, G., 2006. Distributed strain
measurement for pile foundations. Proceedingsof the Institution of Civil EngineersGeotechnical Engineering, 159, pp. 135-144.
[4] Mohamad, H., Tee, B.P., Chong, M.F., and
ANG, K.A., 2010. Investigation of shaft friction
mechanisms of bored piles through distributed
optical fibre strain sensing. 19th International
Conferenceon
Soil
Mechanics
andGeotechnical Engineering 2017, Seoul.
[5] Laboratoire Central des Ponts et Chaussées,
2001. La mesure des déformations à l’aide desextensomètres amovibles LPC : Méthodesd’essai LPC n°34, 17 pages (in French)[6] Szymkiewicz, F., S. Burlon, F. Guirado, C.
Minatchy and G. Vinceslas, 2015. Experimental
study of heating-cooling cycles on the bearing
capacity of CFA piles in sandy soils, XVIECSMGE, Edinburgh.

abFig. 12Brillouin signal in a fiber used forcalibration (a) and implemented in a pile (b)(frequencies vs length)
CONCLUSIONSThe use of optical fiber for the measurement ofstrains during pile load tests or other related projects
is now a solution that is very reliable.
While measured values may differ from values
achieved by more conventional technologies, this is
only due to differences of measurement methods ofthe solutions. Interpretration of the data shall gives
the same results as the other solutions, whether it bedisplacements of the pile segment or load
distributions along the pile, albeit with a higher
resolution.
Nonetheless, it is still very rare to see thistechnology used for pile monitoring, the two main
reasons for this being that:178

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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

SPATIAL DISTRIBUTIONS IN GROUNDWATER DISCHARGE ON
VARIOUS TIDAL FLATS IN A SMALL AND STEEP ISLAND,WESTERN JAPAN
Shingo Nozaki1, *Shin-ichi Onodera1, Yusuke Tomozawa1, Mitsuyo Saito2
1

Graduate School of Graduate School of Advanced Science and Engineering, Hiroshima University, Japan
2
Graduate School of Environmental and Life Science, Okayama University, Japan*Corresponding Author, Received: 00 Oct. 2018, Revised: 00 Nov. 2018, Accepted: 00 Dec. 2018

ABSTRACT: To manage and conserve the seagrass bed and ecosystem in tidal flats, this study examined toconfirm spatial distribution in groundwater (SGD) on tidal flats with the area of around 100m square in a smalland steep island. Various groundwater and nutrient discharges were observed at the W and E sites. 1) Based on
the water budget, the groundwater flux was estimated to be 8.68 m/yr or 23.9 mm/day in E, and 17.75 m/yr or
48.6 mm/day in W, respectively. 2) Spatial distributions of groundwater contribution ratio (%) in pore water at
W was around 60% in average, which was 8 times of that in E site. 3) The NO 3 -N concentration in pore water at
W site was about 30 times of that at E because of the low attenuation rate with high groundwater velocity. 4) The
temporal variation in groundwater flux with tidal fluctuation indicated 2.5m/day in maximum and -4.0m/day inminimum. This huge difference between the average flux and maximum indicated also large seawater
recirculation and heterogeneous distribution of SGD. This heterogeneous distribution at this tidal flat would
contribute to the activity of seagrass and diversity of ecosystem.
Keywords: Submarine groundwater discharge, Spatial distribution, Tidal flat, Island

spatial variation of SGD in a tidal flat scale has notbeen clarified enough [18,19].
The purpose of this study was to confirm spatial
distribution in groundwater (SGD) and nutrient
discharge on tidal flat with the area of around 100m
square in a small and steep island.

1. INTRODUCTION
The tidal flats and shallow coastal areas arenaturally covered by seaweed and seagrass, thesearea contributes to biodiversity in the ecosystem [1].
One of the reasons for the rich seagrass bed from thetidal flat to the shallow bottom in a coastal zone isvarious physical and chemical environments.
Submarine groundwater discharge (SGD) defined as
any flow of water at land margins from the seabed tothe coastal ocean [2,3] has spatial distribution in the
km scale and includes fresh groundwater with thestable temperature [4,5]. SGD has significant
impacts is an important source of not only
freshwater [2,3] but nutrients [6,7,8].
Recently, the coastal ecosystem such as coral
reef and seagrass bed has been degraded by thedevelopment and overuse of coastal zone [9].
Because the degradation of seagrass bed causes
biodiversity loss in coastal zones, this is one ofglobal environmental issues [10]. In urban regions,the huge nutrient supply from the sewage plant [11],the recycling of accumulated nutrient in sea bed [12]by the tidal pumping [13] caused the eutrophic
condition and was degraded ecosystem. In addition,
the groundwater depression by over pumping in the
coastal city caused seawater intrusion and stop of
SGD [14,15,16].
On the other hand, in the rural regions, thecontribution of SGD and coastal current controls thenutrient and freshwater supply. The groundwater
discharge into the sea bed near shore line hasconceptually been understood [8,17]. However,

2. METHOD
2.1 Study Area
The experimental sites were located on Ikuchi
Island in Onomichi City, Hiroshima Prefecture, inthe central Seto Inland Sea, western Japan. (Fig. 1).
The regional climate is warm (average temperatureof 15.6°C), with less precipitation in Japan (approx.
1100mm/y). Ikuchi Island is one of the most famousand important orange and citrus production areas.
The orange groves cover 42% of the total catchment
area, and are mostly located in the downstream area.
Forests cover 43% of the upper area. Groundwater
resources are important water supply resources for
irrigation. However, due to the small annual
precipitation with large inter-annual variation, andsteep sloping topography, the island faces a risk ofwater shortage, especially in the drought season.
Ikuchi Island is characterized by a steep terrain
and granite bedrock [20], and the total area is 32.7
km2. The alluvial fan and plain in the coastal zone isnarrow, but is generally deposited by the sediment
composed of gravel and sand including clay with the
thickness of around 15m [8,20,21].
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SEE - Kyoto, Japan, Nov.18-20, 2020

The research catchments (E and W catchments)
are located in the southern area of the island (Fig. 1),
and are approximately 1700m and 900m in length,and 300m and 150m in width, with an area of 0.434
km2 and 0.242km2, respectively. These catchments
have steep slopes, particularly in the upstream
mountainous area, with a top elevation of 396m and472m in E and W catchments, respectively. And
experimental tidal flats (E and W) have about 75m
and 30m in length and 100m and 250m in width,
respectively. E experimental tidal flat is at the edgeof the alluvial fan made by a small stream with
1.5km in length and it is a half of groundwater
discharge area of the catchment. W experimental
tidal flat is at the mountain slop foot with the twice
average slope gradient of the E catchment and it issimilar to the discharge area of the catchment.

2019, rain water and groundwater samples werecollected monthly at each catchment.
The water budgets were estimated by theprevious researches [21,22] in E catchment based on
the river discharge and groundwater monitoring in2003 and 2004. On the other hand, there is no stream
discharge in W catchment.
2.3 Laboratory Analysis
These water samples were filtered using 0.2 μm
cellulose ester filters in the field and stored in afreezer until analysis. The stable isotope ratio andnutrient concentration of water samples wereanalyzed, using the WS-CRDS method (PicarroCompany, L2120-i) and a spectrophotometric autoanalyzing system (SWAAT; BL TEC K. K., Japan),respectively.
3. RESULTS AND DISCUSSION
3.1 Water budget
Table 1 Water Budget in each catchment.
E catchment
W catchment
P (mm)
1100
1100
Ev (mm)350[22] - 550[21]550
Qr (mm)250[21] – 435[22]0Qg (mm)300[21] – 315[22]550Note: [21] using hydrological observation, and [22]using SWAT model.
Water budget is represented as Eq. (1),P – Ev = Qr + Qg +∆(1)where P is precipitation, Ev is evapotranspiration,
Qr is river discharge, and Qg is groundwater
discharge, respectively. The water budgets in E
catchment were estimated, using the hydrologicalobservation and monitoring [21] and SWAT model
analysis [22]. The water budgets in E and W
catchments are shown in Table 1.
Based on the water budget, groundwater
discharge in W is twice of E. The catchment area in
E is twice of W, and the groundwater discharge
volume in E is estimated to be similar to that in W.
As the E tidal flat is a half of the discharge area of
this catchment, the discharge volume in E site is ahalf of W tidal flat. If the groundwater discharges tothe experimental tidal flat area (7,500m2), annual
groundwater discharge is estimated to be 8.68 m/yr
or 23.9 mm/day in E, and 17.75 m/yr or 48.6mm/day in W, respectively.

Fig.1 Study area and the experimental sites.
2.2 Field Observation
10 and 17 piezometers on two experimental tidal
flats, which is composed of E site (100m x 30m) at
the alluvial fan edge of an experimental catchment
and W sites at the steep mountain slop foot (300m x30m) were installed with the depth of 50cm,
respectively. Pore water samples were collected in
December in 2018 and July and December in 2019.
Water temperature and electric conductivity (EC)were measured in situ, using the potable meter. In
addition, water levels were monitored in 2017 and

3.2 Spatial distribution of groundwater discharge
Figure 2a and 2b shows the distribution of EC in
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SEE - Kyoto, Japan, Nov.18-20, 2020

pore water at E and W site, respectively. The
average EC at E is 46 mS/cm and that at W is 25
mS/cm. The average groundwater discharge rate at E
site was a half of that at W site, the trend of the EC
distribution in pore water was similar to the trend ofgroundwater flux.

offshore. These comparative trends were shown
obviously in the histogram (Fig. 4).

(a)

(a)

(b)

(b)

Fig. 3 Spatial distribution of groundwater
contribution ratio (%) in pore water at W site (a)and E site (b). ◆; piezometer plot.
Fig.2 Spatial distributions of EC in pore water at W
tidal flat (a) and E (b). The unit is mS/cm. ◆;piezometer plot.
Figure 3 shows the spatial distribution ofgroundwater contribution ratio (%) in pore water at
W and E site. The ratio at W is around 60% in
average and the range of from 10% to more than
95%, whereas the ratio at E is around 7% in averageand the range from 5% to 10%, respectively. The
ratio at W site is 8 times of that in E site. These
difference could not explain only by the fresh
groundwater flux described above. This means thesea water recirculation flux by the tidal pumping at
E site would be around 4 times of that at W site. In
general, this flux is related to the length of the tidal
flat, especially the length at E was 2.5 times of thatat W.
The distribution at W site is heterogeneous andthe pore water with the ratio of 10% were found at 2
piezometers in 17 plots while that with more than
50% and 90% were found at 4 and 1 plots,
respectively. On the other hand, the distribution at E
site is homogeneous and the ratio continuously
decreased from 10% near the land to 5% in theFig. 4 The histogram of groundwater contribution
ratio at E and W site.
3.3 Spatial distribution of nutrient discharge
Spatial distribution of NO 3 -N concentration(mg/l) in pore water at W site (a) and E site are
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SEE - Kyoto, Japan, Nov.18-20, 2020

shown in Fig. 5 (a) and (b), respectively. The lower
areas of both catchments are covered by the citrus
plantation, and dissolved nitrogen and phosphorus
was contained so much in fresh groundwater byleaching of fertilizer component [21]. The
concentration distributed the range from 0 mg/l to 7
mg/l at W tidal flat site, whereas it distributed therange from 0 mg/l to 0.2 mg/l. The maximum
concentration at W was about 30 times of that at E.
This means the attenuation rate is relatively small at
W site because of the higher groundwater velocity,
as compared at E. Especially, the concertation was
maximum at the central part of W site.

concentration.
3.4 Temporal variation in pore water pressureand EC
Figure 7 shows the temporal variation in
groundwater flux with tidal variation during 3 days.
The range of tidal variation was 3.5m. The
groundwater flux is maximum at the mid tide during
the decreasing tide and minimum at the mid tide
during the increasing tide. Figure 8 shows the
temporal variation in EC of the pore water with tidal
variation. The EC increased with the tidal level, andthe tidal pumping effect was indicated [3,4]. But thevariation range is only less than 1mS/cm with 34
mS/cm in the average.

(a)

(a)

(b)
(b)

Fig. 5 Spatial distribution of NO 3 -N concentration(mg/l) in pore water at W site (a) and E site (b).
◆; piezometer plot.

Fig. 6 Spatial distribution of SiO 2 concentration(mg/l) in pore water at W site (a) and E site (b). ◆;piezometer plot. ○; piezometer plot monitored waterlevel and EC shown in Fig.7 and 8.

Figure 6 shows spatial distributions of SiO 2
concentration (mg/l) in pore water at W site (a) andE site (b). The concentration distributed the range
from 3 mg/l to 17 mg/l at W site, whereas it
distributed the range from 3 mg/l to 6 mg/l. The
plots with high concentration indicated highcontribution of fresh groundwater. The maximum
concentration at W was about 3 times of that at E.
This means recirculating seawater at E site contained
relatively high concentration of SiO 2 because of the
supply by the river. In addition, the variation ofconcentration was obviously smaller than NO 3 -The groundwater flux was 2.5m/day inmaximum and -4.0m/day in minimum. Thismaximum value was 100 times of the average flux
estimated based on water budget. The negative value
during the increasing tide indicated seawater
recirculation. The sum for three days showed thepositive value, while based on the huge difference
between the average flux and maximum indicatedalso large recirculation and heterogeneous183

SEE - Kyoto, Japan, Nov.18-20, 2020

was about 30 times of that at E because of the low
attenuation rate with high groundwater velocity.
4) The temporal variation in groundwater flux withtidal fluctuation indicated 2.5m/day in maximum
and -4.0m/day in minimum. This huge difference
between the average flux and maximum indicated
also
large
seawaterrecirculation
andheterogeneous distribution of SGD. This
heterogeneous distribution at this tidal flat would
contribute to the activity of seagrass and diversityof ecosystem.

distribution of SGD. This heterogeneous distribution
at W site would contribute to the diversity of thisecosystem on the tidal flat. Recently, seagrassbiomass is still active at W site as compared withthat at E site.

5. ACKNOWLEDGMENTS
This research was supported by JSPS KAKENHI
Grant 18H04151 and 18H03411. We appreciate thereviewers and editors for their suggestions, and Ms.
Morita and Mr. Hanioka for their cooperation.
6. REFERENCES[1] Duffy J. E., Biodiversity and the functioning ofseagrass ecosystems. Marine Ecology Prog. Ser.,
311, 2006, pp.233-250.
[2] Taniguchi M., Burnett W. C., Cable J. E., andTurner J. V., Investigation of submarine
groundwater discharge. Hydrol. Process., 16,2002, pp.2115-2129.
[3] Burnett W. C., Aggarwal P. K., Aureli A.,
Bokuniewicz H., Cable J. E., Charette M. A.,
Kontar E., Krupa S., Kulkarni K. M., LovelessA., 2006. Quantifying submarine groundwater
discharge in the coastal zone via multiple
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[4] Burnett W. C., Dulaiova, H., Radon as a tracer ofsubmarine groundwater discharge into a boat
basin in Donnalucata, Sicily. Cont. Shelf Res.,26, 7, 2006, pp.862–873.
[5] Saito M., Onodera S., Guo X. Y., Seasonalvariation of the 222Rn concentration in theCentral part of the Seto Inland Sea, Japan.
Interdisc. Stud. Environ. Chem. Terrapub, 6,
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[6] Santos I. R., Burnett W. C., Dittmar T.,
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[8] Onodera S., Saito M., Hayashi M., Sawano M.,
Nutrient dynamics with interaction ofgroundwater and seawater in a beach slope of

Fig. 7 Temporal variations in tidal level andgroundwater flux at the eastern part of Site W(shown in Fig.6 ).

Fig. 8 Temporal variations in tidal level and EC atthe eastern part of Site W (shown in Fig.6).

4. CONCLUDING REMARKSThis study examined to confirm spatial distribution
in groundwater (SGD) on tidal flats with the area ofaround 100m square in a small and steep island.
1) Based on the water budget, the groundwater flux
was estimated to be 8.68 m/yr or 23.9 mm/day inE, and 17.75 m/yr or 48.6 mm/day in W,
respectively.
2) Spatial distributions of groundwater contribution
ratio (%) in pore water at W was around 60% in
average, which was 8 times of that in E site.
3) The NO 3 -N concentration in pore water at W site
184

SEE - Kyoto, Japan, Nov.18-20, 2020

International Journal of GEOMATE, Vol.16,
Issue 56, 2019, pp.153-158.
[16] Rusydi A. F., Saito M., Ioka S., Maria R. andOnodera S., Estimation of ammonium sourcesin Indonesian coastal alluvial groundwaterusing Cl- and GIS. International Journal of
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[17] Nakada, S., Yasumoto, J., Taniguchi, M., andIshitobi, T., Submarine groundwater discharge
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Welch E., and El-Kadi A. I., Understanding
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G., Ohta T., and Chen J., Evaluation of thespatial distribution of submarine groundwater
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Marine Chemistry, 209, 2019, pp.25–35.
[20] Takeuchi T., Onodera S., Yamaguchi K. andKitaoka K., Estimation of sedimentation rate
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[21] Saito M., Onodera S., Okubo K., Takagi S.,
Maruyama Y., Jin G., and Shimizu Y., Effectsof physical and morphometric factors onnutrient removal properties in agricultural
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[11] Saito M., Onodera S., Jin G., Shimizu Y.,
Taniguchi M., Nitrogen dynamics in a highly
urbanized coastal area of western Japan: impactof sewage-derived loads. Progress in Earth andPlanetary Science, Volume 5, 2018, DOI:
10.1186/s40645-018-0177-6.
[12] Jin G., Onodera S., Saito M., and Shimizu Y.,
Sediment phosphorus cycling in a nutrient-richembayment in relation to sediment phosphorus
pool and release. Limnology, 2020,
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[13] Onodera S., Saito M., Yoshikawa M., OnishiK., Shimizu Y., and Ito H., Nutrient transportand surface water-groundwater interactions in
the tidal zone of the Yamato River, Japan. IAHS
Publication, 361, 2013, pp.204-211.
[14] Onodera S., Saito M., Sawano M., Hosono T.,
Taniguchi M., Shimada J., Umezawa Y., Lubis
R. F., Buapeng S., and Delinom R., Effects ofintensive urbanization on the intrusion ofshallow groundwater into deep groundwater:
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[15] Tomozawa Y., Onodera S. and Saito M.,
Estimation of groundwater recharge andsalinization in a coastal alluvial plain andOsaka megacity, Japan using δ18O, δD, and Cl-.

185

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ASSESSMENT ON MICROPLASTICS CONTAMINATION IN
FRESHWATER FISH: A CASE STUDY OF THE UBOLRATANARESERVOIR, THAILAND
Pattira Kasamesiri1, Charumas Meksumpun2, Shettapong Meksumpun3 and Chakhrit Ruengsorn3
Faculty of Technology, Mahasarakham University, Thailand; Thailand; 2Department of Fishery Biology,
Faculty of Fisheries, Kasetsart University, Thailand; 3Department of Marine Science, Faculty of Fisheries,
Kasetsart University, Thailand
1

ABSTRACTMicroplastic pollution is now a global issue. Reservoirs are an enclosed aquatic environment at risk fromaccumulation of microplastics. Few studies have used fish species as bio-indicators to monitor microplastic
contamination in reservoirs. Freshwater fish were caught by local fishermen from 10 stations around the
Ubolratana Reservoir, Thailand in October 2018 and the abundance, size, color and shape of microplastic particles
in their stomachs and intestines were investigated. Fourteen fish species were examined. Results showed that
96.4% of the fish had ingested microplastics at mean abundance of 2.92±1.30 particles per fish, with significant
differences of abundance between species. Microplastic abundance was highest in carnivorous fish Parambassis
siamensis (4.11±1.08 particles per fish). The most common size of ingested microplastics was over 0.5 mm(66.4%), with 51.0% as blue color and 98.2% fiber shaped. High levels of microplastics were ingested by fish
located in the middle and lower parts of the reservoir. Results revealed that blue fiber microplastics dominantly
observed in fish were derived from the breakdown of nets used for fishing activities.
Keywords: Microplastic pollution, Freshwater fish, Reservoir, Microplastic ingestion, Plastic waste

substances leach out from discarded microplastic
waste into the environment as both aquatic andterrestrial pollution [12].
Microplastic contamination occurs in the oceans
and also in freshwater. Nevertheless, researchconcerning microplastic pollution in freshwater
systems and aquatic animals remains limited. Highlevels of microplastic pollution in lakes [13]-[14] andriverine fish [15]-[16] have been reported. Reservoirs
are watershed areas that collect water from streams
and rivers. They are closely connected to the land asimportant sources of plastic waste and microplastics[17]. Moreover, reservoirs comprise importantfishery production habitats in South East Asia [18].
Therefore, pollution from microplastics may impact
fisheries’ products as a consumer health risk [18].
Here, the abundance, size, color and shape of
microplastics ingested by freshwater fish in the
Ubolratana Reservoir were quantified and assessed.
Results will be useful for biomonitoring microplastic
contamination in reservoirs and provide a databasefor fisheries to improve food security.

INTRODUCTION
In 1950, global plastic production was 2 million
tons. This increased to 381 million tons in 2015.
Seventy-five percent of primary plastic production
ends up as waste [1], while over half of the polymers,
synthetic fibers and additives produced are buried as
landfill or discarded and washed into rivers andoceans [1]-[2]. Degradation or fragmentation ofplastic waste generates microplastic pollution of theenvironment [2]-[3].
Microplastics are defined as small particles ofplastic less than 5 mm in length, and further
categorized according to their origin as primary andsecondary. Primary microplastics are manufactured
as small size for a specific purpose such as
microbeads in cosmetics, exfoliating personal care or
toothpaste [4], while secondary microplastics result
from the breakdown of larger plastic items bysunlight, wind or waves [5]. Types of microplastics
most commonly found on coastal beaches are lowdensity polyethylene (LDPE), polypropylene (PP)and polystyrene (PS) [5].
The direct effects of microplastics on aquatic
animals are both physical and nutritional. Plastic
ingredients and additives are indirectly transferredthrough aquatic food webs and impact food safety andhuman health [5]-[9]. Chemical substances added inplastic products to enhance polymer properties
include diethylhexyl phthalate, dibutyl phthalate,diethyl phthalate and benzaldehyde [10]-[11]. These

MATERIAL AND METHODS
Study Sites and Samples Collection
Study sites were located at the Ubolratana
reservoir, northeast of Thailand. This man-made lake
was opened in 1966 for electricity generation, flood
control, irrigation, etc. The reservoir aggregate water
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Table 1 Fish species habitats, feeding habits and abundance collected from 10 stations around the
Ubolratana Reservoir.

Species

HabitatFeeding
habitsTotal length(cm)

Weight (g)Abundance

Puntioplites proctozysron

Benthopelagic

Omnivore

7.77±3.53

13.82±7.5737Cyclocheilichthys repasson

Benthopelagic

Omnivore

9.45±2.06

8.18±3.25

14

DemersalCarnivore

4.81±0.64

1.40±0.61

18

Benthopelagic

Herbivore

13.52±4.84

27.14±17.22

22

DemersalCarnivore

12.43±1.1344.28±10.53

7

Labiobarbus leptocheilus

Benthopelagic

Planktivore

11.00±0.71

10.80±0.84

5Barbobymus goniontus

Benthopelagic

Omnivore

9.33±1.15

11.33±3.79

3Rasbora aurotaenia

Benthopelagic

Planktivore

8.91±0.55

5.35±0.80

10Clupeichtys aesarnensis

Pelagic

Planktivore

3.84±0.39

0.47±0.13

10

Mystacoleucus marginatus

DemersalCarnivore

5.83±0.98

2.73±1.4215Osteochilus vittatus

Benthopelagic

Omnivore

18.41±4.5345.72±21.16

8

Paralaubuca harmandi

Benthopelagic

Carnivore

10.64±3.45

4.86±2.29

7

Mystus mysticetus

DemersalCarnivore

12.87±1.28

19.83±4.02

6Hemibagrus spilopterus

DemersalCarnivore

17.10±2.4338.00±14.53

5

Parambassis siamensis
Henicorhynchus siamensis
Pristolepis fasciatusfrom the Nam Phong River, covered an area of two
provinces and flow into the Chi River (the longest
river of Thailand) with capacity 263,000 m3 and12,104 km2 of catchment area. The multi-purpose
reservoir was used for fisheries activity for longtime.
The maximum yield in fisheries have been up to2,480 ton/year in 1976 [19].
Fish samples were collected from ten samplingstations around the Ubolratana reservoir, Thailand(Fig. 1). Fish were caught by local fisherman using
gill nets during the rainy season of August andOctober 2018. Fish samples were weighed andmeasured for total length to an accuracy of 0.1 g and0.1 cm and then dissected to separate stomachs andintestines and stored at -20°C prior to examination for
microplastics in laboratory.

Microplastics were floated by saline solution then the
supernatant was pipetted and filtered through a glass
microfiber filter (Whatman GF/C 1.2 µm pore size).

Microplastic Extraction and Analysis
Fish stomach and intestine was defrosted anddigested with 30% H 2 O 2 in 50 ml Erlenmeyer flasks[20]. Volume of H 2 O 2 was based on weight ofstomach and intestine samples (approximately 30
ml/sample) and placed in an incubator at 65°C for 24
h. The separation of microplastics from extracted
solution used a saturated NaCl solution(approximately 300 g/L) which filtered and added
into the flasks then kept for 12 h at room temperature.

Fig.1 Location (UTM; 48Q) of the sampling stationsin the Ubolratana reservoir, Thailand.
The numbers, colors, sizes and physicalcharacteristics of microplastic particles on the glass
fiber filter were observed under a stereomicroscope(NikonSMZ745/745T).
Microplastics
weremeasured for their longest dimension andcharacteristics were divided into fibers, rods,

187

SEE - Kyoto, Japan, Nov.18-20, 2020

fragments, and pellets.
The abundance of microplastics between fish
species and sampling stations were analyzed by
Independent-Samples Kruskal-Wallis Test withsignificant difference was set as p-value less than 0.05.

2.20±1.24 particles/fish). The number of particles per
fish between species was also significant difference(p=0.001) with the highest ingested microplatics inParambassis
siamensis(average
4.11±1.08
particles/fish) (Fig. 3B). P. siamensis is a demersal
and carnivorous fish. There was significant difference
between habitats (p=0.016) and feeding habits(p=0.002) related to abundance of imcroplastics
ingested. The results showed that demersal andcarnivorous had the highest abundance of
microplastics particle of 3.49±1.32 and 3.29±1.33
particles per fish, respectively. The carnivorous fish
ingested microplastics than other feeding habits, thisdifference to the riverine fish in Skudai River,Malaysia that herbivorous fish had highest
microplastic ingestion (1.50±1.73 particles/fish) [25].

RESULT AND DISCUSSION
Percent of Occurrence and Abundance ofMicroplastics in Fish
Fish sample 167 individuals were identified into
14 species (Table 1). A total of 488 microplastics
particles were observed inside the stomach including
intestine with 96.4% of fish samples (163 individuals).
Ten fish species had 100 percent occurrence of
microplastics in their gastrointestinal tract (Fig. 2).
The percentage of occurrence microplastics ingested
by fish was higher than the Chi river of Thailand(72.9% from 8 species, n=107) [16] and the Pajeu
river, Brazil [22] (83% from 1 species, n=40) but
similar to that the high level and biological risks of
microplatics in Poyang Lake, China (90.9% from 1
fish species, n=11) [23].

A

B

Fig. 2 The percentage of microplastics occurrence infish gastrointestinal tract. Blue bar: ingested
microplastics; Orange bar: not ingested
microplastics.
The abundance of microplastics ingested by fishvaried from 0 to 6 particles per fish with an overall
average of 2.92±1.30 particles per fish, which lower
than the Poyang Lake (0-18 particles/fish) [23] andQinghai Lake (2-15 particles/fish) [24], China but
higher than riverine fish of The Chi river, Thailand(1.76±0.58 particles/fish). There was significant
difference in abundance of microplastics ingested byfish between sampling stations (Kruskal-Willis Test,
p=0.016). The abundance of microplastics per fishvaried among stations, the highest number of particles
per fish was at MP3 (average 3.79±1.25
particles/fish) (Fig. 3A). The tourist spot (Bang Saen
II Beaches) was located at MP3 (Fig. 1) that may
cause source of microplastics. Meanwhile, station
MP8 was located at upper part of reservoir had thelowed abundance of microplastics (averageFig.3 The mean abundance of microplastics between
sampling stations around Ubolratana reservoir(A) and mean abundance microplastics in fishdigestive tract by species (B). Error bar is ± SD.
Colors, Physical characteristics and size ofMicroplastic Particles
Four colors of microplastics were found in
gastrointestinal tract of fish which compose of blue,
black, transparent and red. The main colors of
microplastics in fish samples was blue (51.0%) (Fig.
4A), concurrent with the former studies such as fishin Chi River, Thailand [16] and Skudai River,Malaysia [25]. The color proportion of microplastics
in each fish species were similar (Fig. 5). Although
188

SEE - Kyoto, Japan, Nov.18-20, 2020

most of fish feed on resemble their prey [23],[26] but
our results showed that blue microplastics was
dominant color in all fish species. These may related
to the microplastics abundance in fish environment[23] and there were unexpectedly ingested while fish
feeding. Moreover, blue color was a favorite color offishing net which was used in the Ubolratana
reservoir.

China [23]. Source of fiber shape microplastics comefrom nylon rope, nylon line, fish cage, other fishinggear [27] and sewage from washing clothing made of
woven synthetic textiles [2],[28].
Ingested microplastics size ranged between 0.034.77 mm. The dominant size-class was larger than 0.5
mm (66.4% of total plastic particles) (Fig. 4C).
Microplastics fiber shape are usually classified intolarge size over 0.5 mm [16]. These size rage weresimilar to study in Poyang Lake, China foundmicroplastics in fish gut larger than 0.5 mm,
accounting for 82.1% of total plastic particles [23].
The dominant of color, shape and size in present
study were blue fiber and larger than 0.5 mm. The
result showed impact of plastic fishing gear whichused in fisheries around reservoir to the abundance
and physical character of microplastics. Damaged or
unusable fishing gears disposal, net repairing andother fishing related activities increased abundance of
microplastics as PA nylon in aquatic environments[27], finally could transport to aquatic organism likefish [13].
Freshwater fish collected in this study are commercial
fish in local market of Thailand and some species
were made into fishery products such as pickled fish.
Thus, the potential consumer health risk can be higher
when microplastics comtaminated in fish [9].
However, the monitoring and mitigation of
microplastics pollution must be continue investigatedand including the detrimental impact to aquatic
ecosystem and human health.

A

B

CONCLUSIONSC

The assessment on microplastics contamination
can be used fish species as bioindicators. The
abundance of microplastics ingested by fish in the
Ubolratana reservoir has nearly reached to high-levelcontamination in freshwater fish compared to resultsof previous studies in freshwater systems.
Opportunities to convey microplastics through thefood chain must be concerning and monitoring.
Physical chracters of microplastics indicate their
origin as mainly from damaged fishing gear such as
fish cages and gill nets.
ACKNOWLEDGMENTS

Fig. 4 Percentage of microplastics ingested by all fishsamples base on color (A), shape (B) and size
(C).

Laboratory operations were supported by the
Research Unit of Excellence for Tropical Fisheries
and Technology and Mahasarakham University. We
would like to convey our special thanks to Sukhawit
Noisena for assisting with field operations andensuring project success.

Three shapes of microplastics were found in fish.
The common shape of microplastics ingested by fish
was fiber (98.2%) followed by pellet and rod,
respectively (Fig. 4B). Fiber character ofmicroplastics were also a major shape in other reports
such as in waters and sediments of Magdalena,
Colombia [2] and Taihu Lake, China [14], in fish gutof Chi River, Thailand [16] and fish of Poyang Lake,
189

SEE - Kyoto, Japan, Nov.18-20, 2020

15%

10%

17%
25%

11%

19%

28
%

56%

27
%

47%

Puntioplites proctozysron
8%

Cyclocheilichthys repasson

8% 12%

20
%
20
%

72%

16 9%
%

Labiobarbus leptocheilus
30%

Barbobymus goniontus
13% 13%37%

Mystacoleucus marginatus

Rasbora aurotaenia

13%

65
%

73
%

Osteochilus vittatus

9% 14%

Clupeichtys aesarnensis
14%

23%
12%

37
%
33
%

56%

55
%

42
%
25
%

18 18%%

37%

Parambassis siamensis
33
%

55
%

Pristolepis fasciatus

19
%

33
%

5%

Henicorhynchus siamensis

9%

12%

Paralaubuca harmandi

20
%

32%
45
%

Mystus mysticetus

80%

Hemibagrus spilopterus

Fig. 5 Composition of microplastics particles colors in each fish species.
Vol. 703, 2020, pp. 135504[4] Lusher A., Hollman P. and Mendoza-Hill J.,
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Fisheries and Aquaculture Technical Paper, Vol.
615, 2017, pp. 1-126.
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and Chubarenko I.P., Secondary Microplastics
Generation in the Sea Swash Zone with Coarse
Bottom Sediments: Laboratory Experiments.
Frontiers in Marine Science, Vol. 5, 2018,

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191

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

CHARACTERISTICS OF CULTURAL LANDSCAPE AS
STREETSCAPE IN KUDOYAMA TOWN
Tomoko Miyagawa1, Rena Ozaki2, Kyota Matsuyama3, Shinpei Yamamoto4
and Masahiro Takasago1
1
Faculty of Systems Engineering, Wakayama University, Japan; 2 Takara Standard CO., LTD., Japan;
3
Fukuvi Chemical Industry, 4Kudoyama Town Office, Japan

Managing historic environment and cultural heritage in partnership with the community are becoming more
important, due to the recent trend of shrinking society and limited resources. This study aims to clarify thecharacteristics of cultural landscape as streetscape forming townscape managed by the community in the town
centre of Kudoyama, Wakayama Prefecture. This paper focuses on streetscape and site boundary objects as local
resources. Field observations and literature reviews on cultural landscapes are used for study methods. From theresults, characteristics of the town center of Kudoyama became clear as follows; the narrow and winding streetsfrom the past times have been confirmed to form one of its characteristics of local resources in comparison withthe old map of the year of 1767; many of the narrow streets connected to two main streets are not more than threemeters; the differences of topography were 29.9 meters at the most within the size of 200 by 600 meters to create
steep slopes and retaining walls made by stones or concrete; and site boundary objects to form streetscape, i.e.,
hedgerows, stone or concrete retaining walls, and Japanese style walls. As conclusion, the streetscape of town
center of Kudoyama have unique characteristics and changing landscape by enclosure with narrow and winding
streets as well as site boundary objects in undulating landforms.
Keywords: Partnership, Cultural landscape, Community, Local resources

INTRODUCTIONManagement of Cultural LandscapesManaging historic environment and cultural
heritage in partnership with the community are
becoming more important, due to the recent trend of
shrinking society and limited resources. Working in
partnership can promote the importance of ‘viewing
the landscape from a variety of perspectives’ [1]-[2],which often has been discussed the differences ofviews and values between ‘outsiders’ and ‘insiders’[3]. Working in partnership can also help to create its
own network of people, knowledge and experience,as well as to diversify actions which may lead toincrease other partners.
In terms of managing historic environment andcultural heritage, it would be necessary to understanda diversity and complexity from a wider scale [4], i.e.,
local resources managed by the community, and the
local authority by being registered as culturalproperties. Thus, this study tries to cover perspectivesof community as living environment which also could
form cultural landscape as streetscape.
Cultural Landscapes
Kudoyama

of

Town

Centrein

The town has a World Heritage Site, pilgrimage

routes to Koyasan registered by the UNESCO, as apart of Sacred Sites and Pilgrimage Routes in the Kii
Mountain Range in 2004, and 2016. Along with theworld and national importance of heritage, the town
has a townscape and landscape formed by its
landforms surrounded by the rivers and mountains.
The long-term plan of the town aims to foster local
resource such as historic environment and creating
opportunities for communication between residents
and visitors to overcome structural changes of
population [5]. Based on the questionnaire survey on
the awareness and future images of the town toresidents of town center in Kudoyama in 2016
responded by 108 people in total, it became apparent
that 80 percent of residents are willing to welcome
visitors, as well as nearly 70 percent of residents
agreed on conserving historic buildings andtownscape [6]. According to related research,
townhouses and a part of local resources has beenclarified [7]. However, there are other characteristics
as streetscape. Therefore, this study focuses onstreetscape and site boundary objects to clarify othercharacteristics of town center in Kudoyama.
The concept of local resources has been
described by Miyayama and Kamihogi which can bedivided into ‘natural elements’ and ‘historicelements’, and streets and landforms are in the
category of ‘natural elements’ [8]. Streetscape inresidential areas is formed by houses, exterior, parks
192

SEE - Kyoto, Japan, Nov.18-20, 2020and streets as such, and within exterior, plantings
such as hedgerows, gates, walls, and parking spaces
are included, and in particular, plantings grow andchanges by residents with their individuality [9].

residents (Fig 2). Particularly, it addresses the issuesof traffic and access, and risks in case of emergency.

The Aims and Methods of This Study
This study aims to clarify the characteristics ofcultural landscape as streetscape forming townscapemanaged by the community from the perspectives on
the cultural landscapes in the town centre of
Kudoyama, Wakayama Prefecture.
This paper
focuses on streetscape and site boundary objects as
local resources.
This study undertook fieldobservations including measuring widths of streetsand lengths of site boundary objects by steps andliterature reviews on cultural landscapes to study themethods. In terms of the analysis of streetscapes, thisstudy tries to examine the width of streets anddifferences of inclination in slopes focusing on
narrow streets connected by two major, wider streets
running from the east to the west of the town centerof the Kudoyama. This study also examines thelengths by steps and location of site boundary objects
including retaining walls, i.e., hedgerows, stone or
concrete walls, as well as Japanese style walls andiron fences. In terms of Japanese style walls, thisstudy classified walls made by wood, clay, tiles,
plaster, and stones which encloses houses andtemples.

Fig. 1 Townhouses creating streetscape of
Kudoyama

An Evaluation of Residents Concerning
Townscape of Town Center in Kudoyama

Fig. 2 Streetscape with a narrow street and slopes

An awareness survey to residents per householdin town center of Kudoyama has been conducted in2016, collecting 108 answers out of 270 houses at 40
percent [6]. From the results, 80 percent of residents
are welcoming visitors for sightseeing to enjoy
townscape, thus, residents are largely recognizing
townscape as one of the characteristics of the town [6].
In terms of conservation of townscape in the future,
residents value conservation of historic houses at 39
percent, while conservation of townscape as a whole
town at 29 percent [6].
On the other side, the highest concern of
residents was about streets at 46 percent [6]. The
reasons for the concern about streets, 82 percent has
been responded for the width of streets, and 8 percent
for aging and slope of streets [6]. Particularly, thenorthern area of the town center has steep slopes withnarrow width. Therefore, in terms of street width, themain street has 4.4 meters, while one of the narrowest
streets has 1.04 meters [6].
From the above, residents are welcoming visitorsand conservation of townscape has been largely
recognized (Fig 1). The narrow and winding streetsfrom the past times to form one of its characteristics
of local resources, coincides to be a major concern for

STREETSCAPES IN THE TOWN CENTRE OF
KUDOYAMAA Classification by The Width of Streets
In terms of the width of streets, it became clearthat many of them are less than 2 meters at nearly 80
percent, while more than 2 meters at around 20
percent in total (Table 1, Fig. 3).
Table 1 A Classification by the width of streets [10]Items
Less than 1m
1m to 1.5m
1.5m to 2m
2m to 2.5m
2.5m to 3m
More than 3m
Total

numbers
6
9
9
4
1
2
31

percentages
19%
29%
29%
13%
3%
7%
100%

A Comparison of Street Patterns
In comparison with the old map of the year 1767,
193

SEE - Kyoto, Japan, Nov.18-20, 2020

many of the narrow and winding streets remain in thesimilar pattern (Fig. 4).
Legends
Less than 1m
1m to 1.5m
1.5m to 2m
2m to 2.5m
2.5m to 3m
More than 3m

N

Fig. 6 A narrow slope with stone walls [10](m)

The town is located between two rivers of theKino and the Nyu which created river terraces, andthe differences of topography were 29.9 meters at themost within the size of 200 by 600 meters to create
steep slopes (Fig. 5). Due to the topography, houses
are built on retaining walls made by stones orconcrete which also create characteristics ofstreetscape, i.e., stone walls along the narrow slope(Fig. 6).

Fig. 3 The width of narrow streets (amended) [10]SITE BOUNDARY OBJECTS IN THE TOWNCENTRE OF KUDOYAMAA Classification by Site Boundary Objects
Site boundary objects can be classified into seven
items (Table 2). Concrete walls and concrete
retaining walls are at nearly half of all; and retaining
walls account for at 25 percent in total. The
traditional styled objects were also found at 35.5
percent in total, i.e., hedgerows, stone walls and stone
retaining walls, and Japanese style walls.

N(m)Fig. 4 The old streets remained since 1767 (amended)[10]

Table 2 A Classification of site boundary objects(amended) [11]The Topography Creating Slopes and Retaining
Walls

Items
Concrete walls
Iron fences
Hedgerows
Japanese style walls
Stone walls
Stone retaining walls
Concrete retaining
walls
Total

Legends

10m
1m
More than 6m
Every 1m
Less than 95m

numbers
207
102
52
34
21
91
45

percentages
38%
18.5%
9%
6%
4%
16.5%
8%

552

100%

A Japanese Style Walls
Many of them are constructed on its own.
However, some houses and temples such as the
Sanada Monastery, the Kayanoke House, and theFig. 5 The contour map (amended) [10]194

SEE - Kyoto, Japan, Nov.18-20, 2020

on sites to be able to view trees over the walls (Fig. 79).
Stone Retaining Walls
Stone retaining walls has been confirmed up to
91 places in the town center of Kudoyama (Fig. 10).
Many of them are located along narrow streets withsmaller scale, thus, length is mostly within 30 steps[11]. Stone retaining walls are constructed on its own
i.e., a foundation for houses (Fig. 11), as well as to be
combined with other site boundary objects, such aswith Japanese style walls (Fig.7). To highlight its
characteristics with high walls, it is utilized into aplace for the notice board along streets (Fig.12).
Fig. 7 Japanese style walls on the stone retaining
walls [11]

1-10
steps

Fig. 8 A Japanese style wall at the Sanada Monastery
[11]

11-20
steps

21-30
steps

31-40
steps

41-50
steps

More than
50 steps

Fig. 10 Locations and lengths of Stone retaining
walls (amended) [11]The KayanokeHouse
The Henshoin
TempleThe Sanada
Monastery
(m)

1-10
steps

11-20
steps

21-30
steps

31-40
steps

41-50
steps

More than
50 steps

Fig.11 A stone retaining wall as a foundation for a
traditional house

Fig. 9 Locations and lengths of Japanese style walls(amended) [11]Concrete Retaining Walls

Henshoin temple have larger sites so that it creates
continuous and longer Japanese style walls on stone
or concrete retaining walls as well as having gardens

Concrete retaining walls along streets can be
confirmed at 45 places. Many of them are confirmed
to be within 11 to 20 steps, in the case of construction
195

SEE - Kyoto, Japan, Nov.18-20, 2020

DISCUSSIONS
From the results, the pattern of some of thenarrow streets are winding or joining to other narrow
streets, which may create unique streetscapes but may
also create difficulties in way finding particularly forvisitors. Therefore, the old streets are also creating
characteristics of streetscape in Kudoyama [10].
The other characteristics of streetscape is slopes
created by topography in the town center ofKudoyama. In terms of topography, it is higher andsteep in the north-eastern side, while the southwestern side tends to be lower and gentle along the
Nyu [10]. This may also be one of the reasons of
having a significant amount of constructed retaining
walls. For example, stone retaining walls has been
constructed to reconcile undulations of its landformfrom the past times. Therefore, it tends to beconcentrated in the edge of the town where aconcentration of contours with a terraced landscape
towards surrounding rivers, which is illustrated in thecontour map showing, Fig.5. For concrete retaining
walls, many of them are located around the edge ofthe town center, towards the Kino river and along amain road in parallel to the Nyu river. This is becauseof undulation of landforms, therefore, it is constructedon the places with differences in height in similar tostone retaining walls.

Fig.12 A stone retaining wall along streets utilized
into a place for the notice board
for individual sites. However, there are some caseswith more than 30 steps where the construction isshared with several sites to be a foundation forbuildings or houses which create continuous walls(Fig.13). In addition, the height of walls may create
impacts on landscapes by having majority of views(Fig.14) [11].
The Kino river

CONCLUSIONS
Based on survey and observed research,characteristics of the town center of Kudoyama
became clear as follows; the narrow and winding
streets from the past times have been confirmed toform one of its characteristics of local resources incomparison with the old map of 1767; many of thenarrow streets connected to two main streets are notmore than three meters; the differences of topography
were 29.9 meters at the most within the size of 200 by
600 meters to create steep slopes and retaining walls
made by stones or concrete; and site boundary objects
to form streetscape, i.e., hedgerows, stone or concrete
retaining walls, and Japanese style walls. To
conclude, the streetscape of town center ofKudoyama have unique characteristics and changing
landscape by enclosure with narrow and winding
streets as well as site boundary objects in undulating
landforms.

The Nyu river

1-10
steps

11-20
steps

21-30
steps

31-40
steps

41-50
steps

More than
50 steps

Fig. 13 Locations and lengths of concrete retaining
walls (amended) [11]ACKNOWLEDGEMENTS
The authors would like to express our gratitude forthe financial support provided to the cultural heritage
utilization and community activation project from the
Agency for Cultural Affairs.
REFERENCES
Fig. 14 A concrete retaining wall along a road [11]196SEE - Kyoto, Japan, Nov.18-20, 2020

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[7] Miyagawa T., Yamaguchi S., Yoshino (Aoyama)S., Yamamoto S., and Takasago M.,
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A study on front yards and street-scapes insuburban housing development practices -thechanging process of ready-built houses for sale inJapan part 2 -, Journal of Architecture andPlanning, No.590, Apr., 2005, pp.9-15 (inJapanese).
[10] Ozaki, R., Research on Alleys in Oazakudoyama, Kudoyama-cho, a dissertation
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Wakayama Univ., 2018, pp.1-40 (in Japanese).
[11] Matsuyama, K., Research on borders in town
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Systems, Wakayama Univ., 2019, pp.1-39 (inJapanese).

197

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

UTILIZATION OF ACTIVATED CARBON FROM PALM KERNELSHELLS AS THE BIOADSORBENT OF LEAD WASTE
Muhammad Faisal1, Asri Gani1, Zahrul Fuadi2
Department of Chemical Engineering, Universitas Syiah Kuala, Banda Aceh, Indonesia
2
Department of Mechanical Engineering, Universitas Syiah Kuala, Banda Aceh, Indonesia
1

ABSTRACTThis research aimed to evaluate the use of palm kernel shells for activated carbon to adsorb lead (Pb) ions.
The pyrolysis was performed on oil palm kernel shells at a temperature of 380oC to obtain charcoal which was
reduced using a ball mill. The charcoal was then chemically activated with liquid smoke. Before and after
activation, the sample of charcoal was assessed with scanning electron microscopy (SEM). The activated carbon
was then used to adsorb Pb (II) ions in concentrations of 30, 60, 90, 120, and 150 mg/L. The adsorption process
was performed in a batch reactor with contact times of 30, 60, 90, 120, 150, and 180 minutes at an agitation
speed of 150 rpm. The initial concentration of Pb (II) ions and concentration after adsorption were determinedwith an atomic absorption spectrophotometer (AAS). Research has shown that initial concentrations and contact
times affect the efficiency of Pb (II) removal. The highest adsorption efficiency (> 90%) was obtained at acontact time of 150 minutes and an initial concentration of 60 mg/L. Pb adsorption onto the activated carbon ofpalm kernel shells demonstrated best fit with both Langmuir and Freundlich isotherm models. Kinetics studies
showed that the pseudo first-order reaction was more suitable (R² = 0.9359).
.
Keywords: Palm kernel shell charcoal, Pb (II), Activated carbon, Pyrolysis, Liquid smoke

poisoning in childhood can cause neurotoxic
disorders, cancer, and damage to the kidneys,
pancreas, brain, and liver [7]–[9]. To avoid its
harmful effects on living things, heavy metal
concentration has to be reduced to a safe level byproperly treating the waste before discharge into
water systems.
There are several ways to remove heavy metals
like Pb from wastewater, including precipitation andion exchange, electrodialysis, evaporation, andabsorption using activated carbon [10]. The mostfrequent problem in heavy metal waste treatment is
its high cost, thus, effective and low-cost techniques
are needed. One such technique is adsorption. The
adsorption process occurs on the surface of theadsorbent material’s pores, and the metal in theliquid undergoes a process of transferring metal
mass from the liquid to the adsorbent’s surface [11].
This is among the most frequently used methods forremoving toxic metals from wastewater [12].
Adsorption is a physical–chemical process in which
the adsorbates—in this case, the pollutants—
accumulate on the surface of solids used asadsorbents. The process is suitable for wastewaterwith low metal concentrations, especially inindustries with limited financial resources [13],[14].
Many types of adsorbent have been developed toremove Pb from wastewater, including zeolites[14],[15], Ethylene diamine tetra acetic acid (EDTA)
magnetic graphene oxide [16], papaya seed [17],chlorapatite nanoparticles [18], montmorillonite

INTRODUCTION
The continual expansion of industrialization has
accelerated developments in the chemical industry,causing increased industrial waste—more and moreis being discharged into the environment. Nature's
capacity to tolerate the burden of waste is very
limited, and it is believed that its normal selfpurification systems have been exceeded. Amongthe wastes that pollute the environment and cause
disturbing water pollution today are heavy metals,
such as lead ions (Pb), commonly found in theindustrial waste of manufacturers of batteries, paper,
metallurgy, explosives, paints, and other colouring
materials [1]–[3]. Pb (II) is a soft, blackish-brown
metal that is easily extracted from mining. It comesfrom the earth's crust in the form of pure, organic,
and inorganic material. Industrial processes play animportant role in increasing the levels of this heavy
metal.
Lead belongs to the group of toxic metals that areharmful to living things accumulatively and noteasily degraded [4],[5]. Pb compounds can enter thehuman body through the respiratory and digestive
tracts or through direct contact with the skin.
According to the US Environmental Protection
Agency (EPA), lead tolerance levels in drinking
water and wastewater are 0.015 and 0.1 mg/L,
respectively [6]. Levels of Pb higher than theselimits are known to poison the human body bothacutely and chronically. In addition, continuous Pb
198

SEE - Kyoto, Japan, Nov.18-20, 2020[19], Areca catechu shell [20], palm tree leaves [21],chitosan [22], modified bentonite and magnetic
cellulose [23], charcoal from celery [24], rapeseedbiomass [25], the bark of Cordia macleodii trees[26], and natural zeolite [27]. The challenge inadsorption technology is to select economical andefficient alternative adsorbents to minimize
operating costs, especially in developing countries[28]. An alternate adsorbent that has been proposed
is charcoal from oil palm shell pyrolysis. Before
being used to adsorb heavy metals, the charcoal isactivated chemically and physically. Several studies
have shown that the activated carbon from thepyrolysis process is capable of removing heavy
metals with fairly high removal efficiency [29]. This
research aims to study the ability of activated carbon
from pyrolysis of oil palm shells to remove Pb (II).

filtrate was separated by centrifuging. Pb (II)analysis was carried out using AAS (AA-7000,
Shimadzu, Japan).
RESULTS AND DISCUSSION
Adsorbent Characteristics
Figures 1a and 1b show the results of SEM
analysis of the palm shell carbon before and after
activation. Surface morphology showed a bettersurface after activation by liquid smoke than before.
The figures also show that the size of the activatedcarbon particles reached nanometres, that is, below
500 nm. Particles of the liquid smoke-activatedcarbon have a smaller size than that of NaOHactivated carbon particles under the same conditions
and activation methods [29], demonstrating that
activation in an acidic atmosphere reduced the sizeof the active carbon particles. Liquid smoke as anactivator contains various chemical compounds,
such as acetic acid, phenolic compounds, and othercompounds with varying concentrations [32[,[33],allowing the adsorbent’s surface to adsorb metal
ions. In Figure 1, it can also be seen that the shape of
the activated carbon surface was uneven but thatnanometre sizes of the activated carbon dominated.

MATERIALS AND METHODS
Preparation of Activated Carbon from Oil Palm
ShellsA pyrolysis reactor (stainless steel, homemade)with a height of 60 cm and an inner diameter of 40
cm was used to pyrolyze palm shells at 380°C. The
temperature in the reactor was kept constantthroughout the pyrolysis. The procedure for making
charcoal and liquid smoke followed that in previous
studies [30],[31]. Five kg of palm shells were loaded
into the reactor, and the reactor was tightly sealed. A
steam channel in the lid connected to the condenser
unit condensed the vapor into liquid smoke. Afterthe pyrolysis process was complete, the reactor was
opened and the resulting charcoal was ground in aball mill for 24 hours to reach nano size particles.
The charcoal was then activated using the liquidsmoke, previously purified by distillation, by
immersing it in the liquid smoke solution for 24hours. Then the activated carbon was filtered andwashed with distilled water to a neutral pH before
being dried in an oven dryer at a temperature of
105°C until the weight became constant. The surface
morphology of the activated carbon was analysedusing scanning electron microscopy (SEM) (JEOLJSM 6510 LA, Shimadzu, Japan).

(a) Before activation

Adsorption Test
Carbon nanoparticles activated by liquid smoke
were then used to adsorb Pb metal prepared from alead sulphate (PbSO 4 ) solution. The initialconcentration of Pb (II) varied from 30, 60, 90, 120,
to 150 mg/L. On hundred ml of PbSO 4 was put into
an Erlenmeyer and one gram of adsorbent was added
and stirred at 150 rpm speed. The contact times
between Pb (II) and adsorbent solutions were 30, 60,
90, 120, 150, and 180 min at room temperature.
After the adsorption process was complete, the(b) After activation
Fig. 1 SEM analysis of the palm shell carbon before
and after activation.

199

SEE - Kyoto, Japan, Nov.18-20, 2020

with increasing initial concentration. Low adsorption
efficiency at 180 min was due to the saturation of
the adsorbent's surface impeding further adsorption.
At this point, the diffusion and adhesion of adsorbed
solute molecules occurred more, thereby increasing
the adsorption efficiency. The same trend has beenreported in the literature for lead adsorption using
zeolite-NaX [35]. The results of this study indicatethat for all contact times, the greater the initialconcentration, the smaller the absorption efficiency
produced. Thus, in this study, the adsorption of Pb(II) was preferred at low initial concentrations.

Effect of Contact Time and Initial Concentrationon the Adsorption Efficiency of Pb (II)Figure 2 shows the effect of contact time on theadsorption efficiency of Pb (II) at various initialconcentrations. At 150 rpm agitation, an initialconcentration of 30 mg/L and a contact time of 30
min, as shown in Figure 2, the adsorption efficiency
was 75%. At the beginning of the adsorption of Pb(II) metal ions, the adsorbent surface had notabsorbed much, so the adsorption process was lesseffective. This due to at a contact time of 30 min, theadsorbent and adsorbate had not fully bonded,resulting in fewer adsorbed ions. The adsorption
efficiency increased to 92% at min 150.

Isotherm Studies
Changes in the adsorbate concentration by theadsorption process following the adsorption
mechanism can be studied by determining theadsorption isotherm. Isotherm studies were carriedout to determine the adsorption equilibrium,
capacity, and mechanism. The Freundlich andLangmuir isotherm models are most commonly used
to analyse equilibrium data. The Freundlich isotherm
model is applied to multilayer adsorption with aheterogeneous distribution. The model provides a
relationship between solid and liquid concentrations
and is very helpful in connecting isotherm datacollected in various concentrations.

Removal Efficiency (%)

100
80
60
40

30 ppm90 ppm
150 ppm

20

60 ppm120 ppm

0030

60 90 120 150 180
Contact Time (min)10

Removal Efficiency (%)

Fig. 2 The effect of contact time on the adsorption
efficiency of Pb (II) at various initial concentrations.

y = 0.1097x + 1.1323
R² = 0.9359

Ce/Qe

8

100

6
4
2

80

0

60

0

40

30 min90 min
150 min20

60 min
120 min20

40
Ce (g/ml)6080Fig. 4 Isoterm Langmuir.

0
0

30
60
90
120
150
Initial Concentration (ppm)1

y = 0.3224x + 0.3222
R² = 0.9701

0.8
Log (Qe)

Fig. 3 The effect of initial concentration on theadsorption efficiency of Pb (II) at various contact
times.
Figure 3 shows the effect of initial concentration on
the adsorption efficiency of Pb at various contact
times. At an initial concentration of 60 mg/L, theadsorption efficiency for contact times of 30, 60, 90,
150, and 180 mins were 70%, 72%, 73%, 73%, 77%,93%, and 34%, respectively. The same trend wasobserved for all contact times (i.e., 30, 90, 120, and
150 min). The efficiency of adsorption decreased

0.6
0.4
0.2
0
0

0.5

1
Log Ce1.5

Fig. 5 Isoterm Freundlich.
200

2SEE - Kyoto, Japan, Nov.18-20, 2020

linear if the value of R L = 1, irreversible if R L = 0,
and unfavourable if R L > 1 [35]. Figure 6 shows therelationship between the initial concentration andseparation factor values for Pb (II) adsorption.
As shown in Figure 6, the value of R L at an
initial concentration of 30 mg/L was 0.25, and it
dropped to 0.05 at an initial concentration of 150
mg/L. The R L values are between 0 and 1 for all
initial concentrations, demonstrating that theadsorption process is favourable.

The Langmuir isotherm model assumes
monolayer adsorption with a homogenous
distribution of energetic adsorption sites. The
Langmuir and Freundlich adsorption isotherm
models on Pb metal are shown in Figures 4 and 5,
respectively. Figures 4 and 5 show that the R2 values
for Langmuir and Freundlich were 0.93 and 0.97,
respectively. This indicates that the adsorption of Pb(II) metal using liquid smoke-activated charcoal
from palm shells tended to follow the pattern of thetwo isotherms, namely the adsorption of monolayers
on the adsorbent’s outer surface and multilayer
adsorption on heterogeneous surface sites. Table 1
shows the parameters and constants of the Langmuir
and Freundlich isotherms. As can be seen from theTable 1, the Freundlich constant (K F ) representing
adsorption capacity was 2.099 mg/g with adsorption
intensity (n) of 3.101. The K F obtained from thisresearch was higher than the results of Lou et al.
[23]. For the Langmuir isotherm, the adsorption
ability (qm) of the activated carbon to adsorb Pb
ions was 9.11 g/mg. This value was lower than thatof previous studies using zeolite-NaX adsorbents[34]. The strength of the interaction between Pb (II)ions and the activated carbon is indicated by thevalue of K L , which was 0.096. Previous studies
reported that Pb (II) adsorption using chitosan-gmaleic anhydride-g-methacrylic acid copolymer
tended to follow the Freundlich isotherm [22],whereas the adsorption of Pb (II) using adsorbentsfrom rapeseed biomass tended to follow theLangmuir isotherm [25].

Separation Factor

0.3
0.2
0.15
0.1
0.05
0
30

60
90
120
Initial Concentration (mg/L)

150

Fig. 6 The relationship between the initialconcentration and separation factor for Pb (II)adsorption.
CONCLUSIONS

Table 1. Constant values of both Langmuir andFreundlich isotherm models of Pb (II) adsorption
Langmuir

0.25

Freundlich

R2qm(mg/g)

KL(L/mg)R2

n

KF(mg/g)

0.935

9.11

0.096

0.970

3.101

2.099

In the Langmuir isotherm, to assess whether theadsorption process is favourable, irreversible, or
unfavourable, the dimensionless separation factor(R L ) value can be used, which is calculated with thefollowing equation:
1
𝑅𝑅𝐿𝐿 =
1 + 𝐾𝐾𝐿𝐿 𝐶𝐶𝑖𝑖

This research investigated the ability ofadsorbents from palm kernel shell charcoal activatedby liquid smoke to adsorb Pb (II) metal ions. The
SEM test results showed that the activatedadsorbents had better pore size for adsorption. At
contact times of 30–150 min and initialconcentrations of 30–150 mg/L, the efficiency of Pb(II) absorption ranged from 40% – 93%. At a contact
time of 180 min, efficiency dropped dramatically asa result of the adsorbent's saturation. The best
condition was achieved at 150 min contact time andan initial concentration of 30 mg/L. The results of
the isotherm equilibrium analysis showed that theadsorption process was suitable for the Langmuir
and Freundlich isotherm models.
.
ACKNOWLEDGMENTS
The work was financially supported by
Universitas
Syiah
Kuala
(GrantNo.
289/UN11/SP/PNBP). We wish to thanks Sandi
Putra Kelana and Dodi Eko Nanda for conducting
experiments and data analysis.

where K L = Langmuir constant and C i = initialconcentration.

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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto Japan Nov 18-20 2020 ISBN: 978-4-909106056 C3051

EFFECT OF BIOAUGMENTATION AND PHYTOREMEDIATION ON
DEGRADATION OF PARAQUAT IN CONTAMINATED SOIL
*Mullika Teerakun1, Pensri Plangklang2, Koson Rueangsan3 Piyachat Wiriyaampaiwong1 and Piyawadee
Sarapirom4
1
Faculty of Agricultural Technology, Kalasin University, Thailand; 2Faculty of Technology, Khon Kaen
University, Thailand; 3Faculty of Engineering and Industrial Technology, Kalasin University, Thailand;
4
Faculty of Science and Technology, Rajabhat Mahasarakham University, Thailand

ABSTRACT
Paraquat degrading consortium was isolated from rhizosphere soil collected from the field with a history of
paraquat application. Paraquat removal from soil with natural attenuation (NA), bioaugmentation (BA), andcombined bioaugmentation and biostimulation (BAS) treatments were investigated in comparison to control(autoclaved soil without any treatment). The experiments were conducted with the initial paraquat concentrationof 80 mg/kg soil. At day 60, paraquat removal of 44% was observed in NA treatment. Bioaugmentation with theisolated consortium (BA treatment) enhanced paraquat degradation in soil with the removal percentage of 76%
while the BAS treatment increased the removal efficiency to 84%. The half-life of paraquat in soil with BA andBAS treatments were shorter than 20 days. Phytoremediation (PR) and combined bioaugmentation andphytoremediation (BAP) treatments were further investigated for bioremediation of paraquat in soil at the initial
paraquat concentration of 80 mg/kg soil. The BAP treatments gave the higher paraquat degradation efficiency incomparison to the PR treatments in which the removal percentages of greater than 95% were achieved in BAP
treatments with african sesbania (Sesbania rostrata Brem. and Oberm.), jack bean (Canavalia ensifomis (L.) DC.)or pinto peanut (Arachis pintoi).
Keywords: Pesticide, Bioremediation, Biodegradation, Rhizosphere remediation.

used for the treatment of environmental contaminantswith the advantages, compared to chemical andphysical methods, of cost-effective, easy to maintain,
and highly effective with low contaminantconcentrations [5]. Bioaugmentation is one ofbioremediation techniques that application of
microorganisms to improve the biodegradative
capacities of contaminated sites to accelerate theremoval of undesired compounds [6]. This techniqueis adding indigenous or exogenous or geneticallymodified microorganisms that capable to degrade
pollutants on contaminated media to enhance the rateof contaminant biodegradation in the affected soil orwater because of the density of contaminant-specificdegraders might have been artificially increased [7].
It is the most advantageous method for cleaning-up
soil contaminated with pesticides [8]. The
bioaugmentation found that significantly enhanced
the degradation of pesticide compared withuninoculated soil, and the shortest half-life ofpesticide was detected in the bioaugmentation
treatment of soil [9-10]. One of bioremediation
strategies is phytoremediation which using plants toremoved, immobilized, or degraded contaminantsfrom the environment [11]. It is an in situ, costeffective, easy to adopt, eco-friendly approach forenvironmental remediation and has entered inactive
developmental phase [12]. Some pesticides which

INTRODUCTION
Paraquat (1,1’-dimethyl-4,4’-bipyridinium) is a
non-selective contact herbicide in the group ofquaternary nitrogen compounds. It is a postemergence herbicide that can disrupt thephotosynthesis of the leaves when sprayed into thegreen plant tissue [1]. Paraquat is widely used inagricultural areas because it gives a rapid result,convenient to use, and low cost [2]. Based on theimport statistics of pesticides in Thailand, paraquat is
top ten rankings of imported substances. In 2019,
paraquat was imported in second place with a highamount of 22,162,440.58 kg [3]. The increasing of
paraquat usage causes dispersion and accumulation
into the environment, which have both direct andindirect effects on living and human life. Paraquat ishigh water-soluble and high organic matter affinity, it
can be easily spread and readily adsorbed to theorganic matter in the environment. Since there havebeen reported that paraquat is extremely biologically
active and toxic to plants and animals and very
ecotoxic to the aquatic environment [4], theremediation of paraquat from contaminatedenvironment is needed.
Bioremediation is a pollutant elimination
technique using activities of living organisms such as
microorganisms or plants. This technique has been

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SEE - Kyoto, Japan, Nov.18-20, 2020

have been cleaned up by plants are DDT [13] andsimazine [14]. Yoshitomi and Shann [15] reported
that the increase in pyrene mineralization was
obtained from the addition of corn root exudates.
Several researches considered the rhizosphere as atreatment zone for contaminant degradation plants[16-18]. This research was therefore interested to
combine the biological treatment method for paraquatremoval. After the research completed, the effective
method for treating paraquat in soil will be found andcan be a guideline for the treatment of contaminatedpollutants in the environment, especially thetreatment of soil contamination with pesticides by
biological methods. Moreover, the research teamaims to make treatment process for degradation ofenvironmental pollutants quickly and effectively.

Bioremediation of Paraquat in Soil
Bioremediation of paraquat in soil with naturalattenuation (NA), bioaugmentation (BA), combined
bioaugmentation and biostimulation (BAS) were
investigated in soil microcosms. Fifty grams of soil
were placed in 240 mL glass bottles and mixed withparaquat at initial concentration of 80 mg/kg soil. The
moisture content of the soil was adjusting to about
20% by sterile distilled water. In the BA and BAS
treatment, the isolated bacterial consortium wasadded to the soil at the concentration of 100 g/kg soil.
In the BAS treatment, glucose and KH 2 PO 4 , asbiostimulant, were added to the soil in ratio 100:10:1(C:N:P). The components in the glass bottle weremixed and the bottles were covered by the priorincubation at room temperature without light. The
moisture content of the soil was examined every 3days by comparing the bottle weight at day 0 andadjusted to 20% when the moisture content was lower
than 10% by the addition of sterile distilled water.
Soil samples were sacrificed at day 0, 3, 7, 14, 21, 28,
35, and 60 to extract the remaining paraquat in the soil
using solid-liquid extraction method and analyze theconcentration of paraquat by UV Spectrophotometer.
Phytoremediation of paraquat in soil was further
investigated using five plants i.e., sunflowers(Helianthus annuus), marigold (Tagetes erecta L.),
pinto peanut (Arachis pintoi Krapov. & W.C. Greg.),
jack bean (Canavalia ensifomis (L.) DC.) and african
sesbania (Sesbania rostrata Brem and Oberm.).
These plants are rapid growth, easy to grow, and easy
to maintain with a short life cycle. Besides, thecombined bioaugmentation and phytoremediation
treatments (BAP) was also investigated for theparaquat removal from soil. The seeds of 5 plant types
were soaked in distilled water for 3 hours and thencultivate in soil in a seeding tray. It was nursed atroom temperature for 10 days under natural light anddaily watering to maintain constant soil moisture. The
BAP experiment was assigned to 12 treatments and 3
replicates by Completely Randomized Design (CRD).
In the phytoremediation treatment (PR), two kg ofsoil mixed with 80 mg/kg of paraquat was added into
8-inch diameter pot before planting with each of plantsaplings. For the BAP treatments, the bacterial
consortium was added to the soil at the concentrationof 100 g/kg soil before planting. The pots were dailywatering to control soil moisture at about 60% [21].
Then the samples were sacrificed on day 0, 5, 10, 15,
25, 35, and 45 to extract the remaining paraquat in thesoil using solid-liquid extraction method and analyze
the concentration of paraquat by UV spectrophotometer.
Natural attenuation of autoclaved soil mixed with 80
mg/kg of paraquat was conducted as control.

MATERIALS AND METHODS
Soil Sampling
Soil samples were collected from the field with ahistory of paraquat application. The soil sample wascollected at the depth of 0-15 cm from the surface
level and sifted through a sieve of 2 mm to remove
wood, stone, and grass. It was dried at room
temperature until the moisture content was less than
10% and kept at 4oC until the usage to maintain theactivity of microorganisms. The characteristics andcompositions of the soil i.e., soil texture, organic
matter content, and soil pH were analyzed. In thecontrol treatment, the soil sample was sterilized by
autoclave at 121oC 15 lb/in2 for 15 minutes. The
autoclave procedure was repeated three times with a
24-hour incubation period at room temperature in
between [19].
Isolation of Paraquat Degrading Bacterial
Consortium Microbial Community Analysis
Bacterial consortiums were isolated fromrhizosphere soil which collected from the field with ahistory of using paraquat. The enrichment technique
was applied to increase amount of bacterial
consortiums. Ten-gram of rhizosphere soil was
infused in mineral salt medium [20] supplemented
with paraquat as nitrogen source. The sample wascultured in 250 mL Erlenmeyer flask at 30oC and 150rpm. Sub-culturing was conducted every 7 days toobtain the bacterial consortium capable of paraquat
degradation. The paraquat degradation efficiency was
examined at the end of incubation for each subculture (7 days). The sub-culture was repeated until
the paraquat degradation efficiency was higher than
50%. The obtained bacterial consortiums were thenused in further experiments. The microbialcommunity in the bacterial consortium was examined
by Polymerase Chain Reaction Denaturing GradientGel Electrophoresis (PCR-DGGE) technique.

Extraction and Analysis of Paraquat

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SEE - Kyoto, Japan, Nov.18-20, 2020

The extraction of paraquat from soil samples was
conducted with the modified method from Wong et al.
[22]. Fifty-gram dry weight of soil and 100 mL
methanol were put into 300 mL cover glass bottle forextraction at 150 rpm on the horizontal shaker for 4
hours. The extraction procedure was repeated 3 times.
The extracted solution was collected, pooled together,and filtered through Whatman No. 42 filter paper.
The extracted solution was subjected to methanol
evaporation in a hot air oven at 80oC for 24 h. The
dried extract was dissolved with 1.0 mL deionizedwater and mixed with 3 mL of DI water and 1 mL of
1% Na 2 S 2 O 4 in 0.1 M NaOH solution. The
supernatant was then analyzed for the concentrationof paraquat using UV Spectrophotometer UV-1800
SHIMADZU (Japan) at the absorbance of 600 nm[23]. Paraquat concentration was calculated tocompare with standard curve of paraquat
concentration. The efficiency of paraquat extraction
method was not less than 90%.

lipoferum (93%), Altererythrobacter xinjiangensis(94%) Xanthobacter autotrophicus (92%) andAzospirillum amazonense (99%). In accordance with
report of the researchers are found thatmicroorganism i.e. Sphingomicrobium sp. [24], F.
xuzhouensis [25], A. lipoferum [26], X. autotrophicus[27] capable of degrading recalcitrant natural,
anthropogenic compounds, and different herbicides
and pesticides.
Effect of Bioaugmentation
Degradation in Soil

The data were statistically analyzed by thevariance analysis (ANOVA) with Duncan’s New
Multiple Range Test (DMRT). The SPSS 10.0
program was used for statistical analysis. P<0.05 wasmeasured as statistically significant.
RESULTS AND DISCUSSION
Soil Properties
The physical properties of soil samples were
determined and tabulated in Table 1. The result
indicated that soil texture is loamy sand and color ofsoil is brown. The soil pH is 8.1 and the low organic
matter content of 0.82% was observed in the soil.
Table 1 Properties of soil using in experiments.
Values0.82
Loamy sand
80.91
12.91
6.19
8.10

Isolation and Identification
Degrading Bacterial Consortiumof

Paraquat

This research studied the addition of bacterial
consortium on the efficiency of degradation of
paraquat in soil. Fig. 1 shows the breakthrough curveof C/C 0 versus time and Table 2 shows the paraquatremoval efficiency with various bioremediation
techniques. Paraquat removal in the control (withautoclaved soil) was only 9%, while in the NA
treatment was 44%. Results indicated that theindigenous microorganism has capability to degrade
paraquat which can be the result of microbial
adaptation to paraquat application in the field. BA
treatment and BAS treatment resulted in a rapid
decrease of the concentration of paraquat in soil. BAS
was the most efficient treatment giving 84% of
paraquat removal at day 60 of the experimentfollowed by BA treatment (paraquat removal 76%)
and NA treatment (paraquat removal 44%),
respectively (Table 2). The half-life of the paraquat intreatments BA and BAS were shorter than 20 days.
This study indicated that the addition of bacterial
consortium resulted in better efficiency of paraquat
degradation. In addition, the efficiency of paraquat
degradation increases with the addition of nutrients
together with the addition of bacteria. These results
agreed with the study of Dams et al. [28] who foundthatthebioaugmentationof
Sphingomonas
chlorophenolica ATCC 39723 into pentachlorophenol(PCP) contaminated soil accelerated the complete
decomposition of contaminants. Elväng et al. [29]reported that complete degradation of 4-chlorophenol(4CP)
contaminatedsoils
occurred
when
Arthrobacter chlorophenolicus A6 was added. In
addition, the maximum chlorobenzene removal fromsoil of 80% could be achieved with the addition of
Burkholderia sp. strain PS14 [30].

Statistical Analysis

Soil physicochemical properties
Organic matter content (%)
Soil texture
sand (%)
silt (%)
clay (%)
pHon

Paraquat

Effect of Bioaugmentation and Phytoremediation
on Degradation of Paraquat in Contaminated Soil

The community structure of a bacterial consortium
capable of degrading paraquat was analyzed by PCRDGGE. The isolated consortium was exhibited agreater than 92% identity to the sequences depositedin the databases which were closet matched to 6
genera i.e., Sphingomicrobium marinum (97%),
Ferrovibrio xuzhouensis (93%), Azospirillum

The efficiencies of paraquat removal from soil with
PR and BAP treatments were investigated in his
study. Percentage of paraquat removal was only 46%
in the control treatment (soil without planting andwithout isolated consortium) while 51.43% of
paraquat removal was observed in the treatment withthe addition of isolated consortium.
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SEE - Kyoto, Japan, Nov.18-20, 2020

BAP treatments gave higher paraquat degradation
efficiency with the removal percentages of greaterthan 75% as compared to the PR treatments (removal
percentages in the range of 64-89%). The BAP
treatment with african sesbania showed the highest
paraquat removal of 97.14%, followed by BAP
treatment with jack bean (96.43%) and BAP
treatment with pinto peanut (95.71%). The higher
percentages obtained from BAP treatment withafrican sesbania, jack bean, and pinto peanut ascompared to BA treatments indicated theimprovement of paraquat degradation in soil by thesethree plants. Root exudate substances from theseplants might support the growth and paraquat
degradation activity of the augmented consortium aswell as the indigenous microorganisms hence
enhancing the paraquat degradation efficiency [31].
The root exudate, such as amino acids, sugars, andphenols can induce microorganisms to produce nonspecific enzymes that can degrade contaminants intoless toxic compounds [12]. These affected root
surface properties or rhizosphere soil properties andincreased
contaminantavailability
throughadsorption, and improved physical structure of thesoil allowing more rapid and deeper penetration ofwater, nutrients, and microbes [12, 32].

1.2
1.0

C/C0

.8
.6
.4
.2
0.0
0

10

20

30

40

Time (days)

50

60

70

Fig. 1 The breakthrough curve for varying bioremediation
method at NA: natural attenuation (), BA: bioaugmentation(), BAS: combined bioaugmentation and biostimulation(), control: autoclaved soil without any treatment () andinitial paraquat concentration of 80 mg/kg.
Among the plants used for bioremediation treatments,
african sesbania, jack bean, and pinto peanut
possessed the high efficiency of paraquat remediationfrom with the removal percentages (in PR treatments)of greater than 64%.

Table 2 Effect of biological treatment process on the efficiency of paraquat degradation in contaminated soil.
kt 1/2
paraquat removal
r2(day-1) (days)
at day 60 (%)*
Natural attenuation (NA)
0.011
63.0 0.89
44.12±5.09c
Bioaugmentation (BA)
0.042
16.5 0.86
76.47±1.27b
Combined bioaugmentation and biostimulation (BAS)
0.067
10.3 0.86
83.82±1.27aControl
0.001
495
0.80
8.82±2.21d*Different letters indicate significantly different results obtained by Duncan test (p < 0.05). k is the degradation
rate constant, t 1/2 is half-life of paraquat.
Treatment

Table 3 The effect of Combined bioaugmentation and phytoremediation by various plants on the degradation of
paraquat in contaminated soil at day 45 of experiment.
Treatmentk(day-1)0.01530.0172Control (soil without plant and microbial consortium)
Soil with microbial consortium
Phytoremediation (PR)
Sunflower
0.0284
Marigold
0.0219pinto peanut
0.0366
Jack bean
0.0401African sesbania
0.0405
Combined bioaugmentation and phytoremediation (BAP)
Sunflower with microbial consortium
0.0376
Marigold with microbial consortium
0.0296
pinto peanut with microbial consortium
0.0476
Jack bean with microbial consortium
0.0480African sesbania with microbial consortium
0.0465207

t 1/2(days)
45.29
40.29

0.99
0.98

paraquat removal
at day 45 (%)*
46.43±2.47a
51.43±1.24b

24.40
31.64
18.93
17.28
17.11

0.98
0.99
0.97
0.96
0.96

72.14±3.71d
64.29±1.24c
82.86±2.14e
88.57±1.24f
89.29±2.14f

18.43
23.41
14.56
14.44
14.90

0.94
0.99
0.95
0.94
0.95

83.57±1.24e
75.00±3.27d
95.71±2.14g
96.43±2.47g
97.14±1.24g

r2

SEE - Kyoto, Japan, Nov.18-20, 2020

*Different letters indicate significantly different results obtained by Duncan test (p < 0.05). k is the degradation
rate constant, t1/2 is half-life of paraquat.
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CONCLUSIONSThe efficiency of degradation of paraquat in soil
by bioremediation technique found that BAS
treatment was high efficiency in paraquat degradation(84%) in 60 days. The half-life for paraquat in soil
from treatment BA and BAS were less than 20 days.
The bioremediation efficiency of paraquat incontaminated soil showed that BAP could degrade
paraquat up to 75%. BAP treatments with african
sesbania, showed the highest paraquat degradation
efficiency which was 97.14%, followed by using jackbean and pinto peanut which were 96.43 and 95.71,
respectively. All the experimental groups including
using phytoremediation with isolated bacteria
consortium and the control group were significantly
different (p<0.05). Using isolated bacteria
consortium with phytoremediation showed higher
paraquat degradation efficiency than that ofphytoremediation as seen in the paraquat degradation
percentage.
ACKNOWLEDGMENTS
The authors gratefully acknowledge the financial
support provided by Kalasin University. The authors
are grateful to the Research Group for Developmentof Microbial Hydrogen Production Process from
Biomass, Khon Kaen University, and Department of
Biotechnology, Kalasin University for providing thenecessary laboratory facilities.
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2096th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

CHARACTERISTIC OF LIQUID SMOKE PRODUCED FROMSLOW PYROLYSIS OF CACAO POD SHELLS (THEOBROMACACAO L)
Hera Desvita1, Muhammad. Faisal2, Mahidin2, and Suhendrayatna2Doctoral Program, School of Engineering, Universitas Syiah Kuala, Indonesia
2
Department of Chemical Engineering, Universitas Syiah Kuala, Indonesia

1

ABSTRACTThis study evaluated the characteristics of liquid smoke produced from cacao pod shells (Theobroma
cacao L) through the slow pyrolysis process at various temperatures of 300, 340, 380 and 400 °C. Prior tochemical analyses, the liquid smoke was purified by distillation at 190 °C to remove tar and remaining
carbon and some benzene compounds. The compounds contained in liquid smoke were then analysed using
various analytical techniques. The results showed that temperature plays a significant role in the compositionof liquid smoke. Results of Gas Chromatography Mass Spectrometry (GC-MS) analysis showed that the
number of chemical compounds produced at pyrolysis temperatures of 300, 340, 380 and 400 °C were 9, 14,
10 and 18 compounds, respectively. Pyrolysis temperatures did not have significant effects on the pH (3-4)
value of produced liquid smoke. Phenolic compounds, furan and ketone have been found to be the main
components in liquid smoke. The highest amount of phenol (763.76 mg GAE) was found at 400°C.
Keywords: Cacao pod shells, Liquid smoke, Pyrolysis, Phenol
Previous research stated that the degradation of
biomass compounds, such as lignin, cellulose andhemicellulose, occurs at a temperature of 300400°C, 260-350°C and 180-300°C, respectively[14]. Each temperature plays an important role indetermining the liquid smoke content. Pyrolysis at
a high temperature (above 400o C) will form toxic
carcinogenic compounds such as PAH [15].
Hemicellulose degradation forms a number ofcarbonyl and acetic acid compounds as well as
producing colours, while lignin degradation
produces phenolic compounds that act as bacterial
and flavouring agents [16,17]. There are several
available studies about the content of liquid smoke
produced by various types of biomass, such as oilpalm fruit bunches [11], oil palm shells [4-8] anddurian shells [9,10]. However, there is little
literature about the characterization of liquidsmoke from cacao pod shells. The objective of thisresearch was to identify the components of liquidsmoke produced from cacao pod shells at various
pyrolysis temperatures.

INTRODUCTION
Indonesia is a country with abundant natural
resources across its provinces. Its tropical weather
is ideal for growing cacao trees, especially in Aceh
Province, where cacao is a main plantation
product. Data from the Ministry of Agriculture
showed that Aceh produced 42,180 tons of cacao
in 2019 [1], and this large amount naturally leads
to waste and environmental issues. Cacao beans
are usually dried before being processed into foodproducts such as chocolate powder, while theshells are discarded without any prior processing.
The cacao shell biomass contains lignin (51.98%),
cellulose (20.15%), hemicellulose (21.06%) andpectin (6%) [2],[3]. This high content of lignin,cellulose and hemicelluloses has the potential to be
used as raw materials to produce liquid smoke.
In the past few years, liquid smoke has beendeveloped from various biomass waste, such as oilpalm shells [4]-[8], durian peel waste [9],[10], oilpalm empty fruit bunches [11] and sawdust [12].
The resulting liquid smoke is used as apreservative in wood and food products. In
general, hard-textured wood containing 50%
cellulose, 25% hemicelluloses and 25% lignin [13]is used as liquid smoke material through a process
called pyrolysis. Pyrolysis of wood or otherbiomass produces charcoal, tar and liquid smoke.
The latter is essentially the smoke resulting fromthe decomposition of various compounds within
the biomass, which is then condensated into liquid,
hence the term liquid smoke.

METHODOLOGY
Three kilograms of cacao shells were fed into astainless-steel pyrolysis reactor (60cm height,
40cm diameter and 5kg capacity) and processed at
300oC, 340oC, 380oC, and 400oC. The complete
pyrolysis method has been identified in previous
research [11]. The temperature and volume
changes during pyrolysis were observed every fiveminutes. The crude liquid smoke was then distilled
at 190oC to purify it from tar. A GC-MS (Gas210

SEE - Kyoto, Japan, Nov.18-20, 2020degrade; and (v) zone V at <500o C, where lignin isdegraded.

Chromatography-Mass Spectrometry) was used toanalyse the compounds, while a spectrophotometer(Agilent Cary 60 UV-VIS) was used to analyse thephenol concentration.

Liquid Smoke Production

RESULTS AND DISCUSSION
Volume of liquid smoke (ml)180

Pyrolysis Evaluation

Inside reactor temperature (o C)

450
400
350
300
250
200
150
100
50

Set pyrolysis
temperature (oC)

160
140
120
100
80

Pyrolysis temperature (o C)
300
340
380
400

60
40
20
0

300
340
380
400

0 10 20 30 40 50 60 70 80 90 100
Pyrolysis time (min)Fig 2. The correlation between pyrolysis time andliquid smoke volume resulted at various pyrolysis
temperatures.

0
0 10 20 30 40 50 60 70 80 90 100110120
Pyrolysis time (min)Figure 2 shows that maximum liquid smoke
volume (162ml) was produced at 400oC in 20
minutes. The resulting volume decreases during
pyrolysis until it stops at 110 minutes (0ml)
because all the cellulose, hemicellulose and lignin
have decomposed completely. It also shows thatthe pyrolysis temperature influences the liquidsmoke volume produced. The volumes resulting
from 300oC, 340oC, 380oC to 400oC were quite
similar at 801ml, 799ml, 795ml and 797ml,
respectively. These numbers reflect those resulting
from the work of Cao et al. [20], which used slow
pyrolysis at 350oC and 400oC using corn cobs. In
addition, Rahmat et al. [18] stated that the
maximum liquid smoke volume resulting fromsawdust at 450oC in 10 minutes was 139ml,
stopping at 90 minutes.
The pyrolysis duration of 20-30 minutes resultsin the maximum amount of liquid smoke volume
before it starts decreasing, likely due to thedecomposition of compounds contained within thecocoa shell. The degradation of organic
compounds in the raw material is caused by theincrease in the pyrolysis temperature [21]. The
increase of temperature degraded cellulose,
hemicellulose and lignin, which were thencondensated into liquid smoke. According to
Triastuti et al. [22], the liquid smoke volume
results depend on the cooling system used, such as
water, which accommodates the heat transfer. Hightemperature pyrolysis can cause a decrease in the
resulting volume of liquid smoke because it leads
to increased water temperature, causing the smoke
to fail to condensate in completion.

Fig 1. Correlation between pyrolysis time and thechanges of inside temperature at various set
pyrolysis temperatures.
The time required to reach the constantpyrolysis temperature was different for each set oftemperatures, as can be seen in Figure 1, whichshows that the pyrolysis temperature increases
gradually. This results in the degradation ofcompounds within the cacao pod shells, such as
hemicelluloses, cellulose and lignin. In our
research, the temperature increased significantly to
277oC within 10 minutes and continued to slowly
rise until it reached the designated constant value.
Our results are similar to those of Rahmat et al.
[18], in which the temperature increased to 350oC
in 10 minutes. The constant pyrolysis temperaturesof 300oC, 340oC, and 380oC (same length of time)and 400oC were achieved in 15, 20 and 35
minutes, respectively. In comparison, sawdust
pyrolysis achieves the constant temperature of
450oC in 25 minutes [18]; meanwhile, at >100oC,
the water content evaporates in 10 minutes, leading
to an increase in liquid smoke volume. According
to Ravendran et al. [19], raw material compound
degradation was divided into five zones, namely (i)zone I at >100o C, where water content changes;(ii) zone II at 200-250°C, where compounds start
to degrade; (iii) zone III at 250-350°C, where
hemicellulose starts to decompose; (iv) zone IV at
350-500°C, where lignin and cellulose starts to211

SEE - Kyoto, Japan, Nov.18-20, 2020

The times required for pyrolysis at 300oC,
340oC, 380oC and 400oC were 100, 75, 75 and 85
minutes, respectively. The reason these durations
were similar was likely due to the small
differences in temperatures. A longer pyrolysis
process results in less liquid smoke volume.
According to Yokoyoma et al. [23], cellulose
decomposes at 240-340oC, hemicellulose at 200260oC and lignin at 280-500oC.
Total Amount of Phenol
Phenol plays an important role in providing
aroma and flavour as well as an antimicrobial
agent. Phenol results from the thermal degradationof lignin and cellulose by aliphatic compounds[24]. Table 1 shows the spectrophotometer
analysis of phenol produced from different
pyrolysis temperatures.

No

Component

1.

2-furanmethanol ,2-furanmethanol ,3-furanmethanol
Butyrolactone , Butanoic acid, 4hydroxy, Butanoic acid, 4hydroxy
Heptane, 4-methyl- 2-Nonene, 3methyl-, ®- 1-Butanol, 3-methyl-,carbonate
Phenol2-Cyclopenten-1-one, 2,3dimethyl- 2-Cyclopenten-1-one,
2,3-dimethyl- Cyclooctene
Phenol, 2-methyl-p-Cresol,
Phenol, 3-methylPhenol, 3-methyl, Phenol, 3methyl p-Cresol
Phenol, 2-methoxy-Phenol, 2methoxy-Phenol, 2-methoxy
Methenamine

2.

3.

4.
5.

6.
7.

Table 1. The content of Phenol
8.
No.

Concentration(mg GAE)

1

Pyrolysis
temperature
(oC)
300

2

340

192.513

380

363.684

400

763.76

9.

Area
(%)
4.73
16.54

2.39

45.49
3.59

4.87
9.31
8.52
4.55

Table 3. GC-MS test on liquid smoke resulted
from pyrolysis at 340 oC.

242.96

Table 1 shows that the highest phenol
concentration occurs at 763.76mg GAE (Gallic
Acid Equivalent) at 400oC pyrolysis temperature.
A temperature of 340oC results in a lower phenol
concentration than that at 300oC, while atemperature of 380oC sees an increase in phenol
concentration. This was likely due to lignin
decomposition at 300-450oC. A temperature of
400oC (near the maximum temperature for lignin
degradation) results in even higher phenol
concentration. The research showed that liquidsmoke resulting from the pyrolysis of oil palm
fruit bunches at 420oC contains 1.71% phenol [11].
The amount and quality of the resulting phenol
depends on the amount of lignin content in the raw
material as well as on the pyrolysis temperature
[25].

No

Component

1.

2-furanmethanol ,2- furanmethanol,3-furanmethanol
Butyrolactone , Butanoic acid, 4hydroxy, Butanoic acid, 4hydroxy
Phenol2-Cyclopenten-1-one, 2,3dimethyl- 2-Cyclopenten-1-one,
2,3-dimethyl- Cyclooctene
Phenol, 2-methyl-p-Cresol,
Phenol, 3-methylPhenol, 3-methyl, Phenol, 3methyl p-Cresol
Phenol, 2-methoxy-Phenol, 2methoxy-Phenol, 2-methoxy
Methenamine
2-Aminopyridine, Pyrazine,
methyl- Cyclopropane, (3chloropropyl)methylene
2-Cyclopenten-1-one, 2-methyl1-Pentyne, 2-Cyclopenten-1-one,
2-methyl1-Butanol, 3-methyl-, carbonate,
Propanoic acid, 2-methyl-, 3methylbutyl ester, Diisoamyl
ether

2.

3.
4.

5.
6.
8.
9.
10.

11.
GC-MS Analysis
12.

Temperature plays an important role in theliquid smoke composition, and GC-MS analysis
was carried out to determine its composition at
different temperatures. The GC-MS test results canbe found in Table 2-Table 5.

Table 2. GC-MS test on liquid smoke resulted
from pyrolysis at 300 oC.
212

Area
(%)
17.03
5.47

29.78
4.80

4.10
8.02
14.06
3.03
1.56

4.25

1.27

SEE - Kyoto, Japan, Nov.18-20, 2020

No

Component

13.

Phenol, 4-ethyl-Phenol, 3-ethylPhenol, 4-ethyl1-Propanol, 2-amino- 1Octadecanamine, N-methyl-2Amino-1-propanol

14.

Area
(%)
2.81

No

Component

8.

2-Cyclopenten-1-one, 2-methyl1-Pentyne, 2-Cyclopenten-1-one,
2-methyl2-Cyclopenten-1-one, 3,4Pentadienal Cyclobutene
2-Propanone, 1-(acetyloxy)- 2Propanone, 1-(acetyloxy)- 2Methyl-3-oxobutyronitrile
Ethanone, 1-(2-furanyl)- 2Furancarboxylic acid, 2propenylester 2-Butynal
Cyclopentene,Bicyclo[2.1.0]pentane, 2-Cyclopenten-1-one, 2methylPyrazine, trimethyl-Pyrazine,
trimethyl-Pyrazine, trimethyl
Butanoyl chloride Furan-2carbonyl chloride, tetrahydroButanoyl chloride
2-Cyclopenten-1-one, 2,3dimethyl-Cyclohexene, 1,2dimethyl, 2-Cyclopenten-1-one,
2,3-dimethyl
Terpinen-4-ol, Terpinen-4-ol,
Terpinen-4-ol
Creosol
1,3-Benzodioxole, 4-methoxy-6(2-p ropenyl) 1,3-Benzodioxole,
4-methoxy-6-(2-p ropenyl) 1,3Benzodioxole, 4-methoxy-6-(2propenyl)

1.44
9.
10.

Table 4. GC-MS test on liquid smoke resulted
from pyrolysis at 380 oC
11.
No

Component

1.

2-furanmethanol , 2furanmethanol ,3-furanmethanol
Butyrolactone , Butanoic acid, 4hydroxy, Butanoic acid, 4hydroxy
Phenol2-Cyclopenten-1-one, 2,3dimethyl- 2-Cyclopenten-1-one,
2,3-dimethyl- Cyclooctene
Phenol, 2-methyl-p-Cresol,
Phenol, 3-methylPhenol, 3-methyl, Phenol, 3methyl p-Cresol
Phenol, 2-methoxy-Phenol, 2methoxy-Phenol, 2-methoxy
Methenamine
Phenol, 4-ethyl-Phenol, 3-ethylPhenol, 4-ethyl2(1H)-Pyridinone 4Methylcoumarine-6-(2furylcarbon yl)oxy 2Furancarboxylic acid, anhydridePhenol, 2-methyl-p-cresol-pcresol

2.

3.
4.

5.
6.
7.
8.
9.
10.

11.

Area
(%)
13.42

12.

7.48
13.
14.

33.60
5.67

15.
7.15
9.24
16.
13.08
17.
18.

3.52
2.93
3.73

Component

1.

2-furanmethanol , 2furanmethanol ,3-furanmethanol
Butyrolactone , Butanoic acid, 4hydroxy, Butanoic acid, 4hydroxy
PhenolPhenol, 2-methyl-p-Cresol,
Phenol, 3-methylPhenol, 3-methyl, Phenol, 3methyl p-Cresol
Phenol, 2-methoxy-Phenol, 2methoxy-Phenol, 2-methoxy
Methenamine

2.

3.
4.
5.
6.
7.

5.23
2.71

2.08

1.58

0.58
1.50

1.64

1.05
1.38
1.01

Table 2-Table 5 shows that phenol was themost common component resulting from cacao
shell pyrolysis at 300oC, 340oC, 380oC and 400oC
at 45.49%, 29.78%, 33.60% and 49.87%,
respectively. This result was slightly different fromprevious research [5],[9] on oil palm shell anddurian shell pyrolysis, in which acetic acid was themost component produced. However, our result
was in line with the research by Budagara et al.
[25], where phenol was the most component foundin coconut fibre pyrolysis. The liquid smoke
produced from rice husks contains 85% phenol andits derivatives [26]. The GC-MS analysis on
pyrolysis at 300oC, 340oC, 380oC and 400oC
identified 9, 14, 11 and 18 compounds each. The
compounds were phenol and its derivatives,
ketone, furan and ester.
The largest amount of component in cacao shellliquid smoke was phenol and its derivatives suchas phenol, 2-methyl-p-cresol, phenol, 3-methyl-; 1propanol, 2-amino-1-octadecanamine, n-methyl-2amino-1-propanol; and phenol, 4-ethyl-phenol, 4ethyl. There are also a few other compounds suchas hydrocarbon (2-cyclopenten, cyclopenten),
furan (2-furanmethanol, 2-furanmethanol, 3-

7.15

Table 5. GC-MS test on liquid smoke resulted
from pyrolysis at 400 oC
No

Area
(%)
2.23

Area
(%)
4.52
5.98

49.87
4.99
5.81
6.56
1.29

213

SEE - Kyoto, Japan, Nov.18-20, 2020

furanmethanol) and ketone (2-cyclopenten-1-one,
2,3-dimethyl-2-cyclopenten-1-one, 2,3-dimethylcyclooctene; 2-cyclopenten-1-one, 2-methyl-1pentyne, 2-cyclopenten-1-one, 2-methyl- and 2cyclopenten-1-one, 2,3-dimethyl-cyclohexene, 1,2dimethyl, 2-cyclopenten-1-one, 2,3-dimethyl).
However, at the pyrolysis temperature of 400oC,
benzene compounds (1,3-benzodioxole, 4methoxy-6- (2-propenyl) 1,3-benzodioxole, 4methoxy-6- (2-propenyl) 1,3-benzodioxole, 4methoxy-6- (2-propenyl)) were also produced,
which are carcinogenic in nature and therefore
cannot be used to preserve food products. The
degradation of cellulose, hemicellulose and lignin
compounds at various temperatures produces
various components within the resulting liquidsmoke. Research from Faisal et al. [9] showed thatthe pyrolysis of durian shells at 300oC, 340oC and
380oC results in 18, 14 and 21 compounds,
respectively, such as phenol, carboxylic acid, furan
and lactone. These characteristics were found from
GC-MS testing on liquid smoke that resulted fromvarious raw materials such as oil palm fruitbunches [11], oil palm shells [6], durian shells [10]and rice hulls [26].

CONCLUSION
Cacao shell liquid smoke produced at 400oC
pyrolysis contains a high concentrate of phenol(763.76mg GAE). For all pyrolysis temperatures,
the GC-MS analysis showed that phenol is themain component in this liquid smoke. At
temperatures below 400oC, the liquid smoke did
not contain benzene, while at temperatures above
400oC, it did contain carcinogenic benzene. Higher
pyrolysis temperatures result in less liquid smoke
volume. Maximum volume was achieved in lessthan 30 minutes. The pH value was 3 (acidic),
indicating that the liquid smoke has good quality.
ACKNOWLEDGEMENTS
The authors would like to appreciate Universitas
Syiah Kuala for supporting this study.
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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

A NUMERICAL SIMULATION OF DISASTER WASTE DISPOSAL
IN WAKAYAMA CITY BY USING DHT MODEL
Soichiro ASAI1, Tatsuya AKIYAMA2, Hiroto TANOUCHI3, and Nobuyuki EGUSA4
1

Graduate School of Systems Engineering, Wakayama University, Japan; 2,3,4 Faculty of
Systems Engineering, Wakayama University, Japan
ABSTRACT

We conducted a numerical simulation of disaster waste disposal by using a Dynamic Hauling/Transportation
model (DHT model) in order to extract the factors to hinder the execution of a disposal management plan of
Wakayama city government. The DHT model was developed for estimating number of days required for disaster
waste disposal, following parameters are mandisopdatory as the model inputs; (1) disaster waste characteristics(distributions, volume and contents) in damaged area, (2) hauling/transportation route, (3) number/capacities oftransportation vehicles, (4) maximum capacities at temporary storage / final disposal sites and (5) abilities ofcrushing/classification equipment. Almost all parameters were set by referring to a planning document of disaster
waste disposal provided by Wakayama city and disposal guidelines published by Ministry of the Environment ofJapan. Several parameters without description in these document/guideline, e.g. maximum capacities at temporarystorage and distance of hauling/transportation route were estimated by using GIS. Severe shock and tsunami caused
by Nankai Trough huge earthquake were adopted as external forces generating disaster waste. By assumption thatparameters included in (3) and (5) could be critical parameters for a result of simulation, we performed sensitivity
analysis of each parameter in them. As a result, abilities of several crushing / classification at temporary storages
were the most sensitive parameters of all evaluated parameters. Therefore, augments of crushing/classification
functions at temporary storage might be effective to shorten processing days for disaster waste disposal.
Keywords: Disaster waste disposal, Dynamic hauling/transportation model, Sensitivity analysis, Nankai Troughhuge earthquake, Wakayama city

INTRODUCTION

disaster, e.g. strong earthquake without Tsunami. On
the other hand, few researchers have addressed todevelop numerical simulation models for disaster
waste disposal management. Kayo et. al. 2011
proposed a simplified model to estimate
financial/temporal cost for disaster waste disposal in
Miyagi prefecture[4]. Sakaguchi et. al. 2018
developed a DHT model, which is a prototype of thenumerical system to model all transport/haulingprocesses in the disposal plan. They also applied it foran actual city[5].
There remains a need for a lot of application of thenumerical simulation such as the DHT model toevaluate actual disaster waste disposal planspublished by a lot of governments. The amount andquality of disaster waste have great varieties
depending on a target city, various patterns oftransport/hauling processes also exist. Therefore, amodel specialized and optimized for each target city
is demanded in order to increase the number ofapplications. In this study, we have applied the DHT
model targeting on Wakayama city as a new casestudy. In addition, we discussed to formulate a more
appropriate planning than one proposed in this study
through an evaluation about bottlenecks of disposal
planning of Wakayama city.

An appropriate planning of disaster waste
disposal is a great issue in a disaster recovery phase.
Although it is therefore necessary to makeappropriate assumptions about disasters and develop
an ideal disposal management plan, it is generally
difficult to formulate it with flexibility based onregional characteristics. This is particularly
problematic other than large cities with vast
population because of a lack of specialists and little
financial leeway[1]. Wakayama city is also expecteda huge amount of disaster waste generation caused bya Nankai Trough huge earthquake, a numericalsystem to support a waste disposal planning iseffective in this regard.
Various investigations and studies have been
conducted in order to establish efficient disaster waste
treatment plans. Tanikawa et.al. [2] developed an
accurate prediction method of the amount of disaster
waste generation by considering material stocks ofbuildings and roads. Nasu et.al. [3] implied
governments of several cities had been adopted
inadequate assumption methods to estimate amountsof disaster waste generation. For instance, disaster
waste amount caused by Tsunami shown in somewaste disposal plans were calculated by using other216

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 1 Input parameters of DHT model. Parameter is classified 1) type of set up by referring to official
documents by governments, 2) type of set up by referring to environments of the Great East Japan Earthquake, 3)
type obtained by GIS processes, 4) assumed value in this study originally. Subscripts shows i;SID , j: type of disaster
waste(number of waste types were 6 in this study), k:toSID, l:link ID (number of links were 249 in this study), m: type oftrailers (only 1 in this study)kindStorages

Links

Transports
Classify

variable
SID
Voli
Sui,j ,
Sai,j
C_Ri,j,k

unit
ton
ton

frSIDl,toSIDlDistl

Description
Storage ID
Facility storage volume
Amount of disaster waste(untreated /treated)
Proportion of the volume transported tomultiple destination sites.
Import SID
Export SID
Route lengthvalue
1 to 72

type

Spdl

Average speed

Loadl
Unldl
TPNummLoading time,
Unloading time
Number of trailers

km
/hour
hour

TPAbilitym

Capacity of trailers

CLNumsNumber of crushing / classification machines-

2)

CLAbilitys

Ability of crushing / classification machines

ton/hour

2)

3)
3)

-

4)

-

3)

km

3)
30km/hour

4)-30 minutes
20 minutes
1245

1)
1)
4)

ton

10

1)

in the primaries and secondaries are transported todisposal sites or recycling facilities based on the typeof waste. (7) In these sites and facilities, disaster
waste is completely disposed or recycled (e.g.
landfill, recycling facility, incinerator). Concrete
procedures of calculation in the model is shown in
Sakaguchi et.al. 2018[5].

METHOD
Model Summary
The DHT model is a kind of process-based, masstransfer and state change model, optimized for
reproduction of disaster waste disposal. In actual
disposal management, waste spread in damaged area
generated by a catastrophic forcing are transported
and hauled to each disposal facilities and storages
step by step, aiming to disappear the waste from thearea. In the model, all processes of them can be
reproduced.
Figure 1 shows the general flow of disaster waste
disposal. Reproduced processes in the model arefollowings; (1)Disaster waste generated indamaged area is transported to refuse collection
places. In this phase, disaster waste is generally
unsorted and many types of material are mixtures init. (2) Then, this mixed disaster waste is transported
from the collection places to primary temporarystorages. (3) At the primary temporary storage, thedisaster waste is separated based on material types.
Here, crushing process is also installed generally inorder to facilitate transportation, recycling anddisposal. (4) Residual mixed waste generated byinsufficient separate capability at the primarystorages is transported to secondary temporarystorages. (5) These transported residual mixed waste
undergoes more advanced separation and crushingprocesses than the primary storages in the secondaries.
(6) Disaster waste sufficiently separated and crushed

Fig. 1

General disaster waste management flow.

Parameters
Table 1 shows mandatory parameters in the DHT
model. Although temporal flexibility of eachparameter was necessary in order to reflect processchanges accompany with disposal plan progression,
each parameter value was fixed as initial values
217

SEE - Kyoto, Japan, Nov.18-20, 2020

total area size of it is 209 km2. Especially industrial
areas extend along the coast in the city.
A targeting disaster in this study was Nankai
Trough huge earthquake, we took especially disaster
waste generated by strong earthquakes and Tsunami
into account. Wakayama city government inscribed in
the report[9] that a vast area facing the Pacific ocean
would be swallowed by the Tsunami, and most areas
would receive a severe earthquake with a seismic
intensity of 6 at least.

during the simulation in this study. Additional
function to adjust parameters even in a progression ofanalysis is necessary in future.
In this study, 1) the parameters were set basicallyby referring to official documents showing disaster
waste
planning
publishedby
Wakayama
prefecture[6], Wakayama city[7] and Ministry of theEnvironment, Japan[8]. 2) Several other parameters
without shown in these documents were set based on
environmental value obtained by the Great East Japan
Earthquake[9]. 3) In other parameters, especiallylocation and capacity of each storage were estimatedby GIS processes. 4) The other parameters impossible
to obtain related information were set as reasonablevalues in our assumption.

Transport and disposal network
Figure 2 also shows locations of collection places,
primary and secondary temporary storages, disposalsite and recycling facilities. Collection places wereset as schoolyards of elementary schools, disaster
waste generated in each district is firstly transported
here. Information related with final disposal sites for
combustible waste and incombustible waste were alsomentioned in official documents[6], [7]. locations andcapacities of disposal system of them were set byreferring them. On the other hand, no detailed
description related with recycling facilities were
however shown in them. We therefore establishedrecycling facilities for 4 materials (wood, concrete,
metals and tsunami sediments) uniquely.
The guidelines of the Ministry of theEnvironment[7] noted a policy to set temporarystorages. While referring to it, Candidates of primaryor secondary temporary storages were raised byextracting open spaces (e.g. parks, parking lots andgrounds) by GIS processes. Criterion to extract bothtypes of storages were 1) exceeding 10,000 m2 area
size, 2) not located in riverside land to avoid
secondary disaster caused by flooding, 3) notadjoined disaster base hospital. By these criterions,
we obtained 13 sites as candidates of temporarystorages. Then, the largest site of them were set as
secondary temporary storages because of small
distances between it and final disposal sites andrecycling facilities. Finally, all candidate sites except

Input and output
The input is spatial distributed disaster waste data,an arbitrary number of types and volume of disaster
waste can be set in the model. Although a geospatial
size of each input unit is also arbitrary, elementary
school districts are often appropriate for the units
because they have been adopted as the units for actual
disaster waste disposal in previous managements. The
output of the model is amount of each disaster waste
type stored in each facility at each time step andrequired date to complete disaster waste disposal.
PROPERTIES OF
MODEL SET-UP

TARGET

AREA

AND

Study area and target disasterFigure 2 shows the location and properties of atarget area of this study. The target area was
Wakayama city, Wakayama prefecture, Japan.
Wakayama city is located in coastal area facing the
Pacific Ocean, which has about 350 thousand of
population and about 150 thousand of households.
The city consists of 48 elementary school districts,

Fig. 2The location of all sites and the amount of disaster waste in each school district.
218

SEE - Kyoto, Japan, Nov.18-20, 2020chosen as secondary temporary storage were set as
the primary storages.
As a result, there were 53 collection places, 12
primary temporary storages, 1 secondary temporarystorage and 6 final sites (including final disposal sites
and recycling facilities). Figure 3 shows theconnection relationship of all sites. All collection
places were connected to three primary temporarystorages chosen in close order. Here, all distance
between the collection places and primary temporarystorages were calculated as them along roads. All
primary temporary storages were connected to thesecondary temporary storage. Secondary temporarystorage was also connected to all final disposal sites.
All connections were one-way from upstream todownstream. Transportation vehicles allocated linksof completed disaster waste exporting were reallocated for other links. A rule of the re-allocation isto priory for links of upstream, e.g. links fromcollection places.
Aiming at mitigation the burden on the damaged
areas, an exportation from damaged municipalities tooutside area is generally performed. In this study,
however this kind of outside processing was notmodeled because of facilitating interpretation of theresults. This obvious limitation in this study could
lead to results that the period required for waste
disposal is calculated unfairly longer than actual.

improve work efficiency, the value was also
empirically set as 1.
Table 2 The value of the 𝐴𝑆𝐺
No
1
2
3
4

Type of waste
Wood
Concrete
Metal
Tsunami Sediments

𝑨𝑺𝑮 (t/m3)
0.55
1.48
1.13
1.46

5

Combustible

0.4

6

Incombustible

1.1

Spatial-distributed input data creation
By allocating various types of waste generated
both tsunami and earthquake forcing to eachelementary school district, we created the spatial
distributed data set of disaster waste as model input.
Methods to estimate the amount of disaster waste wasobtained by the Wakayama Prefecture's disposal
management plan[6]. In this study, disaster waste wasclassified waste debris or tsunami sediment, both ofthem were calculated for each school district. The
following assumptions were applied to calculate theamount of disaster waste. 1) Debris was generated
only from buildings for housing, we ignored debris
origin from road or other structures. 2) All buildings
are wooden. 3) Despite of existence of various levelsof destruction, only completely destroyed buildings
are taken into the estimation. 4) Ages of buildings
required to estimate durability of them were obtainedby Japanese statistical survey 2018[10]. Eq. (2) showequations to calculate the amount of debris[5].
𝑄 =𝑠 × 𝑁 × 𝑞

Fig. 3

Where 𝑄 is total amount of debris in each waste
type(t), 𝑠 is average gross floor area of building (m2).
𝑁 is number of buildings destroyed. 𝑞 is debris
generation per unit area of floor. In [6], 𝑞 was
although describes as different values based on debris
types as respective (e.g. 0.194 (t/m2) in combustibles),
we used 𝑞 = 0.696 (t/m2) as total value of all debris
types in order to estimate 𝑄 as the sum of all types.
On the other hand, 𝑠 and 𝑁 were not shown in eachdisposal management plan, we replaced 𝑠 × 𝑁 with
𝑇𝐹𝐴 × 𝐶𝐷𝑅 as follows:

Network structure in Wakayama city.

Capacity of each storage[7]The capacity of each primary or secondary
temporary storages was set as follows:
𝐶𝑎𝑝 = 𝐴𝑟𝑒𝑎 × 𝐴𝑆𝐺 × 𝑆𝐻 / (1 + 𝑊𝑆𝑅)

(2)

(1)

Where, 𝐶𝑎𝑝 is weight based capacity of each storage(t), 𝐴𝑟𝑒𝑎 is area size (m2). 𝐴𝑆𝐺 is an apparent
specific gravity (t/m3), shown in table 2, respectively.
𝑆𝐻 is stacked height (m), the value was set on 5m as
an empirical value. 𝑊𝑆𝑅 is an indicator related to avacant space without stacking with disaster waste to

𝑄 = 𝑇𝐹𝐴 × 𝐶𝐷𝑅 × 𝑞(3)

Where, 𝑇𝐹𝐴 is total floor area of each school district,
219

SEE - Kyoto, Japan, Nov.18-20, 2020

RESULTS𝐶𝐷𝑅 is completely destroyed rate by tsunami or
earthquake forcing. In areas with duplicated attacks
both tsunami and earthquake forcing, 𝐶𝐷𝑅 come avalue as the sum of tsunami’s 𝐶𝐷𝑅 and earthquake
forcing’s 𝐶𝐷𝑅. If the total 𝐶𝐷𝑅 exceeded 100% by
this calculation, it was modified 100%. More detailed
theory and procedures to estimate disaster waste
amount by using 𝐶𝐷𝑅 were described in somedocuments published by governments (e.g. [11]).
Finally, total debris amount of each school district
was classified based on debris types. Some
documents related with past disaster waste
managements have indicated contents and volume ofdisaster waste, we adopted a ratio of constituent
substances in debris obtained by a waste managementof the Great East Japan Earthquake[5]. Table 3 shows
the ratio of constituent substances and the amount ofdisaster waste generated by type in the entire
Wakayama city. Total weight of 𝑄 exceeds 10
million ton, which is equivalent to total waste
generation for 70 years in Wakayama city under nondisaster condition[7].

Figure 4 represents the time series of the disaster
waste amounts in each phase estimated by an analysis
under the above condition. A period to disappear
disaster waste from all collection places was 22.7
years, which is the same as a period from disaster
forcing to export disaster waste from all primarytemporary storages. Finally, it was demanded 22.8
years to complete disposal process for all disaster
waste.

Fig.4 A time series of the disaster waste amounts ofcollection places, primary and secondary temporarystorage, processed in final disposal sites in total.

Table 3 Amount of the disaster waste
No

Type of waste
Wood
Concrete
Metal
Tsunami Sediments

Ratio
(%)
4.5
43.2
5.5
17.0

Amount(million ton)
5.627
54.182
6.877
21.33012
3
45Combustible

14.9

18.755

6

Incombustible

14.9

18.755

Total

100.0

125.526

Periods required under ideal conditions withoutbottlenecks in transportation or separation could be
simply estimated by dividing of each types of disaster
waste amount by ability of disposal site for each type,the longest of them was calculated as 8.4 years. This
period is much smaller than the period obtained by
the numerical simulation in this study.
Figure 5 shows utilization rate of primary andsecondary temporary storages, it was shown that
especially secondary temporary storages were mostly
vacant trough the disposal period. In addition,
primary temporary storages were also un-usedefficiently especially mid to late in disposal. These
results suggested that enhancement and optimization
for transportation and separation were critical issues
for efficient disaster waste disposal planning. On theother hand, it was also shown that fundamentallyenhancements of function final disposal sites werealso necessary for further shorten of date to complete
all disposal process.

The amount of tsunami sediment was calculated
as follows:
𝑆𝑑 = 𝐴𝑡𝑢𝑠 × 𝑑 × 𝑘(4)

Where 𝑆𝑑 weight of tsunami sediment in each school
district(t), 𝐴𝑡𝑢𝑠 is area size of inundation (m2), 𝑑 isaverage depth of inundation(m). 𝑘 is conversion
factor from inundation depth to deposition amount
per unit area by empirical rule[6]. Finally, Total
weight of 𝑆𝑑 exceeds 2 million ton.
An estimated amount of disaster waste (sum of 𝑄
and 𝑆𝑑 ) at each school district was also shown infigure 2. Larger proportion of disaster waste was
generated in the coastal area, the impact of thetsunami was strongly shown.

Fig.5 Utilization rate of primary and secondary
temporary storages in whole disposal period.
220

SEE - Kyoto, Japan, Nov.18-20, 2020

CONCLUSION

of Civil Engineers, Ser. G (Environmental
Research), 2019 Volume 75 Issue 6 Pages
II_261-II_271.
[4] Chihiro K., Koichi T., Tomonori I., Kazuto E.,
Masato Y., Development of Support Tool for
Seismic Disaster Waste Treatment Planning Waste Distribution Planning Model by Time andCost Optimization -, The 22nd Annual
Conference of Japan Society of Material Cycles
and Waste Management, 2011.
[5] Naoya S., Hiroto T., Nobuyuki E. and Yoshikazu
O., Development of a Disaster Waste Disposal
Planning Model Aiming at Supporting ofAppropriate Decision of Disaster Waste
Treatment, Journal of Japan Society of Civil
Engineers, Ser. G (Environmental Research),
Vol.74, Issue 5 ,2018, pp. I_195-I_202.
[6] Wakayama prefecture, Wakayama accident
treatment of waste plan, 2015, https://www.pref.wakayama.lg.jp/prefg/031800/saigaikeikaku/saigaikeikaku.html, Accessed 2020/6/23.
[7] Wakayama city, Disaster waste disposal
management plan for Wakayama city, 2017,
http://www.city.wakayama.wakayama.jp/kurashi/gomi_kankyo/1001113/1001251/1018288/101
8258.html, Accessed 2020/6/23.
[8] Ministry of the Environment, Guideline fordisaster waste management, pp. Teq 14-4 Teq
18-3,
2014,
http://kouikishori.env.go.jp/guidance/download/,
Accessed 2020/4/23.
[9] Okumura Corporation, Entrusted with thecrushing and sorting of disaster waste in the
Yamada area performance report, 2014.
[10] Statistics Bureau of Japan, Housing and Land
Survey2018(e-stat),https://www.estat.go.jp/en/statsearch/files?page=1&layout=datalist&toukei=00200522&tstat=000001127155&cycle=0&year=20180&month=0&tclass1=000001129435&tcl
ass2=000001129436&stat_infid=000031865682,
Accessed 2020/06/29.
[11] Tokyo Metropolitan of Government Disaster
Prevention Information, Damage assumption inTokyo by Nankai Trough disastrous earthquakes(It's published on May 14, 2013.), pp.3-7, 2013,https://www.bousai.metro.tokyo.lg.jp/_res/proje
cts/default_project/_page_/001/000/402/part3-42.pdf, Accessed 2020/4/23.

In this study, the DHT model was applied to
Wakayama city to simulate a disposal process of
disaster waste caused by the Nankai TroughEarthquake.
Althoughtheprocessofcollection/transportation was modelled based onreasonable ideas, temporal storages were not utilized
well chronically. In this case, this surplus caused
inefficiency of the entire processes and a delay theprocessing period. This result suggested thatenhancement and optimization for transportation andseparation were critical issues for efficient disaster
waste disposal planning in Wakayama city. One of
the notable limitation of this study is not to reflect
outsourcing outside the disaster area. The outsourcing
might be effective for further shortening theprocessing time if these kind of enhancement andoptimization had been well-performed. Developmentof methods for enhancement and optimization are
considerable issue in order to improve convenience of
the DHT model, we plan to work on this in the future.
ACKNOWLEDGMENTS
This research was performed by the Environment
Research and Technology Development Fund“JPMEERF20201004” of the Environmental
Restoration and Conservation Agency of Japan.
Hiroaki TANIKAWA provided a distributed TFA
data usable in GIS.
REFERENCES[1] Ministry of the Environment, Discussion of thestatus and promotion of disaster waste
management
plan
development,
2020,
https://www.env.go.jp/recycle/waste/disaster/ea
rthquake/committee2/r1-02/R1_2_02_keikakusakutei.pdf, Accessed 2020/6/23[2] Hiroki T., Shunsuke M., and Cherry M.L.,
Estimates of Lost Material Stock of Buildings
and Roads Due to the Great East Japan
Earthquake and Tsunami, Journal of
INDUSTRIAL ECOLOGY, Vol.18, Issue 3,
2014, pp.421-431.
[3] Yuta N., Akifumi N., Syuiti Y., Yugo Y., Mineo
T. and Noboru Y., Analysis on Intensity of Waste
Generation in Prefectural Disaster Waste
Disposal Plans and Influence in Existing Plan in
Wakayama Prefecture, Journal of Japan Society2216th Int. Conf. on Structure, Engineering & Environment (SEE)
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ENERGY POLICY, CORPORATE STRATEGY, AND CONSUMERBEHAVIOUR IN JAPAN
Hisatoshi Tanaka1, Atsushi Nakashima2 and Nabil Maghrebi3
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Graduate School of Systems Engineering, Wakayama University, Japan;
3
Graduate School of Economics, Wakayama University, Japan

1

ABSTRACT
Natural disasters in Japan have had a significant impact on the Japanese people's relationship with nature andtheir convictions about social and economic life. However, the devastating nuclear accident caused by the Great
East Japan Earthquake in March 2011 led to a drastic change in Japan's nuclear policy. This new energy crisis has
indeed forced a fundamental rethink of Japan's energy strategy, while at the same time calling into question theimportance of non-renewable energy sources. As a result, there has been a growing interest in renewable energy
as a means of achieving sustainable economic and social systems. Despite the promises of clean energy, there arealso various constraints on the operation of renewable energy. The recent social trends are reshaping global energy
policy based on the SDGs and ESG perspectives. This study examines the relation between energy policy andcorporate strategy as well as consumer behaviour in Japan based on evidence from related literature. It argues thatan effective energy policy solution lies in raising awareness not only about structural changes in energy demandand supply, but also about the technical and social challenges. It considers also the strategic role of Japan's energy
policy in providing viable solutions to these serious challenges.
Keywords: Natural energy, Energy policy, Geothermal resources, Energy self-sufficiency rate
has been at the mercy of international conditions andthe international economy. In the case of Japan, it isdependent on Middle Eastern oil-producing countries
for much of its oil, and there was a time in the 1970s
when it was on the verge of "losing its oil"[1]. In the
background, geopolitics is involved, further
exacerbating the problem. Even in recent years, therisk of terrorism has increased and made the sea
routes for oil transport by tankers, such as the Straitof Hormuz, the Strait of Malacca and the South China
Sea, extremely vulnerable [2]-[4]. As the recent
international situation shows, the resource issue is nota simple one. As economist David Ricardo advocatedthe principle of world trade, every country shouldhave benefited from free trade [5], [6]. In reality,
however, due in part to speculation in financial andcommodities markets, the division of labor in theworld has rather increased, making it more difficult toimport resources freely. In order for Japan to maintainand develop its domestic economy in the future, it isnecessary to achieve domestic energy self-sufficiency.
The 1973 oil crisis exposed the weakness ofJapan's resource base and the danger of its
dependence on foreign countries. At the time, Japanlaunched a series of new energy policies, including areview of coal, promotion of nuclear power, andconsideration of environmental issues through theSunshine Plan. They have been followed by the
Moonlight Plan and the new Sunshine Plan, which
has been carried over into today's Basic Energy Plan
[7]-[9].

INTRODUCTION
It has been said that Japan is a "resourcelesscountry". However, there are actually many active
volcanoes and it is blessed with geothermal resources.
On the other hand, most of the land suitable forgeothermal power is designated as a national park. As
a result, development has long been severely
restricted by law. It was also necessary to consider the
impact of pumping large amounts of hydrothermal
water from the ground on the source of the hot springs.
However, Japan's Ministry of the Environment
has eased restrictions on nature parks. Furthermore,
the New Energy and Industrial Technology
Development Organization (NEDO) is aiming to
expand the introduction of geothermal power. The
system has been put in place to resolve the issues.
As the use of natural energy is desirable forenvironmental reasons, the introduction ofgeothermal power generation is expected toaccelerate in the future. It would significantly change
the nature of Japan's energy policy. Thus, this study
explores the possibility of geothermal power
generation in Japan based on data from the Ministryof the Environment, NEDO and the Agency for
Natural Resources and Energy.
THE IMPORTANCE OF ENERGY POLICY
Looking back at the history of Japan's energy
policy, the procurement of resources from overseas
222

SEE - Kyoto, Japan, Nov.18-20, 2020

After the Fukushima nuclear disaster in March
2011, Japan's power companies faced two issues
regarding the safety and economy of nuclear power
faced. The former were the technical challenges
associated with power generation, such as air andwater pollution and radiation. The latter were theeconomic and other issues such as electricity prices,
dividend rates on shares for investors, and funding forbusinesses to prepare for the future. This was a major
challenge. The Fukushima nuclear disaster has shown
the Japanese people that no matter how advanced thetechnology is, it is difficult to meet the demands ofboth safety and economy.
Japan's energy self-sufficiency rate was 20.3%(2010) before the Fukushima nuclear accident.
However, due to the shutdown of nuclear power
plants after the accident, the rate of 9.6% (confirmed
in 2017 in "General Energy Statistics") (value) [10].
As a result, Japan's energy policy has set four
goals: (1) to innovate in safety, (2) to ensuretechnological self-sufficiency and diversity of energy
choices in addition to resource self-sufficiency, (3) totake up the challenge of "decarbonization," and (4) toreinforce Japan's industrial competitiveness inaddition to controlling costs.
In Japan, thermal power generation was promoted
as a substitute for nuclear power. However, this wasa retrograde step in terms of global warming. For thisreason, rather than increasing thermal power
generation, a switch to renewable energy sources,
which use natural energy it became necessary.
Amid concerns about declining global economic
growth rates, a broader focus on the use of renewables
could influence the development of the country's
long-term energy supply and demand outlook. In

order to decommission nuclear power plants in Japanin the future, it will be necessary to make use ofenough renewable energy sources to replace them It
is considered to be one of the conditions. For thisreason, domestic geothermal resources have been
given an important place in Japan's "Basic Energy
Plan"[7].
GEOTHERMAL POWER GENERATION
Modern society has been using fossil fuels to
expand its economy since the "industrial revolution"of the mid-18th century. However, the negative aspectof this has manifested itself today in the form ofglobal warming. Therefore, since the 1992 Earth
Summit (United Nations Conference on Environmentand Development), natural alternatives to fossil fuelsin energy use have been suggested.
It is noted that in Japan, geothermal power is
expected to be an environmentally friendly energy
source. Unlike solar and wind power, which areconstrained by natural and geographic conditions,geothermal power is considered to be capable ofgenerating electricity consistently throughout theyear.
Geothermal power generation in Japan has a long
history, with the first successful geothermal power
plant in Japan in 1925. However, no progress has
been made since then. The first full-scale geothermal
power plant in Japan started operation in 1966. The
oil crisis of the 1970s led to the development ofdomestic geothermal research and development,
encouraged by the Sunshine Plan, an alternative
energy policy [11].

Table 1 Geothermal resources (in terms of electricity) in major countries
Country.

Amount of geothermal
Geothermal energy
Percentage used forresources (in terms ofgeneration capacity
power generation (％)
electricity)USA
30,0003801.00
12.67
Indonesia
27,7901945.50
7.00
Japan
23,470536.002.28
Philippines
6,000
1927.90
32.13
Mexico6,000
950.6015.8
Iceland5,800
753.0012.98
New Zealand
3,650
996.00
27.29
Italy
3,270
767.2023.46
Source: Prepared by the author based on materials from NEDO and other organizations.
・Most recent data: 2018
・Units are megawatts (MW)・Based on geothermal power generation capacity in each country at the end of each year
In countries with active volcanoes, geothermal
resources are being actively developed and used.
Table 1 shows the geothermal resources of majorcountries with active volcanoes in 2018. It is clearthat Japan's geothermal power potential is among thehighest in the world [12]. Japan's geothermal power
potential is one of the best in the world. However,
only a little more than 2% of the potential electricity
is actually used for power generation, highlightingthat the country is not making effective use of its own
223

SEE - Kyoto, Japan, Nov.18-20, 2020

resources.

national parks, and geothermal power plants based ondata from government agencies. The red zone is ageothermal potential area with a series of active
volcanoes. The blue area is a national park. The black
dots represent the current locations of geothermal
plants. Most of the geothermal potential areas aredesignated as national parks, and for a long time, thelaw has been strictly enforcing development it has
been limited. However, the Ministry of theEnvironment eased regulations on nature parks in
March 2012 and a feed-in tariff system wasintroduced in July 2012 to promote the use ofgeothermal energy [14].
As can be seen from the map, it is clear that theareas where geothermal energy can be used are
unevenly distributed. Given the disparities in the
distribution of potential geothermal plants, it may bedifficult to serve the diverse regional needs based on
this natural energy resource.
Table 2 shows the evolution of the power supply
mix in Japan from 2014 to 2019. The decrease in thepercentage of thermal power generation was due tothe restart of nuclear power plants that had been shut
down following the Fukushima nuclear accident andthe increase in the amount of solar power generation.
Geothermal power generation has hardly increased
and remains at rather low rates.
In order to reduce the proportion of thermal andnuclear power generation on the premise ofenvironmental protection, other sources of renewableenergy, especially the question of whether the
proportion of geothermal power generation can beincreased has emerged as a difficult challenge.

Fig. 1. Location of active volcanic belts, nationalparks, and geothermal power plants in Japan
Source: author's drawing on a white map ofJapanese Geographical Survey Institute.
Given the prevailing conditions of the energy
sector, the Japanese government has announced agoal of increasing geothermal power generation toapproximately 1.5 GW by 2030, but currently it is
only 536.00 MW, which is a huge gap [13]. Fig. 1
shows a simple map of Japanese active volcanic belts,
Table 2 Trends in power supply composition in Japanpower source

2014

2015

2016

2017

2018

2019

fire power
nuclear power
hydraulic power
solar power
biomass
wind power
geothermal energy

87.90%
0.00%
8.00%
1.90%
1.50%
0.47%
0.24%

85.70%
0.40%
8.60%
3.00%
1.50%
0.50%
0.25%

83.60%
1.70%
7.60%
4.40%
1.90%
0.54%
0.22%

80.80%
2.80%
7.60%
5.70%
2.00%
0.61%
0.21%

77.90%
4.70%
7.80%
6.50%
2.20%
0.69%
0.22%

75.00%
6.50%
7.40%
7.40%
2.70%
0.76%
0.24%

Source: Compiled by the author based on "Power Survey Statistics" by the Ministry of Economy, Trade andIndustry and the Agency for Natural Resources and Energy.
Thus, in the case of geothermal power, it isundoubtedly costly to install and maintain theequipment, but theoretically the energy resource itself
is cost-free. However, it is undeniable that there aremany areas where geothermal power generation is notpossible due to geographical conditions. Therefore,
measures are needed to address the vulnerability ofthe power source. As a countermeasure, if it ispossible to combine multiple types of natural energies,

it will be possible to increase the amount of electricity
generated in Japan as a percentage of the total amountof electricity. The percentage of renewable energy
could be increased. Naturally, this can be increased
from 18.5% in the fiscal year 2019 [15], [16].

CORPORATE STRATEGY AND CONSUMERBEHAVIOUR
224

SEE - Kyoto, Japan, Nov.18-20, 2020

REFERENCES
In order to utilize renewable energy, thecooperation of Japanese companies is essential, bothin terms of funding and technology. However, it has
become apparent that the influence of Japanesecompanies is declining in global terms [17]. This isdue to the rise of companies seeking to go borderlessand the speed of business in the world. This is due tothe fact that Japanese companies' business models todate have focused on regional rather than global
strategies, and that they have focused on internalmatters rather than negotiations with theircounterparts [18]-[20].
The slowness of management decisions anddecision-making was particularly critical. It has been
pointed out by foreign countries that Japan's social
structure and various regulatory issues have notchanged much, which has greatly delayed the flow ofelectricity liberalization [21]. In addition, Japan's
energy policy is based on the premise of maintaining
and restarting nuclear power plants even after the
Fukushima nuclear accident. On the other hand, theapproval of full liberalization of electricity in April
2016 is a small step forward after a long monopoly on
the supply and sale of electricity by power companies.
If we look at the Japanese energy industry,
especially the power industry, there is a need toreview market needs in light of changing
demographics, consumer behaviour, and a shrinking
market. Furthermore, it will be difficult to survive
without rationalization and economies of scale,through strategic capital investment in ICT and AI,
and outsourcing to reduce fixed costs. It is imperative
also that energy consumption is rationalized throughmore responsible consumer behaviour and energy
education.

[1] Agency for Natural Resources and Energy.,
What happens when the oil stops? ～Learningfrom History, A Risk to Japan's Energy Supply?
, 2019.
[2] Cabinet Office, Government of Japan,
Government Efforts to Ensure the Safety ofJapanese Ships in the Middle East, 2019.
[3] Japan Ministry of Defense. Government Efforts
to Ensure the Safety of Japanese Ships in the
Middle East, 2019.
[4] Ministry of Foreign Affairs of Japan,
Government Efforts to Ensure the Safety ofJapanese Ships in the Middle East, 2019.
[5] Ministry of Economy, Trade and Industry, The
benefits of free trade: a trade white paper, 2017.
[6] David Ricardo, Takuya Hatori et al., Principles
of Economics and Taxation, Iwanami Bunko,Vol. 1, 1987.
[7] Agency for Natural Resources and Energy,
Basic Energy Plan, 2020.
[8] Agency for Natural Resources and Energy (ed.).
Sunshine Project, New Energy Handbook,
March 1999, pp. 221-228.
[9] Agency for Natural Resources and Energy
supervised, resource and energy yearbook
1999/2000, 1999, pp. 642-645.
[10] Ministry of Economy, Trade and Industry, Total
Energy Statistics, 2019.
[11] Agency for Natural Resources and Energy.,
Japan's 150-year history of energy, 2019.
[12] Japan Meteorological Agency and Volcanological Society of Japan. 2020.
[13] Japan Oil, Gas and Metals National
Corporation.2020.
[14] New Energy Subcommittee, Current Status andIssues of Geothermal Power, 2020.
[15] Annual Report on Energy in 2019., Energy
White Paper 2020, 2020[16] Institute for Sustainable Energy Policies.
Renewable Energy White Paper 2020, 2019.
[17] Economic and Social Research Institute, Cabinet
Office, Government of Japan, Structural
Problems and Deregulation, 2019.
[18] Forbes Global 2000, 2019.
[19] Kazuhiro Asakawa., Introduction to Global
Management, Nihon Keizai Shimbun, 2003.
[20] Ministry of Health, Labour and Welfare,
Characteristics of Japanese Society inInternational Comparison, 2019.
[21] Ministry of Economy, Trade and Industry, The
potential for trade in services, 2016.
[22] Research Institute of Economy, Trade andIndustry, 2020.
[23] Bank of Japan, HP, 2020.

CONCLUSION
One of the main characteristics of Japan is that it
is a country with little natural resources, yet it imports
and consumes a large amount and variety of resources.
In other words, the resources of developing countries
are being used unconsciously, and the naturalenvironment of the target country is being destroyed.
An efficient energy policy that reflects thedemographics and environmental needs is thus
warranted.
Japan has already transitioned to a steady-state
economy, and the demand for energy is expected to
decline as the population declines [22], [23].
However,energyindependence,
energydecentralization and responsible corporate strategy
are needed to mitigate for future risks and achieve
meaningful reductions in carbon dioxide emissions. It
is research and development in geothermal energythat may contribute significant toward a moresustainable energy environment.

225

International Journal of GEOMATE, Month, Year Vol.00, Issue 00, pp.000-000
6th Int. Conf. on Structure, Engineering & Environment (SEE),
Geotec., Const. Mat. & Env., DOI: https://doi.org/10.21660/2020/6166Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051
ISSN: 2186-2982 (Print), 2186-2990 (Online), Japan

IMPACT OF CITRUS AGRICULTURE ON THE QUALITY OF
WATER RESOURCE IN A SMALL STEEP ISLAND,SETO INLAND SEA, JAPANSharon Bih KIMBI 1, Shinjo NOZAKI1, *Shin-ichi ONODERA1, Yusuke TOMOZAWA1,
Kungyang WANG1, Anna RUSYDI1, Mitsuyo Saito2
Graduate School of Integrated Arts and Sciences Hiroshima University, Japan
Graduate School of Environmental and Life Science, Okayama University, Japan1

2

ABSTRACT
Groundwater is the major source of water for domestic, agricultural and industrial purposes and its
exploitation for agricultural purposes has increased significantly in the past decades especially in Asian
countries. This paper investigates the groundwater resources of osakishimojima for its quality and possible
effects of agricultural activities on the resources. Fifty-one groundwater samples were collected andanalyzed for major ions and nutrients using an ion chromatography and automated nutrient analyzer
respectively. Results suggested that groundwater quality is strongly influenced by water rock interaction
and by the dominant citrus fruit cultivation in the area. The groundwaters are freshwaters (TDS<500 mg/l)
and are mainly: Ca + Mg-HCO3, Ca + Mg-NO3 + Cl - and Ca-Cl water types. High concentrations of
nitrate (91%) and phosphate phosphorus (53.1%) were observed in the shallowest wells suggesting inputs
from heavy application of NPK fertilizers. Thus, proper groundwater management strategies are necessary
to sustainably protect this valuable resource.
Keywords: Agriculture, Groundwater Quality, Contamination, Small Island, Seto Inland Sea

INTRODUCTION

monitor the quality of water. Previous studies
have been conducted on groundwater quality
assessment in many parts of Japan such as
estimation of sedimentation rate and fresh-saline
environment in coastal alluvial plain using boringcores of alluvium in the central part area of Seto
Inland Sea[5], suitability of groundwater for
agriculture in Northwest Honshu island [6] andestimation of groundwater recharge andsalinization in a coastal alluvial plain and megacity[7].
The present study investigates groundwater
quality in osakishimojima, a small island locatedalong the stretches of the Seto inland in
Hiroshima prefecture located in western Japan(Fig. 1). Osakishimojima like the many small
island in the Seto inland sea is currently a ruralarea suffering from depopulation and population
aging [8] as well as a high rate of rural exodus.
Citrus agriculture is well practiced in this area all
through the year in different scale. Nevertheless,unlike the big islands of Miyajima andNinoshima, osakishimojima has experienced little
or no significant human environment impact over
the years. This relatively pristine condition is
ideal for studying the nature of the groundwater
environment. The inhabitants of osakishimojima
equally rely solely on Kure regional water supply

Groundwater is the major source of water fordomestic, agricultural and industrial purposes inmany countries. Water quality is the criticalenvironmental determinant that influences the
agricultural production in any economy thatsolely depends on it [1]. In Asian countries,
exploitation of groundwater has increased greatly
over the past few decades where it is used for
agricultural and drinking purposes [2]. Elevatedlevels of contaminants such as nitrate andphosphate in water sources can be associated with
rapid population growth, agriculture, industries
and domestic waste. Findings from [3] show that,
agriculture is recognized as a major source ofwater pollution, which is also the most difficult toeliminate due to its spatial character.
A number of factors controlling groundwater
quality have been documented by [4] which
include; rainfall, topographic relief, mineraldissolution, mineral solubility, ion exchange,oxidation, reduction, natural and anthropogenic
activities such as geological structure andmineralogy of the watersheds and aquifers, theresidence time, poor sanitary conditions,application of fertilizers and pesticides for higher
crop yields. Therefore, it is most essential to226International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

system which is over 100km away from Kubi
village. Thus, in an advent of a natural disastersuch as the devasting flood which occurred inJune 2018, contaminating the pipelines with mudand sediments, the villagers were without accessto safe drinking water for over 10 days having toturn to their untested sources of groundwater for
drinking and other uses. The villagers were thenmotivated to seek out other sustainable water
resources of drinking water for future use andguide against being without a reliable source ofwater supply in the future.
On this note, the groundwater sources ofosakishimojima were being analyzed for their
quality and the study seeks to provide baseline
information on the effects of citrus farming on the
groundwater quality with emphasis on nitrates
and phosphates as the major contaminants. The
assessment of water quality in the study area is
one of the important tools for sustainable
development and will provide decisive
information for water resources management.

Geology
Osakishimojima is one of the Archipelago in
the middle of the Seto inland sea located in thewestern region of Japan (Fig. 2). It is made up
of late Cretaceous Hiroshima granitic rocks
which widely intrude into the remote islands of
the Seto island sea. It equally comprises of late
Cretaceous rhyolite- dacitic rocks outcrop and amélange matrix of Early to Middle Jurassic
accretionary complexes associated with Triassic
chert block and Carboniferous to Permian
limestone which underlay the island [9].

METHODS
Study Area
Osakishimojima is one of more than 700
islands located in the center of the Seto inland sea
in japan, about 10km off the coast of Kure city. Its
surface area is about 43km2 with geographic
coordinates 34°10'24"N and 132°50'3"E (Fig. 1)
with a dwindling aging population of about 3,000
people. It is a modest-sized island large enough to
be lined with steep mountains and narrow valleys
yet small enough to be tucked away amid a clusterof other islands. The topography of the area is low
land to shore.

Fig. 2 Geology of Osakishimojima Island modified
from [10]Land-uses
Osakishimojima is known to be one of themost interesting islands in the Seto inland sea.
Renowned for its well-preserved edo periodarchitecture of Mitarai it can easy be visited asa day trip. Dominated by forest, the island has awell-drained soil, which makes it perfect togrow citrus. The island is famous for its richcultivation of Mikan (Japanese mandarin) andlemon. The land-use of Osakishimojima island
is portrayed in Fig 3. In the past when the inland
sea was the superhighway of Japan, it was very
busy and prosperous but since the advent of
powered ships, railways and finally roads, it lostits prosperity and is now little more than afishing village with an ageing population.

Fig. 1 Location of Osakishimojima in Hiroshima
Prefecture and sampling points
227

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

phosphate and ammonia species were determinedwith a continuous flow automated nutrient analyzer.
Each sample was filtered using a 0.2 μm
polytetrafluoroethylene filter and subjected to 10
times and 5 times dilution using distilled water
before analyzing for the major ions. The
investigation of phosphate (PO4-P) sources was
conducted to determine the relationship between
PO4-P and Cl- and their respective contribution to
groundwater contamination. Analytical precision
for cations (Na+, K+, Mg2+, and Ca2+) and anions(Cl−, NO3-, SO42- and HCO3- was checked using
ionic balance error (IBE).
Fig. 3 land-use types of Osakishimojima andsampling locations.

RESULTS AND DISCUSSION
General Groundwater Chemistry andHydrochemical facies

Because of its sheltered location andgentle climate, osakishimojima is Japan’s
citrus island taking advantage of the calm air,strong sunlight, light rainfall, and good
mountain drainage, which is so important for
citrus orchards cultivation.

General groundwater chemistry
The physiochemical parameters and statisticalsummary for all 51 water samples collected fromosakishimojima are presented in Table 1. Physicalparameters such as pH, DO and EC often give us
the preliminary information that is required in any
groundwater study. pH is a negative logarithm of
the hydrogen ion concentration in an aqueous
solution and its temperature dependent thus
measurements should be taken in-situ alongsidetemperature. Thou pH has no direct effect on humanhealth, it is closely related to other chemicalparameters. The hydrogen ion can disrupt mineral
structures so that they contribute dissolved
constituents to groundwater i.e. the lower the pH,
the higher the TDS in the water [12]Sample Collection
Fifty-one water samples (49 wells, 1 stream and1 spring) were collected during the month ofOctober 2019 from representative sites in thevillage of Mikado and Kubi located inosakishimojima island. Sampling points areindicated in (Fig. 1). Samples of each point werecollected in acid washed 250ml polyethylene
bottles after rinsing at least three times with thesample water and preserved airtight to avoid
evaporation. Physicochemical parameters includingpH, electrical conductivity (EC), dissolved oxygen(DO), and water temperature were measured in situ
using portable devices. The values of theseparameters were recorded after they were stabilized.
TDS was calculated from EC by an empiricalformula TDS= 0.64*EC as described by [11].
Samples were filtered through a 0.2 μm
polytetrafluoroethylene filter and preserved at 4˚Cin a refrigerator. Alkalinity measurements werecarried out by acid titration with 0.02N H2SO4
added to each sample to reach its titration end point
within 24 hours of sample collection.

Table 1: Statistical analysis of various chemicalparameters
Parameters Min
Max Mean ST. Dev
EC
22.6
543 281.7
115.6
TDS
14.46 347.5 180.3
74
DO
4.2
10.2
8
1.4
pH
6.02
7.4
6.5
0.3
Temp
11.7
20.6
15.6
1.8
Na+
2.55
39.1
14.5
7.9
+
K
0.45
13.8
4.4
2.7
Ca2+
5.92
86.3
30.7
14.4
Mg2+
2.03
31.2
10.7
5.7
+
NH4
-0.09
3.4
0.5
0.8
HCO30 139.9
55.8
25.9
NO35.4
92.2
34.6
21
PO4-P
0
3.2
0.6
0.7
SO427.6
95.4
41.7
22.1
Cl1.94
48.6
14.1
8.9

Parameters and Chemical Analysis
Concentrations of major ions in water samples
were determined in the Laboratory of
Biogeochemistry at the University of Hiroshima,
Japan. Analyses for major ion chemistry included
sodium (Na+), potassium (K+), calcium (Ca2+),magnesium (Mg2+), chloride (Cl-), nitrate (NO3-)
bicarbonate (HCO3-) and sulfate (SO42-) by ion
chromatography while the concentrations of228

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

freshwater. Minor representations of Ca + Mg-NO3+ Cl (31%) and Ca-Cl (1 %) may suggest the mixingof freshwater with water from contaminatedsources.

Note: Ionic concentrations, TDS and DO: mg/l,
EC: μS/cm, Temp: O/C
The pH values for the study area ranged from6.02 to 7.4 with a mean value of 6.5 (Table 1) thus,
the groundwater of this area is generally neutral.
The maximum depth to the water table (12 m) was
relatively low, suggesting an existence of a shallow
aquifer system for the water sources that wereobserved. The water temperature ranged from 11.7
to 20.6 °C with mean value of 6.5 °C. The relatively
low temperatures recorded in water samples may
indicate their recharge under recent climaticconditions.
Groundwaters in the study area have pH values
slightly out of the World Health Organization [14]guideline limit (6.5–8.5) for drinking water with
only 41% within the acceptable limit making themneutral slightly acidic meanwhile 58% of thesamples were slightly acidic. EC is a measure of thesalt content of water in the form of ions. It is basedon the flow of electrical current through the sample,
the higher the salt content the greater its flow ofelectrical current. The EC of the groundwater varies
between 22.6 to 543μS/cm with the mean value of
281.7μS/cm. The obtained electrical conductivity(EC) values of groundwater samples ranged from
22.6 to 543 μS/cm (Tables 1). Concentration of total
dissolved solids (TDS) in groundwater ranged from
14.46 to 347.5mg/l (Tables 1). However, [14]categorized water based on TDS concentration into
four groups which are represented as fresh (TDS <1000 mg/L), brackish (> 1000 mg/L), saline (>10,000 mg/L) and brine (100,000 mg/L). Based on
this classification, all the groundwater samples fallin fresh category. The concentrations of dissolved
major cations and anions vary spatially.

Fig. 4 Piper trilinear diagram showing the main
Hydrochemical facies of groundwater in Osakishimojima
The order of dominance of ionic species in the
groundwater of the study area. The order of Ca 2+> Na2+ > Mg2+ > K+ for the cations and HCO3−>SO42− >NO3− >Cl− for the anions. (Ca2+ + Mg2+)
dominates (Na+ + K+), and (CO32− + HCO3−)
exceeds (SO42−+Cl−). The high concentration of
Ca2+ and HCO3− may suggests that process suchas chemical weathering occurs within the aquifer
system.
Mechanisms controlling water chemistry
The geochemical process occurring within the
groundwater and reactions with aquifer minerals
have a profound effect on water quality. Thesegeochemical processes are known to be responsible
for the seasonal and spatial variations ingroundwater chemistry. The Gibbs diagram [16]was used to provide information on the mechanismsthat controls the chemistry of the water sources. The
Gibbs’s plot (Fig. 5) revealed that majority of thedata (98%) points plotted in the domain of waterrock interaction suggesting that chemical
weathering of rock forming minerals is apparently
thedominant
process
influencing
thehydrochemistry of the aquifer in the study area.
The interaction between rocks and water resultsin leaching of ions into the aquifer which
subsequently influences the groundwater chemistry.

Hydrochemical facies definition
The chemical composition of groundwater is
primarily dependent on the geology as well as thegeochemical processes and anthropogenic activities
which take place within the aquifer system. Ionic
concentrations of major cations and ions plotted on
the Piper trilinear diagram [15] which provides
useful information on their chemical properties. The
meq/l concentrations of major ions plotted on a pie
chart (Fig. 4) showed that Ca2+ and HCO3− were themajor ions in waters followed by Na2+ and SO42−.
Based on their ionic concentrations and relative
proportions. Three types of water have been
identified (Fig. 3): Ca + Mg-HCO3, Ca + Mg-NO3+ Cl or Ca + Mg-NO3 + SO42-, and Ca-Cl. Majorityof the water samples (68 %) belonged to the mixed
Ca + Mg-HCO3 water type. This type indicatesmineral dissolution possibly secondary carbonate
and silicate minerals with enough recharge from229

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

fertilizers and pesticides are usually applied to thetrees. Equally some organic citrus farmers whoseorchards are near the sea spray their orchards withdiluted salty sea water to ward off pests and fungus.
Figure 6 indicates that there exists a weak negative
correlation between NO3- and Cl-. Hence, the agroindustrial activities of the study area could be themain source of groundwater contaminatedalongside lithologic effects. This contamination of
NO3- in most groundwaters may equally be driven
by the process of leaching of percolating rainwater.
This result was in disparity with those of [21] who
observed that, groundwater analysis of samples
from Indramayu exhibited higher NH4+-N
concentrations as oppose to NO3N.

Fig. 5 Gibbs plots indicating water-rock interaction
as the major process regulating the chemistry ofwaters in osaki-shimojima
Contamination of Groundwater
Phosphates and nitrates are useful nutrients forplant growth but when they become tooconcentrated in our water system, they become
dangerous to both humans and their environment.
Leaching of Nitrogen and Phosphorus from arable
fields to groundwater occurs as a result of highamounts of these nutrients applied in the form ofnatural and mineral fertilizers needed by plants [3].

Fig. 6 Scatter plot of NO3- versus Cl- in
groundwaters
Elevated concentrations of nitrates have undesirable
effects when present in drinking water. Table 2
characterizes water samples bases on the desirable
limit set by WHO [13]

Nitrate Contamination
According to Berner [17], there exist threesources of nitrogen in water; biological fixation,
precipitation, and the application of fertilizers
however humans significantly affect nitrogen loadin the environment. Anthropogenic sources ofnitrogen have been classified into three classes by[18] and they include (1) point source including
industrial sewage, refuse dumps discharged directly
into the surface water, (2) diffuse source including
runoff and leaching from rural and urban land, and(3) precipitation. Generally, lithologic source forNO3- in natural waters is unlikely and atmospheric
input is not often considered to be a major source ofNO3- concentrations in groundwater [19]. Based on
the premises that (Nitrogen, Phosphorous, andPotassium: (NPK), fertilizer is highly used during
agricultural activities, and domestic wastes areoften rich in chloride, a strong and weak correlation
between any pair of these element shall be
indicative of anthropogenic and non-anthropogenic
inputs, respectively[20].
The warm weather, low rainfall and volcanic
soils of osakishimojima have promoted the growthof intensive citrus fruit dating back to the 1930’s. In
order to maintain and increase crop yield, chemical

Table 2: Summary of WHO limit for NO3-N(10mg/l) and PO4-P (0.03mg/l) concentrations inwater samples of osakishimojima.

Parameter

Polluti
on
grade

No
of
Wel
ls

% of
Samp
le

Pollution
StatusNO3(mg/l)

<10

4

7.84

No
Pollution

10-50'

35

68.63

Pollution

50-70'

917.65

Pollution

>70

3

5.88

Pollution

<0.03

23

46.94

No
Pollution

>0.03

26

53.06

Pollution

PO4P(mg/l)

230

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

samples fell between 6-7m, eight samples within 5
and one sample at 12m (Table 2).

Fig. 7 Plot of depth of wells versus nitrateconcentrations in groundwaters

Fig. 8 Plot of depth of wells versus PO4-P
concentrations in groundwaters.

Figure. 7 shows a plot of NO3-N against depth.
The concentration of nitrates is significantly
homogenous spanning from 2m to 13m of theaquifers thou decreasing with depth. Such a
distribution clearly indicates that nitrate species inmost of the considered groundwaters are ofsuperficial origin (anthropogenic). This isindicative of the unconfined nature of the systemand shallow groundwater resources (open wells,
springs and streams) are more vulnerable to nitratecontamination due to natural N-fixing under aerobic
conditions.
As earlier mentioned, the most common land
use in the study area is agro-industrial cultivation
which is usually accompanied by large applicationsof fertilizers and pesticides. Nevertheless, otherfactors responsible for high nitrate concentrations inother basins have been known to include soilleaching and nitrogenous organic waste, poor wellcompletion improper waste disposal, handling andapplications of organic and inorganic fertilizers[22]-[23].

According to WHO [13] the recommended
value of phosphorous in drinking water is 0.3mg/L.
Consumption of water with phosphate more thanpermissible limit causes disease of the kidney andosteoporosis in human being [25]. Our findings
indicated that concentration of PO4-P was high ingroundwater, thus poses a future risk ofeutrophication of surrounding water bodies such as
Japan Sea.
CONCLUSION
This paper presented an analysis of waterchemistry results to identify the effects ofagriculture on the groundwater quality inosakishimojima, a small island in western japan.
According to the results, groundwater quality inosakishimojima is strongly influenced by rockwater interactions and anthropogenic activities(linked to agriculture). The groundwaters are
freshwaters (TDS<500 mg/l) and are mainly: Ca +Mg-HCO3, Ca + Mg-NO3 + Cl - and Ca-Cl watertypes. Chemical content of groundwaters is
primarily controlled by low temperature and water–rock interaction. However, high values of NO3 andPO4-P(mg/l) in most of the well samples renderthem unsafe for drinking and domestic purposes.
Overall, groundwater quality in osakishimojima is
impeded by anthropogenic activities, and proper
groundwater management strategies are necessary
to sustainably protect this valuable resource.
Nevertheless, there is a need to extensively carryout studies on the types of contamination and its
relationship with the environmental conditions in
the area.

Phosphate phosphorus contamination
Phosphorus is a soluble agricultural chemicalthat may be moved from point of application bysurface run off or moved out of the soil surface layer
with percolation [6]. The increase of PO4-P ingroundwater may equally be due to a high exchangeof water which has been documented in sand flatsby [24]. Phosphate phosphorus concentration in
ground water of the study area was varied withdepth (Fig. 8). In present investigation theconcentration of phosphate has been found to be
more than the permissible limit in fifty-three(53.1%) water samples out of forty-nine water
samples (Table 2). The PO4-P for water sources
ranged from 0 to 3.2mg/l with a mean of 0.6mg/l.
Thirty samples were within the depths of 4-5m, six

ACKNOWLEDGMENTS
The authors acknowledge the Graduate School ofIntegrated Arts and Sciences, Hiroshima University
231

International Journal of GEOMATE, Month, Year, Vol (Issue), pp. 000-000

for facilitating this research. We would also like toexpress our gratitude for the valuable comments
provided by reviewers and the editor of
GEOMATE. The authors wish to acknowledge
Google Earth engine for facilitating the access toarchive of publicly available satellite imagery.

sediments for geochemical mapping in the
remote islands of Japan,Seto Inland Sea region.
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233

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Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ECOSYSTEM-LEVEL WET TEST OF CAFETERIA DRAINAGE USINGMICROCOSM SYSTEM
Kazuhito Murakami1, Kakeru Ruike2, Tomomi Tsuchiya1,3, Kazuhi Obata1,4, Ryuhei Inamori2
and Yuhei Inamori2
Faculty of Advanced Engineering, Chiba Institute of Technology, Japan; 2Bio-Eco Engineering ResearchInstitute, Foundation for Advancement of International Science, Japan, 3Kato Construction Co., Ltd., Japan,
4
BML Inc., Japan

ABSTRACTIn Japan, the introduction of the WET (Whole Effluent Toxicity) test is under processing in consideration,
but this test may be different from the actual ecosystem phenomena because it is a single species test in spite of
the natural ecosystem consists of multi species biota. In this study, we developed the WET test using microcosm(M-WET) which is a simulated ecosystem model and consisted of several species of producer, consumer anddecomposer. Both the number of organisms as structural parameter and DO as functional parameter after
cafeteria drainage addition were analyzed by branched-type ANOVA, and the microcosm no observed effectconcentration (m-NOEC) and toxicity unit (TU) were calculated. As result, the m-NOEC of cafeteria drainage
was calculated as 5% and the TU was as 10, and assessed that the cafeteria drainage was discharged safely. It is
important to assess the complex influences of chemical agents, such as surfactants, medicines and so on, to theenvironment. To conduct such comprehensive assessments, M-WET tests should be used to examine drainage
with collecting total toxicity test data through single-species tests of chemical contaminants in environmental
water.
Keywords: Microcosm, Whole effluent toxicity (WET) test, Branched-type ANOVA, Cafeteria drainage, m-NOECWET test method utilizing a microcosm as awastewater management method is needed. In
parallel with a single-species test using species
belonging to different niches, such as ﬁsh,crustaceans, and algae, microcosm tests are
positioned as multiple-species tests. They may becorrelated with natural ecosystems, and it is essential
to construct these systems as comprehensive test
methods based on ecological impact assessment.
The WET test is a method that evaluates toxicity,
including multiple effects, because it is targeted attest waters containing multiple chemical substancesrather than being used for evaluations of the toxicity
of individual chemical substances [1][2]. However,
although we use individual species (ﬁsh, crustaceans,
and algae) located in different niches in the foodchain for the assay, it is a single-species test only. It
is not a test method that accounts for material cycles,
energy ﬂow, or biological interactions, which are thebasic elements of natural ecosystems [4]. The
microcosm is a system that includes multiple species
in coexistence and contains material circulation,energy ﬂow, and biological interactions [5][6].
Therefore, the microcosm makes it possible toevaluate the risks associated with added chemical
substances at the ecosystem level. The safety factors
for the ecological effects of chemical substances
obtained by the microcosm test were supported by

INTRODUCTION
Currently, introduction of WET (Whole Effluent
Toxicity) test is being considered in Japan, but it isdifficult to believe that the actual ecosystem can be
represented by the test method by current single
species as typified by small crustaceans Daphnia
magna as primary consumer and small fish Daniorerio as secondary consumer [1][2]. Therefore, byintroducing microcosms, which is a simulated
ecosystem including producers, predators, anddecomposers, into the WET test, more realistic
evaluation can be considered possible [3].
In this study, we conducted WET test, which is amethod of managing the influence on ecologicalsystems for actual drainage, with a microcosm,
which is a model ecosystem that imitates natural
ecosystem to calculate the microcosm no observed
effect concentration (m-NOEC) and toxicity unit
(TU) from the experimental results.

NECESSITY OF MICROCOSM TEST FOR
WETImpact assessments at the ecosystem levelutilizing aquatic model ecosystems, including a
microcosm, are well understood, but focus on the234

SEE - Kyoto, Japan, Nov.18-20, 2020the high correlation observed between the
microcosm test and mesocosm (natural ecosystem)
test obtained from the Environmental ResearchComprehensive Promotion Fund (2009–2011) andthe New LRI (2012–2014) [4]. Therefore, we
determined that it is possible to use the microcosm
test to evaluate the effects of chemical substances inan ecosystem with higher precision and with lessdispersion than in the conventional single-species
tests, such as the HC5 method. Consequently, it ispossible to calculate more realistic values of the
PNOEC for natural ecosystems using the microcosm.
Microcosms are highly correlated with natural
ecosystems and can be regarded as models
containing the basic components and characterized
by the basic principles of natural ecosystems [7].
From this fact, it is considered that a more realistic
estimate of the NOEC can be obtained using a
microcosm as compared with the current single
species test that does not account for material
cycling, energy ﬂow, or biological interactions [8].
In the ecosystem impact assessment of wastewatercontaining
variouschemical
substances,comprehensive tests were conducted to introduce theecosystem model, a multiple-species test with a foodchain and energy ﬂow, simultaneously with thesingle-species test. A series of test methods wereconstructed, making it possible to evaluate thedegradability and persistence of chemical substances
contained in wastewater and the collapse andrestoration of ecosystem functions [9]. The
microcosm test can be performed at a lower costthan the WET test with commonly used single
species (ﬁshes, crustaceans, and algae).
The microcosm has already been subcultured fornearly 40 years and is easy to use by researchersaccustomed to environmental microorganism testing
who can master the microbial culturing procedures.
It is also easy to use after short-term training.
Additionally, a series of tests are possible without
using expensive culturing tools or measurement
instruments. The position of the microcosm test
within the WET test is shown in Fig.1. The
foundation of a certain ECETOC method and theHC5 method conventionally includes the evaluationof independent chemical substances in toxicity tests
using single species, and the current WET test alsouses single species for toxicity tests on thecomposition of chemical substances. Theinteractions between species constitute theecosystem and drive the cycling of materials andenergy ﬂow; no single species is able to exist alone.
It is therefore insufﬁcient to evaluate the inﬂuence ofadded chemical substances at the ecosystem level
using a single-species test. However, the model
ecosystem consists of combinations of species, andmultiple microcosm tests contain the basic elementsof ecosystems, such as biological interactions,
cycling of materials, and energy ﬂow between

Microcosm

WET byMicrocosm

Fig.1 Placement of microcosm test for WET

Fig.2 Addition procedure of test effluent

Fig.3 Microcosm N-system apparatus
biological species.
Using the microcosm, it is possible for impact
assessments at the ecosystem level to reﬂect thenatural ecosystem, advancing the WET test as wellevaluating single chemical substances.
MATERIALS AND METHODS
Microcosm
A gnotobiotic-type flask-size microcosm system(N-system) [3][5][6] applied in this study consistedof combination of several species of four dominantbacteria as degraders, Bacillus cereus, Pseudomonas
putida, Acinetobacter sp., coryneform bacteria, twogreen algae Chlorella sp., Scenedesmus quadricauda
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SEE - Kyoto, Japan, Nov.18-20, 2020

case, it is impossible to compare it with the nonadditive system (control), so an appropriate medium
was developed with reference to the amount oforganic matter added at the time of wastewater
addition.

and one filamentous alga Tolypothrix sp as producer,
and one species of protozoan ciliates Cyclidium
glaucoma, two metazoan rotifer Lecane sp.,
Philodina erythrophthalma and one metazoan
oligochaeta Aeolosoma hemprichi as consumer.
Since this microcosm is a model microbial
ecosystem with high stability and reproducibility, it
is suitable for experiment [3]. The biomass(individual number) of each microorganism in thestationary phase are maintained about 1.1×106 N/ml
in bacteria, 1.1×105 N/ml in Chlorella sp., 5.3×103
N/ml in Scenedesmus quadricauda, 8.0×102 cm/ml
in Tolypothrix sp., 6.0 × 101 N/ml in Cyclidium
glaucoma, 1.3×102 N/ml in Lecane sp., 1.1×101
N/ml in Philodina erythrophthalma, and 6.0 N/ml in
Aeolosoma hemprichi, respectively.

Substance Concentration
Addition of a substrate was conducted byreplacing the culture medium in the ﬂask with
wastewater. A fresh medium containing wastewater
was added as a substitute for the extracted medium.
However, when the standard microcosm medium
was added as a new medium, the number ofindividuals in the steady state increased. Therefore,
as a new medium, the amount of peptone in themedium was adjusted to 0, 5, 10, 20, and 40 mg/l
and then added into the medium. The impact of each
culture medium was assessed from both the P/Rratio as the functional parameter and the abundanceof microbiota as the structural parameter in the
microcosm. The environmental impact andecological risk were estimated by comparing thetreated microcosms with the no-addition system(control) in both assessment methods. With respect
to the structural parameters, the abundance of
Cyclidium glaucoma, a ciliate primary predator, wasgreatly increased by increasing the amount of
peptone in the medium; there was no major change
in the abundance of other species in the microcosm.
From the P/R ratio, which is the functionalparameter, no change was observed when comparedto the no-addition system (control) as shown in Fig.
9.4. From this, the system was considered stable
unless wastewater was added. Statistical analysis of
the DO concentration was performed. The slope (a)and the coefﬁcient of variation (cv) were obtained
assuming that the microcosm was normally
distributed. If they fell within the range of ±34.13 % for each, it was considered that there was
no inﬂuence. Since the range of ±34.13 % of theslope of the DO was 0.0028 ≦ a ≦ 0.0056, it wasconsidered as having no inﬂuence on the medium
containing only 2 mg/l. Additionally, since the rangeof ±34.13 % of the coefﬁcient of variation of the
DO was 0.10 ≦ cv ≦ 0.20, it was considered ashaving no effect on the medium containing 0 to 20
mg/l. Therefore, a medium containing 2 mg/l of
peptone was considered appropriate for adding
wastewater in the microcosm-WET test [9][11].

Preparation of Test Efﬂuent
According to the testing procedure described in
the 1997 Sewage Examination Method (Japan
Sewage Works Association, Volume III Biological
Examination, Chap.1 Biological Examination,
Sect.10, Ecosystem Impact Assessment Testing)[10], the ratio of TP medium and test efﬂuent should
be set to 0, 25, 50, 75, or 100 %. Remove
contaminants by ﬁltering with a 0.45 μm size meshﬁlter, and add the ﬁltrate to the microcosm. The timeof addition is during the stationary phase (16th dayof cultivation). The water quality of the test efﬂuent
should be analyzed if necessary. The procedures of
microcosm-WET test are shown in Fig.2.
Addition of Test Efﬂuent
Addition of test efﬂuent to the microcosm isconducted on the 16th day, when the microcosm hasreached a stationary phase. For experiments inwhich chemical substances were added on the 16thday, the effect of the test efﬂuent on the microcosm
and the constituent microbiota may or may not allow
for the retention of species diversity (i.e., a stableecosystem may or may not be recovered). The
structural parameter (microbial population) and thefunctional parameter (P/R ratio) should be measured
to evaluate the effects of the test efﬂuent.
In the conventional microcosm experiments,
chemical addition is usually performed on the 16th
day after the cultivation began, when the systemstabilizes. In the WET test using the microcosm, themedium in the ﬂask must be exchanged for
wastewater, which is then added. At that time, it isnecessary to separate the organisms and the culture
medium, and a fresh medium containing wastewater
is added instead of the extracted medium. The
addition of the attached microcosm standard
medium increases the number of individuals in thesteady state. This is because organic substances thatfeed microorganisms are already consumed. In thisMicrocosm WET Test
As shown in Fig.3, for microcosm culture, 200
ml of TP medium adjusted to a concentration of 100
mg/l of polypetone was placed in a 300 ml volume
Erlenmeyer flask, inoculated with 10 ml of
subcultured microcosm as a seed, 25 °C, 2,400 lux(bright 12 hr./dark 12 hr.) and without shaking.
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SEE - Kyoto, Japan, Nov.18-20, 2020

Treated water of cafeteria drainage from thewastewater treatment facility in the university
campus filtered using a membrane filter with acaliber of 0.45 μm. Thereafter, on the 16th day,which is the stable period of the microcosm, it wasadded to have concentrations of 0, 5, 10, 20, 40 and80%.
Assessment Method
Impact risk assessment of each concentration
was estimated from the DO change in the
microcosm was continuously measured sequentiallyby the DO meter, and the transition (functionalparameter) of P (production), R (respiration) andP/R ratio was obtained.
Simultaneously, sampling was started from themicrocosm on 0, 2, 4, 7, 14, 16, 18, 20, 23 and 30
days after the start of culture, and plankton was
sampled under a light microscope using a plankton
counter and the transition (structural parameter) of
thenumberoforganisms
constituting
microorganisms was observed. Also, "Branchedtype ANOVA" was performed on the change overtime of functional parameters and structuralparameters. As shown in Fig.4, in the branched-type
ANOVA evaluation was performed from two items,"group" which is the variance analysis by all thevalues of each system and "interaction" which is ananalysis of variance over time [3].
In the functional/structural parameter, the highest
concentration among the concentrations not affected
as a result of the branched-type ANOVA was taken
as the maximum no-effect concentration (m-NOEC),and the toxicity unit (TU) was calculated from thefollowing equation (1). The safety factor is proposed
as 200 by the former investigation [4][12].

Fig.4 Outline of branched-type ANOVA
Toxicity unit (TU) = 100 / (m-NOEC×200)(1)

RESULTS AND DISCUSSION
Water Quality of Cafeteria Drainage
The water quality of the treated water from thetreatment facility as tested drainage effluent in theuniversity campus was pH: 7.18-7.21, COD: 15.217.2 mg/l, T-N: 2.68-12.4 mg/l, T-P: 0.13-0.98 mg/l,
SS: 9.40-18.5 mg/l, Cl-: 14.2-15.7 mg/l, respectively.
Functional Parameter Analysis
Time course of DO and P/R ratio (functionalparameter) in microcosm under each test condition
were shown in Fig.5. In the evaluation by DO andP/R ratio (functional parameter), the amplitude of
DO decreased as the added concentration became
higher, and the activity in the microcosm was lower.
It is thought that residual chemical substances arecontained in the cafeteria drainage. However, theP/R ratio was stable around 1 at all addedconcentration. This is probably because the activitiesof phytoplankton and zooplankton have both

Fig.5 Time course of DO and P/R ratio (functional parameter) in microcosm under each test condition
237

SEE - Kyoto, Japan, Nov.18-20, 2020

Fig.6 Time course of individual number of microorganism (structural parameter) in microcosm under eachtest condition
decreased. In functional parameters, the P/R ratio,
respiration, and production were tested by branchedtype ANOVA and the presence or absence of
influence was determined. As a result, m-NOEC wasevaluated to be less than 5 %.

Table 1

Summary of evaluation result

Structural Parameter Analysis
Time course of individual number of plankton(structural parameter) in microcosm under each test
condition were shown in Fig.6. Two zooplankton
species (Lecane sp. and Aeolosoma hemprichi)
decreased in 20, 40, 80% addition system in theevaluation by the number of individuals (structuralparameters), but did not exterminate. It wasconsidered that these were influenced by chemical
substances remaining in effluent as well asfunctional parameters. However, since all the
microorganisms did not exterminate but coexisted,
the ecosystem in the microcosm was maintained.
There was no influence in 5 and 10 % addition
system.
Statistical
Assessment

Analysisforbecause the activities of phytoplankton as producer
and zooplankton as consumer have both decreased.
For the functional parameters, the P/R ratio wassignificant-tested by branched-type ANOVA, andthe influence was determined. Based on thestatistical processing result of the functionalparameters, m-NOEC which is the maximum noeffect concentration was evaluated to be present in arange lower than 5% as shown in Table 1. The
toxicity unit (TU) was calculated as 100 / (0.05×200) = 10. Here, 200 is the safety factor for
microcosm test. This value means that 10 times
dilution is necessary to discharge safety to theenvironment, but 10 times dilution is expected after
discharge by natural purification. Considering theabove, the cafeteria drainage in the university
campus was evaluated as being properly treated.
It is important to assess the complex influencesof chemical agents, such as surfactants andmedicines, on the environment. To conduct suchcomprehensive assessments, microcosm-WET tests
should be used to examine drainage by collecting
total toxicity test data through single-species surveys
of chemical contaminants in environmental water. It
is thought that more details for high-risk materials
can be analyzed by the microcosm-WET test with a

EcotoxicologicalIn the evaluation by DO and P/R ratio(production/respiration ratio) as the functionalparameter, the amplitude of DO decreased as theadded concentration became higher, and the activity
in the microcosm became lower. It is thought that
residual chemical substances were contained in thedrainage. However, the P/R ratio was stable around
1 at all added concentration. This is probably
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SEE - Kyoto, Japan, Nov.18-20, 2020

general comparison analysis. Additionally, because
the microcosm-WET test offers high precision at alow cost, and it is expected that the correlation
between the natural ecosystem and the microcosm ishigh, the estimated NOEC is more realistic than thatderived from single-species tests, and the predictionof the behavior of the natural ecosystem is morepractically enabled.
It can also be expected that wastewater
management can greatly contribute to theremediation of the environmental impacts ofeffluents by introducing the microcosm-WET test of
the Ministry of the Environment, Japan.

REFERENCES[1] United States Environmental Protection Agency,
Method Guidance and Recommendations for
Whole Effluent Toxicity (WET) Testing, 40 CFRPart 136, EP 821-B-00-004, 2000.
[2] Tatarazako N., The Newest Domestic andOverseas Trend of Assessment and Regulation of
Efﬂuent Water using Bioassay –Overseas
Operation Case to Japanese WET Test
Introduction”, Tokyo, NTS, 2014. 322pp. (inJapanese)[3] Inamori Y., ed,, Microcosm Manual for
Environmental Impact Risk Assessment: From
Chemicals to Whole Effluent Toxicity (WET),New York, Springer, 2019, 258pp.
[4] Inamori Y., Murakami K., Kakazu K., Inamori
R., Kanzo Y., Shibata K., Amemiya T. andSugiura K., Development of Environmental
Impact Risk Assessment Method using
Microcosm for OECD Standard Test,
Proceedings of 20th Symposium on Japan
Society of environmental Toxicology in Toyama,
2014. (in Japanese)[5] Kurihara Y., Finite Ecology –A System of
Stability and Coexistence-, Tokyo, Iwanami
Shoten, 1975, 187pp. (in Japanese)[6] Kurihara Y., Stability in Ecological Microcosm,
Proceedings of Japan Academy, Series B,
Physical and Biological Sciences, Vol.80, No.7,
2004, pp.327-335.
[7] Beyers R. J., and Odum H. T., Experimental
Microcosms, New York, Springer-Verlag, 1993,
545pp.
[8] Graney, R. L., Kennedy, J. H. and Rodjers, J. H.
Jr., Aquatic Mesocosm Studies in Ecological
Risk Assessment, Boca Raton, CRC Press,
Lewis Publishers, 1994, 736pp.
[9] Tsuchiya T. and Murakami K., Ecosystem Level
Whole Effluent Toxicity Test using Microcosm
System, Papers on Environmental Information
Science, Vol.33, 2019, pp.31-36. (in Japanese)[10] Japan Sewerage Works Association,
Wastewater Examination Method -FY2012-,
Tokyo, 2012, 819pp. (in Japanese)[11] Tsuchiya T., Murakami K., Inamori R. andInamori Y., Development and Verification of
Microcosm-WET Test on Basal Medium
Concentration, Proceedings of IWA World
Water Congress & Exhibition 2018, Tokyo,
2018, online.
[12] Sugiura K., Effects of Chemicals on
Microcosms: Comparison with the NOECs inExperimental and Natural Ecosystems, Japanese
Journal of Environmental Toxicology, Vol.13,
2010, pp.13-22.

CONCLUSIONS
A gnotobiotic-type flask-size microcosm system(N-system) was applied to assess the whole effluent
toxicity (WET) of cafeteria drainage, which
consisted of several species of four dominantbacteria as decomposer, two green algae and one
filamentous alga as producer, and one species ofprotozoan ciliates, two metazoan rotifer and one
metazoan oligochaeta as consumer.
In the evaluation by DO and P/R ratio(production/respiration ratio) as the functionalparameter, the amplitude of DO decreased as theadded concentration became higher, and the activity
in the microcosm became lower. It is thought that
residual chemical substances were contained in thedrainage. However, the P/R ratio was stable around
1 at all added concentration. This is probably
because the activities of phytoplankton andzooplankton have both decreased.
In the functional parameters, the P/R ratio wassignificant-tested by branched-type ANOVA, andthe influence was determined. Based on thestatistical processing result of the functionalparameters, m-NOEC (microcosm No Observed
Effect Concentration) was evaluated to be in therange lower than 5 %.
The toxicity unit (TU) was calculated as 100 /(0.05×200) = 10, and the cafeteria drainage fromthe university treatment facility was evaluated as
being properly treated.
From above, microcosm WET test is considered
to be essential for ecosystem-level environmental
impact risk assessment of various drainage.
ACKNOWLEDGEMENT
Special thanks to late Dr. Yasushi Kurihara,
emeritus professor of Tohoku University, and Dr.
Katsura Sugiura, emeritus professor of Sagami
Women’s University, for their kind and essential
discussion in microcosm experimental method.

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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

RIVER ENVIRONMENT EVALUATION BY WATER QUALITY,ATTACHED DIATOM AND MACROBENTHOS IN BOSO PENINSULA,JAPAN
Kazuhito MURAKAMI1, Haruna NIIDA1,Tsuyoshi DOYAMA1 and Kenji WATANABE2
1
Chiba Institute of Technology, Japan,
2
Tokyo Metropolitan Kohoku High School, Japan
ABSTRACTTo evaluate river environment in Boso peninsula of Japan, Koito river (FY2009), Obitsu river (FY2010), Yoro
river (FY2011), Inba marsh inflow and outflow rivers (Shinkawa river, Hanami river, Kashima river) (FY2012,2016), Tega marsh inflow and outflow rivers (Ohori river, Ohtsu river, Someiiriotoshi, Tega river) (FY2013),
Kuriyama river (FY2013), Isumi river (FY2014), Sakuta river (FY2015), Ichinomiya river (FY2016), Minato river(FY2017), Kamo river (FY2018), Maruyama river (FY2019), Murata river (FY2019), and their watershed wereresearched their water quality, attached diatom and macrobenthos. The survey were carried out four times a year
at each of three to seven points of each river seasonally. BOD (water quality), DAIpo (attached diatom) and ASPT
(macrobenthos) were measured and calculated. The Boso peninsula was shown to be divided into three areas: theNorthwestern (urban area), the Northeastern part (plains), and the Southern part (hilly area). The Northwesternpart (urban area) and Northeastern part (plains) were evaluated as "polluted", and the Southern part was evaluatedas "clean", and it was shown that rich nature was left in the Boso hills. Note that, there was the great gap between
the evaluation by macrobenthos and attached diatom. The Northwestern part, where large cities are gathered, were
evaluated as "polluted". Despite the large city does not exist, the Northeastern part was assessed as "polluted". It
was considered due to nonpoint sources from huge paddy fields along Kujyukurihama coastal line. ECIeco as theoverall index, which comprehensively evaluates attached diatoms and benthos, evaluated the hilly area as clean.
Keywords: River environment, Water quality, Attached diatom, Macrobenthos, Boso peninsula

INTRODUCTION

integrally.

Utilization of biological indicators for water
environmental evaluation is different from water
quality indicator by chemical analysis. It has theadvantage of reflection a relatively long-term
environmental change and easy to convert as an
influence to human. On one hand, there is a big
problem that they require skill in the classification,
identification and counting and susceptible to the
influence of analysis of individual differences andmethod of investigation.
In Japan, when evaluating rivers, chemical water
quality survey is main investigation but biologicalwater quality survey is not, as well as in Chiba
Prefecture. Then, it is thought that comprehensive
biological water quality survey in Chiba Prefecture
will be possible by using attached diatom as a
producer and benthos as higher-end consumers [1].
In this study, the river environment evaluation
using the biological index was carried out for the riverwhich flows down the Boso Peninsula, and the riverenvironment map in the Boso Peninsula was made,and it aimed at the construction of the bioenvironment information of Chiba Prefecture at thesame time. Also, ECIeco (Environmental Condition
Index of Ecosystem) was devised and calculated. It is
indicators that express attached diatom and benthos

RESEARCH METHODSRivers to survey
Fig.1 shows the survey river. To evaluate riverenvironment in Boso peninsula of Japan, ① Koito
river (FY2009), ②Obitsu river (FY2010), ③Yoro
river (FY2011), ④Inba marsh inflow and outflow
rivers (Shinkawa river, Hanami river, Kashima river)(FY2012, 2016), ⑤Tega marsh inflow and outflow
rivers (Ohori river, Ohtsu river, Someiiriotoshi, Tegariver) (FY2013), ⑥ Kuriyama river (FY2013), ⑦
Isumi river (FY2014), ⑧Sakuta river (FY2015), ⑨
Ichinomiya river (FY2016), ⑩ Minato river(FY2017), ⑪ Kamo river (FY2018), ⑫ Maruyama
river (FY2019), ⑬Murata river (FY2019), and theirwatershed were researched their water quality,
attached diatom and macrobenthos. It was carried out
four times a year at each of three to seven points ofeach river by season.
Water quality survey
The surface water was collected with a heyrothwater sampler and measured BOD according to JIS240

SEE - Kyoto, Japan, Nov.18-20, 2020

K0102 [2] of the factory wastewater test method andthe ocean observation guidelines [3].

Table 1 shows the relationships between DAIpo,
BOD, and pollution class

Attached diatom

RPId

Attached diatom was collected using a quadrate
frame of 5 cm × 5 cm from the bottom of the river,and we classified, identified, and counted using a
biological microscope (Nikon Ecripse E 800).
DAIpo (Diatom Assem blage Index to organic
water pollution) and RPId (River Pollution Index
based on DCI) were calculated, and the riverenvironment was evaluated.

RPId is a river total evaluation value based on
DAIpo, which is possible to compare the pollution ofrivers different flow path length [4]. It was calculated
the area of the trapezoid created by plotting the valueof DAIpo on the graph and drawing a perpendicularfrom the plot and flow path length, and calculated
from Eq. (2)
RPId = S/L

(2)

DAIpo
It is an organic pollution index based on attacheddiatom community, and it is used as a biologicalindex for organic contamination common to stillwater areas (lakes) and running water areas (rivers)[4].
We calculated Eq. (1) after identifying what
species category the attached diatom belongs to.

Here,
S: The area of figure consisting of DAIpo (horizontalaxis) at each survey site flow path channel length(vertical axis) of the survey river
L: The flow path length of the river surveyed(Distance between the most upstream point and themost downstream point among the surveyed
points)

DAIpo = 50＋0.5(A－B)

Benthos(1)

The benthos was collected using D-frame net or
Ekman-Birge bottom sampler, and classified,
identified, and counted using a substantive
microscope (Nikon smz445). The ASPT (Average
Score Per Taxon) value from the BMWP score(Biological Monitoring Working Party score) was
calculated, and the river environment was evaluated[5][6].

Here,
A: The sum of the relative frequency (%) of all goodclear water species at the survey site
B: The sum of the relative frequency (%) of all good
pollution species at the survey site

ASPT
After classifying and identifying benthos intofamilies, we applied those benthos to a score tablethat classified the benthos of the 62 families intoscores of 1-10 [7]. ASPT was calculated by Eq.(3).
ASPT = TS / TF

Table 1

Fig. 1

Survey rivers in this study
241

(3)

Relationship between DAIpo, BOD, andpollution classSEE - Kyoto, Japan, Nov.18-20, 2020

Table 2

Evaluation of water environment by
ASPT value (provisional)

Table 3

Evaluation of water environment by
ECIeco

Fig.2

BOD of each river (The numbers below
correspond to Fig.1.)

RESULTS
Water quality
Figs.2 and 3 show the result of BOD andenvironmental condition map of Boso peninsula
based on BOD.
From Fig.2, BOD was highest in the Sakuta river⑧ and lowest in the Kuriyama river⑥ in the Boso
Peninsula. From Fig.3, urban and plain area were
evaluated as “slight clean” by BOD.

Here,
TS: Total BMWP score of appeared benthos
TF: Total family number of appeared benthos
The survey point is evaluated from 1 to 10 points
by the ASPT value (Table 2).
ECIecoAs the overall index, ECIeco (Environmental
Condition Index of Ecosystem) was calculated by
DAIpo (attached diatom) and ASPT value (benthos)[8]. ECIeco expresses biological interaction as themultiplication of each pollution class. ECIeco wasdevised as an index that comprehensively expresses
both. Each evaluation result is converted into 10classes and calculated. ECIeco was calculated from Eq.
(4).
ECIeco = (Cdiatom × Cbenthos)1/2

(4)

Here,
Cdiatom：Evaluation classification based on DAIpo
Cbenthos ： Evaluation classification based on ASPT
value
Fig.3

The result of 10 is clean and 0 is dirty (Table 3).

242

Environmental condition map of Boso
peninsula based on BOD, divided into
three areas.

SEE - Kyoto, Japan, Nov.18-20, 2020

Attached diatom
Figs.4 and 5 show the result of RPId andenvironmental condition map of Boso peninsula
based on attached diatom.
The Boso peninsula was shown to be divided into
three areas, that is the Northwestern (urban area),
Northeastern (plains) and Southern parts (hilly area)[9]. The Northwest (urban area) and the Northeast(plains) were estimated as "dirty" and the South (hillyarea) was estimated as "clean", and it was shown thatrich nature was left in the Boso hills. The Minato river⑬, which flows down the southern part of the Boso
Peninsula, was evaluated as β-Oligosaprobic water(clean) only in the Boso Peninsula.

Fig.4

southeastern part. The southwestern part was in themountains and the river mouth was also rich in nature.
The southeastern part was evaluated somewhat
polluted water to polluted water, because th eresidential area and the fields were expanding along
the river mouth, it was the effect of domesti c
wastewater and agricultural wastewater.

Benthos
Fig.6 shows environmental condition map of
Boso peninsula based on benthos.
Like attached diatoms, the Boso peninsula wasshown to be divided into three areas, that is theNorthwestern (urban area), Northeastern (plains) andSouthern parts (hilly area) [9]. In addition, there was
the great gap between the evaluation benthos andattached diatom.
As for benthos, it was shown that the southern partwas further divided into the southwestern part and the

Fig.5

RPId value in each research point (Thenumbers below correspond to Fig.1.)

ECIecoFigs.7 and 8 shows the result of ECIeco.
The results of ECIeco showed that the values in thesouth (hilly area) were higher than those in thenortheast (plains) and northwest (urban areas). The
comprehensive evaluation of attached diatoms andbenthos also showed that the southern part (hilly area)

Fig.6

Environmental condition map of Boso
peninsula based on attached diatom, divided
into three areas.
243

Environmental condition map of Boso
peninsula based on benthos, divided into
four areas.

SEE - Kyoto, Japan, Nov.18-20, 2020

Fig.7 ECIeco in each research point (The numbers below correspond to Fig.1.)
yellow: North part (plains and urban area), blue: hilly area, white: coastal area
“Polluted water”. The value exceeded 3 at all points.
Therefore, there are no rivers that are rated "dirty" in
the Boso Peninsula. It seems to be in the range of alittle dirty to a little clean.

was clean. For each river, many rivers had lower
values from upstream to downstream, and it was
shown that there is a tendency for pollution especiallyfrom upstream to downstream in the south (hilly area).
DISCUSSION
The river environment map of the Boso Peninsula
The Northwest (urban area), where many large
cities are gathered, were evaluated as "polluted". It
was considered due to the pollution caused a vibranturban economy. Despite the big city does not exist,
Northeast (Plains) was assessed as "polluted". It wasconsidered nonpoint sources from paddy fields along
Kujyukuri because fluctuation of pollution connectedfarm work. BOD becomes somewhat clean reputationin the Northwest (urban areas), and Northeastern(Plains), and BOD and biological indicators were notconsistent. The water quality is evaluated frominstantaneous sampling, however, biologicalindicators are for the evaluation of long-lasting water
quality of river. Attached diatoms reflect the water
quality, and benthos reflect the sediments pollution
condition.When the water quality was improved, thequality of the water changed immediately but thebottom sediment took a long time to improve, so theevaluation results were different. Therefore, it may
show improvement from pollution state.
Furthermore, ECIeco as the overall index was
shown to be lower in the downstream. ECIeco resulted
closer to DAIpo than ASPT value but, the trend was
similar to ASPT value. Also, it was not evaluated as

Fig.8

244

Environmental condition map of Boso
peninsula based on ECIeco, divided into
three areas.

SEE - Kyoto, Japan, Nov.18-20, 2020

In the future, using assessment by existing
individuals, population and water quality and DNA
analysis (eDNA), more detailed environmental
assessment will be conducted considering
quality/quantityofexisting
creature
andconstruction/structure/function of ecosystem. Whilecontinuing to accumulate data, it try to create new
indicators that comprehensively evaluate water
quality, attached diatoms, and benthos.

cooperation.
REFERENCES[1] Tanida K., Indicators Biology of River
Environment, Hokuryukan, 2010, 197pp. (inJapanese).
[2] Japan
Standards
Association,
Factory
Wastewater Test Method JIS-K0102, 1993,
593pp. (in Japanese).
[3] JMA, Manual on Oceanogaphic Observation,
Meteorological Business Support Center, 1999,
252pp. (in Japanese).
[4] Watanabe T., Ecology of Freshwater Diatom,
Uchidaroukakuho, 2005, 666pp. (in Japanese).
[5] Environmental Management Bureau, Search forriver creatures, Ministry of the Environment,
Japan, 2017, 34pp. (in Japanese).
[6] Environmental
AgencyWater
Quality
Conservation Bureau, Survey manual forassessing river water environment using large
benthic
animals,
Environment
Agency,1992, .21pp. (in Japanese).
[7] Environmental Management Bureau, Manual for
Water Quality Assessment by Aquatic
Organisms -Japanese version ASPT method-,
Ministry of the Environment, Japan, 2017, 33pp.
(in Japanese).
[8] Murakami K., Gomyo M., Agatsuma S., Amano
Y.,Inoue-Kohama A., Environmental Condition
Index for Estimation on Eutrophic State of
Enclosed Aquifer Ecosystem, Journal of
GEOMATE, Vol.5, Issue 2, 2013, pp.706-711.
[9] Murakami K., Doyama T., Niida H., Watanabe
K., Evaluation of River Environment by
Biological Indicators in Boso Peninsula,
Proceedings of 17th World Lake Conference(Ibaraki-Kasumigaura 2018), 2018, pp.942-944.

CONCLUSIONS
1) The Boso peninsula was shown to be divided into
three areas of the Northwestern (urban area),
Northeastern (plains) and Southern parts (hillyarea)2) The Northwestern part (urban area) and theNortheastren part (plains) were estimated as"dirty" and the Southern part (hilly area) was
estimated as "clean", respectively.
3) There was the great gap between the evaluation by
benthos and attached diatom as biologicalindicators, and from this reason, it is necessary toevaluate both indicators comprehensively.
4) ECIeco as the overall index, which comprehensively
evaluates attached diatoms and benthos, also
evaluated the hilly area as clean. It was shown that
there is a tendency for pollution from upstream todownstream.
ACKNOWLEDGMENTS
In carrying out this research, many graduate
students of our laboratory made much efforts toprovide useful discussion. We would like to express
our sincere gratitude for their kindly and serious

2456th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

IDENTIFYING IMPACTS OF DENSITY-DRIVEN FLUCTUATION TO
GROUNDWATER CAUSED BY SALTWATER INTRUSION
Theara Seng1, Junichiro Takeuchi1 and Masayuki Fujihara1
1
Graduate School of Agriculture, Kyoto University, Japan

ABSTRACTEngineering knowledge on soil and water is crucial for sustainable water resources management. Saltwater
intrusion due to such as storm surges or high tide often causes salt damage to crop farmlands. To prevent losses,
it is recommended to leach salt by freshwater; however, this activity might create a density-driven flow of salinity
into groundwater, and finally, it has possibility to get saltwater to spread widely in downstream. This study aimed
to analyze the impact of saltwater intrusion on groundwater flow by laboratory experiments. The technique was toverify the oscillatory phenomena of vertical intruding saltwater into horizontally flowing groundwater. To find out
the qualitative difference of saltwater intrusion under various conditions, a laboratory-scale of aquifer flow model
was set up. The oscillatory flow could be estimated by the proposed Rayleigh number which comes from different
saltwater concentrations, basal groundwater flow rate and so on. According to the photography results, oscillatory
flow occurred, and its variation could be evaluated by the Rayleigh number, whereas the increase of basal
groundwater flow rate tends to reduce the side effects of salinity intrusion.
Keywords: Saltwater Intrusion, Density-driven Flow, Rayleigh Number
saltwater into horizontal groundwater flow throughlaboratory experiment. Kawabata [6] investigatedthese phenomena through numerical approach, inwhich the dispersion was treated as a constant scalar.
Their results illustrated that the oscillatory flow
pattern depends on three parameters includingRayleigh number, basal groundwater flow, andsaltwater intrusion rate. Three types of saltwater
intrusion were found: rapid convergence without
oscillation, oscillation, and oscillatory convergence.
It is also concluded that some bifurcations occur
relative to given basal groundwater flow rate. But
they considered that the basal flow rate is anotherparameter that changes flow regime except for theRayleigh number because they adopted the constantdispersion coefficient. The dispersion coefficient is atensor and it depends on the flow rate [7]. Hence, it isconsidered that the basal flow rate needs to be
included in the Rayleigh number.
Kawabata [8] extended investigation on saltwater
intruding behaviors through laboratory experiments
by using lab-scale groundwater flow tank. The resultsfrom photography and measurement of electricalconductivity indicated oscillatory flow and its
variation caused by the Rayleigh number whereas
periodic pattern happened for the numerical model
which meticulous investigation is needed. Further, a
study of the stability of density-driven flows insaturated homogeneous porous media by Musuuza[9] suggested that dispersion has a significant effecton flow states, in which varying degrees of instability
can be seen by different assumptions of dispersion.
Holzbecher [10] proposed the mixed convection
number instead of the Rayleigh number to evaluate

INTRODUCTION
Density-driven flow of fluids usually caused bydensity difference due to instability of fluids causedby solutes and/or heat, resulting the changes in flow
behaviors of solute and/or heat. When thisphenomenon happens in groundwater, it willcontribute a significant impact on solute and/or heattransports. For these reasons, it is important tocomprehensively observe the condition for
occurrence of density-driven flow and to identify its
dynamics to sustainably manage water resources.
Density-driven flow comes from different sources
for both natural and human activities. Saltwater
intrusion in coastal regions is a specific case, causedby high tides, storm surges, and saltwater wedge
which is formed by density gradient of seawater andfreshwater [1]. Dumping sites and chemical fromindustrial wastes also can be sources of contaminantleakage to the groundwater. In a case of dense nonaqueous phase liquids (NAPLs) leaking from thesesites move downward straightly and disperse widelyto the flow. In contrast, light NAPLs will cause thesump on the water table [2].
In some cases, density-driven flow also associateswith temperature difference. Holzbecher [3] showedthat flow instability emerges under specificconditions. When cold water intrudes from groundsurface into shallow groundwater, the groundwaterflow rate and the Rayleigh number were found bynumerical experiments to be conditions for the onset
and decay of thermal convection phenomena [4].
Momii [5] reported that saltwater density effectcauses oscillatory phenomena of vertical intruding
246

SEE - Kyoto, Japan, Nov.18-20, 2020

where I is an identity matrix, D m is the molecular
diffusion coefficient, and α L and α T are longitudinal
and transverse dispersion lengths, respectively.
In this study, the stream function is used todescribe flow for 2D situation with,the stability of groundwater flow with a heat source.
In the equation of the mixed convection number,groundwater flow velocity is included explicitly,
which implies flow instability depends on the flow
velocity. In a case of instability caused by saltwater
concentration, the dispersion depends on the flow
velocity [7], and hence flow velocity needs to beconsidered in the Rayleigh number, in which flow
velocity is not included normally. For this reason, thisstudy is intended to propose a new Rayleigh number
taking flow velocity into consideration explicitly andverify the availability of it through laboratory
experiments.

∂ψ


, w)
( u=

T

 ∂z

∂ψ 

T


∂x 

,−

(5)

By substituting Eq. (5) into Eq. (2) after curl isapplied to the both sides of Eq. (2), the governing
equation for the stream function is derived.
∂  µ ∂ψ 

∂  µ ∂ψ 
∂ρ
g

+ 
=
∂x  κ ∂x  ∂z  κ ∂z ∂x

GOVERNING EQUATIONS
The governing equations for groundwater flow
and solute transport are based on the one fromHolzbecher [1]. The domain is considered to be a
vertical two-dimensional coordinate system where x
and z are the horizontal and vertically upward axes,
respectively.
The mass balance of fluid with variable density inporous media under assumptions that water isincompressible, the aquifer is rigid, and there is anabsence of sources or sinks, is represented as follows
when the Oberbeck-Boussinesq approximation isapplied to:Here, it is assumed that the domain ishomogeneous, and the retardation factor R is unit.
To evaluate the Rayleigh number Ra, thedimensionless forms of the governing equations forgroundwater flow with variable density is derived bysubstituting the following dimensionless variables
into Eqs. (6) and (3): X = x/H, Z = z/H, Ψ = ψ/D 0 , U= uH/D 0 , W = uH/D 0 , and T = tH2/D 0 .
∂∂X∂C∇ ⋅ v =0

(1)

∂T

v =−

µ

∂t

∂Ψ

+

∂X

(2)

c

∇=
X

vv
v

(3)

(7)

X

(8)

X

(

∂

f

min

∂
,

ρ =ρ + ∆ρ C , Ra
,=

min

−c

∂X ∂Z

)

∆ρ gκ H

(9)

µD

0

T

V
,=

(U , W =
)
T

(

∂Ψ
∂Z

,−

∂Ψ
∂X

)

T

(10)

density between saltwater ( ρ s = ρ (1) ) andfreshwater ( ρ f =ρ (0) ); 𝑐𝑐max and 𝑐𝑐min are themaximum and minimum salinity in the domain,
respectively. Regarding the representative dispersion
coefficient D 0 , it is defined as follows to evaluate
whether the intruding saltwater shows instability ornot, using the basal groundwater velocity v 0 .

T+ αT v I

∂C
=
Ra
∂X

where X and Z are the dimensionless coordinates forx and z, respectively; Ψ is the dimensionless stream
function; Ra is the Rayleigh number; U and W are thedimensionless velocities; C is the dimensionless(normalized) salinity; H is the representative length,
which is given as the height of an objective domain in
Holzbecher [1], but is given as the vertical thicknessof the saltwater thickness here; the saltwater densityρ =ρ (C ) is assumed to be proportional to C, where𝜌𝜌𝑓𝑓 is freshwater density, ∆𝜌𝜌 is the difference of

where ϕ is the porosity of the porous media, t is thetime, R is the retardation factor, D is the dispersion
tensor, and c is the salinity.
The dispersion tensor is implemented according
to Scheidegger’s law,
φ D= φ Dm I + (α L − α T )

∂Z

0

max

= ∇ ⋅ (φ D∇c ) − ∇ ⋅ ( vc )

∂Ψ

φ

D∇ C  − V ⋅ ∇ C
D


X

c−c

( ∇p + ρ g ∇z )∂∂Z

= ∇ ⋅

C=

where ρ is the density of the fluid, v = (u, w)T is theDarcy velocity of the fluid, u and w are vector
components of x and z directions, respectively, κ isthe intrinsic permeability tensor of the porous
medium, μ is the viscosity of the fluid, p is thepressure, g is the gravitational acceleration. Here, theporous medium is assumed to be isotropic, and κ
becomes a scalar κ.
The transport equation for salinity simplified by
Oberbeck-Boussinesq approximation is represented
as follows,∂ (φ Rc )( ) ( )

withwith generalized Darcy’s Law
κ

(6)

(4)

247

SEE - Kyoto, Japan, Nov.18-20, 2020

D0 = α L v 0

Figure 2 shows the schematic diagram of theexperimental setup. The experiments are conducted ina flow tank with internal dimensions of 165 cm
length, 54 cm height, and 5 cm width shown in Fig.
3. To model the aquifer, the flow tank is filled withhomogeneous glass beads with a diameter of 2.0 mm
up to the height of about 45 cm. Freshwater isreleased to flow from left side to the right side, andsaltwater intrudes via the saltwater tank which isplaced on the upstream of the top of the flow tank.
The water levels in the left and right sections, which
are separated by perforated acrylic sheets with wire
nets, are controlled by the adjustable drainage pipe ineach section.

(11)

By using Eq. (11) and variables Eq. (12), the Rayleighnumber is represented in this study as follows.
=
K

Ra =

ρ f gκ
ρs
, γ
=
µ
ρf
(γ − 1) KH

α L v0(12)(13)

where K is the hydraulic conductivity of the domain,and γ is the specific weight.
Boundary and Initial Conditions
The boundary conditions for the groundwaterflow and the salt transport governed by Eqs. (6) and(3), respectively, are provided in Figure 1. In thisstudy, unconfined groundwater flow is considered.
The objective domain is the one under water, and thesaltwater intrusion zone is on the upstream of the top
boundary. Respective to the stream function, the top
and bottom are set as Dirichlet-type boundary
condition whereas the both sides of the domain are set
as Neumann-type. The basal flow rate and thesaltwater intrusion rate are represented by ψ top andψ ent , respectively.

Fig. 2The saltwater tank is packed with 1 mm glass
beads and its bottom is perforated and covered with
non-woven fabric. Saltwater is pumped from a tankthat contains commercial salt solution dyed with red
food color (New Coccine Red No. 102, Kiriya
Chemical), whose concentration is set as 1.5 g per 3
L according to Luyun Jr. [11]. The behavior ofsaltwater intrusion is monitored by two fixed cameras
to photograph every fixed time step. One camera isused to take fixed photos and another one is used totake to whole video of the experiments.

Fig. 1 Boundary conditions of the objective domain.
Constant values ψ top and ψ top +ψ ent are given to
the top except for the saltwater intrusion zone, and thefollowing function is given to saltwater intrusion zone.

ψ top0 < x < x0
x − x0*( x )  ψ top +=ψ ψ=ψ ent x0 < x < x1x
1 − x0ψ + ψ
x1 < x < x2
ent
 top

Schematic diagram of experimental setup.

(14)

Groundwater flows freely across both side boundaries
not for the top and bottom. As an initial condition for
stream function, a flow without any salt intrusion is
given such that c = 0.

Fig. 3

Appearance of the flow tank.

Experimental Setting
The Rayleigh number Ra can be calculated using Eq.
(13) with the hydraulic conductivity K, which isestimated from measured flow volume Q f as follows.

LABORATORY EXPERIMENTS
Laboratory Approach

248

SEE - Kyoto, Japan, Nov.18-20, 2020

K =2Q f Lb(2∆hh0 - ∆h )2

1.006, 1.012, 1.024, 1.048 (with Ra = 20.30, 40.61,
81.21, 162.42), and ∆h = 2.5 cm, respectively.
Figure 4 (b1) shows saltwater intrusion under alow salinity with γ = 1.006. It is found from this figurethat intruding saltwater almost not downward but inthe right direction. It is observed that saltwater didn’t
develop any more pattern after sufficiently long-timeelapse, although some disturbances were observed
when the Rayleigh number is lower than thresholdvalue. On the other hand, from Figs. 4 (b2) – (b4)which are corresponding to γ equal to 1.012, 1.024
and 1.048, respectively, it indicates that saltwater
intrusion visually developed with oscillation likeType II of numerical experiments by Kawabata [5].
From the beginning of intrusion, the saltwater
gradually moved downward and started to develop an
oscillatory flow after 15 minutes until the saltwater inthe tank became empty. These evidences show thatsalinity distributions get to an unsteady state in a highenough Rayleigh number regime in which Ra exceeds
the threshold value. Figure 4 (b4) displays the salinity
distribution under a high saltwater density with γ =1.048 and also exhibits in a relatively high Rayleighnumber. It is visible that the intruding saltwateroriginally penetrated almost downward direction,then after 10 minutes it became oscillating until
saltwater reach the bottom and to the rightest end of
the tank. However, after long-time elapse, theintruding pattern stopped oscillate and it becamealmost steady convergent at the end. This is because
no freshwater exists under the saltwater after thesaltwater reached the bottom. To summarize, all the
results in Figs. 4 (b1) – (b4) reveal that in a mild flow
regime of the basal groundwater in which ∆h = 2.5
cm, salinity varies with oscillation in case of highRayleigh number (Ra > 4π 2 ≅ 39.48) whereas it
does without oscillation in case of low Rayleighnumber (Ra < 39.48). It is considered that theoscillation occurs as a bifurcation with increase of theRayleigh number.

(15)

where L is the length of the flow tank, b is the widthof the tank, h 0 is the water level at the upstream end,and ∆h is the water level difference of the upstream
and downstream ends. The dispersion length α L isgiven as 2 mm according to Luyun [10].
Experimental condition to be specified for theverification of oscillation occurrence in the case of
relatively high Rayleigh numbers, four kinds ofrelative saltwater density are prepared: γ=ρ s /ρ f =1.006, 1.012, 1.024, 1.048. These conditions will
yield the values of Rayleigh number corresponding tochanges in the basal groundwater flow rate. In eachexperiment, the difference of water level between theleft and right sections ∆h are adjusted as 1.5, 2.5, and3.5 cm in each saltwater density using the drainage
pipes in order to make a hydraulic gradient. The
upstream water level is fixed as 40 cm in allconditions. The groundwater rate Q f from flow tankis measured in each experiment to calculate the valueof the hydraulic conductivity K and the basal
groundwater velocity v 0 . Saltwater intrusion rate Q s
is decided based on the measured groundwater rate tokeep the same shape of streamlines throughexperimental conditions. To do so, the saltwater
intrusion rate is set as 1/20 of the measured
groundwater rate.
EXPERIMENTAL RESULTS
Essentially, the Rayleigh number varies
depending on the location in the experimental tank as
defined in Eq. (9) or (13), because H and v 0 varyalong flow down. From some preliminary
experiments, it was observed that oscillatory flow
began when the vertical thickness of the saltwaterplume was about 15 cm, which is also shown in thefollowing figures. Therefore, H and |v 0 | are given as
15 cm and Q f /(h 0 b), respectively, in this study toevaluate a representative Ra in experimental
conditions.

P

Cases of ∆h = 1.5 cm and 3.5 cm
The Rayleigh number causes different saltwater
intrusion patterns as discussed in the previous section.
In this section, we will discuss on the consequencesof changing the horizontal flow rate of groundwaterfrom lower to higher flow rates.
Figures 4 (a1) – (a4) shows the result of saltwater
intrusion by changing to a lower horizontal flow rate
at which the difference of water level between bothsides of the tank is ∆h = 1.5 cm. The resulted Rayleighnumber corresponding to each specific weight ofsaltwater are Ra = 39.74, 79.48, 158.97, and 317.93,
respectively. From Fig. 4 (a1), it is found that salinity
distribution almost flow horizontally; however, its
streamlines is slightly downward than in case of ∆h =2.5 cm. Additionally, since the Ra = 39.74, which isnearly approach to the threshold value, the intruding

A Case of ∆h = 2.5 cm
From the numerical results found by Kawabata [5],the patterns of intruding saltwater were classified into
3 types: rapid convergence without oscillation (TypeI), oscillation (Type II), and oscillatory convergence(Type III). According to the classical analysis ofHolzbecher [1], it is indicated that the saline
conduction state becomes unstable if Ra > 4 π 2,
which is a threshold of stability, or occurrence ofdensity-driven flow, and which is applicable to asaltwater case. In the current study, Figs. 4 (b1)through (b4) shows the photography results of the
behaviors of saltwater intrusion in the cases of γ =249

SEE - Kyoto, Japan, Nov.18-20, 2020

saltwater seems to have a small degree of oscillations
after a long-time elapse. When the Ra increase totwice, Fig. 5 (a2) is observed to disperse steeper thanprevious case, and it started to oscillate after 15 minof intrusion. This case is similar to the case in Fig. 4(b3) which is identified as Type II pattern. On theother hand, saltwater intrusion converges to a steadystate when the Ra is increase to 158.97 and 317.93 asshown in Figs. 5 (a3) and (a4). This occurrence isthought to be the same reason with the case of ∆h =2.5 cm and Ra = 162.42. However, since thegroundwater flow rate is slower than the case of ∆h =2.5 cm, and which leads to the higher Rayleighnumbers, it is obvious that salinity is finallyFig. 4submerged to the bottom of the tank. It is investigatedfrom these results that the low flow of the basal
groundwater makes the Rayleigh number high, andthat the oscillatory flow occurs even in low
concentration of saltwater. Figures 4 (c1) – (c4)shows the behavior of intruding salinity when thebasal groundwater flow rate is increased higher bychanging the difference of water level up to 3.5 cm.
As the horizontal flow rate increases while keeping
constant the specific weight of saltwater, there is a
proportional decrease of the Rayleigh number. The
resulting Ra are 14.59, 29.19, 58.37, and 116.74,
respectively.

Photography of time variation of salinity distribution
250

SEE - Kyoto, Japan, Nov.18-20, 2020(a1) – (a4): ∆h = 1.5 cm, (b1) – (b4): ∆h = 2.5 cm, (c1) – (c4): ∆h = 3.5 cm
From Figs. 4 (c1) – (c2), it is observed that saline
Analysis on the Simultaneous Seepage of Porewater moved almost horizontally to the right exit of
Water and Oils in Soils, Proceeding of thethe tank when the flow is in the relatively low
School of Engineering of Tokai University,
Rayleigh number regime. This can be inferred that
2012, pp. 217-224.
impact of less dense saltwater intrusion is[3] Holzbecher E. and Yusa Y., Numericalconsiderably not significant in the high basal
Experiments on Free and Forced Convection in
groundwater flow. However, the oscillatory pattern
Porous Media. International Journal of Heat andcan be found when the Rayleigh number is higher
Mass Transfer, Vol. 38, Issue 11, 1994,
than the threshold. Figure 4 (c3) indicates an
pp.2109-2115.
oscillatory flow of salinity distribution which is[4] Takeuchi J., Kawabata M., and Fujihara M.,
similar to the cases of Figs. 4 (a1), (b2), and (b3).
Numerical Analysis on the Occurrence ofFurthermore, the oscillatory convergence pattern is
Thermal Convection in Flowing Shallow
expected from Fig. 4 (c4) in a case of the relatively
Groundwater,
International
Journalofhigh Rayleigh number and when time elapse is long
GEOMATE, Vol. 11, Issue 27, 2016, pp. 2688enough.
2694.
[5] Momii, K., Study on Solute Dynamics in
Groundwater and Lake as Agricultural Water
CONCLUSIONSResources. Proceedings of Annual Symposium,
In this study, oscillatory flow behaviors ofApplied Hydraulics Division, JSIDRE, 2013,
vertically saltwater intrusion into horizontally
pp.68-71. (in Japanese)
flowing groundwater are investigated through[6] Kawabata M., Takeuchi J., and Fujihara M.,
laboratory experiments. The proposed RayleighNumerical Analysis of Density-Driven
number which is associated with the saltwater density,
Fluctuation in Groundwater Caused by
the hydraulic conductivity, the height of a domain, theSaltwater Intrusion, Jurnal Teknologi, Vol. 76,
dispersion length, and the basal groundwater flow
No.15, 2015, pp.7-12.
rate was varied to identify the impacts of the density[7] Bear J. and Verruijt A., Chap. 6 Modelingdriven flow to groundwater.
Groundwater Pollution, Modeling Groundwater
From the obtained results, the proposed Rayleigh
Flow and Pollution, D. Reidel Publishingnumber can estimate the occurrence of oscillatory
Company, 1994, pp.153-195.
flow compare to the threshold value without[8] Kawabata M., Analysis and Verification of
considering other parameters separately. The
Density-driven Fluctuation Caused by Saltwaterphotography results showed that the intruding
Intrusion into Groundwater. Master’s Thesis,
saltwater flows down spreading widely because of its
Kyoto University, 2017.
[9] Musuuza J.L., Radu F.A., and Attinger S., The
instability when the Rayleigh number exceeds theeffect of dispersion on the stability of densitythreshold value. It will cause significant impact on thedriven flows in saturated homogeneous porous
downstream.
media, Advances in Water Resources, Vol. 34,
Issue
3, 2011, pp.417-432.
ACKNOWLEDGMENTS[10] Holzbecher E., Chap.10 The Mixed Convection
Number for Porous Media Flow, Emerging
This research was partially funded by Grant-inTechnologies and Techniques in Porous Media,
Aid for Scientific Research(B) JP20H0310.
Ed. Ingham D.B., Bejan A., Mamut E., Kluwer
Academic Publishers, 2003, pp.169-182.
REFERENCES[11] Luyun R.A.Jr., Effects of Subsurface PhysicalBarrier and Artificial Recharge on Seawater[1] Holzbecher E., Modeling Density-Driven Flow
Intrusion in Coastal Aquifers. Doctoralin Porous Media. Springer, 1998, pp. 1-47.
Dissertation, Kagoshima University, 2010.
[2] Tamai Y. and Honma S., Experiments and251

6thInt. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

CHARACTERIZATION OF GROUNDWATER POLLUTION SOURCESBY KRIGING BASED LINKED SIMULATION OPTIMIZATION
Anirban Chakraborty1and Om Prakash1
1

Department of Civil and Environmental Engineering, Indian institute of Technology Patna, Bihta, Patna, India
801106.

ABSTRACT
Often untreated wastes are buried underground as convenient method of disposal. These clandestine disposal
methods are adopted to offset the cost incurred in proper waste management. Though there might be short term
economic gain to the disposer but the long-term impact of such disposal manifests in form of groundwaterpollution, which if left unchecked would potentially pollute the entire aquifer. Any contaminated aquifer
treatment technique requires prior information about the pollutant sources characteristics. Thus, characterizationof unknown groundwater pollution sources becomes imperative in remediation process. The first step involves
the identification of number of sources and their locations. In a clandestine scenario the entire study area istreated as a potential source and the search for the actual source can be extensively rigorous in space and time.
To overcome this challenge a kriging based zoning is adopted to narrow down the search space for the actual
sources in a limited data availability scenario. A comparative analysis of two methods is presented; first method
where only (Simulated Annealing based Linked Simulation Optimization) SALSO is used, and second method
where kriging based zoning plus SALSO is adopted for pollution source characterization. It is found that kriging
method clubbed with SALSO gives significantly better results compared to initial results. A boundary of Indian
Institute of Technology Patna with hypothetical hydro-geological parameters is used to test the developed
method. The location of the pollutant sources is easily identified when a kriging based Simulated Annealing
Linked Simulation Optimization (KSALSO) method is adopted.
Keywords: Linked simulation optimization; Groundwater pollution source identification; Simulated annealing;
Kriging

the release flux histories of groundwater pollution
sources. Linked Simulation Optimization (LSO)
models are very popular in identifying the releasehistories of pollution sources [2]-[5]. Surrogate
models are efficiently used to recover the releasehistories of groundwater pollution sources whenlocations of sources are well known [6]-[7]. Thesemethods are valid for only some simple case studies,
which cannot be used for complex scenarios ofsource identification problems involving clandestine
sources.
There are very few methods which
simultaneously identify the locations and release
flux histories of groundwater pollution sources [8][9]. One of the biggest limitations of these methods
are that these methods assume the location of thesources to be anywhere in the study area, whichmakes these methods computationally expensive.
However, these developed methods fail to yield any
fruitful result when the study area is large and there
is no initial guess about the number of sources andtheir location. In such scenarios the number ofpossibilities to be evaluated in LSO is very large andmay not converge to an optimal solution. [10] used ageo-statistical kriging method to identify the number

INTRODUCTION
Groundwater is one of the most importantsources of drinking in many parts of the world.
Groundwater pollution is the biggest threat tosustainability of groundwater resources and evenmore difficult to detect. Clandestine dumping of
toxic wastes underground to offset the cost incurredin proper waste management has further complicatedthe scenario. Finding such sources of pollution ishighly challenging due to their untracebility.
Presences of such pollutant sources are unknown
until pollution is first detected in some sparsely
located wells. In designing an effective remediation
strategy for these polluted aquifers, accurate
knowledge of pollution source characteristics interms of their numbers, their locations with release
flux histories are most vital. It may be possible todecipher the number of sources from the pattern ofland use, but the greatest challenge is to estimate thehistory of release flux and location of these pollution
sources.
Various methods have been developed to identify
the unknown pollution source characteristics. [1]developed a nonlinear regression model to identify
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SEE - Kyoto, Japan, Nov.18-20, 2020

sink mixing in groundwater system;
In LSO approach, the residual error between
simulated and observed pollutant concentration
values are minimized in Eq. (3). Simulation model
replicates flow and pollutant transport ingroundwater system [10]. The unknown LRF areconsidered as explicit unknown decision variables.
For different combinations of source numbers,
locations and fluxes, simulation model is solved
iteratively, such that the optimal solution represents
the best estimate of the unknown decision variables.
SA is used to solve the optimization problem. In
LSO method, location and release flux histories(LRF) of pollutant sources are estimated byformulating optimization problem.

of sources and their locations using pollutant
concentration measurement from a sequentiallydesigned monitoring network.
In order to reduce the computational burden andaccurately identify groundwater pollution sources, a
KSALSO methodology is proposed. This
interpolation technique termed as kriging method isapplied to determine the pollutant concentration
profile over the study area. This concentration
profile gives an overview of location of pollutant
sources which reduces the area of search. Thereafter,
LSO method is used after kriging interpolation forsource identification. Here, Simulated Annealing(SA) is used as optimization algorithm. A
comparative study is also presented between thedeveloped KSALSO model and conventional SA
based SALSO technique in identifying unknown
source characteristics.

𝑘𝑘𝑘𝑘
𝐹𝐹 = 𝑀𝑀𝑀𝑀𝑀𝑀 ∑41 ∑61(𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖− 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖)(3)

Subjected to,
METHODOLOGY

𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ≤ 𝐿𝐿 ≤ 𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ;In order to estimate Location and Release Flux
histories (LRF) of these pollutant sources, twodifferent pathways are adopted. In the first caseconventional SALSO is used. Conventional SALSO
was mostly used previously to identify the release
flux histories of pollutant sources. In the current
study, SALSO methods are used to identify both
location and release flux histories. Here, a newly
developed KSALSO method is implemented for
simultaneous identification of LRF of pollutant
sources. The search space for the sources isnarrowed down by kriging based pre-processing to
reduce the computational budget.

In Eq. (3) objective function is minimized at𝑘𝑘
is theany arbitrary location iob and time k; 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖
𝑘𝑘
observed concentration and 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖 is the simulated
concentration at measurement time step k at location𝑘𝑘
is obtained from sampling aniob; 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖
𝑘𝑘
observation well; and ; 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖
is obtained from Eq.
(5);
𝑘𝑘=𝑓𝑓(𝐿𝐿, 𝐹𝐹, 𝐻𝐻)
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖𝑖𝑖𝑖𝑖

Linked Simulation Optimization (LSO) is widelyused in groundwater pollution source identification
problems. The proposed methodology uses metaheuristic optimization algorithm clubbed with asimulation model (Eq.(1) & Eq.(2)) to reconstruct
LRF of pollutant sources.
𝜕𝜕ℎ
𝜕𝜕𝜕𝜕

(1)

Eq. (1) represents groundwater flow equation and isbased on Darcy’s law. The hydraulic head is denotedby h; 𝑘𝑘𝑖𝑖 is the hydraulic conductivity in i th direction
𝑅𝑅ℎ is the storitivity of the aquifer; t is the elapsed
time.
𝜕𝜕𝜕𝜕
𝜕𝜕𝜕𝜕

=𝐷𝐷𝑖𝑖,𝑗𝑗 ∇2 𝐶𝐶 −

𝜕𝜕ℎ
𝜕𝜕𝜕𝜕

∇𝑐𝑐 + 𝐶𝐶𝑠𝑠 𝑞𝑞𝑠𝑠

Description of Kriging
Kriging is popular interpolation technique, which
is applied in the developed methodology to identify
the groundwater pollution source locations to reducethe computational burden in identifying the LRF. In
geo-statistics, kriging or Gaussian regression isoriginally an interpolation procedure for which theinterpolated values are determined by a Gaussianmechanism controlled by prior covariance [8].
Application of Geo-statistics is very common in thefield of pollution [9]. Kriging as a tool is often used(2)

Eq.(2) simulates the transport of pollutant ingroundwater system. C represents the concentrationof pollutant sources; 𝐷𝐷𝑖𝑖,𝑗𝑗 is the disversivity
coefficient at i, j; the term 𝐶𝐶𝑠𝑠 𝑞𝑞𝑠𝑠 represents the source(5)

L is the location (grid) of pollutant sources and it
depends on the study area and constrained by Eq. (4),
F is the release concentration of the sources and H
represents the hydrogeological characteristics of thepolluted aquifer study area. In the optimization
formulation L and F are the decision variables. The
SALSO method links the simulation model to the
SA optimization algorithm. SALSO approach
incorporates the groundwater flow and pollutant
transport simulation models as set of binding
constraints in the optimization formulation which issolved iteratively.

Linked Simulation-Optimization𝑘𝑘𝑖𝑖 ∇2 ℎ + 𝑅𝑅ℎ = 𝑆𝑆𝑠𝑠

(4)

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SEE - Kyoto, Japan, Nov.18-20, 2020

to determine the quality of groundwater with thehelp of intensity profile. The approach is commonlyused in the spatial analysis context and in machine
experiments.
Generally, L values of the pollutant source
depend on the size of the study area chosen. If thestudy area is large, the variable L increases thecomputational burden as more number of source
combination scenarios need to be evaluated to findthe optimal result. In order to avoid the excessive
load in computing, Ordinary Kriging (OK) is
incorporated as a preprocessor. This preprocessor
tool is used to reduce the load on optimization. The
OK equation is stated in Eq. (6).
𝐺𝐺(𝐿𝐿0 ) = 𝐹𝐹(𝐿𝐿0 ) + 𝜇𝜇

given in Fig. 1.

Start

Taking concentration measurement from wells

Perform Kriging over the study area

(6)
Perform Kriging based Zoning to reduce potential sourcesl ti

𝐺𝐺(𝐿𝐿0 ) is the concentration obtained by OK; F(L 0 ) is
the unknown concentration value interpreted by
combined neighborhood function at the location 𝐿𝐿0 ;and the 𝜇𝜇 is the standard normalized error occurredat same location (Eq. 6).

Perform SALSO model for identifying LRF

Kriging Based Zoning of KSALSO Method

End

The proposed methodology (KSALSO) uses two
step processes. In the 1st step, pollutant
concentration data from monitoring wells arecollected. From these concentration data, a kriging
interpolation is carried out to generate concentration
profile over the entire study area, which is further
used as input for the source identification model. In
this 2nd step, higher concentration region isdesignated as potential source location zones (Eq. 7)
for LSO model. If,
𝐺𝐺 𝑚𝑚𝑚𝑚𝑚𝑚 (𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ) ≫ 𝐺𝐺 𝑚𝑚𝑚𝑚𝑚𝑚 (𝐿𝐿0 );(7)

𝐿𝐿𝑇𝑇𝑚𝑚𝑚𝑚𝑚𝑚 ≤ 𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ;(8)

𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ≤ 𝐿𝐿 ≤ 𝐿𝐿𝑇𝑇𝑚𝑚𝑚𝑚𝑚𝑚 ;(9)Figure 1: Flowchart of KSALSOPERFORMANCE EVALUATION
Table 1: Hydro-geological parameters of study area
Name of the parameter
Length of the area
Breadth of the area
Thickness of the area
Length of the grid
Breadth of the grid
Thickness of the grid
Hydraulic conductivity
Horizontal anisotropy
Size of stress period
Porosity
Source grid
Well Number

𝐺𝐺 𝑚𝑚𝑚𝑚𝑚𝑚 (𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 ) is the maximum concentration
obtained after creating the variogram at location
𝐿𝐿𝑚𝑚𝑚𝑚𝑚𝑚 , L 0 is reduced potential grid after Kriging
based zoning; L 0 is not considered as a potential
source location in LSO. After OK the 𝐿𝐿𝑇𝑇𝑚𝑚𝑚𝑚𝑚𝑚 variable
is deduced. 𝐿𝐿𝑇𝑇𝑚𝑚𝑚𝑚𝑚𝑚 is maximum length of study areaof KSALSO method;

Unit
m
m
m
m
m
m
m/s
Unit less
Days
Unit less
-

Value
5410
3628
30.6
50
50
30.5
21.34
0.8
365
0.3
(16,7), (20,6)
16

In order to test the performance of the developed
methodology, site of Indian Institute of Technology
Patna is chosen. The location of the site is 25.5357°
N, 84.8512° E (Fig. 2). It is assumed that there are
two pollutant sources and there are sixteen points
where the concentration data is recorded. The hydrogeological parameters of the study area are given intable 1. It is assumed that all these sixteen
observation locations are impacted by pollution
coming from two point sources. It is assumed thatEq. (4) is replaced by Eq. (8) to forms Eq. (9).

These variable 𝐿𝐿𝑇𝑇𝑚𝑚𝑚𝑚𝑚𝑚 become the final constraintof the optimization. Thus, the search space isreduced from entire study area to smaller region for
actual source locations in LSO. The schematic chart
representing the flow of developed KSALSO is254

SEE - Kyoto, Japan, Nov.18-20, 2020

pollutant is conservative, and the sources are active
for seven stress periods. Each stress period is of one
year. Source fluxes remain constant throughout eachstress periods.
A three-dimensional unsteady transient pollutant
transport model was developed to estimate the fate
and transport behavior of polluted aquifer. It was
assumed that the initial concentration is zero. The
simulation is performed with the implicit assumptionthat the starting time of these sources are known. In
the LSO model SA is used as optimization algorithm
to estimate the source flux release history and source
locationsusing
pollutantconcentration
measurements from few monitoring locations. The
fundamental
idea
of
SA
comes
from

thermodynamics. Groundwater pollution source
identification problems are categorized as
multivariate optimization problem. The non-linearity
phenomenon makes the solution more complex. The
formulation of such complex problem has multiple
local optima. SA works efficiently in getting out
from this trap of local optima. Using hill-climbing
moves to avoid local optima makes SA is effective
in solving problems of non-convex optimization.
The simplicity of application to the complex
problem and convergence to an optimum global
solution extends the competency to solve the illposed inverse problems, as in the case with the
problem.

Figure 2: Plan view and interpolated concentration in the study area
From Fig. 2, the likelihood of sources to bepresent are in the higher concentration zone which isdenoted by deep blue color. By kriging, the potential
source locations are reduced from 108 active grids to
36 active grids (refer: table 2). Thereafter, SALSO
model is applied to identify the sourcescharacteristics in the limited search area. Basically,
Kriging based zoning method helps SALSO method
to perform in reduced search area for location ofpollutant sources, which invariably decreases theplausible number of source characters’ combinations
to be evaluated in the SA optimization algorithm insearch for the optimal LRF.

Table 2: Comparison of optimization parameters
between SALSO and KSALSO
MethodSALSO
KSALSO

Number ofdecisionvariables
18
18

L

108
36

Source location
combinations forsearch5778
630

In this study area, the maximum number ofsources are two. Total number of stress period foreach sources are seven. So, the number of variables
to be estimated is eighteen (2 × 2 + 7 × 2). The
description of and L variable is given in table 2.

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SEE - Kyoto, Japan, Nov.18-20, 2020second source. The location is expressed in terms ofgrids.
The release flux histories are also presented in
the Fig. 3, where X dimension represents the stressperiod and Y dimension represent the release historyof each sources. It is observed from Fig. 3 that
KSALSO method give better recovery of release
flux of the identified sources compared to SALSO.

RESULTS AND DISCUSSIONS
The identified source characteristics result isgiven in table 3 and Fig. 3. In case of KSALSO, outof two sources, location of one source matches
exactly with the actual location of the source, andthe location of other sources is slightly shifted (onegrid shift) from the actual source location of theActualFlux (kg/d)

6000

KSALSO

SALSO

3000

0
S11 S12 S13 S14 S15 S16 S17

S21 S22 S23 S24 S25 S26 S27

Figure 3: Release flux histories of identified sources
method KSALSO, and the conventional method
SALSO are analyzed to estimate the efficiency inusing kriging for potential source location zoning.
From the estimates it is seen that performance of
KSALSO model is superior in efficiency andreduces the computational burden by 97.40%.
By comparing the breakthrough curves, theaccuracy of the estimated source fluxes using both
KSALSO and SALSO methodology is examined in
Fig 4. Estimated source flux values for producing
the breakthrough curves are used in a forward
simulation for both KSALSO and SALSO method.
The concentration versus observation location is
generated at 1200 days after pollution started. Thosevalues are compared with the actual concentration atsame time and it is found that KSALSO gives
greater accuracy in recovery of breakthrough curvethan that of SALSO method.

A comparative study is also presented between
developed KSALSO method and conventional
SALSO methods. From the table 3, it is obvious that
KSALSO give significantly superior result than thatof SALSO in terms of identifying location of thepollutant sources. KSALSO method converged withless number of iteration compared to SALSO
method. That is why elapsed time for completing
KSALSO method is also lower than that of SALSO
method.
Table 3: Characteristics of identified sources
Characteristics
Co-ordinates (S1)
Co-ordinates (S2)Time taken (sec)Actual(16,7)(20,6)-KSALSO(16,7)(21,6)
31294

SALSO(12,8)(18,8)
591432Computational time taken by the developed
t=1200 d
ActualKSALSOSALSOConc (mg/l)

90

45

0
0

4

8

Observation point

Figure 5: Breakthrough curve comparison

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which is a major advantage of developed KSALSO
method. One of the major challenges in groundwaterpollution is to identify the locations of pollution
sources. The proposed methodology is able to relax
this difficulty. The number of sources is not taken as
unknown explicit variable in this developed
methodology.

CONCLUSIONSKSALSO is significantly more efficient than
SALSO in identifying the sources characteristics.
The location of each sources are identified with 90%
precision. The recovery of flux histories are alsosatisfactory (87% precision). KSALSO method
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Surrogate Model Together with Four
Heuristic
Optimization
Algorithms." Advancesin
Water
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[8] Sophia, L., & Bhattacharjya, R. K. (2020).
A GA Based Iterative Model for
Identification of Unknown Groundwater
Pollution Sources Considering Noisy Data.
In Nature-Inspired
MethodsforMetaheuristics Optimization (pp. 303-321).
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[9] Ayvaz, M. T. (2010). A linked simulation–
optimization model for solving the
unknown groundwater pollution source
identification
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optimal monitoring network design anditerative spatial estimation of pollutant
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groundwaterpollution
sourcelocations. Environmental monitoring andassessment, 185(7), 5611-5626.
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systems. SS Papadopoulos & Associates.

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(1983). Identifying sources of groundwaterpollution: An optimization approach. Water
Resources Research, 19(3), 779-790.
[2] Mahar, P. S., & Datta, B. (2000).
Identification of pollution sources intransientgroundwater
systems. Water
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V. (2018). Identification of groundwatercontamination sources using mesh-free
RPC simulation and particle swarm
optimization. Water
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management, 32(4), 1517-1538.
[4] Prakash, O., & Datta, B. (2014).
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groundwaterpollution
sourcesincorporating genetic programming–based
monitoring. JournalofHydrologic
Engineering, 19(11), 04014025.
[5] Prakash, O., & Datta, B. (2015). Optimal
characterization of pollutant sources incontaminated aquifers by integrating
sequential-monitoring-network design andsource identification: methodology and an
application in Australia. Hydrogeology
Journal, 23(6), 1089-1107.
[6] Xing, Z.X., Qu, R.Z., Zhao, Y., Fu, Q. , Ji,
Y. ,Lu, W.X , 2019. Identifying therelease history of a groundwater pollution257

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

THE KUMAMOTO EARTHQUAKE’S CREATIVE RECONSTRUCTIONEFFORT LED BY A DIVERSE RANGE OF ORGANIZATIONS
Reiko MACHIDA1, Eri OTSU2 , Hiroko SHIMA2, Hitomi YaGI2 ,Katusunori MOCHIZUKI3
Junya MACHIDA4,Hijiri SHIMOJIMA1 and Naomasa HONDA1
1 Department of Regional Regeneration Science, Tokyo University of Agriculture, Japan
2 Institute of GIAHS Life Aso, Japan, 3 Institute of YUHUIZUM, Japan
4 Co. Environment Design, Japan
ABSTRACTThis study analyzed the creative reconstruction efforts led by a diverse range of organizations from the
Kumamoto earthquake in the Aso region in chronological order. In addition, this study was aimed to clarify theefforts of the residents and communities of the Aso region ranging from disaster relief to tourism and various
forms of exchange. These efforts utilized the unique human networks and organizations during the period for
ensuring survival (10 days after the earthquake) and the period for securing living conditions (1 month after theearthquake) and also provided quick support where the government could not reach. Furthermore, we clarified
how the unique efforts undertaken by each subject has made it easier to continue the relief effort and how they
developed into tourism, exchange and disaster prevention education programs reviewing local communities
Keywords: Kumamoto Earthquake, Aso, reconstruction, tourism,

so that it would lead to further development in the
future.
Learning from the Great East Japan Earthquake,
Yamakawa (2018) [3]. points out that "Build Back
Better" is important not only as infrastructuredevelopment, but also as support for the affected
people and the local communities.
According to the overview of "Build Back Better"of the Great East Japan Earthquake, which supported
the affected people and local communities in Minamisanriku Town, Miyagi Prefecture, it has been reported
that the network of people, organizations, and regions
before the earthquake had transformed into
supporting the victims and developing tourism[4].. In
Miyako City, Iwate Prefecture, various forms of
tourism utilizing resources that will remain in theregion after the disaster have led to regional
revitalization[5]. In addition, visitors to the Sanriku
Reconstruction National Park Tanesashi Coast
Michinoku Shiokaze Trail have been effectively
increasing their degrees of attachment to the area andtheir intentions to revisit thanks to their interactions
with local residents[6]. There has also been raised
awareness and formulations of networks throughvolunteer tourism to the disaster-stricken areas. Even
more importantly, new leaders of the regional
development are being trained through thesereconstruction activities.
During "Build Back Better", the creative recovery
effort a diverse group of actors which included theGrassland Restoration Committee, grasslandconservation volunteer groups, accommodation
providers and residents strove to provide disaster
relief to the victims and to revive the local community
using the preexisting networks.

INTRODUCTION
The Aso area is located in the northwestern partof Kyushu. The main topographic feature of Aso is
the huge caldera which was created by four volcanic
eruptions with pyroclastic flows. The vast grassland
landscape spreads over the central cone and the top of
the caldera. In Japan, the designation of nationalparks started in 1929 and 5 years later Aso wasdesignated as a national park in 1934.The grasslandsof Aso were certified as Globally Important
Agricultural Heritage Systems (GIAHS) in 2013, andthey were also certified as Geoparks in 2014. The
grasslands of Aso have been managed by local
agricultural activities such as controlled burning,mowing and pasturage.
Tourism is one of the main industries of the Aso
region. The number of tourists who visited the Asoarea in 2012 was 16,559,613, which was the highest
number in the whole of Kumamoto prefecture[1].
The Kumamoto Earthquake struck the Aso area ofKumamoto Prefecture on April, 14 and April 16 in
2016, killing at least 20 people. The earthquake witha Magnitude of 7.3 triggered a sediment disaster inthe mountain slope. The sediment disaster was further
aggravated by the subsequent torrential rainfalls (1925, June 2016). The sediment disaster caused groundcracks and sediment movement cracks across thegrasslands. As a result, road and rail transportation
was shut down. Also, some tourist facilities wereclosed down since the hot springs ran dry.
Kumamoto Prefecture formulated a policy for thedisaster recovery called "Build Back Better"[2] which
aimed to not only restore the area to its former
condition, but to rebuild it to a state better than before
258

SEE - Kyoto, Japan, Nov.18-20, 2020

For example, the Grassland Restoration
Committee and the grassland conservation volunteer
group "NPO Aso Greenstock" provided immediate
support to the livestock farmers by repairing thepastures and thereby restoring their livelihoods.
These activities then developed into various touristand exchange projects.
The accommodation facility "Namino Yasuragi
Exchange Center", which provided environmental
education programs before the earthquake, urgently
set up evacuation centers and provided mental carefor infants and their mothers. Once the support
programs were no longer needed, they were turned
into disaster prevention education programs.
In addition, a group of young disaster volunteers
together with local residents have contributed to therevitalization of the community by organizingsightseeing tours for reconstruction and opening acommunity cafe (GIAHS Cafe) that also functions asa shelter.
The supporting measures of "Build Back Better"
were split into categories based on time periods suchas the time to secure survival (10 days after thedisaster), the time to secure living conditions (onemonth after the disaster), the time to secure livelihood(three months from the time of the disaster), and thetime until the resumption of business activities[7].
The purpose of this study was to analyze thesequence of efforts of the local residents,
communities, organizations from the immediate
support of the victims to the reconstruction efforts
through tourism and exchange.

METHODThe local residents were able to overcome after
the disaster by the reconstruction assistance from thegrassland conservation volunteers, and support for
infants form exchange facilities. In addition, the local
residents succeeded in the reconstruction andrevitalization of the local community through thereconstruction assistance form divers range oforganizations and the collaboration between the local
residents and the Kumamoto earthquake volunteers.

Aso Green Stock
Namino Yasuragi Exchange Center
The Grassland Restoration

Grassland
GIAHS Cafe

Crack area
Sediment
movemenFig.1 Research Area
Table 1 The interview survey of subsequent creative reconstruction effort
Interviewee
The Grassland Restoration
Committee

Context
Pre-earthquake activities
Various members
Discussions for restoration(livestock farmer, government,
and conservation of thevolunteers and academic
grassland
expert)Creative reconstruction effort
The disaster support forlivestock farmer①The disaster support for
Support the grassland
maintenance tasks such as the livestock farmer
controlled burning②Plan of sightseeing tours

Aso Green StockNPO

Namino Yasuragi Exchange
Cente

Accommodation and training Providing environmental
facility
education programs

A shelter for mothers with
infants and toddlers.
①Opening a community cafe

GIAHS CAFÉInhabitant

Earthquake volunteer

that also functions as a shelter②Plan of a restaurant bus① Participation as a vegetable

GIAHS CAFÉInhabitant

Vegetable pastry chef inanother city259

sweets pâtissier in a "restaurant
bus②Management of GIAHS Café

SEE - Kyoto, Japan, Nov.18-20, 2020

By clarifying the reconstruction assistance of theorganizations that played a leading role in creative
reconstruction in chronological order using the timeframes, it is possible to clarify the efforts ofreconstruction support from the immediate supportof the victims to the reconstruction efforts throughtourism and exchange.
This study conducted the interview survey with
the Grassland Restoration Committee, the coreleadership group a local collaboration and exchange,
The Aso Green Stock, Namino Yasuaragi Exchange
Center specialties in infant support and urban rural
migrated volunteers to support the revitalization of
local community.
The question topics were as follows: relationshipbetween activities before and after the earthquake,thereconstruction assistance and the implementation
periods following the Kumamoto Earthquake, thesupport activities, methods of information
distribution and funding. The interview surveys wereconducted on May 4, 2017, September 12, andSeptember 13, 2017, and September 8, 2018. In
addition, literature surveys related to thereconstruction from the Kumamoto Earthquake werecarried out using the written reports of Aso Green
Stock and the Grassland Restoration Committee.
This study analyzed the recovery efforts of thegrassland conservation volunteers, the exchange
center, and the collaboration between local residents
and earthquake volunteers in a chronological orderusing the following time frames, on a time seriesbasis: the time to secure survival (10 days after thedisaster), the time to secure living (one month after
the disaster), the time to secure livelihood (threemonths from the time of the disaster), and the time tomake a forecast for the business resume.

Earthquake, the Wild grasslands mainly composed ofNezasa and Susuki plants which have been managed
by controlled burning, mowing and pasturage were
not eligible for the National Disaster Assistance. This
made it difficult for livestock farmers to foresee theresumption of the livestock industry.
Therefore, the Grassland Restoration Committee
conducted an emergency questionnaire to thelivestock farmers on the disaster support,
immediately after the Kumamoto Earthquake[8].
On June 15, about two months after theearthquake the Grassland Restoration Committee has
restored a pasturage road in Nishimura village, which
was damaged by surface ruptures. On June 17
damaged water wells, feeders and farm fences were
repaired or replaced.
Three months after the Kumamoto Earthquake, on
July 19 new water tanks were installed in thegrasslands of Minami-Aso Village.
Also, 11 months after the Kumamoto Earthquake,the Grassland Restoration Committee carried out
supporting activities in order to restart the fire
controlled burning for the livestock farmers on thegrasslands where the land had been damaged bysurface ruptures The methods of information of theGrassland Restoration Committee was the mass
media such as the newspapers and the report of theGrassland Restoration Committee.
These creative reconstruction efforts were
financed by the fund of the Grassland Restoration
Committee.
Aso Green Stock
The decline of the livestock industry and theincreasingly aging population, the landscapemanagement of grasslands has become increasingly
difficult. To address the shortage of manpower, thevolunteer activity in Aso attracted a lot of motivatedpeople outside of Aso since 1990’s. A volunteer
group was founded to support the controlled burning
work under the name Aso Green Stock in 1995.Also,
approximately 960 volunteers carry out maintenancetasks such as the controlled burning together with thelocal inhabitants presently.
Aso Green Stock implemented three projects asemergency support for the livestock farmers.
Firstly, it supported the resumption of the fire
controlled burning in the ruptured grassland areas.
Secondly, it repaired the grassland roads that weredamaged by the earthquake. Thirdly, it raised fences
for preventing cattle and horses from slipping into thecracks across the grasslands. It also repaired the barns
and cattle sheds damaged by the earthquake.
3 days after the Kumamoto Earthquake, on April
19th, Aso Green Stock surveyed the area struck by thedisaster and assessed the extent of damage to the

RESULTSThe Grassland Restoration Committee
The Act for the Promotion of Nature Restorationin 2003 established the system to restore the lost
natural environment in collaboration with various
bodies. Under this law, The Grassland Restoration
Committee discusses the conservation of grasslands
with various members from local people, government,
volunteers and academic experts totaling 224
members since 2015.
The Grassland Restoration Committee wasestablished as the fund for the restoration of thegrasslands in Aso since2011. The fund is used for thepromotion of livestock and for the restorationof grassland.
Although the improved grasslands were subjectsof the National Disaster Assistance of the Kumamoto
260

SEE - Kyoto, Japan, Nov.18-20, 2020

grasslands.
11 days after Kumamoto Earthquake, the Aso
Green Stock started raising funds for the affected
livestock farmers. The donations have reachedapproximately 2.8 million yen in four months.
Aso Green Stock organized sightseeing tours andexchange opportunities in order to facilitate
constructive participation efforts. These tours
included grassland management experiences,barbecues and visits to the local hot springs. The tours
began in Oct, 2016; buses departed from the cities of
Fukuoka and Kumamoto in Kyushu. In total, 119
people have participated in these events.
These creative reconstruction efforts for Aso
Green Stock were financed by donations from theKirin Kizuna Project and by Coca-Cola．

Fig. 2

Namino Yasuragi Exchange Center opened up as ashelter for mothers with infants and toddlers.
To support the victims, they lent the facility’sbaths and launderettes to families with infants. In
addition, they provided updated information on baths,
launderette facilities and road traffic information in
Aso, based on the information published by the city.
The Namino Yasuragi Exchange Center initiateda program called: “Playing and Healing – Recovery
Starting with the Hearts of Mothers and Children”,
which provided mental care. The program drew on
the actual experiences gained from the earlier
environmental education programs. It started 5 days
after the Kumamoto earthquake and ran for 18 days
between 2016, April 19 and May 8. The activities
included reading sessions, hardcover and paperback
rentals, creating chalk art works, yoga, head massages
and chiropractic sessions for mothers.
They held “Play Activities” every Saturday fromMay 8th to July 2016 and they held “Healing
Activities” twice a month from September 2016.
From May 2016 they opened a recycling shop forhome appliances such as refrigerators and washingmachines, and storage furniture in collaboration witha logistics company.
From July, 2016 they held disaster prevention
workshops in collaboration with NPOs specializing indisaster prevention.
2 years and 5 months after the earthquake, sincelocal residents and children’s level of interest towards
disaster prevention was still high, they held a disasterprevention workshop in collaboration with
universities. The workshop featured the following
contents: introduction of the local community’s
mutual assistance during the Kumamoto earthquake,
explanation of the characteristics of the sedimentdisaster in the Aso area, preparation of emergency
food, proposed emergency action plan utilizing Aso
region’s hazard map and 3D topographic models.
The methods of information was the web site of
the Namino Yasuragi Exchange Center and social
media platforms such as Facebook. These creative
reconstruction efforts were financed by several
grants.

The controlled burning

Aso Green Stock used postal mail and social media
platforms such as Facebook to share information withits members about the reconstruction support.
As a result of the aforementioned efforts, thepartnerships with the volunteers of the grasslandpreservation before the Kumamoto Earthquake have
led to the swift recovery of the livestock farmers
following the earthquake.
After 6 months, the disaster support activities of
the grassland volunteers have successfully developed
into various tourist and exchange projects.

GIHAS CAFÉNAMINO YASURAKI EXCHANGE CENTER

GIAHS Cafe is a community cafe established bya female farmer living in the Aso area who waspreviously actively involved in the efforts torecognize the Aso area as a Globally Important
Agricultural Heritage System.
The concept of GIAHS Cafe is to serve as a hub
for local communication in daily life and to function
as a shelter at times of disaster.
The interview subject is a person who participatedas an earthquake volunteer at the evacuation center
immediately after the Kumamoto earthquake, andvisited Minamiaso Village.

The Namino Yasuragi Exchange Center was
opened in 2002 as an accommodation and training
facility and to serve as a venue of interaction between
urban and rural areas. The Exchange Center has also
been providing environmental education programs
such as camps and nature watching programs.
During times of disasters, mothers in evacuation
centers often worry about the noise of their children
crying and bothering other evacuees which causes
them great stress. To tackle this problem,
immediately after the Kumamoto earthquake, the261

SEE - Kyoto, Japan, Nov.18-20, 2020

She sympathized with the concept of the GIAHS
cafe and moved to Minamiaso village four months
after the earthquake to open GIAHS cafe.
A workshop was held to remodel the venue for the
opening of the GIAHS cafe. The renovation
workshop was attended by more than 30 people intheir 20s and 30s who participated as volunteers. At
the renovation workshop, the walls and the ceiling of
the barn were painted.
In order to allow the GIAHS Café to function as ashelter during times of disaster, it was equipped witha biomass toilet, a solar power generator, a pellet
stove, and a pellet fired pizza kiln.
The other interviewee was working outside
Minamiaso as a vegetable sweets pastry chef.
Her opportunity to move to Minamiaso village
came about when she participated as a vegetable
sweets pâtissier in a "restaurant bus" ran by a female
farmer in Minamiaso village in May 2017.
The idea of the restaurant bus came from female
farmers and young people who moved to Kumamoto
after the earthquake[8].The restaurant bus was set up
in collaboration with the East Food Society and
WILLER Co., Ltd., which creates local attractions
using the restaurant bus. The restaurant bus is an
open-top double-decker bus with a kitchen on the firstfloor and a dining room on the second floor. The
course of the restaurant bus tour ran around farmlands, sake breweries, and brewery cellars whichwere recovering from the disaster. The restaurant bus
successfully connected the landscape, food andpeople creating local production for local
consumption in the Aso area. Two years have passed,
GIAHS Cafe is holding workshops sharing life
related techniques and wisdom with residents.
The subsequent creative reconstruction effort led
by a diverse range of organizations
The following three points can be considered as
results of the creative reconstruction effort led by theorganizations.
The first key to success was that each body
utilized its networks and facilities to support subjects
that typically lack support at times of disasters suchas supporting infants who are highly vulnerable orsupporting the grasslands that couldn’t qualify forgovernment aid. The other crucial point was taking
quick action that led to the speedy recovery.
They secured living conditions within the firstmonth of the earthquake and secured livelihood
within three months.

Time to secureTime to secureTime to secure
The time until the Transmission of
information
survivalliving conditions
livelihood
resumption ofInterviewee
Context(10 days after the (one month after (three months from business activities.
disaster),the disaster)
the timeof the range of organizations
Table 2 The subsequent creative
reconstruction
effort led bya diverse
disaster)
The Grassland
Restoration
Committee

Various
Questionnaire tomembers
the livestock
for thefarmers on theconservation of disaster support
the grassland in
Aso

Coordination ofdisaster support

Aso Green
Stock

Restored apasturage road/
Damaged water
wells, feeders andfarm fences were
repaired or
replaced/
New water tanks
were installed
Restored apasturage road/
Damaged water
wells, feeders andfarm fences were
repaired or
replaced/
New Barn were
installedNPO
Survey of the area Fundraising/(Support thestruck by the
Coordination ofcontrolled
disaster anddisaster support
burning with the assessed the
local inhabitants extent of damage
by volunnteers) to the grasslands/
Started raisingfunds for theaffected livestock
farmers.
NaminoAccommodation Opened up as a“Playing andOpened a
Yasuragi
and training
shelter for mothers Healing –recycling shop for
Exchange Cente facility
with infants andRecovery Starting home appliances
toddlers/
with the Hearts ofLending theMothers andfacility’s baths and Children”, whichlaunderettes toprovided mental
families with infant/ care.

GIAHS CAFÉAn earthquake
volunteer at theevacuation center
Inhabitant

An earthquake
volunteer at theevacuation center

Newspapers and Fund of the
Supported
activities in order the report of the Grassland
to restart the fire Grassland
Restoration
controlled burning Restoration
Committee
on the grasslands Committee
where the land had
been damaged bysurface ruptures
Sightseeing tours Postal mail andand exchangesocial media
opportunities inplatforms suchorder to facilitate as Facebook
constructive
participation efforts

A disasterprevention
workshop in
collaboration with
universities.

A workshop for the Open of the
opening of the
GIAHS café/
GIAHS cafe
Plan of therestaurant bus
Participation of therestaurant bus

262

Fund

Donations fromthe members
and theCompany

The website of Several grants
NaminoYasuragi
Exchange Centeand social media
platforms suchas Facebook

Social media
platforms suchas Facebook

Donations fromthe members
and theCompany

SEE - Kyoto, Japan, Nov.18-20, 2020

Second, each body continued its activities fromthe stages of securing survival to securing livelihood.
During this process the activities have expanded into
new forms such as tourism and disaster prevention
education, where creative reconstruction activities
were proposed and implemented by local residents.
These creative reconstruction efforts also served as
triggers to young migrants and led to the revival of
the local community.
Thirdly, each body independently disseminatedinformation through social media and other channels
to raise awareness and gain support for the creative
reconstruction.

https://www.pref.kumamoto.jp.e.qp.hp.transer.com/kiji_16643.html[3] YAMAKAWA Mitsuo., East Japan Great
Earthquake Disaster and Socio-economic
Reconstruction Paradigm Putting the Kumamoto
Earthquake in Range, Annals of the Japan
Association of Economic Geographer, Vol.64，
2018,pp.129-137[4] SANO Hiroyoshi., The Network on Tourism
toward the East Japan Earthquake Disaster
Reconstruction in Minami-sanriku Town,
Proceedings of Japan Institute of Tourism
Research Annual Conference Vol.26,2011,
pp.329-332.
[5] KAIZU Yurie., Empirical studies of earthquake
reconstruction assistance through eco-tourism inMiyako city, Iwate, From over thousand years
treasure hunting to Ecotourism, The journal of
the Tourism Research, Vol24(1) ，2012 , pp.4144.
[6] YAMAMOTO Kiyotathu,The Influence ofContact with Local People upon the Tourists'
Consciousness of Tourism in a Natural
Sightseeing Spot : A Case of Urabandai,
Fukushima, Proceedings of Japan Institute ofTourism
Research
AnnualConference
Vol.26,2011, pp.329-336..
[7] Cabinet Office of Japan, The Hand book ofDisaster Management,
bousai.go.jp/kaigirep/houkokusho/hukkousesaku/
saigaitaiou/output_html_1/images/dept/cao_fukk
ou/handbook.pdf[8] OTSU Eri., Grass Root Activities in Aso before
and after the Big Earthquake, Journal of ruralplanning 35(3),369-374[9] Hossain M.Z. and Awal A.S.M.A., Experimental
Validation of a Theoretical Model for Flexural
Modulus of Elasticity of Thin Cement Composite,
Const. Build. Mat., Vol.25, No.3, 2011, pp.14601465.

CONCLUSION
This study analyzed the creative reconstruction
efforts led by a diverse range of organizations fromthe Kumamoto earthquake in the Aso region inchronological order. In addition, this study was aimed
to clarify the efforts of the residents and communities
pp.333-336of the Aso region ranging from disaster
relief to tourism and various forms of exchange.
These efforts utilized the unique human networks
and organizations during the period for ensuring
survival (10 days after the earthquake) and the period
for securing living conditions (1 month after theearthquake) and also provided quick support where
the government could not reach.
Furthermore, we clarified how the unique efforts
undertaken by each subject has made it easier tocontinue the relief effort and how they developed into
tourism, exchange and disaster prevention education
programs reviewing local communities.
Therefore, we can conclude that thecharacteristics of the creative reconstruction effort of
the Aso area are that the prompt support was based onleveraging the preexisting strengths of each entity,
and the efforts were linked to tourism, exchange andother activities which resulted in providing new value
and appeal to the Aso region.
The research subject is one of the key people orplatforms in the Aso area. New proposals for creative
reconstruction efforts built upon the cooperation ofeach entity is a topic of further interest.

ACKNOWLEDGMENTS
This work was supported by JSPS KAKENHI Grant
Number JP17K02130 and JP19H02981 , the Strategic
Research Project of Tokyo University of Agriculture.
REFERENCES[1] The Ministry of Environment., The number ofusers in National Park,2015
https://www.env.go.jp/park/doc/data/[2] Kumamoto Prefecture., Revival plan from 2016
Kumamoto earthquake,263

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

ASSESSMENT OF HABITAT SUITABILITY AREA OF ENDANGERED
SPECIES USING MAXENT BY LAND USE CHANGE IN FUKUSHIMAPREFECTURE, JAPAN
Hideyuki Ito1, Hiromu Tomita2, Makoto Ooba3 and Takahiro Fujii4
College of Science and Technology, Nihon University, Japan; 2Fujita Road Construction, Japan;
3
National Institute for Environmental Studies, Japan

1,4

ABSTRACT
Fukushima prefecture in Japan is the third largest of Japan's 47 prefectures and stretches over 150 kilometersfrom the Pacific coast into the mountainous interior of northeastern Honshu. Fukushima prefecture is abound withrich nature such as Mt. Bandaisan, Lake Inawashiro and Bandai highlands including beautiful ponds and lakes.
However, the number of endangered species in Fukushima has been increasing since the 1970's because the areaof nature environment has been decreasing and then various habitat for valuable living organisms have been
destroyed by rapid urbanization and infrastructure developments.
Therefore, in this research, we analyzed the time-series change of amount of habitat area for four endangered
species (Aquila chrysaetos, Accipiter gentilis, Macaca fuscata and Ursus thibetanus) using MaxEnt (Maximum
Entropy Modeling) software for modeling species distributions. As the result, it was concluded that total habitat
possibility area for only Golden eagle was increased slightly but the one of other species was decreased.
Keywords: MaxEnt, GIS, Endangered Species, Green Area

increased damage to agricultural products caused by
the expansion of the habitat of Japanese macaques.
Li et al. [5] researched the impact of environmental
variables and land use in Nagoya City on the habitatof tanuki (raccoon dogs) and Japanese weasels using
Maxent analysis, albeit without performing a broadbased analysis. Matsuura et al. [6] created vegetation
models, etc., for the Yatsu Higata tidal flats andestimated the environment required by the gray-faced
buzzard eagle. However, the gray-faced buzzard
eagle also lives in habitats such as mountains, underconditions different from those of tidal flats. Suchhabitats were not estimated in this research andrequire further study. Kamata et al. [7] proposed
methods of forest zoning on the basis of land
productivity and mountain disaster risks. However, it
is also necessary to perform analysis from theviewpoint of wildlife habitats. Miyamoto [8]indicated the focal points to propose Marine
Protection Area by applying MaxEnt to Emperor
Seamount Chain using limited data. Pan et al. [9]estimates the suitable habitat area of Chinese
Alligator that is a critically endangered crocodilian
and predicted its distribution in Anhui Province,
China by MaxEnt. West et al. [10] developed apresence-only model of invasive cheat grass (Bromus
tectorum) distribution in Rocky Mountain National
Park, Colorado, USA in from 2007 through 2013 withlimited data to compare with the result of GLM(Generalized Linear Model). Remya et al. [11]represented current and future habitat suitability
distribution of Myristica dactyloides Gaertn, a

INTRODUCTION
Fukushima prefecture in Japan is the third largest
of Japan's 47 prefectures and stretches over 150
kilometers from the Pacific coast into themountainous interior of northeastern Honshu.
Fukushima prefecture is abound with rich nature suchas Mt. Bandaisan, Lake Inawashiro and Bandai
highlands including beautiful ponds and lakes.
However, the number of endangered species inFukushima has been increasing since the 1970's
because the area of nature environment has been
decreasing and then various habitat for valuable
living organisms have been destroyed by rapid
urbanization and infrastructure developments.
For the changes in land use, a lot of existing
researches have analyzed the area and green coveragedepending on the land use classification. A study by
Hashimoto et al. [1] on umbrella species, which needlarge habitats satisfying specific conditions,elucidated their winter habitat preferences in the Lake
Inba basin. Field research has also been conducted on
raptors by evaluating the effects of environmental
factors on the birds using the jackknife method.
Ikemi et al. [2] performed quantitative analysis
regarding the impact of artificial landform changes on
biodiversity through a time-series analysis of land usechanges. Harada et al. [3] conducted quantitative
analysis on the extent of degradation of a forest
environment through a count of each type of tree.
Iwasaki et al. [4] reported on the changes in land use
up to the 1980s and on their relationship with the264SEE - Kyoto, Japan, Nov.18-20, 2020

medicinally and ecologically important tree species
by MaxEnt in order to implement sustainable
conservation or adaptation strategy. Pratumcharta etal. [12] predicted the distribution of B. s.
goniomphalos in Thailand on the basis ofenvironmental and climatic factors and also indicatedthat altitude, land cover, normalized difference
vegetation index (NDVI), precipitation in the driest
month, land surface temperature and soil pH affected
its distribution.
Previous researches encompassed the evaluationof lands and forests by GIS, as well as the evaluationof habitats for target species by MaxEnt. However,there are few studies on the impact of urban
development, including transportation infrastructuredevelopment, over time and in a wide area withinwildlife habitats.
Therefore, in this research, we analyzed the timeseries change of amount of habitat area for four
endangered species (Aquila chrysaetos, Accipitergentilis, Macaca fuscata and Ursus thibetanus) using
MaxEnt (Maximum Entropy Modeling) software formodeling species distributions.

I [13] and II [14] recorded sufficient habitat data. As
for the number of habitat data, to obtain a uniform
degree of accuracy, we selected those with 15 ormore meshes indicating confirmed habitat.
As a result, the golden eagle (Aquila chrysaetos)
and the northern goshawk (Accipiter gentilis), two
raptors with a particularly large habitat which are
Category I threatened species, were selected among
birds. Two vulnerable species, the Japanesemacaques (Macaca fuscata) and the Asian black
bear (Ursus thibetanus) were selected among
mammals. Japanese macaques and black bears arevulnerable species, and although their conservation
priority was not especially high in 2002, they wereselected due to the increasing necessity of measuresfor conservation and animal protection which were
expected in the future.
The land use classification of each period wasused Digital National Land Information [15]; land
use subdivision meshes have different land use
categories from year to year. In light of the need tounify land use classifications in order to perform
analysis over time, a new classification has beencreated, integrating land use into 9 categories: rice
fields, other agricultural land, forests, wastelands,
Buildup Area, main line traffic sites, other land,
rivers and lakes, and seaside areas.

DATA
The wildlife habitat data used in MaxEnt wereobtained from the Red Data Book[13], [14]compiled in 2002, plotted in QGIS, then converted
into CSV data so as to be usable in MaxEnt. Having
examined various habitat data, these were found tobe the most suitable for analysis and further use.
Further, because these habitat data were gathered ina mesh of 10km x 10km, at the time of plotting, thepoints were placed in the land use category thatoccupied the largest portion of the mesh.
Table 1 is a list of the environmental variables
used in MaxEnt. According to the Digital National
Land Information [15], seven environmental
variables were used and arranged by QGIS in
MaxEnt: land use subdivision data on Fukushima
Prefecture from 1976, 1987, 1991, 2006, 2009 and2014; average elevation in 2009; average inclination
angle in 2009; annual average temperature, annual
average precipitation, and annual deepest snow
cover calculated from the average of the past 30
years; road edge data created from 2015 to 2016 by
the Geographical Survey Institute of Japan (GSI)[16]. Road edge data were obtained by calculating
distance from the road with the raster distance toolin QGIS and digitizing it for analysis.
Figure 1 shows the analyzed target species. The
target species were selected from the Fukushima
Red Data Book I [13] and II [14] (created in 2002).
The selection criteria were: habitat conditions
considered to be related to each environmental
variable used in the study, species with a large
habitat (due to the use of a 10km x 10km mesh data),
and the condition that the Fukushima Red Data Book

Table 1

Data sets input into MaxEnt
Data

Mesh size

Year

Source

2014
2009
2006
Land use

100m

1997
1991
1987
1976

Average slope angles

10m

2009

Average altitudes

10m

2009

Average rainfall amount

１km

2010

Annual average temperature

１km

2010

Deepest snowfall in the year

１km

2010

Distance from nearest road

-

2016

Fig. 1
Target species
RESULTS265

Geospatial Information
Authority of Japan

SEE - Kyoto, Japan, Nov.18-20, 2020

habitat plot data confirming location of the target
species.
In the case of the Golden eagle, the suitable
habitat mainly extends in the southwest and north,such as Oze National Park and Aizukomagatake,which is blessed with a rich natural environment. In
a comparative evaluation of suitable habitats in 1976
and 2014, almost no significant change was found in
the habitat suitability map.
The habitat suitability map for northerngoshawks shows that there are many suitable
habitats in the mountains, northern areas, etc.,
between Hamadori located in the east area andNakadori in the central area in Fukushima prefecture.
The most remarkable change in the habitat
suitability map between 1976 and 2014 was foundin Nakadori, Fukushima Prefecture, where habitats
with a low degree of suitability are extending
gradually. Further, the same tendency is seen in the
Aizu region and the nearby mountainous areas,
which can be said to be greatly affected by recent
urban development.
The suitable habitats for Japanese macaque were
found in the northern part of Hamadori and in thenorthern and southwestern parts of Lake Inawashiro(black part in the center). In the case of Japanesemacaques,
yellow
moderate-degree
habitatsuitability was found often, whereas red andorange—indicating highly suitable habitats—wererarely seen. Since Japanese macaques may appear inurban areas in search of food, their habitat is
considered to be widely distributed. Comparing themap between 1976 and 2014, no significant change
was found in the habitat suitability map, but there isa tendency toward the shrinking of suitable habitats
in the mountains due to the opening of expressways.
The habitat suitability map of Asian black bearshows suitable habitats in the northern andsouthwestern parts in Fukushima prefecture. It was
found that suitable habitats in the northern andsouthwestern parts of Fukushima prefecture havedecreased due to environmental changes as aconsequence of deforestation due to a highcontribution ratio related to forest land.

Comparison result of area of each land use
In Table 2, land use areas are comparedaccording to land use in Fukushima prefecture. Ricefields decreased uniformly, and other agriculturalland, despite showing a growing trend from 1976 to
1997, decreased thereafter, resulting in a total areathat was only 0.3% larger in 2014 than in 1976.
Forests decreased almost uniformly from 1976 to
2006, but recovered remarkably in 2009. Although
the results of conservation activities such asafforestation can be taken into account, it may besupposed that the number of high-quality forests isdecreasing due to the decline of forestry. Wastelands
decreased almost uniformly, and showed asignificant decrease between 1976 and 2014 as well.
Buildup Area increased almost uniformly. The landthat is considered unsuitable as a wildlife habitat,such as Buildup Area, main line traffic sites, andother land increased by 82.7% between 1976 and2014. The green ratio, including rice fields, otheragricultural land, forests, and wastelands, decreasedby 2.9% between 1976 and 2014. As for the reasonof the significant decrease in the number of mainline traffic sites in 2009, it is likely due to the factthat since 2009 roads and railways have been
divided into two categories of land, whereas until
2009 there was only one category for both.
Furthermore, in this land use subdivision mesh, theland use category that occupies the largest area in a
100m x 100m mesh constitutes the land use of thatentire mesh. Thus, for example, even if the traffic
land itself has not decreased, new buildings may
have been constructed in the surroundings,
occupying the largest area in the mesh, anddetermining the land use to be changed from traffic
land to buildup Area.
Analysis results of suitable habitat area
Figure 2 shows the result of suitable habitat areaof four target species by MaxEnt in 1976 and 2014.
The map of habitat suitability for the target species
being expressed as a value from 0 to 1. Habitat
suitability increases as the color changes from blue
Table 2

(1,000ha)

Comparison result of area of each land use

Land use

1976

1987

1991

1997

2006

2009

2014

Rice fields

162.1

157.0

155.0

149.0

149.0

146.8

145.2

Comparison between
1976 and 2014 (%)-10.4%

Other agricultural land

89.6

96.6

96.5

103.0

95.2

87.4

89.9

0.3%

Forests

1002

997

992

972

971

1015

1009

0.7%

Wastelands

41.4

33.2

32.9

31.0

31.2

15.3

13.7

-66.9%

Buildup Area

36.5

43.0

42.8

54.8

57.3

62.6

63.2

73.2%
237.5%

Traffic sites

1.6

2.5

6.6

8.1

10.5

1.3

5.4

Rivers, Lakes and Ponds

35.1

35.2

35.0

40.9

36.4

30.1

33.6

-4.3%

Coastal Area

14.2

2.8

2.7

18.2

25.2

2.6

1.9

-86.6%

Others

9.3

12.5

16.1

18.8

26.8

18.1

18.0

93.5%

to green, yellow, orange, and red. White dots are

266

SEE - Kyoto, Japan, Nov.18-20, 2020

The result of Golden eagle had an AUC of 0.775,

Fig. 2

Suitable habitat area estimated by MaxEnt
which was a good result. Regarding the contribution
ratio of Golden eagle, the land use contribution ratio
for the golden eagle was found to be very low at 0.6%,
and each environmental variable exerts an impact on
the Golden eagle, and it is understood that the averageslope angles and average altitude have a large impact.
These two environmental factors influences may behigh because the Golden eagle lives and nests on
rocky spots such as steep cliffs in mountainous area.

Result of AUC and Contribution Rate
Table 3 shows the Area Under the Curve (AUC)
and contribution rate of respective environmental
factors of each species. A model with AUC value
exceeding 0.7 is considered as a good model, and thecloser to 1 is better model.

267

SEE - Kyoto, Japan, Nov.18-20, 2020

On the other hand, the land use contribution ratio was
only 0.6%. Therefore, the impact of land use is notparticularly significant. The highest contribution ratiois that of other agricultural land.
The AUC of the Northern goshawk was 0.765,
which was a good result. The contribution ratio ofland use and average altitude for Northern goshawks
were as high as 49.5% and 33.2% respectively. The
detail land use contribution ratio of Northerngoshawk is shown in Figure 3. Figure 3 is thecontribution ratio showing which land uses are likely
to influence habitat suitability, and the likeliness ofhabitat suitability itself. As raptors such as thenorthern goshawk catch their prey in grasslands,
paddy fields, wetlands, etc., with good visibility, thecontribution ratio of rice fields, other agriculturallands, and wastelands were high. In contrast, forests
reduce the range of vision and obstruct flight,
resulting in a low contribution ratio.
The AUC of Japanese macaque was 0.766, which
was a good result. The highest contribution ratio forJapanese macaques was temperature, followed by theangle of inclination. In the case of Japanese macaques,
it was found that all environmental variables had acertain degree of contribution. Consequently, habitat
suitability tended to be high only in areas where allenvironmental factors were well-balanced.
The AUC for the black bear was 0.809, thehighest among the four target species. In the case of

Table 3that the black bear is easily affected by environmental
factors related to temperature.
Result of time-series change of potential suitable
habitat area
Table 4 and Figure 4 show numerical values
corresponding to the changes in potential suitable
habitat areas in Fukushima Prefecture over time foreach four species. From the data in the ASC fileobtained by MaxEnt analysis, data evaluating suitable
habitats at a ratio of 0 to 1 were extracted and used todefine potential suitable habitat area by multiplying
the numerical values by the area of each mesh (100m
x 100m mesh). As a result, a comparison between
1976 and 2014 confirmed a decrease in habitability
areas by 3.57% for the Japanese macaque, by 7.44%
for the northern goshawk, and by 1.92% for the black
bear. The habitability areas for the golden eagle were

AUC and contribution rate of respective environmental factors

Fig. 3
Response curve on each land use of
Northern goshawks

Fig. 4
Suitable habitat areas response curve oneach land use of Northern goshawks

the black bear, the contribution ratio is high fortemperature, land use, and snowfall. This suggests

Golden eagle

AUC

Land use
(%)

0.775

0.6

AnnualAverageaverage
Averagerainfalltemperature altitudes (%)
amount (%)
(%)
0.8

1.8

32.7

Averageslope
angles (%)
52.0

DeepestDistance
snowfall in from nearest
the year (%) road (%)
0.3

11.9

Northern goshawk

0.765

49.5

5.2

0.0

33.2

1.2

10.8

0.1

Japanese macaque

0.766

15.3

6.6

28.2

5.1

23.3

11.9

9.7

Asian black bear

0.809

18.2

1.5

48.2

0.6

9.9

18.2

3.4

268

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 4

Result of potential suitable habitat area between 1976 and 2014
1976

1987

1991

1997

2006

2009

2014

Comparison between
1976 and 2014

Golden eagle

48.75

48.65

48.81

48.80

48.47

48.75

48.80

0.10%

Northern goshawk

50.76

51.40

50.76

51.40

51.22

48.01

46.99

-7.44%

Japanese macaque

54.28

54.04

54.18

53.61

52.40

52.33

52.35

-3.57%

Asian black bear

43.55

43.37

43.46

43.42

43.08

42.93

42.72

-1.92%

found to have increased by 0.1%. The results suggestthat a decrease in suitable habitats for wildlife due tourban development and transportation infrastructure
maintenance has become increasingly likely.

Identification of potential habitats of Gray-faced
Buzzard in yatsu valleys based on DEMs andvegetation data, Proceedings of Japanese Instituteof Landscape Architecture, 65(0), 2002, pp.39-39.
[7] Kamada M., Sanpei R., and Oka K., Method forforest zoning in broad area based on the evaluationof land-productivity and mountain hazard,
Landscape and Ecological Engineering, 18(2),2013, pp.109-122.
[8] Miyamoto M., Attempts to estimate habitat of coldwater corals, Aquabiology, Vol.35(5), 2014,
pp.461-468.
[9] Pan T., Wang H., Duan S., Ali I., Yan P., Cai R.,
Wang M., Zhang J., Zhang H., Zhang B. and Wu
X., Historical population decline and habitat loss ina critically endangered species, the Chinese
alligator (Alligator sinensis), Global Ecology andConservation, Vol.20, 2019, e00692.
[10] West M. A., Kumar S., Brown S. C., Stohlgren J. T.
and Bromberg J., Field validation of an invasive
species MaxEnt model, Ecological Informatics,
Vol.36, 2016, pp.126-134.
[11] Remya K., Ramachandran A. and Jayakumar S.,
Predicting the current and future suitable habitat
distribution of Myristica dactyloides Gaertn using
MaxEnt model in the Eastern Ghats, India,
Ecological Engineering, Vol.82, 2015, pp.184-188.
[12] Pratumcharta K., Suwannatrai K., Sereewong C.,
Thinkhamrop K., Chaiyos J., Boonmars T. and
Suwannatrai T. A., Ecological Niche Model basedon Maximum Entropy for mapping distribution of
Bithynia
siamensis
goniomphalos,
firstintermediate host snail of Opisthorchis viverrini in
Thailand, Acta Tropica, Vol.193, 2019, pp.183-191.
[13] Fukushima prefecture, Japan, Red Data Book
Fukushima Ⅰ (Plants, Insects and birds),
http://is2.sss.fukushima-u.ac.jp/fksdb/txt/51603.002/thumb/00000_01.jpg[14] Fukushima prefecture, Japan, Red Data Book
Fukushima Ⅱ (freshwater fishes, amphibians,
reptiles and mammals), http://is2.sss.fukushimau.ac.jp/fks-db/txt/51603.003/index.html[15] Ministry of Land, Infrastructure, Transport andTourism, digital national land information,
http://nlftp.mlit.go.jp/ksj/[16] Geospatial Information Authority of Japan, basemap information,
http://fgd.gsi.go.jp/download/menu.ph

CONCLUSIONSIn this research, MaxEnt was used to analyze thesuitable and potential habitat area of four endangered
species in Fukushima prefecture over time,demonstrating the impact of rapid urbanization andinfrastructure developments and the tendency forsuitable habitats to decrease for species other than the
golden eagle. Thus, it was cocluded that the habitat forvarious species including endangered species needs toprotect from the point of view of the harmony ofenvironment conservation and human activity.
For further research, it is necessary to improve
the accuracy of the plot data for habitat places bycollecting more data and by including otherenvironmental variables for MaxEnt.
REFERENCES[1] Hashimoto D. and Hasegawa M., Habitat
preference and species distribution modeling ofraptorial birds inhabiting Inbanuma-lake during
winter season, Report of the Chiba Biodiversity
Center (7), 2014, pp.65-78.
[2] Ikemi H., Esaki T., Mitani Y. and Tran T. A., Spatial
Distribution of Human Impacts on Terrain Based on
Land-use Change Analysis : Development and GIS
Analysis of Land-use Maps since 1900 in the
Fukuoka Prefecture Area, Engineering Geology,
Japan, 52(3), 2011, pp.97-108.
[3] Harada I., Matsumura T., Hara K., and Kondoh A.,
Spatial analysis of changes in Japanese forests
during the process of modernization, Landscapeand Ecological Engineering, 16(1), 2011, pp.17-32[4] Iwasaki N., and Sprague D., A study of the land use
history in the Japanese macaque habitat expansion
area of the Boso Peninsula, Japan, Journal of Rural
Planning Association, 24, 2005, p.1-6.
[5] Li R., Ooba M., Hayashi K., Noro T., Dhakal, A.,“The potential distributions of mammalian withland use changes by the MaxEnt model - case of
Nagoya city”, ISETS’13, 2013, pp.13-15.
[6] Matsumura T., Yokohari M., and Azuma A.,269

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

HEAVY METALS EXPOSURE AND RISK ASSESSMENT OFCOOKED RICE FROM THE FIELD NEAR THE OLD DUMPSITE IN
INDONESIA
Fajri Mulya Iresha1,2, Suphia Rahmawati2, Dhandhun Wacano2, Kasam2, Ratna Kartika Sari2,
Minoru Yoneda1
1
Graduate School of Engineering, Kyoto University, Japan; 2Faculty of Civil Engineering and Planning,
Universitas Islam Indonesia, Indonesia
ABSTRACTThe lack of implementation of spatial planning and landfill site planning in several areas of Indonesia in
the past has led to the case of the rice field directly bordering the open dumping site. High intensity of rainfall,leachate-contaminated irrigation, and the open dumping site with steep slopes create a high risk of rice pollution.
This study aims to identify the concentrations and the exposure of heavy metals consist of Cr, Cd, Cu, Fe, Mn,
Zn, and Pb in the cooked rice which is consumed by residents around the open dumping site, the rice, and thewater using for rinse the rice. In this research, rice also compared between two zones which are upstream sitezone and downstream site zone. Thus, applicable quality standards and analysis of estimated metal intake will
be conducted. The results of this work demonstrate the heavy metals in the downstream zone concentrations
are higher than the upstream zone. Besides, there are several samples whose exceeds the quality standard.
Based on the test results obtained heavy metal concentrations in rice samples are higher than heavy metal
concentrations in cooked rice. The higher Pb content in adult (Risk Quotient (RQ) value > 0.2) and Cr content
in children (Excess Cancer Risk (ECR) value > 10-3) suggest the risk of the health of the people near the site.
Keywords: Exposure, Heavy Metals, Open Dumping, Rice, Risk Assessment

INTRODUCTION

dumping method in which existing waste was not
being processed. With the application of the open
dumping method, it was high possibility thatleachate originating from the degradation of thewaste from the landfill will enter the soil pores,
which then will subsequently enter to thegroundwater. With the groundwater that has been
contaminated with leachate even with slow
groundwater flow, the heavy metal pollutants will
still be exposed to the environment around the
Gunung Tugel dumpsite [2].
Heavy metals that are in the soil can be sourced
from nature and also anthropogenic. In soils that are
still not utilized, heavy metals can be contained insoil parent materials, geochemical and pedologicalprocesses in soil formation [3]. Ballistic soil
naturally contains heavy metals Cu, Zn, Ni, and Cr .
In anthropogenic processes, heavy metals can enter
through the addition of chemicals such as pesticides
and also the use of fertilizers, motor vehicle
pollution [4, 5].
Around the Gunung Tugel dumpsite, there is arice farm owned by residents with an irrigation
channel just below the landfill. Rice produced fromrice fields around the Gunung Tugel dumpsite will
be consumed by themselves for daily food byresidents around the Gunung Tugel dumpsite. The
presence of heavy metals in the environment, suchas in soil and irrigation, can be hazardous to humanEvery day, human activities produce waste.
Almost all sectors of human activity always
produce waste. With the increase in the number ofresidents will increase the percentage of the amountof solid waste. With the times will change lifestylepatterns. With these changes will also affect theincrease in the amount of waste generated. Whether
it is domestic, electronic, industrial waste and others.
In Indonesia, the percentage of waste transported to
the landfill is still very high without prior treatment,such as the sorting of solid waste from a waste
source. So that with a large amount of garbage
transported to the landfill, over time, the solid waste
will continue to accumulate in the landfill without
any management [1].
The Gunung Tugel dumpsite operated in 1983
and was closed because it was considered to havebeen overloaded. In 2016, therefore the Gunung
Tugel dumpsite was no longer used. However, theGunung Tugel dumpsite is still prone to landslides
and garbage fires that occur every dry season. The
Gunung Tugel dumpsite itself now has a land areaof 5.3 hectares by accommodating waste from
Purwokerto with a more significant percentage oforganic waste. Every day, the Gunung Tugeldumpsite can provide 300-350 m3 of garbage.
The Gunung Tugel dumpsite uses an open
270

SEE - Kyoto, Japan, Nov.18-20, 2020

health. There is other study in the open dumping sitethat found the concentration of heavy metals in soil
and water around the landfill were higher than thepermissible limit because of the leachate migration[6]. Even some plants those are in the landfill could
be a promising trace metals contamination indicatorfor heavy metals [7]. For rice plant, also can adsorb
the heavy metals so that there is high content in therice grains and cause the risk for the human health[8]. The entry of heavy metals from theenvironment into the food chain can cause theconcentration of heavy metals that are higher andhigher, because of difficulty nature heavy metals
properties to decompose and to be deposited on thesurface of the soil that can be absorbed by thesurrounding organisms.
Therefore, to identify whether the Gunung
Tugel dumpsite has a role in the entry of heavy
metals in an agricultural land owned by residents
around the landfill or not. So, this research was
conducted to identify the magnitude of theconcentration of heavy metal content contained inwater, rice and also in the cooked rice consumed byresidents from the rice field around the Gunung
Tugel dumpsite.

The location of the rice and water sampling inthis study was divided into two zones for each test
sample. The first zone is the paddy field zone withirrigation flow before the landfill landslide occurred.
The second zone is the paddy area zone withirrigation flow after landfill landslide. The water
sampling zone was also divided into two zones. The
first and second zones are based on the residence ofthe rice field owner at the location of the rice
sampling point (See in Fig.2). For the rice and thewater samples in zone 1, there are eight sampling
points for each house and rice field. For the second
zone, there are three sampling points for each houseand rice field. In this study, the number of 12 sample
points was based availability of the farmers in thefields and the using water in the rice fields is fromthe irrigation flow which contaminated withleachate especially within and after zone 2 of rice
field .
Zone 2Water
Dumpsite
Irrigation
flow

MATERIALS AND METHODS

Zone 2 Rice
Location

Zone 1 Rice

This study was conducted at the Gunung Tugel
Dumpsite, Banyumas Regency, Central Java. The
local government closed this site approximately in2016. The object of research carried out consistedof the water using for rinse the rice, the rice itself
and the cooked rice. The rice was used for researchoriginating from rice fields belonging to residents
around the landfill, and they consumed it directly.
For the water using for rinse the rice, the residents
are devided into two groups, who use of tap waterfrom local water company and from ground water.
The map of research locations can be seen in Fig. 1.

Zone 2 Water

Fig. 2 Water and Rice Sampling Location
Sample Preparation and Laboratory Analysis
The rice is taken from the rice field around the
Gunung Tugel Dumpsite, and residents themselves
consume the rice. The water sample taken in thisstudy is from the well water or tap water that is usedby residents to cook the rice every day.
The sampling method used in this study isstratified Sampling method. Considerations taken in
the sampling of rice and water in the form of
residents around the Gunung Tugel Dumpsite whohave rice fields, consume rice from the harvested
rice fields around the landfill and live around thesite. Samples taken in the form of rice and water areused for cooking rice at the Gunung Tugel
Dumpsite. A sampling of the water is done based on
SNI 6989: 58: 2008 Concerning Groundwater
Sampling Methods .
Physical observations carried out in the form ofconditions from topography, irrigation flow forN

LOCATION
BREBESPURBALINGGABANYUMASKEBUMEN
CILACAP

Fig.1 Location of Gunung Tugel Dumpsite
271

SEE - Kyoto, Japan, Nov.18-20, 2020

irrigating rice fields. Then the primary data is also
in the way of data from the results of heavy metal
tests. Interviews and questionnaires to residents ofrice fields around the Gunung Tugel dumpsite arealso conducted. Interview data were made in theway of how many times people consume rice in aday, how many times people cook rice in one day,how many times people rinse rice, what kind ofwater is used.
For the equipment or detecting the heavy metals
this research use Flame-Atomic Absorption
Spectroscopy (AAS) instruments. Samples thathave been taken from the field will be tested andanalyzed in the Environmental Engineering
Laboratory of the Universitas Islam Indonesia.
Samples that were tested were carried out indestruction process until the volume decreased up
to 10 ml and then extracted to 25 ml. In testing, thissample is carried out under applicable Indonesia
National Standard and no modification of sample
testing. In the metal test, the sample was added with
a 65% concentrated nitric acid.

Dt
Wb
tavg
RQ
RfD

ECR
SF

Based on the Risk Quotient (RQ), it is found that
there are health risks stated if the RQ value > 1.
Assume that there is other paths of exposure,especially from drinking water and vegetables, sothat RQ < 0.2 is thought to be acceptable. Based on
the value of Excess Cancer Risk (ECR) Risk levelis expressed in exponent numbers without units(example: 1.3E-4). The level of risk is said to be
acceptable or safe if the ECR ≤ E-4 (10-4) based on
guidelines for Environmental Health Risk Analysis
issued by the Indonesian Ministry of Health and
Health in 2012. The level of risk is said to beunacceptable or unsafe if ECR> E-4 (10-4).

Data Analysis
Exposure analysis or usually referred to as
exposure assessment or commonly also called
contact assessment which aims to identify the pathof heavy metal exposure through food or risk agentsso that the amount of intake received by potentiallyrisky individuals can be calculated. By using the
calculation formula as follows [9].

RESULT AND DISCUSSION
Heavy Metals in the Water Used for Rinsing the
Rice

Intake Exposure ( Ink)𝐼𝑛𝑘 =𝐶 𝑥 𝑅 𝑥 𝑓𝐸 𝑥 𝐷𝑡

The concentrations of heavy metals in the waterused for rinsing the rice for Gunung Tugel dumpsite
followed the decreasing order of Fe > Mn > Zn > Cr
> Pb > Cd > Cu. Based on the AAS, Cr, Cd, Fe, andZn test results exceed the quality standards at all
sampling points. The rest, other heavy metals
namely Mn, Pb, and Cu exceed quality standards atseveral points (See Fig. 1 & Fig. 2).

(1)

𝑊𝑏 𝑥 𝑡 𝑎𝑣𝑔

Risk Quotient (RQ)
𝑅𝑄 =

𝐼𝑛𝑘

(2)

𝑅𝑓𝐷

The duration or number of years the exposure
occurred (years).
Human weight (kg)The average period for carcinogenic and noncarcinogenic effects (days). For non-carcinogenic(30 years x 365 days) for carcinogenic (70 years
x 365 days)
Risk agent reference value in ingestion exposure
The dose/concentration of daily non-carcinogenic
risk agent exposure is estimated to have no
detrimental effect even though the exposure
occurs throughout life (for life)
The magnitude of the risk expressed infractions
multiples of rank 10 - (exponents)
The reference value of risk agents withcarcinogenic effects

Excess Cancer Risk (ECR)

0.400
Cd (mg/kg)

ECR = Ink x SF

0.350

(3)

Cu (mg/kg)
Cr (mg/kg)
Pb (mg/kg)

0.300

Max. Cd
Max. Cu
Max. Cr

Notes :

0.250

Table 1 Description of Variables in FormulasMax. Pb

0.200
0.150

SymbolDefinition

Ink

Total concentration of risk agents (mg / kg.day)

C
R
fE

0.100
0.050

Concentration of risk agents in clean water /drinking or food (mg / kg)
The rate of consumption or the amount of weightof food that enters the human body (g / day)
The duration or number of days a year occurs(days/years)

0.000
Area 1 Area 2 Area 3 Mean Area 4 Area 5 Area 6 Area 7 Area 8 Area 9 Area 10 Area 11 Area 12 Mean
Zone 1
Zone 2

Fig. 3 Concentration of Cd, Cu, Cr & Pb in the
Water
272

SEE - Kyoto, Japan, Nov.18-20, 2020

The amount of Pb in tap water caused by pipes used
to distribute the water, are made from polyvinyl.
This plastic containing Pb stearate. It shows theoccurrence of Pb leaching into the water when wateris overnight in the water pipe. For Fe, Zn and Mn
are naturally present in the environment and at
specific concentrations also needed by the body.
The rest, such as Cu, Cd, Cr may be present because
of seepage of leachate into wells for those whose
source of water is from well water, and also seepageof leachate water to piped water network for those
whose source of water is from tap water.

land. In a study, it was found that the pesticides
contained heavy metals As, Cu, Zn, Mn, Hg, and Pb
with Pb metal content had a higher concentrationcompared to other heavy metals which are around11 - 60 ppm [11].
Cd (mg/kg)

Cu (mg/kg)

Cr (mg/kg)

Pb (mg/kg)

Max. Cd

Max. Cu

Max. CrMax. Pb

4.00
3.50
3.00
2.50

3.000

2.00
1.50
Fe (mg/kg)

1.00

2.500
Mn (mg/kg)

0.50
Zn (mg/kg)

0.00

2.000

Area 1 Area 2 Area 3 Mean Area 4 Area 5 Area 6 Area 7 Area 8 Area 9 Area
Zone 1
10Max. FeArea
11

Area Mean
12 Zone 2

Max. Mn

1.500

Fig. 5 Concentration of Cd, Cu, Cr & Pb in the Rice

Max. Zn

1.000

Fe (mg/kg)

Mn (mg/kg)

Zn (mg/kg)

Max. FeMax. Mn

Max. Zn

30.00

0.500

25.00
20.00

0.000
Area 1 Area 2 Area 3 Mean Area 4 Area 5 Area 6 Area 7 Area 8 Area 9 Area 10 Area 11 Area 12 Mean
Zone 1
Zone 2

15.00
10.00

Fig. 4 Concentration of Fe, Mn, & Zn in the Water

5.00
0.00

Heavy Metals in the RiceArea 1 Area 2 Area 3 Mean Area 4 Area 5 Area 6 Area 7 Area 8 Area 9 Area
Zone 1
10

The concentrations of heavy metals in the rice
for Gunung Tugel dumpsite followed thedecreasing order of Fe>Cu>Zn>Mn>Pb>Cr>Cd.
Based on the results of the AAS test, concentrationsof Mn, Cr, and Zn did not obtain a single rice
sampling point that exceeded the maximum
allowable value. For the concentrations of Cu,
Pb, Fe, and Cd, there are several sampling points
whose values exceed the quality standard (See Fig.
3 & Fig. 4). Pb, found in the most sampling points
that exceeded the quality standard is likely to occur
due to the location of paddy fields in zone 2 close to
the landfill with irrigation flow entering zone 2
being
hit by a landslide from landfill so that leachate
containing heavy metals Zn, Cu, Fe, Co, Mn, Hg,
Cd, Pb, and Cr [10]. Entering the irrigation channel
and mixed with irrigation water, but apart fromcoming from irrigation water that has been buried
by landslides.
There is also a possibility that is caused by theuse of pesticides and TSP fertilizer used by farmers.
Excessive use of pesticides can also contribute to
the accumulation of heavy metals in agricultural

Area
11

Area Mean
12 Zone 2

Fig. 6 Concentration of Fe, Mn, & Zn in the Rice
Heavy Metals in the Cooked RiceThe concentrations of heavy metals in the
cooked rice for Gunung Tugel dumpsite followed
the decreasing order of Zn>Pb>Fe>Cu>Mn>Cr>Cd.
Based on the results of the AAS test, the Pb
concentration exceeds the quality standard that havebeen set at all sampling points. This can be possible
in the cooked rice accumulation of Pb metal fromwater and also cooked rice. It was found that theconcentration of Pb in zone 1 is higher than theconcentration of Pb in zone 2. It can be said that theaccumulation of rice by heavy metals Pb occurs
because there is already Pb metal in rice andaccumulates with Pb metal in hydrolyzed water
entirely when cooking rice so hydrolyzed water will
make the heavy metal enter and be absorbed entirely
into cooked rice. And there is also a possibility
because of the tools used to cook rice. For theconcentration of Cd and Zn, several sampling points
exceed the quality standard. As for the273

SEE - Kyoto, Japan, Nov.18-20, 2020

concentrations of Fe, Mn, Cr, and Cu, noconcentrations at all were found that exceeded thequality standard at all sampling points.

the Ministry of Health 2012 with reference Dose
(RfD) and Slope Factor (SF) values obtained fromUSEPA, WHO and USDOE IRIS (Integrated Risk
Information System) 2011. Exposure analysis is anevaluation of exposure to the organism, system, or
sub/population, and this exposure analysis is step 4
of Environmental Health Risk Analysis (EHRA).
While the calculation of risk characteristics itself isa qualitative and quantitative calculation which
includes the probability of potential adverse effects
from exposure to organisms, systems, or subpopulations to determine the level of risk whether
risk agents at certain concentrations will pose a riskof causing harm to the health of the community or
not.
Based on the calculation results in Fig. 6, it isfound that the concentrations of heavy metals Cr,
Cu, Mn, Fe, Zn, Cd have a safe risk value because
they have an RQ value of ≤ 0.2. While for heavy
metals Pb metal for adults, has a risk level value
which is not safe with an RQ risk level value ˃ 0.2.
The level of risk for carcinogenic effects isexpressed as Excess Cancer Risk (ECR). The levelof cancer risk is acceptable or safe if the ECR valueis ≤ E-4 (10-4) and is declared unacceptable orunsafe if the ECR value> E-4 (10-4). Based on theFig. 7 obtained for heavy metal Cd, children havethe potential to become cancerous cases because
they have an ECR value> E-4 (10-4).

12.00010.000

8.000

6.000

4.000

2.000

0.000
Area 1 Area 2 Area 3 Mean Area 4 Area 5 Area 6 Area 7 Area 8 Area 9 Area
Zone 1
10

Area
11

Area Mean
12 Zone 2

Cd (mg/kg)

Cu (mg/kg)

Cr (mg/kg)

Pb (mg/kg)

Fe (mg/kg)

Mn (mg/kg)

Zn (mg/kg)

Max. Cd

Max. Cu

Max. CrMax. Pb

Max. FeMax. Mn

Max. Zn

Fig. 7 Concentration of Heavy Metals in the Cooked
Rice
Estimation of Heavy Metal Intake
The path of heavy metal intakes can come fromvarious kinds, but in this study rice consumption is
the primary intake of heavy metals into the humanbody [12]. Heavy metal intake is estimated by thelevel of daily consumption with the metal content inrice [13].
Based on the results of interviews with residents
of agricultural land owners who are used forsampling it is estimated that in 1 day adults willconsume 170 g of rice / person / day, with anestimated adult weight of 55 kg and for children of
15 kg of the estimate based on Technical Guidelines
for Environmental Health Risk Analysis for 2012.
Duration time (Dt) for non-carcinogenic intakes is
estimated for 30 years for adults, and six years forchildren and carcinogenic Dt intakes for 70 years it
is based that for carcinogenic the effect that can becaused to be a symptom of cancer requires a long
duration to the symptoms of cancer, the value istaken based on the 2012 Technical Guidelines forEnvironmental Health Risk Analysis—used as anevaluation of daily intake and hazard quotient. In
calculating the estimated intake is done bycalculating the intake or exposure analysis and also
calculating the risk characteristics.
In this study, the path of exposure comes fromoral exposure (rice consumed by residents aroundthe Gunung Tugel Dumpsite) in the Guidelines forEnvironmental Health Risk Analysis [14], Ministryof Health 2012 called intake ingestion. In theestimation of intake estimates based on theEnvironmental Health Risk Analysis Guidelines,

Hazard Quotient (HQ) for2
Adult
Hazard Quotient (HQ) for
1.8
Children
1.6
Heavy Metal
concentration (mg / kg)
1.4
1.06151.2
10.77840.8
0.6
0.4
0.1484 0.0007
0.00430.002
0.09170.02020.0672 0.1088
0.2
0.0032 0.0014 0.0148
0.0006
0
Cr
Cd
Cu
Pb
Mn
Fe
Zn

Fig. 8 The level of Risk Quotient from all Heavy
Metals
4.00E-03
3.50E-03

Excess Cancer Risk (ECR)
for Adult

3.00E-03

Excess Cancer Risk (ECR)
for Children

3.43E-03

2.50E-03
2.00E-03
1.50E-03

3.16E-05

9.35E-04
5.04E-04
5.00E-04 1.38E-04
1.00E-03

1.16E-04

0.00E+00

Cr

Cd

Cu

Pb

Mn

Fe

Zn

Fig. 9 The level of Excess Cancer Risk (ECR) fromAll Heavy Metals
274

SEE - Kyoto, Japan, Nov.18-20, 2020

CONCLUSION

Problems of the Environment International
Council of Scientific Unions, Vol. 54, 1995, pp.
93-106.
[5] Chancy, R.L., Reeves, P.G. and Angle, J.S.,
Rice plant nutritional and human nutritional
characteristics role in human Cd toxicity,
In Plant Nutrition, Dordrecht, Springer, 2001,
pp. 288-289.
[6] Alam R., Ahmed Z. and Howladar M.F.,
Evaluation of heavy metal contamination inwater, soil and plant around the open landfill
site
Mogla
Bazar
in
Sylhet,Bangladesh. Groundwater for Sustainable
Development, Vol. 10, 2020, p. 100311.
[7] Bakar, A.A., Yoneda, M., Thuong, N.T. and
Mahmood, N.Z., Development of assessment
for potentially toxic element contamination
indicator in closed landfills and prospective
geostatistical analysis. International Journal of
GEOMATE, Vol. 17, Issue 60, 2019, pp. 136143.
[8] Kasam, Rahmawati S., Mulya Iresha, F.,
Wacano, D., Farida Fauziah, I. and Afif
Amrullah, M., Evaluation of Heavy Metal
Exposure to Soil and Paddy Plant around the
Closed Municipal Solid Waste Landfill: Case
Study at Gunung Tugel Landfill, BanyumasCentral Java. MS&E, Vol. 299, Issue 1, 2018,
p. 012012.
[9] Agency for Toxic Substances and Disease
Registry. Toxicological Profile For Cadmium.
United State : Department Of Health And
Human Services Public Health Service, 2012.
[10] Irhamni I., Serapan Logam Berat Esensial dan
Non Esensial pada Air Lindi TPA Kota Banda
Aceh Dalam Mewujudkan Pembangunan
Berkelanjutan.
JurnalSerambiEngineering, Vol. 2, Issue 1, 2017.
[11] Senesil G.S., Baldassarre G., Senesi N. andRadina B., Trace element inputs into soils byanthropogenic activities and implications forhuman health. Chemosphere, Vol. 39, Issue 2,
1999, pp. 343-377.
[12] Liu J., Hong Zhang, X., Tran, H., Wang Qiu,
D., Zhu Nian, Y., Heavy Metal Contamination
and Risk Assesment in Water, Paddy Soil, andRice Around and Electroplating Plant.
Environmnetal Science Pollution Research.
Vol. 18, 2011, pp. 1623-1632.
[13] Shimbo S., Zhang Z.W., Watanabe T.,
Nakatsuka
H.,
Matsuda-Inoguchi
N.,
Higashikawa K. and Ikeda M., Cadmium andlead contents in rice and other cereal products
in Japan in 1998–2000. Science of the total
environment, 281(1-3), 2001, pp.165-175.
[14] Kementrian Kesehatan. Pedoman Analisis
Risiko Kesehatan Lingkungan, 2012.

It was found that the concentration of heavy
metals in upstream zone (zone 2) has an average
higher than downstream zone (zone 1). This isfollowing the division of zones wherein zone 2, thedistance is closer to the landfill than zone 1 andaccording to the direction of the contaminant flow
it is directly flow to zone 2.
Based on the established quality standards forthe water, rice and cooked rice test samples
obtained consecutively the concentration of Cu, Cr,
Cd, Pb, Zn, Mn, and Fe are 33%, 28%, 58%, 78%,39%, 6%, 42% of sample points that exceed thequality standard of the total sample size. Based on
the test results obtained heavy metal concentrations
in rice samples are higher than heavy metal
concentrations in rice.
Obtaining the result of the calculation of risk
characteristics (RQ) on the prediction of adult Pb
metal risk having an RQ value> 1, it can beconcluded that there is a potential risk which isnecessary to control, and obtaining an ECR value
for the metal Cd of children> 10-4 , it can beconcluded that there is a potential to be a symptomof cancer.
ACKNOWLEDGEMENTS
The authors would like to acknowledge
Directorate of Research and Community Service,
Islamic University of Indonesia and Environmental
Risk Analysis Laboratory of Kyoto University forthe funding the research. Also, for Universitas Islam
Indonesia and students from the Banyumas landfill
group 2019. We also thank to Development
Planning Agency at Sub-National Level of
Banyumas Regency for the support of the current
condition data of the site and the permission for the
sampling activity.
REFERENCES[1] Tchobanoglous G., Theisen H., dan Vigil S. A.,
Integrated Solid Waste Management, UnitedStates : McGraw Hill International, 1993.
[2] SEPA, The Geological Barrier, Mineral Layer
and the Leachate Sealing and Drainage System,
Framework for Risk Assessment for Landfill
Sites, 2002.
[3] Hardy M. and Cornu S., Location of natural
trace elements in silty soils using particle-size
fractionation. Geoderma, Vol. 133, Issue 3-4,
2006, pp. 295-308.
[4] Mortvedt J.J. and Beaton J.D., Heavy metal andradionuclide contaminants in phosphate
fertilizers. Scope-scientific Committee on2756th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

DEVELOPMENT OF AN INTERACTIVE AND VISUALIZATIONSYSTEM FOR DETERMINING CLIMATE RISK
Makoto Ooba1, Takuya Togawa1, Ronald Canero Estoque1, Shogo Nakamura1, Takashi Tsuji1,
Akira Yoshioka1 and Yasuaki Hijioka1
1
National Institute for Environmental Studies, Japan
ABSTRACTIn its Fifth Assessment Report, the Intergovernmental Panel on Climate Change reported the seriousness ofclimate change and its future effects. Human society faces certain inevitable consequences without a plan foradapting to global climate change. A multi-sector collaboration to plan local adaptation is necessary because
climate change affects many sectors. Extreme rain events (hazard) may enhance the risk of river floods and are
related to river management, residential evacuation, traffic control, etc. To promote a multi-sector approach foradaptation planning, a visualization system for mapping climate change risk (Vulpes) was developed to suggest
adaptation policies at the local governmental level. The authors also developed an interactive method, i.e.,organizing workshops regarding local adaptation to climate change using the system. Such workshops have been
conducted for local policy makers as well as the staff of the regional center of climate change adaptation. These
workshops showcase the decrease in disaster risk, or changes in the ecosystem and the socio-economic system
resulting from regional climatic changes.
Keywords: Climate change, Adaptation, Multi-sector approach, Workshop, GIS (Geographical information
system)future risk and geographical extent of disaster.
Moreover, there is need for an interactive method toassess climate risk, such as workshops for local
adaptation to climate change.
The impact chain method is a major candidate
among the many assessment methods for risk.
Rather than a rigorous analysis of causal factors andtheir relationship in the impact process under climatechange, the impact chain method provides aqualitative assessment of risk through visualizationof the causal chain. GIZ [3] published a guidebook
on the development of the impact chain. In addition
to related quantitative assessment (calculation ofindicators and their integration), they recommended
risk communication, specifically by conducting
workshops with policy makers, administrators,
specialists, and stakeholders.
In this paper, first, climate risk is defined, after
which the interactive and the visualization systems
are explained. Then, workshops for creating impact
chains with policy makers are described. Finally, wesuggest the direction of risk assessment using theinteractive method.

INTRODUCTION
Around the world, including Japan, there isincreasing attention on risk assessment to climatechange. Climate change can impact not only one
sector, but several sectors simultaneously. For
example, an extreme rain event can cause not only
river flooding but also related disturbances such as
runoff of river water into agricultural land andresidential areas, as well as traffic hazards that may
cause serious disruption to the supply chain. The
Ministry of Environment of Japan (MOEJ) started
the promotion of local adaptation planning forclimate change at municipalities-level within Japan,
and the National Institute for Environmental Studies(NIES) conducts several studies and provides
information for the planning via A-PLAT [1] within
Japan, as well as for the Asia-Pacific region via APPLAT [2]. However, climate risk information is still
limited, especially on a detailed geographical scale,to be helpful for local assessment by municipalities.
In addition, at the municipality level, humanresources are also found to be lacking. While local
governmental bodies have conducted miscellaneousenvironmental tasks, climate risk assessment is not ahigh priority in local administration.
Visualization is a key factor in assessment andrecognizing climate risks that impact wide sectors.
Various data (biodiversity, ecosystem, andinfrastructure) and high geographical resolution(km-level) may aid visualization of the current and
276

SEE - Kyoto, Japan, Nov.18-20, 2020

Fig. 1 The definition of risk for climate change and components with examples (balloons)
Vulnerability is further divided into two risk
factors: sensitivity (lacking adjustment or coping)
and adaptation capacity.

METHODS
Concept of Climate Risk
In this paper, climate risk is defined as per thedefinition of IPCC AR5 (Fig. 1, [4]).
The risk consists of three risk components:
hazard (such as an extreme event: heavy or
extensive precipitation, very hot summer days, etc),
exposure (people, land, and goods), andvulnerability.

Visualization System
More detailed information such as higher
geographical resolution, larger amounts of data, andincreased multiple simulation of models (agricultural,
ecological, and geographical models) are helpful for

Fig. 2 The system for visualization of climate risk (Vulpes: Vulnerability Pluralistic Evaluation System)
277

SEE - Kyoto, Japan, Nov.18-20, 2020

the assessment of climate risk for multiple sectors.
Visualization of these data may also enhance nonspecialists’ imagination and interest in risk. The
Vulnerability Pluralistic Evaluation System (Vulpes)
was developed based on logic programming and theGeographical Information System (GIS) system.
Vulpes can load the impact chain that is coded bylogic programming and conduct an inference
according to the chain, and indicate geographicalresult on the GIS pane.

(prefectural level) and the other for environmental
policy officers of the municipality. Each workshop
had approximately 20 attendees who were divided
into three work groups.
In each group, a diagram of the impact chain wasdeveloped by identification of the intermediatefactors and risk complements with deep discussions
led by a facilitator. Prior to the group work,
information on local adaptation based on our system
and a workshop tutorial were presented.

Interactive Risk Assessment

RESULTS AND DISCUSSION

GIZ proposed assessment methods by using theimpact chain in nine steps [3]: (1) Preparation forassessment; (2) Development of the impact chain;(3) Identification and selection of risk indicators; (4–7) Data acquirement, estimation of the indicators,
and integration; (8) Indication and interpretation of
results; and (9) Identification of adaptation. Step (2)was directory adopted, while the other steps wererefereed to our methodology due to limitation of theworkshop time schedule.
Two types of workshops were held in 2019: onefor the staff of regional adaptation centers

Our assessment system for climate risk canmanage various types of data and actual diagrams ofimpact chain programmed by Prolog (Fig. 2).
In our workshops for development of impact
chains, natural disaster, water resources, andagriculture were covered. Heat shock in urban areas
was also discussed by a group in a workshop withenvironmental policy officers of municipality (Fig.
3). A diagram of impact chain consists of three risk
components (hazard, exposure, and vulnerability)
and intermediate factors. An intermediate factor iscorresponded to one or more vulnerability factors
and they can be grouped as: indoor living

Fig. 3 An example diagram of impact chain for heat health risk developed by the workshop
278

SEE - Kyoto, Japan, Nov.18-20, 2020

comfortability (air conditioner and introducing aliberal summer dress code), care of weak person toheat (such as an elderly person), monitoring andalert system for heat shock, consolidation of
emergency medical service, and mitigation of urban
heat island. Some factors were previously
considered by the group, and adaptation policies
were implemented to examine their vulnerability(living comfortability and alert system). However,other groups were not well recognized, and theattendees confirmed the need to install additional
effective adaptation policies. Several adaptation
policies needed the collaboration of wide-ranging
sectors, for example, by extending and rearranging
urban green spaces and preventing urban heatislands, which must be implemented by related
sections of administrators (agricultural manager,urban planner, environmental officer, etc.), scienceadvisors (urban meteorology, conservational ecology,etc.), and local residents.

originally listed from the limited time (less than twohours).
The current version of Vulpes is not
automatically connected between development of
impact chain in workshops and indication of risk
assessment: a diagram of the impact chain is
manually coded and input into the Vulpes system.
However, the forthcoming version of Vulpes will
support real-time development of the diagram anddisplay the assessment results in the GIS pane. This
full interactive system may accelerate deep
discussions of climate risk.

CONCLUSION[1] Ministry of the Environment Government of Japan (MOEJ)
and National Institute for Environmental Studies (NIES),
Climate Change Adaptation Information Platform (A-PLAT),
2018.http://www.adaptationplatform.nies.go.jp/en/index.html[2] Ministry of the Environment Government of Japan (MOEJ)
and National Institute for Environmental Studies (NIES),
Asia-Pacific Climate Change Adaptation Information
Platform(AP-PLAT),
2018.
http://www.adaptationplatform.nies.go.jp/en/ap-plat/index.html[3] GIZ, EURAC and UNU-EHS. Climate Risk Assessment for
Ecosystem-based Adaptation – A guidebook for planners andpractitioners. GIZ, 2018. Bonn.
[4] Intergovernmental Panel on Climate Change, IPCC Fifth
Assessment Report, WG2 Impacts, Adaptation, andVulnerability, 2014. https://www.ipcc.ch/report/ar5/

ACKNOWLEDGMENTS
This study was supported by the Environment
Research and Technology Development Fund (21708 and 2-2009, MOE, Japan). I also thank theresearch team of E-konzal corporation.
REFERENCES

Visualization of climate risk has strong appeal.
The system for visualization of local data and impact
chain (Vulpes) was well accepted even by nonspecialists in the workshops. Deep discussions forplanning adaptation are also effective in considering
the intermediate effects of climate change and final
risk, and the workshop for developing the impact
chain is a significant tool to enhance deep
discussions. In the workshop for officers of themunicipality, fifty three factors of intermediate
effect and forty two indicators of vulnerability were279

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

MEASURING TOD READINESS OF THE BANDAR LAMPUNG CITY
Aleksander Purba1, Aken Andha Runiawan2, Rahayu Sulistyorini3, Shahnaz Nabila Fuady4, Lusmeilia Afriani5,
Dikpride Despa6, Ratna Widyawati7, and Rosalia Dwi Werena8
1,5,6,7,8
Engineering Faculty, the University of Lampung, Indonesia
2,3,4
Urban and Regional Planning Study Program, Institut Teknologi Sumatera, Indonesia

ABSTRACT
Referring to the Bandar Lampung City Regulation Act No. 10/2011 concerning Regional Spatial Planning(2011-2030) emphasized that city government will develop an integrated activity center area at the mass public
transportation node through the concept of Transit Oriented Development (TOD) in Bandar Lampung City. In
article 20 explained more details of TOD location will be built and developed in the area of the transit station
Tanjung Karang. In preparing the development of the TOD area in the primary center, city government will prepare
the integration of bus services that implicates also on the provision of facilities for pedestrian. The steps undertaken
by city government are based on Ministerial Regulation Act of ATR/BPN No. 16/2017 concerning Guidelines forDevelopment of Transit-Oriented-Development which generally regulates the procedures for developing transitoriented areas based on specific criteria and characteristics. This paper explores the readiness of the Tanjung
Karang transit station as a TOD area using Calthorpe scheme, Indonesian guidelines and ITDP standard.
Measurement results indicate, the Tanjung Karang station not yet functioning as TOD. The main variables i.e.
walk, cycle, connect, transit, mix, densify, compact, and shift has been stated in the city Act, but there is no
implication in the field within surrounding area after almost ten years planned.
Keywords: TOD, Readiness, Procedure, Implication, Tanjung Karang
combination of mobility modes, at the lowest
financial and environmental cost, and with the highest
resilience to disruptive events. Inclusive TOD is anecessary foundation for long-term sustainability,
equity, shared prosperity, and civil peace in cities [2].
The Bandar Lampung city itself embarked on an
implementation step towards a transit-oriented city
through City Act's No. 10/2011 enacted Regional
Spatial Planning for period of 2011-2030 [3]. In
article 20 mentioned more detail that the area of TOD
will be built and developed in Tanjung Karang stationand surrounding areas. This paper explores the extent
of TOD's achievement of readiness, after a ten-yearplanning process since being declared by the city
government. This kind of step needs to be conducted
due to understanding the degree to which transit
corridors and station areas are potential places for
TOD helps public agencies implement TOD. To date,
the Metropolitan Council does not have a system forevaluating the potential for TOD along transit
corridors and within station areas. Instead, TOD
evaluation is typically performed on a project-byproject basis without considering the existing corridor
and station area [4].

INTRODUCTION
Currently, the Indonesian Government has begun
to implement more innovative strategies inaddressing rapid motorization issues in major cities
such as expressed by capital Jakarta by integrating
land development along MRT line. One of theinnovations applied is the Transit Oriented
Development (TOD) concept as a transit-based
development strategy. Transit Oriented Development
is at the very heart and soul of sustainability, andbrings together compact, walkable communities withhigh quality rail systems. This creates low carbon
lifestyles by enabling people to live, work, and playwithout depending on a car for mobility. This type oflifestyle can reduce energy consumption and driving
by up to 85% [1]. Based on long experiences indeveloped cities of developed countries, there are anumber of factors driving the trend toward TOD.
They are rapidly growing, mind-numbing traffic
congestion nation-wide, growing distaste for suburbia
and fry-pit strip development, growing desire for
quality urban lifestyle, growing desire for more
walkable lifestyles away from traffic, changes infamily structures: more singles, empty-nesters,
growing national support for smart growth,
respectively. TOD means integrated urban places
designed to bring people, activities, buildings, andpublic space together, with easy walking and cycling
connection between them and near-excellent transit
service to the rest of the city. It means inclusive
access for all to local and citywide opportunities andresources by the most efficient and healthful

METHODOLOGY
Bandar Lampung is the capital and largest city of
the Indonesian province of Lampung. Located on thesouthern tip of Sumatra, Bandar Lampung was
originally called Tanjungkarang–Telukbetung, since
it was a unification of two major settlements in
Lampung, before being renamed in 1983. Bandar

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SEE - Kyoto, Japan, Nov.18-20, 2020
Lampung or Tanjung Karang has become the thirddensest city in Sumatera, after Medan and
Palembang. The city's area is about 169.21 km², withan estimated population of 1,015,910 as of 2017.
Hence, the average density is 5,151 people/km2; thedensiest area is located in the Tanjung Karang Timur
district with density of about 24,549 people/km2,
while the Sukabumi district has density of 1,235
people/ km2. According to these figures, the Tanjung
Karang Timur district is near five times denser thanthe city average density and almost twenty times
higher compared to the lowest figure. Tanjung
Karang station itself is the terminus of the railway
service from Palembang, Baturaja, Blambangan
Umpu and Kotabumi although the railway trackcontinues all the way until Panjang harbor andTarahan coal offloading point at the southern end of
the city. The research scope includes a transit station
with a radius of 1 km as shown in Figure 1. Primarydata collection through field observation andinterview with a number stakeholder include railway
operator, city bus operator, city officers, and landdevelopers. Each country may have different ways interms of TOD standard and how elements or
attributes are set and measured. In Indonesia, thesteps undertaken by city government are based on
Ministerial Regulation Act of ATR/BPN No. 16/2017
concerning Guidelines for Development of TransitOriented-Development which generally regulates theprocedures for developing transit-oriented areas
based on specific criteria and characteristics [5].
According to Calthorpe [6], the concept of TOD is
simple: moderate and high-density housing, alongwith complementary public uses, jobs, retail andservices, are concentrated in mixed-use developments
at strategic points along the regional transit system. In
summary, the principles of TOD are to:• Organize growth on a regional level to be compact
and transit-supportive;• Place commercial, housing, jobs, parks, and civic
uses within walking distance of transit stops;• Create pedestrian-friendly street networks which
directly connect local destinations;• Provide a mix of housing types, densities, and costs;• Preserve sensitive habitat, riparian zones, and highquality open spaces;• Make public spaces the focus of building
orientation and neighborhood activity; and• Encourage infill and redevelopment along transit
corridors within existing neighborhoods

Fig. 1. Transit station and surrounding areas
Several years later after the Calthorpe’s concept,
the Institute for Transportation and Development
Policy (ITDP) developed TOD standard regarding
Principles of Urban Development for Transport in
Urban Life, and identifies the key concrete objectives

that are essential to implementing these principles inurban development. Hence, the TOD standard is aunique assessment tool available to score the plansand products of urban development according to theiradherence to the TOD principles and implementation

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SEE - Kyoto, Japan, Nov.18-20, 2020
objectives [7]. Furthermore, we perform syntheses
and simplification of variables and indicators andSourceCalthorpe (1993)Elem
entfunction

Regulation Act of
ATR/BP
N No.
16/2017

location

ITDP(2017)

physi
cal
envir
onme
nt

combined into the tool for measuring TOD readinessas shown in Table 1.

Table 1 TOD-forming variables
Variablecompact and transit-supportive
surrounding area within walking distanceof transit stops
street networks directly connect local
destinations
mix of housing types
high quality open spaces
public spaces the focus of building
orientation and neighborhood activity
infill and redevelopment along transit
corridors within existing neighborhoods
transitdisasterdirections in development
securewalkcycle

connecttransitmix

densifycompact
shift

Indicator

planning policy
function performs
function performs
type of housing
function performs
planning policy
planning policy
transit stop
intramode and intermodetransit services
vulnerability and disaster mitigation
compliance with spatial development
interference to state-owned vital
installations
walkways (3 points)
crosswalks (3 points)
visually active frontage (6 points)
physically permeable frontage (2 points)
shade & shelter (1 point)
cycle network (2 points)
cycle parking at transit stations (1 point)
cycle parking at buildings (1 point)
cycle access in buildings (1 point)
small blocks (8 points)
prioritized connectivity (2 points)
walk distance to transit
complementary uses (8 points)
access to local services (3 points)
access to parks and playgrounds (1)affordable housing (8 points)
housing preservation (3 points)
business services preservation (2 points)
non-residential density (7 points)
residential density (8 points)
urban site (8 points)
transit options (2 points)
off-street parking (8 points)
driveway density (1points)
roadway area (6 points)

transit station. Though, for station areas, strategies topromote TOD could therefore focus on increasing
density and improving walkability to match theiralready high mix. The characteristics of station areas
suggest a different set of strategies. Their urban
density is relatively high, but their transportation
supply is relatively low, suggesting that improving
the transit dimension is a more logical strategy topromote TOD there [8]. Based on field identification,

RESULT AND DISCUSSION
Functions of the Surrounding Area
The function of the TOD in terms of compact andtransit-supportive has been stated in the City Act
document, but has not yet seen the implementation
plan in the surrounding areas including theredevelopment plan of the pedestrian path to the282

SEE - Kyoto, Japan, Nov.18-20, 2020
Tanjung Karang station categorized as urban TOD
model, since the high-intensity commercial functions
already exist around the area. This type ofdevelopment includes the redevelopment site wherebuildings around the relatively are old and supporting
facilities require a massive revitalization. In different
cases, the condition of Tanjung Karang also
experienced other areas relatively developed by City
Region Arnhem and Nijmegen, where urban
development has high TOD levels, but has poortransit connections/the TOD levels are high but train
connections are further away than 800 m [9]. The
street networks directly connect local destinations is
not yet available in terms of length and its quality as
shown in Fig. 2. Referring to case study in Brisbane,
Australia, in comparison to people living in areas
classified as residential TODs, people who reside in

non-TOD clusters were significantly less likely to use
public transport (PT) (1.4 times), and active transport(4 times) compared to the car. People living in areas
classified as potential TODs were 1.3 times less likely
to use PT, and 2.5 times less likely to use active
transport compared to using the car. Only a little
difference in mode choice behaviour was evident
between people living in areas classified as residential
TODs and activity centre TODs [10]. The Brisbane
experience also takes place in Washington, D.C. and
Baltimore metropolitan areas: results indicate thatpeople living in TOD areas tend to drive less,reducing their VMT by around 38% in Washington,
D.C. and 21% in Baltimore, compared to the residentsof the non-TOD areas even with similar land use
patterns [11].

Fig. 2 Pathway network
Related to the existence of mix of housing types
in the study area has not been seen and not yet
available a high quality open spaces around thestation. According to available documents andinterview with city officials the redevelopment alongtransit corridors within existing neighborhoods does
not include a priority plan for the next few years.
Referring to Carlton and Fleissig [12], because TOD
planning is so often formulaic and based on
templates, land use plans may describe visions that do
not match market conditions. Unsophisticatedlandowners may hold onto land in spite of reasonablepurchase offers because they expect impending
development will increase their value.
Then, unrealistic prices can lead to frozen landmarkets, an inability to accumulate lots necessary fordevelopment, and stalled TOD investment. On theother hand, delaying longer implementations canresult in higher land prices, such as other city
experiences where TOD projects tend to cause anincrease in land value leading to gentrification anddisplacement. As a result, prioritizing social equity as
a key component of TOD implementation is an
essential pathway for achieving equitable solutions tosuch projects [13]. Table 2 shows the readiness levelof Tanjung Karang station referring to Calthorpe
scheme.
Table 2 Readiness level (Calthorpe)
Readinesslevel
Variable & Indicatoryes
no1. transit-supportivex
2. walking distance to transit stopsx
3. street connect destinationsx
4. mix housingx
5. high quality open spacex
6. building orientationx
7. redevelopment along transit
xcorridor

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SEE - Kyoto, Japan, Nov.18-20, 2020
1. Walk

TOD Location
As stated by Ministerial Regulation Act of
ATR/BPN No. 16/2017, the location or surroundingarea of TOD required satisfy the criteria and meet therequirements. They are transit, disaster, direction indevelopment, and secure, respectively. Transit
variable means that the Tanjung Karang has been
designated as a transit station in the city Act
document even though it is not fully ready to run its
functions due to various supporting facilities as atransit station is very limited after ten years of initialplanning. In the opinion of related stakeholders, thestation is relatively safe against possible disaster andsecure against criminality. As mentioned previously
the Tanjung Karang station has been designated as atransit-oriented development area in the city Act
document. This means that land developers andrailway operators must follow the instructions in the
document when developing projects around thestation. Referring to experiences in other cities,
centralizing housing and jobs along transitway
corridors is the best strategy to follow if increasing
regional accessibility is the goal. Particularly astrategy that focuses on targeted jobs centralization
along transitway corridors would have significant
payoffs. With a joint population and jobs
centralization along transitway corridors, increases inaccessibility as large as 7% are possible; by focusing
on jobs centralization alone gains of 4.5% can beachieved [14]. Since those variables the readiness of
TOD are widespread application, the end result is as
seen in Table 3.

2. Cycle3.
Connect
4.
Transit
5. Mix6.
Densify

7.
Compact
8. Shift

Table 3 Readiness level related location
Variable & Indicator

Readiness levelyes
no1. transit
a. Transit stopb. intramode and intermodec. transit services
2. disaster3. directions in development
4. securexx

Physical Environment
The ITDP method relatively easier to implement
since most of variables can be measured and observedin the TOD region although the final value set is not
fully objective depend on the observation of someone
which can differ from others for the same variable.
Table 4 shows the results of the TOD assessment
readiness referring to the ITDP method thatemphasizes the physical environment element.
Table 4 Readiness level of TOD (ITDP)
Variable

Indicator

Score

Max
Score

0
0
2

3
3
6

x
x
x

0

2

x

0
0
0

1
2
1

x
x
x

0

1

x

0

1

x

0
1

10
5

x
x

3

8

x

1

3

x

0

1

x

1

8

x

0

3

x

0

2

x

3

7

x

2

8

x

1
1
2

8
2
8

x
x
x

1

1

3
21

6
100

√
x

As seen in table 4, there are no variables in the
study area that meet the requirements if TOD
readiness measured based on the ITDP scheme. The
city bus services are already available since a few
years ago and pass the transit station, but service
quality of the bus is not reliable and without
timetable. Ideally, as Pavneet stated, comprehensiveplanning funded through the program must examine
ways to improve economic development andridership, foster multimodal connectivity andaccessibility, improve transit access for pedestrian
and bicycle traffic, engage the private sector, identify
infrastructure needs, and enable mixed-use
development near transit stations [15]. Moreover, as
the project was launched as a bicycle lane, cyclists
were expecting permanent infrastructure in the city
center, while the purpose of the project was leisurerather than transport. City officials tend to use theapparent a-political technical solutions in order togain legitimacy, placate social demands and minimize
political debates, as experienced by Curitiba [16].

√
√
√
√

a. walkways
b. crosswalks
c. visually active
frontaged. physicallypermeable
frontagee. shade & sheltera. cycle network
b. cycle parking
at transit stations
c. cycle parking
at buildings
d. cycle access inbuildings
a. small blocks
b. prioritized
connectivity
a. walk distanceto transit
a. complementaryuses
b. access to local
services
c. access to parks& playgrounds
d. affordable
housinge. housingpreservation
f. businessservicespreservation
a. non-residential
densityb. residential
densitya. urban siteb. transit options
a. off-street
parkingb. driveway
densityc. roadway area
Total

Readiness
Level
yes
no

284

SEE - Kyoto, Japan, Nov.18-20, 2020
Humphrey School of Public Affairs, 2018, pp. 1106.
[5] Ministerial Regulation Act of ATR/BPN No.
16/2017.
Availableat:https://www.atrbpn.go.id/Publikasi/PeraturanPerundangan/Peraturan-Menteri-ATR-KepalaBPN/peraturan-menteri-agraria-dan-tata-ruangkepala-badan-pertanahan-nasional-republikindonesia-nomor-16-tahun-2017-70794(inIndonesian)[6] Calthorpe, P., The Next American Metropolis:
Ecology, Community, and the American Dream,
Princeton Architectural Press, New York, 1993,
pp. 1-175.
[7] Institute for Transportation and Development
Policy.
Availableat:https://www.itdp.org/library/standards-andguides/tod3-0/the-tod-standard-scorecard/[8] Lyu, G., Bertolini, L., and Pfeffer, K., Developing
a TOD typology for Beijing metro station areas, J.
of Transport Geography, Vol. 55, 2016, pp. 40–
50.
[9] Singh, Y. J., Fard, P., Zuidgeest, M., Brussel, M.,
and Maarseveen, M., Measuring transit oriented
development: a spatial multi criteria assessment
approach for the City Region Arnhem andNijmegen, J. of Transport Geography, Vol. 35,
2014, pp. 130–143.
[10] Kamruzzaman, M., Baker, D., Washington, S.,
and Turrell, G., Advance transit oriented
development typology: case study in Brisbane,
Australia, J. of Transport Geography, Vol. 34,
2014, pp. 54–70.
[11] Nasri, A., and Zhang, L., The analysis of transitoriented development (TOD) in Washington,
D.C. and Baltimore metropolitan areas, J. of
Transport Policy, Vol. 32, Issue C, 2014, pp. 172179.
[12] Ian, C., and William, F., Steps to Avoid Stalled
Equitable TOD Projects, Living Cities, 2014, pp.
1-45.
[13] Beryl O., Measuring Equity in Transit-Oriented
Development: Application to Affordable
Housing, Sustainable Development: International
Policy and Management, Washington, DC, 2015,
pp. 1-115.
[14] Tilahun, N., and Fan, Y., Transit and job
accessibility: an empirical study of access tocompetitive clusters and regional growthstrategies for enhancing transit accessibility, J. of
Transport Policy, Vol. 33, 2014, pp. 17-25.
[15] Pavneet, K., Assessing Richmond Transit
Network Plan for Transit Oriented Development.
Greater Richmond Transit Company (GRTC),
2017, pp. 1-82.
[16] Duarte, F., Procopiuck, M., and Fujioka, K., No
bicycle lanes! Shouted the cyclists. A
controversial bicycle project in Curitiba, Brazil, J.
of Transport Policy, Vol. 32, 2014, pp. 180–185.
[17] Papa, E., and Bertolini, L., Accessibility andTransit-Oriented Development in European

CONCLUSION
This paper explores a number of variable in order
to measure the TOD readiness of Tanjung Karangtransit station using Calthorpe method, Indonesian
guidelines and ITDP scheme. As the result of
measurements vary, although the conclusion is thesame: Tanjung Karang Transit station not yet
functioning as TOD based on ITDP standard as
measurement tool commonly used in many countries.
The main variables i.e. walk, cycle, connect, transit,
mix, densify, compact, and shift has been stated in thecity Act, but there is no implication in the field withinsurrounding area after almost ten years planned.
Issues related to land-use and transport integration are
one of critical issues due to rapid motorization and assuggested by Papa and Bertolini [17], strengthening
the relationship between the railway network and land
uses is an effective measure for increasing cumulative
rail-based accessibility; improving railway network
connectivity is also important, but just increasing
densities is not. A key role is played by the correlation
between railway system connectivity values and landuse densities, what we term the TOD degree of theurban structure. Planners wishing to enhance thecumulative rail-based accessibility of an urban area
should primarily focus on transport and land use
interventions that improve this correlation. The
condition of Tanjung Karang station was experienced
by Beijing several years ago, related to policy at ahigher level of government which several aspects ofurban planning and development policies in Beijing
still prevent TOD from reaching a higher potential.
First, station orientation cannot be detected among
land parcels leased before station construction,
partially because developers tend to avoid the risk
associated with station location change. In addition,
station impacts are not significant in the new suburbs,
partially because of the municipal government’s
under-investment in transit and social services insuburbs. Furthermore, the Beijing city government
does not have an explicit policy statement toencourage higher density around transit stations [18].
REFERENCES[1] Transit Oriented Development Institute, US High

Speed Rail Association. Available at:
http://www.tod.org/sustainability.html[2] Institute for Transportation and Development
Policy.
Availableat:https://www.itdp.org/library/standards-andguides/tod3-0/what-is-tod/[3] City
Act No. 10/2011. Available at:https://peraturan.bpk.go.id/Home/Details/114606/perda-kota-bandar-lampung-no-10-tahun-2011(in Indonesian)[4] Frank, A., Joanne Cho, Y.J., Andrew, D., Ashley,
H., and Reed, S., THE TOD EVALUATIONMETHOD Evaluating TOD on Station Area andCorridor Scales, University of Minnesota

285

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metropolitan areas, J. of Transport Geography,
Vol. 47, 2015, pp. 70–83.
[18] Yang, J., Quan, J., Yan, B., and He, C., Urban rail
investment and transit-oriented development inBeijing: Can it reach a higher potential? J. of
Transportation Research Part A: Policy andPractice, Vol. 89, 2016, pp. 140–150.

286

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

SPATIAL VARIATIONS OF WATER QUALITY IN ACIDIC RIVER
BASINS OF NORTHEAST JAPANTakeshi Saito1 and Naoki Watanabe2
Graduate School of Science and Engineering, Saitama University, Japan; 2Research Institute for Natural
Hazards and Disaster Recovery, Niigata University, Japan

1

ABSTRACTIn Japan, there are some environmental issues related to acid mine drainage (AMD) and acidic hot springs
generally characterized by low pH values and relatively high concentrations of harmful elements such as As(arsenic) and Pb (lead). In this study, spatial variations of water quality parameters especially including pH andconcentrations of harmful elements were investigated in the Sukawa river basin (Yamagata Prefecture) and theTamagawa river basin (Akita Prefecture) that are located in volcanic areas of Northeast Japan. In the Sukawa
river basin with no specific neutralization treatments, the pH values ranged from 1.93 to 6.72 were observed
from the upstream to downstream, while in the Tamagawa river basin with neutralization treatment using
limestone, the pH values showed 1.2 to 6.93 from the upstream to downstream. The river acidity andconcentrations of As, Pb, and Zn (zinc) as harmful elements were markedly improved due to the dilution by themixing with other rivers and the associated coprecipitation with Fe (iron) and Al (aluminum) hydroxides.
Especially, effect of the neutralization on the improvement of water quality was probably more significant in the
Tamagawa river basin.
Keywords: Water quality, pH, Harmful elements, Acidic river basins, Northeast Japan, Neutralizationand one of the most effective and common
neutralizers is limestone, which is a limited natural
resource. Therefore, the authors are trying to findappropriate alternative neutralizers selected fromwaste materials. It is highly important to investigate
and clarify spatial variations of water quality inacidic river basins as fundamental knowledge todevelop effective alternative neutralizers when they
are applied to acidic rivers. The objective of thisstudy is to investigate spatial variations of water
quality parameters especially including pH andconcentrations of harmful elements in the Sukawa(Yamagata Prefecture) and Tamagawa (Akita
Prefecture) river basins which are famous acidic
river basins located in volcanic areas of Northeast
Japan.

INTRODUCTION
Acid mine drainage (AMD) is generally
characterized by low pH values and relatively highconcentrations of harmful elements. Especially inJapan, there are also many acidic hot springs which
represent almost the same characteristics with theAMD. These acidic waters are typically produced by
the natural oxidation of sulfide minerals and often
contain harmful elements such as As (arsenic) andPb (lead) [1-3].
In the acidic river basins which are formed byreceiving the acidic waters, there are some possible
negative
impactsonsurrounding
naturalenvironment and human activity including thedegradation of infrastructures, the incompatibility
for agricultural water usage, and adverse effect on
the biosphere. Therefore, large-scale water
treatments are sometimes applied in the upstream of
the acidic river basins. For example, in the Kusatsu
hot spring as one of the most famous acidic hot
springs in Japan located in the upstream of theAgatsuma river basin (Gunma Prefecture),
neutralization treatment using limestone has been
applied over 50 years [4, 5]. The positive effect of
the treatment on the river acidity and concentrationsof harmful elements was clearly observed in aprevious study [6].
The neutralization treatment is essential toreduce the acidity and concentrations of harmful
elements, however, the treatment needs a high cost

MATERIALS AND METHODS
Study Areas
The Sukawa river basin in Yamagata Prefecture
and the Tamagawa river basin in Akita Prefecture
which are located in volcanic areas of Northeast
Japan were selected for investigating spatial
variations of water quality (Fig. 1).
In the Sukawa river basin, a total of 8 sampling
locations were selected. Field investigation was
performed in November 2018 and May 2019. In the
Tamagawa river basin, a total of 10 sampling
locations were selected. Field investigation was
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SEE - Kyoto, Japan, Nov.18-20, 2020

carried out in July 2018. These sampling locations
are shown in Fig. 1.

The Zao hot spring as one of the most famous
acidic hot springs in Japan is in the upstream of the
Sukawa river. For the discharged water from the Zao
hot spring, the pH and EC values in November 2018
were 1.93 and 5730 µS/cm, respectively. A closed
sulfur mine is located in the upstream of the
Zaougawa river that is also an acidic river. These
two acidic rivers discharge to the mainstream of the
Sukawa river and it (the mainstream) finally flows
into the Mogami river which is one of the biggest
rivers in Japan. Even under these acidic conditions,
there are no specific neutralization treatments
applied in the Sukawa river basin. In the following
section, variations of water quality along the Sukawa
river basin are discussed based on the data of 5
sampling locations as shown in Fig. 2.

Field investigation and water quality analysis
In-situ measurements of water temperature, pH,
and electric conductivity (EC) were conducted using
a portable analyzer (WM-32EP, DKK-TOA
CORPORATION, Japan) calibrated precisely before
each field investigation.
The river water was immediately filtered using a
0.20 µm membrane filter (DISMIC-25CS, Toyo
Roshi Kaisha, Ltd., Japan) and the following water
quality parameters were analyzed in the laboratory.
Major cations (Na+, NH 4 +, K+, Mg2+, and Ca2+) andanions (F-, Cl-, NO 3 -, and SO 4 2-), dissolved
inorganic carbon (DIC), and heavy metals and othertrace elements including harmful elements (Li, Al:
aluminum, Si, Cr, Mn, Fe: iron, Ni, Cu, Zn: zinc, As,
Se, Sr, Cd, and Pb) were analyzed using an ion
chromatograph (ICS-1500, Nippon Dionex K.K.,
Japan), TOC (total organic carbon) analyzer (TOCV CSH, SHIMADZU CORPORATION, Japan), and
ICP (inductivity coupled plasma)-MS (massspectrometer)(ICPM-8500,
SHIMADZUCORPORATION, Japan) or atomic absorption
spectrophotometer(AA-6200,SHIMADZUCORPORATION, Japan), respectively. For the DIC,
there are mainly three chemical forms of H 2 CO 3 ,HCO 3 -, and CO 3 2-. Because the relative abundance
ratios depend highly on the pH in water [7], theconcentration of HCO 3 - was estimated using pH,
ionic strength, activity coefficient, and equilibrium
constant in this study.

Fig. 1

Fig. 2

Study area of the Sukawa river basin.
Orange circles show water sampling
locations. The base map was downloaded
from Google Maps.

Figure 3 shows variations of pH, EC, andconcentrations of Fe, Al, As, Pb, and Zn as water
quality parameters from the upstream to downstream
along the Sukawa river basin. In the mainstream of
the Sukawa river before discharge of the acidic
water from the Zao hot spring and the Zaougawa
river, the pH and EC values in November 2018 were
6.18 and 242 µS/cm, respectively (not shown in theFig. 3). After the inflow of the acidic water, the pH
dramatically decreased to 2.95 and the EC increased
to 748 µS/cm at the sampling location as “Sukawa
river (middle stream)” in Fig. 3. In the downstreamof the Sukawa river (shown as “Sukawa river(downstream)” in Fig. 3) before flowing into the
Mogami river, the pH still showed a slightly acidic
value of 5.40 and the EC value was 353 µS/cm.
Finally, the pH showed an almost neutral value of
6.72 and the EC value was 165.5 µS/cm after
flowing into the Mogami river at the sampling
location as “Mogami river” in Fig. 3.
For behaviors of harmful elements, As was
detected only in the Zaougawa river, however,Study areas of the Sukawa river basin in
Yamagata Prefecture and the Tamagawa
river basin in Akita Prefecture, Northeast
Japan. Orange circles show water sampling
locations. The base map was downloaded
from Google Maps.

RESULTS AND DISCUSSION
Spatial variations of water quality in the Sukawa
river basin

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SEE - Kyoto, Japan, Nov.18-20, 2020

relatively high concentration of Zn was found atalmost all the sampling locations. The Zn
concentration gradually decreased with decrease inboth Fe and Al concentrations. Especially in thedownstream of the Sukawa river, all these elements
showed significantly low concentrations at the
sampling location as “Sukawa river (downstream)”in Fig. 3. Saito and Watanabe (2020) [6]investigated variations of water quality along theAgatsuma and Nagase (Fukushima Prefecture) river
basins as famous acidic river basins in Japan. Thisprevious study suggested that harmful elements such
as As and Pb were probably coprecipitated with the
Fe and Al hydroxides due to increase in the pH
values. Because the Fe hydroxides were at least
found in the river bed of the Sukawa river basin,
harmful elements including Zn were suggested to becoprecipitated with the hydroxides. Finally, at the
sampling location as “Mogami river” in Fig. 3, allthese elements were not detected.
Considering all observation results, the river
acidity and concentrations of harmful elements in
the Sukawa river basin were significantly improved
due to the dilution by the mixing with other rivers
and the associated coprecipitation with Fe and Al
hydroxides
without
specific
neutralization
treatments.

Fig. 3

The Tamagawa hot spring as the strongest acidic
hot spring in Japan is located in the upstream of theTamagawa river basin. Based on a previous study,
the pH value is usually around 1.2 [8]. The
discharged acidic water flows into the Shibukuro
river and the water in the Shibukuro river is
continuously neutralized using limestone. In thefollowing section, variations of water quality along
the Tamagawa river basin are discussed based on thedata of 7 sampling locations as shown in Fig. 4.

Fig. 4

Study area of the Tamagawa river basin.
Orange circles show water sampling
locations. The base map was downloaded
from Google Maps.

Figure 5 shows variations of pH, EC, andconcentrations of Fe, Al, As, Pb, and Zn as water
quality parameters from the upstream to downstream
along the Tamagawa river basin. Before theneutralization treatment, the pH and EC values in
July 2018 were 2.42 and 2100 µS/cm, respectively,
at the sampling location as “Shibukuro river (before
neutralization)” in Fig. 5. After the neutralization
treatment, the pH increased to 2.99 and the EC
slightly decreased to 1421 µS/cm at the sampling
location as “Shibukuro river (after neutralization)”in Fig. 5. Finally, the pH showed an almost neutral
value of 6.93 and the EC value was 68.5 µS/cm inthe downstream of the Tamagawa river (at the
sampling location as “Tamagawa river (downstream)”in Fig. 5) before flowing into the Omono river whichbroadly flows in Southern Akita Prefecture.
Harmful elements, As, Pb, and Zn were detectedwith high concentrations in the upstream of theTamagawa river before flowing into the Tamagawa
dam (shown as “Tamagawa dam” in Fig. 5). The
neutralized acidic water is sufficiently mixed in thedam and the water in the dam is gradually released
to the Tamagawa river. Therefore, these harmful
elements were not generally detected. Also, Fe andAl were not detected even at the sampling location
as “Tamagawa river (middle stream) in Fig. 5”. As
previously discussed, in the Sukawa river basin, Zn
as one of harmful elements might be coprecipitated

Variations of pH, EC, and concentrations of
Fe, Al, As, Pb, and Zn from the upstream todownstream along the Sukawa river basin.
Water sampling locations correspond to
Fig. 2.

Spatial variations of water quality in the
Tamagawa river basin

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with Fe and Al hydroxides due to increase in the pH
values. In the Tamagawa river basin, at least Fehydroxides were clearly found in the river bed
before flowing into the Tamagawa dam. Harmful
elements, As, Pb, and Zn were also suggested to becoprecipitated with the hydroxides.
As observed in the Sukawa river basin, the river
acidity and concentrations of harmful elements wereclearly improved by the dilution effect and therelated coprecipitation with the Fe and Al
hydroxides. Especially, effect of the neutralizationon the improvement of water quality was probably
more significant in the Tamagawa river basin.

other rivers and the associated coprecipitation with
Fe and Al hydroxides in the river basin.
In the Tamagawa river basin with neutralization
treatment using limestone, the pH values ranged
from around 1.2 to 6.93 were observed from the
upstream to downstream. Harmful elements, As, Pb,
and Zn were detected with high concentrations in the
upstream of the river basin. Similarly observed in
the Sukawa river, the river acidity andconcentrations of As, Pb, and Zn were clearly
improved by the dilution effect and the related
coprecipitation with the Fe and Al hydroxides.
Especially, effect of the neutralization on the
improvement of water quality was probably moresignificant in the river basin.
ACKNOWLEDGMENTS
This study was supported from a Grant-in Aid
for Scientific Research (no. 26889015) by the Japan
Society for the Promotion of Science, a research
grant by JFE 21st Century Foundation, ISIJ
Research Promotion Grant by the Iron and SteelInstitute of Japan, and the Collaborative Research
Project (2017-17, 2018-13-, 2019-15, and 2020-12)
by the Research Institute for Natural Hazards andDisaster Recovery, Niigata University, Japan. Water
quality analysis was partly conducted by the support
from Joint Research Grant for the Environmental
Isotope Study of Research Institute for Humanity
and Nature (RIHN), Japan. The authors deeply
appreciate Professor Ichiro Tayasu, Dr. Ki-Cheol
Shin, and Dr. Shiho Yabusaki all of RIHN forsupporting the water quality analysis.
REFERENCES

Fig. 5

Variations of pH, EC, and concentrations of
Fe, Al, As, Pb, and Zn from the upstream todownstream along the Tamagawa river
basin. Water sampling locations correspondto Fig. 4.

[1] Akcil A. and Koldas S., Acid Mine Drainage(AMD): Causes, treatment and case studies.
Journal of Cleaner Production, Vol. 14, Issue 1213, 2006, pp.1139-1145.
[2] Herrera S.P., Uchiyama H., Igarashi T., Asakura
K., Ochi Y., Ishizuka F. and Kawada S., Acid
mine drainage treatment through a two-stepneutralization ferrite-formation process innorthern Japan: Physical and chemical
characterization of the sludge. Minerals
Engineering, Vol. 20, Issue 14, 2007, pp.13091314.
[3] Nieto J.M., Sarmiento A.M., Olías M., Canovas
C.R., Riba I., Kalman J. and Dlvalls T. A., Acid
mine drainage pollution in the Tinto and Odiel
rivers (Iberian Pyrite Belt, SW Spain) andbioavailability of the transported metals to the
Huelva Estuary. Environment International, Vol.
33, Issue 4, 2007, pp.445-455.
[4] Kikawada Y., Kawai S., Shimada K. and Oi T.,
Arsenic originating in Kusatsu hot springs,
Gunma, Japan, and arsenic pollution status of

CONCLUSIONS
Spatial variations of water quality parameters
including pH and concentrations of harmful
elements were investigated in the Sukawa river basinin Yamagata Prefecture and the Tamagawa river
basin in Akita Prefecture which are located in
volcanic areas of Northeast Japan.
In the Sukawa river basin with no specificneutralization treatments applied, observed pH
values were in the range of 1.93 to 6.72 from the
upstream to downstream. Harmful elements, As andPb, which are regulated by environmental criteria,
were not detected, however, relatively highconcentration of Zn was detected. The river acidity
and the Zn concentration were significantly
improved due to the dilution by the mixing with
290

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Kusatu rivers. Journal of Disaster Research, Vol.
3, Issue 4, 2008, pp.261-269.
[5] Mitsuya D., Hayashi T., Wang Y., Tanaka M.,
Okai M., Ishida M. and Urano N., Isolation of
aquatic yeasts with the ability to neutralize acidic
media, from an extremely acidic river near
Japan’s Kusatsu-Shirane Volcano. Journal of
Bioscience and Bioengineering, Vol. 123, Issue 1,
2017, pp.43-46.
[6] Saito T. and Watanabe N., VARIATIONS OF
WATER QUALITY ALONG ACIDIC RIVERS
IN VOLCANIC AREAS OF EASTERN JAPAN.
International Journal of GEOMATE, Vol. 19,

Issue 71, 2020, pp.36-41.
[7] Weathers K.C., Strayer D.L. and Likens G.E.,
Fundamentals of Ecosystem Science. Academic
Press, New York, USA, 2013.
[8] Sasaki S., Narita, S., Kikuchi, Y. and Fuda, K.,
Intake of As and Cr Atoms into SchwertmanniteLike Sediment at the Neutralization Treatment
Plant for Tamagawa Hot Spring Acidic Water.
Journal of Japan Society on Water Environment,
Vol. 36, Issue 5, 2013, pp.137-141 (in Japanesewith English abstract).

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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

OIL/WATER SEPARATION TECHNIQUES USINGHYDROPHOBIZED/OLEOPHILIZED GRAINS: A REVIEW OFRECENT STUDIES
Akihiro Matsuno1, Zafar Muhammad Junaid1, Takeshi Saito1, Huyen Thi Thanh Dang2, Pham Thanh
Huyen3, Tran Thi Viet Nga2 and Ken Kawamoto1,2
1
Graduate School of Science and Engineering, Saitama University, Japan; 2 National University of Civil
Engineering, Vietnam; 3 Hanoi University of Science and Technology, Vietnam
ABSTRACT
Many domestic sources and industries such as foods, textiles, metal industries, petrochemicals, and mining
produce massive volume of oily wastewater all over the world. Especially, the insufficient treatment of oily
wastewater in developing countries lead a serious environmental pollution. To treat oily wastewater, manytechniques such as flotation, chemical coagulation, biological treatment, filtration and membrane separation, andadsorption have been developed. Among them, the oil/water separation techniques based on adsorption andfiltration utilizing natural hydrophilic sands and hydrophobized/oleophilized grains are worth being paid attention
due to the ease of application and cost effectiveness. In this review, we have summarized the recent studies on theadsorption- and filtration-based oil/water separation utilizing natural hydrophilic sands and grains coated/modified
with hydrophobic/oleophilic substances and compared the treatment performance, categorizing types of grains,coating substances, used oil, and testing methods. Prospects and challenges on the oil/water separation studies arealso given.
Keywords: Oily wastewater, Oil/water separation, Hydrophobized/oleophilized grains, Adsorption, Filtration
INTRODUCTION

contains 480 - 7,782 mg/L, and wastewater/fluids
from metalworking contain 20 - 200,000 mg/L [5].
Thus, the treatment of oily wastewater has been
obliged all over the world and permissible levels ofoil and grease are regulated before discharging thetreated effluents to the environment. For example,
Water Pollution Prevention Act (1970) of Japan
regulates the maximum permissible levels of treatedwater discharge are 5 mg/L for mineral oil and 30
mg/L for animal and vegetable oil. In Vietnam, thepermissible levels of animal and vegetable oil andgrease in domestic wastewater range between 10 - 20
mg/L in QCVN 14:2008/BTNMT, depending on thedestination of discharge.
In recent years, many techniques of oily
wastewater such as flotation, coagulation, chemicaltreatment, gravity separation, biological treatment,
filtration and membrane separation, and adsorption
have been developed [6]. Among of them, theoil/water separation techniques based on adsorption
and filtration have been progressed by using various
types of materials such as membrane, mesh, film,
porous media, grains (powders), and so on. For theoil/water separation, not only using naturalhydrophilic/oleophobic
(vice
versa
naturalhydrophobic/oleophilic) materials but also thesynthetic materials with hydrophobic/oleophilic
substances can be applied to improve the surfacehydrophobicity/oleophilicity [7]–[10]. Althoughvarious types of oil/water separation techniques have

The discharge of massive volumes of oily
wastewater due to the rapid industrialization,
unplanned
urbanization,
andagriculturaldevelopment over the last few decades has led toserious impact to environment and human health [1].
Especially, insufficient treatment and inadequate
disposal of oily wastewater generated from humanactivities and industries such as petrochemical, foodprocessing, textiles, and metal industries, mining,biopharmaceuticals, and oil and gas refineries as wellas oil-spill accidents are causing serious waterpollution in developing countries. These negative
phenomena in endangering aquatic life significantly
affect human health, living nature, and naturalenvironment, finally induces substantial economic
losses [2].
In general, oil (as well as grease) in wastewater
exists as various forms such as free and floating oil,dispersed oil (emulsified with surfactant and/or
mechanically), and dissolved oil. The concentrationsin oil and grease in wastewater are highly dependent
on the sources of wastewater. Typical concentrationof oil and grease in untreated domestic wastewater
ranges 50 - 150 mg/L [3]–[4]. On the other hand, it
has been well known that industrial activities generate
wide range of oil and grease concentrations: e.g.,
oilfield-produced water contains 2 - 565 mg/L,
wastewater generated from vegetable oil factories
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been reported, the further development of costeffective and environmentally friendly (e.g., use ofrecyclable/reusable materials) methods are required
especially to treat large volumes of oily wastewaterwith high efficiency [11].
Among the oil/water separation techniques basedon adsorption and filtration, the utilization of naturalhydrophilic sands and hydrophobized/oleophilized
grains are of the most interest due to the ease of
application and their cost effectiveness. In this study,
we especially reviewed on the recent progress on theutilization of natural hydrophilic sands andhydrophobized / oleophilized grains for the oil/water
separation techniques and compared the treatment
performance, categorizing types of grains, coating
substances, used oil, and testing methods.

tested grain sizes ranged < 1 mm and mostly around
0.2 mm that is a typical boundary between fine sandand medium sand in the fields of GeotechnicalEngineering and Soil Science.
is
used
to
characterizetheCAahydrophobicity/oleophilicity of grain surface andCAo is used to characterize the hydrophilicity/
oleophobicity of grain surface. The relationshipbetween measured CAa/CAo and the grain size areplotted in Fig. 1. The contact angles with > 150o are
identified as materials with “superhydrophobic/
superoleophilic” surface or “superhydrophilic/superoleophobic” surface [23]. The measured CAa
and CAo were dependent on the tested oils, but, mostof the tested grain surfaces became > 150o, indicatingthat the tested grains were categorized as“superhydrophobicity / superoleophilicity” or“superhydrophilicity /superoleophobicity”. However,it has been reported that the grain size and geometry
affected the water repellent characteristics ofhydrophobized grains [24]. Thus, the effects of grain
size geometry on the surface are needed to assess
carefully for selecting suitable materials for theoil/water separation techniques.

METHODOLOGY
Data review was based on the keywords such as
oil/water separation, oily wastewater, hydrophobicity(oleophilicity),hydrophilicity(oleophobicity),hydrophobized/oleophilized grains, adsorption, andfiltration. Tens of journal papers, books, and reports
published in English after 2000’s were searched inthis study [e.g., Web of ScienceTM (Clarivate
Analytics)]. After checking the searched literaturesfrom the viewpoint of the utilizations ofhydrophobized/oleophilized grains for the oil/water
separation have been chosen, a total of 11 literatures
was selected to summarize and compare the data.

Used Oils for Oil/Water Separation Studies
As shown in Table 1, various types of oils such as
gasoline, diesel, crude oil, vegetable oils (soybean
cotton seed, rapeseed and so on) including so-called
volatile organic compounds (VOCs) such as
petroleum ether, hexane, and chloroform were used
depending on the purposes of studies. Besides, both“oil in water” and “water in oil” were used and bothconcentration (given in mg/L or mL/L in Table 1) andoil/water ratio (given in O/W in Table 1) were used in
the oil/water separation studies

RESULTS AND DISCUSSION
Table 1 summarizes the oil/water separation
techniques utilizing natural hydrophilic sands andhydrophobized/oleophilized grains, categorizing
types of grains, coating substances, measured contact
angle of water in air (CAa) and contact angle of oil inwater (CAo), used oil and concentration (or oil/water
ratio), testing methods, and separation efficiency
and/or separation capacity. The oil/water separation
techniques are classified into two types: one is theadsorption-based technique and the other is thefiltration-based technique.

Testing Methods and Separation Efficiency for
Oil/Water Separation Studies
Basically, all reported studies on both adsorptionbased and filtration-based gave a good oil/water
separation performance. For the adsorption-based
techniques using batch and mixing methods, theadsorption/adhesion capacities ranged between 110
to 500 mg/g. Atta [14] reported that the adsorption
capacity of crude oil was increased from 160(uncoated silica particles) to 500 mg/g after thecoating of grain surface. Bigui [15] reported that theadsorption capacities of hydrophobized quartz sands
increased 54% for engine oil and 45% for rapeseedoil compared to those of uncoated quartz sands. For
the filtration-based techniques, the gravity-driven
method was commonly used to assess the separation
efficiency and capacity. The separation capacity wasvalidated based on the performance under repeatedseparation tests (i.e., cycles).

Types of Grains and Measured Contact Angles
For both adsorption-based and filtration-based
oil/water separation techniques, sand materials weregenerally used for the oil/water separation techniques
except for [22]. This is because the sand materials areeasy-available, low-cost, and nontoxicity toenvironment [16]. Among of the sand materials,
quartz sand was commonly used for fabricatinghydrophobicity/oleophilicity on the grain surface [13],[15], [20], [21], and natural desert sand was used forthe filtration-based oil/water separation due to its
surface hydrophilicity/oleophobicity [17]– [19]. The
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Table 1 Oil/water separation techniques utilizing natural hydrophilic sands and hydrophobized/oleophilized grains.
Grains/sands
Coating(size in mm)
substances
Adsorption-based
Silica particles 1,7-octadiene(~0.4)
monomer
Quartz sand
ODTS, ZnO
(0.55-0.83)
nanoparticles
Sand
TEOS, VTS
(0.1-0.25)
Quartz sandChitosan, SiO2
(0.6-0.9)
nanoparticles
Filtration-based

CAa / CAo (o)CAa = 129-144
CAa = 150-154

Used oil*Motor oil, crude oil,kerosene
Engine oil, rapeseedoil, and so on

CAa = 140-170

Crude oil

CAo = 152

Engine oil, rapeseedoil

Oil concentration
or O/W
20 g/L
(in water)
N.C.
20 mL/L(in seawater)
N.C.

MethodSeparation efficiency (in %)and/or separation capacity**

Batch(4 g solid to 80 mL oil)
Mixing(10 g solid to 5 mL oil)
Mixing(Sand : oil = 1:1, 1:2, 1:10)
Mixing(20 g solid to 100 mL oil)> 99 %
330-500 mg/g
96.5-99.7 %180-380 mg/g
80-92 % (Coating substances:
sand = 1:2)
~ 280 mg/g (Engine oil)~ 110 mg/g (Rapeseed oil)Sand(0.1-0.5)

ODTS

CAa = 155

Hexadecane,chloroform

O/W = 5:3
(in volume)

Gravity-driven withvacuum (Oil: chloroform)

Desert sand(0.13-0.27)(Non-coating)CAo = 146-152

Decane, sesame oil,crude oil, diesel oil,and so on

N.C.

Gravity-driven(Oil: petroleum ether)

Desert sand(> 0.05)(Non-coating)CAo = 112***(CAa = 0)

Diesel, petroleum
ether, and so on

O/W = 50:1
(in volume)

Gravity-driven(Porosity: 79.6%)

High separation capacity was
kept even after 5 cycles ofseparation
High separation capacity
depending on the thickness sandlayer
> 99.8% (Separation capacity
was maintained even after 10cycles of separation)

Ref.
[12]
[13]
[14]
[15]

[16]
[17]
[18]

Desert sandCu(OH)2
O/W = 2:1
CAa = 158
1,2-dichloroethane
Gravity-driven
Up to 99.5 %[19](0.1-0.2)
nano-needles(in volume)
Quartz sand17.3 mg/L
IDT, 3-MPS
N.D.
Gasoline engine oil
Steady effluent flow rate
74-87 % (in the first 9 hours)[20](0.55-0.83)(in water)
Quartz sand
HMDS
Xylene, chloroform,
O/W = 1:1
97-98 % (96 % even after 50
CAo = 154
Gravity-driven[21](0.1-0.3)(nano silica)
diesel oil(in weight)
cycles of separation)
Quartz sandChitosan, SiO2
O/W = 1:19
Gravity-driven
CAo = 152
Engine oil~ 100 %
[15]
(0.6-0.9)
nanoparticles(in weight)(Porosity: 45%)
Waste brick
N.C. (water-in-oil~ 98 % (Separation capacity
Soybean oil,
Gravity-driven
grainsand oil-in-water
was kept even after 10 cycles of [22](Non-coating)CAo = 146
hexane, and so on(Porosity: 47%)
(0.1-0.4)
emulsions)separation)***
Note: Used oil including volatile organic compounds (VOCs). Capacity: Adsorbed amount of oil / grains (g/g) was given for the adsorption-based technique. Applicablerange and observed performance of oil/water separation were given for the filtration-based technique. ***CAo was read by the figure in the literature.
[Abbreviations] CAa: Contact angle of water in air (o), CAo: Contact angle of oil in water (o), HMDS: 1,1,1,3,3,3-hexamethyldisilazane, IDT: Isopropyl dioleic(dioctylphosphate) titanate, N.C.: Not controlled (used as it) or not clarified, N.D.: Not determined, ODTS: Octadecyltrichlorosilane, O/W: Oil/water ratio, TEOS:
Tetraethoxysilane, VTS: Vinyltrimethoxysilane, 3-MPS: 3-methacryloxypropyltrimethoxysilane
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SEE - Kyoto, Japan, Nov.18-20, 2020(a)Fig. 1(b)  

Relationship between grain size and (a) contact angle of water in air (CAa) and (b) Contact angle ofoil in water (CAo).

CONCLUSIONS AND PROSPECTS

ACKNOWLEDGMENTS

In this paper, recent studies and progress on theoil/water separation techniques based on adsorption
and filtration utilizing natural hydrophilic sands andhydrophobized/oleophilized grains were reviewed.
All reviewed literatures performed well and gave highoil/water separation efficiency and capacity throughthe laboratory tests. Most of the studies used sands as
tested grains. It is worth to note that Li [22] used thegrains from waste clay brick (origin fromconstruction waste). In addition, Shi [25] utilized
waste brick powders for coating membrane for theoil/water separation. Junaid [26] assessed the water
repellency for hydrophobized autoclaved aerated
concrete grains originated from the scrap ofconstruction materials. Those harmless wastematerials and industrial by-products should be
encouraged to utilize for the oil/water separation
techniques from the viewpoints of reuse and recycleof waste, sustainability, and green development.
With regard to the practical applications of tested
studies to the actual treatment of oily wastewater, notonly the assessment of the grain size and coating
substances but also the examination of suitable
packed density (porosity) and flowing conditions ofoily wastewater such as line velocity, hydraulicretention time, and mass transport analysis undercontinuous flowing condition are important. Further
studies and challenges are necessary to evaluate theperformance of oil/water separation techniques
utilizing those natural hydrophilic sands andhydrophobized/oleophilized grains fully considering
the packed density and flowing conditions.

This research was supported by JST-JICA
Science and Technology Research Partnership for
Sustainable Development (SATREPS) project (No.
JPMJSA1701).
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124, 2021 "In press".

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6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

HEAVY METAL CHARACTERISTICS OF WASTEWATER FROMBATIK INDUSTRY IN YOGYAKARTA AREA, INDONESIA
Any Juliani1, Suphia Rahmawati2 and Minoru Yoneda1
1Department of Environmental Engineering, Kyoto University, Japan;
2 Faculty of Civil Engineering and Planning, Universitas Islam Indonesia, Indonesia

ABSTRACT
Batik is a traditional Indonesian textile product with a unique production method. It involves the applicationof wax in its multiple coloring stages. The application of synthetic dyes in batik production raises concern on
heavy metal content in its wastewater. As wastewater from most factories is released to the environment without
proper treatment, the pollutants including heavy metal content would pose health risks to humans and theenvironment. However, data on heavy metal characteristics of wastewater from batik industry in Indonesia is very
limited. This paper presents the heavy metal characteristic of 17 (seventeen) samples of wastewater from batik
factories in Yogyakarta Area, Indonesia. The total concentration of Cr, Co, Ni, Cu, As, Cd, and Pb were measured
by using inductively-coupled plasma mass spectrophotometry (ICP-MS). The concentration of Cr, Co, Ni, Cu, As,
Cd, and Pb ranged from 9.87 to 101 ppb, 0.03 to 3.89 ppb, 5.37 to 82.8 ppb, 19.7 to 472 ppb, 1.46 to 21.2 ppb,
0.03 to 20.3 ppb and 0.78 to 40.1 ppb respectively. Hierarchical Cluster Analysis (HCA) was then performed toobserve group of samples or parameter with similar characteristics that represent similar production method which
affects their wastewater characteristics. This would be the basis for risk assessment which can further be used todevelop appropriate measures to control negative impact of batik industry to human and environment. However,
the result indicates that other factors may affect the heavy metal concentration in batik wastewater which demands
further study.

Keywords: Batik Wastewater, Heavy Metal, Cluster Analysis, Risk Assessment

metals are part of organic-based coloring dyes toenhance its absorption to fabrics or at least present
as impurities of dyes [7] [9]. Various heavy metal
including Cd, Pb, Fe, Cu, Zn, Al, Mn, Mg, Ca, Cr
and Si were detected in batik wastewater sample
from Batik factory in Malaysia with similar
production method as that is used in Indonesia [1][7]. The concentration for each element of heavy
metal varies according to production stage[1].
In Indonesia, batik is produced mostly by middle
to small scale industries which are categorized ashome industry. One characteristic of home industries
is their limited capacity in various aspects including
occupational and environment health management.
Factory workers are being exposed to chemicals
involved in the production process with minimum
personal protection equipment. On the other hand,batik wastewater from most factories are released toenvironment without proper treatment. While manybatik factories are located in vicinity to housing
areas, this improperly handling of wastewater may
release pollutants to soil and groundwater. A study
conducted by Syuhadah, et.al showed a strong
positive correlation between concentration of heavy
metals measured in soil and plants surrounding abatik factory and heavy metal concentration in
effluents from that particular batik factory [7]. This
would pose health risk to human from direct use and

INTRODUCTION
Batik is a traditional Indonesian textile product,
although it is also developed in Malaysia [1]. Batik
industry is an important economic sector inIndonesia. In 2019, export of batik products fromIndonesia reached US$ 52.4 million. It is asignificant number as compared to US$ 442 billionof textile product global market value of the same
year [2].
Batik production method differs from common
method used in textile industries. It involves theapplication of wax in its multiple coloring stages. A
two colored batik sheet will require two times
coloring stages. A three colored would require threetimes coloring stages, and so on. Part of the motive
which is not intended to have the first color would
be covered by wax to undergo the dyeing process ofthe first color. Afterward, the wax is removed andthe process continues to the second coloring process
by using the same method.
The application of wax, dye and also fixing
agents in batik production results in wastewater
characteristic of high pH, organic content (COD,BOD), total suspended solids (TSS) and color
intensity [3]–[6]. Similar to the general textile
wastewater, there is also concern on possible heavy
metal content in batik wastewater[1],[7],[8]. Heavy
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exposure to contaminated soil, water bodies andgroundwater. To develop appropriate measure tocontrol this negative impact, risk based approachthrough risk assessment can be applied. Risk
assessment consists of four generic steps, namely, (i)hazard identification, (ii) hazard assessment, (iii)
exposure assessment, and (iv) risk characterization[10]. In the case of batik industry, hazard
identification as the first step of risk assessment canbe conducted through characterization of the sourceof hazard. In this case, it is wastewater. However,data on heavy metal characteristic of wastewaterfrom batik industry in Indonesia is limited mostly toconcentration of total Chromium (Cr), as it is the
only heavy metal parameter regulated by Indonesia
national standard[11]. On the other hand, study on
batik wastewater are mostly focused on thedevelopment of treatment technology [12]–[14]. No
study had been conducted to assess the risk can beposed by present wastewater handling to theenvironment and human health. This paper presents
the heavy metal characteristic of 17 samples ofwastewater from batik factories in Yogyakarta Area
as one of the center of batik industries in Indonesia
as the initial phase of the risk assessment of batik
industry in study area.

Wastewater samples for this study were takenfrom batik factories located in Yogyakarta City andBantul Regency (Fig.1). Samples were collected inpolypropylene (PP) bottles. Parameter pH was
measured on site by using Multiparameter Water
Quality Checker Horiba U-50. Samples for heavy
metal analysis were acidified with concentrated
HNO 3 (grade for heavy metal measurement, 65%,
Merck) until pH<2 for preservation. All samples
were kept in 4° C until analysis.
Samples were wastewater after dyeing (step 4)
and wax removal process (step 5) of batik production
as referred to Fig. 2. Table 1 presents from which
production process by referring to Fig.2 and type ofdye used in the factories where the samples weretaken from.
Table 1 Source of samples
Sample
Code
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
X14
X15
X16
X17

MATERIALS AND METHODS
Study Sites and SamplingSpecial Region of Yogyakarta is one ofprovincial administrative area of Indonesia. It is
located in Java Island, bordered by the Indian Ocean
in the south and sharing land border with Central
Java Province. It consists of four regencies, namely:
Bantul, Sleman, Kulonprogo and Gunungkidul, andone city, Yogyakarta City as the capital [15]–[17].

Source ofProcess
After step 4
After step 5
After step 4
After step 5
After step 4
After step 4
After step 4
After step 4
After step 4
After step 5
After step 5
After step 4
After step 4
After step 4
After step 5
After step 5
After step 4

Type of dyes usedby factory
Naphtol
Naphtol
Naphtol
Naphtol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Remasol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, Indigosol
Naphtol, IndigosolFig. 1 Indonesia region (top), Special Region of Yogyakarta(middle),study area (bottom)
Samples
Analysis299

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Inductively Coupled Plasma Mass Spectrometry(ICP-MS) was used to analyze heavy metal content
in the samples. Prior to analysis, samples werepretreated following a modification of EPA method
3015A for microwave assisted acid digestion. Acid
mixture of HNO 3 (grade for heavy metal
measurement, 61 %, Wako Chemical ) and HCl (3537%, Wako Chemical) were added to samples withthe ratio of 9:1 and digested in laboratory microwave
oven (CEM type MARS 6 using Easy Prep Plus
vessel type). Digestion was set to 800 psi pressureand 200°C temperature held for 15 minutes with
ramping time of 15 minutes. Digested samples werethen filtered by using 0.45 µm cellulose acetate
membrane filter. Prior to measurement, filteredsamples were diluted with 1 N HNO 3 solution.
Standard solutions were prepared by dilution ofstandard stock (Wako Chemical) of each elementswith 1 N HNO 3 solution. Isotopes used formeasurement were 52Cr, 59Co, 60Ni, 63Cu, 75As, 111Cd
and 208Pb. Internal standard 89Y and 115In were used
to ensure stability during measurement. Limit ofdetection (LoD) for Cr, Co, Ni, Cu, As, Cd, and Pb
were 0.18, 0.05, 0.31, 0.82, 0.07, 0.05, and 0.06 ppb
respectively.
Heavy metal in textile related wastewater isassociated with dyes which generally are organic
compound [7]. Therefore, in addition to heavy metal,organic content in samples was also measured
through analysis of Total Organic Carbon (TOC). It
was conducted by using TOC analyzer type TOC-V
CSN by Shimadzu. Samples were diluted andfiltered to remove particulate prior to measurement.
Standard solution for TOC measurement was
prepared by using KHP (C 8 H 5 KO 4 , 99.8-100.2%,
Wako Chemical) which was dried and then diluted
with milli-Q water to prepare necessary
concentration of standard solutions.

RESULTS AND DISCUSSIONS
Batik Production Process
In general, there are 2 types of batik which are
differentiated by the device used to apply wax on thecloth. The first type is hand painted batik in which a
pen like device is used during wax application.
Another type is called stamping batik in which a big
stamp like device is used for wax application. The
stamp is made of copper with usually a 20 x 20 cm2
size. Basically, both types are produced through theprocess described in Fig.2.
1. Cloth is soaked in water for softening
2. Cloth is soaked in boiling water and thenwashed with detergent and dried
3. Batik craftsman will handpaint the motif byusing wax to part of motif which will be left
uncolored
4. Coloring process by soaking the wax
painted cloth in the first color. Fixation agent
and other chemical are also used to enhance
the color intensity
5. Wax removal process by heating up thewax using hot water and then scrapping or
sponging off the remaining wax afterwards
Fig. 2 Batik production process
Step 3-5 will be repeated according to the numberof colour would be applied on each production. A“canting” is used in step 3 for hand painted type,while a “cap” is used in stamp batik making process.
Chemical used during process consists of wax,
colouring agent both natural or synthetic and fixation
agent. Some most commonly used chemical are aspresented in Table 3.

Statistical Analysis
Statistical analysis was conducted by using R
software version 4.0.0 [18]. By using Mardia Test in“MVN” Package [19], it was checked that the data
was multivariate normal after logarithmictransformation. Then, Hierarchical Cluster Analysis(HCA) was performed to group the samples by using
Ward’s linkage method [18]. To ensurecomparability among datasets, standardization was
performed
beforeclustering.
Dendrogramvisualization of HCA was performed by using“factoextra” Package [20].

Table 2 Most common chemical used in batik
industry [21]DyeNaphtolRemasolNat./Syn.*)
Syn.
Syn.

Indigosol
Syn.
Indigofera
Nat.
Teger, Jambal,
Nat.
Tingi, Mahoganyskin*) Nat. = natural ; Syn. = synthetic
300

Fixation agent
Diazonium-salt
Water
glass
(Na 2 (SiO 2 ) n O)
H 2 SO 4 , HCl
Air(K 2 (SO 4 ) 2 ),(FeSO 4 ),(CaOH 2 )

SEE - Kyoto, Japan, Nov.18-20, 2020

effluent according to both regulations is 1 ppm.
Compared to both standards, no sample exceed Cr
maximum concentration. Compared to effluent
standard in other countries such as Japan and
Malaysia, concentration of heavy metal in all
samples are also still below standard. Table 4
presents comparison of wastewater data to thesestandards.
As only Cr which is regulated for batik effluent
standard in Indonesia, data on heavy metal content
in batik wastewater in Indonesia was mostly limited
to this parameter as reported by [11] and [22]. Thesestudies reported the Cr concentration in batik
wastewater samples taken from factories in
Banyumas, Central Java Region and Sidoarjo, EastJava Region respectively. Syahputra, et.al. [12]reported concentration of Cr6+ and Pb in batik
wastewater taken from one factory in Yogyakarta,
the same area with this study. Data on other heavy
metal elements in batik wastewater was from batik
factories in Malaysia as reported by [1] and [7].
These studies reported heavy metal concentration in,samples taken from batik factories in Kelantan,
Malaysia. Other heavy metal elements of Fe, Zn, Al,
Mn, Mg, Ca, and Si with concentration of 3.0, 0.29,
12, 0.02, 0.97, 4.23, and 8965 ppm respectively werealso reported in [1]. Compared to other studies,
heavy metal concentration in samples in this study isrelatively lower.

Laboratory Analysis Result
Total concentration of some heavy metalelements including Cr, Co, Ni, Cu, As, Cd, Pb as
well as pH and Total Organic Carbon (TOC) arepresented in Table 4.
Table 3 Descriptive statistics of laboratory analysis
resultParameter
Cr (ppb)
Co (ppb)
Ni (ppb)
Cu (ppb)
As (ppb)
Cd (ppb)
Pb (ppb)
pH
TOC (g/L)

Min.
9.87
0.03
5.37
19.7
1.46
0.03
0.78
6.21
1.25

Max.
101
3.89
82.8
472
21.2
20.3
40.1
11.1
13.6

Mean
36.9
2.05
27.2
120
6.49
3.79
14.5
8.83
3.47

SD
25.0
1.14
22.6
110
5.93
5.34
11.7
1.62
3.11

Heavy metal parameter which is being regulated
in Minister of Environment Regulation No.5/2014
on textile wastewater effluent standard and Local
Regulation of Yogyakarta Special Region
No.7/2016 on Effluent standard for batik industry in
Yogyakarta Special Region is only Total Chromium(Cr). The maximum Cr concentration in batik

Table 4 Comparison of maximum concentration in samples (ppm) to effluent standards of Indonesia, Japan and
Malaysia and to other studies

Effluent Standard
A. Indonesia
Local 1)
National 2)
B. Japan
B 1)
B 2)
C. Malaysia
C 1)
C 2)
Max. conc. in sample
Dewi, et.al [11]Syahputra, et.al [12]Suprihatin, et.al [22]Moradi, et.al. [1]Syuhadah, et.al. [7]Site A
Site B
Site C

Cr

Cr6+

Cr3+

Cu

Ni

As

Cd

Co

Pb

1.0
1.0

-

-

-

-

-

-

-

-

2

0.5
-

-

3

-

0.1
-

0.03
-

-

0.1
-

0.01
1.1
0.06
0.08

0.05
0.05
0.16
-

0.20
1.0
-

0.20
1.0
0.47
0.29

0.20
1.0
0.08
-

0.05
0.10
0.02
-

0.01
0.02
0.02
-

0.00
-

0.10
0.5
0.04
0.47
0.04

0.00
0.00
0.00

-

-

0.19
0.57
0.02

-

-

0.01
0.01
0.00

-

0.16
0.34
0.47

A 1) Indonesian Minister of Environment Regulation No.5/2014
A 2) Local Regulation of Yogyakarta Special Region No.7/2016
B 1) Japan Standard for the protection of human health
B 2) Japan Standard for the protection of living environmentC 1) Malaysia Standard A: if discharged to inland waters within catchment areas
C 2) Malaysia Standard B: if discharged into other inlands waters or Malaysian waters

301

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Concentration were varied as showed in Table 3
Based on their standard deviation (SD), Cu had thehighest variation among all measured metalelements followed by Cr, Ni, Pb, As, Cd and Co
respectively. The same order was also applied to the
distribution of heavy metal among samples which is
Cu>Cr>Ni>Pb>As>Cd>Co. Cu had given thehighest concentration compared to other elements.
Studies conducted by [1] and [7] presents data on
heavy metal concentration in batik wastewater
following distribution order of Cu>Cr>Pb andCu>Pb>Cd>Cr respectively. Compared with these 2other studies, data in this study is consistent as Cu
gives the highest concentration. Cu along with Cr, Ni
and Co are predominant element for metal complex
azo dyes [23] [24]. Included in azo dyes is naphtol
which is commonly used in batik industry.

is represented in dendrogram that other heavy metalelements belong to different cluster than Cu, Ni and
Cr. On the other hand, the sample cluster
dendrogram shows that sample X17 and X4 are themost similar. However, sample X17 and X4 camefrom different production stage and X17 also usedindigosol dye instead of only napthol like that of X4.
This indicates factors other than the type of dye andproduction
stage
that
affectwastewater
characteristic. Also similar to textile wastewater,
composition of batik wastewater may vary among
factories due to variation of type of fabric, chemicals
other than dyes, quality of water and equipment used
for production [25].
CONCLUSIONS
Analysis on 17 (seventeen) wastewater samples
from batik factories in Yogyakarta Region showedvariation among elements and samples. The
concentration of Cr, Co, Ni, Cu, As, Cd, and Pb
ranged from 9.87 to 101 ppb, 0.03 to 3.89 ppb, 5.37
to 82.8 ppb, 19.7 to 472 ppb, 1.46 to 21.2 ppb, 0.03
to 20.3 ppb and 0.78 to 40.1 ppb respectively.
Hierarchical Cluster Analysis (HCA) produced
dendrograms showing cluster of strong similarity
among parameters Ni, Cr and Cu which indicatesthat the source of these metals is from dyes. HCA
also indicates that other factors may affect the heavy
metal content in batik wastewater which should beclarified through further study.

Hierarchical Cluster Analysis
Hierarchical Cluster Analysis (HCA) was
performed to classify samples and parameters into
different clusters. Two dendrograms were produced
showing clusters of samples and parameters aspresented in Fig. 3.
Parameter cluster dendrogram shows that Ni
and Cr belongs to the same cluster with the lowest
dissimilarity. These parameters also in the samecluster with Cu with higher dissimilarity. This may
indicate the Ni, Cr and Cu content in effluent werefrom the same source. Cr, Cu, Ni along with Co aresaid to be predominant element for metal complex
azo dyes [23] [24] which are the type of dyes mostly
used in batik production. Similar
totextilewastewater, other source of heavy metals in batik
wastewater can be from impurities of chemical usedin different stages of production processes [25]. This

ACKNOWLEDGMENTS
This research was supported by Indonesia
Endowment Fund for Education and Department ofEnvironmental Engineering, Kyoto University.

Fig. 3 Dendrogram of Hierarchical Cluster Analysis (HCA) among parameters (left) and samples (right)

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303

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

CONSUMER REVIEW WEBSITE-BASED APPLICATION TO
DETERMINE POPULARITY INDEX AND SPATIAL DISTRIBUTION
OF RESTAURANTS IN BANDUNG
Dewi Susiloningtyas, Syarifah Salma A’idah, Febiana Nur Azizah, and Iqbal Putut Ash Shidiq
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia

ABSTRACT
Consumer review website (CRW) is a web-based type of platform that provides information on one’s
perspective. In this case, the information provided is a review of a particular object. This information can be used
as a spatial database because the object being assessed has spatial attributes in the form of geotagging. One formof CRW is the Zomato application, which provides information on ratings of various types of dining objects (cafes,
fine dining, quick bites, stalls). This study utilizes attribute data available in the Zomato application to map the
spatial distribution of the restaurant's popularity index in the city of Semarang. The popularity index is built basedon the rating of consumers of a restaurant. This study utilizes the application program interface (API) owned by
Zomato to get restaurant location data and rating attributes. The popularity index value is divided into three groupclassifications: high, medium, and low popularity. Using the Geographic Information System (GIS), eachclassification can be analyzed to see what factors are the differentiators of each restaurant classification. By using
Nearest Neighbor Analysis (NNA) and Kernel Density Analysis (KDA), it is known that each classification has adifferent distribution pattern.
Keywords: CRW, Popularity index, Restaurant, Spatial distribution, NNA

restaurants in the form of ratings and written reviews.
Ranking (popularity index) is subjective and could bemade based on the food, service, price, location, andenvironment of a particular restaurant [4]. This
popularity index can be displayed or illustrated basedon the ranking and distribution of restaurants in aregion.
Human perspectives, such as reviews or thoughts,
could have been influenced by the so-called ‘spatial
cognition’ of a particular individual. It is a cognitive
process of gathering and manipulating information
about the nature of the spatial environment andutilizing them in the adaptive process of decision
making [5],[6]. Therefore this study aims todetermine and map the spatial distribution patterns ofrestaurants in Bandung based on their popularity
index and to find out what factors that are influencing
the distribution patterns.

INTRODUCTION
In this digital age, communication andinformation technology are increasingly advanced.
With the growing popularity of the internet among the
public, a review has become an essential source indetermining the quality of a product that will end in
the consumer's decision before purchasing certain
goods [1]. The reviews obtained are no longer
discussed by word of mouth (WoM) but through avery diverse social media (e-WoM). Consumers canregularly obtain product reviews from online sellers,
product websites, blogs, and third-party review
platforms where consumers can participate andengage in discussions about their consumption
experiences [2]. This consumer review platform or
consumer review website (CRW) is now widely usedby consumers as their reference in choosing products
are following the quality they desired. Nevertheless,for choosing the place to eat, many consumers rely on
CRW to choose the restaurant or restaurant that theywant to visit.
Bandung is a city with many exciting tourist
attractions, including food and beverage tourism, or
what is commonly referred to as culinary tourism [3].
With the number of places to eat (restaurants) in
Bandung, many tourists are following the reviews
from the CRW platforms to choose their place to eat.
One of the websites or applications providing
consumer reviews for a restaurant is Zomato. Zomato
provides information about consumer’s reviews on

METHODS
Most of the secondary data are gathered from
Zomato (www.zomato.com). The informationcollected from the secondary data is the attributes ofa particular restaurant, such as location (latitude andlongitude), popularity index, type of restaurant, andtypes of food served by the restaurant. The
geographic information system (GIS) analysis arebeing utilized to map and to describe the spatial
distribution of restaurant based on their popularity
index. A cross-tabulation and statistical analysis are
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SEE - Kyoto, Japan, Nov.18-20, 2020

employed to explain which factor is affecting themost.

network data are being classified as arterial andcollector roads (Figure 2). This data was obtained
from Open Street Map (www.openstreetmap.org).

Study Area
Table 1 Categories of restaurant’s popularity index
The study is located in the city of Bandung.
Bandung City is the capital of West Java Province,
Indonesia, which has an area of 167.31 km2 anddivided into 30 sub-districts, covering 151 subdistricts (Figure 1). The city of Bandung has apopulation of 2,507,888 inhabitants in 2019.
Bandung has many attractions that attract tourists tocome to visits, such as nature and culinary tourism.

Fig. 1

Popularity index< 2.9
3 – 3.9>4

Category
Low
AverageHigh

Fig. 2

The artery and collector road networks in thecity of Bandung.

Fig. 3Distribution of hotels and malls in the city ofBandung.

Study area located in the city of Bandung.

Materials
Some materials used in this study were gatheredfrom the secondary source. Those materials were
essential to answer the research questions and to build
the hypothesis prior to the conclusions. Thosematerials are related to the popularity index,
accessibility, and urban functional units.
Popularity index
The popularity index was obtained from theZomato website (www.zomato.com). Zomato uses
index values ranging from one to five based on
consumer reviews. The thing that also takes into
account is the credibility of these consumers.
Furtherly, the popularity index is being categorized
into three classes (Table 1).
Accessibility
Urban functional unit
Accessibility is one of the factors that is suspected
will affect the distribution of restaurants.
Accessibility is representing the distance between therestaurant and the road networks. Furtherly, the road

Urban functional units are the geographical units
consisting of various interrelated elements in a citythat are intended to provide space for people's lives,
305

SEE - Kyoto, Japan, Nov.18-20, 2020

production, recreation, and business activities, andprovide a pleasant living environment and form an
exchange platform [7]. Examples of this functional
unit are malls, hotels, offices, hospitals, and banks.
This study only limits the urban functionals unit tomalls and hotels (Figure 3). Mall and hotel data are
obtained from the Open Street Map. In addition, thecentral business district (CBD) can also influence the
distribution of this restaurant. CBD data wereobtained from Colliers International Indonesia Research.
Land-use
Land use can affect the distribution of restaurant
popularity related to the type of land use that is at thelocation of the restaurant. The type of land use usedin this study is the type that has functions forsettlement, business, social and culture, and tourism.

Fig. 4

Location of restaurants based on the
popularity index.

Fig. 5

Number of restaurants on each sub-district.

Fig. 6

Number of restaurants based on popularity
level.

Data Processing and Data Analysis
Spatial distribution analysis
The analysis was performed using the Nearest
Neighbor Analysis (NNA) and Kernel Density
Analysis (KDA) methods. NNA is used to determine
what distribution patterns are formed, for example, bygrouping, spreading, or random. KDA is used todetermine the density of existing restaurants per unitof a particular region. These NNA and KDA analyses
are being performed using GIS software.
Distance analysis
The distance analysis that will be carried out inthis study includes the employment of NEAR tools
using GIS software. This analysis is to observe
variations in the distance between restaurants andurban functional units (hotels, malls, and CBD). The
distance between the restaurant and urban functional
unit suspected to have an influence on the restaurant’s
popularity index. The NEAR tool from GIS softwareis being utilized to measure the distance. The crosstabular analysis is used to measure the relationshipbetween restaurant locations, accessibility, and urban
functional units.
RESULTS AND DISCUSSIONSDistribution of Restaurants in Bandung City
In total, there are 4078 restaurants across Bandung
City. This study has collected 980 locations ofrestaurants, with all of them are having the popularity
index in their attribute (Figure 4). Most of therestaurants are located in the center of Bandung City,
from which large groups of average-popularity
restaurants have occurred.

Figure 4 shows a clustered type of restaurant
distribution, especially in the city center. Based on thedata, Bandung Wetan is the sub-district with asignificant number of indexed restaurants in Bandung
City (Figure 5). According to several studies,
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SEE - Kyoto, Japan, Nov.18-20, 2020

Bandung Wetan sub-district is one of the iconic
places in Bandung with many clothing and crafting
stores filled with creative workers and designers. The
need to find a comfortable place for working andchanneling their creative minds are becoming thefactor behind the rapid growth of cafés andrestaurants [8],[9]. Based on the popularity level, it is
known that most of the restaurants are in averagepopularity, in which the rating score ranges from 3 to
3.9 (Figure 6).

popularity. The NNA analysis proves it, which shows
the z-score value of -27.9306. Based on the z-score,
the type of distribution of the average-popularity
restaurants is clustered (Figure 9). The KDA for
average-popularity restaurant shows a slightly
different result, where the highest density occurred in
Sukajadi. The highest density class shows that there
are probably more than 144 average-popularity
restaurants per km2 (Figure 10).

Restaurant’s Popularity Distribution
High popularity restaurants
NearestNeighbor Ratio:
0.643428
z-score: 8.071280
p-value:
0.000000HighPop/ Km2< 24,27231158
24,27231159 - 46,01625737
46,01625738 - 78,88501264> 78,88501265

Fig. 8Nearest Neighbor
Ratio:
0.454758
z-score: 27.930592
p-value: 0.000000

Given the z-score of -8.07128012599, there is a less than 1%
likelihood that this clustered pattern could be the result of random
chanceFig. 7

KDA result for high-popularity restaurants
in Bandung.

NNA result for high-popularity restaurants
in Bandung.

Restaurants with a high-popularity index have aclustering pattern around the center of Bandung. The
NNA analysis proves it, which shows the z-scorevalue of -8.0713. Based on the z-score, thedistribution type of the high-popularity restaurants isclustered (Figure 7). The KDA analysis shows asimilar result where the highest density of the highpopularity restaurants found in Bandung Wetan.
Based on the KDA, the highest density shows that
there are probably more than 78 high-popularity
restaurants per km2 (Figure 8).
Average popularity restaurants

Given the z-score of -27.9305921725, there is a less than 1%
likelihood that this clustered pattern could be the result of random
chanceRestaurants with an average-popularity index arealso having a clustering pattern located in Bandung
City Center. Restaurants with this category are mostdominant among restaurants with low- and high-Fig. 9307

NNA
resultforaverage-popularity
restaurants in Bandung.

SEE - Kyoto, Japan, Nov.18-20, 2020clusters found in Sukajadi, Coblong, andBatununggal (Figure 12). Those areas are slightly far
from the city center. The highest density class showsthat there are probably more than 36 low-popularity
restaurants per km2 (Figure 12).

AvgPop/ Km2< 36,10622254
72,21244508 - 108,3186676
108,3186677 - 144,4248901> 144,4248902

LowPop/ Km2< 9,041282655

Fig. 10 KDA
resultforaverage-popularity
restaurants in Bandung.

18,08256532 - 27,12384796
27,12384797 - 36,16513062

Nearest Neighbor
Ratio:
0.649388
z-score: 7.438917
p-value: 0.000000> 36,16513063

Fig. 12 KDA result for low-popularity restaurants in
Bandung.
Distance Analysis
Distance could play a significant role when it
comes to someone’s preferences. The relative
locations or the distance between the restaurant toother specific entities might influence people's
perspectives on how they will rate the restaurant. Zhai
et al. [10] suggested that the restaurants with highpopularity were closed to urban functional units,
whereas those with low popularity were at a faraway
distance. It was supported by the study from Habib etal. [11], who suggested that a well-reputed restaurant
will have less interest if far away. This study tries to
examine whether the distance is related to therestaurant’s popularity. A cross-tabulation is being
employed to measure that condition. Table 2 shows
the number of restaurants based on their distance tothe road networks (arterial and collector roads).
Based on the table, the majority of low-popularity
restaurants are closer to the collector road, which isaround 109 restaurants with an average distance of
331 meters. In comparison, there 14 low-popularity
restaurants closed to arterial roads, with an average
distance of about 1979 meters. Restaurants withaverage-popularity are also closer to the collector
roads (615 restaurants), with an average distance of
418 meters. The number of restaurants with averagepopularity near arterial roads is 102, with an average
distance of 2033 meters. Similarly, the majority ofhigh-popularity restaurants are near the collector road
(133 restaurants), with an average distance of 343

Given the z-score of -7.43891651252, there is a less than 1%
likelihood that this clustered pattern could be the result of random
chanceFig. 11 NNA result for low-popularity restaurants in
Bandung.
Low popularity restaurants
Restaurants with a low-popularity index also havea clustered pattern in the city of Bandung. This low
index is dominant around the Bandung City Center.
The z-score from NNA shows a value of -7.438917.
Based on the z-score, the distribution type of lowpopularity restaurants is clustered (Figure 11). The
KDA for low-popularity restaurants shows a slightly
different result, where the number of highest density
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SEE - Kyoto, Japan, Nov.18-20, 2020

meters. The number of high-popularity restaurants
near arterial roads is seven, with an average distanceof 2201 meters. Conclusively, 87.4 percent of thetotal restaurants are closer to the collector roads.

to most of the restaurants, especially the highpopularity restaurants, while only a few restaurants
near the malls.
ACKNOWLEDGMENTS

Popularity

Table 2 Number of restaurants based on the distanceto the road networks

Low
Avg.
High

Num.
of
nearestrest. toarterial
road
14
102
7

Num. ofnearestrest. tocollector
road

Mean
distance
rest. toarterialroad

Mean
distance
rest. tocollector
roadThis study is supported and funded by the
Directorate Research and Community Services(DPRM), University of Indonesia under the Publikasi
Terindeks International (PUTI) 2020 research grant.
The authors also express their greatest gratitude andthe highest appreciation to Department of Geography,
Faculty of Mathematics and Natural Science,
University of Indonesia which has facilitated theresearch activities.

109
615
133

1979,152033,222201,81

331,19418,25
343,70REFERENCES[1] Zhu, F., and Zhang, X., Impact of online
consumer reviews on sales: The moderating roleof product and consumer characteristics. Journalof Marketing, Vol. 74, Issue 2, 2010, pp. 133-148.
[2] Kim, S. J., Maslowska, E., and Malthouse, E. C.,
Understanding the effects of different review
features on purchase probability. Int. J. Advert.,
Vol. 37, Issue 1, 2018, pp. 29-53.
[3] Komaladewi, R., Mulyana, A., and Jatnika, D.,
The Representation of Culinary Experience as
the Future of Indonesian Tourism Cases in
Bandung City, West Java. International Journalof Business and Economic Affairs, Vol. 2, Issue
5, 2017, pp. 268-275.
[4] Zhang, Z., Zhang, Z., and Law, R., Positive andnegative word of mouth about restaurants:
Exploring the asymmetric impact of theperformance of attributes. Asia Pacific Journal of
Tourism Research, Vol. 19, Issue 2, 2014, pp.
162-180.
[5] Lloyd, R., Cognitive maps: Encoding anddecoding information. Annals of the Associationof American Geographers, Vol. 79, Issue 1, 1989,
pp. 101-124.
[6] Lloyd, R., Spatial cognition: Geographic
environments (Vol. 39), Springer Science &Business Media, 1997, pp. 1-264.
[7] Hu, Y., and Han, Y., Identification of Urban
Functional Areas Based on POI Data: A Case
Study of the Guangzhou Economic andTechnological
Development
Zone, Sustainability, Vol. 11, Issue 5, 2019, pp.
1-15.
[8] Anugrah, I. W., and Suhaeni, T., Pengaruh
Kepemimpinan Stratejik Terhadap Strategi
Bersaing UKM Café dan Restoran. Jurnal Riset
Bisnis dan Investasi, Vol. 3, Issue 3, 2017, pp.
78-88.
[9] Siswanto, M. R., and Choandi, M., Ruang
Pertukaran Ide di Bandung Wetan. Jurnal Sains,
Teknologi, Urban, Perancangan, Arsitektur

Table 3 shows the number of restaurants based on
their distance to the urban functional units (malls andhotels). About 86 percent of the total restaurants arecloser to the hotels than to the malls. The highpopularity restaurants are closer to the hotels, with amean distance of 229 meters. In comparison, only 16
high-popularity restaurants near to the malls, with amean distance of 953 meters. Restaurants withaverage-popularity are also closer to the hotels (619restaurants), with an average distance of 278 meters.
The number of restaurants with average-popularity
near malls is 98, with an average distance of 1032
meters. Similarly, the majority of low-popularity
restaurants are near the hotels (101 restaurants), withan average distance of 270 meters. The number of
low-popularity restaurants near malls is 22, with anaverage distance of 946 meters.

Popularity

Table 3 Number of restaurants based on the distanceto the urban functional units

Low
Avg.
High

Num.
of
nearestrest. to
hotel
101
619
124

Num.
of
nearestrest. to
mall
22
98
16

Mean
distance
rest. to
hotel

Mean
distance
rest. tomall

270,02278,91
229,12946,941032,38
953,59CONCLUSIONSThis study concludes that high, average, lowpopularity restaurants are clustering in Bandung. The
densest cluster in high-, average-, and low- popularity
groups has up to 78 restaurants/km2, 144
restaurants/km2, and 36 restaurants/km2, respectively.
The majority of the restaurants are closer to collector
roads rather than arterial roads. The hotels are closer
309

SEE - Kyoto, Japan, Nov.18-20, 2020

(Stupa), Vol. 2, Issue 1, 2020, pp. 707-718.
[10] Zhai, S., Xu, X., Yang, L., Zhou, M., Zhang, L.,
and Qiu, B., Mapping the Popularity of Urban
Restaurants Using Social Media Data. Applied
Geography, Vol. 63, 2015, pp. 113-120.
[11] Habib, M. A., Rakib, M. A., and Hasan, M. A.,
Location, Time, and Preference Aware

Restaurant Recommendation Method. In 2016
19th International Conference on Computer andInformation Technology (ICCIT), 2016, pp. 315320.

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310

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

COMPARATIVE STUDY ON KOREA AND JAPAN URBAN PARKS
CONCERNING THE DEVELOPMENT POLITICS AND THE
TRANSITION OF SYSTEM

1

Shinya Tsukada1, Sangbok Yoon2, Yeongha Kim3, Tetsuo Morita4 and Hiroshi Sugita5
Maebashi City Office, 2Dong-eui University, 3 Dong-A University, 4Mebashi Institute of Technology,
5
The Institute of Behavioral Sciences

ABSTRACT
Urban parks are open space with trees that provides a place of relaxation and peace for residence. Urban parks
have been rapidly constructed in Korea since the Seoul Olympics (1988). On the other hand, In Japan the supplyof urban parks is sufficient, and the maintenance and utilization of park that have been stocked during the periodof high growth has become a problem. We thought it necessary to compare the parks of Korea and Japan during
the period when the environment changed significantly after the Seoul Olympics. This purpose of study is to clarify
the characteristics of Korea and Japan parks by comparing them. As a result of this study, the following features
were clarified. In the transition of urban park politics, we found that there are similarities in responding to issues
such as "diversifying needs", "park master plan", and "private entry". In both Korea and Japan, the important
direction of future park policy is considered to be “use and maintenance”.
Keywords: Urban Park, Comparison, Development Politics, Korea and JapanINTRODUCTION

survey on the awareness of greenery to the residentsof Daegu City. According the survey, as a ward
associated with green, Daegu citizens associate itwith "green(color) and blue(color)" and Sapporo
citizens associate it with "park". As a ward associatedwith park, Daegu citizens associate it with " a placeof rest" and Sapporo citizens it with "Child".
Song [2] summarized the history of thedevelopment of the park system in Korea and Japanby examining matters related to urban parks in Korea
and Japan from 1870 to 1980.
Kang [3] conducted a survey focusing on therelationship between the development of shrines andurban parks under the Japanese rule.
Song et al. [4] compared the flow of major
policies concerning urban parks in Korea and Japan
since the 1970s.
Kim et al. [5] grasped the actual conditions of theurban park in Ilsan New City and investigated how
park users evaluated this urban park. In addition, as aresult of a questionnaire survey on future
maintenance intentions, it was understood that urban
parks utilizing natural forests were desired for future
development. By the survey of Kim et al. [6] about
the future intentions for urban park development,
residents said that they wanted the urban parks withnatural forest.
Kin et al. [6] conducted a spatial evaluation ofpark users in Ilsan New City. As a result of theevaluation, it was clarified that the neighboring parks
established by the urban development are used forlight sports and nature walks, and the green area ratioof the city is high.

Both Korea and Japan, which are adjacent to eachother, have developed while experiencing the periodof high growth after World War II. However, in the
future, both countries will continue to experience a
declining birthrate and aging population, and due tothis effect, the population will decline not only inrural areas but also in urban areas, making economic
growth again difficult.
National policies in the future will requireinternational efforts to address environmental issues
such as biodiversity and disaster prevention efforts
such as large-scale earthquakes. As a solution to thesepolicy issues, it is also meaningful to focus on thepark policy, which is a green base, and proceed withthe study.
In this paper, based on the future changes in thesocial situation in Korea and Japan, such as thedeclining birthrate and aging population, we surveyed
the park system in Korea and Japan and the actual
usage situation.
By conducting a survey, we examined the
direction of the park system and the points to keep inmind when formulating a plan in anticipation of
future national trends.
OVERVIEW OF THE STUDY
In this section we summarize the overview ofexisting research and describes the focus our study.
Lee [1] 's study compared the awareness of green
in Korea and Japan. They conducted a questionnaire
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SEE - Kyoto, Japan, Nov.18-20, 2020

Table 1 Review of urban park politics

A.C.
1986

Korea

Japan

Han-gang Waterfront Site Park Project

Fourth Five-Year Plan for Urban Park

1991

Fifth Five-Year Plan for Urban Park

1993

Revision of Urban Park Law
Addition of Physical Education Park

Revision of Urban Park Law
Increase in Park Area Level and Change the Type Name

1994

Busan Amenity Plan

Green Master Plan
(Formulation: City)

1995

Civic Green Space System

1998

Sixth Five-Year Plan for Urban Parks
Green Plan 2000

1999

Expansion of Green Areas

2000

Revision of Urban Park Law(Park MP, Purchase Request System)

Social Capital Development Priority Plan

2003

Established Seoul Green Trust
Third Sector Introduction System for Urban Park
Maintenance and Creation Projects

Abolition of Attraction Distance Standard for Parks andEstablishment of Designated Manager System

2004

Five-Year Plan for National Balanced Development(2004-2008)

Landscape Law
Creation of Multi-Dimensional Urban Park System

2005

Urban parks and Open space Law(Park and Open Space Basic Plan System)

2007

Landscape law

2009

Private park exception system
Imagination Children Park Project (2008-2011)2012

Urban Renewal Law

2014

Revision of the Landscape Act(Mandatory Landscape Planning)
Five-Year Plan for Regional Balanced Development
Abolition Guidelines of Long-Term Unexecuted City
Planning Facility

2015

Arboretum ▪ Garden Creation and Promotion
Methods
Founding of National Garden ▪ Regional Transfer ▪
Private Garden ▪ Community Garden

2016

Revision of Urban parks and Open space Law
Development Exception Business of Private Park
Guideline

Plan to Extend Life of Park Facilities

Development of Open Space for New age

2017

Revision of Urban Park Law
Park-PFI Established
Legalization of Maintenance and Repair Standards

2018

Planning Guidelines to Extend Life of Park Facility

area in Busan City.
Nakanishi et al. [9] investigated the relationshipbetween land use systems in Korea, Japan, andTaiwan.
Nakanishi et al. [10] analyzed the relationshipbetween the city planning master plans of Japan and
Korea.

Sugawara and colleagues [7] clarified thedevelopment and characteristics of the civil
movements in Korea.
Kim et al. [8] analyzed the causal relationship byconducting a questionnaire survey on residents inorder to clarify the influence of the green areas on theslopes of the urban edge on the choice of residential
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SUTUDY AREA AND STUDY METHODS

Table 2 The present situation of urban parks in
Korea (2020)

As mentioned above, there are many studies thatcompared Korea and Japan regarding urban parks andgreenery. However, few studies have compared
Korea and Japan on urban parks and greenery since
the Seoul Olympics (1988).
This study clarified the similarities anddifferences by clarifying the changes in the politics ofurban parks in Korea and Japan from the time ofSeoul Olympics to the present day. Moreover, thecharacteristics of urban park were clarified bygrasping the amount of improvement for each type ofurban park.
The research method was mainly based on theexisting literature survey. In addition, based on the
results of the survey, basic consideration was given to
future issues regarding urban parks.

Subdivision

Location

Area
[ha]

Children's Park

10,627

2,591

5,168

6,181

57

2,950

65

13,524

15,91725,24622,07022,176

Amusement Park

244

15,509Physical Education Park

319

2,719

Total (12.7m2 per person)

38,55065,650Type

Urban park

Neighborhoodpark
Cemetery park
Urban naturalpark
Subtotal

Green SpaceCOMPARATIVE STUDY ON KOREA AND
JAPANESE URBAN PARK SYSTEM

Table 3 The present situation of urban parks in Japan(2019)

Review of Urban Park Politics
Type

Table 1 summarizes the changes in policies
regarding urban parks since the Seoul Olympics(1988).
In Korea, a part of the Urban Park Law wasrevised in 1993, when the Seoul Olympic Games
were held, and "Physical Education Park" was added
as one of the parks. In 2000, Urban Park Law wascompletely revised. In 1986, "The plan of Han-gang
Waterfront Site Park Project" was formulated.
This plan is also linked to the Han River
Renaissance in 2003 based on the "Enactment of the
National Land Planning Act of 2000 with the basic
principle of nature restoration" in order to improve
the natural environment of the Han River waterfront.
Based on this plan, the development of the World Cup
Park and Urban Park by converting land use of Seoul
Forest was promoted.
In 2012, Urban Park Law was revised against the
backdrop of decentralization, and Park Master Plan
has been created by the city government. In 2015, theLaw for the Creation and Promotion of Arboretum
and Gardens was enacted to promote the conservation
and utilization of valuable gardens.
On the other hand, in Korea, a non-service Urban
Park Plan was an issue. To solve this, in 2014
Guideline of a long-term Unexecuted Urban Planning
Facility Cancellation was created. In 2016, the“Private Park Development Guidelines” were
established to promote the participation of the vitalityof the private sector in urban parks.
In 1986, the 4th Five-Year Plan for Urban Park
was formulated in 1986. In addition, in 1991, the 5th
Five-Year Plan for Urban Park was formulated inJapan.

Urban

in

park
housing

area

Urban park incity area

Urban park inwide area

Subdivision

Location

Area
[ha]

Block Park
Neighborhood
Park
District park

88,052

14,198

5,792

10,430

1,619

8,589

Country Park(180)

(1,400)Subtotal

95,643

34,617

General park

1,375

26,099Sports park

834

12,978Subtotal

2,209

39,077215

14,906

6

564

221

15,470

17

4,251

1,360

13,713

240

1,814

8,939

16,259

156

932

348

163

Green Road

968

923

Subtotal
Citizen's Green

12,01133,804

7

3

169

100

110,277

127,321

Wide area Park
Urban
Recreation
Subtotal

Urban park in Nationally

Urban park
of
Green
space

Contracted
Space
Contracted
Space

Unique Urban
Park
Buffer Green
Space
Urban
Green
Space
Urban Forest
Open
Space
Urban Park

Citizen's

Total (10.6m2 per person)

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Fig. 1

Green Space in Korea

Fig. 3

Brock Park in Japan (1)Fig. 2

Physical Education Park in Korea

Fig. 4

Brock Park in Japan (2)An added issue that was not included in theconventional plan was "meeting diverse needs." In1993, "Children's Park" was renamed "Block Park".
This reason is that, based on the progress of anaging society, the idea has changed from a uniform
park for child to a park with diverse needs. In 1994,
against the backdrop of decentralization, by theestablishment of Green Master Plan, open spaces andparks were integrated. Also, in 2000, the conventional
Five-Year Plan for Urban Parks, etc. was integrated
into the Social Capital Development Priority Plan.
Designated Manager System was established in2003 by amending the Local Autonomy Law against
the backdrop of increasing stock and deregulation.
Designated Manager System was also introduced
in urban parks, and in 2017, Park-PFI system wascreated to promote the participation of the vitality ofthe private sector. On the other hand, the deterioration
and renewal of urban park became serious, Park
Facility Extension of Life Plan Development
Guideline was created in 2018.
The similarities and differences between the urban
park policies in Japan and Korea are as follows.
First, regarding the similarities, the type of urban
park was changed.

Korea has added the type of Physical Education
Park in 1993 after the Seoul Olympics, Japan haschanged the children's park to a block park in 1993,
and These changes addressed "diversified needs".
The next similarity is the creation of the "Green
Master Plan and Landscape Initiatives" created by thecity due to the progress of decentralization. Korea
enacted Park Master Plan in 2011 and the Landscape
Law in 2007, Japan enacted Establishment of Green
Master Plan in 1994 and the Landscape Law in 2004.
Third is the entry of private vitality into urban
park. Japan introduced Designated Manager System
in 2003 and Park-PFI in 2017, and Korea amended
the Law Concerning Urban Parks and Green Spaces
and prepared the “Private Creation Guidelines” in
2016.
Next is the difference between Korea and Japan.
In Korea, with the enactment of the "National
Planning Law" in 2003, the tendency to return tonature increased. "World Cup parks that turn garbage
collection into parks" and "Seoul forests that turnracetracks and golf courses into parks" are being
actively converted into land alongside rivers.
In Japan, the increase in stock and thedeterioration of existing facilities are becoming more
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SEE - Kyoto, Japan, Nov.18-20, 2020

serious. Proper maintenance and management ofstock has become an important issue, such as
notification for the safety of playground equipment in2002 and showing the basic concept of extending
Plan to Extend Life of Park Facilities in 2012.

In the transition of urban park policies since theSeoul Olympics, we grasped the similarities
corresponding to the issues of " diversifying needs ","Park Master Plan", and " Private Entry ".
In addition, it has become clear that in Japan, aplan for maintenance and renewal of parks has beenformulated in consideration of the increase in stockand renewal of facilities, on the other hand, that in
Korea, park maintenance is being promoted by land
use conversion.
Furthermore, Japan has approximately 1.9 times
the total area of urban parks, etc. as compared with
Korea, while Korea has 1.2 times the park area perperson and 1.1 per location as compared to Japan.
We were able to understand the actual conditionsof development in Korea and Japan and thebackground of park policy. Both Korea and Japan are
facing a population decline and an aging population.
Therefore, how to maintain and update the current
stock satisfactorily becomes an issue.
For this reason, Korea is promoting the natural
return to parks, but considering that Japan is having
difficulty in the maintenance plan for renewal, we
think that the maintenance renewal plan should beformulated at this point.

The Present Situation of Urban Park
Table 2 shows the current status of urban parkdevelopment in Korea in 2020 (Statistics Agency).
The total number of urban parks in Korea is 33,260
locations, 42,995 ha (park area per person is 12.7 m2/ person, 1.29 ha / location). Focusing on the type ofpark, Green Space have the largest number and area
(22,070 locations, 22,176 ha (1.00 ha / location)).
Table 3 shows the current status of urban parkdevelopment in Japan in 2019 (surveyed by the
Ministry of Land). The total number of urban parks inJapan is 110,277 locations and 127,321 ha. Park area
per person is 10.6 m2 / person, 1.15 ha / location.
Focusing on the type of park, Block parks havethe largest number (88,052 (0.16 ha / location)) andgeneral parks have the largest area (26,099ha (18.9ha/ location)).
In Japan, green spaces are included in urban parks,
whereas in Korea, green spaces are excluded fromurban parks, but in this study, green spaces areincluded in urban parks [11].
Comparing Korea and Japan, Korea has a total
park area of 65,650 ha, urban park area in Japan was
1.9 times larger than that in Korea. On the other hand,the area of parks per person in Korea is 12.7m2 /person, whereas the area of parks per person in Japanis 10.6m2, urban park area of one person in Korea was
1.2 times that of one in Japan.
In addition, the park area per location is 1.29 ha in
Korea and 1.15 hectares in Japan, and the park area
per location in Korea is 1.1 times that of Japan.
In Korea, construction of skyscrapers for housing
has been promoted as a city regeneration project since
the Seoul Olympics [12]. As a result, green spaces are
increasing at the same time as housing supply [12].
Green Space (Fig.1) is a park like a Green Roadin Japan. Green Space and Physical Education Park
(Fig.2) have functions that can be used on foot like a
block park (Fig.3 and Fig.4) in Japan. As a result ofcomparing the Korean Physical Education Parks with
the Japanese Block Parks, we found that the Japanese
Block Parks were used by children, otherwise the
Korean Physical Education Parks were used by theelderly.

REFERENCES[1] Lee Y. D., Asakawa S. and Park C. Y., A
Comparative Study on Consciousness ofGreenery between Inhabitants of Daegu andSapporo,Japanese
InstituteLandscapeArchitecture, Vol. 52, No. 4, 1989, pp. 255-262.
[2] Song T. and Shirai H., A Comparative Study on
Japanese and Korean Urban Parks Concerning of
Policies since 70's, Japanese Institute LandscapeArchitecture Vol.55., No. 5, 1992, pp. 13-18.
[3] Kang S., Urban Parks and Prosperity of Japanese
Zinza Shrines in Korea, Japanese InstituteLandscape Architecture, Vol. 56，No. 5, 1993,
pp. 61-66.
[4] Song T. and Hikoe S., A Comparative Study on
Japanese and Korean Urban Parks Concerning of
Policies since 70's, Japanese Institute LandscapeArchitecture, Vol. 56, No. 5, 1993, pp. 85-90.
[5] Kim Y. and Sawaki M., The Greenery Park
Evaluation Study from View of Inhabitant incase of IIsan New town in Korea, JapaneseInstitute Landscape Architecture, Vol. 63, No. 5，
2000, pp. 657-662.
[6] Kim Y. and Sawaki M., Spatial Evaluation byUsers of Park in Case of Ilsan New Town in
Korea,
Japanese
InstituteLandscapeArchitecture, Vol. 64, No. 5, 2001, pp. 641-646.
[7] Sugawara A., Yoshimura T. and Watanabe S., A

CONCLUSIONSIn this study, the following was clarified bygrasping the changes in urban park policies and theamount of urban park development since the Seoul
Olympics in Korea and Japan.
315

SEE - Kyoto, Japan, Nov.18-20, 2020[10] Nakanishi M. and Fujioka M., A Comparative
Study on Urban Planning Master Plan in Japan,
South Korea and Taiwan, Journal of City
Planning Institute of Japan, Vol. 54, No. 3, 2019,
pp. 1438-1445.
[11] Park. K. W. and Sakai M., A comparative study
was carried out on the development policies ofurban parks in japan and Korea, Kyushu
University Institutional Repository, Vol. 75,
1996, pp. 27-47.
[12] Li Huien, Changes in urban landscape in Seoul,
Korea, Historical Geography, 50-1(237), 2008,
pp. 19-33.

Study on Characteristics and Tasks of Korean
Machi-Zukuri, "Maulmandulgi": A Case of
Pusan, Korea, Journal of City Planning Instituteof Japan, Vol. 38, No. 3, pp. 883-888.
[8] Kim Y., Kaneko T. and Kumagai Y., A Study on
the Relation between Slope Green and the
Residence Choice in Busan City, JapaneseInstitute Landscape Architecture Vol.72, No.5,
2009, pp. 859-862.
[9] Fujioka M., Nakanishi M. and Suzuki N., A
Comparative Study on Local Implementation ofHistoric Urban Conservation System in Japan,
South Korea and Taiwan, Journal of City
Planning Institute of Japan, Vol. 54, No. 3, 2019,
pp. 998-1005.

316

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

THERMAL ENERGY EVALUATION OF
THE INCINERATOR WASTE
Kantayut Trebooniti
Faculty of Industrial Education Rajamangala University of Technology Suvarnabhumi, Thailand

ABSTRACTThis paper evaluates the thermal energy from the incinerator waste. The incinerator system composed of 6
sections: the first section is a waste hopper and feeder, the second section is the rotary kiln primary, the third
section is a secondary chamber, the fourth section is the ash cooling conveyer, the fifth section is cyclone and thesixth section is stack. The stack section was interested to consider. The waste and diesel oils were 200 kilogramsand 200 liters, respectively. The experimental results presented the temperature ranges on the stack surface by
about 180 - 300 C corresponds to thermal energy from the stack, and it appropriated for engineering processes.
Keywords: Incinerator, stack, thermal energy, waste

INTRODUCTION

composed of conduction, convection, and radiationfrom the surface by about 14300 MJ/h. The potentialof energy saving is estimated by about 14300 MJ/h,which is the energy recovery of 15.7% of energy
input in the raw mill. The waste heat recovery fromthe exhaust gas at the top of the chimney had studied
by S. Erel, 2009, the thermoelectric converter was
installed on the top of the chimney.
The results were showed that electrical energy canbe obtained by means thermoelectric converter unit
thrown from chimneys in the form of heat energy.
The graphical showed the electrical power increasing
with temperature difference (hot and cold sides).
This paper presents the thermal energy fromincinerator waste focused on the heat loss from thestack surface.

The rising cost of energy is serious widely in theworld and also global warming is one problem fromfossil fuels. The alternative energy is interested indeveloping the energy system to increase efficiency
and to reduce emissions. There is alternative energy
for different systems such as solar energy, windenergy, etc. Guo et al., 2010 presented the energy andexergy analysis of the power generation system which
consists of an economizer, an evaporator, asuperheater, a steam turbine, a condenser, and a pump.
San, 2010 performed a second law analysis todetermine the efficiency of heat exchanger for waste
heat recovery.
Butcher and Reddy, 2007 presented thetemperature profiles across the heat recovery steam
generator, network output, second law efficiency, andentropy generation that are simulated for various
operating conditions.
The waste heat from the combustion is urgent torecover for any system. Shaaban, 2007 presented the
management of medical waste at hospitals in Egypt.
The medical waste estimated about 75 tons/day fromthe governmental hospitals in Cairo. The data showed
the most appropriate incinerator capacity is 150 kg/h.
Bujak, 2009 reported the energy efficiency of theincinerator for medical waste. The experimental
result showed the 100 kg of medical waste could be
converted to the usable energy by about
600-800 kW, and the energy efficiency is in therange of47-62%. Ulu et al., 2006 studied the energy andexergy analyses of a raw mill in the cement
production. The first and second laws efficiencies are
84.3% and 25.2%, respectively. The heat losses are

THERMODYNAMICS ANALYSISThe incinerator waste consists of main equipment
as follows: the first section is a waste hopper andfeeder, the second section is the rotary kiln primary,the third section is a secondary chamber, the fourth
section is the ash cooling conveyer, the fifth section
is cyclone and the sixth section is stack. First andsecond laws of Thermodynamics are considered thesystem. For the case of steady-state steady flow, thebalance equations are applied to evaluate the energyof the equipment. The mass balance equation (Utlu etal., 2006) expressed in the form of the rate as m in =  m out
317

(1)

SEE - Kyoto, Japan, Nov.18-20, 2020

8%, syringe 15%, glove 25% and other 7%. The highheating value (HHV) and the average density of the
medical waste are 12,327 kJ/kg and 280 kg/m3,
respectively.

Wherever = mass flow rate at the inlet and is mass
flow rate at the outlet.
The general energy balance (Utlu et al., 2006) canbe expressed as

Table 1 Mass of the system E in =  E out

(2)
Item

Or

 +
Q

 m h = W +  m h
in

in

out

out

(3)

Where is the rate of net energy transfer in, is therate of energy transfer out by heat and h is the specificenthalpy.
The first law efficiency (Utlu et al., 2006) expressedasE output
=
E

Input

Ti

m

OutputTommaterial(K)(Kg/h)

material(K)(Kg/h)

1

Waste

303

70

Ash

370

10

2

Air

309

750

Dust

390

60

3

Fuel

310

55

Flue

550

805

875

Total

Total

875

EXPERIMENTAL MEASUREMENT
This experiment was carried out in the summer
season in the Suphan Buri province. Thermocouples
type K (range: 0-1250 ºC, accuracy ± 0.5 ºC) were
installed for measuring the temperature at different
positions as shown in Fig. 2. The thermocouples wereconnected to a data logger (Hioki, Model: 8422-52,
accuracy ± 0.8%).
The infrared thermometer (UT 301A) was measured
the surface temperature of the stack, combustion
chambers and the kiln. The inlet air temperatures
intake the combustion chambers were measured using
the velocity probe (TSI Model 8380, range 0-50 m/s,
error ± 0.5%).

(4)

input


Where  is an energy efficiency, E
useful is an energyuseful and E
input is an energy input

Fig. 1 Incinerator waste
Fig. 2 Schematic of incinerator and measuring
positions

INCINERATOR AND WASTE
The incinerator waste was installed at Suphan Buri
Province (Fig. 1). The capacity of the incinerator is
300 kg. The incinerator system composed of 6
sections: the first section is a waste hopper and feeder,
the second section is the rotary kiln primary, the third
section is a secondary chamber, the fourth section isthe ash cooling conveyer, the fifth section is cyclone
and the sixth section is stack. The waste is medical
waste; it composed of cotton and gauze 45%, paper

RESULT AND DISCUSSION
The mass balance of the system is presented on
the law of mass conservation as follows: m = min318

waste + m f ,1 + m a ,1 + m f , 2 + m a , 2 (5)









SEE - Kyoto, Japan, Nov.18-20, 2020

 mout = m ash + m fl + m dust







Table 2 Energy balance of the system (Input)

(6)

Item

The input and output materials are presented intable 1.
The energy balance of the system, which isarranged according to the energy components given
in Table 2. The energy balance in the system ispresented on the law of energy conservation as
follows:

Input

Cp(kJ/kh)/Tmmaterial HHV(kJ/kg) (K)(kg/h)

(K)

1

Waste

12,327303

70862,890

2

Air

1.005

309

750

232,908.75

Fuel

43,767.7

310

3

Total


 waste (HHV) + m
 f (HHV) + m
 a c p,a Ta ] = Q[mloss +

Q

55

2,407,223.5875

3,503,032.25

Table 3 Energy balance of the system (Output)

 ash c p,ash Tash + m
 g c p,g Tg + m
 dustc p,dustTdust ] (7)
[m

Item

Heat losses in the system are composed of threemodes of heat transfer. Heat losses with theconvection are between outside air temperatures andsurface temperatures. The heat losses with theconduction are due to the temperature differences ofthe outer and inner surfaces. Heat losses with theradiation occurred from the outer surface andambient air. The total heat losses could be calculated(Utlu et al., 2006) as follows:1

Ash0.75 370

10

2,775

2

Dust gas

1.05 390

60

24,5703

Flue gas1.55 550

805

686,262.5





Q
total = Q conv + Q cond + Q radm

Q(kg/h)(K)

2,789,424.75

fromsurface
Total

(8)

875

3,503,032.25

CONCLUSION
This study aims to evaluate the thermal energy
utilization for the engineering process. Mass andenergy balances were analyzed using the incinerator
process. The thermal efficiency was defined byenergy losses from the surface to divide energy input.
The medical waste was used to combustion andanalyzed the thermal energy.
The result showed high thermal efficiency andsuitable for use in the waste heat process andapplication engineering process.

(9)

(10)

ACKNOWLEDGMENT
The results of this experiment can beaccomplished with great help from the consultation of
the Faculty of Mechanical Engineering. Thank you to
Research and Development Institute. Rajamangala
University of Technology Suvarnabhumi, the budget
for the research and the Faculty of MechanicalEngineering, Faculty of Industrial Education Suphan
Buri Center Providing facilities, tools, and support.
The researcher highly appreciates.

The radiation from the surface to the ambient air
calculated from = D  (T 4 − T 4 )Qrado
sf ,outa

THeat

The conduction through the cylinder calculated from

(Tsf ,in − Tsf ,out )Qcond =ln(ro / ri )2kl

Cp(kJ/kh)/losses

The convection around the surface of the rotarykiln primary, secondary chamber and stack was
calculated fromQ
conv = D o hl(Tsf ,out − Ta )Outputmaterial HHV(MJ/kg) (K)(11)

The energy efficiency of the system is calculated
from Eq. 4, using energy analysis values from table 2,
as follows: (or 79.6%)
Due to this experiment, the energy output is heatlosses from the surface system and energy input is
total materials (waste, oil, and air).

319

SEE - Kyoto, Japan, Nov.18-20, 2020

REFERENCES[1] J. Guo, M. Xu and L. Cheng, Thermodynamic
analysis of waste heat power generation system.
Energy 2010, 35; 2824-2835[2] J.Y. San, Second law performance of heatexchangers for waste heat recovery. Energy 2010,
35; 1936-1945.
[3] C.J. Butcher and B.V. Reddy. Second law analysis
of a waste heat recovery based power generation
system. Int. J. Heat and Mass Transfer 2007;
50:2355-2363.

[4] A.F. Shaaban, Process engineering design ofpathological waste incinerator with an integrated
combustion gases treatment unit. J. Hazardous
Materials 2007; 145: 192-202.
[5] J. Burak, Experimental study of the energy
efficiency of an incinerator for medical waste.
Applied Energy 2009; 86: 2386-2393

320

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

RESEARCH ON THE DURABILITY OF RECYCLED AGGREGATE
CONCRETE INCORPORATING HIGH VOLUMES OF BLAST
FURNACE SLAG
Chung-Hao Wu1 and Shu-Ken Lin2
Department of Civil Engineering, Chung Yuan Christian University, Taiwan
2
Department of Civil Engineering, National Chung Hsing University, Taiwan
1

ABSTRACTThis study experimentally investigated the durability of concrete containing high replacement levels of blast
furnace slag. Two kinds of concrete with natural aggregate and recycled aggregate were adopted. Concrete
mixtures made with 0%, 15%, 30%, 45%, 60% and 75% replacement of cement with blast furnace slag wereprepared for testing. Water-cementitious material ratios are 0.30, 0.34, 0.38 0.42, 0.36 and 0.50. The compressive
strength (at 7 days, 28 days, 56 days and 91 days), the resistance to chloride-ion penetration, and the water
permeability of concrete (at 28 days, 56 days and 91 days) were measured and presented. Test results indicate thatthe recycled aggregate concrete showed a similar durability as the natural aggregate concrete. The compressive
strength, the durability-related chloride-ion penetration, and the water permeability of concrete containing highreplacement level (75%) cement replacement of blast furnace slag was obviously superior to the concrete without
blast furnace slag or with lower replacement levels.
Keywords: Blast furnace slag, Recycled aggregated concrete, Water permeability, Chloride ion penetration,
Durability

M. El-Hawary et al. [2] reported the results ofexperimental research on the durability andperformance of various mixtures of RAC
incorporating 25% BFS as a cement replacement. The
compressive strength, drying shrinkage, water
permeability, water absorption, alkali-aggregate
reactivity and sulfate content of the concrete mixtures
were tested. The results indicated that the addition ofmineral slag improved the mechanical properties anddurability characteristics of the RACs. Addition of
25% BFS evaluated to be efficient in reducing water
absorption, alkali-silica reactivity and sulfate attackin RAC. However, the test results also showed thatthe introduction of 25% BFS is not effective enoughto prevent the excessive expansion of the alkalicarbonate reaction in RAC after 1 year. Furthermore,
it has an adverse impact on resisting the water
permeability and drying shrinkage of the RAC
mixtures.
Y. Khodair et al. [3] examined the effect of RCA
on the properties of self-compacting concrete (SCC).
Twenty RAC mixtures with different dosages of RCA,
fly ash (FA) and BFS were prepared and tested. The
results showed that the replacement percentage of
RCA (0 ~ 100%) increased, the compressive
strengths of concrete decreased at 3, 14, and 28 days,
and the tensile strengths decreased at 28 days. Use
50% BFS as a replacement for cement resulted in theleast reduction in the split tensile strength of all RAC
mixtures when compared to the replacements of 50%
FA and 25% FA and 25% BFS. Moreover, the partial

INTRODUCTION
The reuse of waste concrete has always been an
important issue in Taiwan. In general, the reusemethod is mainly to crush waste concrete as coarse
aggregate for producing concrete. This concrete wasnamed recycled aggregate concrete (RAC). The
surface of recycled coarse aggregate (RCA) is
generally full of pores, presenting high water
absorption, which affects the property of theinterfacial transition zone in concrete, leading tonegative effects for the durability of concrete. In orderto improve the durability of RAC, Pozzolans such as
fly ash and blast furnace slag are added to concrete,
however, there are restrictions on the dosages of the
Pozzolans in many national standard codes. For past
decades, more and more research results of concretewith high volumes blast furnace slag (BFS) were
published, most of them were discussed for natural
aggregate concrete (NAC), but rare for the reports
relating to the RAC incorporating high replacementlevels of BFS, especially for the durability.
R. K. Majhi et al. [1] investigated the fundamental
properties of concrete prepared using high volumes of
RCA (0%, 50% and 100%) and BFS (0% and 60%),
and adding lime (0%, 5%, 7% and 10%) as an alkaline
activator. The experimental results revealed that thelime was effective in activating the BFS and enhance
the mechanical properties such as compressive
strength, splitting tensile strength, flexural strengthand bond strength of high volume BFS based RAC.
321

SEE - Kyoto, Japan, Nov.18-20, 2020

replacement of cement by Pozzolans presented anadverse effect on the 28-days-RAC compressive
strength; however, it increased the resistance tochloride permeability.
F. U. A. Shaikh [4] reported the effect of slag
fume on the early-age and long-term mechanicalproperties of RAC. The test results showed that
addition of 50% slag fume significantly reduced themechanical properties of the RAC at early age, while
the long-term (56 and 91 days) compressive andtensile strengths of the RAC containing slag fume and10% silica fume are higher than that of the control
RAC mixture. It was also observed that the slow
pozzolanic reaction of slag fume contributed to thelong-term compressive and tensile strengths of RAC
containing slag and 10% silica fume.
R.K. Majhi et al. [5] researched the effects of
RCA and BFS on fresh and hardened concrete
properties. 16 concrete mixtures were prepared with
0%, 25%, 50% and 100% replacement of natural
aggregate by RCA for each 0%, 20%, 40% and 60%
replacement of cement by BFS. The test results
showed that the workability increases with the use of
RCA or BFS or both of these two. The compressive,
split tensile and flexural strength decreased with theincrease in the replacement percentages of RCA or
BFS or both. Water absorption and volume of voidsof the concrete mixtures increased with the increaseof RCA content. However, the use of BFS improves
the quality of the concrete mixtures by improving the
ITZ and bond strength between mortar and RCA. The
concrete mixture with 50% RCA and 40% BFS
achieves the values of these properties closer to thoseof the concrete without RCA and BFS.
Based on the results of the above mentioned
researches, it is seen that RAC with high replacementlevels BFS may present better durability and higher
compressive strength at later age. Therefore, thisstudy aims to further investigate the fresh properties,
compressive strength and durability of RAC
incorporating high replacement level of BFS.

2.40.
(5) Coarse Aggregate: crushed river stone with a
specific gravity of 2.61, bulk density of 1470
kg/m3 and D max of 19 mm.
(6) Recycled Coarse Aggregate: crushed waste
concrete with a specific gravity of 2.26, bulk
density of 1280 kg/m3 and a diameters of 5 ~ 20mm.
(7) Superplasticizer (SP): High performance waterreducing agent of Type G with a specific gravityof 1.2 ± 0.02 and the pH value of 7.0 ± 1.0.

Table 1 Composition and physical properties of
cement and blast furnace slag
Components

CementSiO 2 (wt%)
Al 2 O 3 (wt%)
Fe 2 O 3 (wt%)
CaO (wt%)
MgO (wt%)
Na 2 O (wt%)
SO 3 (wt%)
K 2 O (wt%)
Loss on ignition(wt%)
Specific surface
area (m2/kg)
Specific gravity

21.4
4.9
3.8
64.2
1.1
0.2
2.1
0.44

Blast
Furnace Slag
38.12
7.48
0.33
39.86
10.58
0.36
0.17
0.36

2.1

1.4

336

538

3.15

2.90

Mixture Proportion and Specimen Preparation
The mixture proportions of concrete were
designed according to the ACI 211 for providing thecompressive strength of 35 MPa at 28 days. The waterto cementitious material ratio (w/cm) ranged from0.30 to 0.50, and the blast furnace slag content ranged
from 0% to 75% by weight of the total cementitious
materials as cement replacement. The mixture
proportions are shown in Table 2.
The fresh properties of concrete, including slump,
air content, unit weight and setting time, were
simultaneously measured for each batch. Various
specimens for tests were then cast from each mixture,they were: cylinder specimen of φ100 x 200 mm forcompressive strength test, cylinder specimen of φ150
x 50 mm for water permeability test, and cylinder
specimen of φ100 x 50 mm for chloride-ion
permeability test. After removal from the molds, allspecimens were moved to a standard moist-curing
room until date for testing.

EXPERIMENTAL PROGRAM
Test Materials(1) Water: ordinary water meets the requirements of
ASTM C 1602.
(2) Cement: Type I Portland cement produced by
Taiwan Cement Company, with a specificgravity of 3.15. The basic properties of cement
are shown in Table 1.
(3) Blast Furnace Slag: Grade 120 of groundgranulated blast furnace slag obtained from
Advanced-Tek Systems Co.,Ltd. in Taiwan. The
basic properties of fly ash are shown in Table 1.
(4) Fine Aggregate: natural river sand with a
specific gravity of 2.60 and fineness modulus of322

SEE - Kyoto, Japan, Nov.18-20, 2020

Table 2 Mixture proportions of concrete
CA SP
W
C
BFS FASpecimen
w/cm
3
no.
kg/m
NC35B00 0.50 210 420
0800 860 1.1
NC35B15 0.46 193 357
63
839 860 1.0
NC35B30 0.42 176 294 126 878 860 1.8
NC35B45 0.38 160 231 189 918 860 2.6
NC35B60 0.34 143 168 252 956 860 3.6
NC35B75 0.30 126 105 315 995 860 6.3
RC35B00 0.50 210 420
0793 750 1.1
RC35B15 0.46 193 357
63
832 750 1.5
RC35B30 0.42 176 294 126 871 750 2.3
RC35B45 0.38 160 231 189 910 750 3.6
RC35B60 0.34 143 168 252 950 750 5.9
RC35B75 0.30 126 105 315 989 750 8.7
1 Specimen number: N is normal aggregate concrete,
R is recycled aggregate concrete, C35 is thecompressive strength of 35MPa, B45 is 45%
cement replacement ratio of blast furnace slag.
2 The containing water of Superplasticizer (SP) is not
calculated in the mixture design.
3 W: water, C: cement, BFS: blast furnace slag, FA:
fine aggregate, CA: coarse aggregate, RCA:
recycled coarse aggregate

Testing of Specimens

Fig. 1

Slump of concrete.

Fig. 2Air content of concrete.

Compressive Strength of Concrete

The compressive strength test that meets therequirement of ASTM C 39 was performed at the agesof 7, 28, 56, and 91 days. According to ASTM C 1202,
the resistance of concrete to the penetration ofchloride ion was measured in terms of the charge
passed through the concrete in coulombs. The water
permeability of concrete was tested using a water
permeability apparatus subjected to a water pressureof 0.29 MPa for 3 hours to determine the flow throughthe concrete specimen. The chloride ion penetration
and water permeability tests were performed at 28, 56,
and 91 days.

Figure 3 shows the compressive strength of theconcrete mixtures measured at the ages of 7 days, 28days, 56 days and 91 days. The strength developmentof the NAC and RAC series presented a similar trend.
At 7 days, the compressive strength for both kinds of
the BFS concrete were higher than that of the control
concretes without BSF. At 28 days, 56 days and 91
days, the strength of the BSF concretes exceeded
obviously that of the control concrete. These results
indicate that the BFS mixtures had larger strength
gain than that of the control mixtures.

RESULTS AND DISCUSSION
Properties of Fresh Concrete
Figure 1 and 2 present the measured results of theslump and air content of concrete. It can be found thatthe natural aggregate concrete (NAC) and recycled
aggregate concrete (RAC) mixtures were mixed byusing superplasticizer to produce slumps of 210 mm
to 250 mm and 200 mm to 250 mm, respectively. The
air contents of NAC and RAC ranged from 1.2% to2.3% and 1.4% to 3.0%, respectively. These results
indicate that the blast furnace slag (BFS) RAC
mixtures prepared for the test can exhibit adequate
workability.

Fig. 3323

Compressive strength of concrete.

SEE - Kyoto, Japan, Nov.18-20, 2020

Resistance to Chloride Ion Penetration
Table 3 summarized the measured results for the
resistance of concrete to the chloride-ion penetration,
the results are also illustrated in Figure 4. Overall, thecharacteristic of the resistance to chloride-ion
penetration of the RAC was almost similar to the
NAC, in which the resistance to the chloride-ion
penetration of concrete incorporating BFS was higher
than that of control concrete without BFS. At 91 days
the total charge passed, in coulombs (C), were 1076
C and 581 C (classified as low and very low
permeability) for NC35S75 and RC35S75, and were6482 C and 8114 C (high permeability) for NC35S00
and RC35S00, respectively. This indicates thatincorporating high replacement level (75%) of BFS in
concrete may reduce the chloride-ion penetration,
resulting in the improvement of the durability ofconcrete. This is believed to be due to contribution of
the pozzolanic effect of the BFS mixtures.

Table 3 The resistance topenetration of concretetheFig. 4

Water Permeability
The water permeability of concrete was tested
using a uniaxial flow apparatus performing on
cylinder specimen (φ150 x 50 mm) subjected to a0.29 MPa pressure for 3 hours. The water
permeability was calculated with following formula:chloride-ion

Classificationof thechloride-ion
28 days 56 days 91 days permeability*
NC35S00 9605
6267
6482 high/high/highSpecimenno.

Total charge passed(coulombs)

NC35S15

6941

6189

5068

NC35S30

5617

4004

3919

NC35S45

3562

3042

2928

NC35S60

2266

1478

1416

NC35S75

1446

1109

1076

high/high/highhigh/high/moderate
moderate/
moderate/
moderate
moderate/low/low
low/low/low

RC35S00

10506

8029

8114

high/high/high

RC35S15

6214

4813

4139

Relationship of total charge passed and blast
furnace slag content.

Water

permeability=

m2 − m1
× 100%
m2(1)
where m 1 = initial weight of specimen,m 2 = specimen weight after test.
Figure 5 illustrated the measured water
permeability of the concrete mixtures. It is seen thatthe water permeability decreased with the age ofconcrete for both kinds (NAC and RAC) of BFS
concretes. The water permeability of NAC is superior
to that of RAC. In addition, incorporating BFS in
concrete may inherently reduce the water
permeability of concrete. This can be particularly
found in NC35S75 and RC35S75 (containing 75%
BFS) at later age of 91 days, which have water
permeability of 1.22% and 1.88%, compared less thanthose of NC35S00 and RC35S00 of 4.57% and 7.89%,
respectively. These results signify the facts that theconcrete containing high replacement level BFS of
75% at later age may exhibit lower water
permeability, namely superior durability to theconcrete without BFS.

high/high/highhigh/high/
RC35S30 5889
4459
3598
moderate
moderate/mod
RC35S45 2973
2299
2136
erate/moderate
low/low/very
RC35S60 1507
1385
922
low
very low/very
RC35S75938
861
581
low/very low*Charge passed, chloride permeability, coulombs:> 4000C = high2000 - 4000C = moderate
1000 - 2000C = low
100 - 1000C = very low< 100C = negligible

324

SEE - Kyoto, Japan, Nov.18-20, 2020

The authors appreciate the Architecture andBuilding Research Institute (ABRI), Taiwan, for thefinancial support to this research.
REFERENCES

Fig. 5[1] Majhi R. K., Nayak A. N., and Mukharjee B. B.,
Development of Sustainable Concrete Using
Recycled Coarse Aggregate and Ground
Granulated Blast Furnace Slag, Construction and
Building Materials, Vol. 159, 2018, pp.417-430.
[2] El-Hawary M., Nouh K., and Al-Yaqout A.,
Durability of Recycled Aggregate Concrete
Incorporating Slag, Waste and Resource
Management, Vol. 172, Issue 4, 2019, pp. 107117.
[3] Khodair Y. and Bommareddy B., Selfconsolidating Concrete Using Recycled
Concrete Aggregate and High Volume of Fly
Ash, and Slag, Construction and Building
Materials, Vol. 153, 2017, pp. 307-316.
[4] Shaikh F. U. A., Mechanical Properties of
Recycled Aggregate Concrete Containing
Ternary Blended Cementitious Materials,
International Journal of Sustainable Built
Environment, Vol. 6, 2017, pp. 536-543.
[5] Majhi R. K., and Nayak A. N., Production of
Sustainable Concrete Utilizing High-volume
Blast Furnace Slag and Recycled Aggregate with
Lime Activator, Journal of Cleaner Production,
Vol. 255, 2020.

Water permeability of concrete.

CONCLUSIONS
Based on the results of the experimental work,
following conclusions can be drawn:(1) Both of natural aggregate concrete (NAC) andrecycled aggregate concrete (RAC) with thesame mix proportion and adequate
superplasticizer could present appropriate
workability.
(2) The blast furnace slag (BFS) mixtures of both
RAC and NAC had larger early compressive
strength gain than that of the control mixtures,the strength of BFS concrete could exceed thatof the control concrete without BFS at 7 days.
(3) RAC had similar characteristic of theresistance to the chloride ion penetration to
NAC. The resistance to the chloride-ion
penetration of concrete incorporating BFS was
higher than that of control concrete. Especially,
incorporating high replacement level (75%) of
BFS in concrete may reduce the chloride-ion
penetration, resulting in the improvement of
the durability of concrete.
(4) The water permeability of NAC was superior
to that of RAC. Incorporating BFS in concrete
may reduce the water permeability of concrete.
The concrete containing BFS of highreplacement level (75%) at all ages may
exhibit lower water permeability, namely
more durable than the concrete without BFS.
(5) The resistance to the chloride ion penetration
and water permeability increased with theincrement of compressive strength of NAC
and RAC. It is considered generally that the
durability can be enhanced by increasing thecompressive strength of concrete. Hence, it
can be proved that adding BFS can bestrengthened the durability of RAC.
ACKNOWLEDGEMENTS

325

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

NITROGEN FLOW ANALYSIS FROM DIFFERENT LAND-USE OF
THE CHI RIVER BASIN(MAHA SARAKHAM REGION, THAILAND)
1

Nida Chaimoon1
Circular Resource and Environmental Protection Technology Research Unit (CREPT),
Faculty of Engineering, Mahasarakham University, Thailand
ABSTRACTThis paper aims at assessing the effect of land use on nitrogen flows from a significant land-use area in the
Chi River basin (Maha Sarakham region) in Thailand. The Chi River is one of the main rivers, and many land
use categories affect the quality of the river. Statistical data and referred data was collected as the secondary datafrom credible sources to identify the flows. The data show a strong effect of land use on nitrogen with thehighest load dominated by paddy field (1,589,812 tonne/year), and the lowest value in the community (1,006
tonne/year). Nitrogen flow increased with the fertilizer application in paddy field and farm plants (44,897
tonne/year). Paddy field discharged nitrogen to the Chi River 1,113 T/year. Also, the community without
wastewater collection system takes part in a non-point source (NPS) of nitrogen to the Chi River at 299
tonne/year. The management's suggestion is to control fertilizer application, burning of agricultural residue suchas rice straw, and wastewater treatment before disposal.
Keywords: Nitrogen; Chi River; Substance Flow Analysis (SFA); Land-Use
significantly positive correlated with water pollution
due to fertilizer application entering surface water
through runoff [7].
Urbanization is associated with changes in landuses through infrastructure development, population
density, and community. The increase in impervious
areas (i.e., roads, rooftops, impermeable pavement,
and parking lots) results in NPS pollution increase in
runoff and transportation of NPS pollutants toreceiving waters [8]. The Forest area was considered
as net sinks of nitrate [9]. Land-use category is
relevant to water quality within a watershed, andlandscape alignments may be more sensitive
predictors of water quality.
The Chi River is the longest river in Thailand. It
is 765 km long. In wet seasons there are often flash
floods in the floodplain of the Chi River basin. The
river originates in the Phetchabun mountains andthen flows to the east part through the central Isan
provinces of Chaiyaphum, Khon Kaen, and Maha
Sarakham, then turns south in Roi Et and runs
through Yasothon and joins the Mun River in the
Kanthararom district of Sisaket Province. The Chi
River carries approximately 9.3 km3 of water per
annum [10]. Maha Sarakham is the fast-growing city
located along the Chi River. It has undergone rapid
urbanization. Chi River is used as a water resourceof tap water supply, agriculture and fishery.
Substance Flow Analysis (SFA) is anenvironmental accounting tool used to trace andtrack environmental problems. SFA is an appropriate
method to answer the questions of substance flows
from input transformation processes until
discharging in system boundary [11]. Therefore, thisstudy aimed to analyze nitrogen flows by SFA

INTRODUCTION
Pollution from natural phenomena or humanactivities and living things actions affects water
quality in any water resource. Water quality disturbs
the environment, natural resources, human activities,
and human health [1, 2]. Pollution can be
categorized into point source (PS) and non-point
source (NPS) pollution. PS pollution mainlycomprises of industrial and domestic wastewaterloads, which can be identified through thedischarging point or pipe [3]. NPS pollution usuallycomes from unidentified sources, such as agriculture
land, street runoff, and the deposition of atmosphericpollutants [4]. The pattern of NPS pollution leads tothe effect of land use on water quality.
Nutrient load is one of significant problems forwater resource management, the interaction ofnutrient, water and pathways has been traced andtracked by much research in the past. Nutrient loadin water is a result of several interacting processes inthe basin, including an exchange between cycles inthe terrestrial, aquatic, geological, and atmosphericenvironment. These processes can be characterized
into: (1) nutrient release (e.g., throughmineralization,
weathering,fertilization,
atmospheric deposition, sewage effluents); (2) watertransport (conducting, e.g., transit time and flow
paths); and (3) transformation and immobilization(e.g., denitrification, sedimentation, and adsorption).
Nutrient problems can be magnified by the
improper land-use that discharges nutrients to water
bodies [5, 6]. Concentrated agricultural activities
and rapid urbanization created immense pressure on
water quality. The percentage of agricultural land is326

SEE - Kyoto, Japan, Nov.18-20, 2020

quantitatively, and propose implemented solutions.
The results can be one approach to control othernutrients or organic substances in the environment
and applied for better NPS and land-use area
management.
METHODOLOGY
Substance Flow Analysis (SFA)
Substance Flow Analysis (SFA) is anenvironmental accounting tool based on the conceptof mass balance in a specific area and time. SFA for
nitrogen provides a systematic assessment of flows
and stocks within a defined system in space and time.
It was undertaken to quantify nitrogen flows fromdifferent land-use area (as a process) in the Chi river
basin (Maha Sarakham region).

Fig. 2 Maha Sarakham province Location [13]Data Collection

System Boundary

Nitrogen flows in the system boundary weretraced to define quantity and pathway throughrelevant processes until discharge to theenvironment. The nitrogen flow diagram of thesystem boundary is shown in Fig 3.

The Chi river basin covers the middle part of thenortheastern region (Fig.1). The area of the basin in
Maha Sarakham province was selected to be thespecific system boundary.

Fig. 1 Chi River Basin [12].
Fig.3 Nitrogen flows

The Chi River basin area is 53.18% of Maha
Sarakham province (Fig. 2) which was 2,998 km2.
The land-use area in the system boundary was
categorized into community along the Chi River
6.83% (205 km2), agriculture 82.88% (2,484 km2),
forestry 3.94% (118 km2) and miscellaneous 2.63%(79 km2). The activities that have an impact on the
Chi River were only community and agriculture
along the Chi River. The major agriculture included
paddy field 62.17% (1,864 km2), corn 0.01% (0.3km2) and cassava 11.28% (338 km2). The period ofdata collection was in the year of 2018 (one year
period).

In order to know the nitrogen flows through thevarious land use categories, secondary data was
obtained from official reports by relatedorganizations and relevant literature review [14-29].
Details of data acquisition were described asfollows:
Statistical data
Official reports from governmental organizations
such as Department of Land Development, National
Statistical Office, Department of Irrigation, andOffice of Regional Environment.
327

SEE - Kyoto, Japan, Nov.18-20, 2020

Reference data
Due to unavailable data in the system boundary,secondary data (nitrogen concentrations) was
obtained from a nearby area, which has similar
management based on literature review was applied
to the nitrogen flows.

Stock

(PO4)
Rice straw(PO5)
Infiltration(PS1)

N in rice straw × area
× rice straw
N in input × %infiltration

Table 2 Data acquisition and calculation for farm
plantsAssumption and scope
Flows
Input

Main processes in the system boundary werecategorized by major agricultural activities affecting
the water quality of the Chi River, such as paddy
field, cassava and corn farming, community, and theChi River as the receiving water. Input flows
associated with the basic requirement of eachprocess. Stocks were quantified by the accumulated
nitrogen from input within the process and may beremoved from the process without interruption with
the Chi River. Output flows were traced by nitrogenflow in products of the processes or N discharged toother processes.

Fertiliser
cassava (FI2)
Irrigation corn
(FI3)
Irrigationcassava (FI4)

Calculation
The calculations basically multiplied the flows(which is recognized as activity) of input, output,
and stock of each land-use area in the systemboundary with their nitrogen concentration ([N], mg
N/L). Finally, the results of nitrogen flows wereshown in the unit of ton N/year. Nitrogen flows were
calculated based on mass balance over the processes.
Determination methods for nitrogen flows weresummarized in Tables 1-3.

OutputTable 1 Data acquisition and calculation for paddy
field
Flows
Input

Material
Fertiliser (PI1)
Irrigation (PI2)Rain water(PI3)
Seed (PI4)

OutputAtmospheric
fixation (PI5)
Burning (PO1)
Evaporation(PO2)
Surface runoff
(PO3)
Rice
production

Material
Fertiliser corn
(FI1)

Calculation
N in fertilizer × area ×loops
N in irrigated water ×
area × water
consumption × days
N in rainwater × area
× loopsN in seed × area ×loops
N in atm × area ×loops
N in input × %burning
N in input × %evaporation
N in input × %burning
N in rice × area

Stock

Rain water
corn (FI5)Rain water
corn (FI6)
Atmospheric
fixation corn
(FI7)
Atmospheric
fixationcassava (FI8)
Burning (FO1)
Evaporation(FO2)
Surface runoff
(FO3)
Corn
production(FO4)
Cassava
production(FO5)
Infiltration(FS1)

Calculation% N in fertilizer ×
area × fertilizer
consumption × loops% N in fertilizer ×
area × fertilizer
consumption × loops
N in irrigated water ×
area × water
consumption × loops
N in irrigated water ×
area × water
consumption × loops
N in rainwater × area
N in rainwater × area
N in atm × area ×loops
N in atm × area ×loops
N in input × % burning
N in input × %evaporation
N in input × factor of
runoffN in corn x area ×loops
N in cassava × area ×loops
N in input × %infiltration

Table 3 Data acquisition and calculation forcommunity
Flows
Input

Material
Water supply
(CI1)
Rice
consumption
(CI2)
Beef
consumption

328

Calculation
N in water supply ×
water consumption ×
population
N in rice ×
consumption ×
population
N in beef ×
consumption ×

SEE - Kyoto, Japan, Nov.18-20, 2020

Output

Stock

(CI3)
Pork
consumption(CI4)
Chickenconsumption
(CI5)
Milk
consumption
(CI6)
Egg
consumption(CI7)
Fresh water
animals
consumption(CI8)
Wastewater(CO1)
Infiltration(CS1)

population
N in pork ×
consumption ×
population
N in chicken ×consumption ×
population
N in milk ×
consumption ×
population
N in egg ×
consumption ×
population
N in fresh water
animals ×
consumption ×
population
N in wastewater ×
wastewater generation
rate × population
N in input × % stock

OutputStock

Atmospheric fixation
corn
Atmospheric fixationcassava
Burning
Evaporation
Surface runoff
Corn production
Cassava production
Infiltration

0.24
84.52
214.20
68.23
1.96
10.92
3,943.23
279.64

Table 6 Nitrogen flows in community process
Flows
Material
Flows(Ton/year)
Input
Water supply
10.10
Rice consumption
510.84
Beef consumption
22.69
Pork consumption
32.68
Chicken consumption
142.70Milk consumption
7.74
Egg consumption
41.18
Fresh water animals
237.78
consumption
OutputWastewater
299.09Stock
Infiltration
100.57

RESULTS AND DISCUSSIONSSFA calculation of the current situation (2018)

The mass balance of the flows was done tocompare to the calculation above. It was found thatthe paddy field had over the inflow of 1,411,039
tonne/year. This amount of nitrogen could be
adsorbed to the soil, whereas the farm had lower
input flow than output flow and stock. This could
have resulted from mechanisms of cassava planting.
The modeled consumption of the community
roughly showed that the input was more than stockand output.
The major flow of nitrogen into the Chi River
is from the paddy field, which is similar to researchdone in China [4,7]. People living the Chi river basin
are mostly farmers and reach irrigation during
drought season and plentiful rainwater in the rainyseason. Therefore, farmers in the system boundary
can plant rice all year round and leads to highnitrogen flow. However, people who live far fromthe Chi River but still in the range of the catchment
plants corn and cassava, which are the primary farm
plants in the northeastern region. Therefore the main
land-use area, which affects the nitrogen input inagriculture. The nitrogen flow from the community
affects the Chi River due to a non-point source ofwastewater discharge. Therefore the suggestion is tocontrol the fertilizer application in the paddy field
and burning of agricultural residue. Community
should reduce the flow of wastewater discharging
into the river by installing wastewater treatment unit.

Three processes included in the system boundary
were traced to the nitrogen flow and calculated theflows as detailed in the previous section. The resultsfrom each process are shown in Tables 4-6 asfollows.
Table 4 Nitrogen flows in paddy field process
Flows
Material
Flows(Ton/year)
Input
Fertilizer
42,674Irrigation
110,581
Rainwater
1,402,572
Seed18,588
Atmospheric fixation
15,397
OutputBurning
124,800
Evaporation
19,078
Surface runoff
1,113
Rice production
21,524
Rice straw
14,628Stock
Infiltration
1,890
Table 5 Nitrogen flows in farm plant process
Flows
Material
Flows(Ton/year)
Input
Fertilizer corn
4.21
Fertiliser cassava
2218.86
Irrigation corn
0.25
Irrigation cassava
291.62Rain water corn
0.17
Rain water corn
196.53329

SEE - Kyoto, Japan, Nov.18-20, 2020

Calumet Area. Greater Chicago, Environ.
Manag. vol. 45 (5), pp. 1096–1111.
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(2015). Controls and forecasts of nitrateyields in forested watersheds: a view overmainland Portugal. Sci. Total Environ. vol.
537, pp. 421–440.
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04/02/2019[11] Brunner, P.H. and Rechberger, H. (2004).
Practical Handbook of Material Flow
Analysis, Lewis Publishes, New York[12] Arunyanart N. and Limsiri C., UchaipichatA., (2017). Flood hazards in the Chi River
Basin, Thailand: Impact management ofclimate change. Applied Ecology andEnvironmental Research, vol. 15(4), pp. 841861.
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(2004).
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Sattelmacher, and Odum H. T. (1996). The
ground-cover rice production system(GCRPS): a successful new approach to

CONCLUSIONS
Land-use area and activities influence the flow ofnitrogen into the Chi River according to theapplication of fertilizer and other post-harvesting
activities. The communities along the Chi River also
take responsibility for NPS of nitrogen in terms ofwastewater discharge. The strategy could apply toagriculture management and wastewater collection
and treatment.
ACKNOWLEDGMENTS
The author wishes to acknowledge the National
Research Council of Thailand (NRCT) for researchfunding.
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331

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

EVALUATION OF ENVIRONMENTAL ENGINEERING EDUCATIONPROGRAM FOR STUDENTS FROM SOUTHEAST ASIA TO HIGHSCHOOL IN JAPAN1

Kenji Arai1, Tetsuo Morita2 and Toshikazu Nishio3
Maebashi Institute of Technology Graduate School, 2 Maebashi Institute of Technology, 3 Takasaki
Technical High School
ABSTRACT

A high school in Gunma Prefecture, Japan, conducted an environmental engineering education program forinternational students from Southeast Asia for 13 years from 1998 to 2010. The purpose of this study is tounderstand the effect of the program on former international students and the Japanese high schools thatparticipated in the environmental education program 10 years after its completion.
International students stayed in a Japanese home for a year and learned environmental engineering technology
while interacting with Japanese high school students. In order to sort out the exchange activities between former
international students and Japanese high schools, and to conduct a post evaluation of the program, a survey was
conducted with former foreign students and the Japanese high school students, the Southeast Asian and Japanesehigh school staffs, and the host families.
Using the survey data, a logic model for the environmental engineering education program was created. As aresult, it was found that three elements of cross-cultural understanding, training agricultural engineers, andacquiring language skills are important for global human resource development. And it was found that the threeelements involved four resources/inputs: homestay families, support for language learning, acquisition ofagricultural technology, and learning and living experiences in foreign countries. I was able to confirm that thefour resources exist in many places throughout the country, and there is a high possibility that the programs canbe applied nationwide, and there is a possibility to establish a mechanism to disseminate the programs for global
human resource development.
Keywords: engineering education, high school, Southeast Asia, evaluation, logic model
INTRODUCTION

in the promotion of the exchange program forinternational students of Asian agricultural highschools, as a result of the project there had been apositive effect not only on the international students,
but also on the students and staff involved [1].
A study by Goji at Hiroshima University on theinfluence of the experience of studying in Japan on
the intercultural adaptation of ex-students in theworkplace of foreign employees suggests that theexperience of studying abroad is positive forintercultural adaptation in the workplace. This effectwas confirmed by Omae et al. in their study [2].
The positive influence an experience of studying
abroad had on voluntary activities and careerdevelopment was also shown, and that time spent
studying abroad may promote voluntary activities andcontribute to career development. Iketani's influenceand significance of exchange programs withinternational students on Japanese people. Experienceof multicultural coexistence in the usual environment
on campus leads to increased contact with foreigners
in daily life. And that going out is not necessarily

For the development of the agricultural field in
Asia and the development of human resources thatcan play an active role as an international setting, anagricultural high school in Gunma prefecture in Japan,
accepted foreign students from Southeast Asia
(Philippines, Thailand, Malaysia, Indonesia,
Mongolia) for 13 years from 1998 to 2010 as part of
the Environmental Engineering Education Program(Asia Agricultural High School International Student
Acceptance Project) Even after the program ended,exchanges between former international students andJapanese high schools continued, and now exchange
programs between Japanese agricultural high schools
and the Philippines and Thailand are continuing.
PURPOSE OF THIS STUDY AND RESEARCHMETHOD
Previous Studies
The International Affairs Division of the General
Affairs Department of Gunma Prefecture stated that332

SEE - Kyoto, Japan, Nov.18-20, 2020

project and the impact of the project. Takada showedthat in the current situation and challenges [5] ofuniversity management plans, medium-term plansthat clarify the logical structure according to the logic
model are desirable for the formulation of mediumterm plans for national universities. In this research,
we considered the research method with reference tothe structural analysis using the logic model presented
by Takada.
The aim of this study is to reveal the effects thathave been given to former international students andthe Japanese high schools 10 years after the end of theenvironmental education program.

internationalization. In this way, many previous
studies have shown the effects of studying abroad or
accepting international students [3].
In Okuda's research trend on the effects of career
education and vocational education in high school,
most of the studies that examined the effect of career
education in high school were biased toward focusing
on the effect of "before high school graduation." Itreveals that very few studies have analyzed the effects
on “employment” [4].
Purpose of This Study
The environmental engineering education
program implemented in Gunma Prefecture was
implemented as an advanced example of local
government in career education and international
understanding education. Utilization of resources
such as farms and agricultural high schools in local
governments, ex-students who have completed the
project still have exchanges with Japan, short-term
exchange programs between Japan and Asia started,
agricultural technology in Asian countries the featureof this research is that it is highly likely to lead to thedevelopment of human resources with the ability. The
Asian Agricultural High School International Student
Acceptance Program has completed 178 students in
13 years, and most of them have advanced toagriculture and related industries. Many former
international students return to their home countries
and play an active role as leaders in agriculture andrelated industries, and some former international
students are playing an active role as a bridge between
Asia and Japan by taking advantage of the Japanese
language skills they have learned. However, there areno cases that summarize the business and specificallypresent the effect.
Therefore, in this research, the structure of the
program is organized by the logic model. In order tounderstand the content of the project and the effect, I
got the information about the program from thematerials and teachers in charge. 10 years have passed
since the end of the project, and some former
international students and teachers in chargeinterviewed about the merit and demerit of the projectand its difficulties. After that, the implemented
projects were analyzed and evaluated item by item.
Although there are very few cases of ex-post
evaluation, it is important in this research that theevaluation was made after the project was completed.
In this study, based on the fact that Okuda's postproject impact analysis is scarce, we investigated thecareer paths of former international students after the

Research Method and Target
The research method was as follows. The logic
model was applied to structurally deconstruct thecontents of the program, and to understand theresources utilized in each component, the activity
contents, and the produced results. The logic model isa systematic diagram of the path toward therealization of the ultimate vision of a business ororganization, and is likened to a business blueprint.
The research target is a project to accept
international students from Asia to Japan. There are
178 former international students. Since 10 years
have passed since the end of the project, it wasdifficult to obtain quantitative information from all
former foreign students, such as conducting aquestionnaire with all of them. Therefore, we
conducted a hearing from 33 former international
students who we could contact and visit, andconducted a questionnaire and a hearing from thefaculty members who were in charge of theinternational students at that time, constructed a logic
model, analyzed and evaluated it. We also conducteda supplementary survey on mutual exchange between
Asian countries and Japanese high school students,
which began in 2012. The specific method is asfollows.
1) Implementation of environmental engineering
education program and hearing survey2) Construction of logic model for environmental
engineering education program3) Analyze and evaluate the logic model tounderstand the effect of the program.
EDUCATION PROGRAM AND SURVEY
Engineering Education Program333

SEE - Kyoto, Japan, Nov.18-20, 2020of their international students, and they will stay in a
family centered on farmers. In August, theyexperienced about a month of farm stay and practiced
practically to learn agricultural technology.
Fig. 1 shows various agricultural training
experiences such as rice planting, crops,
biotechnology, livestock, and landscaping. Fig. 2
shows Japanese training and life in Japan.

International students from Southeast Asia will
stay home in the home of a Japanese family for a year
and learn environmental engineering and agricultural
techniques while interacting with Japanese highschool students. Students came to Japan in May andfor the first semester until August, they mainly
studied Japanese at Gunma Prefectural Seta
Agriculture and Forestry High School. During thesecond semester starting from September, students
will be divided into eight agricultural high schools in
Gunma prefecture, depending on the learning content

Hearing Survey
In order to understand the structure of the program,the staff in charge of international students at the time
provided information such as the annual schedule ofthe program, the timetable of the international
students, the event plan, and the career paths of thecurrent international students. Interviews wereconducted with former international students and thestaff in charge of international students in September
and December 2019 for former international students,
and in February and March 2020 for former staff incharge of international students. The contents of theinterview were the merits and demerits of the
program, and the difficulties in implementing the
program.
The items identified as merits in the results of theinterview survey were learning languages,
understanding different cultures, establishingconnections with Japan, having a valuable experiencein adolescence, and being exposed to agricultural andadvanced technologies. Disadvantages include highprices, differences in lifestyle and religion, and fooddeference.
Among N=33, the career paths of ex-international
students obtained from the interview survey wereshow that they were more likely to work in agriculture
and agriculture-related industries. And they active asa leader in various fields.

Fig. 1 Experience of various agricultural training(taken by the international exchange teacher)

LOGIC MODEL ANALYSIS
Logic Model for Program
In this study, an environmental engineering
program was analyzed and a logic model was created.
Table 1 shows the flow of the manifestation ofplanning effects along the framework of resources,
activities, outputs, and outcomes.
The purpose, inputs, activities, initial outcomes,
intermediate outcomes, and final outcomes of thelogic model of the environmental engineering
education program are shown below. The backgroundFig. 2 Language learning and life in Japan (takenby the international exchange teacher)
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SEE - Kyoto, Japan, Nov.18-20, 2020

Table 1

Concept of logic model and each component (Created by the author)

Elements
PurposeDifinition

Main cases

What the plan aimes for

Human resource development capable of international success・Homestay families

Resources

・Support for language learning

Management resources used to excute the plan

・Agricultural technology acquisition
・Learning and life experience in Japan
・Home stay・Lessons and life abroad

Activity

・Learning and practical training at agricultural high school

Means for implementing the plan・Practice at farms and research facilities
・Support by assigning Japanese teachers・Daily language activities
・Home stay・Experience living abroad

Initial outcome

Elements needed to achieve the intermediate outcome

・Agricultural knowledge acquisition
・Agricultural practical skills acquisition
・Language learning support
・Intercultural understanding

Intermediate outcome

・Agricultural engineer training

Elements needed for final outcome

・Language acquisition
Final outcome

・Development of global human resources

Goals of what they are trying to change

was started with the aim of agricultural reconstructionand economic development in Asian countries.
Against this background, in Asian countries,
agriculture has been a key industry of the country
until recently, but due to recent changes in theindustrial structure due to economic growth and thedecline of agriculture, the reconstruction ofagriculture has become an issue. Based on this, thisprogram aims to develop human resources who canplay an active role internationally.

to the successful business was that agriculture, which
was a key industry, was in danger of declining as the
economic growth of Asian countries proceeded, andthe aim was to rebuild agriculture in Asia. The
purpose of the program was to achieve the aim ofdeveloping human resources who can be active
internationally.
Table 1 shows the definition of the constituent
elements in the logic model and the cases handled in
the research. The purpose of what the plan aims at isset, and the necessary elements to achieve it are
resources. Table 1 shows the relationship between
resources and final outcomes.
A short-term exchange program between Japan andAsian countries started in 2012, triggered by anenvironmental engineering education program.
Compared to the one-year program, there areadvantages such as the lower cost and shorter
duration that makes it easier to participate in, and it
can be expected to play a role as an opportunity todevelop human resources who can play an active roleinternationally.

Resources (inputs)
Resources (inputs) are all management resources
used for executing the plan. The number of families
accepting international students was 149. In language
learning, 5 Japanese teachers, 1 counselor, classmates,
HR teachers, exchanges among international students,
etc. were supported. All the elements and conditions
that agriculture can tackle, such as nature, farmland,
prefecture agricultural high school and agriculturalcollege, agricultural testing grounds, farmers, andagricultural engineers, were taken as agricultural
technology acquisition. In addition to the above, theparticipation of international students in school
events and daily life were taken as learning and life
experiences at Japanese high schools.

Analysis by Logic Model
PurposeThe environmental engineering education program
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SEE - Kyoto, Japan, Nov.18-20, 2020

Long-term program
Hierarchy

Production of 178 human resources

Final outcome

Globalhuman
resource
development

Necessary for training human resources
who can play an active role internationally

Short-term program

210 Asians

Intermediate outcome

Crosscultural
understandingInitial outcome

Experienceliving in aforeigncountry

Acquisitionofagricultural
knowledge

Acquisitionofagricultural
practical
skillsForeignclasses/life

Agricultural
high school
study/practicePractical
training at
farms andresearch
facilities

Homestay

Specific business content

Homestayexperience(Output/Activity)

Fig. 3280 Japanese

Agricultural
engineertraining

Acquisitionof language
abilityLanguagelearning
supportJapaneseteacher
placement

Dailylanguage
activities

Structure of the Program (Created by the author)
and language learning support for acquisition of
language ability are initial outcomes.

Status of activities
This study dealt with two programs. It is a one-year
environmental engineering education program fromSoutheast Asia to a Japanese high school, and a shortterm mutual exchange between high school students
between Japan and the Philippines and Japan and
Thailand since 2012.
Activities in the program include homestay forcross-cultural understanding and lessons/living inforeign countries, learning/practice at agricultural
high schools to train agricultural engineers andpractical training at farms and research facilities, andlanguage acquisition. Support by a Japanese teacher
for daily activities and daily language activities.

Status of interim outcomesIntermediateoutcomesarecross-cultural
understanding for global human resource
development, agricultural engineer training, andlanguage acquisition, and these are the conditions forachieving the final outcome.
Status of final outcome
The goal of the program is to develop humanresources who can be active internationally.
Therefore, the final outcome was global humanresource development. In the long-term program, 178international students from Southeast Asia completed
one year study abroad in Japan, and in the short-term
program of mutual exchange between Japan and Asia,
a total of 280 Japanese high school students and 210
Philippine and Thai high school students havefinished the exchange.

Status of initial outcome
As an intermediate outcome, homestay to realize
cross-cultural understanding, life experience inforeign countries, acquisition of agricultural
knowledge to realize cultivation of agricultural
engineers, acquisition of agricultural practical ability,
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SEE - Kyoto, Japan, Nov.18-20, 2020

Effects of Program

improvement in learners’ motivation.
Through an environmental engineering programthat lasted 10 years, 178 global human resources havebeen trained and are active. It also led to a short-term
mutual exchange program, with 280 Japanese highschool students and 210 Asian high school students
completing the program, improving cross-cultural
understanding and language skills, learning
agricultural technology in Asian countries, andimproving motivation to learn.
From the above, it was found that there is an effectof improving the motivation of high school students,
and by recognizing this effect, the cooperation of highschools and local residents can be obtained, and theeffectiveness of this program could be demonstrated
empirically.

The structure was created from the results ofhearing the program, the logic model of theenvironmental engineering program, and the conceptof each component (Table 1). Fig. 3 is a model of thesituation in which international students fromSoutheast Asia got their current course after studying
for one year in Japan. It was found that the flow of
inputs, outputs, and outcomes has the structure shownin the figure, which leads to the achievement of the
project purpose.
From Fig. 3 and Table 1, four resources (inputs),
homestay, support for language learning, acquisitionof agricultural technology, learning and living
experience overseas are important elements of the
program and are linked to outputs and outcomes.
It was found that activities that utilize the four
resources have the effect of leading to anunderstanding of different cultures and an
improvement in motivation for learning, leading to
the path to agriculture and related industries, andleading to the development of human resources who
can play an active role internationally.
The resources used in this program are available
to many local governments throughout Japan, and webelieve that if the program spreads nationwide in the
future, it will lead to further global human resource
development.

Subject for Next Study
We created a logic model to show the structure andeffects of the long-term study abroad program (Figure3). In addition, the structure of the short-term
interaction program was outlined. The short-term
exchange is realistic considering the ease ofparticipation because of reduced financial costs andthe effect on many students, and as a result, it
continues even now. In many cases, short-term
exchanges have led to long-term study abroad andinternational work. The long-term study abroad
program has immeasurable effects such as crosscultural understanding and language learning effect,
but the financial burden is large. From this, we thinkthat it is important to focus on short-term exchanges
and build a system that will lead to long-term
exchanges and future work. Economic support suchas scholarships and crowdfunding is also required in
the mechanism, and it is possible to quantitatively
show the effects of the benefits of long-term
exchange and to create a transition from short-term
exchange programs to long-term programs and global
human resource development. This is a future issue.
It is also an issue to evaluate programs in local
governments that practice environmental engineering
education programs outside Gunma prefecture.

CONCLUTION
Results of This Study
The results obtained in the present study can besummarized as follows:
1) Cross-cultural understanding is important for
global human resource development.
2) It is important to train agricultural engineers todevelop global human resources.
3) Acquisition of language skills is important for
global human resource development.
4) 1) to 3) are linked to global human resource
development.
This study evaluated an environmental
engineering education program for international
students from Southeast Asia to Japanese highschools.
By implementing the program, we also found that
there is a tendency to get a profession that makes useof specialized skills, that international exchange
continues even after the project ends, which can leadto language learning opportunities and an

REFERENCES[1] General Affairs Department of Gunma Prefecture,
Promotion of exchange programs for Asian
agricultural high school students, Municipal
Internationalization Forum, No. 175, 2004. pp. 811.
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SEE - Kyoto, Japan, Nov.18-20, 2020

[2] Omae Y., Kasuya R., Yoshino K., Mitsui T. andand Takahashi H., Effects on Self-activity andCareer of Experience of Studying Abroad, Journalof Japan Educational Technology, Vol. 40, No.
Suppl., 2016, pp. 21-24.
[3] Iketani T., The Value of the Joint Instruction with
International Students at Kobe Shoin Women’s
University, Journal of the Faculty of Letters,
Kobe Shoin Women’s University, No. 5, 2016,
pp55-70.
[4] Okuda J., A Review of Studies on Effect ofCareer Education and Vocational, Bulletin of
Hokuriku University, No.47, 2019, pp.37-56.
[5] Takada E., Current Status and Issues of University
Management Plans: Focusing on Analysis of
National University Mid-term Plans from Logic
Model Perspective, Kobe University, University
Education Research, No. 28, 2020, pp.29-39.

338

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

CAUSAL RELATIONSHIP MODEL OF PROBLEMS IN PUBLIC
SECTOR PROCUREMENT
Tanayut Chaitongrat1, Surapong Liwthaisong2, *Preenithi Aksorn3, Wuttipong Kusonkhum4,
Narong Leungbootnak5, and Korb Srinavin6
1,2
Faculty of Architecture, Urban Design and Creative Arts, Mahasarakham University, Thailand;
3-6
Faculty of Engineering, Khon kaen University, Thailand

ABSTRACT
Although e-Government Procurement System has been adopted and used in the public sectors, small amountof studies has concerned about the procurement relating to a construction sector. This research, therefore, wasintended to investigate concordance between a hypothetical causal model and empirical information.
Questionnaires were used with 353 samples from the government officers. Statistical analysis was conducted byutilizing SPSS 25 and AMOS 25 to determine percentage, mean, standard deviation, factor analysis and structural
equation modeling (SEM). Results revealed that the analysis model was in accordance with empirical information
which resulted in Chi square (χ2) = 43.376, χ2/df = 1.276, df = 34, p = 0.130, NFI = 0.989, GFI = 0.979, CFI =0.998, RAR = 0.008, RMSE = 0.028 and R2 value = 0.819. This indicated that the causal relationship model fromthis study was appropriately corresponding to the empirical information at a substantial level.
Keywords: Causal relationship model, Government Procurement, Project Management

helps to enhance work productivities. [8].
Although e-Government Procurement System has
been adopted and used in the public sector, many
problems related to the process remain unresolved
and the actual needs of stakeholders remainunfulfilled [9]. Several research and media reports
have reflected upon the problems which include nontransparent procurement in public sector’sconstruction projects, purchase prices which arehigher than the actual price, and nepotism [10]. Wareet al. (2007) [11]. divided the corruptions from thegovernment procurement into four types: 1) bribery,2) bid rigging, 3) a false company, and 4) others.
These issues allow people who are responsible for the
procurement could have financial gains from indirect
profits by reducing quality of supplies. The
compromised quality consequently contributes tomassive losses of the annual government’s
expenditure which were around 10-20% of a project
spending [12]. Moreover, construction materials thatare acquired through the procurement process may
not commensurate with whether prices or quality [13].
These issues have raised the many authors’ interests
to discover the best solutions for developing the
public sector’s procurements. [2]-[4],[8]. However,small amount studies have concerned about the
procurement relating to a construction sector.
Therefore, this research aimed to synthesize
problems that are related to the Government
procurement regarding the construction projects andto develop the causal relationship model of suchproblems. The research hypothesis is the Causal
Relationship Model of Problems in the Public Sector

INTRODUCTION
Public procurements are highly significant for anational budget allocation in many departments suchas educational management, state security,
infrastructures, basic structures, health cares, andpublic safety [1]-[3]. Such the government
procurements and supplies management are
significant in many departments. Therefore, public
procurements are considered the heart of delivering
civil services and demonstrating results of the state’s
operational achievements.
The average values of the public procurements foreach country ranged between 10-15% of the total
Gross Domestic Product (GDP) [4]. The
procurements are particularly more evidenced inconstruction industry which resulted in 2 billion US
dollars per year [5].
In order to reciprocate the world’s economic
growth, procurement processes in many countries
have rapidly developed in different aspects. Amid thechanging environment, the rapid developments were
designed to facilitate and enhance tasks execution thatare performed by public and private sectors as well as
the civil society [6]. As a result, the state has beenenabled to perform its tasks in strengthening theprivate sector which mutually contributes to thedevelopment of the country’s sustainable growths [7].
Technology advancement that play a significant roleis all public and private organizations mostly rely on
information technology to receive higher volume,
rapidly transferred, and constantly updated
information. Hence, the technology consequently
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Procurements fits with the empirical information. The
results of the research will benefit many stateagencies’ operations as well as other organizations inThailand and abroad in adopting to their respective
works.

RESEARCH METHODOLOGYThis research was intended to develop a causal
relationship model of problems in public sector
procurements for research methodology as following;
A. Units of analysis of this quantitative research werebased on state’s construction project procurements.

LITERATURE REVIEW

B. Population and samples

The previous studies by Chaitongrat et al. (2017)and Leungbootnak et al. (2018) [5]-[6] mentioned the
problems in public sector procurement focusing on
the Government construction projects in 3 key factors(Fig. 1) which are;Factors 1: The Planning Process (PP) factors
referred to lack of staff’s understanding in rules andregulations. [6] stated that the lack of understanding
could cause the problems in 3 different ways: whichare; 1) Preparation problems (PPA), 2)
Announcement and clarification problems (PPB), and
3) Procurement process problems (PPC). As a result,many suppliers were unable to prepare document on
time. Hence, there were less competitors in theprocess.
Factors 2: the project managements andtechnicality (PMP) indicated to the complication in
working procedure, budgeting, and assessments
which could contribute to low-quality of partners ofcontract. This factor consisted of 2 observed variables,
which are; 1) Project management problems (PPE)and 2) Technical problems (PPD).

In this research, population and samples consistedof 5,024,885 procurements of state’s construction
projects (data acquired between October 2018 –September 2019) The number of samples were
determined at approximately 20 times of observed
variables in accordance with the concept that wasdeveloped by Hairs et al. (2010) [14]. This concept
suggested that the lowest criteria in determining
samples to analyze Structural Equation Modelling(SEM) should be 5-10 respondents per 1 evaluative
parameter. This research model comprised of 36
parameters which indicated that 180-360 construction
projects that involved state’s procurement wererequired.
C. Instrument and its quality
This research employed questionnaires [15]. The
construction of the research tool and its quality
evaluation were made in the following steps.
1) Studying of documents, concepts, theories, andresearch that are relevant to components whichconstitute the procurement problems.
2) Formation of 40 questions which were divided
into two parts; personal factors, and problems related
to procurement of construction projects. The questions
were constructed as standard measurements inreference to Rating Scale designed by Likert’s 5assessment levels of the highest, high, moderate, low,
and the lowest.

Problems related to
procurement process (PP)
Problems regarding project
management andtechnicality (PMP)(+)

Problems inpublic sector
Procurement

3) The questionnaires were assessed by a panel of
5 experts, in order to determine language
appropriateness, concordance between questions andresearch objectives, and content validity.

Endogenous organizational
problems and external
influences (OEP)

4) Assessment scores as determined by the experts
were furthered tested for Index of Item-Objective
Congruence (IOC). Only questions that received IOC
index value of 0.60 or higher were selected.

Fig. 1 Hypothesis Measurement Model.

5) Amendments of questions as perrecommendations by the panel of 5 experts were
executed which finally yielded the last 36 questions.

Factors 3: Endogenous organizational problems
and external influences (OEP) imply to the inter- andintra- organization conflict which could deliver thedelaying of a projects. This factor consisted of 2
observed variables, which are; 1) Internal problems(PPF) and 2) External problems (PPG).

6) Trying out of questionnaires with a populationof 30 who were not participating in the actual research.
Then, each question were evaluated for discrimination
values, in order to itemize the question that received
discrimination values at 0.20 or higher. All of these 36
questions scored discrimination values between 0.22
and 0.73 whilst the overall confidence of thisquestionnaires was 0.986 which illustrated that thequestionnaire is highly trustworthy.
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D. Data collection

There were also 4 mediating variables involved
which were, Procurement Project Management (PPM),
Conduct
Procurement(ConP),
Administer
Procurement (AP) and Closing Procurement (CP).
According to the concordance assessment of Causal
Relationship Model of Problems in Public Sector
Procurements, results were; Chi square (χ2) = 43.376,
χ2/df = 1.276, df = 34, p = 0.130, NFI = 0.989, GFI =979, CFI = 0.998, RAR = 0.008, RMSE = 0.028 andthe value of R2 = 0.819. Thus, the model is inaccordance with the empirical information from thisresearch. The model is capable of explaining andpredicting problems that are related to public sector
procurements at 81.9 % as further elaborated in Figure
2 and Table 1.

The government officers were systematicallycontacted for assistance and cooperation. The datacollection process, initiated in January 2020 andcompleted in February 2020, received 360 ofcompleted questionnaires which were accounted for
100% of the response rate.
E. Data analysis
Computer packages, SPSS25 and AMOS25, wereused to assess concordance between the model andempirical information by considering statistical Chi –square, Adjusted Goodness of Fit Index (AGFI), andRoot Mean Square Residual (RMR).
Data analysis was divided into 3 phases which
were; 1) the results of information analysis regarding
samples’ backgrounds, 2) the results of basic
statistical analysis of variables that were used in the
research by considering mean, standard deviation,
elaboration regarding each studied variable andpercentage analysis of Nominal Variable and Ordinal
Variable, 3) the results of Causal Relationship Modelof Problems in Public Sector Procurements which was
determined against Goodness of Fit of the model as
per 9 assessment criteria which were; p-value or X2,
X2/df, Normal Fit Index (NFI), Goodness of Fit Index(GFI), Fit Index (CFI), Standardized RMR, and Root
Mean Square Error of Approximate (RMSEA) [16].

Table 1 Demographic profiles (n=353)
Factors

RESULTS

Frequency Percentage Mean SD

GenderFemale
Male

161
192

45.6
54.4

Age (years)
< 20
21-30
31-40
41-50
51-60

0
26
102
119
106

0
7.4
28.9
33.7
30.0

Level of education
Diploma degree
Bachelor degree
Master degree
Doctoral degree

32
225
91
5

9.1
63.74
25.8
1.4

28
75
84

7.9
21.2
22.9

165

46.7

14

4.0

-

-

122
40
43
9
129

34.6
11.3
12.2
2.5
36.5

10

2.8

124
6
28

35.1
1.7
7.9

-

-

-

-

-

-

-

-

-

-

-

-

9.5

7.6

-

-

-

-

-

-

1) Respondent profiles
Positions
Director of a division
Purchasing committee
Committee of Building
Inspector
A material department’s
officer
A user

54.4% of the sample groups were male. The
majority of samples were between 41 and 50 years ofage which formed 33.7%. As for educational
background, bachelor degree holders represented amajority of the respondents which accounted for
63.74 %. Most of these individuals have worked in amaterial department (46.7%), and Building
Inspectors Committee (22.9%), respectively. The
average experience in procurement of construction
projects was 9.5 years (SD=7.6). The procurements
mostly belong to local administration organizations(36.5%), and followed by other governmental
agencies (34.6%). Lastly, the construction projects
mostly involved with building constructions (35.1%)
and road constructions (34.0%). (Table 1).

Average experiences inconstruction projects(years)Type of organizations
General governmentState Enterprises
Educational Institution
Government hospital
Local Administration
Organizations
Other governmental
agencies2) According to the development of Causal
Relationship Model of Problems in Public Sector
Procurements by using Structural Equation
Modelling (SEM) to determine concordance of themodel and empirical information, 3 exogenous
variables were revealed 3 main factors which are;Planning Process (PP), Other Exogenous Problems(OEP), and Project Management Problem (PMP).

Types of construction
projects
Building constructions
Road constructions
System utilities

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SEE - Kyoto, Japan, Nov.18-20, 2020

Table 3 Concordance value of the measuring modelfor each latent variables related to PPSC Model.
LatentVariab
le
PP

PMP

OEP

Obse
Regression Weights
rved
Estim
Varia
SE
CR
ate
bles
PPA
1
PPB
1.10
0.04
26.70
PPC
1.19
0.05
25.61
Path coefficient =0.51
PPE
1
PPD
1.06
0.04
29.45
Path coefficient =0.33
PPF
1
PPG
0.93
0.04
26.02
Path coefficient =0.40

Regression
Standardized Weight

R2

*
*

0.85
0.87
0.97

0.71
0.76
0.93

*

0.90
0.94

0.81
0.88

*

0.94
0.87

0.88
0.76

p

0.82

Note: * Statistical significant level (p<0.05)
Fig. 2 Results of accuracy analysis of the Causal
Relationship Model of Problems in Public Sector
Procurements.

Table 3 illustrates concordance of each variable inthe measuring model which, when construct themodel by using these variables, revealed that themodel of problems in public sector’s procurement
was statistically significant. In addition, thestandardized regression weights that ranged between
0.85 to 0.97. Each of these variables related to latentvariables and square multiple correlation value (R2)
at statistical significance level. The coefficient ofdetermination of the observable variables of the
problem in procurements was calculated to be
between 71 to 93 %. The highest standardized
regression weights were that of evaluate contractor (β= 0.97), endogenous organizational problem (β =0.94) and technicality (β = 0.94), and preparation andplanning (β = 0.85) respectively.

3) According to an analysis of the Direct Effectand Indirect effect of variables that influence problems
related to public sector’s procurements of construction
project, there are 7 variables that generally influencesuch procurements at statistical significance level of
0.05. These variables namely; preparation andplanning, announcement and explanation, evaluate
contractor, management, technicality, exogenous
problems, and indigenous problems. Three variables
that one-directionally influenced problems of public
sector’s procurements of construction projects were
procurement procedures, endogenous organizational
problems and external influences, and project
management and technicality (Table 2).
Table 2 Statistical concordance of the accuracy
analysis of the Causal Relationship Model ofProblems in Public Sector Procurements (PPSC)

Index

Prior to Model
After Model
Adjustment
Adjustment
Criteria
Statistical Assessment Statistical Assessment
Value
Results
Value
Results

X2/df< 3.00

2.693

Pass

1.28

Pass

p-value of> 0.05X2<0.001

Fail

0.13

Pass

P

NFI

> 0.90

0.974

Pass

0.99

Pass

GFI

> 0.90

0.950

Pass

0.98

Pass

CFI

> 0.95

0.984

Pass

0.99

Pass

RMR

< 0.08

0.012

Pass

0.01

Pass

RMSEA < 0.08

0.069

Pass

0.03

Pass

-

-

0.82

Pass

R2

0.5-1

Fig. 3 PPSC model for Thai public construction
project procurements

The model in Figure 2 showed a set of guidelines
on PPSC for Thai public construction project
procurements with the weight in each latent factor:
1) Problems related to the Planning Proces: thegovernment should focus on the procurement
planning since the beginning of the process; the TOR
writing and specification, then making ananouncement, and providing enough time to writing a
342

SEE - Kyoto, Japan, Nov.18-20, 2020

compatible with the pre-determined criteria which
could be illustrated as per the following reasons;proposal correctly. Last but not least, the government
should monitor the middle price for the government
partnerships
2) Problems regarding project managements andtechnicality: the government should be strict on the
procurement timeline, conflict between stakholders,
and the quality of the construction projects.
3) Endogenous organizational problems andexternal influences: the government should emphasis
on a budget allocation for a construction project inorder to reduce some problems about the low-qualityof interested vendors sending their proposal lower
than the middle price. Moreover, the relatedorganizations suppose to focus on risks from theinterorgnaisation that can effect the governent
procurement.

1) Due to the Structural Problem Equation Modelof the Public Sector Procurements that has beendeveloped by utilizing theories and other previous
research are relevant to this research, and by adheringto the content validity. Each step requires contextual
analysis of the problem’s components by prioritizing
prior to being used to construct the questionnaire that
subsequently checked by qualified experts andsubjected to further adjustments prior to being usedwith trial samples. The questionnaire was proven tohave high reliability, and in accordance with empiricalinformation as its construct validity was verified byexisting IOC of latent variable measurement modelthat has been developed by using relevant theories andresearch. Furthermore, the questionnaire’s confidence
level which was determined by assessment of thecollected information was also high as well. Therefore,
the above mentioned reason may enhance theefficiency of the structural equation model that is
related to public sector’s construction project
procurement. Although further adjustment of themodel maybe required, but this helps to shape themodel to be more statistically appropriate.

DISCUSSUION
According to the results, state’s construction
project procurements are highly problematic due tomany causes for which 3 compositions are capable ofexplaining the said problems at 82 %. These
compositions are;2) According to the sample group of this research,
expressions and practices were in accordance with thetheories and other research that were used to develop
the structural equation model of problems in public
sector’s procurements of construction project. The
phenomenon could have been a reflection of theactuality in the public sector’s procurements that has
been practiced. All of the findings indicated that thedeveloped model is in accordance with empiricalinformation and vice versa. Also, there are 3 variablesof direct influence coefficient which were; problems
that are related to procurement process, endogenousand exogenous organizational problems, and project
management problems and technicality.

1) Problems related to procurement process: As
per the research, path coefficient value was at 0.51 andthe problems mainly stemmed from evaluate
contractors, announcement and explanation, and work
preparation and planning. This finding is in line with;the 2012 reports from the Office of the Auditor
General of Thailand (OAG) which sated that problems
and inaccuracy in the procurements were due to theabsence of the procurement planning, andChonpitakwong B. et al., 2009 [17]. which studied
obstacles in implementing the e-Procurement system.
2) Endogenous organizational problems andexogenous organizational problems: These problems
resulted in the path coefficient of 0.33 which due
mainly to endogenous problems of state offices andexogenous problems of state offices. The finding was
supported by [10] . who explained that operators must
thoroughly and carefully study each step of the
procurement process.

CONCLUSION
The research reveals problems in public sector’sconstruction project procurement are highly
problematic. There were 36 problems that were foundwhich could be categorised, as per the main
components, into 3 groups; the problems that are
related to procurement process, the endogenous andexogenous organizational problems, and the project
management problems and technicality. As a result,the obtained information could be used to explain thevariance value of all variables at 82 %. Eachcomponent’s details can be concluded hereafter;

3) Project management problems and technicality:
The research resulted in the path coefficient value of0.40 which due mainly to problems related to project
management and technicality.
The Concordance assessment of the Structural
Problem Equation Model of Public Sector
Procurements revealed that the Causal Relationship
Model of the Problems that influences Public Sector
Procurements that has been developed well related tothe empirical information. As per the research,statistical chi square value was not significant (P-value=0.130), relative chi square value was 1.276, NFI
index was 0.989, GFI index was 0.979, CFI index was
0.998, whereas Standardized RMR value was 0.008
and RMSEA value was 0.028. All of these value were

1) The problems that are related to
procurement process, the research revealed that state
offices were generally highly problematic which,upon considering factor loading of each observed
variables, stipulated that such problems were; problem
with evaluate contractor β = 0.935, problems with
343

SEE - Kyoto, Japan, Nov.18-20, 2020

announcement and work explanation β = 0.874, andproblems with preparation and planning β = 0.850.

Khoman, S., Wanrak M., Vatchareeya T.,
Chayun T., Chatchai C., Sutthi S., Sittikorn N.,& Napon S., The World Trade Organisation’s
government procurement agreement: A study ofthailand’s preparation for accession, 2009,
Research report submitted to the ComptrollerGeneral’s Department, Monistry of Finance.
Bangkok; Thailand. (in Thai).
[5] Leungbootnak N., Chaithongrat T., & Aksorn P.,
An Exploratory Factor Analysis of Government
Construction Procurement Problems, MATEC
Web of Conferences 192, 02053, 2018, pp.1-4,
DOI:
https://doi.org/10.1051/matecconf/20181920205
7.
[6] Chaithongrat T., Leungbootnak N., Aksorn P., &Manu P., Application of Confirmatory Factor
AnalysisinGovernment
Construction
Procurement Problems in Thailand, International
Transaction
JournalofEngineering,
Management, & Applied Sciences &Technologies., Vol 8, Issue 3, 2017, pp. 221-231.
[7] Brammer S., & Walker H., Sustainableprocurement in the public sector: Aninternational comparative study, International
JournalofOperations&
Production
Management, Vol 31, Issue 4, 2011, pp. 452-476,
DOI: 10.1108/01443571111119551.
[8] Du, J., Jiao,Y.Y., Jiao, R.J., Kumar, A. & Ma, M.,
A case study of obsolete part procurement
process reengineering. Paper presented at the2007 IEEE International Conference on
Industrial Engineering and Engineering
Management, 2 - 5 Dec 2007, Furama Riverfront
Hotel,
Singapore,
DOI:
10.1109/IEEM.2007.4419410.
[9] Chaithongrat T., Leungbootnak N., & Aksorn P.,
Exploratory Factors Analysis of the Corruptionin Public Procurement, Engineering Journal of
Research and Development, Vol 29, Issue 3,
2018, pp. 5-14.
[10] Chaitongrat T., Leungbootnak N., Kusonkhum
W., Deewong W., Srinavin K., Measurement
model of good governance in government
procurement, IOP Conference Series Materials
Science and Engineering, 639:012024, Volume639, Issue 1, 2019, DOI: 10.1088/1757899X/639/1/012024.
[11] Ware N., Hopper K., Tugenberg T., Dickey B.,
Fisher D., Connectedness and citizenship:
Redefining social integration. PsychiatricServices. 2007 April; in press. 2007.
[12] Chaithongrat T., Leungbootnak N., & Aksorn P.,
A Confirmatory Factors Analysis of the Successfactorson
Government
Construction
Procurement Project, SWU Engineering Journal,
Vol 13, Issue 2, (2018), pp. 131-140.
[13] ADB, Quality Guidance Note on Procurement,
2018,
DOI:
http://dx.doi.org/10.22617/TIM189229-2.
[14] Hair J.F., Black W.C., Babin B.J., & Anderson
R.E., Multivariate Data Analysis, Seventh
Edition, 2010, Prentice Hall, Upper Saddle River,
New Jersey.
[15] Neuman W.L., Social research methods:
qualitative and quantitative approaches, 2011,
Boston, MA: Pearson.
[16] Andy F., Discovering statistics using IBM SPSS
statistics. 4th edition, 2013, Sage Publications Ltd.
London, United Kingdom.
[17] Chonpitakwong B., Kusonkhum W., Chaitongrat
T., Srinavin K., & Charnwasununth P.,[4]2) The eendogenous and exogenousorganizational problems, the research revealed thatstate offices were generally highly problematic which,upon considering factor loading of each observed
variables, stipulated that such problems were; problem
with project management β = 0.935 and problems withtechnicality β = 0.898.
3) Problems that are related to project
management and technicality, the research revealed
that state offices were generally highly problematicwhich, upon considering factor loading of eachobserved variables, stipulated that such problems
were; endogenous organizational problems β = 0.938
and exogenous organizational problems β = 0.873.
The concordance assessment of the structural
relationship model that affects the public sector’sconstruction procurements, developed by using
empirical information, revealed a good level ofconcordance which was determined by referring to;statistical chi square value that was not significant (Pvalue =0.130), relationship chi square (1.276), NFI
index (0.989), GFI index (0.979), CFI index (0.998),
Standardized RMR (0.008) and RMSEA (0.028).
Upon considering direct influences, indirect
influences and overall influences of the problems inpublic sector’s construction project procurement, thiscan be concluded that; direct influences has direct
influence coefficient values of 3 variables which indescending order of values, were; the problems ofprocurement process, the endogenous organizational
problem and exogenous influences, and the problems
in project management and technicality which had
path coefficient values at the values of 0.507, 0.395
and 0.334 respectively.
ACKNOWLEDFEMENT
The study is supported by Mahasarakham
University which are gratefully acknowledged.

REFERENCES
[1]

[2]

[3]

Dzuke A., & Naude M.J.A., Procurement
challenges in the Zimbabwean public sector: A
preliminary study, Journal of Transport andSupply Chain Management, Vol. 9 Issue 1, 2015,
pp.
1–9,
DOI:
https://doi.org/10.4102/jtscm.v9i1.166.
Hazra J., A procurement model in an electronic
market with coordination costs, International
Conference on Industrial Engineering andEngineering Management, Accession Number:
12490097,
2011,
DOI:
10.1109/IEEM.2011.6118139.
Kevitt M., & Davis, Supplier development andpublic procurement: Allies, coaches andbedfellows, International Journal of Public
Sector Management, Vol 27 Issue 7, 2013, pp.
550-563, DOI: 10.1108/IJPSM-03-2014-0041.
344

SEE - Kyoto, Japan, Nov.18-20, 2020

Readiness of Applying Big Data Technology for
Construction Management in Thai Government.
Hindrance of Applying Big Data Technology for
Construction Management in Thai Government,
The 4th International Conference on Civil andBuilding Materiais , January 17-20, 2020,
Okonawa, Japan.

345

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

MOLECULAR IDENTIFICATION OF A CARBONIC ANHYDRASEPRODUCING BACTERIUM ISOLATED FROM A NATTO IN
INDONESIA TO BE USED IN BIOCONCRETE DEVELOPMENT
Tomone Ikai1,a, Masahide Uomi1,2,a, Diana Waturangi3, Hiroshi Yonemitsu1, Masa-aki Yoshida4, Januarti J.
Ekaputri2, *Davin H. E. Setiamarga1
1

National Institute of Technology (KOSEN), Wakayama College, Gobo, Wakayama, Japan
2
Institut Teknologi Sepuluh Nopember (ITS), Sukolilo, Surabaya, East Java, Indonesia
3
Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
4
Oki Marine Biological Station, Shimane University, Oki, Shimane, Japana
Equal contributors* Corresponding Author / Senior Author

ABSTRACT
Recently, research about the inclusion of bacterial agents with biomineralizing capability in building materials
with extra features, such as concrete with added strength and self-healing capability, has been popular in the fieldof civil engineering. Previously, we reported the isolation of a CaCO 3 -producing bacterium from an Indonesian
natto, and have tested its usefulness as a biomineralizing agent in fly-ash and OPC pastes. Here, we report theinitial result of molecular and biochemical characterizations of the bacterium, in order to confidently identify its
species, and the presence of ß-carbonic anhydrase gene in its genome, which was confirmed by genomic
exploration by PCR and crude enzyme activity measurement. First, BLASTn analysis of the 16S-rRNA genesuggested that the organism belonged to the genus Bacillus, and that it was either B. safensis or B. pumilus(sequence identity = 99.86; E-value = 0). Subsequent phylogenetic analysis of the gene revealed that it was B.
safensis. Genomic exploration by PCR using specific primers also indicated the presence of ß-carbonic anhydrase
gene in its genome. Sequence analyses of ß-carbonic anhydrase also confirmed that our bacterium is B. safensis(sequence identity = 99.34; e-value = 2E-153). Our present results provided a set of additional evidence, that ourprevious report about increased strength and presence of aragonite crystals in OPC paste and fly-ash-based
geopolymer paste specimens with bacterial addition, were caused by the presence of B. safensis inside thespecimens. In the future, other molecular and biochemical characterizations of the bacteria are still needed.
However, we are confident that our results presented here is an important piece of information for future studies
on this bacterium, and on its utilization as a biomineralizing agent in alternative building materials.
Keywords: Bacillus, biomineralization, bio-concrete, ß-carbonic anhydrase, natto"Microbial-Induced Calcite Precipitation (MICP)[1][4].
In most of these studies, the biomineralizing
microbial agent used is ureolytic bacteria such as
Sporosarcina pasteuri [5]. Such bacteria produce the
enzyme urease, which catalyzes urea hydrolysis. The
reaction happens in two steps: First, the enzyme
urease hydrolyzes urea and produce carbonate ions.
The produce carbonate ions then bind with available
calcium ions in the surroundings, forming the calcium
carbonate [6]. The reaction can be shown as follows:
Step 1: CO(NH 2 ) 2 + 2H 2 O → 2NH 4 ++ CO 3 2−
Step 2: Ca2++CO 3 2−→ CaCO 3(1)
The calcium carbonate is then precipitated into themicropores of the concrete specimens. Meanwhile,calcium sources, such as calcium chloride, are often
added to the biomineralizing system.

INTRODUCTION
Recently, many studies on the utilization of
microorganisms with biomineralization capability inthe field of general constructions have been
conducted. These studies have different aims, forexample, (1) letting the microbes produce micropore
filler (usually calcium carbonate (CaCO 3 )) in
building materials such as cement-based or
geopolymer-based concretes, in order to strengthen
the materials [1]; (2) allowing the microbes to
produce calcium carbonate crystal deposits to fill incracks in concrete structures (the "self-healing"
concrete) [2]; (3) stabilizing soil particles by letting
the microbes to produce CaCO 3 precipitates to bindthe soil particles to one another and thus preventing
soil liquefaction [3]. The process of precipitating
CaCO 3 assisted by chemical reactions catalyzed byenzymes produced by microorganisms is called the346

SEE - Kyoto, Japan, Nov.18-20, 2020

A

B

Figure 1. Maximum Likelihood phylogenies of the A: 16S-rRNA, and B: carbonic anhydrase genes. Nodal bootstrap values
lower than 40% are not shown. The UOM_BS numbers refer to the same strain of Bacillus safensis, which we
named the IDN-1 strain.

and nitrites [7]. When used for geoengineering
purposes, adding a massive amount of urea andcalcium chloride might cause environmental
pollution. Besides that, the production of ammonia asa byproduct might cause health concerns sinceammonia is harmful to the human body if inhaled [8].
Another popular MICP method is by using
microorganisms with the ability to produce the
enzyme ß-Carbonic Anhydrase (CA) [1][9]. CA
catalyzes the interaction of CO 2 and HCO 3 -.

Urease-based MICP has been very popular in civilengineering, and its prospect has been studied
extensively [6]. However, urease-based MICP
requires external addition of urea to the object of
biomineralization to either the target concrete or thetarget soil. Urea and calcium chloride additions mightbring unwanted side effect to target systems. For
example, urea might compromise the durability of theconcrete and might cause corrosion of the reinforcing
metal, because it produces the strongly acidic nitrates
347

SEE - Kyoto, Japan, Nov.18-20, 2020

the genus Bacillus. However, no decisive species
identification of the bacterium was presented.
Here, we report our molecular genetics andbiochemical characterizations of the isolated
bacterium. From our 16S-rRNA molecularphylogenetics analysis, the bacteria were identified as
Bacillus safensis. Our genomic survey using specificprimers for the ß-carbonic anhydrase gene also
showed the presence of the gene, and sequence
analyses supported the 16S-rRNA phylogeny.
Enzymatic activity of the crude enzyme was also
assesed, by investigating the crude enzyme’s ability
to decrease pH. We also investigated the amount of
CO 2 produced by bacterial expiration, which is notpresent in most target systems such as cement paste
or geopolymer paste.

400b

①

②

③

④

Figure 2. The result of PCR genomic survey for carbonic
anhydrase gene in the bacterial isolate. (①UOM_BS_5,②UOM_BS_6, ③UOM_BS_9, ④UOM_BS_10).

Afterward, HCO 3 - produces the carbonate ions,which then bind with available calcium ions to
produce calcium carbonate.
Step 1: CO 2 + H 2 O → HCO 3 - + H+
(HCO 3 -→ CO 3 2- + H+)
Step 2: Ca2+ + CO 3 2− → CaCO 3(2)
Bacteria of the genus Bacillus are known to have thisenzyme, and also known for the ability to survive inharsh environments, including in highly alkaline
environments inside concretes [10]. Previously, we
collected a bacterial strain from a natto sold in amarket in Indonesia. Commonly, the bacterium used
for natto fermentation is of the genus Bacillus. In thatstudy,
we evaluated the biominerali-zing
performance of the bacterial strain in cement andgeopolymer pastes [11]. We found that calcium
carbonate (CaCO 3 ) was deposited in the microporesof specimens made from geopolymer paste andconcrete paste, if the bacteria was added into the
mixture. Specimens with bacterial addition showed
an increase in compressional strength. The presenceof CaCO 3 precipitate in the specimens with bacteria
was confirmed by XRD, while the presence of natto
bacteria was confirmed by SEM. In addition, thecrystal aggregates of CaCO 3 formed in the presenceof organisms, including CA enzyme-producing
bacteria, were aragonite and calcite [11][12].
Although we were able to show that our bacteria weremost likely the cause of the increased strength in both
the geopolymer and cement pastes, in that study, we
did not report any detailed characterization of thebacteria themselves. A quick BLASTn analysis of the
16S-rRNA gene of the bacteria indicated that it was of
9

MATERIAL AND METHODS(1) Bacterial Isolation
The bacterial strain used in this study was isolated
from a natto pack purchased from a market in
Surabaya, East Java, Indonesia. We named the strain
as "IDN-1" strain. Glycerol stocks from isolated
single colonies were prepared and stored at -80°C.
Subsequent analyses used the four colonies obtained
from these glycerol stocks of IDN-1, which we named
UOM_BS_5, UOM_BS_6, UOM_BS_9, UOM_BS_10(Fig. 2).

(2) Sequence Analyses
2-1 Sequence data acquisitions

Control

Crude enzyme

pH

8
7
6

0

100

200

300

400

Time [S]Figure 3. A diagram showing extracted total crude enzyme
activity to catalyze the reaction to lower the pH of Tris-HCl(pH: 8.5) in the presence of CO2. The control was the mixtureof Tris-HCl and CO2 but without the crude enzyme. The
reaction proceeded faster with the addition of crude enzyme
when compared to the control.

348

16S-rRNA gene amplification was conductedfollowing standard PCR protocol for bacteria, using
the bacterial universal primer 27F/1492R [13], withannealing temperature of 50°C. Sequencing using
both Forward and Reverse primers were outsourced
to FASMAC, Inc., Japan. Obtained sequences wereused as queries for BLASTn searches of the Genbank
nr database for species identification.
ß-carbonic anhydrase (ca) gene was amplified
using specific primers designed in this study. First,
the nucleotide sequences of the six strains of Bacillus
safensis and one strain of Bacillus subtilis were
downloaded from GenBank. The sequences werealigned using MAFFT (online ver.) [14] under the GINS-i algorithm to allow for an alignment over theentire sequence length. A set of specific primers forca (saf_F1, saf_R1; Table 1) were designed based onthese sequences. Sequences were visualized in
MEGA 7 [15]. PCR using these primers was
performed at the annealing temperature of 55°C. PCR
products sequencing was outsourced to FASMAC,
Inc, and obtained sequences were used in subsequent
analyses such as homology searches using BLASTn,

SEE - Kyoto, Japan, Nov.18-20, 2020and phylogenetic analysis.

enzyme.
Enzyme activity was assessed by measuring thedrop of pH of the substrate + enzyme solution (the"enzyme solution"). 0.2mL of crude enzyme wasadded to a solution of 9mL of 20mM Tris-HCl (pH8.5; on ice). Afterward, 6mL of CO 2 saturated water(ice cold) was added to the solution, and the time forthe pH to drop 8.5 to pH 6.4 was measured. The
control solution contains only the Tris-HCl and CO 2 saturated water.

2-2 Phylogenetic analyses
We obtained 16S-rRNA gene sequence data for
four colonies (designated as UOM_BS_5, UOM_BS_6, UOM_BS_9, UOM_BS_10). Sequences of six
strains of B. safensis and three strains of B. pumilus
were collected from Genbank. The 16S-rRNAsequences of B. licheniformis, B. indicus, B. anthracis,
and B. subtilis, also from Genbank, were used as
outgroups. Sequences were aligned using MAFFTver. 7 using the Q-INS-i algorithm to allow for theconsideration of secondary structures. Aligned
sequences were edited to remove ambiguouslyaligned regions using the online version of GBlocks
ver. 0.91b [16] under the least stringent setting.
MEGA X [17] and Mesquite ver. 3.61 [18] were used
to visualize the sequences. Model selections
performed using MEGA X under the AIC parametersuggested GTR+G as the best fit model. Maximum
Likelihood (ML) phylogenetic analyses with 1000
bootstrap replications were conducted in MEGA X.

(4) Characterizations Of The Isolated Bacterium
4-1 Growth curve
Bacterial cells were cultured in 5mL of LB liquidmedium was prepared in test tubes with and without
shaking at 37ºC. Turbidity was measured using aspectrophotometer (TAITEC, miniphoto518R) for 2
hours each up to 24 hours, then 4 hours each up to 32
hours, and finally 12 hours later, at 44 hours, for the
final measurement.
4-2 Measuring bacterial CO 2 emissions

Table 1. Specific primers for carbonic anhydrase
designed in this study
Primer Base sequence

We measured the amount of CO 2 produced
through respiration by living bacterial cells. In acompletely sealed desiccator, test tubes containing
5mL LB broth bacterial solution were incubated at
37ºC in an incubator. The amount of expirated CO 2
concentration in the desiccator was measured during
stationary incubation by using a gas detector tube
(GASTEC). The first measurement was taken forevery 2 hours for the first 6 hours. The fourth
measurement was taken 4 hours later, and the fifth at
the 17th hour. Afterward, from the 17th to 81st hours,
measurements were taken for every 8 hours.

Forwardsaf_F1 CGTGCATGGATACYCGTCTKKTGG
Reversesaf_R1 CACRCTCKCTTCMACTGAATCAAAGC
Phylogenetic analysis for the carbonic anhydrase
gene were also conducted on the sequences obtained
from the same four colonies used for the 16S-rRNA
analysis. Sequences of eight strains of B. safensis,
four strains of B. pumilus, two strains each of B.
subtilis and B. altitudini, and 1 strain each of B.
aerophilu,
B.
cellulasensis,
Mycobacterium
tuberculosis,
Neisseria
meningitides,
andStreptococcus pneumoniae were downloaded from
Genbank and used in the analysis. Sequences werealigned using MAFFT ver. 7 using the G-INS-i
algorithm. Model selection in Mega X under both the
BIC and AICc parameters suggested K2+G+I as thebest fitting model. Afterward, Maximum Likelihood(ML) phylogenetic analyses with 1000 bootstrap
replications were conducted in MEGA X.

RESULTS(1) Molecular Identification Of The Bacterial
Species Using The 16S-rRNA Gene
1420 bp-long sequences were obtained for the
16S-rRNA gene after assembling forward and reverse
sequences. BLASTn searches suggested that thisbacterium belongs to the genus Bacillus, either B.
safensis or B. pumilus (sequence identity = 99.86, Evalue = 0). The resulting phylogeny showed that ourbacterial samples are indeed B. safensis because they
formed a monophyletic clade with other B. safensis
sequences (bootstrap support = 87%) (Fig. 1A).

(3) Crude Enzyme Activity Assay
A total of 3µL of cultured bacteria in LB broth(shaken at 37°C for 24 hours) was centrifuged(10,000 rpm, RT, 10 min). After washing, the pellet
was suspended in distilled water to achieve a celldensity of of OD 600 1. Bacteria cells were lysed byultrasonication (TOMY, UD-201). Afterward, thesuspension was centrifuged (12,000 rpm, RT, 5 min),and the supernatant was collected as the crude(2) ß-carbonic anhydrase Sequence Analyses
We confirmed the presence of ß-carbonic
anhydrase (ca) in the genome of our B. safensis by
PCR survey (Fig. 2). 307 bp-long sequences were349

SEE - Kyoto, Japan, Nov.18-20, 2020

1500

1
0.8

CO2 emissions [ppm]

Number of bacteria ×106
[cells]

1.2

Shaking culture
Stationary culture

0.6
0.4
0.2
0

0

20

40

1000
B. safensis

500
0

0

10 20 30 40 50 60 70 80 90

Time [h]Time [h]Figure 4. Bacterial growth curves of our isolate,cultured with shaking culture and stationary. The
growth of stationary culture was slower when compared
to shaking culture.

Figure 5. CO2 expiration by Bacillus safensis. The amountof expirated CO2 increased in proportion to the incubation
time of the stationary culture (shown in Fig. 4).

obtained after assembling forward and reverse
sequences. BLASTn searches confirmed that thesequences were homologs of ca of B. safensis(sequence identity = 99.34; e-value = 2E-153). In theca phylogeny, our sequences formed a monophyleticclade with other B. safensis sequences (bootstrap
support = 99%), and thus further confirmed theidentity of our isolate (Fig. 2B).

ppm at 0 hours. The values did not change much until
about 20 hours, but after 20 hours, they began toincrease, and the CO 2 concentration was 1160 ppm at
73 hours. This result suggests that the CO2 emissionof B. safensis during stationary culture (Fig. 4) was
about 300 ppm in 73 hours (Fig. 5).

(3) Crude Enzyme Activity(1) Our Bacillus safensis Isolate Has An Active ßCarbonic Anhydrase Enzyme

DISCUSSION

The initial pH of both the enzyme solution (20mM
Tris-HCl + CO 2 -saturated water + crude enzyme
extract)) and those of the control solution (only
20mM Tris-HCl + CO 2 -saturated water) were 8.58.
Up to about 100 seconds, the pH of both the enzyme
and control solutions slowly decreased to ca. 7.91.
However after that, pH of the enzyme solution
decreased at a significantly faster rate than that of thecontrol (from 7.91 at 100th second to 6.68 at 200th
second, a decrease of pH value of 1.23 in the span of
100 seconds). The control solution's pH decreased byonly 0.79, from 8.03 to 7.24 over the same time period.
The result (Fig. 3) indicated that the Carbonic
Anhydrase (CA) enzyme from our B. safensis isolate
is active.

Genomic exploration by PCR using primers
specific for ß-carbonic anhydrase revealed thepresence of the gene in the genome of B. safensis (Fig.
2). Meanwhile, the activity of the enzyme wasconfirmed by crude enzyme analysis (Fig. 3).
This results provide additional evidences that ourprevious reports about the higher strength of the fly
ash-based geopolymer paste with bacterial addition(when compared to those without), and the presenceof aragonite crystals in the specimens could probably
be attributed to B. safensis presence in the specimens.
Without doubt, however, further studies, which
include molecular, microbiological, and biochemicalassessments of fly-ash geopolymer paste and concrete
specimens, to confirm the actual presence of thebacteria in them, are still needed to confirm thisobservation.

(4) Growth Curve
The bacteria were cultured with shaking andwithout (stationary culture). Bacterial growth of theshaking culture was found to be in the exponential
growth phase until the 10th hour, and then entered thestationary phase at around the 15th hour (Fig. 4).
Meanwhile with the stationary culture, the bacterial
growth was slower when compared to the shaking
culture. This is indicated by the tendency of thenumber of bacteria to increase in proportion to time,and still increasing even after 44 hours of cultivation.

(2) Phylogenetic Analyses of two genes increased
the Confidence of the Bacterial Identification
BLASTn searches of the 16S-rRNA gene alone
could not determine whether our isolate was B.
pumilus or B. safensis, despite the relatively longsequence length. However, phylogenetic analysis of
the sequences helped to identify that our isolate is B.
safensis. However, previous studies have indicatedthat the two species are actually not decisively
identifiable only by 16S-rRNA sequence analyses[19]. Those studies suggested that the housekeeping
gene gyrB is useful for this purpose. In this study,(5) CO 2 Expiration
The CO 2 concentration in the gas phase was 810
350

SEE - Kyoto, Japan, Nov.18-20, 2020

however, we also conducted BLASTn searches andphylogenetic analysis of the gene ß-carbonic
anhydrase (ca), which results also confirmed that ourisolate is B. safensis. Therefore, our study here
showed that this gene is probably also useful, fordifferentiating the two closely related species of B.
safensis and B. pumilus. While we are very confident
that our molecular identification result reported here
is correct, in the future, we intend to do further
confirmation, by conducting sequence analyses ofgyrB.

REFERENCES[1] Alshalif A.F., Irwan J.M., Othman N, Al-Gheethi
A, Hassan A., Nasser I.M. Potential of carbonic
anhydrase and urease bacteria for sequestrationof CO 2 into aerated concrete. MATEC Web ofConferences Vol. 138, 01019, 2017.
[2] Wiktor V., Jonkers H.M. Quantification of crackhealing in novel bacteria-based self-healing
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microorganisms to geotechnical engineering forbioclogging and biocementation of soil in situ.
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[4] Chaparro-Acuña S.P., Becerra-Jiménez M.L.,
Martínez-Zambrano J.J., Rojas-Sarmiento H.A.
Soil bacteria that precipitate calcium carbonate:mechanism and applications of the process. Acta
Agronomica. Vol. 67, No. 2, pp. 277-288, 2018
[5] Whiffin V.S. Microbial CaCO3 precipitation forthe production of biocement. PhD thesis of
Murdoch University, 2004.
[6] Bang S.S., Galinat J.K., Ramakrishnan V.
Calcite Precipitation Induced by PolyurethaneImmobilized Bacillus Pasteurii, Enzyme andMicrobial Technology. Volume 28, Issues 4–5,
pp. 404-409, 2001.
[7] Sadegzadeh M., Page C.L., Vassiet P.R.W.
Effects of urea on durability of reinforced
concrete, Magazine of Concrete Research. Vol.
45, No. 164, pp. 179-186, 1998.
[8] Li M., Fu Q.L., Zhang Q., Achal V.,
Kawasaki S., Bio-grout based on microbiallyinduced sand solidification by means ofasparaginase activity, Scientific Reports Vol. 5,16128, 2015.
[9] Sundaram S. Thakur I.S. Induction of calcite
precipitation through heightened production of
extracellular carbonic anhydrase by CO2
sequestering bacteria. Bioresource Technology,
Vol. 253, pp. 368-371, 2018.
[10] Zhang Z., Lian B., Hou W., Chen M., Li X., Li
Y. Bacillus mucilaginosus can capture
atmospheric CO2 by carbonic anhydrase. African
Journal of Microbiology Research Vol. 5 pp.
106-112, 2011.
[11] Setiamarga D.H.E., Uomi M., Waturangi D.,
Suhartono M.T., Shovitri M., Kusube M.,
Yonemitsu H., Hirano H., Ekaputri J.J.
Exploration Of The Potentials Of Carbonic
Anhydrase producing Bacteria Utilization In
Geopolymer-Based Bioconcrete Development,
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Materials and Environment, 1231–1236, 2019.
[12] Alshalif A.F., Irwan J.M., Othman N., Zamer
M.M., Anneza L.H. Carbon Dioxide (CO2)(3) Our Present Results Corroborate Our
Previous Bio-Geopolymer Paste Study
We succeeded in confirming the presence andactivity of the enzyme ß-Carbonic Anhydrase (CA)in the isolate. We also revealed that the isolate
respirations caused CO 2 concentration to increase
proportionaly with the growth in stationary culture ofbacterial. Since the actual reaction in the concretetakes place under conditions such as stationary
incubation rather than shaking culture, it is likely that
CO2 will also follow the increase in this result. These
results allowed us to hypothesize an explanation forour previous study using fly-ash-based geopolymer
paste [11][20].
Fly-ash usually does not contain any calcium.
However, fly-ash obtained from power plants inIndonesia has high calcium contents because ofincomplete combustions caused by low temperatureburning [21]. Our previous study used fly-ash from an
Indonesian power plant to make the geopolymer paste.
When B. safensis grew inside the paste, it also
expirate CO 2 , which was dissolved in the surrounding
moisture content. It was then catalyzed by CA andbecame CO 3 2– ions, which then bound to the calcium
ions that are abundant in the fly-ash, and formed
calcium carbonate, which then fill the pores of thepaste specimens.
Although many further studies to validate ourhypothesis above are still needed, we are confident
that the progress report published here contains
valuable information on both the understanding of
Bacillus safensis, and the development of alternative
geopolymer-based building materials.

ACKNOWLEDGEMENTS
DHES work was partially supported by the
National Institute of Technology, Wakayama College
Competitive Internal Research Grant for Education
and Research 2016, 2018, and The Asahi GlassFoundation Research Grant 2016. DHES, TI, and MU
thanked Masataka Kusube (National Institute ofTechnology, Wakayama College) for invaluable
discussions.

351

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Sequestration In Bio-Concrete, An Overview.
MATEC Web of Conferences, Vol. 103, 05016,
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from Multiple Alignments for Their Use in
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K. MEGA X: Molecular Evolutionary Genetics

Analysis across Computing Platforms. Molecular
Biology and Evolution. Volume 35, Issue 6, pp.
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[18] Maddison W.P., Maddison D.R. Mesquite: amodular system for evolutionary analysis,
Version 3.61, 2019.
(http://www.mesquiteproject .org)[19] Satomi M., Duc M.T.L., Venkateswaran K.
Bacillus safensis sp. nov., isolated fromspacecraft and assembly-facility surfaces,
International Journal of Systematic andEvolutionary Microbiology, 56, 1735–1740,
2006.
[20] Wulandari K.D., Ekaputri J.J., Triwulan,
Fujiyama C., Setiamarga D.H.E. Effects of
microbial agents to the properties of fly ashbased paste. MATEC Web of Conferences 195,
01012, 2018.
[21] Ekaputri J.J., Ulum M.B., Ridho B., SusantoT.E., Abdullah M.M.A.B. A Comprehensive
Characterization and Determination of Fly Ashes
In Indonesia using Different Methods. Vol. 754755, pp. 320-325, 2015.

352

6th Int. Conf. on Structure, Engineering & Environment (SEE),
Kyoto, Japan, Nov.18-20, 2020, ISBN: 978-4-909106056 C3051

INFLUENCE OF RICE HUSK ASH WASTE ON COMPACTABILITY
OF SOIL
Sayful Kabir Khan1, 2, Najmun Nahar1, 3, Zakaria Hossain1 3, Noma Tamaki4
Graduate School of Bioresources, Mie University, Japan, 2Directorate General of Food, Ministry of Food,
Bangladesh, 3Life and Earth Science, Jagannath University, Bangladesh,
4
Make Integrated Technology Company, Osaka, Japan

1

ABSTRACT
Usually, measurement of optimum moisture content and maximum dry density is essential for assessing thequality control of the compacted fill or earthwork constructions as the parameters of compaction characteristics.
Rice husk ash, which is plentifully available in many rice-producing countries, can be used as a construction
material. The present study mainly tries to investigate the effect of rice husk ash on compaction characteristics ofsandy soil classified as A-2-4 or SW-SM for soil stabilization. Six different percentages of rice husk ash amountwith soil considered for the standard Proctor compaction test. The result revealed that with increasing the amountof rice husk ash, the optimum moisture content increased but decreased the maximum dry density of soil. It canconclude that the utilization of soil-rice husk ash combination is beneficial for ground improvement.

Keywords: Soil texture; Optimum moisture content; Maximum dry density; Soil stabilizationsome advantages, like improving strength, enhancing
durability, or decreasing carbon dioxide emissions,etc. [14].
RHA is not a new material for soil improvement.
The application of RHA in soil has shown dramatic
success in many types of soils around the world. Soilcompaction is an essential part of the construction ofbuilding foundations, roadways, walkways, and earth
retaining structures, highway embankments, earth
dams, foundations, and many other engineering
structures [15]. Soil compactibility illustrates themechanical behavior of soil, which is influenced by
the soil texture, water content, inherent bulk density,
structural stability, organic matter, soluble salts, andcompactiveenergy[16].
Regardingthecompactability, mixing of rice husk ash (RHA) withsoil increases the optimum moisture content (OMC)
and decreases the maximum dry density (MDD) [6,
17-20]. There are many pieces of research oncompaction characteristics of soil [21- 25]. Still, very
few studies have been conducted on compaction on
the ground with RHA [17, 25-28], where a small
amount of RHA was used. Therefore, the present
study attempts to present the effects of lower to ahigher amount of RHA on the compaction
characteristic of soil.

INTRODUCTION
Rice is one of the most consumed food items
throughout the world, and the annual global paddy
production estimates for the year 2010 are 678
million tons, which implies 149.16 million tons ofrice husk production that year [1]. Rice husk is anagricultural by-product of rice and produced frompaddy during the milling process [2], which isplentifully available in many rice-producing
countries [3]. Rice Husk Ash (RHA) forms when ricehusk burns under controlled temperature [4]. Every
year more than 20 million tons of RHA are produced
over the globe [5-6]. Due to lack of its utilization, thelarge amount of RHA is discarded at open places,
riversides, and abandoned areas, which causes
environmental pollution [7] and also poses a healthhazard due to local air pollution. However, RHA is apozzolanic material, and it contains around 85–90%
amorphous silica, which is reactive as a pozzolan toreplace part of Portland cement [8-9] that canpotentially use as a construction material for thevarious geotechnical application. On the other side,
the production of cement, a key binding componentof concrete, is costly, consumes high energy, depletes
natural resources, and emits vast amounts ofgreenhouse gases [10] that also causes environmental
degradation, severe pollution [11-13], and even
health hazards. So, if most of the RHA use in ground
improvement, it would not only get rid of dumping
RHA but would also have decreased the CO2
emissions to the atmosphere by bringing down the
cement production. As a pozzolanic material, usageof rice husk ash in cement/concrete that brings about

MATERIALS AND LABORATORY TEST
Materials Used
In this study, testing specimen made of soil and
RHA. The soil sample has collected from the Handa
area, Tsu City, Mie Prefecture, Japan. The physical353

SEE - Kyoto, Japan, Nov.18-20, 2020

properties of soil were determined through a series oflaboratory tests and presented in Table 1. From thegraph of particle size distribution by sieve andhydrometer analysis of soil, the coefficient ofgradation (𝑪𝒖 ) and the coefficient of curvature (𝑪𝒄 )values are correspondingly 9.275 and 0.906, and fromthe Atterberg limit test, the plasticity index (PI) is
8.55%. According to the Unified Classification of
Sandy soils by ASTM D-2487, the particular soil iswell-graded sand with silt, and the symbol is SW-SM
as the coefficient of gradation (𝐂𝐮 ) of soil particles
are greater than or equal to 6, and the coefficient ofcurvature (Cc) value is between 1 and 3 (𝐂𝐮 ≥ 𝟔
and 𝟏 ≤ 𝐂𝐜 ≤ 𝟑 ) besides with plasticity index isgreater than 7 (PI >7). According to the American
Association of State Highway and Transportation
Officials (AASHTO) soil classification system, theparticular soil is Silty gravel and sand (A-2-4), wherepercent passing no. 200 sieve ≤ 35%, LL ≤ 40 and PI≤ 10 (Fig.1 and Table 1).

Readymade RHA collected from Make Integrated
Technology (MIT) Company, Osaka, Japan. Table 2
represents the basic properties of RHA, and Fig.1 also
shows the particle size distribution of RHA with soil
particle size. Available ordinary tap water in thelaboratory was used in all of the specimens.
Table 2 Physical and chemical properties of RHA
Properties

Parameters

ValuesPhysicalproperties

Average Particle Size

0.1 to 0.3 μm

Loss of Ignition

85%

Specific Gravity

0.12 g/cm3

Burning Temperature

600°C

Burning Time

24 hours

Silica (SiO

91.10%

Chemicalproperties

2)

Carbon dioxide (CO )

4.35%

2

Potassium Oxide (K O)

2.40%

2

Table 1 Physical properties of soilParameters

Calcium Oxide (CaO)
Phosphorous Penta Oxide (P O

Values2

3

Specific gravity (ρs))

dry max

Optimum Water Content (W

opt.

)

Sand (75 μm - 2 mm)
Silt (5 - 75 μm)
Clay < 5 μm
Liquid limit, LL
Plastic limit, PL
Plasticity Index, PI
AASHTO classification
ASTM D-2487 classification

3

1.696 g/cm
17.50%

Percent Finer (%)

Chlorine (Cl)

0.18%

Magnesium Oxide (MgO)

0.16%

Manganese Oxide (MnO)

0.14%

Iron Oxide (Fe O )

0.05%

2

3

Alumina (Al O
2

0.03%

3)

Others0.12%

Mix Designs of Specimen
In this study, the mixing design of the specimen,from nominal to a maximal percentage of RHA
amount of soil weight considered to understand theeffects of RHA on the samples. Initially, Soil addition
with RHA of 0.5%, 1.0%, 1.5% used, and later thepercentage of RHA amount was mixed ten times
higher than that of the previous amount, and theamount was 5%, 10%, and 15% RHA which
presented with index in Table 3.

RHA particle size

100
80
60

Table 3 Investigated mixtures with indices40

Mix design

20
0
0.001

0.38%

3

89%
9%
2%
37.52%
28.97%
8.55%
A-2-4
SW-SM

Soil particle size

0.52%

5)

Sulphur Tri Oxide (SO )2.74 g/cm

Maximum dry density (γ

0.57%

0.01

0.1

1

Soil (Control)
Soil + 0.5% RHA
Soil + 1.0% RHA
Soil + 1.5% RHA
Soil + 5% RHA
Soil + 10% RHA
Soil + 15% RHA

10Particle diameter (mm)Fig. 1 Particle size distribution curve of soil and RHA
354

Index
Control
S+0.5R
S+1.0R
S+1.5R
S+5R
S+10R
S+15R

SEE - Kyoto, Japan, Nov.18-20, 2020of a sample was divided into nine parts from where
the central part was taken as a sample for the ovendry weight (Fig. 4). Similar way, water was added
repeatedly to get the optimum water content andmaximum dry density.

Laboratory Test
Compaction test
According to Japanese Industrial Standards (JISA-1210), the Standard Proctor compaction test was
conducted to determine the optimum moisture
content (OMC) and maximum dry density (MDD) of
soil control and other mix types. The applied
apparatus for performing the test was a 10 cm
diameter cylindrical compaction mold equipped witha base and a collar, rammer mass of 2.5 kg, and afalling height of 30 cm (Fig. 2).

Fig. 4 Sample collection from the central part of alayer in a specimen for oven-dry weight after
compaction
RESULT AND DISCUSSIONS
Compaction Characteristics
Fig.2 Standard Proctor compaction apparatusA) Base with mold; B) Collar; and C) Rammer

The variations of MDD and OMC with RHA
addition with soil are presented in Figs. 5 and 6. The
figures illustrate that with increasing the amount of
RHA, OMC increases, but MDD decreases
significantly.

In the compaction mold, the RHA mixed soil
compacted in three layers with 25 blows for eachlayer. For each mix type, Soil-RHA was manually
mixed homogenously in dry condition. Subsequently,
different
moisturecontents
were
added
homogeneously by manual mixing like the previous
step for getting the expected moisture content (Fig. 3).

Control

S+0.5R

S+1.0R

S+1.5R

16

20

24

Dry Density, ρd

1.72
1.68
1.64
1.6
1.56
1.52
8

12

28

Water Content, %Fig. 5 Compaction curves of control and soil-RHA
combination types
Fig. 3 Water mixing manually with air-dried soil forreaching expected water content

The OMC of control was 17.5%, and MDD was
1.696 g/cm3. Soil with RHA of 0.5%. 1% and 1.5%
mixing displayed the little increasing tendency(0.4%) of OMC and slightly decreasing tendency(0.016 g/cm3) of MDD. Furthermore, soil addition
with RHA of 5%, 10%, and 15% exhibited acomparatively more increasing tendency of OMC and

For measuring the water content, samples werecollected from the top, middle, and bottom layers byequally separating the three layers after extruding thecompacted specimen from the mold. Then each layer
355

SEE - Kyoto, Japan, Nov.18-20, 2020

decreasing trend of MDD than that of 0.5%. 1% and1.5% RHA mixed soil (Table 4 and Fig. 7), whichindicates a higher percentage of RHA amount withsoil gives a higher OMC and a lower MDD value ofa specimen. Because after mixing the RHA with soil,
the quantity of fines increases in the soil that needs
more water for hydration [26]. This trend was also
found in some researches [6, 17-19, 27]. The
declining tendency of dry density of soil specifies thatthe low compaction energy requires achieving the
MDD of a particular specimen that reduces thecompaction cost [29-30].
Control

S+5R

S+10R

CONCLUSIONS
The following conclusions can be drawn based on the
results obtained from the compaction test on soilRHA in the paper:



S+15R

Dry Density, ρd

1.7



1.6
1.5
1.4
1.3
1.2

REFERENCES

1.1
8

13

18

23

28

33

38

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Water Content, %Fig. 6 Compaction curves of control and soil-RHA
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OMC (%)MDD, ρdControl
S+0.5R
S+1.0R
S+1.5R
S+5R
S+10R
S+15R

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Water Content, %

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and S+1.5R specimen types.
Utilization of RHA waste with soil can apply
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improvement purposes where a massive
amount of earth materials need. The
successful application of the waste material
can reduce construction costs significantly,
which will also be environment-friendly.

Fig. 7 Variation of OMC and MDD of control andsoil-RHA combination types
356

SEE - Kyoto, Japan, Nov.18-20, 2020

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