SEE 2022, MIE, JAPANSTRUCTURE, ENGINEERING AND ENVIRONMENTiPROCEEDINGS OF EIGHTH INTERNATIONAL CONFERENCE – SEE 2022
STRUCTURE, ENGINEERING & ENVIRONMENT MIE, JAPAN 10-12 NOVEMBER, 2022

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

Copyright @ 2022 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: 978-4-909106094 C3051

iii

Eighth International Conference on Structure, Engineering & Environment,
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

Table of Contents
Prefacex

Organizationxi

Keynote Papers

1

k1

EFFECTIVENESS OF BRYOPHYTES AND CICADA SHELLS AS A BIO-INDEX FOR HEAVY METALCONTAMINATION OF RIVER WATER AND SOIL
Prof. Dr. Hiroyuki Ii2

k2

CURRENT CHALLENGES IN GEOLOGICAL STORAGE OF CARBON DIOXIDEProf. Dr. John Smith11k3

DEVELOPMENT OF A NEW VIBRATION ACTUATOR FOR INSPECTION OF LARGE IRONSTRUCTURES
Prof. Dr. Hiroyuki Yaguchi

17

Technical Papers

25

ID

ID

Structures

26

s8512

TORSIONAL BEHAVIOR OF SPANDREL REINFORCED CONCRETE BEAMS
Noor Ayaad and Nazar Oukaili

27

s8529

EXPERIMENTAL STUDY ON SEISMIC SHEAR DEFORMATION OF BOX TUNNEL FOCUSING ON
STIFFNESS RATIO AND FRICTION BEHAVIOR
Takafumi Shimada, Hidetoshi Nishioka and Takahiro Furukawa

35

s8545

GLOBAL DAMAGED INDEX ASSESMENT OF DYNAMIC LOADS BASED UPON ARTIFICIAL NEURALNETWORKS
Widya Apriani, Reni Suryanita and Hendri Rahmat

39

s8557

STRUCTURAL DESIGN OF SEISMIC ISOLATION FOR TEMPLE AND SHRINE
Yasuhide Mochida and Kengo Wada

45

s8561

STRESS ANALYSIS OF VALLEY FILLS CONSIDERING RAINFALL INFILTRATION CONDITIONS
Daiki Yamashita and Shin-ichi Kanazawa

51

s8572

ANALYTICAL STUDY OF THE STRENGTH CHARACTERISTICS OF COMPACTED SOIL
Kazuki Naito and Shin-ichi Kanazawa

59

s8575

CORROSION BEHAVIOR ANALYSIS OF SELF-COMPACTING CONCRETE USING IMPRESSEDCURRENT AND RAPID CHLORIDE PENETRATION TEST
Stephen John C. Clemente and Jason Maximino C. Ongpeng

67

s8585

DAMAGE AND SUBMERGED PROBABILITY EVALUATION OF FLOATING OFFSHORE WINDTURBINES UNDER WIND AND WAVE ACTIONS
Ken-ichi Fujita and Harumi Yashiro

73

s8601

RESILIENCE ASSESSMENT OF A FIVE-STOREY SOCIALIZED HOUSING USING THE REDI RATINGSYSTEMJohn Pol A. Aguilar, Wilfed A. Chan, Ted Marius U. Delos Reyes, Richard M. De Jesus andRodolfo79

iv

s8624

THE EFFECT OF TSUNAMI LOAD ON PRAYOGA FOREIGN LANGUAGE COLLEGE IN PADANG
CITY, INDONESIA
Fauzan, Ferdy Muhammad Ikhwan, Dyan Adhitya Nugraha M and Zev Al Jauhari

85

s8625

STRUCTURAL EVALUATION OF THE MELATI HOSPITAL BUILDING AT SUNGAI PENUH CITY
Fauzan, Lukman Nulhakim, Dyan Adhitya Nugraha M and Zev Al Jauhari

91

s8636

ANALYSIS OF REINFORCED CONCRETE STRUCTURES EMPLOYING KOHONEN SELF ORGANISING
MAP
Omar Al Juboori and Rabee Rustum

97

s8655

EXISTING BRIDGE CAPACITY EVALUATION FOR TRANSPORTATION HAVEY TRAILER
Douangmixay DOUNSUVANH and Chanpheng PHOMMAVONE

102

s8658

AN INTRODUCTION TO LINI APPLICATION FOR EARTHQUAKE RESISTANT DESIGN OF BRIDGESIN INDONESIA
Desyanti and Fahmi Aldiamar

107

s8672

EXPERIMENTAL MEASUREMENT OF THE LOAD-BEARING CAPACITY OF WIRE HOOKS AND
BENDS USED IN GABION RETAINING WALLS
Radim Cajka, Kamil Burkovic, Zdenka Neuwirthova, Petr Mynarcik and David Bujdos

112

ID

Engineering

116

s8508

A NEW TYPE OF ELECTROMAGNETIC-VIBRATION PUMP WITH HIGH EFFICIENCY AND FLOW
RATE
Hiroyuki Yaguchi, Takuya Watanabe and Toshiki Mishina

117

s8510

GEOPHYSICAL INVESTIGATION OF GROUNDWATER RESOURCES USING ELECTRICALRESISTIVITY AND INDUCED POLARIZATION METHOD
Jannatul Hasni Omar, Nordila Ahmad, Jestin Jelani, Zuliziana Suif and Maidiana Othman

123

s8518

MACHINE LEARNING MODELS TO DETERMINE THE COEFFICIENT ANGLE OF FRICTION OF
MAKATI CITY, PHILIPPINES SOIL LAYERS
Joenel Galupino and Jonathan Dungca

129

s8532

A STUDY ON VIBRATION AND SOUND SIGNALS OF AN ELECTRIC VEHICLE
Suphattharachai Chomphan

138

s8536

CONSTANT VOLUME SHEAR TESTS ON COMPACTED SILTY SOIL UNDER CONSTANT WATERCONTENT CONDITION
Tufail Ahmad, Riko Kato and Jiro Kuwano

144

s8538

NUMERICAL SIMULATION OF ENERGY EXTRACTION FROM A RESONATING RESERVOIR
Bang-fuh Chen, Hsing-nan Wu and Po-hung Yeh

150

s8548

DURABILITY PERFORMANCE OF CONCRETE INCORPORATING DIMENSION LIMESTONE WASTE
AS FINE AGGREGATES REPLACEMENT
Jasmin M. Panganiban and Mary Ann Q. Adajar

156

s8549

RECYCLING OF FISHERY WASTE AS PLANTING BASE POROUS CONCRETE AIMED AT ACHIEVINGCARBON NEUTRALITY
Ayane Yanaka, Hidenori Yoshida, Shinichiro Okazaki, Yui Oyake and Yoshihiro Suenaga

162

s8552

EXAMINATION OF SEDIMENT GRAIN-SIZE MEASUREMENT AND CALUCULATION AT MULTIPLE
POINTS ON THE SANDBAR IN CLASS B RIVER
Yoshitaka Jiken, Kazuya Watanabe and Noritoshi Saito

168

s8554

RESIDUAL STRUCTURAL CAPACITY EVALUATION OF BRIDGE PIERS AFFECTED BY THE LOCALSCOURING WITH A WATER LEVEL FORCASTING MODEL USING MACHINE LEARNING
Ryosuke Takahashi, Takuma Kadono and Shinichiro Okazaki

174

s8564

TIME, STRESS AND STRAIN DEPENDENCY OF PILE STIFFNESS: IMPACT ON PILE BEHAVIOR AND
STATIC PILE LOADING TESTS RESULTS
Fabien Szymkiewicz, Wassim Mohamad, Nader Elayni and Carlos Minatchy

180v

s8582A STUDY ON THE PROPERTIES OF CONCRETE WITH FLY ASH AND GARBAGE MOLTEN SLAGFINE AGGREGATE
Zihao Liu, Koji Takasu, Hidehiro Koyamada and Hiroki Suyama

186

s8596

LABORATORY STUDY OF PHYSICAL AND THERMAL PROPERTIES OF CONCRETE MIXED WITH
BAKELITE
Sitthiphat Eua-apiwatch and Worasit Kanjanakijkasem

191

s8606

s8610

ELECTROCHEMICAL EVALUATION OF CORROSION PROTECTION OF REINFORCING STEEL BARSUSING SUGARS
Yoko Sakakihara, Kiyofumi Yamagiwa, Kyosuke Isoda and Shinichiro Okazaki
PHYSICAL AND MORPHOLOGICAL PROPERTIES OF POLYURETHANE MODIFIED BITUMEN
UNDER AGEING CONDITIONS
Faridah Hanim Khairuddin, Siti Zubaidah Mohd Asri, Noor Aina Misnon, Nur Izzi Md Yusoff
and Ahmad Nazrul Hakimi Ibrahim

197

203

s8611

PUSHOVER ANALYSIS OF RC FRAMES WITH SUBSTANDARD BEAM-COLUMN JOINTS
Zaidir and Syafri Wardi

209

s8616

LIFE CYCLE ASSESSMENT IN THE PRODUCTION PROCESS OF CRUDE PALM OIL (CPO) ON PALMOIL PLANTATION AND MILLS
Deffi Ayu Puspito Sari, Malikhatun Nikmah and Nugroho Adi Sasongko

215

s8639

SEDIMENT EXPERIMENTAL STUDY ON BARK STRIPPING PROCESS USING DRIFTWOOD MODEL
Kazuya WATANABE, Noritoshi SAITO and Yoshitaka JIKEN

220

s8641

s8644

s8650

BUDGET PRIORITIZATION OF RURAL ROAD MAINTENANCE USING THE INTEGRATED AHP –TOPSIS METHOD TO DECISION SUPPORT SYSTEM
Pawarotorn Chaipetch, Chisanu Amprayn, Paijit Pawan and Vatanavongs Ratanavaraha
FIXATION OF SOYBEAN EXTRACT METHOD FOR BIOCATALYST IN CALCITE PRECIPITATIONMETHOD AND ITS APPLICABILITY AS A SOIL IMPROVEMENT TECHNIQUE
Heriansyah Putra, Baiq Heny Sulistiawati, Hideaki Yasuhara, Minson Simatupang and Dede
Heri Yuli Yanto
PERFORMANCE COMPARISON OF GEOMETRIC SHAPE OF DESILTING BASIN RECTANGULAR
AND VORTEX DESILTING BASIN
Muhammad Isnaeni, Muhammad Syahril Badri Kusuma, Joko Nugroho, Mohammad Farid and
Muhammad Cahyono

226

232

238

s8653

CASE STUDY AND EVALUATION OF ROAD LANDSLIDE OVER TUFF MATERIAL
Fahmi Aldiamar and Dea Pertiwi

247

s8654

FIELD PERFORMANCE EVALUATION OF ENVIROMENTALLY FRIENDLY PREFABRICATEDVERTICAL DRAIN (PVD)
Dea Pertiwi

253

s8656

AN APPROACH STUDY OF REDUCING THE SUB-BALLAST THICKNESS OF RAILWAY USINGGEOTEXTILES
Saad F.I. AL-Abdullah, Zaman T. Teama, Maysaloon A. Zaidan and Suha Aldahwi

258

s8657

EVACUATION RISK ASSESSMENT OF FLOODED SLOPING ROAD IN THE CITY OF KAMAISHI
Yuriko Matsubayashi and Mako Ebina

264

s8661

EXPERIMENTAL STUDY ON ECO-BINARY MORTAR AT HIGH -TEMPERATURE EXPOSURE
R.A Malek and S. Gooven

270

s8676

FAULT DETECTION USING PALSAR-1/2 IMAGE DATA FOR GROUNDWATER ANALYSIS (STUDY
AREA: CENTRAL AND SOUTHWEST OF DJIBOUTI)
Yessy Arvelyna, Sawahiko Shimada, Sergio Azael May Cuevas and Fadoumo Ali Malow

276

s8678

THE EFFECTS OF RICE HUSK ASH DOSAGE ON COMPRESSIBILITY AND MICROSTRUCTURAL
DEVELOPMENT OF STABILIZED CALCITE-RICH RIVER SLUDGEAlex Otieno Owino and Zakaria Hossain

282

vi

s8680ANAYSIS OF UNREINFORCED CONCRETE BEAMSON SOIL BY FINITE ELEMENTS
Radhi Alzubaidi, Husain M Husain and Samir Shukur

291

s8622

EXPERIMENTAL STUDY ON RETROFITTING OF HOLLOW BRICK MASONRY HOUSES USING A
FERROCEMENT LAYER
Fauzan, Jonathan Vincensius Osman, Geby Aryo Agista, Naurah Daffa Carol and Yundha Syah
Putra

300

Environment

306

s8504

LABORATORY INVESTIGATION ON WATER QUALITY OF SPRING WATER FOR SMALLCOMMUNITY FOR WATER SECURITY
Mohamad Nazrul Hafiz, Maidiana Othman, Noor Afiza Mat Razali, Zuliziana Suif, Jestin Jelani
and Nordila Ahmad

307

s8515

POTENTIAL FOR DESCENDING METEORIC WATER RECHARGE IN HYDROTHERMAL SYSTEMS AS
A PATHWAY FOR CARBON DIOXIDE SEQUESTRATIONJohn Victor Smith

313

s8526

Cu, Zn, Fe AND Mn CONCENTRATIONS OF SOME GASTROPODS IN THE WAKAGAWA ESTUARYTIDAL FLAT
Kazuko Kubo and Hiroyuki Ii

320

s8522

EFFECTIVENESS OF COMPACTED POLYURETHANE-CLAY AS A SANITARY LANDFILL LINER
Cielo Frianeza and Mary Ann Adajar

326

s8524

FEASIBILITY OF OYSTER SHELL PERVIOUS CONCRETE WITH DIFFERENT PARTICLE SIZE AS A
SEAWEED BED
Shuta Hiura, Itaru Horiguchi and Yoichi Mimura

332

s8530

PHYSICAL PROPERTY AND HEAVY METAL LEACHING BEHAVIOR OF CONCRETE MIXED WITHWOODY ASH
Takuto Ueno, Ayane Yanaka, Shinichiro Okazaki, Naomichi Matsumoto and Hidenori Yoshida

338

s8533

TECHNOLOGY FOR IMPROVING OCTOPUS RESOURCE PRODUCTIVITY USING ARTIFICIAL REEFS
AND AI
Takafumi Yamamoto, Yoshihiro Suenaga, Tetsuya Tamaki, Shinichiro Okazaki and Hidenori
Yoshida

344

s8544

NUMERICAL AND ANALYTICAL STUDY FOR SOLVING HEAT EQUATION OF THE REFRIGERATIONOF APPLE
Dalal Adnan Maturi

350

ID

s8546

s8547

s8550

THE INVESTIGATION OF BIOGAS PERFORMANCE AFTER PURIFICATION USING NATURALZEOLITE AND RICE-HUSK BIOCHAR
Ambar Pertiwiningrum, Margaretha Arnita Wuri, Alva Edy Tontowi, Andang Widi Harto andMisri Gozan
WATER AND SANITATION SERVICE: A PRIORITY TO IMPROVE QUALITY OF SLUM AREAS IN
PONTIANAK CITY BASED ON STAKEHOLDERS’ PREFERENCES
Zulfa Amala, Ahmad Soleh Setiyawan, Prasanti Widyasih Sarli, Prayatni Soewondo and Dion
Awfa
IDENTIFICATION OF POTENTIAL URBAN SLUM SETTLEMENTS TO IMPLEMENT WATERSENSITIVE URBAN DESIGN
Nico Halomoan, Ahmad Soleh Setiyawan, Prayatni Soewondo, Prasanti Widyasih Sarli andDion Awfa

355

360

366

s8555

THE CHARACTERISTICS AND DISTRIBUTION OF DEEP GROUNDWATER IN DJIBOUTI
Yasuhiro Asakura, Sawahiko Shimada, Ko Hinokidani and Yasuhiro Nakanishi

372

s8558

HYDROCHEMICAL CHARACTERISTIC OF THE EASTERN SLOPES OF MOUNT KARANG, WEST
JAVA, INDONESIA
Hadi Hidayat, Deden Zaenudin and Boy Yoseph CSS Syah Alam

379

s8560

RELATIONSHIP BETWEEN THE LIVING ENVIRONMENT AND THE SENSE OF TIME-SPACE
Kazuki Miyake and Kazunari Tanaka

383

s8566

A REVIEW OF THE CURRENT LEGISLATION ON WASTE MANAGEMENT IN DEVELOPING AND
DEVELOPED COUNTRIES
Kylie Douglas, Daniela Ionescu, Joe Petrolito and Bandita Mainali

387

vii

s8567

THE IMPACT OF THE COVID-19 PANDEMIC ON RESORT AREAS AND ITS RELEVANT TOAGRICULTURAL MARKETS -A CASE STUDY OF KARUIZAWA, NAGANO PREFECTURE, JAPANReiko Machida, Yuya Mikami, Waya Kobayashi, Nobuhiko Tanaka, Teruaki Irie, Hijiri
Sjimojima, Tomohiro Kimata and Shigeyuki Miyabayashi

393

s8568

SOCIAL COSTS BY OCCURRING ROADKILL OF AMAMI RABBIT IN KAGOSHIMA, JAPAN
Hideyuki Ito, Yosuke Imahashi and Takahiro Fujii

399

s8570

IMPUTATION OF OUTLIERS AND MISSING VALUES FOR ACTIVATED SLUDGE DISSOLVEDOXYGEN DATABASE USING MULTIVARIATE IMPUTATION BY CHAINED EQUATIONS (MICE)
Hatem Nijim and Rabee Rustum

405

s8576

THE EFFECT OF FLEXIBLE WORKING ARRANGEMENT AND WORK LIFE BALANCE ON EMPLOYEEPRODUCTIVITY IN GOVERNMENT OFFICES IN BEKASI CITY, WEST JAVA
Beti Nurbaiti, Waluyo and Dwi Setyowati

409

s8581

ACOUSTIC EMISSION OF INTERNAL DRAINAGE IN MULTI-STOREY BUILDINGS
Anaebo Chike Emmanuel, Rabee Rustum, Lynne B Jack and Adebayo J. Adeloye

415

s8584

INFRASTRUCTURE IMPACTS CALCULATOR: AN INFRASTRUCTURE ASSESSMENT TOOL USING
CO-BENEFIT APPROACH
Nicanor R. Roxas, Jr., Krister Ian Daniel Z. Roquel, Krista Danielle S. Yu, Alerik Ezekiel C. Ruiz
and Alexis M. Fillone

421

s8588

GROWTH CHARACTERISTICS OF PINUS DENSIFLORA IN SIMULATED HEAVY METALCONTAMINATED SOIL
Takuma Kubohara, Hiroyuki Ii, Ryoichi Araki and Masakazu Saito

427

s8593

ANALYSIS OF FLOOD FLOW RATE CALCULATE FROM PRECIPITATION AT TYPHOON NO.19 IN
2019 IN THE ABUKUMA RIVER BASIN
Masanobu Taniguchi

432

s8594

ANALYSIS OF SEASONAL AND SECULAR VARIATIONS IN DISSOLVED OXYGEN CONCENTRATION
AT THE BOTTOM OF LAKE BIWA, JAPANJinichi Koue

437

s8595

GREEN PROCESS FOR CRUDE PALM OIL BIODIESEL PRODUCTION USING COMMERCIAL LIPASEENZYME
Mallika Tapanwong, Rayakorn Nokkaew, Pinsuda Viravathana and Vittaya Punsuvon

443

s8603

QUANTIFICATION OF HYDRATION PRODUCTS IN RICE HUSK ASH (RHA)-BLENDED CEMENTCONCRETE WITH CRUMB WASTE RUBBER TIRES (CWRT) & ITS CORRELATION WITH
MECHANICAL PERFORMANCEJohn Mark L. David, Richard M. De Jesus and Rodolfo P. Mendoza

449

s8605

FEASIBILITY STUDY FOR ENVIRONMENTALLY FRIENDLY PROCESS IN PREMIUM CRUDE PALMOIL PRODUCTION
Sureerat Namwong, Vittaya Punsuwan, Pinsuda Viravathana and Rayakorn Nokkaew

455

s8608

TUNGSTEN, COPPER, MANGANESE, ZINC, IRON AND ARSENIC CONCENTRATIONS OF PLANTS
IN KIWADA MINE
Daiki Yamamoto and Hiroyuki Ii

461

s8609

DIFFERENCES IN PLANTS HEAVY METAL CONCENTRATIONS BY REGION
Takuya Ueda and Hiroyuki Ii

467

s8614

A STUDY ON APPLICATION POSSIBILITY OF WOODEN BIOMASS COMBUSTION ASH MODIFIEDBY FLOTATION METHOD AS CONCRETE ADMIXTURE
Shilun Liu, Koji Takasu, Hidehiro Koyamada and Hiroki Suyama

472

s8615

EXAMINING WATER ENVIRONMENT DATA FOR AN ARTIFICIAL INTELLIGENCE EVALUATION
MODEL
Shengping Zhang and Jie Qi

478

s8626

FEASIBILITY OF USING BAUXITE RESIDUE STABILIZED WITH CEMENT KILN DUST FORGEOETCHNICAL APPLICATIONSMohamed Farid Abbas and Sultan Abdulaziz Almuaythir

484

s8632

MODELING ADSORPTION OF HEXAVALENT CHROMIUM USING A LOW-COST JORDANIAN
OLIVE STONE WASTE ADSORBENT
Aymen Awad

489

viii

s8635

EFFECT OF LANDCOVER CHANGE ON LAND SURFACE TEMPERATURE IN THE URBANIZED AREA
Agus Suharyanto

498

s8638

POLICIES AND PLANS FOR OPEN SPACE MANAGEMENT IN PARTNERSHIP IN POST-INDUSTRIALLANDSCAPES
Tomoko Miyagawa, Clare Olver, Noriko Otsuka and Hirokazu Abe

504

s8643

SURVEY ON RESIDENTS' AWARENESS TO BUILD THE SYSTEM OF RESIDENTS’-PATTICIPATIONMONITORING FOR SLOPE DISASTER PREVENTION USING THE TILT SENSORS
Zhijun Tang, Yoshikazu Miyamoto, Shusuke Oji and Hisashi Fujitani

512

s8647

CONCRETE BEHAVIOR USING RECYCLED WASTEWATER
Khaled Mohamed Nabil I. Elsayed, Gerald Benjamin Felipe Guico and Rabee Rustum

518

s8659

LOW-COST TECHNOLOGY FOR HERITAGE BUILDINGS DOCUMENTATION
Yohannes Firzal, Reni Suryanita, M. Arief Al Husaini and Nangkula Utaberta

524

s8667

s8569

APPLICATION OF DESIGN FOR MANUFACTURING AND ASSEMBLY ON TEMPORARY SHELTERSIN THE PHILIPPINES
Cheryl Lyne C. Roxas, Orlean G. Dela Cruz, Rhem Leoric C. Dela Cruz, John Paul Q. De Pedro,
Jonathan R. Dungca, Bernardo A. Lejano and Jason Maximino C. Ongpeng
DETECTION OF GEOGRAPHIC FRACTURE-FAULT STRUCTURES USING DEEP LEARNING MODELWITH STEPWISE ELIMINATION METHOD FROM HIGH RESOLUTION SATELLITE IMAGERY IN
DJIBOUTI
Denis Pastory Rubanga, Sergio Azael May Cuevas, Yessy Arvelyna and Sawahiko Shimada

528

534

s8520

SPATIAL ANALYSIS ON THE WIN OF CANDIDATE NUMBER 2 IN THE 2020 DEPOK CITY
ELECTION
Imam Budi Hartono, Chotib

540

s8574

EVALUATION OF GEOGRAPHICAL CHARACTERISTICS OF FARMLANDS LOCATION IN
DJIBOUTI USING GIS
Ayako Sekiyama, Towa Goto, Takumi Sato and Sawahiko Shimada

546

s8681

ENVIRONMENTAL IMPACTS ASSESSMENT OF REAL ESTATE PROJECT AT PALLABI EASTERNHOUSING AREA IN DHAKA CITY, BANGLADESH
Md. Mahabub Alan, Md. Soybur Rahman, Alex Otieno Owino, Abd Elmageed Atef, Md.
Yachin Islam and Zakaria Hossain

551

s8682

SEASONAL VARIATION OF RESIDENTIAL INDOOR AIR QUALITY IN MYMENSINGH CITY,BANGLADESH
Md. Soybur Rahman, Md. Mahabub Alam, Alex Otieno Owino, Abd Elmageed Atef, Md.
Yachin Islam and Zakaria Hossain

555

ix

Eighth International Conference on Structure, Engineering & Environment,
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

PrefaceOn behalf of the SEE 2022 Organizing Committee, it is our great pleasure to welcome you to the EighthInternational Conference on Structure, Engineering & Environment, held at Miyako Hotel Yokkaichi, Mie,
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

Even with the COVID-19, this year we have received many submissions from different countries all over theworld including Australia, Czech Republic, . The technical papers were selected from the vast number ofcontributions submitted after a review of the abstracts. The final papers in the proceedings have been peer
reviewed rigorously and revised as necessary by the authors. It relies on the solid 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 2022. We hope you enjoy the conference
onsite and ZOOM online and find this experience inspiring and helpful in your professional field. We lookforward to seeing you at our upcoming conference next year.

Best regards,
Prof. Dr. Zakaria Hossain, ChairmanxEighth International Conference on Structure, Engineering & Environment,
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 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, E/Prof. Mie University, Japan (Co-Chair)Dr. Masaaki Kondo, A/Prof. Mie University, Japan (Co-Chair)
National & International Advisory Committee:
Dr. Fumio Tatsuoka, E/Prof., Tokyo University of Science, Japan
Dr. Junichiro Takeuchi, Prof., Kyoto University, Japan
Dr. Kingshuk Roy, Prof., Nihon 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, E/Prof., Angles Univ. Found., Philippines
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, E/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. Ohio State University, USA
Dr. Md. Nurul Amin, Prof. Dhaka University, Bangladesh
Dr. Chan Chee-Ming, Prof. Universiti Tun Hussein Onn Malaysia
Dr. Ahmed H. A. Dabwan, A/Prof. TATI Univ. College, Malaysiaxi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, Polandxii

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, Thailandxiii

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. Alex Otieno Owino (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

xiv

Keynote Papers

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EFFECTIVENESS OF BRYOPHYTES AND CICADA SHELLS AS A BIOINDEX FOR HEAVY METAL CONTAMINATION OF RIVER WATER
AND SOIL
Hiroyuki Ii1
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Metal concentrations of sampled bryophytes varied widely and increased depending on the metal
contamination conditions. The highest values in bryophytes were several 10,000 ppm for Cu and Zn, 100,000
ppm for Pb, several 1,000 for As and a few 100 ppm for W. Bryophytes are therefore considered to be aneffective index of Cu, Zn, Pb, As, and W contaminations. However, the heavy metal concentration in bryophytes
at a W mine was low and the heavy metal concentration in other plants showed a higher concentration than thatof bryophytes. The presence of W is thought to be the cause of the decrease in the heavy metal concentrations in
bryophytes. The other possibility is that only bryophytes with a low copper concentration can grow. The highest
Zn concentrations in a cruciferous species reached several 10,000 ppm among sampled plants. The Cu and Znconcentrations in both cicada shells and adult cicadas were not always high at metal mines. Therefore, Cu andZn concentrations of cicada shells were not effective as a Cu and Zn contamination index. Pb and As
concentrations in cicada shells at Pb and As mines were higher than those for non-Pb and non-As contaminatedareas and were higher than those in cicada adults. Therefore, cicadas were thought to release Pb and As into theirshells during molting and maintain high concentrations of Pb and As in their cicada shells. Pb and As
concentrations in cicada shells were thought to be an effective contamination index.
Keywords: Cicada shells, Bryophyte, Heavy metals, Bio-index, Metal contamination

INTRODUCTION

accessible for metal ions [4], [5], pronounced ionexchange properties [6] and a large surface-toweight ratio also significantly contribute to thisability [7].
Advantages of bryophyte-performed monitoring,compared to conventional measurements, are costeffectiveness and easier sampling that results in amuch higher sampling density and a larger numberof sites that can be included in the survey [3], [8].
Due to the great capacity of bryophytes to absorb
and retain heavy metals in high concentrations, it isalso easier to perform chemical analysis and there
are fewer contamination problems [9].
The heavy metal concentration in river insect
larvae was found to decrease with weight. In
identical river conditions the heavy metal
concentrations in different insects, weighing thesame as the larvae, were the same. Therefore, bioconcentrations in small herbivorous insect larvae tolarge carnivorous insect larvae was not found [10].
Heavy metals in river insect larvae was thought to bereleased with the shells of river insect larvae.
Although it is difficult to sample shells of river
insect larvae because the molting of aquatic insects
is carried out in water, it is easy to sample cicada
shells found on trees. Metal concentrations in cicada
shells show a positive correlation with soil metal
concentrations[11].
Comparing
metal

Metal concentrations in river water and soil were
measured to investigate the influence of heavy
metals on local plants, insects and animals.
Generally, metal concentrations in river water isvery low. Moreover, they are changeable dependingon the change of flow rate. Heavy metals in soil
contain both soluble and insoluble metals, but livingorganisms use only soluble metals. Not all heavy
metals in the soil are used by living organisms.
Therefore metal concentrations in river water andsoil were not always useful as an index of theinfluence of heavy metals on life. Then, in thisstudy, bryophytes and cicada shells were proposed
as a new index for gauging metal contamination.
Bryophytes are easily found around rivers andcicada shells are easy to sample without digging andboth contain long term information and bryophytes
and cicadas absorbed metal into living body.
Bryophytes were the first green plants tocolonize the terrestrial environment [1], and as such
had to evolve mechanisms to cope with the muchgreater amounts of heavy metals present on land
than in the water [2]. The absence of a root system
indicates the ability of these plants to absorb heavy
metals over their entire surface [2], [3]. The lack of
the cuticle layer, which makes their cell walls easily2

SEE-Mie, Japan, Nov.10-12, 2022

concentrations in cicada shells and cicada bodies, Al,
Fe, and Pb were enriched in cicada shells and Cu
and Zn were enriched in cicada bodies [12]. Thus,
cicada shells are thought to be useful as a bio-index
for metal contamination. The purpose of this study istherefore to clarify the effectiveness and character ofbryophytes and cicada shells as a bio-index forheavy metal contamination of rivers and soils incomparison with plants at the same sampling points
and cicada adults.

RESULTS
BryophyteFirstly, Cu, Pb, Zn, As and W concentrations ofbryophytes were measured by studying thedifferences of metal concentrations in bryophytes
between metal contaminated and non-contaminatedareas. Bryophytes in Ikuno, Waidani, Tada, Rendaiji,
Kiwada, Kaneuchi, Nishinomaki and Dundasu mines
were sampled as metal contaminated areas. Yoshi
River (Okayama prefecture) - Tenjin River (Tottori
prefecture) and Izumi Mountain (Wakayama andOsaka prefecture) - Kongo Mountain (Osaka andNara prefecture) areas were non-contaminated areas.

METHOD
Bryophytes and some kinds of plants (ferns,
cruciferae, pines, Boenninghausenia albiflora, alders,rushs, laurels, and fruit plants) and cicada shells andadults were sampled at metal contaminated andmetal non-contaminated areas. Metal contaminatedareas were metal mine dumps and the ruins of old
factories. Metal mines were Ikuno (Cu, Pb, As, Zn
and W), Waidani (Cu, Pb, Zn and As), Tada (Cu, Pb
and Zn), Rendaiji (Cu, Pb and Zn), Kiwada (Cu, As
and W), Kaneuchi (Cu, As and W), Nishinomaki(As), Dundas (Cu, Pb, Zn and As), Naganobori (Cuand As), Iwami (Pb, Zn), Ningyotouge (U), Nyu(Hg) [13], [14]. Nishikino is the ruin of a wire
factory. Bryophytes in non-contaminated areas were
sampled at the river sides of the Yoshi and Tenjin
rivers (Okayama and Tottori prefecture) and a small
river on the Izumi and Kongo mountains.
The cicada shells and cicada adults sampled were
black cicadas, large brown cicadas, evening cicadas,
Oncotympana maculaticollis and Platypleura
kaempferi and Terpnosia nigricosta (sampled at only
Kusatsu). They were sampled on trees located atmetal contaminated areas (trees were on the metalmine dump) and non-contaminated areas. Noncontaminated areas were city parks in Osaka,
Wakayama and Tokyo, Serpentinite Hill (Ryumon,
Kamogawa (Mineoka), Nakase and Ogose, basalt
lava (Fujinomiya) and a hot spring area (Kusatsu).
In the laboratory, the sampled bryophytes, plants
and cicada adults and shells were first rinsed withultra pure water and then desiccated by a dryer.
After drying, they were dissolved with concentrated
nitric acid and filtered with a membrane filter with a
0.45 micrometer pore size. After filtering, the W, Cu,
Pb, Zn and As concentrations in plants and cicada
were measured by ICP-OES (AMETEK, Inc.,
SPECTRO ARCOS) in the laboratory at Wakayama
University. The actual detection limit of ICP-OES is0.001ppm for W, Cu, Pb, Zn and As. Plants,
excluding bryophytes, were divided into leaves,stems and roots and each part was separately
analyzed.

100000Cu(ppm)plantCu(ppm) bryophyte

10000
1000
100
10

Fig. 1

Nishinomaki
Dundas
Yoshi
TenjinIzumi
Kongo

KaneuchiKiwadaTada

Waidani

Ikuno

0.1

Rendaiji1

Cu concentrations of bryophyte for metal
contaminated and non-contaminated areas.

Figure 1 shows Cu concentrations in bryophytes
for metal contaminated and non-contaminated areas
and their variations were several 0.1 ppm to several
10,000 ppm. Except for Nishinomaki mine, mainly
Cu ore was produced at the mines and their Cu
concentrations were over 100 times higher thanthose for non-contaminated areas, mainly several toseveral tens ppm. Cu concentration at the
Nishinomaki mine was the same as those at the noncontaminated area. Even at the same mine, Cu
concentrations varied with sampling points. Under
the same non-contaminated conditions, thosesampled at Yoshii - Tenjin River area were higher
than those sampled at Izumi - Kongo area. The Cu
concentration in bryophytes varied widely by
location and particular sampling points. The highest
Cu concentration of bryophytes reached over 10,000
ppm at Waidani and Tada mines and these values
were also recorded by past studies [10], [11], [15],[16], [17], [18], [19]. Therefore, the Cu
concentrations in bryophytes was very sensitive to3

SEE-Mie, Japan, Nov.10-12, 2022

metal contaminated conditions. However, Cu
concentrations for Ikuno, Kiwada and Kaneuchi
mines accompanied with W mineral were not muchhigher than those for non- contaminated areas.

areas were the same as those at the Nishinomaki,
Kiwada and Kaneuchi mines. Even at the same mine,
Zn concentrations varied with sampling points.
However under the same non-contaminatedconditions, Zn concentration variations between the
Yoshii - Tenjin River area and the Izumi - Kongo
area were small. Zn concentrations in bryophytes
varied widely by location at particular sampling
points. The highest Zn concentrations in bryophytes
reached10,000 ppm at the Waidani and Ikuno mines
and these values were the largest values comparedwith past studies [11], [15], [16], [17], [18], [19].
Therefore, the Zn concentration in bryophytes wasvery sensitive to the level of metal contamination.

100000Zn(ppm)plant

1000
100

10000

10

As(ppm)plantAs(ppm) bryophyte

Nishinomaki
Dundas
Yoshi
TenjinIzumi
Kongo

KaneuchiTada

Waidani

Ikuno

Fig. 2

Kiwada1000

1

RendaijiZn(ppm) bryophyte

10000

Zn concentrations of bryophyte for metal
contaminated and non-contaminated area.

100
10
1

100

Nishinomaki
Dundas
Yoshi
TenjinIzumi
Kongo

Kaneuchi

Tada

Ikuno

1000

KiwadaPb(ppm) bryophyte

10000

Waidani

0.1

Pb (ppm)plant

Rendaiji

100000Fig. 4 As concentrations of bryophyte for metal
contaminated and non-contaminated areas.

10

Figure 3 shows Pb concentrations in bryophytes
for metal contaminated and non-contaminated areas
and their variation was from several 0.1 ppm toabout 100,000 ppm. The exceptions being
Nishinomaki, Kiwada and Kaneuchi mines where Pb
concentrations in bryophytes at Pb mines were from10 to 1000 times higher than those for noncontaminated areas whose concentrations weremainly several to several 10 ppm. Pb in bryophytes
sampled at metal non-contaminated areas were thesame as those at the Nishinomaki, Kiwada andKaneuchi mines. Even at the same mine, Pb
concentrations varied by sampling points. Pb
concentrations in bryophytes varied widely by
location and particular sampling points. The highest
Pb concentrations in bryophytes reached several
10,000 ppm at the Dundas mine and these values
were the largest values compared with past studies[10], [15], [16], [17], [18], [19]. Therefore, the Pb
concentrations in bryophytes were very sensitive tothe metal contaminated conditions.
Figure 4 shows As concentrations in bryophytesFig. 3

Nishinomaki
Dundas
Yoshi
TenjinIzumi
Kongo

KaneuchiKiwadaTada

Waidani

Ikuno

0.1

Rendaiji1

Pb concentrations of bryophyte for metal
contaminated and non-contaminated areas.

Figure 2 shows Zn concentrations in bryophytes
for metal contaminated and non-contaminated areas
and the variation was several ppm to a few 10,000
ppm. Except Nishinomaki, Kiwada and Kaneuchi
mines, Zn concentrations in bryophytes at Zn mines
were 10 to 100 times higher than those for noncontaminated areas whose concentrations weremainly several 10 to several 100 ppm. Zn.
Bryophytes sampled at metal non-contaminated4SEE-Mie, Japan, Nov.10-12, 2022

for metal contaminated and non-contaminated areas
and their variation was from several 0.1 ppm toseveral 1,000 ppm. Bryophyte As concentrations at
Nishinomaki, Ikuno, Dundas and Waidani mines
where As ore mineral was extracted were over 100
ppm, 10 to 100 times higher than those for noncontaminated areas. As minerals, Realgar AsS andorpiment As2S3 were found at the Nishinomaki
mine. The maximum As concentration in bryophytes
reached several 1,000 ppm at the Waidani mine andthese values were the largest values compared withpast studies [10], [11], [15], [16], [17], [18], [19].
Therefore, As concentrations in the bryophytes weresensitive to the metal contamination condition.

contaminated areas and their variations which werefrom several ppm to a few 100 ppm.
W
concentrations in most of the samples were very low
and undetectable. However, W concentrations at the
Kiwada mine was 100 to 1000 ppm, 10 to 100 times
higher than the non-contaminated areas. The
sampling points at the Kiwada mine were the stored
ore composed of mixed sands and stones with a W
content of of about 10%. The plants in this area had
grown naturally for over 10 years. At the Ikuno andKaneuchi mines, W minerals were found but the W
concentrations were not extremely high, 10 to 100
ppm. The maximum W concentration in the
bryophytes reached several 100 ppm at Kiwada mine.
Therefore, the W concentrations in the bryophytes
was sensitive to the metal contaminated condition.

1000

PlantsNext, Cu, Pb, Zn, As and W concentrations of
the bryophytes and plants were measured to study
the difference in metal concentrations between
bryophytes and plants for Ikuno, Waidani, Tada,
Rendaiji, Kiwada, and Kaneuchi mines. Figure 6
shows Cu concentrations in bryophytes and plants
for metal contaminated areas. Cu concentrations in
bryophytes were not always the highest value of allplants for each metal contaminated area. For the
Kiwada mine, Cu concentrations in alders had thehighest values even though their Cu concentrations
varied. It’s root concentrations were high. Cu
concentrations in bryophytes at the Tada, Waidani
and Rendaiji mines were the highest values
compared to other plants. Cu concentrations in
bryophytes at the Kaneuchi and Ikuno mines were
almost the same as those of ferns. Kiwada mine wasa W mine and plants and bryophytes were sampled
on the W ore sediments. Ikuno and Kaneuchi mines
produced W ore accompanied with Cu ore. Tada,
Waidani and Rendaiji mines did not produce W
minerals. When accompanied with W minerals, Cu
concentrations in bryophytes at mines were lowered.
Therefore, the W mineral was thought to beimportant for Cu concentrations in bryophytes.
Figure 7 shows Zn concentrations in bryophytes
and plants for metal contaminated areas. The highest
Zn concentrations were in cruciferous plants at the
Tada and Ikuno mines. They were several 10,000
ppm, and the highest of the sampled plants as well as
the ferns at the Tada mine. The highest bryophyte
Zn concentrations at the Ikuno and Waidani mines
reached 10,000 ppm. Therefore, the Zn
concentrations in bryophytes were not always thehighest values among the plants for each metal
contaminated area. However, the Zn concentrations
in pines and other plants were lower than those of
the bryophytes. For the Kiwada mine, the highest Zn
values in the bryophytes, pines, ferns and alders
increased from several 100 ppm to 1,000 ppm in that100

Fig. 5

Nishinomaki
Dundas
Yoshi
TenjinIzumi
Kongo

KaneuchiTada

WaidaniIkuno

1

Kiwada10

RendaijiW(ppm) bryophyte

W plant

W concentrations of bryophyte for metal
contaminated and non-contaminated areas.

100000

Ikuno
Tada

KiwadaKaneuchiWaidaniRendaijiCu(ppm)plant

10000
1000
100

Rush
LaurelFruit
Plants

Alder

Fern

B.
albiflora

Pine

Bryophyte

1

Cruciferous

10Fig. 6 Cu concentrations of plants for metal mines.
Figure 5 shows the W concentrations in
bryophytes for metal contaminated and non5

SEE-Mie, Japan, Nov.10-12, 2022

order. Zn concentrations in the bryophytes for the
Kiwada mine was almost the same as non-Zn
contaminated areas. When accompanied with W
minerals, Zn concentrations in bryophytes at mines
were lowered. Therefore, the W mineral was thought
to be important for Zn concentrations in bryophytes.

several 100 ppm, in the alders, ferns and pines at the
Kiawada mine which were higher than the several
10 ppm, in the bryophytes at the Kiwada mine. The
highest Pb concentrations in pines and ferns at
Kaneuchi were several 10 ppm, almost the same as
those in the bryophytes at Kaneuchi. Without the W
mineral, the highest Pb concentrations in bryophytes
reached several 1,000 ppm. When accompanied with
W minerals, Pb concentrations in bryophytes atmines were low. Therefore, the W minerals arethought to be important for Pb concentrations in
bryophytes. Without W, the bryophytes’ Pb
concentrations reached the higher values.

100000Zn(ppm)plant

10000
1000

10000

100

Ikuno
Tada

1000

KiwadaKaneuchiWaidaniRendaiji10
WaidaniRendaiji101
0.1

Zn concentrations of plants for metal mines.

Pb(ppm)plantFig. 9Alder

Cruciferous

100

Fern

Bryophyte

1000

B.
albiflora

0.01

10000

Rush
LaurelFruit
Plants

Alder

Fern

B.
albiflora

100

Pine

Fig. 7

Pine

Bryophyte1As(ppm)plant

KiwadaKaneuchi

Cruciferous
Rush
LaurelFruit
PlantsIkuno
Tada

As concentrations of f plants for metal
mines.

10
10000

1
1000

0.1

10
1

Rush
LaurelFruit
Plants

Cruciferous

Alder

0.01
Fern

Figure 8 shows Pb concentrations in bryophytes
and plants at metal contaminated areas. Pb
concentrations in bryophytes were always thehighest value among plants in each of the metal
contaminated areas except for the Kiwada andKaneuchi mines. The highest Pb concentrations in
bryophytes reached several 1,000 ppm. Pb
concentrations in pine roots, ferns and cruciferous
plants were over 1,000 ppm, although Pb
concentrations in pines, ferns and cruciferous plants
were variable. The highest Pb concentrations were,B.
albiflora

0.1

Bryophyte

Pb concentrations of plants for metal mines

Ikuno
Tada
KiwadaKaneuchiWaidaniRendaiji
Pine

Cruciferous
Rush
LaurelFruit
Plants

Alder

Fern

B.
albiflora

Pine

BryophyteFig. 8W(ppm)plant

100

0.01

Fig. 10 W concentrations of f plants for metal
mines.
Figure 9 shows As concentrations in bryophytes
and plants for metal contaminated areas. As
concentrations in bryophytes were always the6

SEE-Mie, Japan, Nov.10-12, 2022

highest values among plants for each of the metal
contaminated areas except for the Kiwada W mine.
The highest As concentrations in bryophytes reacheda few 1,000 ppm. The highest As concentrations inpine roots, ferns and alders were over 100 ppm,
although the As concentrations were variable. The
highest As concentrations, were several 100 ppm,inalders, ferns and pines at the Kiawada mine whichwere higher than the several 10 ppm, in the
bryophytes at the Kiwada mine. Without a lot of W
minerals, the highest As concentrations in the
bryophytes reached a few 1,000 ppm. Whenaccompanied with a lot of W minerals, Asconcentrations in bryophytes at the mines was low.
Therefore, W minerals were thought to be importantfor As concentrations in bryophytes.
Figure 10 shows W concentrations in bryophytes
and plants for metal contaminated areas. W
concentrations in bryophytes were not always thehighest values among plants for each of the metal
contaminated areas. For the Kiwada mine, thehighest values in bryophytes, pines, ferns and alders
increased from 1,000 ppm to several 1,000 ppm inthat order. The maximum W concentrations in
bryophytes, pines, ferns and alders in the Kiwada
mine were more than 10 to 100 times higher thanthose in the Ikuno and Kaneuchi mines and the W
concentrations in plants depended on the W
concentrations in the soil.

Figure 11 shows Cu concentrations of cicada
shells and cicada adults which were very variable.
From several 0.1 ppm to several 1,000 ppm for
cicada shells and from several 10 ppm to over 300
ppm for cicada adults. The mark of “Large brown”
showed large brown cicadas and Oncotympana
maculaticollis as well as the following figures. They
were the same sizes. The mark of “Evening” showedevening cicadas, Platypleura kaempferi and
Terpnosia nigricosta (sampled at only Kusatsu) as
well as the following figures. They were the same
sizes. Black cicadas (the mark of Black) were
sampled in city parks and ruins in various cities inWest Japan. Their shell Cu concentrations weremainly several to several 10 ppm and lower thanthose of the other cicada shells. Cu shellconcentrations of large brown cicadas andOncotympana maculaticollis were from 10 toseveral 1,000 ppm and higher than those of othercicada shells. Cu shell concentrations of large brown
cicadas and Oncotympana maculaticollis for Cu
non-contaminated areas, serpentinite, Tokyo parks,
and Fujinomiya (Basalt flow) were almost the sameas the Cu mining areas (Ikuno, Tada, Naganobori,Rendaiji, and Iwami mines). Cu shell concentrationsof the evening cicada and Platypleura kaempferi
were very variable, from several to several 1,000
ppm. Their Cu concentrations at Cu mines (Ikuno,
Tada, Naganobori, Rendaiji, and Iwami mines) were
not higher than those at Cu non-producing.
Therefore, the Cu concentrations in cicada shells at
Cu metal mines were not always high.
The Cu concentration variations in cicada adults
was very narrow relative to those of cicada shells
when comparing Cu concentrations in cicada adults
between Ikuno mine and Tokyo parks. Bothvariations were almost the same. Therefore, the Cu
concentrations in cicada shells for Cu metal mines
were not always high when comparing Cu
concentrations between cicada shells and cicada
adults at the same points and these results wereconsistent with past results [12]. Therefore, cicadas
did not selectively release Cu into their shells duringmolting.
Figure 12 shows Zn concentrations of cicada
shells and cicada adults. The concentrations werefrom several ppm to 10,000 ppm for cicada shells
and from 50 ppm to 1,200 ppm for cicada adults.
Zn concentrations in black cicada shells werefrom 10 to several 1,000 ppm, not lower than thoseof the other cicada shells and had a very wide
variation unlike the Cu results. Zn shellconcentrations in large brown cicadas andOncotympana maculaticollis were from several 100
ppm and lower than those of the other cicada shells
even for Zn mines such as Ikuno, Tada, Rendaiji andIwami. Zn concentrations in the shells of large
brown cicadas and Oncotympana maculaticollis at
Zn metal mines were not always high relative to

Cicada shells and adults
Cu, Pb, Zn, As and W concentrations in cicada
shells and adults were measured by studying thedifference in metal concentrations in cicada shells
and cicada adults comparing metal contaminated andnon-contaminated areas.
10000

100
10
1
0.1

Black
Large brown
Evening
Adult
Ikuno
Tada
Naganobori
WaidaniRendaiji
Iwami
Nishinomaki
Nishikino
Osaka
Wakayama
Serpen (R K)
Serpen (N)Tokyo
Kusatsu
NingyouFujinoNyu
Serpen (O)
Bajyo
Syuri

Cu(ppm)1000

Fig. 11 Cu concentrations of cicada shell andcicada adult.
7

SEE-Mie, Japan, Nov.10-12, 2022

those for non-Zn contaminated areas, serpentinite,
Tokyo parks, and Fujinomiya (Basalt flow).

variations were almost the same. Therefore, the Zn
concentrations in cicada adults for Zn metal mines
were not always high when comparing Zn
concentrations between cicada shells and cicada
adults at the same points, Ikuno mine, Kusatsu hot
spring and Tokyo parks. Both Zn cicada adultconcentrations were higher than those of cicada
shells and these results were consistent with past
results [12]. Therefore, the cicadas selectively kept
Zn in their bodies during molting.
Figure 13 shows Pb concentrations in cicada
shells and cicada adults The concentrations werefrom 0.1 ppm to several 100 ppm for cicada shells
and from several 0.01 ppm to several 10 ppm for
cicada adults.
Pb concentrations in black cicada shells had awide variation, from 0.1 to several 100 ppm.
However, these values were divided into three types.
At Nishikinohama (ruins of wire factory), they wereseveral ppm to several 100 ppm. At Osaka parks,
they were from 1 to several 10 ppm. At Wakayama
parks, they were from several 0.1 to 10 ppm. The
differences were thought to depend on
contamination because Osaka parks in the city weremore polluted by air than Wakayama and the wire
factory previously used Pb.
Pb concentrations in the shells of large brown
cicadas and Oncotympana maculaticollis were fromseveral ppm to several 100 ppm for Pb mines suchas the Ikuno, Tada, Naganobori, Rendaiji and Iwami
mines and from several 0.1 ppm to less than 10 ppm
for non-Pb contaminated areas such as serpentinite.
Similarly, Pb concentrations in the shells of evening
cicadas and Platypleura kaempferi were fromseveral ppm to several 100 ppm for Pb mines suchas the Ikuno, Tada, Naganobor, and Waidani mines
and from several 0.1 ppm to less than 10 ppm for
non-Pb contaminated areas such as serpentinite.
Therefore, Pb concentrations in cicada shells at Pb
mines were higher than those for non-Pb
contaminated areas.
The high Pb concentrations in cicada adults
sampled at Pb mines were higher than those at nonPb contaminated areas although they had wide
variations. When comparing the Pb concentrations in
cicada shells and adults, the Pb concentrations in
cicada shells were higher than those in cicada adults
even though both concentrations had wide variations.
As a result, these results were consistent with past
results [12]. Therefore, cicadas were thought torelease Pb into their shells during molting and keephigh Pb concentrations in their shells in Pb
contaminated areas. Pb concentrations in cicada
shells was thought to be contamination index.
Figure 14 shows As concentrations in cicada
shells and cicada adults and their concentrations
were from 0.1 ppm to several 1,000 ppm for cicada
shells and several 0.1 ppm to several ppm for cicada
adults.

10000

Zn(ppm)

1000

100

10
Evening
Adult

Ikuno
Tada
Naganobori
WaidaniRendaiji
Iwami
Nishinomaki
Nishikino
Osaka
Wakayama
Serpen (R K)
Serpen (N)Tokyo
Kusatsu
NingyouFujinoNyu
Serpen (O)
Bajyo
Syuri

1

Black
Large brown

Fig. 12 Zn concentrations of cicada shell and cicada
adult.
1000

Pb(ppm)

100
10
1

0.01

Black
Large brown
Evening
Adult
Ikuno
Tada
Naganobori
WaidaniRendaiji
Iwami
Nishinomaki
Nishikino
Osaka
Wakayama
Serpen (R K)
Serpen (N)Tokyo
Kusatsu
NingyouFujinoNyu
Serpen (O)
Bajyo
Syuri

0.1

Fig. 13 Pb concentrations of cicada shell and cicada
adult
Zn concentrations in the shells of evening
cicadas and Platypleura kaempferi were veryvariable, from several 10s to several 1,000 ppm andhigher than those in large brown cicadas andOncotympana maculaticollis. The Zn concentrations
at Zn mining areas (Ikuno, Tada and Waidani mines)
were not higher than those at non-Zn mining areas.
Therefore, Zn concentrations in cicada shells for Zn
metal mining areas were not always high.
The Zn concentration variations in cicada adults
were very narrow relative to those of cicada shells.
When comparing the Zn concentrations in cicada
adults between the Ikuno mine and Tokyo parks, the8SEE-Mie, Japan, Nov.10-12, 2022

Generally, As concentrations in black cicada
shells had a wide variation, from 0.1 to10 ppm. As
The concentrations in the shells of large brown
cicadas, Oncotympana maculaticollis. evening
cicadas and Platypleura kaempferi at the Ikuno,
Naganobori, Nishinomaki and Bajyo mines andserpentinite (Nakase mine), of As minerals werehigher than those of non-As contaminated areas(mines without As mineral and serpentinite (R, K,
O). Therefore, As concentrations in cicada shells at
As mines were higher than those for non-As
contaminated areas.
The As concentrations in cicada adults werefrom several 0.1 to several 1 ppm at the Ikuno mine
The As produced was almost the same as other areas.
Therefore, As concentrations in cicada adults for As
contaminated areas was not always high. When
comparing the As concentrations in cicada shells andadults, the As concentrations in cicada shells wereover 10 times, higher than those of cicada adults andin particular, for the Ikuno mine and Tokyo parks
Therefore, cicadas were thought to release As
into their shells during molting and keep a high As
concentration in their shells. As concentration in
cicada shells was thought to be contamination index.

several 0.1 ppm to about 100,000 ppm for Pb, fromseveral 0.1 ppm to several 1,000 ppm for As andfrom several ppm to a few 100 ppm for W andincreased depending on the metal contamination
conditions. Therefore, it is considered to be effective
as an index of Cu, Zn, Pb, As, and W
contaminations. However, the Zn concentrations in
bryophytes was not always the highest among theplants in each of the metal-contaminated areas. The
highest Zn concentrations in a kind of cruciferous
plants were several 10,000 ppm, which was thehighest among the sampled plants. In addition,
where there is a large amount of W, such as theKiwada W mine, the heavy metal concentrations in
bryophytes were not high, and the heavy metal
concentrations in other plants showed a higher
concentration than that of the bryophytes. At the W
mine, the alders had the highest Cu, Zn, Pb, and As
concentrations. The presence of W is thought to be
the cause of the decrease in the heavy metal
concentration in bryophytes, which prevents theadsorption of metals into the cell walls of thebryophytes. The other possibility is that only
bryophytes with a low metal concentration weregrowing.
The metal concentrations in cicada shells fromblack cicadas, large brown cicadas, Oncotympana
maculaticollis, evening cicadas and Platypleura
kaempferi varied from several 0.1 ppm to several
1,000 ppm for Cu, and several ppm to 10,000 ppm
for Zn. The metal concentration variations in cicada
adults was from several 10 ppm to 300 ppm for Cu,
and 50 ppm to 1,200 ppm for Zn. The Cu and Znconcentrations in both cicada shells and adults were
not always high for the metal mines and cicada shellconcentrations were not always higher than those of
cicada adults. Therefore, the cicadas did notselectively release Cu and Zn into their shells duringmolting and as a result the Cu and Zn concentrations
in cicada shells sampled from Cu metal mines (Cuand Zn contaminated areas) were not always high.
As a result, it is unsuitable for a Cu and Zn
contamination index.
The metal concentrations in cicada shells andcicada adults were from 0.1 ppm to several 100 ppm
and from several 0.01 ppm to several 10 ppm for Pb
and from 0.1 ppm to several 1,000 ppm and fromseveral 0.1 ppm to several ppm for As. Pb and As
concentrations in cicada shells at Pb and As mines
were higher than those for non-Pb As contaminatedareas. Pb and As concentrations in cicada shells
were higher than those of cicada adults. Therefore,
cicadas were thought to release Pb and As into theirshells during molting and keep Pb and As highconcentration in cicada shells in Pb and As
contaminated areas. Pb and As concentrations in
cicada shells were thought to be a good
contamination index

10000
Black
Large brown
Evening
Adult

As(ppm)

1000
100
10
1

0.01

Ikuno
Tada
Naganobori
WaidaniRendaiji
Iwami
Nishinomaki
Nishikino
Osaka
Wakayama
Serpen (R K)
Serpen (N)Tokyo
Kusatsu
NingyouFujinoNyu
Serpen (O)
Bajyo
Syuri

0.1

Figure 1 4 As concentrations of cicada shell andcicada adult
CONCLUSIONSIn this study, effective indicators of metal
contamination need a wide variation of metal
concentrations depending on the contamination.
Therefore, metal concentrations in bryophytes,
plants, cicada shells and cicada adults sampled atmetal-contaminated and non-contaminated areas
were measured.
The metal concentrations in bryophytes varied
from several 0.1 ppm to several 10,000 ppm for Cu,from several ppm to a few 10,000 ppm for Zn, from9

SEE-Mie, Japan, Nov.10-12, 2022

REFERENCES

As Contaminations in Rivers, Japan,
International Journal of GEOMATE, Vol. 12,No.33, 2017, pp. 153-159.
[11] Ii H., Effectiveness of using cicada shell andriver bryophyte as an index of available Cu, Zn,
Pb, As, Ni and Cr contamination, in Proc. 4th
Int. Conf. on SEE, 2018, pp. 914-919.
[12] Robinson Jr. G.R., Sibrell P.L., Boughton C.J.
and Yang L.H., Influence of soil chemistry on
metal and bioessential element concentrations in
nymphal and adult periodical cicadas(Magicicada spp.), Science of the Total
Environment, Vol. 374, 2007, pp. 367-378.
[13] Exploration Working Group of Japan Mining
Industry Association, Overview of Japanesedeposits, Volume1, Japan Mining Industry
Association, 1965, pp. 1-581. In Japanese.
[14] Exploration Working Group of Japan Mining
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Association, 1968, pp. 1-941. In Japanese.
[15] Ii H., Konno H., Yamashita Y., Uno J.,
Shimogaki H., Ikeda S. and Nishimura T.,
Arsenic concentration and stable isotopic ratiosof oxygen and hydrogen for groundwater andriver water around the Midoro and Shidenhigashi
tunnels in Gose city, Nara, central, Japan, in Proc.
7th Int. Conf. on GEOMATE, 2017, pp. 684-689.
[16] Ii H. and Yamashita M., Mapping stable
isotopic ratios of stream water and Cu, Zn, Pb
and As concentrations of Bryophyte along
streams in the east of Okayama and Tottori
prefectures, Japan, in Proc. 4th Int. Conf. on SEE,
2018, pp. 925-930.
[17] Kubohara T. and Ii H., Cu Co and Ni
Contamination Index for River Using River
Insects and River Plants, International Journalof GEOMATE, Vol.11, Issue 26, 2016,
pp.2651-2658.
[18] Kubohara T. and Ii H., Evaluation of Metal
Contamination for River using Bryophyte in the
Kinokawa River Catchment, International
Journal of GEOMATE, Vol.12, Issue 37, 2017,
pp.135-142.
[19] Kubohara T. and Ii H., Zn and Fe
Contamination Index for River using River
Insects and Water Plants in The KinokawaRiver Catchment, International Journal of
GEOMATE, Vol.19, Issue 75, 2020, pp.76-83.

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[2] Degola F., De Benedictis M., Petraglia A.,
Massimi A., Fattorini L., Sorbo S., Basile A., anddi Toppi L. S., A Cd/Fe/Zn-responsive
phytochelatin synthase is constitutively present
in the ancient liverwort Lunularia cruciata (L.)
Dumort. Plant and Cell Physiology, Vol. 55,
2014, pp. 1884-1891.
[3] Berg T. and Steinnes E., Use of mosses(Hylocomium
splendens
andPleuroziumschreberi) as biomonitors of heavy
metal deposition: from relative to absolutedeposition values. Environmental Pollution Vol.
98, 1997, pp. 61-71.
[4] Choudhury S. and Panda S. K., Toxic effects,
oxidative stress and ultrastructural changes inmoss Taxithelium nepalense (Schwaegr.) Broth.
under chromium and lead phytotoxicity. Water,Air, Soil Pollution, Vol. 167, 2005, pp. 73-90.
[5] Koz B. and Cevik U., Lead adsorption capacityof some moss species used for heavy metal
analysis. Ecological Indicators, Vol. 36, 2014, pp.
491-494.
[6] Little P. and Martin M. H., Biologicalmonitoring
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Environmental Pollution, Vol. 6, 1974, pp. 1-19.
[7] Sun S. Q., He M., Cao, T., Zhang Y. C. and Han
W., Response mechanisms of antioxidants in
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[8] Schröder W., Holy M., Pesch, R., Harmens H.,
Ilyin I., Steinnes E., Alber R., Aleksiayenak Y.,
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[9] Berg T., Røyset O. and Steinnes E., Moss
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River Insect Larvae as an Index of Cu, Zn and10

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CURRENT CHALLENGES IN GEOLOGICAL STORAGE OF CARBONDIOXIDEJohn Victor Smith1
Faculty of Engineering, RMIT University, Australia

1

ABSTRACTThe storage of carbon dioxide in secure underground sites has been identified as an important contributor topreventing climate change impacts of excessive CO2 in the atmosphere. Significant quantities of carbon dioxidemust be collected and stored for this technology to make the required contribution to climate change abatement.
The quality of the storage must be validated by a range of techniques to ensure that the CO2 is stored safely without
the risk of excessive leakage. The carbon dioxide can be stored as a gas, supercritical fluid or a solid bymineralization. Trapping gas or supercritical fluid requires a setting similar to the natural trapping of gases in subsurface sedimentary rock reservoirs. Mineralization most commonly occurs in the form of carbonate minerals.
The most advanced high-volume projects focus on the trapping of supercritical fluids. Smaller scale project haveachieved some success in mineralization within basalt lavas. Other potential geological settings are reviewed.
Keywords: CO2 Sequestration, Geological Storage, Saline Aquifers, Carbonate Mineralization
INTRODUCTION

Capillary Number can be used to define the transitionof the flow mechanisms [4].

International studies of pathways to moderatingclimate change recognize the need for reduction inatmospheric carbon dioxide (CO2) by use ofgeological storage [1]. The most advanced methodsof geological storage of CO2 are those that build on
knowledge and technology of the oil and gas
industries. In particular, the injection of supercritical
CO2 into sedimentary rock reservoirs has been
demonstrated as a feasible technology [2]. The
injection of dissolved gas into reactive rocks such as
basalt has also been demonstrated as a feasible
technology, albeit at a smaller scale [2].
Biological and soil-based sequestration is
acknowledged as a significant technology [3] but is
not addressed in this paper.
In this paper, challenges and opportunities forgeological storage of CO2 are reviewed. In particular,
the need for greater application of knowledge of thepermeability and reactivity of a range of geologicalsettings is addressed.
The primary challenge
recognized is the need for large volume storage.

Depleted Reservoirs
The most direct experience of geological storageof CO2 comes from injection into productive
reservoirs for the purpose of enhancing oil and gas
recovery. These reservoirs may become suitable
places for storage of CO2. However, the presence ofnumerous production wells in some such fields may
make the seal integrity problematic [2].
Saline Aquifers
Most deep aquifers are typically saturated withsaline water. Such aquifers have generally not been
drilled extensively and can provide large potential
storage volumes.
The Sleipner project has used a deep saline aquifer
below the previously productive oil and gas fields in
the North Sea to store large volumes of CO2 [5]. Suchoffshore basins represent very extensive potential
reservoirs for future CO2 storage [6].
Onshore basins also include many potential saline
aquifers. Large CO2 storage projects such as In Salah
in Algeria [7] and Aquistore in Canada [8] have usedsuch onshore basins.

DEEP STORAGE
The transition to supercritical CO2 with pressuremeans that efficient storage can be achieved at depths
where pressure is sufficient to maintain the
supercritical condition.
As supercritical CO2 is injected into an aquifer
flow initial follows Darcy’s Law. However, Darcy
flow soon gives way to Invasion Percolation flow
behavior. Invasion Percolation flow is dominated bycapillary and buoyancy effects. The unit-less

Non-Sandstone Aquifers
The potential for storage sites is greatly increased
if aquifers other than sandstones can be found to haveadequate permeability. One such example is at theCO2 injection site at Tomakomai, Hokkaido,
11

SEE-Mie, Japan, Nov.10-12, 2022

Fig.1 Conceptual summary of some methods of carbon dioxide trapping relative to depth
Japan.
The Tomakomai trial CO2 injection site targeted asandstone aquifer and a volcanic unit [9]. The
volcanic unit being the Takinoue Formation which
consists of a lower mudstone and upper volcanoclastic members. During investigation, the volcanoclastic rocks were considered to have potential as areservoir. The upper Takinoue Formation is divided
into two parts, an upper part dominated by tuff and alower part dominated by lava and breccia. According
to the data used at the assessment stage of the project,
the lava and breccia tended to have higher
permeability than the tuff. Seismic data also
supported the potential for coarse volcanic sediments
to have high porosity and permeability. A structural
trap was also present in the form of an anticline. The
overlying thick mudstones of the Fureoi and BiratoriKarumai Formations were considered to havepotential to form a good cap rock [9].
However, low injectivity was achieved in the
Takinoue Formation compared to the Moebetsu
Formation sandstones which were the main reservoir
targeted in the trial [10]tensile micro-cracks, and/or mobilising of preexisting critically stressed fractures.
The stress-dependent changes in effective
permeability in the injection region are speculated toenhance CO2 injectivity performance. However, thetemperature-induced stresses could also create new,
localized, flow pathways through low-permeability
non-reservoir formations, including caprock units.
The overall pore pressure distribution in an
aquifer has the potential to re-activate faults which
would become evident as seismic activity. It is notedthat although this has occurred at some projects no
induced seismicity has been detected at the Aquistore
project [8].
Understanding the complex thermal and stressphenomena in a reservoir injected with CO2 isessential for successful long-term containment andconformance of the host aquifers and sealing units[11]. Other processes at the injection point include
CO2-brine chemical interaction such as salt
precipitation which can locally impede injectivity[12, 13].
It has been proposed that CO2 plumes canpotentially be used as a recirculated geothermal fluidwith a syphon effect [14,15].

Gas Injectivity
The Aquistore project in Canada showed a generalincrease in well injectivity performance with time.
These injectivity observations and operational data
were collected from two highly instrumented
injection and observation wells specifically drilled forCO2 storage at Aquistore [11]. The injection location
typically experience complex stress conditions thatcan overcome the tensile strength of the host rockleading to temperature-induced pore deformation,

OPPORTUNITIES FOR MINERALIZATION
Many of the existing projects intend to store CO2
by trapping the gas within pore space. Somemineralization may incidentally occur. Other projects
are focusing on the potential to form minerals with
CO2 as a form of storage. There are also significant
new technologies developing to utilize CO2 in
manufacturing which will not be reviewed here.
12

SEE-Mie, Japan, Nov.10-12, 2022

Near Surface
The process of weathering of rocks generally
consumes CO2. More specifically, a number ofprojects are investigating the use of mine tailings as
an opportunity to store CO2. Mine tailings are
typically fine-grained and some have significant
alkalinity to react with CO2 [16,17]. Another projectis applying carbonate mineralization with CO2 to the
problem of dealing with asbestos minerals that arepresent in some mine waste dumps and tailings [18].
Shallow Underground
The Carbfix project in Iceland is a well known sitewhere carbonate mineralization is the main focus as acarbon storage mechanism [19]. The CO2 is typicallynot in a supercritical state as the depth of injection isdown to about 750 m. The gas is mixed with and/or
dissolved in water which is understood to enhance themineralization process. The abundance of calcium inbasalt promotes the formation of calcium carbonate(calcite).
Studies on the natural carbonate mineralization
systems in the basalt have also contributed tounderstanding of the mechanism [20].

Fig.2 Natural mineral infilling in a fracture in basalt(photograph by author)

Deep Underground

Ultramafic Rocks

Other projects have targeted gaseous storage andmineralization with supercritical injection of CO2 into
basalt [21]. In the Columbia River basalts brecciatedzones between lava flows at depths between 800900m were injected with supercritical CO2 [22].
Approximately 1000 tonnes of CO2 were injected
over a 25-day period in July to August of 2013.
Testing two years later identified free phasesupercritical CO2 fluid in the vicinity of the injection
site. Carbonate mineral (ankerite, a mixed Ca-Mg-Fe
carbonate) nodules were also recovered from the coresampling and could be directly linked to the injected
CO2 through analysis of isotopes [22].
It is notable that in saline aquifers naturalcarbonate minerals can also be found forming. For
example, siderite (Fe carbonate) has been recorded inaquifers related to the Gorgon CO2 storage project inAustralia [23].

Basalt is known as a ‘mafic’ igneous rock due tocontaining mainly silicate minerals with a highproportion of Mg, Fe and Ca. Such minerals include
olivine, pyroxenes and plagioclase. These minerals
have the greatest potential to fix CO2 as carbonate
minerals because they have a high molar proportionof divalent cations and they react relatively rapidly toform carbonate minerals [24].
Ultramafic rocks contain even higher proportionsof Mg and as such are also potential opportunities forreactions with CO2 [24]. Ultramafic rocks are present
in many locations around the world.
Intrusive Mafic (and Ultramafic) Rocks
An interesting occurrence of mafic (andultramafic) rocks is as intrusions into sedimentarystrata. This is of interest as the sedimentary layers
may represent reservoirs and caprocks augmented by
the presence of reactive mafic rocks.
Many onshore and offshore basins contain mafic
intrusions within their strata. For example, thepassive margin sedimentary sequences of the Otway
Basin of Victoria, Australia have been trialed for CO2
storage. The strata have also been found to containmafic intrusions that were initially indentified due tothe doming of strata in their vicinity [25].

Reactive Rocks
Oceanic Crust
As pointed out by the proponents of the Carbfix
project, Iceland is a location where oceanic crust ispresent above sea-level [19]. They emphasize that theentire oceanic crust is basaltic rock with CO2
mineralization potential. As will be discussed below
there are many other geological environments withpotentially reactive rocks.
13

SEE-Mie, Japan, Nov.10-12, 2022

The Sydney Basin in New South Wales, Australia
was intruded by mafic magmas within thesedimentary strata. One such intrusion is the Prospect
Intrusion which is approximately 100 m thick withthe mafic rock dolerite in the upper half and theultramafic rock picrite making up the lower half.
Picrite formed by the gravity-driven accumulation ofolivine crystals during cooling [26].
The intrusion is exposed at the surface and is nota high potential CO2 storage location itself but
understanding of its geology is a natural laboratory
for understanding permeability and reactivity in suchrocks. The intrusion has a significant amount ofcalcite formed by reaction of the mafic rocks with
CO2. Two groups of calcite have been identified as
early high temperature calcites related to magmatism
and later low temperature calcites related tocirculation of water from the surrounding strata.
Isotopic analysis indicates that the later calcite
crystallized at between 51–73oC, which is consistent
with the temperature of water circulating from thesurrounding sedimentary layers. These carbonate
minerals deposited in the vesicles and fractures within
the intrusion and were derived from later, cooler
ﬂuids with signiﬁcant meteoric (near-surface) input.
The Prospect Intrusion was emplaced at theboundary of the highly permeable Hawkesbury
Sandstone and the overlying low permeability
Ashfield Shale. A CO2-rich ﬂuid derived from marine
porewater in the Ashﬁeld Shale may have contributed
to the formation of the later carbonates. The Ashﬁeld
Shale has a low permeability implying that thecomposition of its porewater at the time of
emplacement of the Prospect Intrusion (ca 180 Ma)
would have been similar to the composition it had at
the time of sedimentation [26].
Another intrusion in the Sydney Basin is the
Coonemia Complex which has similar proportions to
the Prospect Intrusion. Isotopic studies of theCoonemia Complex show that the mafic rocks
underwent carbonate alteration at periphery asreactions occurred with the pore water of surrounding
sedimentary rocks [27].

Volcanicalstic Rocks
Volcaniclastic (or volcanoclastic) rocks areformed by a combination of volcanic and sedimentary
processes. The resulting materials can be mafic incomposition and be permeable. The material
produced is often chemically immature and evenfelsic (opposite composition to mafic) materials canreact to form carbonate minerals during alteration andmay therefore have potential as storage sites [29].
Carbonate Sequences
Intuitively, carbonate rocks themselves, forexample limestones, seem least likely to be reactive
to CO2. However, a study of injectivity of water and
CO2 found that the acidity of the solution produced
complex dissolution and re-precipitation processes
that led to a net gain of carbonate mineralization [30].
Seals
As CO2 is dominated by buoyancy within thesaline host waters a seal or caprock must be present
to prevent leakage of the gas. As with oil and gas
reservoirs, the seal is typically a low permeability
fine-grained rock such as a shale (Fig. 3).

Greenstones
Greenstone is the name mainly applied to rocks
which were formerly basalts and weremetamorphosed during continental collisions andother related tectonic events. The greenstone rocks
typically retain their high levels of calcium andmagnesium although some mineral reactions havetypically occurred.
Much of Western Australia has greenstone as thedominant rock type. Also, Victoria, Australia wasthought to have small amounts of greenstone but
recent studies of the deep crust have found that large
zones of greenstone are present [28].

Fig.3 Porosity in mudrocks related to composition.
Upper) terrestrial argillaceous rock (Ashfield Shale)[31]. Lower) Carbonate argillaceous rock [32]14SEE-Mie, Japan, Nov.10-12, 2022

The efficacy of fine-grained rocks in trapping
supercritical CO2 is under intensive laboratory
experimentation and field trials. Fine-grained rocks
have a porosity and permeability that may be affectedby CO2 [30]. This is especially problematic where thefine-grained rock has a significant component ofcarbonates that may be dissolved in the acidic CO2rich conditions [31].

considerable volume of mineralized carbon could beachieved.
Locating high volume reservoirs with anenhanced reactivity behavior such as sandstones withhigh calcium/magnesium content should also be ahigh priority.

DISCUSSION

Discussions on carbon sequestration withcolleagues at RMIT University and CMW
Geosciences are acknowledged.

ACKNOWLEDGMENTS

When considering the future of geological storageof CO2 all parts of the geological cycle should beconsidered (Fig. 4). Sedimentary, igneous andmetamorphic rocks all have potential to havepermeability to transmit and store gas. All rock types
have potential to contain reactive minerals that cancontribute to mineralization of the CO2.
Finding favorable combinations of these features
at appropriate depths and with sufficient volumes forstorage is challenging but literally represents a worldof opportunities.
Geology also provides many natural analogues forCO2 storage and mineralization that can be interpreted
from the natural rock record.

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and Wilcox J., An Overview of the Status andChallenges of CO2 Storage in Minerals andGeological Formations. Frontiers in Climate, Vol.
1, Issue 9, 2019, pp. 1-20.
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16

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

DEVELOPMENT OF A NEW VIBRATION ACTUATOR FOR
INSPECTION OF LARGE IRON STRUCTURES
Hiroyuki Yaguchi
Faculty of Engineering, Tohoku Gakuin University, Japan

ABSTRACTIn general, vibrations generated by machines are generally considered harmful. Research to reduce thesevibrations is still being actively conducted. On the other hand, research has been conducted on the effective useof mechanical vibration. However, there are only a few examples of practical applications, such as ultrasonicmotors, vibration conveyors and vibration power generation. The author has devised a propulsion module using
an original magnetic circuit. By combining this propulsion module with mechanical vibration, an actuator with a
new operating principle was invented. In the present study, four types of vibration actuators with a new operating
principle proposed by the authors are shown. The vibration type actuator can be driven directly without any
additional device. The developed actuators are smaller and lighter than existing robots, and have many
advantages such as propulsive force per own weight, movement efficiency, and scalability. In recent years, theinspection and maintenance of social infrastructure such as large bridges and tanks has become a very important
issue. One of these actuator systems can be equipped with an automatic tapping device to realize the inspectionof large steel complex structures. The four vibration type actuators introduced in this paper are compact,
lightweight, and have good controllability, so they can also be used as driving sources for robots. Moreover,since these actuators have high output per unit volume, they are useful in various industrial fields as new devices.
Keywords: actuator, mechanical vibration, system, electromagnetic force, inspection, complex iron structure
INTRODUCTION
require the adhered device to have a relatively large
weight. Recently, robots that apply drone technology[7, 8] have been developed. However, drone
inspection technology has not advanced because it
requires skill in investigations due to the effects ofstrong winds and thunderstorms.
In general, vibrations generated by machines
are generally considered harmful. Research to
reduce these vibrations is still being actively
conducted. On the other hand, research has been
conducted on the effective use of mechanicalvibration. However, there are only a few examples
of practical applications, such as ultrasonic motors,
vibration conveyors and vibration power generation.
The author has devised a propulsion module using
an original magnetic circuit [9]. By combining this
propulsion module with mechanical vibration, an
actuator with a new operating principle was invented.
As a result of them, the author proposed an actuatorcapable of movement on a magnetic substance by
combining electromagnetic force and mechanicalvibration. [10 - 12]. The results demonstrate that theactuator can move stably in slide-on-ceiling andwall-climbing plane motions.
In this paper, in addition to the actuators shown
above, four vibration actuator systems capable ofmovement by a new principle were introduced.

In recent years, many large structures havebeen constructed in every country due to economic
development. Infrastructures built 50 years ago do
not have well-developed earthquake resistancestandards. Within 20 years, it is expected that morethan 50 % of Japan’s social infrastructure will be
more than 50 years old.
For this reason, they may collapse in the eventof a large-scale disaster. However, due to thelocation of the site, it is very difficult to inspect large
steel structures such as large bridges and storage
tanks. For this reason, various inspection robots havebeen developed to ensure the safety of workers andto reduce costs. In particular, there is a high demandfor inspection at the cable joint of a cable-stayed
bridge having a height of a main tower over 200 m.
Numerous robots have been proposed forstructural inspection. Adhesion methods for wall
surface movement include the following proposed
techniques: mimicking of a living leech [1], roller
structure with a belt and suction cups [2], van der
Waals forces [3], negative pressure produced by apump [4], adhesive materials [5], and a claw gripper[6]. Multiple actuators are always mounted on thedrive unit of these robots. Additionally, thesemethods involve complicated mechanisms and17

SEE-Mie, Japan, Nov.10-12, 2022

Vertical upward speed (mm/s)

1) Vibration actuator combining electromagnetic
force and mechanical vibration.
2) Vibration actuator using the phase difference ofvibration.
3) Rotary type vibration actuator system.
4) Vibration actuator system combining flexible
material and magnetic wheel.
As previously mentioned, the inspection andmaintenance of social infrastructure such as large
bridges and tanks has become a very important issue.
These actuators have been shown to be applicablefor inspection of social infrastructure.

Fig. 1 shows a diagram of the vibration actuatorcapable of movement on a magnetic substance. The
vibration actuator consists of a permanent magnet, atranslational spring, an electromagnet, an acrylic
Cylindical
permanent
magnetN
S

Electromagnet
Iron core

Vibration
component

Springα
Rubberpermanent
magnetTriangular
frame
Attractive
force

Magnetic
substance

Attractiveforce

Fig. 1. Structure of the vibration actuator.
Displacementof mass

Direction ofinertia force
Verticalforce

Frictional
Horizontal
force
force
Attractive force(Permanent magnet)(a) Sliding

60
40
20
0

200
400
Load mass (g)600frame of triangle shape, a permanent magnet
attached to the bottom of the frame and a natural
rubber sheet. The permanent magnet, which is themass of the vibration component is cylindrical
NdFeB and is magnetized in the axial direction. Thismagnet is 15 mm in diameter and 6 mm in height.
The surface magnetic flux density measured using atesla meter was 380 mT. The translational spring
was a stainless steel compression coil type having anouter diameter of 14 mm, a free length of 30 mm,
and a spring constant k of 4,812 N/m. The
electromagnet was inserted in the translational
spring. This electromagnet consists of an iron core
having a diameter of 5 mm and a length of 25 mmwith 1000 turns of 0.2-mm-diameter copper wire.
The permanent magnet attached to the bottom of
the frame has a diameter of 12 mm, and a thicknessof 5 mm. The average surface magnetic flux density
was 383 mT. The natural rubber sheet with athickness of 1 mm was attached to this permanent
magnet for the purpose of increasing the frictional
force. The vibration component was inclined atangle α from the horizontal plane. The vibration
actuator has a height of 42 mm, a width of 15 mm,
and a total mass of 30 g.
The angle α of the vibration component was set
to 60 degrees based on the results obtained in aprevious study [10]. The attractive force generated
by the permanent magnet attached at the support partacts on the vibration actuator when it is placed on amagnetic substance, as shown in Fig. 2(a), (b). The
frictional force between the rubber sheet and themagnetic substance alternates periodically during
one cycle of vibration. Because 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 the

An actuator capable of movement on an ironstructure by combining electromagnetic force andmechanical vibration has been proposed [10 - 12].

NS

〇 : 0.6 W△ : 0.9 W□ : 1.4 W

80

Fig. 3. Relationship between load mass and vertical
upward speed for single actuator.

OUTLINE OF COMBINING
ELECTROMAGNETIC FORCE AND
MECHANICAL VIBRATION

Vibration

100

Displacementof mass
Verticalforce

Frictional
Horizontal
force
force
Attractive force(Permanent magnet)(b) No sliding

Fig. 2. Principle of locomotion.

18

SEE-Mie, Japan, Nov.10-12, 2022

rubber sheet in the support [10-12].
In the experiment, an iron rail with a width of 50mm, a thickness of 50 m, and a length of 1,000 mm
was used as the target magnetic structure. The
vibration component was driven at a resonancefrequency of 106 Hz using a signal generator and an
amplifier. The attractive force F between theactuator unit and the iron rail was 8 N. The
coefficient of friction between the iron rail and thenatural rubber as measured in the experiment was
0.67.
Fig. 3 shows the relationship between the load
mass and the vertical upward speed of the actuatorwhen the input power was 0.6, 0.9, and 1.4 W. In
this figure, the actuator can move upward at a speedof 24.1 mm/s even with a load mass of 650 g.
This vibration actuator has a very simple
structure and can generate propulsion about 21 times
its own weight. However, the movement direction islimited to only one direction movement from theprinciple of operation.

IB

IA

y

x
Movingdirection
Fricnalforce Ff
Attractive force Fs(Sub)
Attractive force FIB

Attractive
force Fm
(Main)(a) Sliding
IB

IA

y
x
Movingdirection

PRINCIPLE OF OPERATION FOR
VIBRATION ACTUATOR USING PHASE
DIFFERNCE

Fricnalforce Ff

Attractive force Fs(Sub)
Attractive force FIB

Attractive
force Fm
(Main)(b) No sliding
To solve the problem described above, a new
Fig. 5. Principle of reversible motion(Out-of-phase).

IB

IA

y
x

vibration actuator that extends the principle ofoperation invented [13] by the authors was proposed.
New principle of operation for the actuator capableof reciprocating movement by controlling the phaseof two vibration components has been considered.
As shown in Fig. 4, when two vibration components
A and B are arranged orthogonally, the movement
direction of the new vibration actuator can bechanged by controlling the phase of the vibration ineach component. The cases of displacement in thehorizontal and vertical directions are referred to as
the vibration components A and B, respectively. The
displacement coordinates x and y of each of thevibration components A and B are determined asshown in Fig. 4.
When the vibration actuator is set on a magnetic
substance, the frame of this actuator is held by themain and sub rubber permanent magnets with theattractive force of Fm and Fs. Due to this reaction, thevibration component can be displaced. It was
assumed that the vibration components A and B
were vibrating at the angular frequency ω. The
period of the vibration component in this case is τ,Fricnalforce Ff

Movingdirection

Attractive force Fs(Sub)
Attractive force FIB

Attractive
force Fm
(Main)(a) Sliding
IA

IB

y

x
Movingdirection
Fricnalforce Ff
Attractive force Fs(Sub)
Attractive force FIB

Attractive
force Fm
(Main)(b) No sliding
Fig. 4. Principle of reversible motion (In-phase).

19

SEE-Mie, Japan, Nov.10-12, 2022

Vertical upward speed (mm/s)

respectively.
First, as shown in the Fig. 4(a), consider a casewhere the phase difference between the vibration
components A and B is 0 degree (in-phase).
Focusing on one cycle (τ = 2π/ω) in the vibration
component B, the holding force F and the frictional
force Ff of the support part for the actuator change
periodically as shown in Equation (1) due to theinertial force IB by the permanent magnet of thevibration component B.
F = Fm + Fs - IB sin ω τ ( 0 <τ< π/ω) , Ff = μ F-------------------- (1)where, t is time, and μ is the friction coefficient.
When the component A is displaced in the +x
direction in the same phase while the vibration
component B is displaced in the +y direction, thevibration actuator easily slides in the +x direction.
As shown in equation (2), when the inertia force IAof the permanent magnet in the vibration component
A exceeds the friction force Ff, the actuator canmove in the +x direction.
(2)
IA > Ff
On the other hand, as shown in Fig. 4(b), whenthe vibration component B is displaced in the -ydirection, the holding force F and the frictional force
Ff increase as shown in Equation (3) due to theinertial force IB by the permanent magnet.

60
50
40

〇 : 50 mA△ : 70 mA□ : 90 mA

30String20

Load mass

10
0

100
Load mass (g)200

Vertical upward speed (mm/s)

Fig. 6. Relationship between load mass and vertical
upward speed (Direction A).
60
50
40

〇 : 50 mA△ : 70 mA□ : 90 mA

30String20

Load mass

10
0

50
100
Load mass (g)150

Fig. 7. Relationship between load mass and vertical
upward speed (Direction B).

F = Fm + Fs + IB sin ωτ (π/ω <τ< 2π/ω) , Ff = μ F-------------------- (3)Even if the component A is displaced in the -ydirection in opposite phase, the inertia force I A
cannot exceed the friction force Ff. Therefore, theactuator cannot move as shown in Equation (4).
I A < Ff
(4)
The actuator can move in one direction bychanging the frictional force of the rubber permanent
magnet attached to the frame.
Fig. 5 shows a case where the phase difference
between the vibration components A and B is 180
degrees (opposite phase). The actuator can move inthe -x direction according to the principle ofmovement by the frictional force and the inertial
force described above. Accordingly, the present
actuator can change the movement direction
between forward and backward by controlling thephase of the two vibration components. For thevibration component, a smaller spring andpermanent magnet were used than in Chapter 1, andthe propulsion characteristics were measured.
The 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 6 and 7 show the

relationship between the load mass mounted on theactuator and the vertical upward speed when theactuator moves forward and backward direction. The
input current to the electromagnet in each vibration
component was changed from 50 mA to 110 mA inthree types. As shown in the figure, the maximum
pulling force of the actuator in the case of forward
movement is 1.9 N, while that in the case of
backward movement is only 1.3 N. As describedabove, this is because the attractive force of the sub
rubber permanent magnet has an effect. The
presence of the attractive force asymmetric withrespect to the vibration component B degrades the
movement characteristics of the actuator. However,the sub rubber permanent magnet is needed to drive
the actuator straight. However, this actuator cannot
move on steel structures with small rust andunevenness.
OUTLINE OF WHEEL TYPE ACTUATOR
In order to solve the above problems, a rotary
movement type actuator has been developed [14, 15].

20

SEE-Mie, Japan, Nov.10-12, 2022

( a ) Plan view
Acrylic
shaft

5 mm

Rod
Rod
C
B
40 mm

(c) E-shaped acrylic frame

Vibration
component B
S

RubbermagnetAcrylic material

Iron wheel

Iron structure

Iron structure( b ) Front view( d ) Side view

E-shaped
acrylic
frame

Fig. 8. Structure of the magnetic wheel actuator.
Vibration
component (Free)

Iron
wheel
(Fixed)(a) Action

Vibration component(Movement prevention)
Frame(Fixed)Vibration component(Movement prevention)

Iron disk(Free)

Iron disk(Free)(b) Reaction

80
60
40
20

0

Vibration component B

N

NS

Vibration
component A

Rod A

Vertical upward speed (mm/s)

Vibration Electromagnet Vibration
component A (Cross section) component B

18 mm

5 mm

40 mm

Rod D

N
S

N
S

E-shaped
acrylic
frame

5 mm

40 mm
Acrylicshaft

E-shaped
acrylic
frame

Iron rail(c) Linear movement

Fig. 9. Principle of locomotion.
By extending the principle of locomotion, as shownin Fig. 8, a new type of a magnetic wheel actuator issuggested. The magnetic wheel actuator consistsof two vibration components (labeled A and B),
two E-shaped acrylic frames with four rods (labeled
A, B, C, and D), an electromagnet, an acrylic shaft,and two iron disks. The vibration component was asmaller spring and permanent magnet than in
Chapter 1. The two iron disks are rotated using thereaction force generated by the vibration component
as described below. Since the frictional force
between the iron disk and the rubber magnet can be
maintained constant, the frictional force during therotational movement of the wheel actuator on the
structure does not change. The dimensions of theE-shaped frame in this figure correspond to those of
an iron disk of 40 mm in diameter. The thickness of
this E-shaped frame is 3 mm.
The principle of operation of this rotary actuator
will be discussed. As shown in Fig. 9, when thevibration component is placed on an iron structure,
the component can vibrate due to the attractive force

Load mass〇 : 0.2 A△ : 0.16 A□ : 0.12 A

20

40
60
Load mass (g)80Fig. 10. Relationship between load mass andvertical upward speed.
of the rubber magnet. The vibration component
moves as a result of the vertical and horizontal
components of the forces generated by the vibration
component attached at an angle of 60°. Whenthe vibration component is placed on a fixed iron
disk, as shown in Fig. 9(a), the component moves inthe direction in which the vibration component istilted. When a supported state is imposed in order toprevent the motion of the vibration component, theiron disk rotates as a result of the reaction force ofthe component, as shown in Fig. 9(b). By inserting
the vibration component into the E-shaped acrylic
frame in such a way that the component is attracted
to the iron disk, it is possible to rotate the disk while
preventing the movement of the vibration
component. When the two vibration components (Aand B) are driven at the same frequency and the same
amplitude, the wheel actuator can move linearly.
Fig. 10 shows the relationship between the load
mass and the vertical upward speed for the input
power of 0.37 W for each vibration component.
Here, the DC input current into the electromagnet ofthe magnetic wheel was changed to 0.12 A, 0.16 A,
and 0.2 A. As shown in the figure, the maximum
pulling force of this magnetic wheel actuator is
0.8 N. However, this rotary actuator is not capableof traveling on a stepped surface. Also, an inspection
device cannot be mounted.
VIBRATION ACTUATOR SYSTEM CAPABLE
OF MOVEMENT OVER A STEP
Finally, a new vibration actuator system wasdeveloped [16] capable of movement with theinspection device on a complex steel structure withsteps of 25 mm in height. This new vibration
actuator system has a flexible frame capable ofdeformation over uneven parts of the structuresurface. Silicone rubber was used for the flexible

21

SEE-Mie, Japan, Nov.10-12, 2022

330 mmSilicone rubber A

Actuator A

Actuator B O

140 mm

165 mmA-partpart

85 mm
Silicone rubber E

Silicone rubber C

X

20 mm

L = 685 mm
85 mm

Actuator D

Actuator C

140 mm

165 mm(a) Plan view
Actuator A

Cylindical
permanent
magnetActuator C

Actuator B
Centermass

Siliconerubber B

Three-layer
magnetic wheel

Actuator D

Siliconerubber D

C = 5 mmThree-layer
magnetic wheel

Iron structure
145 mm

120 mm

145 mm

145 mm

120 mm(b) Front view
20 mm
8 mm

Acrylic
disk
Shaft

6 mm

5 mm

Silicone rubber 6 mm

Bearing

R = 30 mm

Acrylic
material
Ring-type
Permanent magnet(c) Details of Area A in (a)(d) Photograph of actuator system

Fig. 11. Vibration actuator system capable of movement over a step.
frame, and the attractive force was generated bymultiple permanent magnets.
Fig. 11 shows a vibration actuator system inwhich four actuators (A, B, C, D) capable ofmovement are connected by a flexible silicone
rubber frame. The silicone rubber is divided into fivesegments. The lengths of silicone rubber segments A,
B, C, D, and E and are L 1 , L 2 , L3 , L4 , and L 5 ,respectively. A magnetic wheel is attached to
opposite ends of silicone rubber segments A and E.
By attaching a magnetic wheel to the tip of theactuator system, it is possible to exert an appropriate
attractive force on the iron structure and provide a
guide for movement over a step. The magnetic
wheel has a three-layer structure in which a ringtype permanent magnet is sandwiched between two
acrylic disks having outer diameters of 30 mm and a
thickness of 2 mm. In addition, auxiliary permanent
magnets are placed at distances x1, x2, x3, x4, and x5

from the origin O to adhere to an iron structureduring movement over a stepped surface.
The longitudinal stiffness of the silicone rubber
connecting the four actuators has a significant effecton the traction and movement over a step.
Furthermore, the attractive force exerted by themagnetic wheel also affects the movement over the
step. Because there are countless combinations ofparameter for designing the actuator system, thefollowing four criteria were introduced:
1) The total length of the actuator system isapproximately 700 mm to allow portability.
2) Considering long cable traction over 200 m, thetraction force for the actuator system is morethan 15 N (load mass of 1,500 g).
3) In the future, an automatic tapping device mass
weighing 260 g can be installed in the center of
the actuator system.

22

SEE-Mie, Japan, Nov.10-12, 2022

Vertical upward speed (mm/s)

4) The height of the step over which the actuatorsystem can move does not exceed 25 mm in thevertical plane.
Preliminary experiments were conducted tosatisfy the above design criteria. By trial and error,
the dimensions of the silicone rubber material were
determined. All silicone rubber segments A, B, C, D,
and E had a thickness of 5 mm. In addition, thewidth B and length L of the silicone rubber were set
to B = 20 mm and L1 = 120 mm, L2 = 140 mm, L3 =140 mm, L4 = 140 mm, and L4 = 120 mm. As theauxiliary attractive force, cylindrical permanent
magnets were arranged at x1 = 0 mm, x2 = 165 mm,
x3 = 305 mm, x4 = -165 mm and x5 = -305 mm insegments A, B, C, D, and E. Cylindrical permanent
magnets with an outer diameter of 15 mm and a
thickness of 6 mm were attached at these positions.
The attractive force on the iron rail for this magnet
was 1.8 N. The vibration components described in
Chapter 1 were used.
The ring-shaped permanent magnet for themagnetic wheels had an outer diameter of 16.5 mm,
an inner diameter of 8.5 mm, a thickness of 4 mm,
and a magnetic flux density of 356 mT. A threelayered wheel with a shaft with an outer diameter of
1 mm in the center was attached to the silicone
rubber via bearings. The attractive force for themagnetic wheel was 0.9 N.
The overall length of the actuator system was
715 mm, and the distance between the magnetic
wheels was L = 685 mm. The width, height, andtotal mass of the actuator system were 20 mm, 42mm, and 250 g, respectively. In this system, theattractive force F for each vibration actuator was set

40○:0g△ : 200 g□ : 300 g

30
20
10

0

100

200
300
400
Load mass (g)500Fig. 13. Relationship between load mass and vertical
upward speed for single infinite step.

L mm

to 11 N. Fig. 11(d) shows photographs of thevibration actuator system.
The locomotion characteristics of the vibration
actuator system for two step patterns were measured.
First, as shown in Fig. 12(a), an iron structure having
a single step with an infinite length was examined.
In these experiments, the measurement distance was
set to 750 mm. The power input to each actuator
was 1 W.
Fig. 13 shows the relationship between the load
mass of the actuator system and the vertical upward
speed for a single step with a height of 25 mm byvarying for central masses of 0, 200, 300, 400, and
500 g. It was found that even with a central mass of
300 g, a traction force of 5 N (load mass of
500 g) was generated. However, the speed was only
6 mm/s.
Next, the speed of the actuator system for thetwo-step case shown in Fig. 12(b) was measured.
Even for a central mass of 300 g, the system could
move over the vertical surface while generating a
traction force of 5 N.
CONCLUSIONS

Centermass(Virtual
automatic
tappingdevice)In the present study, four types of vibration
actuators with a new operating principle proposed by
the authors are shown and their movement
characteristics were introduced. Each actuator has its
own characteristics and can be used according to thecase of application. All vibration actuators can be
driven directly without any additional device. Thesedeveloped actuators are smaller and lighter thanexisting robots, and have many advantages such as
propulsive force per own weight, movement
efficiency, and scalability.
In particular, in the vibration actuator system
combining flexible material and magnetic wheel, theCentermass(Virtual
automatic
tappingdevice)Load mass

Load mass(a) Single infinite step(b) Two steps

Fig. 12. Two step patterns for vertical iron structure.

23

SEE-Mie, Japan, Nov.10-12, 2022

Khan, S. Sharmin and N. J. Lisa, “ ALW drone:
A new design and efficient approach”, in Proc.,
IEEE 1 9 th Internatio nal Co nference o nComputer and Information Technology (ICCIT),
DOI:10.1109/ICCITECHN.2016.7860244 ,pp. 474-479 (2017).
[8] M.Morita, H. Kinjo, S. Sato, T. Sulyyon and T.
Anezaki, “ Autonomous flight drone for
infrastructure (transmission line) inspection”, in
Proc., IEEE International Conference onIntelligent Informatics and Biomedical Sciences(ICIIBMS),
pp.
198-201,
DOI:
10.1109/ICIIBMS.2017.8279692 (2017).
[9] Yaguchi H. and Izumikawa T., ” Wireless InPiping Actuator Capable of High -Speed
Locomotion by a New Motion Principle,
IEEE/ASME Transactions on Mechatronics,
Vol. 18, No. 4, pp. 1367 - 1376 (2013).
[10] Yaguchi H. and Sakuma S., ” A Novel
Magnetic Actuator Capable of Free Movement
on a Magnetic Substance”, IEEE Transactions
on Magnetics, Vol. 51, No. 11,
DOI:10.1109/TMAG.2015.2443061 (2015).
[11] Yaguchi H. and Sakuma S., ” Characteristic
Improvement of a Magnetic Actuator Capableof Movement on a Magnetic Substance”, IEEE
Transactions on Magnetics, Vol. 52, No. 7,
DOI: 10.1109/TMAG.2016.2533433 (2016).
[12] Yaguchi H., and Sakuma S., Vibration
Actuator Capable of Movement on Magnetic
Substance Based on New Motion Principle,
Journal of Vibroengineering, Vol. 19, Issue 3,
pp. 1494 -1508 (2017).
[13] Yaguchi H., A new type of electromagneticallypropelled vibration actuator for appearance
inspection of iron structure, International
Journal of GEOMATE, Vol. 20, No. 77,
pp. 69 - 76 (2021).
[14] Yaguchi H., Kimura I., and Sakuma S., A
Novel Actuator System Combining MechanicalVibration and Magnetic Wheels Capable ofRotational Motion Using Shape Memory Coils,
Actuator, Vol. 8, No. 1, pp. 1 - 12 (2019).
[15] Yaguchi H., and Itoh Y., Vibration actuatorsystem with small-scale size capable of visualinspection of large complex iron structures,
Applied Sciences, Vol. 11, No. 16, pp. 1 - 16
(2021).
[16] Yaguchi H., and Itoh Y., Vibration actuatorsystem for internal inspection of large
complex iron structures, International Journalof GEOMATE, Vol. 22, No. 89,
pp. 9 - 15 (2022).

experimental result of the actual prototype
demonstrates that the maximum efficiency of thevibration actuator was 25.2 %, and the maximum
pulling power was 6.5 N. Therefore, this actuatorsystem has the potential for inspection of largesocial infrastructures. In recent years, the inspection
and maintenance of social infrastructure such aslarge bridges and tanks has become a very important
issue. This actuator system can be equipped with anautomatic tapping device, which might allow it toinspect large iron complex structures.
However, this actuator system cannot switch its
direction of movement. To solve this problem, it isnecessary to change the actuator to a structure thatuses a vibration phase difference, as previously
proposed by the author. It is necessary to put the
research results to practical use and contribute tosociety.
REFERENCES[1] Kanada A., Giardina F., HowisonT.,Mashimo T.
and Iida F.,“Reachability Improvement of a
Climbing Robot based on Large Deformations
induced by Tri-Tube Soft Actuators, Soft
Robotics Vol. 6, No. 4(2019)[2] Ge D., Ren C., Ma S. and Matsuno T., Guide
Rail Design for a Passive Suction Cup based
Wall-Climbing Robot, in Proc. 2016 IEEE/RSJ
International Conference on Intelligent Robots
and Systems (IROS2016), pp. 5776-5781, 2016.
[3] Kim S., M. Spenko, S. Trujillo, B. Heyneman,
V. Mattoli and M. R. Cutkosky, ”Whole bodyadhesion hierarchical directional and distributed
control of adhesive forces for a climbing robot”,
IEEE International Conference on Robotics andAutomation, (2007).
[4] Subramanyam A., Mallikarjuna Y., Suneel S.and
Bhargava K. L., ” Design and Development of a
Climbing Robot for Several Applications”,
International Journal of Advanced Computer
Technology, Vol. 3, No. 3, pp. 15-23 (2011).
[5] Unver O. and Sitti M., ” Tankbot: A Miniature,
Peeling Based Climber on Rough and SmoothSurfaces”, in Proc., IEEE International
Conference on Robotics and Automation, pp.
2282-2287 (2009).
[6] Provancher W., Ensen-Segal S. and Fehlberg
M., ” ROCR: An Energy-Efficient Dynamic
Wall-Climbing Robot”, IEEE Transaction on
Mechatronics, Vol. 16, No. 5, pp. 897-906(2011).
[7] N. Mahamud, G. Muhammad Shahriar, H. U.

24

Technical Papers

Structures

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

TORSIONAL BEHAVIOR OF SPANDREL REINFORCED CONCRETE
BEAMS
Noor Ayaad1 and Nazar Oukaili2
Department of Civil Engineering Department, University of Baghdad, Baghdad 10070, Iraq.
2
Department of Civil Engineering Department, University of Baghdad, Baghdad 10070, Iraq.
1

ABSTRACT
Spandrel beams are typically subjected to a series of vertical eccentric loadings when used in parking
structures or the abutments of bridges. Embedded Through-Section (ETS) method is a recently developed method
to increase the shear capacity of reinforced concrete using steel reinforcing rods. This study presents anexperimental program conducted on spandrel beam systems to gain a deeper understanding considering different
parameters including the aspect ratio of the section (i.e., height/thickness) and the strengthening type (i.e., theeffectiveness of the ETS method). This study focuses on the test results including the ultimate shear-torsion
capacity, cracking load, load-twisting, and load-deflection responses. The outcomes had shown the superior
performance of the ETS method, increase in torsion capacity was 45% compared to the control spandrel beams(i.e., unstrengthened). These results also indicate that using embedded steel rods showed improvement in
restricting the deflections and rotation of spandrel beams due to increasing spandrel stiffness. The skewed failure
plane for the strengthened spandrel beams was slowly reaching the upper surface of the web which was attributed
to the prop effect provided by embedded steel rods.
Keywords: L-Shaped Spandrel Beam, Torsional Equilibrium, Shear Effects, Rotation, ETS Method

INTRODUCTION
The L-shaped spandrel reinforced concretebeams are structural members that are subjected to aseries of discrete loads eccentric to the shear centerof the beam.These loads cause vertical displacement,
significant lateral displacement, and rotation. The
maximum internal torsion and shear effects occur inthe end regions of the specimen. In many cases, acontinuous ledge runs along the bottom edge on one
side of the beam, resulting in what is known as an Lshaped spandrel beam. The spandrel beams are
subjected to high shear, torsion, and bending
moments consequently resulting in deformations in
the vertical plane and out plane accompanied byflexural and shear cracks [1,2]. These loads withrespect to the unsymmetrical L-shaped spandrel
cross-section cause vertical in addition to significant
lateral displacements and rotation. The ends of thesespandrel beams are also connected to the columns toprevent out-of-plane rotation about the longitudinalaxis. In addition, the deck sections are often
connected to the spandrel web inner face at discrete
locations, providing lateral restraint along the span.
The maximum torsional and shear effects occur inthe end regions. Point loads from the deck sections
locate along the ledge, column reactions appear ateach end, and lateral restrain forces from the
spandrel deck connection distribute along the innerface of the web [3,4].
The required reinforcement for spandrel
members, as required by international codes [5,6] isgenerally designed according to a general procedure
originally proposed by Zia and McGee [7].
Though several studies on the spandrel
reinforced concrete beams have been performed inpast decades, studies on spandrel beams
strengthening were loaded under two stages are
exceptional. In terms of the influence of the ETS
method on the torsional behavior of spandrel beams,
no studies have been conducted yet with many
unanswered questions. Therefore, the objective of
this research study is to investigate the effect of theefficiency of embedded steel rods installed throughthe web of spandrel beams to improve the torsional
behavior of L-shaped reinforced concrete spandrel
beams loaded in two stages under static loads.
EXPERIMENTAL PROGRAM
Four simply supported L-shaped RC beams were
cast and tested under two stages of loadings. The
ledge mid-span was loaded under an eccentric onepoint load to study various limit state behaviors. Twospandrel beams were tested as control specimens
without strengthening, while the others wereretrofitted with the embedded through-section (ETS)
method using steel rods.
Test Matrix and Reinforcement Details
In this experimental study, two aspect ratios were
investigated 4.3 and 3. The aspect ratio of the27

SEE-Mie, Japan, Nov.10-12, 2022

spandrel beam is defined as the ratio of the web
height to web thickness (h/t). All spandrel beams
have a span of 1500 mm, with a ledge cross-sectionof (250 x 200) mm. Whereas the ledge was cut backfor 150 mm on either end of the spandrel beam tosimulate an idealistic field conditions detail thatallows the typical web to be connected to supportingcolumns. The geometry of the slender and compact
spandrel beams had web sections of (650 x 150) and(450 x 150) mm, respectively. Each side of the web
was provided with two holes over the web’s crosssectional width to achieve connection with thevertical rigid frame assembly with high-strength
threaded rods, as idealistic field conditions. Table 1
summarizes the details of the tested spandrel beams.

Fig. 1 Geometry and dimensions
spandrels. (all dimensions are in mm)fortestedTable 1 Properties of spandrel beams
All spandrel beams in his study were fabricatedaccording to international codes [5,6]. Conventional
deformed steel reinforcement was used to resist the
Cylinderconcretestrength,(MPa)
SB1-US-S
4.3
Unstrengthen
43.20
SB1-ES-S
4.3
Strengthened
44.66
SB2-US-S
3.0
Unstrengthen
45.00
SB2-ES-S
3.0
Strengthened
45.47
bending, shear, and torsion combination that was
induced in each spandrel. According to theassumptions of the mentioned codes the outerbranches of closed vertical stirrups are resisting
torsion stress and acting as a hanger for the ledge.
Thus, all spandrel beams were designed to resist
shear-torsion distress, and twist loadings. In thispresent study, to assure end-region failures,
additional flexural and ledge reinforcement wasprovided. Also, the ledge punching shear (localized
failures) must be considered and prevented totransfer the load from the ledge to the spandrel web
by using extra reinforcement. All spandrel beams
had one configuration of shear and torsion
reinforcement which was available in the frontal andback web faces. Figure 1 shows the concretegeometry and dimensions while Fig. 2 shows thereinforcement configurations used for test spandrel
beams.
Spandrels
ID

Aspectratio

Strengthening
statusFig. 2 Reinforcement details for tested spandrels.
(all dimensions are in mm)
Three standard cylinders of (150 × 300) mm were
tested in conformity with (ASTM C39-17) and threestandard cubes of size (150 mm × 150 mm × 150)
mm were tested to determine the compressive
strength of concrete. Table 2 summarizes thecompressive strength of concrete. Three samples ofeach steel bar with 0.5 m length with a diameter of ∅10 mm, ∅12, and ∅ 16 mm were tested. The ASTM
A615 was used to evaluate the yield tensile strength

Material Properties
The properties of hardened concrete were based on
the average strength of three samples for each spandrel
beam. Concrete standard samples were prepared andtested to determine the compressive strength of
concrete.

28

SEE-Mie, Japan, Nov.10-12, 2022

and ultimate tensile strength of steel bars. The resultsof the reinforcing steel bar are listed in Table 3.

All instrumentation was linked to a computerized(NI) data acquisition system to capture data
automatically. Figure 3 shows a profile of the test
setup while the plate of the completed test setups isshown in Fig. 4.

Table 2 Compressive strength of concrete
Properties
Spandrels
ID

𝑓𝑐𝑢 ,
(MPa)

𝑓′𝑐 **,
(MPa)

𝑓′𝑐
𝑓𝑐𝑢

SB1-US-S

53.60

43.20

0.80

SB2-US-S

57.00

45.00

0.79

*

SB1-ES-S
57.13
44.66
SB2-ES-S
54.50
45.47
*Compressive strength of the cube**Compressive strength of the cylinder

Loading Frame

0.78
0.83

Vertical
Rigid
Assembly

Table 3 Mechanical properties of steel reinforcement
Nominaldiameter,
(mm)

𝑓𝑦 ,
(MPa)

𝑓𝑢 ,
(MPa)

Elongation,
(%)

Ø 10

575.00670.67

9.34

Ø 12
Ø 16

605.05612.67698.00707.00

9.42
11.18

Load Cells

LVDT Sensors

Fig. 3

Profile of the test setup.

Fig. 4

Typical test setup and Instrumentation.

Setup and Instrumentation
The same loading rig was used to test both
slender and compact spandrel beams which applieda single point load at the mid-span section of theledge at a distance of 150 mm from the frontal faceof the web. To record the applied load at the
spandrel beam, a 1000-kN capacity of load cell wasused. All spandrel beams were tested in a simply
supported scheme at the ends over an effective spanof 1300 mm and were rested on thick steel plateswith dimensions of (100 x 150) mm, centeredrelative to the spandrel web, through which thevertical components of reactions were transferred.
Two load cells were used with a capacity of 500-kN
to determine the vertical component of the reaction,
one for each end located at the center of the web.
Two main features of these load cells, are mainly,
monitoring and recording the reaction value at thesite of influence. All spandrel beams were supported
laterally by restraining the web at both ends. The
vertical rigid assembly was used to restrain the
movement of the test specimen and to provide
torsional restraint at the web ends. To capture thelateral forces at the web ends, other load cells wereconnected at the top of the web’s frontal face and thebottom of the web’s back face. Furthermore, linear
variable displacement transducers (LVDT) wereused for recording vertical deflections and lateraldisplacements at various locations. The electricalresistance pre-wired strain gauges were used tomeasure strains in concrete and steel reinforcement.

Loading
Sequence
Implementation

andStrengthening

The control specimen (unstrengthened) was
exposed to two stages of monotonic static loading. In
stage 1, the load was applied up to the level
corresponding to 60% of yielding stress in thevertical steel stirrup at the web mid-span section
followed by an unloading process up to zero level. In
stage 2, the test specimen was reloaded up to thefailure level in multi-steps.
At every loading step, the corresponding linear
and rotational displacement were recorded and thedeveloped cracks were traced. The testing procedureof the strengthened spandrel beams was the same as
for the control specimen during stages 1 and 2 except
that, before starting the reloading stage, the spandrel
beam was strengthened using (ETS) method by steel

29

SEE-Mie, Japan, Nov.10-12, 2022

reinforcing rods which were installed through thecenterline of the web’s cross-sectional width. One
strain gauge was used to measure steel rod strain(SG-2). After completing the steel rod installation,

Fig. 5the spandrel beam was reloaded in steps to failure.
Figure 5 illustrates the loading sequence for a typicaltest. Fig. 6 shows the preparation of the steel rods.

Typical loading sequence.
At stage (1) of loading, all the tested spandrel
beams showed cracks in various directions. Generally,light deviant cracks have occurred on the web’s frontal
face (inner) of the spandrel beam while minimal
flexural cracking appeared on the web’s back (outer)face near the mid-span section. Several of these cracks
were closed during unloading. Also, at stage (2) ofloading, the cracking propagation was investigatedwhen the load reached to failure level. The cracking
pattern for all tested spandrel beams was similar. This
cracking pattern appeared when a spandrel beam was
exposed to the combination of shear and torsion
stresses. In the web’s frontal face of the spandrel beam,
it is substantial to detect that the shear and torsional
stresses act in the same direction which led to creatinga high conventional diagonal tension in the end regionsof the web. Diagonal cracks on this face were initiatedfrom the outer corners of the ledge and propagatedupward with an initial angle of nearly 45 degrees.
Moving away from the web ends to the mid-spansection, the crack’s angle progressively dropped andthe crack changed its direction that became parallel tothe intersection line between the web and the ledge.
Also, there was inclined severe cracking at 45 degrees
on the web’s frontal face adjacent to the support,
resulting from the out-of-plane bending induced by theend lateral couple force needed to prevent the spandrel
from turning toward the applied load in response to
eccentric vertical load.
In the web’s back face (outer) of the spandrel
beam, the diagonal tension was reduced and could
even be reversed to that on the frontal face dependingon the values of the shear and torsional stresses.
Spread some vertical flexural cracks during loading
upward from the soffit of the ledge around the regionof the mid-span section. These cracks were wrapped
under the soffit of the web also linked to the flexural
cracks on the web’s back face. Between the ends of the
spandrel beam and the mid-span section, many tilted
cracks were noticed, due to the shear effect in theseFig. 6 Preparation of the steel reinforcing rods.
EXPERIMENTAL RESULTS ANDDISCUSSION
Cracking Pattern and Failure Modes

30

SEE-Mie, Japan, Nov.10-12, 2022

regions. Increasing the applied load to higher levels,
the symptoms of severe spiral cracking would become
prominent in all spandrel beams' end regions of the
web’s faces accompanied by face-shell concrete
spalling as their surfaces warp and deform under theeffects of torsion stress, see Fig. 7. All four spandrel
beams elucidated the same failure mode including
moderate diagonal cracking on the web’s frontal faceand moderate flexural cracking on the web’s back faceat the first stage. While, at the failure stage, thespandrel’s failure modes began to vary depending on
the availability of the ETS steel rods.
As was expected, localized failures did not occur
during the testing of all spandrel beams. The control
spandrels failed along a skew-diagonal crack growing
upward from the bottom corners of the web andshowed inclusive diagonal cracking on their innerfaces along with inclusive flexural cracking on theirouter faces with virtually identical modes at end
regions. The skew-crack plane intersected the bottomedge of control spandrel beams and intersected the topedge of that spandrels. At the failure stage, theobserved failure mechanism for the strengthened
spandrel beams (SB1-ES-S and SB2-ES-S) the skewed
failure plane slowly reached the top surface of the webthat reflected the torsion effect. The crack width
depends on the implementation of the strengthening
system. It was observed that the strengthened spandrel
beams (SB1-ES-S) and (SB2-ES-S) had minimal crack
width across the top edge of the web in comparison to
the control spandrel beams (SB1-US-S) and (SB2-USS), even though the strengthened spandrels were
subjected to higher applied loading, see Fig. 7

mid-span section is plotted in Fig. 9. The values ofrotation degrees for all tested spandrel beams areshown in a bar chart in Fig. 10. In comparison tocontrol spandrel beams, the strengthened spandrel
beams showed stiffer behavior attributed to theimplementation of embedded steel rods which
achieved an effective restrainer to the increased
deflection. Thus, the maximum rotation values ofspandrel beams (SB1-US-S) and (SB2-US-S) were
exceeding the rotation values of strengthened
spandrels (SB1-ES-S) and (SB2-ES-S), see Table 4.
ETS steel rods that were inserted inside the web
section led to reducing the angle of rotation in thestrengthened spandrels due to the increase of therestraining effect induced by the embedded steel rods
installed in the structural member. This is due to thepropped concrete core of the specimen where the rods
were embedded, although the strengthened spandrels
afforded a higher load.
Strain of Reinforcing Steel and ETS steel rods
The strain gauges were glued on transverse steel
reinforcement and embedded steel rods to monitor
the strain readings and elucidate the load-strain
response during loading for each specimen. A strain
gauge (SG-1) was positioned on the vertical leg ofthe transverse reinforcement of the web, whilst thestrain gauge (SG-2) was placed on the embedded
steel rods, see Fig. 5. As mentioned before, the tested
spandrel beams were first exposed to incremental
concentrated load up to the load that attained a strain
in the web’s vertical steel stirrup at the mid-spansection of 1725 × 10−6 (i.e., a strain corresponding
to 60% 𝑓𝑦 of the bar of 10 mm diameter). At thisstage, all spandrel beams showed an identical linear
elastic behavior with various slopes, see Fig. 11.
Whereas, after cracking and increasing torsionalload, the slope of these curves incrementally dropped
with different slope changes depending on the level ofdeterioration that affected the tested specimen (i.e., theaspect ratio and the availability of the strengthening
system). The spandrel beams were unloaded in one
step. Otherwise, at the unloading stage, the strain (SG1) is incrementally decreased where the residual value
ranged between (503 - 630) × 10−6 (i.e., 30% of theyielding strain). Thus, all specimens passed over theyielding strain of 2875 × 10−6 at the failure stage. It
is important to observe that the strain value inembedded steel rods (SG-2) achieved (1066 × 10−6 )at failure load. The strain in the transverse steel was
significantly greater in specimens with no embeddedrod. The load-strain relationships in embedded steelrods were illustrated in Fig. 12.

Load-Deflection Response and Degrees of Rotation
The vertical deflection and the horizontal
displacement were measured at the mid-span section.
At loading stage (1), the deformational behavior of all
spandrel beams was almost correspondent. It wasobserved that during loading, the spandrel beam
rotated toward the applied load achieving at mid-spansection a bottom surface outward movement (i.e.,away from the applied load) and a top surface inward
movement (i.e., toward the applied load), more so thebottom surface moved more than the top surface. The
contribution of steel rods gave the superior torsionalload with the presence of transverse steel
reinforcement in the strengthened spandrel beams
when using the ETS method. Further, the embedded
steel rods method has proven to be an effective way to
improve the shear and torsion capacities of spandrel
beams even in the presence of a limited amount ofinternal transverse steel reinforcement of the web.
Figure 8 shows the load-vertical mid-span deflection
curve, whereas the profile of deflected shape at the31

SEE-Mie, Japan, Nov.10-12, 2022

Bottom Fiber

Left

Right

Fig. 7 Cracking pattern and failure mechanism of spandrel beams.

Fig. 7 Continued.

32

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 8 Load- vertical deflection curve at mid-span section for tested spandrel beams.
Total
appliedload atmid-span,(kN)

Increase of
appliedload,(%)

SB1-US-S

190.0

SB1-ES-S

SpecimenID

Maximum
vertical
reactions,(kN)

Maximum lateralreactions,(kN)

Mid-spanverticaldeflection,(mm)

Rotation,(deg.)

Left

Right

Bottom
left

Top
right

Control

94.5

93.8

34.2

33.4

28.90

1.50o

275.5

45

135.0

131.2

47.0

42.5

26.70

1.35o

SB2-US-S

200.0

Control

97.9

99.3

85.6

79.9

30.61

4.40o

SB2-ES-S

290.0

45

139.7

142.0

Fig. 9 The profile of deflected shape at mid-span

33

130.4
124.5
28.90
3.90o
Table 4 Test results of load and deflection at failureSEE-Mie, Japan, Nov.10-12, 2022

Fig.10 A bar chart of the values of rotation degrees for
all tested spandrel beams. section.

beams (SB1-US-S) and (SB2-US-S), even though thestrengthened spandrels were subjected to higher
applied loading.
3. Using the ETS method is efficient in providing
additional torsional capacity. The contribution of steelrods gave the superior torsional load with the presenceof transverse steel reinforcement in the strengthened
spandrel beams. In this experimental test, theembedded (SB1-ES-S) and (SB2-ES-S) spandrel
beams increased the torsional capacity by 45%,
relative to the control specimen. These results
confirmed that the performance of strengthening
specimens was satisfactory and will increase thetorsional strength of RC spandrel beams.
4. The outcomes indicate that using embedded steelrods showed moderate improvement in controlling thedeflections and rotation angle of spandrel beams. The
reduction in rotation degree of the spandrel (SB1-ESS) when compared to the control spandrel beam (SB1US-S) was 10%, while the reduction in (SB2-ES-S)
was about 11.4% when compared to its counterpart
spandrel beam (SB2-US-S). This moderate
improvement is attributed to the strengthened spandrel
beams afforded a higher load.

Fig. 11 The strain profile in transverse steel.

REFERENCES[1] Lucier G., Walter C.A., Rizkalla S., Zia P., and Klein
G., Development of a Rational Design Methodology
for Precast Slender Spandrel Beams: Part 1,
Experimental Results., PCI Journal, Vol.56, Issue 2,
2011, pp.88-112.
[2] Alla O.K., and Rizkalla S., Design and Behavior ofLedges for Short Span L-Shaped Spandrel Beams. A
thesis requirement for the degree of Master of
Science, North Carolina State University, 2015[3] Walter C.A., Rizkalla S., Behavior of Slender Precast
L-Shaped Spandrel Beams, A thesis requirement forthe degree of Master of Science, North Carolina
State University, 2008
[4] Lucier G.,Walter C., Rizkalla S., Zia P., and Klein G.,
Development of a Rational Design Methodology for
Precast Slender Spandrel Beams. Technical report
no. IS-09-10. Constructed Facilities Laboratory,
North Carolina State University, Raleigh, NC.2012[5] ACI Committee 318 Building code requirements forstructural concrete, (ACI 318-19) and commentary(318R-19).
AmericanConcrete
Institute,
Farmington Hills, Michigan. USA. 2019[6] PCI Industry Handbook Committee. PCI Design
Handbook: Precast and Prestressed Concrete. MNL120. 8th ed. Chicago, IL: PCI. 2017[7] Zia P.,and McGee D., Prestressed Concrete under
Torsion Shear and Bending. Journal of the American
Concrete Institute, vol.73, Issue 1, 1976, pp.26-32.

Fig. 12 The load-strain relationships in ETS steel rod.
CONCLUSIONS
Depending on the results of this study, the main
conclusions are summarized as follows:
1. At stage (1) of loading, the diagonal shear cracks on
the end regions of the web’s frontal face appeared andinitiated from the outer corners of the ledge andextended up with an initial angle of about 45o. During
increasing applied load, the failure mechanism (i.e.,skewed failure plane) for the strengthened spandrel
beams was delayed reaching the upper surface of the
web which was attributed to the prop effect provided
by embedded steel rods.
2. The increase in crack width depends on theimplementation of the strengthening scheme. It wasobserved that the strengthened spandrel beams (SB1ES-S) and (SB2-CES-S) had minimal crack width
across the upper surface of the web that reflected thetorsion effect in comparison to the control spandrel
34

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXPERIMENTAL STUDY ON SEISMIC SHEAR DEFORMATIONOF BOX TUNNEL FOCUSING ON STIFFNESS RATIO ANDFRICTION BEHAVIOR
Takafumi Shimada1, Hidetoshi Nishioka2 and Takahiro Furukawa3
1,2,3
Faculty of Science and Engineering, Chuo University, Japan
ABSTRACTIn the design of cut and cover box tunnels, the interaction between the structure (box) and surrounding groundmust be properly evaluated. In particular, when it comes to determining the strain transmissibility during
earthquakes (shear strain of the box/shear strain of the ground), the shear modulus ratio of the surrounding groundto the box is a key parameter; however, the effect of ground nonlinearity on this relationship has not yet been
elucidated. The interaction forces between a box and the surrounding ground can be roughly divided into the shear
force along the box surface and the normal force. Considering the frictional and sliding motion is especially
important when evaluating the shear force. In this study, we conducted model experiments in a small shear soiltank containing stacked aluminum rods, which were used to simulate ground nonlinearity, with the stiffness of thebox and friction coefficient used as parameters. The experiments showed that the smaller the shear modulus of thebox was with respect to the ground, the greater the effect of frictional motion on the box surface.
Keywords: Box tunnels, Seismic shear deformation, Shear soil tank test, aluminum rods model ground, FE analysis
different box stiffness values Gs, with and without
friction reduction on the surface of the box (which
was used as a parameter), to investigate the frictionalmotion of the box (in particular the presence orabsence of sliding).

INTRODUCTION
The interaction between the structure andsurrounding ground must be properly evaluatedduring the seismic design because undergroundstructures, such as cut and cover box tunnels, aresurrounded by ground. In general, seismic motions
that should be considered in seismic design are thosecaused by inertial forces or shear deformation of thesurround-ding ground. As most undergroundstructures have a relatively large inner space, theinfluence of inertia forces is small, while theinfluence of ground displacement is dominant. Theinteraction force that deforms the box during grounddisplacement is considered highly dependent on theshear modulus ratio Gg/Gs, which is the ratio of theground stiffness Gg (i.e., the shear modulus of theground) to the box stiffness Gs (i.e., the shear modulusof the cut and cover tunnel frame). The interaction
forces can be roughly divided into the shear force
along the peripheral surface of the box and the normal
force on the peripheral surface of the box. Whenevaluating the shear force, frictional motion (thepresence or absence of sliding) should be considered.
In previous research, we conducted simple shear
tests on a model where the ground comprised stacked
aluminum rods, with boxes of different shear
modulus embedded to investigate the effect of theshear modulus ratio on the interaction forces [1].
However, in this study, we did not fully investigate
the frictional motion of the peripheral surface of thebox. Therefore, in the present study, we conducted
experiments using three different model boxes withOUTLINE OF EXPERIMENT
Model Ground and Test Apparatus
The model ground was constructed by piling up a
mixture of 150 mm long aluminum rods of threedifferent diameters (1.5 mm, 2 mm, and 3 mm) in aweight ratio of 1:1:1. We iteratively piled thealuminum rods to a depth of 20 mm and thencompacted them using a small vibrator and a 200 mm
× 150 mm plate, preparing a model ground with a unit
weight of 21.0 kN/m3.
Figure 1 shows the test apparatus used in theexperiments. The shear soil tank has pin hinges at the
top and bottom of the left- and right-side walls toallow for simple shear deformation. We capped themodel ground constructed in the soil tank with a lid,
applied an overburden pressure w to it, and used ajack to apply a horizontal load to the soil tank itself to
induce a simple shear deformation in the model
ground.
The overburden pressure was set to w = 3.07
kN/m2, corresponding to a vertical stress σv of 4.8
kN/m2 at the top surface of the model box. Note thatthe inner surface of the soil tank and the underside of35

SEE-Mie, Japan, Nov.10-12, 2022

the top lid were in direct contact with the aluminum
frame and aluminum rods.
We installed model boxes with a width and heightof 40 mm at the center of the model ground andgenerated simple shear deformations within themodel ground to simulate the behavior of the box
during an earthquake. In the experiment, we directly
measured the load of the jack used to deform the soiltank and the displacement of the side walls, and thenused image analysis to calculate the shear strains on
the model box and ground.
Model Boxes
Fig. 1

The three model boxes used in this study weremade of materials with different box stiffnesses Gs,
which are listed in Table 1. The friction conditions
were set as experimental parameters and are shown in
Table 2. Under Case F1, the friction is cut using a
Teflon sheet. Under Case F2, the friction is not cut,and the coefficient of friction is 0.85.
To simulate the burial of the model boxes, wearranged three blocks with a width of 40 mm, heightof 40 mm, and depth of 30 mm at equal intervals inthe depth direction and embedded them in the model
ground. Note that the box stiffness Gs shown in Table
1 is the entire shear modulus of the model box,
averaged in the horizontal depth direction.

External view of test apparatus.

Table 1 Box stiffness Gs of model boxes used in theexperiment
Case
Name
Gs

Case1

Case2

Case3

90

199

453

2

(kN/m )

Table 2 Friction conditions
Friction conditions

RESULTS OF EXPERIMENTS

F1

With friction cut by Teflon sheet

F2

Without friction cut

2.5: σv=4.8kN/m2

Shear stress τ （kN/m2）

Characteristics of the Model GroundA total of six boxes were tested twice using threevalues of box stiffness Gs (90, 199, and 453) and two
types of skin friction conditions (F1 and F2). Figure
2 shows the relationship between the experimentallyobtained model ground shear stress τ and soil tankshear strain γgf, and Fig. 3 shows the relationshipbetween the ground stiffness Gg and soil tank shear
strain γgf. The shear stress τ was determined by
dividing the jack load by the contact area of the lid,
and the soil tank shear strain γgf was determined by
the amount of angular change in the side wall. The
ground stiffness Gg was obtained as the secant
modulus by dividing the shear stress τ by the shear
strain γgf of the soil tank at that time.
Figures 2 and 3 clearly show that the model
ground exhibits nonlinearity at the microstrain level.
The ground stiffness Gg varied with the soil tank shear
strain γgf and was obtained by averaging the values atthree strain levels, as outlined in Table 3.

2.0
1.5
1.0
0.5
0.0
0.000

0.005

0.010

0.015

0.020

0.025

Soil tank shear strain γg f

Fig. 2

Relationship between shear stress τ and soiltank shear strain γgf.

Ground stiffiness Gg （kN/m2）

10000: σv=4.8kN/m2

1000

100
10-4

Relationship Between the Shear Strain of theModel Box and Surrounding Ground

10-3

10-2

10-1

Soil tank shear strain γg f

Figure 4 shows the relationship between theexperimentally obtained shear strain of the box γs andFig. 336

Relationship between ground stiffness Gg
and soil tank shear strain γgf.

SEE-Mie, Japan, Nov.10-12, 2022

0.010

0.005

0.000
0.000

Fig. 4

0.005

0.010

0.010

F2-1
F2-2
F1-1
F1-2

Shear strain of the box γs

F2-1
F2-2
F1-1
F1-2

Shear strain of the box γs

Shear strain of the box γs

0.010

0.005

0.000
0.000

0.005

F2-1
F2-2
F1-1
F1-2
0.005

0.000
0.000

0.010

0.005

0.010

Shear strain of the surrounding ground γg

Shear strain of the surrounding ground γg

Shear strain of the surrounding ground γg

(a)

(b)

(c)

Relationship between shear strain of the box γs and of the surrounding ground γg: (a) case 1 Gs = 90
kN/m2; (b) Case 2 Gs = 199 kN/m2; (c) Case 3 Gs = 453 kN/m2.

of the surrounding ground γg. Note that Fig. 4 isorganized according to the experimental cases
detailed in Table 1. To calculate the shear strains, weused image analysis to find the vertex displacement
in a rectangular area (about 120 × 120 mm) aroundthe model box and the surrounding ground and thencalculated the strains by assuming that each region
was a constant strain element [1].
Figure 4 shows that as the box stiffness Gs
increases, the box strain γs decrease, confirming thesame pattern observed in our previous study [1]. The
relationship between the shear strain of the box γs andof the surrounding ground γg was different with andwithout friction reduction after γg = 0.005 in Case 1
and γg = 0.0025 in Case 2. In Case 3, where the box
stiffness Gs was large, there was no clear difference
between the cases with and without friction reduction.
These tendencies indicate that the sliding motion
on the surface reduces the strain on the box, and the
reduction of friction can be expected to improve theseismic resistance; however, the smaller the box
stiffness, the greater the effect, and the greater the box
stiffness, the smaller the anticipated effect.

Table 3 Box stiffness Gs of model boxes used in theexperiment
Soil tank shear strain
γ gf
G g average value
2(kN/m )

0.001

0.005

0.01

797.2

272.1

155.6

(a)

FE ANALYSIS
Overview of Analysis
Our experiments revealed that the relationshipbetween the shear strain of the box γs and of theground γg of the ground changed depending on thefriction reduction conditions of Case 1 and Case 2. To
reproduce this tendency in an analytical study, we
conducted a two-dimensional finite element analysis.
The analytical model used in the FE analysis is
depicted in Fig. 5. In the FE analysis, we modeled
both the box and the ground as square 2 × 2 mm planestrain elements, with the box positioned in the centerof the ground. A joint element was also provided
between the box and ground elements to account for
the effects of sliding and separation.
The load conditions in the analysis were(b)Fig. 537

Diagram of the analytical model andconditions used for the FE analysis: (a)initial step; (b) Enforced displacement step.

SEE-Mie, Japan, Nov.10-12, 2022

0.005

(Exp.) F2-1
(Exp.) F2-2
(Exp.) F1-1
(Exp.) F1-2
(FEM) F2
(FEM) F1
0.000
0.000

Fig. 6

0.005

0.010

0.010

0.005

(Exp.) F2-1
(Exp.) F2-2
(Exp.) F1-1
(Exp.) F1-2
(FEM) F2
(FEM) F1
0.000
0.000

0.005

Shear strain of the box γs

0.010

Shear strain of the box γs

Shear strain of the box γs

0.010

0.010

(Exp.) F2-1
(Exp.) F2-2
(Exp.) F1-1
(Exp.) F1-2
(FEM) F2
(FEM) F1
0.005

0.000
0.000

0.005

0.0

Shear strain of the surrounding ground γg

Shear strain of the surrounding ground γg

Shear strain of the surrounding ground γg

(a)

(b)

(c)

Comparison of the relationship between the shear strain of the box γs and of the ground γg obtainedby either experiments or by FE analysis: (a) case 1 Gs = 90 kN/m2; (b) Case 2 Gs = 199 kN/m2; (c)Case 3 Gs = 453 kN/m2.

implemented as follows. After applying the gravity
and the overburden pressure in the initial step, we
subjected the ground to rightward enforced
displacement to simulate a linear tilt on both sides ofthe soil tank to induce simple shear deformation of
the model ground. The boundary conditions were set
as fixed to the bottom and horizontally fixed to thesides for the initial step before being fixed to thebottom and vertically fixed to the sides during theenforced displacement loading.
We used the same values of box stiffness Gs in the
FE analysis as used in the experiments, as detailed inTable 1. To express the characteristic that the groundstiffness Gg decreases with an increase in the shear
strain γgf of the soil tank, we used

Figure 6 shows the relationship between the shear
strain of the box γs and of the ground γg obtained fromthe 2D FE analysis, along with the corresponding
results obtained from the experiments.
The experimental results, including the effects of
cutting the friction, were accurately reproduced by
the analysis for Cases 1 and 2. However, while theanalysis reproduced the small effect of the presenceor absence of the friction cut for Case 3, the results do
not quantitatively match, possibly because theequivalent linear model does not reproduce thesmaller shear strain of the box in the experiment due
to the pre-dominant rotation of its bottom caused by
the nonlinear behavior of the ground near the bottom.
CONCLUSIONS

G g  6.32   gf

0.702(1)

In this study, we conducted model experiments
and an FE analysis with three different model boxesof different box stiffness values Gs, both with andwithout friction reduction on the surface of the box.
Our experimental and analytical investigations
confirmed that cutting friction as a seismic
countermeasure was effective when the box stiffness
was small but not when the box stiffness was large.

to set the equivalent linear stiffness according to thesoil tank shear strain γgf. Note that Eq. (1) is anapproximation of the relationship between the groundstiffness Gg and the soil tank shear strain γgf shown in
Table 3.
The Poisson's ratio ν of the ground was set as ν =0.3 based on a previous analytical study of aluminumrods model ground [2]. And for the box, ν = 0.499
because the model material used in the experiment
was a dense rubbery material and was considered
incompressible. The unit weight of the box was set toa value based on the specific gravity of the materials
used in the experiment, while the unit weight of theground was set to a value based on the unit weight ofthe model ground. The boundary between the box andthe ground was a joint element that models Coulomb's
friction law. The friction coefficient μ was set to μ =0 (an extremely small value in the analysis) for Case
F1 (with friction cut by the Teflon sheet) and μ = 0.85
for Case F2.

REFERENCES[1] Shimada T., Nishino F. and Nishioka H.,
Experimental Study on the Effect of Nonlinearity
of Ground on Shear Strain Ratio in Cut and CoverTunnel During the Earthquake, Journal of Japan
Society of Civil Engineers, Ser. A1 (StructuralEngineering & Earthquake Engineering (SE/EE)),
2022. “In press, in Japanese”[2] Akagi H., Sato K. and Kiriyama T., Numerical
Study on Load-settlement Relationships of
Shallow Foundation Under Extremely Low
Confining Pressure, Proceedings 6th International
Conference on Particle-Based Methods Fundamentals and Applications, Barcelona, Spain,
2019.

Analysis Results

38

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

GLOBAL DAMAGED INDEX ASSESMENT OF DYNAMIC LOADSBASED UPON ARTIFICIAL NEURAL NETWORKS
Widya Apriani1, Reni Suryanita2 and Hendri Rahmat3
Civil Engineering, Lancang Kuning University, Indonesia
2
Civil Engineering Department, Faculty of Engineering University of Riau
1,3

ABSTRACTDisasters due to the collapse of bridge structures that cannot be predicted in advance require enormous
rehabilitation costs. This is caused by a decrease in ability or damage that cannot be identified earlier (early
warning). The difficulty of directly predicting the condition of the bridge structure is caused by the limitations of
the test equipment and the testing environment conditions. Structural Health Monitoring (SHM) is an effort toidentify damage, including determining the event, location and severity of each damage. This study aims toevaluate the Damage Index condition of the bridge structure due to the dynamic load of the bridge so that it canbe used for planning maintenance of rational and economical structures. The study centered on various dynamic
loads from the analysis of Steel Arch bridges. The damage detection approach is based on Artificial Neural
Networks (ANN) with the help of the MATLAB computer program. In this study, the Global damage index uses
the parameters of acceleration, velocity, displacement, and stiffness reduction. The newly proposed damage
expression combines the top three influential engineering determining parameters (EDPs). In this study, ANN
method requires structural dynamic response statistics as a damage index for SHM so that it can predict the healthcondition of bridge structures quickly. Then, verification is carried out using the finite element method program.
The results are A comparison between the proposed GDI with Park- Ang GDI. The Proposed Damage Estimation
method produces a relative index that is 20% higher than that of Park-Ang. The R-value for training and testing of
ANN ranges from 97.2% to 97.6%, which shows that the ANN predictions for displacement, velocity, and centerspan acceleration of the bridge structure can represent 97.2% to 97.6% of all data. This shows that the level ofaccuracy of the target value with the predicted value of ANN is very good.
Keywords: Artificial neural network, Steel arch bridge, Bridge condition, Global damage index
INTRODUCTION

using the Damage Index (DI) on bridges can beapplied (Park et al., 2001). DI is generally defined as
the ratio of the initial resistance capacity to the
reduced resistance capacity of a structure.
Comprehensive reviews have been done with wellnarrated damage assessment structures for thedetermination of the local Damage Index and GDI for
buildings (Kurniawandy & Nakazawa, 2019) andbridges (Suryanita & Adnan, 2013). Park-Ang DI for
the MDOF system has introduced the Damage Index
method (Hait et al., 2019). From the literature review,
the building DI was evaluated using the maximum
deformation and cyclic loading as described in the
Park-Ang method. It is stated that the deviation value
in a four-storey building can be predicted, but it isdifficult to apply if the number of floors of thebuilding increases, because it requires accurate
calculations and requires a large amount of time. For
large-scale investigations, this method is difficult toapply. In this study, the method proposed to assess thedamage is the Global Damage Index (GDI) methodwith the Proposed Damage Estimation Procedure
approach. This method combines many engineering
determining parameters (EDP), such as acceleration,
velocity, and maximum displacement. The EDP was
combined into an equation by multivariable

Bridge structure has a risk of susceptibility todamage and decreased strength during its service life
due to various factors, with earthquakes being one of
the most severe. The structure needs to be monitoredwith a Structural Health Monitoring System tool toprevent the danger of structural failure due todisasters occurring (Mardiyono et al., 2012), resulting
in the loss of property and many lives (Hait et al.,2019). In this study, the case study is the Siak III
Bridge, which was built in 2011. This type of bridge
is a curved steel frame that has a length of 120 meters,a height of 11 meters and a width of 11 meters, thetype of girder is a steel structure (Muslikah, 2011).
This bridge is not equipped with a bridge SHM tool.
This bridge is located in Indonesia, where the country
is known as the ring of fire for earthquakes withmoderate to high earthquake risk levels (You et al.,2014).
To predict the condition of the bridge, there areseveral methods that can be applied, among then are
field visualization (Park et al., 2001) and numericalprediction (Apriani & Lubis, 2019). However, to date,procedures that require data and time as well as highaccuracy are needed. Damage assessment procedures
39

SEE-Mie, Japan, Nov.10-12, 2022

regression (MVR) analysis . A correlation has been
established between the Park-Ang GDI and EDP by
MVR analysis. The application of this method to a
multi-storey building structure shows satisfactory
results. Therefore, this study will apply the GDI
method as the proposed damage estimation procedure.

seconds. Then, the response spectrum analysis isapplied to the adjusted accelerogram and a response
spectrum graph is generated that closely follows thedesign response spectrum as the target.
Indent are two ways to modify a time history record
to fit the design response spectrum, namely: (a)scaling in the time domain, and (b) scaling in thefrequency domain. The scaling procedure in the time
domain is carried out to obtain the minimum
difference squares between the ground motion
response spectrum and the target spectrum (minimum
least squares method), namely:

METHODOLOGYThis research consists of the stages of diagnosis,
analysis, and verification. The diagnosis begans witha numerical analysis model and experimental bridge
girder. This phase was done by entering data input
into the finite element program to then be used as
input data on artificial neural networks with the helpof a computer program called MATLAB. The
designed bridge girder was subjected to NLTHA
analysis under real earthquake ground floor motion toreveal true elastoplastic behavior. Adopting the ParkAng method assumes that all members are corrupted
and all DI members are estimated to determine global
damage. It is, therefore, very important to know thelevel of vulnerability that reflects the actual conditionof the building after an earthquake. In this study, a
new damage expression is proposed to combine the
top three influential EDPs as an option to estimate
structural DI. The diagnosis phase was carried out bycomparing the results obtained from ANN analysis
with the finite element method program (SAP, 2000).
Furthermore, testing is done to reflect the actual
conditions as a basis for condition assessment(Asmarani et al., 2020). Based on the simulation
carried out, the total weight of the passing vehicle was
generated based on the recorded dynamic response.
Artificial neural network planning is carried out withthe stages of training and evaluation stages andpreparing the data beforehand.

2𝑇[𝑑𝑖𝑓𝑓𝑒𝑟𝑒𝑛𝑐𝑒 ] = ∫𝑇 𝐴[𝛼𝑆𝑎𝑎𝑐𝑡𝑢𝑎𝑙 (𝑇) − 𝑆𝑎𝑡𝑎𝑟𝑔𝑒𝑡 (𝑇)] 𝐷𝑇
𝐵(1)
Where the actual Sa is an actual earthquake
acceleration response spectrum. Sa target are thetarget earthquake acceleration response spectrum. α
is a scale factor. T are oscillator period. TB is lower
boundary period of scaling. TA is upper limit periodof scale. By differentiating equation (1) once against
α and then equating it to 0 (zero), a scale factor will
be obtained:𝑻

𝜶=𝒕𝒂𝒓𝒈𝒆𝒕 𝟐(𝑺𝒂𝒄𝒕𝒖𝒂𝒍
−𝑺𝒂
)
𝒂
=𝑻𝑩
𝑻𝑨
∑𝑻
(𝑺𝒂𝒄𝒕𝒖𝒂𝒍)𝟐
=𝑻𝑩 𝒂

∑𝑻 𝑨

(2)

The results shown in fig. 1 are the results ofmodifying a time history record to fit the design
response spectrum from Imperial Valley earthquake
data to Pekanbaru-Indonesia response spectrum data.

Acceleration respons spectrum,
Sa (g)

1

Ground Motion Selection

0.8
0.6

rs pekanbaru

0.4
0.2
0

The time historical ground motion of anearthquake provides an overview of the intensity, ameasure related to a certain level of disaster, namely
the return period, which will describe the magnitude,
distance to the epicenter, site conditions, and several
parameters that determine the characteristics of theground motion characteristics (Wahyudi, 2017). It isnecessary to pay attention to the selection of records
with the appropriate magnitude because this has avery large influence on the frequency content andduration of ground motion. A means of selecting andscaling the time history record of real earthquake
accelerograms to match the response spectrum of thedesign earthquake acceleration according to Seismic
Code Indonesia (SNI 1726-2012) has been carried out
covering the period range period 0.05 until 4.0012Period, T3

4

5

Fig. 1 Acceleration Response Spectrum adjusted forlocation at Pekanbaru, Indonesia.
So that the earthquake accelerogram response
spectrum is obtained which is adjusted for thefollowing Pekanbaru city:

Fig. 2 Earthquake accelerograms adapted for the40

SEE-Mie, Japan, Nov.10-12, 2022

city of Pekanbaru
L

Model Selection
The model used is a steel arch bridge with alength of 168 m. Bridge structure elements consist ofarch rib frame (1200x800 x 24mm), hanger (100 mm,
fy is 490MPa), tie beam (600x600x24mm), concrete
floor beam (400x400 mm). Type of structure is JIS G
3106 SM YB, stress yield (fy) is 295 MPa, modulus
of elasticity existing condition is 200,000 MPa, andspecific gravity is 78.5 kN/m3.

L

SU

SU

Fig 3 Schematic diagram of the laboratory girder ofarch bridge model.

Table 1 Damage scenarios of steel Hollow Beam
Damage
Case
1
2
3
4

Stiffness
reduction,
SR (%)
10
20
30
40

BO

L

Young
Modulus(MPa)
180000160000140000120000Existing DI of Structure
A method for estimating DI is based on several
responses, such as ductility, displacement, joint
rotation and no. of the inelastic loop. Among them,
Park-Ang DI, a significant and well-known method,
was adopted in this study. The formula for determing
DI as proposed by Park and Ang is given in Eq. (3)The equipment needed in this research is
supported by the Engineering Laboratory of the
University of Riau, including LVDT. To measure thevibration, the LVDT sensor is installed on the bridge
girder. Furthermore, the resulting dynamic response
data is recorded with a data acquisition unit (Data
Acquisition Device). The data are stored for later
processing with calibration result data. Calibration isdone using acceleration data. The following are theresults of modifying a time history record to fit thedesign response spectrum from Imperial Valley
earthquake data to Pekanbaru response spectrum data.

𝜹𝜷𝑫𝑰 = ( 𝜹𝑴 + 𝑸 𝜹 ∫ 𝒅𝑬)
𝒖

𝒚 𝒖

(3)

When Damage Index is equal to 0, it indicates nobreakdown, DI indicates total damage or collapse, δM
is maximum deformation under earthquake, δu ishighest deformation under monotonic loading, Qy is
calculated yield strength, dE is incremental absorbing
hysteretic energy and β is a non-negative parameter.
This is complicated, because you have to enter theparameters one by one for each girder. Furthermore,
the parameters of acceleration, velocity, andmaximum displacement on each girder are also input
to the GDI calculation of the Proposed Damage
Estimation Procedure method, which is more
complete and faster in analyzing.

Experimental Procedure: Analyzed Similitude
Girder
The girder element in this case study has a large
dimension and cannot be tested in a laboratory.
Therefore, modeling is made using the similitude
method, namely scaling the dimensions of the model
dimensions, loading, and material parameters to besmaller. Experimental models using the LVDT tool
were used to obtain estimates of lateral deflection andlateral strain due to loading. The similitude girder
results were further validated by the results with theuse of the LUSAS program (Tan et al., 2017). The
results show the maximum load that can cause thegirder to melt, which is the reference in the deflection
analysis in FEM and ANN. Bridge girder number 11
is modeled to be a simple supported I beam using ananalyzed similitude girder with a scale ratio of 1: 5.
The LVDT tool is attached to both sides of the end of
the girder. The planned load is in stages from 10 to 60
kN. The load is applied through the loading plate aspressure on the beam, as shown in Figures 3.

Proposed Damage Estimation Procedure (EDPs)
The proposed damage procedure is a combinationof parameters that most influence the occurrence of
global damage. This is under the corresponding Eq.
(2). The EDP was combined into equations bymultivariable regression (MVR) analysis. A
correlation has been formed between Park-Ang GDI
and EDP by MVR analysis and the DI expression is
mentioned in Eq (2). This concept applies ninefactors, namely acceleration direction x, y and z (%),
velocity direction x, y, and z, as well as displacement
direction x, y, and z for four planned stiffness
reductions, namely 20%, 30%, and 40 %. The
parameter coefficient is determined by the MVR
analysis. The parameters are a combination of nine
effect EDPs and estimates 21 data points from thesimulation considered by the model. Given the
maximum value of the parameter, GDI is estimated41SEE-Mie, Japan, Nov.10-12, 2022

from a structure directly using Eq. (2).

(2013a). Sharing training data and testing the ANN
model was carried out according to Shahin et al.
(2004). The ANN model is trained by 70% data andtested by 30% data. Statistically, the obtained training
statistical parameters and test data. In this approach,backpropagation has been adopted. The neuralarchitecture of the network model is optimized by thenine numbers of neurons in the hidden layer of theInternet by trial and error. The ANN model
performance is reported in terms of two statisticalparameters: mean squared error
and the linear
correlation coefficient (R). Levenberg-Marquardt
optimization and weight backpropagation bias
function were used to better generalize to training
data.
Data inputted by ANN consist of nine input layers
and nine neurons. which are displacement, velocity
and acceleration. The sum of iteration done is 1000
times and the correlation coefficient value approaches
one.
The verification phase is done by comparing theresults obtained from ANN analysis with the finite
element method program. Based on the bridge detailsurvey data in the form of bridge structure dimensions
and, material characteristics, a bridge structure model
can be using the finite element method. The bridge
structure model is made by adjusting the calibration
results and bridge load stress results of the bridge
structure, then loading simulation that can respond in
the form of strain due to vehicles that cross over thebridge. Based on the simulations that have been
carried out, the total weight of the vehicle passing isbased on the dynamic response that has beenrecorded.

GDI = -0,0102 X1+ 0,0045 X2 + 0,00162 X3 +0,3897 X4 + 0,01808 X5 + 0,04159 X6 + 0,02328 X7- 0,0035 X8 - 0,00339 X9(4)
Predictive Model Based on ANN
On the other hand, to predict GDI, the ANN
model was used based on the damage model. The
summary of the proposed method can be expressedby several parameters, such as acceleration, velocity,and displacement. In Park-Ang DI, only deformationand dissipating hysterical energies are considered.
Artificial neural networks (ANN) are derivatives ofthe biological nervous system. This method has
reliability if used to complement the Structural Health
Monitoring System (SHMS). With ANN, predictionsof structural health conditions can be done quickly,
because, in the process, ANN mimics the workings ofthe human brain.
The backpropagation algorithm belongs to therestricted learning class, where the learning algorithm
is trained on the examples of desired behavior. In a
multi-layer backpropagation network, the output
from one layer becomes input to the next layer. The
steps below are for predictive model based on ANN.
Step 1: Initialize the weights to initialize a small
random value.
Step 2: A set of training is chosen randomly andput into a neural network. For each pair of training,
steps 3-8 are repeated.
Step 3: The first layer receives the input signal ℎ𝑖and sends this to the adjacent layer (hidden unit).
Each hidden unit (𝑧𝑗, 𝑗 = 1, ... ..) adds the weighted
input signal as:
Step 4: Each output unit (𝑦𝑘, 𝑘 = 1, ... ..., 𝑛) sums
the weighted input signal as:(𝑦𝑖𝑛 )𝑘 = (𝑤𝑜 )𝑘 + ∑𝑚
(5)
𝑗=1 𝑧(𝑤𝑗 )𝑘And apply the activation function to calculate theoutput signal, 𝑦𝑘 = 𝜃 (𝑦𝑖𝑛 𝑘).
Step 5: Each unit of output (𝑦𝑘, 𝑘 = 1, ... ..., 𝑛)receives a target pattern that matches the input
training pattern, calculates the error information term𝛿𝑘 = (𝑑𝑘 − 𝑦𝑘 )𝜃(𝑦𝑖𝑛 )𝑘(6)
Calculate a weighted correction term (used to
update 𝑤𝑗𝑘 later)Δ𝑤𝑗𝑘 = 𝛼𝛿𝑘𝑧𝑗(7)
Δ𝑤0𝑘 = 𝛼𝛿𝑘(8)Step 6: Each hidden unit (𝑧𝑗, 𝑗 = 1, ... ..) adds thedelta input and multiplies it by the derivative of theactivation function to calculate the error information,(𝛿𝑖𝑛) 𝑗 = ∑𝑛𝑖=1 δ𝑘 𝑤𝑗𝑘
𝛿j = (𝛿𝑖𝑛) 𝜃(𝑧𝑖𝑛 )𝑗Δ𝑤𝑖𝑗 = 𝛼𝛿𝑗𝑥𝑗
Δ𝑤0𝑗 = 𝛼𝛿𝑗

RESULT AND DISCUSSION
Table 2. shows the difference in displacement
test results in the similitude mode test and comparedwith the results of the LUSAS analysis on bridge
girder number 11. The results show that the increased
load results in greater deflection. Displacement inexperimental testing showed a greater result of 0.55%
compared to using LUSAS. The first melting
condition occurred at a load of 50 KN with adeflection of 11.92 kN. The difference between the
maximum deflection results from the analysis of thesimilitude and LUSAS methods at 50 kN loading was
3.404 mm. Loads above 50 kN show a more gentle
graph, meaning that, during this time, the girderelements have begun to experience strain hardening.
The maximum load value is used as a reference formaking stiffness reduction (RI) simulations for ANN
analysis with a maximum of 50% with a range of
20%, 30%, 40%, 50 and 60%.

(9)
(10)
(11)
(12)

Table 2 Results of Flexural Structure Laboratory
Testing with LVDT 1 and LVDT 2

ANN modeling was executed using MATLAB
42

SEE-Mie, Japan, Nov.10-12, 2022

Load
(kN)

Displacement 0,25 L(mm) (LVDT 1)

Displacement 0,25
L(mm) (LVDT 2)

Lusas

Lusas

10
20
30
40
50

1.015
2.031
3.046
4.061
5.076

Experiment
al
1.78
3.32
4.82
6.48
8.48

60

6.49

11.56

1.528
3.056
4.585
6.113
7.642
9.9

compared to Park-Ang. The Park-Ang method onlyuses the maximum deformation parameter and cyclicloading as the main parameters. Meanwhile, theproposed GDI uses more complex determining
parameters (EDP), such as acceleration, velocity, andmaximum displacement.
ANN is performed after data input in the form of
GDI values is obtained. The trial process was carriedout approximately 150 times on the variation of ANN
training parameters; the best training results wereobtained with the number of iterations of 50000
epochs, a learning rate coefficient of 0.05, a range of
normalization of maximum to minimum variables of
0 - 0.5, and one hidden layer with the number ofneurons as many as 10 neurons.

Experime
ntal
2.26
4.3
6.46
8.88
11.92
(yield)
16.66

From Fig. 4 it can be seen that the deflection in
the middle of the span on the graph coincides between
the results obtained from the LUSAS program (65.14mm) and experimental results (65.88 mm). At lines
above 50 KN, melting begins with a deflection valueof 11.92 mm

Fig. 4 Deflection in LUSAS and experimental
Therefore, the reduction in stiffness is limited to50 KN. There is a good agreement between thepredicted values and the experimental data. The
testing of girders has been analyzed with the help of
the SAP 2000 and LUSAS programs. Based on the
results of laboratory tests, the maximum deformationand cyclic loading are input to the DI calculation of
the Park-Ang method.
A comparison between the proposed GDI with
Park- Ang GDI has been plotted in Fig. 5.
Comparison between the Park-Ang Damage Index
and the Proposed Damage Estimation Procedure are
made to the maximum load value, which is used as areference for making a stiffness reduction (RI)
simulation, which is a maximum of 50%.

Fig. 6 Coefisien of determination (R)To determine the accuracy of the target value with
the ANN prediction value, the coefficient ofdetermination (R) is shown in Fig.6. If R is 1, then the
ANN prediction results for the target are considered
accurate and the predicted results are close to the realone. Calculation of R for displacement, velocity, andthe acceleration for the X, Y, and Z directions areshown in Table 5 and Table 6. Based on the twotables, for the results of training and testing, the Rvalues were obtained ranging from 97.2% to 97.6%.
From this value, it can be concluded that the ANN
prediction for displacement, velocity, and middle
spans of the bridge structure girder can represent
93.0% to 97.2% of all data. This shows that the levelof accuracy of the target value with the ANN
prediction value is very good.
The iteration process is carried out until the ANN
error rate is smaller than the desired error rate limit(MSE). However, the iteration process can also stop
if there are too many iterations and the error rate does
not show a decreasing pattern. In addition to
calculating the MSE value, the coefficient of

Fig.5 Compared Global Damage Index andPark-Ang Damage Index
The Proposed Damage Estimation Procedure
method produces a 20% higher relative index
43SEE-Mie, Japan, Nov.10-12, 2022

determination (R) is also calculated to determine theaccuracy of the ANN prediction results. If the R-value
gets closer to 1, this indicates that the ANN prediction
results are getting closer to the real one (target).

2. The R-value for training and testing of ANN
ranges from 97.2% to 97.6% which shows that the
ANN predictions for displacement, velocity, andcenter span acceleration of the bridge structure canrepresent 97.2% to 97.6% of all data. This showsthat the level of accuracy of the target value with thepredicted value of ANN is very good.
ACKNOWLEDGMENTS
Gratitude to the Ministry of Research,
Technology and Higher Education of Indonesia Grant
for Higher Education Cooperation Year 2019–2020,
Ministry of Public Works and Public Housing
Indonesia and Civil Engineering Study Program at
Lancang Kuning University.

Fig. 7 Plot damage indexed prediction vs. target
The comparison between the predicted severity
and target data for the test data set is shown in Figure
10. Based on Figure 10, the ANN that has been
trained has been able to predict the Global Damage
Index very well. This is indicated by the sufficient
proximity of the distribution of the target andpredicted points to the diagonal line. ANN succeededin predicting the severity of the damage for the test
equipment which was close to the actual output. The
results also look quite reasonable and the test set error
has very similar characteristics without over-fitting.

REFERENCES[1] Hait, P., Sil, A., & Choudhury, S. (2019).
Overview of damage assessment of structures.
Current
Science,117(1),
64–70.
https://doi.org/10.18520/cs/v117/i1/64-70[2] Kurniawandy, A., & Nakazawa, S. (2019).
Seismic performance evaluation of existing building
using Seismic Index method. MATEC Web ofConferences, 276, 01015.
[3] Neves, A. C., González, I., Leander, J., &Karoumi, R. (2017a). Structural health monitoring ofbridges: a model-free ANN-based approach todamage detection. Journal of Civil Structural Health
Monitoring,7(5),689–702.
https://doi.org/10.1007/s13349-017-0252-5[4] Tan, Z. X., Thambiratnam, D. P., Chan, T. H. T.,& Abdul Razak, H. (2017). Detecting damage in steel
beams using modal strain energy based damage indexand Artificial Neural Network. Engineering Failure
Analysis,79(January),
253–262.
https://doi.org/10.1016/j.engfailanal.2017.04.035[5] Widya Apriani, Fadrizal Lubis, R. S. and Y. F.
(2019). Proceedings of AICCE’19: The Evaluation of
Changes in Camber Position to Deflection of Arch
Steel Bridge in Extreme Loads. In I. Marco di Prisco,
Politecnico di Milano, Milano (Ed.), Proceedings of
AICCE’19 : The Evaluation of Changes in Camber
Position to Deflection of Arch Steel Bridge in
ExtremeLoads(pp.
843–853).
Springer.
https://link.springer.com/chapter/10.1007/978-3030-32816-0_62

CONCLUSION
A comparison of the two methods of Park Ang
and Pusposed has been carried out on the case studyof the bridge box girder in this paper. ANN is used toevaluate the accuracy of the analysis. Based on thefindings of this study the following conclusions weredrawn.
1. A comparison between the proposed GDI Park –Ang GDI has been analyzed. The Proposed Damage
Estimation Procedure method produces a relativeindex that is 20% higher than that of Park Ang. The
Park Ang method only uses the maximum
deformation parameter and cyclic loading as themain parameters. Meanwhile, the proposed GDI
uses more complex determining parameters (EDP)
such as acceleration, velocity, and maximum
displacement. Artificial Neural Networks model
based on acceleration, velocity, and displacements
data domain indicated that all MSE models have thesame trend after 50000 iterations.

44

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

STRUCTURAL DESIGN OF SEISMIC ISOLATION FOR TEMPLE ANDSHRINE
1

Yasuhide Mochida1, Kengo Wada1
Ritsumeikan University, Japan Graduate School of Science and Engineering, Ritsumeikan University, Japan
2

ABSTRACT
Seismic isolation is known as effective for saving traditional architecture. However, there are only a few existing
seismic wooden buildings, because traditional building has great variability of material and structuralcharacteristics. Thus, I suggest new type of design flow for temple and shrine, which consider this dispersion. This
flow consists of three stages: seismic diagnosis for original building, seismic diagnosis for seismic isolatedbuilding and force test. Considering scattering, force test plays a very important role. Then, I evaluate theusefulness of the flow by virtual building. As a result of the evaluation, it becomes clear that by fitting the interlayer
deformation angle of seismic isolated building in maximum elastic deformation angle of original building, force
test is possible. Through this test, I can obtain “true restoring force characteristics of original building”, whichsolves these problems. Lastly, I notice that by using this data, design flow is useful for designing Seismic Isolation
Retrofit of temple and shrine.

Keywords: Seismic isolation retrofit, force test, Restoring force, Seismic diagnosis
INTRODUCTION

measurement data, and to evaluate the resiliencecharacteristics of each structural element by creatinga frame model of the entire building. In this study,
first, existing examples will be surveyed and analyzed
to clarify the construction method of seismic isolation
work. After that, we will show the problems thatvariations in the structural performance of traditional
wooden buildings themselves pose to seismic
isolation retrofit design, and propose a design flow,which we hope will contribute to the maintenance andpreservation of traditional wooden buildings as wellas to the seismic isolation retrofit of traditional
wooden buildings with high reliability.

Given the damage to traditional wooden buildings
caused by earthquakes, it is important to improve thedurability of traditional wooden buildings. To
improve durability, seismic isolation retrofitting oftraditional wooden buildings is being promoted.
However, the number of seismic retrofits of existing
traditional wooden buildings is very small. The
reason for this is the large variation in the materialand structural properties of wooden buildings
themselves. In other words, there is a gap between the
average estimated performance and the actual valueof the building. For this reason, it is considered mosteffective to directly understand the characteristics ofa building in the field by means of microtremor
measurements and vibration tests. To date, studies
have been conducted to estimate vibration
characteristics by collecting various types of

OVERVIEW OF SEISMICRETROFIT CONSTRUCTIONISOLATION

Table 1 shows a list of seismic isolation retrofit
construction of wooden structures. The buildings are

Table 1: List of Wooden Seismic Isolation Retrofit Construction
CLASS

A

B

C

Houtoku Ninomiya
NAME

ShrineYutenji Main Hall

D

E

Hongwanji Obihiro

Main hall of

Yotensa Jizo Hall

worship hall
Jonai, Odawara City,

Nakameguro, Meguro-

Nakameguro,

Betsuintemple H,

Main Hall

Ota-ku, Tokyo

Obihiro City,

Meguro-ku,

GNishi Arai

Eiheiji Nagoya Betsuin

Daishonin

Higashi Ku, Nagoya

Nishi Arai,

TempleLOCATION

Kanagawa

City, Aichi Pref.

Adachi-ku, Tokyo

TYPE OF WORKS

Seismic retrofit

Seismic retrofit

Seismic retrofit

Seismic retrofit

Seismic retrofit

new construction

Seismic retrofit

COMPLETION

1894

1860

1718

1929

1612

1953

826年(1971年

CONSTRUCTION

January 1998～

November 2009～

January 2014～

October 1996～

April 2009～

February2014～

April 2008～

PEROID

December 1999

April 2010

August 2015

November 1997

March 2010

March2016

October 2008

BUILDING AREA

176

379

74

947

159

436

1624

FLOOR SPACE

176

379

74

947

159

702

2330

NUMBER OF STAIRS

0－1－0

0－1－0

0－1－0

0－1－0

0－1－0

1－1－0

0－2－0

ku, Tokyo

Prefecture

Hokkaido

Tokyo

HEIGHT

13.08

11

15

25.45

STRUCTURE

W+RC(Base)

W+RC(Base)

W+RC(Base)

W+RC(Base)Ota-ku, Tokyo

F

9.5

17.06

27

W+S(Floor)

W+RC(Floor)

RC

Torerubber:5
Laminated rubber：
600φ2 units,
SEISMIC ISOLATOR

550φ2 units,
350φ1 unit,
Viscous damper:2
units

Rolling Bearing:52
units,
laminated rubber:10 units,
Oil damper:8 units

units,Viscous
Viscous damper:4 units,
Oildamper:2units

Laminated rubber:450φ20 units,
500φ6 units

dampe:58 units,
ResinWindresistantrestraining device:2 units

45

Laminated rubber:4
units、
Viscous dampe:21
units、
Oil damper:4 units

High Damping
Laminated Rubber:32 units,
Viscous damper:7 units,
Oil damper:8 units

SEE-Mie, Japan, Nov.10-12, 2022

excavated and seismic isolators were installed. For
the towing work to the original location, the Jizo Hall
was raised 50 cm, the floating pillar was fixed
between steel frames from both sides, the steel frames
were placed on rails, and the Jizo Hall was moved 30
m. The Jizo Hall was then towed to the original
location.

classified as temples and shrines and were completed
between the 1600s and 1900s. The seismic isolation
retrofit work was done between 1996 and 2015. The
buildings are all one-story, and the seismic isolation
method is the foundation seismic isolation method.
The basic construction process is to temporarily
receive and dismantle the wooden frame or toconstruct the foundation slab with towing. In
principle, this method does not damage theappearance of the existing building, improves its
seismic resistance, and maintains its cultural value.
Here, one newly constructed wooden seismicallyisolated building of a temple and shrine and one
reinforced concrete seismically isolated retrofit
building were used for comparison.

Houtoku Ninomiya Shrine Worship Hall
Fig. 3 shows the arrangement of the seismic isolation
devices. Five laminated rubber bearings and two
adhesive dampers were used for the seismic isolators.
The overall construction process was as follows: (1)Once the wooden worship hall was dismantled, asolid foundation was installed on the site. (2) Aseismic isolation layer was installed on top of thesolid foundation. (3) RC lattice beam foundation is

EXISTING BUILDING DESCRIPTION
Yutenji Main Hall and Shoin
Since this building consists of the main hall, the shoin
and the butsuri-den, the renovation was divided into
two phases, from the shoin to the main hall. Fig. 1
shows the layout of the seismic isolation system. The
seismic isolators consisted of 52 units of linear rolling
bearings, 10 units of laminated rubber reinforcing
materials, and 8 units of oil dampers. The seismic
isolators were installed between the newly
constructed RC base and the RC foundation slab. The
newly constructed RC foundation supports the upper

Fig. 3 Layout of seismic isolation layer
installed on top. (4) Rebuild the wooden portion.
Honganji Obihiro Betsuin Main Hall
The seismic isolators used were 26 laminated rubber
bearings with lead plugs. The building is supported
on direct foundations, but for the renovation, one of
the existing foundations was removed and a new deep
pile foundation was built on it, and the seismic
isolators were installed. The construction procedure
was as follows (1) Remove the existing wooden floor
and construct a temporary foundation. (2)Construction of reinforced foundation beams on bothsides of the existing foundation beams. (3) Remove
the existing foundation at the location where theseismic isolation device was to be installed. (4) Deepfoundation piles, new foundation, and seismic
isolation components were installed at the same
location. (5) Remove the remaining existing
foundations and temporary foundations. (6) Construct
a RC first floor slab on top of the steel floor assembly.

wooden structure. Fig. 2 shows a cross-section of theFig. 1 Layout of seismic isolation system

Branch temple of Ikegami Honmonji

Fig.2 Cross section of seismic isolation layer
seismic isolation layer.

Fig. 4 shows the layout of the seismic isolation layers.
The building was constructed using the "column leg
anchorage" method, in which the seismic isolation
devices were directly attached to the column legs. The
seismic isolators consisted of 58 units of sliding

Yutenji Jizo Hall
The ground where the Jizo Hall originally stood was
46

SEE-Mie, Japan, Nov.10-12, 2022

temporary bearing jack-up → ground excavation →seismic isolation layer construction → jack-down.
Most of the seismic isolation layer construction uses
RC foundation slab and RC base of the first floor. The
main reason for this is the effective seismic use of the
RC foundation for the purpose of weight reduction of
the lightweight wooden frame for long-period
construction and to establish a rigid floor assumption
for the first floor.

bearings and 5 units of laminated rubber reinforcing
materials. In addition to the seismic isolators, a wind
restraint system was also installed as acountermeasure against wind storms. The
construction procedures were in the following order:(1) reinforcement of the shed roof, (2) fixing of thecolumn legs, (3) jack-up, (4) pile press-in, (5) solid
foundation driving, (6) installation of the equipment,(7) jack-down, and (8) exterior work such as seismic
isolation clearances.

PROBLEMS IN SEISMIC ISOLATION

Eiheiji Nagoya Betsuin

Constant microtremor measurements are used todetermine the vibration characteristics of traditional
wooden buildings. The natural period of a steel-framebuilding is proportional to its height, as stipulated in
the second bulletins of the 1980 Construction NoticeNo. 1793, but for a traditional wooden building, asshown in Fig. 6, there is a range between 0.4 and 0.6
seconds for a building 7 m high, for example.
In addition, in structurally evaluating woodenbuildings, it is often assumed that the horizontal
structural surfaces are rigid. However, mosttraditional wooden buildings have flexible floors. In
a flexible floor, each vertical structural plane behaves
non-uniformly depending on the stiffness, bearing
capacity, and arrangement of the vertical structure.
Since it is difficult to calculate this, the assumption ofa rigid floor is often used in the design of seismicallyisolated buildings.
In addition, as shown in Fig. 7, the natural periodvaries due to the sliding of the column legs.
Generally, the resilience of traditional woodenbuildings is evaluated on a street-by-street basis using
the deformation increment method. However, asThis building is a newly constructed seismic isolation.
It is a temple building with one basement floor and
one ground floor, with an eave height of 10.5 m. The
seismic isolation system consists of 20 elastic sliding
bearings, four natural rubber laminated bearings andfour oil dampers. The seismic isolators used were 20
elastic sliding bearings, 4 natural rubber laminatedbearings, and 4 oil dampers. The arrangement of theseismic isolators is shown in Fig. 5. The clearance
between the main body and the outer basement wall
was set at 600 mm because of relative displacement
during earthquakes.

Fig.5 Layout
Fig.4 Layout
Nishiarai Daishi Soji Temple
The building is a "mid-level seismic isolationbuilding" with seismic isolators placed at the tops ofthe first floor columns; because the first floor isseismically isolated, the RC walls under the front
staircase and at the rear of the building were removed
and replaced with drywall. The seismic isolation
system consisted of 7 elastic sliding bearings, 32
laminated rubbers, and 8 oil dampers. The
construction procedure was as follows: 1)
Temporarily support the superstructure with jacks; 2)
Cut the columns; 3) Install the seismic isolation
bearings, preload jacks and preload cases underneath;and 4) Place concrete for the lower part of the
bearings.

Fig. 6 Relationship between height and natural period

CONSIDERATION OF SEISMIC ISOLATIONCONSTRUCTION
Seismic isolation systems for wooden seismic
isolation retrofits are often based on sliding supports,
restoring rubber, and oil dampers. In addition, thegeneral construction procedure is as follows:

Fig. 7 Variation of natural period due to sliding ofcolumn legs
47

SEE-Mie, Japan, Nov.10-12, 2022

shown in Fig. 8, the effect of the PΔ effect due tovertical loading is expected to cause variation in therestoring force.

side without considering variations are conducted inadvance to confirm that the maximum elastic
deformation angle of the building does not exceed the
maximum response deformation angle after baseisolation. Then, the required restoring force can beobtained without damaging the building by applying
force up to the maximum deformation angle after
seismic isolation.

SOLUTIONS TO PROBLEMS IN SEISMIC
ISOLATION
For the eigenvalue evaluation, the eigenperiod under
low strain can be obtained by measuring the constantmicrotremors in the field survey.
The rigid-bed assumption can be established byplacing a concrete slab between the seismic isolation
layer and the upper building when the building isseismically isolated. To prevent the column legs fromslipping, the foundation stones are fixed withconcrete, and horizontal movement is restrained bypassing transverse members between the columns andanchor bolts.
To obtain the building-derived resilience, it is
proposed to conduct on-site static loading tests.
Slowly apply positive and negative forces to theactual building up to an arbitrary angle of inter-story
deformation, measure the maximum load at eachmeasurement point as shown in Fig. 9, and create adeformation angle-restoring force envelope. Since it
is not possible to measure beyond the elastic range ofthe building as a problem of the test, seismic
diagnosis of the existing building and calculation of
the seismic response after base isolation on the safe

TRADITIONALWOODENSEISMICISOLATION RETROFIT DESIGN FLOW
Fig.10 shows the flow. To accurately determine theresponse of existing buildings, the stiffness of a onemass model is determined by calculating backwards
from the natural period obtained from constantmicrotremor measurements. In the seismic diagnosis,
the response to level 1: rare seismic motion and level2: extremely rare seismic motion is examined basedon seismic response calculations to determine theneed for base isolation and to determine themaximum elastic deformation angle of the building.
If necessary, a seismic isolation method is developed.
In the seismic isolation layer setting, the seismic
isolation device and slab are selected. Based on this,the seismic response of the upper building and thetwo-mass system is calculated to determine theseismic isolation effect. In addition to Level 1 andLevel 2 ground motions, Level 3 ground motions are

Fig.9 Creation of restoring force by force testingFig. 8 Resilience of traditional wooden architecture

Fig. 10. Flow of seismic isolation of traditional wooden buildings
48

SEE-Mie, Japan, Nov.10-12, 2022

set for verification of the margin. If the seismic
response does not satisfy the judgment, the seismic
isolation layer is set up again. If the judgment issatisfied, confirm that the maximum response
deformation angle of the upper building after baseisolation is within the maximum deformation angle ofthe elastic range of the existing building, and conduct
a force test. After obtaining the true restoring force ofthe existing building through the force test, performthe seismic response calculation again using a twomass system. Confirm that the response value
satisfies the judgment and complete the design.

As shown in Table 3, it was found that seismic
isolation was necessary. The maximum elastic
deformation angle was 1/60.
Setting of seismic isolators
The seismic isolation layer was a combination oflaminated rubber and sliding bearings as shown in Fig.
12. A two-mass system model of the seismic isolation
layer (seismic isolator + concrete slab) and the upperbuilding was used for the model.

UPPER
PART

VERIFICATION OF DESIGN METHOD
Overview of the building for verification
The virtual temple model prepared for validation was
reduced to a one-mass system and is shown in Fig.11
and Table 2.

BASE
ISOLATION

Height[m]Mass[kg]

Rigidity[N/mm]

Fig. 12. Model of post-seismic isolation building
Response values survey of post-isolation buildings
based on theoretical values

Fig. 11 1-mass point system model
Table 2: Building Characteristics
Building Overview

The results in Table 4 show that the building after
seismic isolation satisfies the determination. Since thebuilding can be subjected to forces up to the
maximum building elastic deformation angle (1/60),
it can be concluded that force tests can be performed.

Single-story wooden house

Dimensions

Tensile Spacing×Girder Length

Height

H[m]

7

Mass

M[kg]

27232

Rigidity

K[N/mm]stepwise10.8[m]×10.8[m]Response values of existing buildings (before
seismic isolation)

Table 4. Response values of buildings after
seismic isolation (theoretical values)

Table 3: Response values of existingbuildings (before seismic isolation)

1
2

RESPONSE VALUE

BCJ-L1

BCJ-L2

1

Shearing Force

17.4

27.8

29.4

2

Acceleration

64.4

103

108.9

3 Deformation Angle

1/285

1/156

1/50

1

Shearing Force

117.4

180.5

-

ISOLATI 2

Acceleration

25.2

389

-

UPPER

RESPONSE VALUE

BCJ-L1

BCJ-L2

PART

Shearing Force

62.8

-

BASE

Acceleration

232.6

-

3 Deformation Angle

1/267

-

TARGET VALUE≦1/120≦1/25

JUDGEMENT

OK

NG

Maximum Angle

ON
TARGET
VALUE

BCJ-L3

Skewness[%]

50

100

150

Deformation Angle

1/250

1/150

1/50

Acceleration

250

300

-

Skewness[%]

50

100

150

OK

OK

NG

JUDGEMENT

Seismic design of post-isolation buildings usingbuilding-derived resilience

1/60

The response values to level 1.2 earthquake motion
were investigated by seismic response calculations.
49

SEE-Mie, Japan, Nov.10-12, 2022

Table 5 shows the results of the seismic response
calculations using the restoring forces assumed in theforce tests. As a result, a larger response value waspredicted, but the target value was sufficiently met.

building with seismic retrofit, a response calculation
based on theoretical values was performed in advance,a static force test was conducted on the building basedon the obtained response values to obtain therestoring force derived from the building, and thepost-isolation seismic response calculation was
conducted again using these values. The design
method was proposed to obtain accurate response
values derived from the building by conducting staticforce tests on the building based on the response
values obtained after the post-isolation calculations.
The verification showed that the actual response
values were predicted to be slightly larger than thetheoretical values calculated, indicating the validityof using the building-derived values, even when
considering the safety side.

Table 5. Response values of buildings after
seismic isolation (original building values)
RESPONSE VALUE

BCJ-L1

BCJ-L2

1

Shearing Force

11.1

60.2

-

2

Acceleration

41.1

223

-

3 Deformation Angle

1/296

1/164

-

1

Shearing Force

117.4

180.5

-

ISOLATI 2

Acceleration

25.2

389

-

UPPER
PART
BASE
ON
TARGET
VALUE

BCJ-L3

Skewness[%]

50

100

150

Deformation Angle

1/250

1/150

1/50

Acceleration

250

300

-

Skewness[%]

50

100

150

OK

OK

NG

JUDGEMENTCONCLUSIONSREFERENCES

In this study, seismic isolation retrofit construction
for existing traditional wooden buildings was firstinvestigated and the construction method wasanalyzed. As a result, it was found that theconstruction procedure of the RC base increases theweight of the lightweight wood structure andlengthens the natural period, and that the rigid floor iseffective in making the horizontal structure of a
traditional wooden building, which generally has aflexible floor, behave in a constant manner.
A seismic isolation retrofit design flow was thenproposed, and the validity of the flow was verified
using a concrete building. In the flow, in order toobtain accurate response values for a pre-isolation[1] Japan Institute of Building and StructuralEngineers, ISCA Edition Design of Wooden Building
Structures (2nd ed.), Japan, 2021
[2] Yoshihiro Yamazaki, Hiroyasu Sakata, Simple
Evaluation and Control Methods for Dynamic
Properties of One-Layer Wooden Structures with Soft
Floors, Japan, 2018[3] Editorial Committee of Design Manual for
Wooden Buildings Using Traditional Construction
Method, Wooden Seismic Design Method for
Traditional Construction, Japan, 2019[4] Architectural Institute of Japan, Seismic Isolation
Structure Design Guideline, Japan, 201350

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

STRESS ANALYSIS OF VALLEY FILLS CONSIDERING
RAINFALL INFILTRATION CONDITIONS

1Daiki Yamashita1 and Shin-ichi Kanazawa2
Environmental Science and Technology, Master’s Program Graduate School of Science and Technology
Niigata University, Japan;
2
Civil Engineering Program, Faculty of Engineering, Niigata University, Japan

ABSTRACTIn recent years, many cases of collapse and damage of soil structures have been reported worldwide due to thesudden increase in heavy rainfall due to climate change. However, analysis of the factors that lead to the fractureof these structure and the fracture mechanisms have not been fully investigated. Therefore, numerical analysis is
attracting attention as a way to better understand the behavior of ground under various construction and rainfall
conditions to ensure the ultra-long-term safety of soil structures and to extend their life. Under these circumstances,
we performed in this study a construction analysis of valley fills by using three types of materials (sand, silt-mixed
sand, and sand-mixed silt) and rainfall analysis under multiple conditions and intensities. From the analysis results,
we conclude that the weakening of valley fills can be roughly divided into three patterns according to therelationship between the flow rate due to rainfall and the infiltration rate of the embankment material.
Keywords: Valley fills, Finite element analysis, Rainfall analysis

1. INTRODUCTION

above makes it urgent to understand the behavior ofground under various construction and rainfall
conditions to ensure the safety of soil structures.
Against this background, this study will analyze theconstruction of valley-filled embankment using three
types of materials (sand, silt-mixed sand, and sandmixed silt) and rainfall analysis under multiple
conditions and intensities. Based on the results, weanalytically examine the changes in ground behavior
when fill materials and rainfall conditions change.

In recent years, many cases of collapse anddamage to soil structures have been reported due tothe increase in sudden heavy rains due to climatechange, such as guerrilla rainstorms and typhoons.
The danger of sediment-related disasters increasingly
plague us every year. Even in the last few years, majordisasters are still fresh in our memory, such as theflooding and collapse of river embankments causedby the typhoon in East Japan in the first year of Reiwa
and the landslide that occurred in Izusan district,Atami City, Shizuoka Prefecture, in the third year of
Reiwa. In addition, the typhoon in East Japan in thefirst year of Reiwa broke 140 embankments
nationwide. These disasters are becoming a familiar
problem in our daily lives.
At origination, soil structures are managed bycompaction at the time of construction to improve
deformation characteristics due to rainfall infiltration.
However, to date, the factors and mechanisms thatlead to the fracture of soil structures have not been
fully elucidated. Because of this, soil structures havegenerally been constructed based on a specification
design that lacks consideration of long-term safety;
although, in recent years, the introduction of
performance design has progressed in this regard.
Under these circumstances in recent years numericalanalysis has been given particular importance in thefield of geotechnical engineering as a method for
ensuring safety and examining the required
performance of both design methods. Furthermore,
the frequent damage to soil structures described

2. AIR-DISSOLVED UNSATURATED SOIL /WATER / AIR COUPLED FINITE ANALYSIS
In this study, we use the air-dissolved unsaturated
soil / water / air coupled finite analysis code
“DACSAR-MP” [1]. The unsaturated soil elastoplastic composition model, water retention curvemodel, and finite element formulation in this analysis
code are as shown below.
2.1 The unsaturated soil elasto-plastic compositionmodel
So far, several unsaturated soil composition
models have been proposed, but the elasto-plastic
composition model of unsaturated soil proposed by
Ohno et al. [2] is used in this analysis code. Ohno etal. [2] propose a model in which the effective
saturation is used as a state agent to express therigidity, with reference to the model given thedefinition of effective stress considering the watercontent of Karube et al. [3]. The effective stress is51

SEE-Mie, Japan, Nov.10-12, 2022

given by the following equations, Equation (1) showsthe effective stress, Equation (2) shows the basic
stress tensor and attractive stress, and Equation (3)shows the attractive force.

σ  σ N  ps 1

(1)

σ N  σ  pa 1, ps  sSe(2)s  pa  pw , Se 

S r  S rc
1  S rc

Equation (6) is the original Cam-Clay model [5]because it is   1 in the saturated state ( Se  1 ).
Fig.1 shows a conceptual diagram of the yieldsurface of unsaturated soil shown by the Se Hardening model [2], and Fig.2 shows the yieldsurface of the EC model proposed by Ohno et al. [4].
This shows that the larger nE is, the more the singularpoint is eliminated and it becomes differentiable, andin the case of nE  2.0 , it is similar to the modified
Cam-Clay model [6]. In this analysis code, it is used
as an isotropic model.

(3)Here, σ  is the effective stress tensor; σ N is thebase stress tensor; σ is the total stress tensor; 1 is thesecond order unit tensor; pa is the pore air pressure;
ps is the suction stress; s is the suction; pw is thepore water pressure; Se is the effective degree ofsaturation; and Src is the degree of saturation ats.
Furthermore, in this study, the EC model of Ohno
et al. [4], who has no singular point (Ex: Preconsolidation stress at saturation) on the yield surface,
was incorporated into the analysis code in order toavoid shifting to a singular point that cannot be
differentiated in numerical calculation. The EC modelis an elasto-plastic composition model that expresses
the soil's contractility characteristics as an
exponential function, and Ohno et al. [4] derived theyield function of unsaturated soil as follows.
p  MD lnp psatMD  qnE  Mp 

Se
Se=1.0Se=0.0p'satnE

 v  0p(4)

 is the yield stress at saturation; p  isHere, psat
mean effective principal stress; q is axial stress; M
is the q p in the limit state; D is the dilatancypcoefficient;  v is the plastic volume strain; and nE isthe shape parameter.
In addition, the increase in consolidation yieldstress due to desaturation is expressed in the form of
 in the times the consolidation yield stress psat
saturated state.  is a function of the effective
saturation and can be expressed as the following
equation.
  exp (1  Se )b ln a   MD lnp psat

( 

q
p

)

p'

nE=1.0(Original Cam-Clay model)
nE=1.1c.s.l
nE=1.2nE=1.3nE=1.4nE=1.5nE=2.0

Yield surface of EC model

2.2 Moisture characteristic curve model
It is widely known that the water retention curve(suction-saturation relationship) that influences themechanical behavior of unsaturated soil differs
between dehydration and water absorption. In otherwords, the water characteristic curve showing thesuction-saturation relationship is not unique, andthere are innumerable scanning curves depending on
the water retention state during dehydration or water
absorption. Therefore, Kawai et al. [7] proposed awater characteristic curve model capable ofexpressing hysteresis by utilizing the fact that thesescanning curves have similar shapes during
dehydration and water absorption. In addition to themodel capable of hysteresis expression, this analysis
code uses the logistic curve equation as shown in
Fig.3. Here, the figure is "(1) dehydration curve" and"(2) water absorption curve" drawn on thedehydration side and the water absorption side froman arbitrary suction-saturation state, which was
proposed by Sugii and Uno [8].
Here, the dehydration curve that passes through an(5)p
 D   v  0

ap'satEffective means stress p' (kPa)

Fig. 2

Here, b is parameter to adjust the spacing of theisosaturation lines on plane e  ln p ' ; a is parameterthat determines the multiplication factor of theconsolidation yield stress when the increase inrigidity due to desaturation is maximum. In particular,
a is often treated as a fitting parameter.
Substituting nE  1.0 into Equation (4) gives thefollowing equation.
pf σ ,  ,  v

p'satFig. 1 Conceptual diagram of the yield surface of
unsaturated soil
Deviator stress q (kPa)f σ ,  ,  v

q(6)

From Equations (3) and (5), it is shown that52

SEE-Mie, Japan, Nov.10-12, 2022

・Effective stress formula

arbitrary suction-saturation degree (s1 , Sr1) converges
to the limit water content ratio wC at s   , and if
the influence of the gap is ignored, the saturation
degree that converges at s   is Src  Gs wc / e .
Here, Gs is soil particle specific density; e is void
ratio. Using S rf* obtained in this way, the dehydration
curve is expressed by the following equation.

Sr 

S rf*  S rc

 


*

S rf S ra*  S raε

1  exp AW  BW log e s1

Degree of saturation Sr (%)(s1, Sr1)

ng

ryi
yd

dar
e

v
cur

Degree of saturation Sr (%)

un
Bo

S*
60 rf

40

20

Src

0

100

200

300

400

500

600

nd

nSr  Sr  v  divv  0(8)p(1  S r ) v  nS r  n(1  S r ) a  divva  0
Ka

0

100

200

300

(1) Dehydration curve

400

500

600

ps 

(2) Water absorption curve

The governing equation in the unsaturated soil /water / air coupled problem consists of balanced
ceremony, effective stress formula, unsaturated
elasto-plastic constitutive equation, conformity
expression, Darcy’s rule, air Darcy’s rule, continuous
conditional expression, and continuous conditional
expression considering gas phase, and is given by thefollowing equations.
・Balanced ceremony
T

(15)

(16)

(17)

S  SrcSrs rs
1  Src
1  Src(18)

However, Src is considered to be the saturation
degree indicated by the adsorbed aqueous phase, andis a material constant.
Here, σ  is the effective stress tensor; σ N is thebase stress tensor; σ is the total stress tensor; ps isthe suction stress; pa is the pore air pressure; D isthe elastic stiffness tensor; ε is the strain tensor; C s
is the coefficient tensor; S e is the effective degree ofsaturation; u is the displacement vector; v is theflow velocity vector of interstitial water; k is thepermeability coefficient tensor; h is the all head; S r
is the degree of saturation;  v is the volumetricstrain; n is the porosity; K a is the air pressure; v a isthe flow velocity vector of interstitial air; and the

2.3 Finite element formulation

T

dSr
dS
s   r pw
ds
ds

1  dSrs  Sr  Src  s1  Src  ds
Moisture characteristic curve modeldivσ   g  0, σ  σ(14)

In addition, the increment of suction stress inEquation (10) is calculated by the following equation.

eSuction s (kPa)

Suction s (kPa)

Fig. 3

Sr 

yw

cu
rv

(13)

Here, assuming that the saturation is a function thatcan be expressed only by suction, the following
equation is obtained.

ar

in
g

(12)

・Continuous conditional expression considering gas
phase

Sra*

Src

(11)

・Continuous conditional expression

ett

20

S

v a  k a  gradpa(s1, Sr1)

Bo
u
40

(10)

・Air Darcy’s rule

*

Srfc

u

v  k  gradh

80 Srf(Sra)60 σ  pa 1

・Darcy’s rule

100

80

1
2

As a result, the dehydration curve and water
absorption curve at any suction-saturation degree canbe obtained. Here, the subscript W indicates the water
absorption.
100

N

s
σ   D : ε  C Se

(7)

1



 ps 1, σ・Unsaturated elasto-plastic constitutive equation

Here, Se is the effective degree of saturation; S r is
the degree of saturation; s is the suction; Src is thedegree of saturation at s   ; S rf is the degree ofsaturation in s  0 ; A, B are fitting parameters ofmoisture characteristics (subscript D indicatesdehydration).
Next, the water absorption curve that passes
through an arbitrary suction-saturation degree (s1 ,Sr1) has a non-constant convergence saturation ats   , so unlike the dehydration curve, twoparameters S ra and S rf must be determined. In otherwords, it is sufficient to find S ra* that satisfies thefollowing equation.
S r1  S ra

N・Conformity expression

 S rc1  exp  AD  B D log e s1 σ  σ(9)53

SEE-Mie, Japan, Nov.10-12, 2022

superscript s indicates the symmetric part of thetensor in ( ).
By weakly formalizing the above governing
equation, discretizing it spatially and temporally, andsolving it under the conditions of initial value andboundary value, the solutions of unknowns u N  ,N, and p aN
can be obtained.
ht  t tt  t t
Here, u N is the amount of change in node
displacement; h N is the amount of change in totalhead in minute time t ; p aN is the amount of change
in air pressure in a minute time t .







3. ANALYSIS MODEL DETERMINATIONAND CONSTRUCTION METHOD

1.0m

1.0m

3.0m

18.0m

0.6m

3.1 About the analysis model
In this study, we perform construction-rainfall
analysis for valley fills. There are various standards
and formats for the valley fills, but in this study, theanalysis model shown in Fig.4 is used as the finite
analysis model. The size of the valley fills structure isa trapezoid with an upper side of 18m, a lower side of
10m, and a height of 3m. The foundation ground is
set to surround the embankment, with a total lengthof 3.6m and width of 20m. The embankment iscomposed of a total of 400 meshes, 10 in the verticaldirection and 40 in the horizontal direction. The
displacement boundary, head boundary, and air
boundary are as follows.
＜The displacement boundary＞
・Lower side, right left side, upper side (foundationpart): x, y-axis fixed・Upper side (embankment part): freedom

5.0m

10.0m

5.0m

： Embankment Part

： Foundation Part

Finite element analysis model

3.0m

Fig. 4

0.6m

Exhaust conditions
Drainage conditions
x, y-axis fixed＜The head boundary＞
・Lower side: drainage conditions
・ Top side, right and left sides: non-drainage
conditions＜The air boundary＞
・Upper side: exhaust conditions
・Lower side, right left side : non-exhaust conditions

Fig. 5

Various boundary conditions

Table 2

Material parameters
Sand

Silt-sandSand-silt

1.33

0.80

1.0

0.10

0.12

0.18

Sand

Silt-sandSand-silt

1.3

1.2

0.33

0.010

0.012

0.018

Sand

Silt-sandSand-silt

0.15

0.50

2.7

8.7

0.87

0.087

Different materials

Common to all materials

1

Degree of saturation Sr (-)

1
0.8

Drying
AD=-24.6,BD=5.2

0.6

In addition, the road earthwork-embankment
guideline [9] states that the embankment material
should be easy to use in construction, maintain thesafety of the embankment, and not cause harmful
deformation. With this guideline, structures areconstructed using a wide range of materials, as shownin Table 1. Therefore, in this study, we will perform
construction-rainfall analysis considering three typesof materials that imitate "sand", "sand-mixed silt",
and "silt-mixed sand". Each material parameter andmoisture characteristic curve are shown in Table 2
and Fig.6. These parameters were determined withreference to the research results by Honda, Iizuka,
Ohno, Kawai and Wang [10]. The parameters shown
below are for use in the embankment．When thesematerials are used for the foundation, thepermeability coefficient was lowered by 2 orders to

Degree of saturation Sr (-)

make the foundation less permeable than theembankment portion of the model.
Regarding the material parameters,  is the
expansion index;  is the compression index; M isthe limit state parameter; m is the unsaturated
permeability coefficient of Mualem [11]; n is theE c model parameter; n E is the enlargement ratio ofyield surface; e0 is the initial void ratio;  is the
Poisson's ratio; k x is the permeability coefficient inthe x-axis direction [m/day]; k y is the permeability
coefficient in the y-axis direction [m/day]; S r 0 is thecritical saturation; and Gs is the soil particle density.

0.8

Drying
AD=-27.2,BD=5.2

0.6

0.4

0.4

0.2 Wetting
AW=-14.6,BW=4.0
0
0
100
200
Suction s (kPa)

0.2 WettingWW
A =-17.2,B =4.000
100 200 300
Suction s (kPa)400

Degree of saturation Sr (-)

1
0.8

Drying
AD=-34.7,BD=5.9

0.6
0.4
0.2 Wetting
AW=-24.0,BW=4.6
00
200 400 600
Suction s (kPa)

Fig. 6800

Moisture characteristic curve (upper left: sand,upper right: sand-mixed silt, lower left: silt-mixed sand)54

SEE-Mie, Japan, Nov.10-12, 2022

3.2 Construction analysis

3.2.2 Construction analysis results

3.2.1 Construction method

Fig.8 shows the analysis results of the various
construction methods described in the previous
section. The results show effective mean stress p ,degree of saturation S r , void ratio e , shear strain  s ,and suction S in each construction method, and only
the left half of the model is shown.
From the above analysis results, effective meanstress p , degree of saturation S r , void ratio e , shear
strain  s , and suction S demonstrate the following
tendencies in all construction methods, and no
significant difference in ground behavior dependingon the construction method was observed.
・Effective mean stress p
Stress decreases in the upper part of theembankment and near the boundary between theembankment and the foundation.
・Degree of saturation S r
Degree of saturation increases near the uppersurface of the embankment.

In this study, after performing the construction
analysis of the valley fills under the above-mentioned
conditions, the rainfall analysis was performed bygiving the upper surface of the embankment a flowrate similar to rainfall. However, there are few
existing examples of numerical analysis of valley fills
by construction method. Therefore, the construction
analysis was performed by each of the following fourconstruction methods, and the construction method touse for the analysis was determined from the results.
The four different construction methods are as
follows.
①

The foundation and embankment portions of thestructure are generated all at once.
After generating the foundation, theembankment is generated all at once.
After generating the foundation, theembankment is divided into 10 layers for every
30cm of layer thickness.
After generating the foundation, theembankment is generated with a layer thicknessof 30cm compacted with 300kPa (repeated for a
total of 10 layers).

②③④

・Shear strain  s
Shear strain occurs along the boundary between theembankment and the foundation.
・Suction S
Suction disappears near the upper surface of theembankment.

After the construction was complete, a flow rateequivalent to a rainfall intensity of 100mm/hour was
given to the upper surface of the embankment until
the total flow rate reached 200mm. The groundbehavior of each case was compared. In thisinvestigation, the analysis model and various
boundary conditions are as described in the previous
section, and the material used is "sand".

For the void ratio e , the results show a decrease at
the boundary between the embankment and thefoundation for all construction methods. However, inthe construction methods ③ and ④, in which theembankment is divided into layers, the range in which
the void ratio decreases is wide. Furthermore, inconstruction method ③, an increase in the void ratio

①

①

②

②

③

④

[kPa]

0.0
①

②

Effective mean stress

245.0

③

④

[%]

③

20.0

①

・・・・・・・・①④

300kPa②

Degree of saturation

90.0

③

④

1.185

Void ratio e

1.207

②

③

④

[%]

300kPa0.0

300kPa①②

Shear strain

1.0

③

④

・・・・・・・・： Embankment Part

Fig. 7[kPa]： Foundation Part

19.6

How to construct valley fills

Fig. 855

Suction S

117.6

Construction analysis results

SEE-Mie, Japan, Nov.10-12, 2022

between the bottom of the embankment and thefoundation also occurs. This was contrary to what was
expected from the results of change in saturation, as
it is uncommon for the porosity ratio at the bottom of
the embankment to rise, that is, for the volume toexpand before rainfall has penetrated to the bottom.
Based on the above results, construction method①,
where “the foundation and embankment are
generated all at once", was adopted for this study.

Sand

Silt-mixed sandSand-mixed silt

[kPa]

19.6

Sand

Effective mean stressSilt-mixed sand

176.4

Sand-mixed silt

[%]

49

Sand

Degree of saturation
Silt-mixed sand100

Sand-mixed silt

4. CONSTRUCTION / RAINFALL ANALYSISCONSIDERING VARIOUS MATERIALS
1.179

4.1 Construction / rainfall analysis conditions

Sand

To clarify the changes to the in-ground behavior of
the valley fills by material type and rainfall intensity,
construction and rainfall analysis were performed inthis study using the combinations shown in Table 3.
The analysis model and construction method usedwere as described in the previous section. In addition,
for rainfall analysis, rainfall was applied only to theupper surface of the embankment after the valley fills
was constructed. Regarding the rainfall intensity, twopatterns were applied: 10mm/hour, which is definedas slightly heavy rain, and 100mm/hour, which isdefined as heavy rain [12].
Furthermore, in order to investigate how the
behavior of the ground changes due to actual heavy
rainfall, rainfall analysis was performed withreference to the rainfall data of the East Japan
Typhoon in the first year of Reiwa [13].
Table 3100mm/hour

10mm/hour

2019 Typhoon No.19

Pattern 1

Pattern 4

Pattern 7

Silt-mixed sandPattern 2

Pattern 5-

Sand-mixed Silt

Pattern 3

Pattern 6-

Embankment material

1.214

Sand-mixed silt

[%]

0.00

Sand

Shear strain
Silt-mixed sand

1.20

Sand-mixed silt

[kPa]

29.4

Fig. 9Suction S

323.4

Analysis results focusing on materials

embankment and the foundation decreased regardlessof material.
Next, we examine degree of saturation S r andcompare each distribution. The results confirm thatthe poorer the permeability of the material, the more
the saturation inside the embankment progresses. In
addition, the more impervious the material, the more
rainfall permeates the upper surface of theembankment. Therefore, impervious material cannot
allow rainfall to penetrate the inside of theembankment. On the other hand, these results
confirmed that rainfall penetrated to the bottom of theembankment with materials having goodpermeability, such as sand, and the characteristics ofrainfall penetration for each embankment material
could be reproduced.
Finally, we compare each distribution of shear
strain  s . These results confirmed that, as with the
distribution of the degree of saturation, larger shear
strain occurred in materials with poorer permeability.
Examining the location of shear strain reveals that alarge value was generated where saturation had
progressed into all the embankment material.
However, the maximum shear strain in this analysis
was about 1.20%, suggesting that the embankment
was weakened, but likely not to the point leading to
fracture.
The above results confirm that when focusing onmaterial type, materials with poor permeability
promote saturation on the upper surface of theembankment and structures built with these materials
may weaken with rainfall.

Analysis pattern

Sand

Void ratio e
Silt-mixed sandRainfall

4.2 Construction / rainfall analysis results
4.2.1 Analysis results focusing on materials
Fig. 9 shows the results of construction and rainfall
analysis of various materials at a rainfall intensity of
10mm/hour. The results show effective mean stressp , degree of saturation S r , void ratio e , shear strain
 s , and suction S in each construction method, andonly the left half of the model is shown. The durationof rainfall was 20 hours, and the total rainfall was
200mm.
First, we examine effective mean stress p andcompare each stress distribution. The results
confirmed that the more permeable the material, thelower the effective mean stress across a wide area ofthe embankment. This is thought to be due to thedisappearance of suction and the increase in porewater pressure due to rainfall. It was also confirmedthat the stress value near the boundary between the

4.2.2 Analysis results focusing on rainfall intensity
Fig. 10 shows the analysis results of construction
56

SEE-Mie, Japan, Nov.10-12, 2022

method by each rainfall intensity in the material"sand". The results show effective mean stress p ,degree of saturation S r , void ratio e , shear strain  s ,and suction S for each construction method. Only theleft half of the model is shown in the figure. The
duration of rainfall was 2 hours at a rainfall intensityof 100m/hour and 20 hours at a rainfall intensity of
10mm/hour. The total rainfall was 200mm.
First, we examine effective mean stress p andcompare both stress distributions. The results confirm
that the stress value decreased as rainfall intensity
increased. As mentioned above, this is thought to be
due to the disappearance of suction and the increasein pore water pressure due to rainfall.
Next, we look at the degree of saturation S r andcompare both distributions. These results confirm thatsaturation progresses as rainfall intensity increases. In
addition, saturation progresses only to the top edge ofthe embankment at a rainfall intensity of
100mm/hour; whereas, saturation progresses to thebottom of the embankment at a rainfall intensity of
10mm/hour. It is probable that rapid rainfall with arainfall intensity of 100mm/hour did not allow therainfall to penetrate into the embankment. On theother hand, at a rainfall intensity of 10mm/hour, there
was sufficient margin for rainfall penetration, so
rainfall likely penetrated to the bottom of theembankment and saturation progressed.
Finally, we compare both distributions of shear
strain  s . The shear strain results confirm that there
was no large difference in the shear strain values
between the two rainfall intensities, but there was alarge difference in the location of where the shear
strain occurred. Similar to the above discussion ofsaturation, the shear strain values tended to increaseat the areas where saturation progressed. Shear strain
was confirmed near the boundary between theembankment and the foundation at a rainfall intensityof 100mm/hour, and at the bottom of the embankment
at a rainfall intensity of 10mm/hour. Here, themaximum value of shear strain was about 0.4%. As
mentioned above, this does not lead to the destructionof the embankment, but it does suggest that
progressive weakening may occur at the affected sites.
The above analysis results confirm that the area ofvalley fills weakening differs depending on the
difference in rainfall intensity.
4.2.3 Rainfall analysis results simulating full-scale
heavy rainfall

3.0m

In this study, rainfall analysis using actual heavy
rainfall data was carried out, and changes in groundbehavior over time were also be investigated. In thisanalysis, we analyzed the rainfall with reference tothe rainfall data from the typhoon in East Japan in thefirst year of Reiwa. The data used is the maximum 24hour rainfall during the East Japan typhoon in the firstyear of Reiwa at the meteorological observation pointin Mitsumine, Chichibu City, Saitama Prefecture. The
total rainfall is 561.5mm/hour.
Fig. 12 shows the time course of each parameterfor the study elements of the embankment in therainfall analysis. The study elements are as describedin Fig.11.
As a general feature, analysis results confirmedthat the effective mean stress decreased, the degree ofsaturation increased, the void ratio decreased, shear
strain was present, and suction disappeared in theentire embankment. This indicates that the stressdecreases with volume compression, and, considering
the 𝑒 − ln 𝑝′ relation, it demonstrated that there is atendency for weakening throughout the embankment.
This was particularly remarkable in No.181, anelement at the bottom of the embankment.
Furthermore, from around 10 hours, when the rainfall

0.6m

No.181
No.501
No.901
No.521
No.921

Fig. 11The study elements
100
Degree of saturation [%]Effective mean stress [kPa]

100
181
501
901
521
921

80
60
40
20
0

4

8

12
16
Time [hour]

20

1.205

98.0

1.192
9.8

Effective mean stress
100mm/hour

[kPa]

1.195

49

Degree of saturation

[%]

181
501
901
521
921

70
60
4

8

12
16
Time [hour]

20

24

8

12
16
Time [hour]

20

24

0.6

1.190

181
501
901
521
921

1.185
0

4

Shear strain [%]10mm/hour

88

100mm/hour

10mm/hour

Void ratio

100mm/hour

10mm/hour

80

50
0

24

1.200

100mm/hour

90810mm/hour

1216Time [hour]

20

24

12
16
Time [hour]

20

24

0.4

181
501
901
521
921

0.2

0
0

4

120

1.205

Void ratio e
100mm/hour

0.00

Suction [kPa]

100

1.192

0.43

Shear strain[%]

10mm/hour

80
60
40
20
0
0

1.192
29.4

117.6

Suction S

Fig. 10

[kPa]

181
501
901
521
921
4

8

Fig. 12 Changes over time for each parameterfor each element

Analysis results by rainfall intensity
57

SEE-Mie, Japan, Nov.10-12, 2022

intensity became high, a remarkable increase in the
degree of saturation and a decrease in the void ratio
were confirmed in No. 901, the upper surface elementof the embankment. This suggests that there is atendency for weakening near this element.
Comparing the behaviors of the elements at the same
depth (No.901-No.921，No.501-No.521) confirmedthat the elements at the end of the embankment had asignificant increase in the degree of saturation and ahigher occurrence of shear strain compared to theelements at the center of the embankment.
The above suggests that as a result of the actual-scale
heavy rainfall, the valley fills tend to weaken in thevicinity of the boundary between the embankment
and the foundation.

long-term changes to ground behavior. Therefore, inthe future, we would like to run analysis assuming
long-term rainfall and the change in the behavior in
the ground when measures such as drainage layers are
implemented.
6. REFERENCES[1] Kanazawa S., Toyoshima K., Kawai K.,
Tachibana S. and Iizuka A.: Analysis ofmechanical behavior of compacted soil with F.E.
method, journal of JSCE, No.68 (2), pp.291-298,
2012.
[2] Ohno S., Kawai K. and Tachibana S.: Elastoplastic constitutive model for unsaturated soil
applied effective degree of saturation as aparameter expressing stiffness, journal of JSCE,
Vol.63/No.4, pp.1132-1141, 2007.
[3] Karube D., Kato S., Hamada K. and Honda M.:
The relationship between the mechanicalbehavior and the state of porewater inunsaturated soil, journal of JSCE, No.535/Ⅲ-34,
pp.83-92, 1996.
[4] Ohno S., Iizuka A. and Ohta H., Two categoriesof new constitutive model derived from nonlinear description of soil contractancy, Journal of
applied mechanics, pp. 407-414, 2006．
[5] Schofield, A and Wroth, P.: Critical State Soil
Mechanics, McGraw-Hill, pp. 1-310, 1968.
[6] Roscoe, K. H and Burland, J. B.: On the
Generalised Stress-Strain Behavior of Wet Clay,Engineering Plasticity eds. J. Heyman and F. A.
Leckie, Cambridge University Press, pp.535-609,
1968.
[7] Kawai K., Wang W. and Iizuka A.: The
expression of hysteresis appearing on water
characteristic curves and the change of stresses inunsaturated soils, Journal of applied mechanics,
Vol.5, pp.777-784, 2002.
[8] Sugii T. and Uno T.: Modeling the New Moisture
Characteristic Curve, Journal of JSCE, pp.130131, 1995.
[9] Japan road association: Road earthworkembankment work guidelines, MARUZEN
publishing, 2010.
[10] Honda M., Iizuka A., Ohno S., Kawai K. andWang W.: A study of the evaluation method for
deformation characteristic of compacted soil,
journal of JSCE, No806/Ⅲ-73, 33-44, 2005.12.
[11] Mualem, Y.: A new model for predicting thehydraulic conductivity of unsaturated porous
media, Water Resources Research, Vol.12, No.3,
pp.514-522, 1976.
[12] Japan Meteorological Agency:[13] Cabinet office, Government of Japan: About thedamage situation related to Typhoon No. 19 etc.
in the first year of Reiwa, p1, 2020.

5. SUMARRY
In this study, we performed construction andrainfall analysis focusing on soil materials andrainfall intensity of valley fills using unsaturated soil
/ water / air coupled finite element analysis. As aresult, it was possible to analytically express thechanges in the behavior of the ground depending on
the material and rainfall. In all cases, the results
suggest weakening of the ground due to rainfall. The
analysis results in the previous chapter clarified thatthe tendency of weakening, based on rainfall amountand embankment permeability, exhibits the following
three patterns.
(1) Rainfall > Permeability (Penetration rate)
Although rainfall permeates the lower layer, not all
rainfall permeates, and it becomes saturated from theupper layer, which tends to weaken accordingly. At
this point, the degree of saturation progresses along
the boundary between the embankment and thefoundation.
(2) Rainfall < Permeability (Penetration rate)
The valley fills become saturated from the lower
layer (bottom) of the embankment and tends toweaken accordingly. At this point, the degree ofsaturation progresses along the boundary between theembankment and the foundation.
(3) Rainfall << Permeability (Penetration rate)
Only the upper layer tends to saturate without
penetrating from the upper layer to the lower layer ofthe embankment. At this point, the degree ofsaturation progresses quickly near the boundary
between the embankment and the foundation,
weakening the structure and leading to its destruction.
Because the purpose of this study is to follow thechanges in the ground behavior of the valley fills,
measures such as drainage layers were not expressed.
In addition, the maximum rainfall duration was 24hours, and it was not possible to analytically examine58

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ANALYTICAL STUDY OF THE STRENGTH CHARACTERISTICS OFCOMPACTED SOIL

1

Kazuki Naito1 and Shin-ichi Kanazawa2
Environmental Science and Technology, Master’s Program Graduate School of Science and Technology
Niigata University, Japan;
2
Civil Engineering Program, Faculty of Engineering, Niigata University, Japan

ABSTRACTIn recent years, many cases of river embankment and levee collapse due to sudden torrential rains orearthquakes have been reported. The mechanism of the strength development of compacted soil in the field has
not been fully elucidated, and it is important to clarify compaction and collapse mechanisms based on themechanics of unsaturated soil to establish a quality evaluation method. Therefore, in this study, compaction
behavior considering soil material was analyzed using the coupled soil/water/air finite element analysis program(DACSAR-MP). Subsequently, the obtained compaction specimens of silt-mixed sand were subjected to flooding
analysis and constant volume shear analysis to determine their strength properties.
Keywords: Compaction curve, Unsaturated soils, Water characteristic curve

The Unsaturated Soil Elastic-plastic Composition
Model

INTRODUCTION
Many cases of riverbank and embankment failure
have been reported in recent years due to sudden
heavy rains, typhoon torrential rains, and earthquakes.
To date, the mechanisms of the strength developmentof compacted soil in the field and its relationship withthe strength of the soil have not been fully elucidated.
Current construction guidelines do not preparemangers for the maintenance of embankments
subjected to recent torrential rains and earthquakes.
To establish a quality evaluation method forembankment structures that considers performance
design, it is important to clarify the relationshipbetween compaction mechanisms and the strength ofembankment structures based on unsaturated soil
mechanics and the mechanism leading to collapse,
and to propose an index for evaluating compacted soil.
In this study, the coupled soil/water/air finite
element analysis program (DACSAR-MP) [1][2] isused to analytically explain the mechanicalinterpretation of compaction behavior considering
differences in soil materials. The strength propertiesof the compaction specimens were then determinedby performing water immersion and shear analyses.

So far, several unsaturated soil composition
models have been proposed, but the elastic-plastic
composition model of unsaturated soil proposed by
Ohno et al [3] is used in this analysis code. Ohno et al[3] propose a model in which the effective saturation
is used as a state agent to express the rigidity, withreference to the model given the definition ofeffective stress considering the water content of
Karube et al [4]. The effective stress is given by thefollowing equations, Equation (1) shows the effective
stress, Equation (2) shows the basic stress tensor andattractive stress, and Equation (3) shows the attractive
force.

σ = σ N + ps 1

(1)

σ N = σ − pa 1, ps = sSe(2)

S − S rcs = pa − pw , Se = r
1 − S rc

(3)Here, σ  is the effective stress tensor; σ N is thebase stress tensor; σ is the total stress tensor; 1 is thesecond order unit tensor; pa is the pore air pressure;
ps is the suction stress; s is the suction; pw is thepore water pressure; Se is the effective degree ofsaturation; and Src is the degree of saturation ats→.
Furthermore, in this study, the EC model of Ohno
et al [5], which has no singular point on the yieldsurface (e.g., pre-consolidation stress at saturation),
was incorporated into the analysis code to avoid

ANALYSIS METHOD
In this study, we use the air-dissolved unsaturated
soil / water / air coupled finite analysis code
“DACSAR-MP” [1][2]. The unsaturated soil elasticplastic composition model, the water retention curvemodel, and the finite element formulation in thisanalysis code are described below.

59

SEE-Mie, Japan, Nov.10-12, 2022

Substituting nE = 1.0 into Equation (4) gives thefollowing equation.

shifting to a singular point that cannot be
differentiated in numerical calculation. The EC modelis an elastic-plastic composition model that expresses
the soil's contractility characteristics as an
exponential function. Ohno et al [5] derived the yieldfunction of unsaturated soil as follows.

) = MD lnp psat+MD  qnE  Mp 

− v = 0(4)

 is the yield stress at saturation; p  isHere, psat
mean effective principal stress; q is axial stress; M
is q p in the limit state; D is the dilatancypcoefficient;  v is the plastic volume strain; and nE isthe shape parameter.
In addition, the increase in consolidation yieldstress due to desaturation is expressed in the form of
 in the times the consolidation yield stress psatsaturated state.
is a function of the effective
saturation and can be expressed as the following
equation.
 = exp (1 − Se ) ln a bqSe
Se=1.0Se=0.0
ap'satp'nE=1.0(Original Cam-Clay model)
nE=1.1c.s.l
nE=1.2nE=1.3nE=1.4nE=1.5nE=2.0Degree of saturation Sr (%)

100

q
p

(6)

)

100

ve
cur
ing
dry
ary
und
Bo

Deviator stress q (kPa)

Fig.1 Conceptual diagram of the yield surface of
unsaturated soil

80

S*
60 rf

(s1, Sr1)

40

20

Src

0

100

200

300

400

500

Suction s (kPa)(1) Dehydration curve

Fig.2

( =

It is widely known that the water retention curve(suction-saturation relationship) that influences themechanical behavior of unsaturated soil differs
between dehydration and water absorption. In otherwords, the water characteristic curve showing thesuction-saturation relationship is not unique, andthere are innumerable scanning curves depending on
the water retention state during dehydration or water
absorption. Therefore, Kawai et al [8] proposed awater characteristic curve model capable ofexpressing hysteresis by utilizing the fact that thesescanning curves have similar shapes during
dehydration and water absorption. In addition tousing a model capable of hysteresis expression, thisanalysis code uses the logistic curve equation asshown in the Fig.3. In this figure, "(1) dehydration
curve" and "(2) water absorption curve" are drawn on
the dehydration side and the water absorption sidefrom an arbitrary suction-saturation state, as proposedby Sugii and Uno [9].
In the model shown in Fig.3, the dehydration curvethat passes through an arbitrary suction-saturation
degree (s1 , Sr1) converges to the limit water content
ratio wC at s →  , and if the influence of the gap isignored, the saturation degree that converges at
s →  is Src = Gs wc / e ; where, Gs is soil particle(5)

p'satp+ D −  v = 0

Moisture Characteristic Curve Model

Where, b is parameter to adjust the spacing of theis saturation lines on plane e − ln p ' , and a is aparameter that determines the multiplication factor of
the consolidation yield stress when the increase inrigidity due to desaturation is maximum. In particular,
a is often treated as a fitting parameter.

p'sat

 psat

From Equations (3) and (5), it is shown that
Equation (6) is the original Cam-Clay model [6]because it holds  = 1 in the saturated state ( Se = 1 ).
Figure 1 shows a conceptual diagram of the yieldsurface of unsaturated soil shown by the Se Hardening model, and Fig.2 shows the yield surfaceof the EC model proposed by Ohno et al [4]. Thisshows that the larger nE is, the more the singularpoint is eliminated and becomes differentiable. In thecase of nE = 2.0 , this is similar to the modified CamClay model [7]. In this analysis code, the EC modelis used as an isotropic model.

nE
p

p

) = MD ln

Degree of saturation Sr (%)(

p
f σ ,  ,  v(

pf σ ,  ,  v

Yield
surfacemeansof thestress
EC modelEffectivep' (kPa)

Fig.3
60

600

*

80 Srf(Sra)

60

Srfc

(s1, Sr1)
Sra*

Bo
un
da
40
ry
we
tti
ng
Src
cu
20
rv
e
0

100

200

300

400

500

Suction s (kPa)(2) Water absorption curve

Moisture characteristic curve model600

SEE-Mie, Japan, Nov.10-12, 2022

specific density and e is void ratio. Using S rf*
obtained in this way, the dehydration curve can be
expressed by the following equation.

Sr =S rf* − S rc

1 + exp ( A + B log e s1 )D

D

+ S rcv a = −k a  gradpa
・Continuous conditional expressionnSr − Sr  v + divv = 0

(7)

( )

S rf S ra* − S ra*

=

(

1

1 + exp AW + BW log e s1)p(1 − S r ) v + nS r − n(1 − S r ) a − divva = 0
Ka

Sr =

(8)

ps =
=

・Balanced ceremony(9)・Effective stress formulaσ = σN+ ps 1, σN= σ − pa 1

(17)

S − SrcSrs+ rs
1 − Src
1 − Src
1  dSrs + Sr − Src  s
1 − Src  ds

(18)

Furthermore, Src is the saturation degree indicatedby the adsorbed aqueous phase and is a material
constant.
Here, σ  is the effective stress tensor; σ N is thebase stress tensor; σ is the total stress tensor; ps isthe suction stress; pa is the pore air pressure; D isthe elastic stiffness tensor; ε is the strain tensor; C s
is the coefficient tensor; S e is the effective degree ofsaturation; u is the displacement vector; v is the flow
velocity vector of interstitial water; k is thepermeability coefficient tensor; h is the all head; S r
is the degree of saturation;  v is the volumetricstrain; n is the porosity; K a is the air pressure; v a isthe flow velocity vector of interstitial air; and thesuperscript s indicates the symmetric part of thetensor in ( ).

The governing equation in the unsaturated soil/water/air coupled problem consists of a balanced ceremony,an effective stress formula, an unsaturated elasticplastic constitutive equation, a conformity expression,
Darcy’s rule, air Darcy’s rule, a continuous
conditional expression, and a continuous conditional
expression considering gas phase, and is given by thefollowing equations.
T

dSr
dS
s = − r pw
ds
ds

In addition, the increment of suction stress inEquation (10) is calculated by the following equation.

Formulation of The Finite Element Method

T

(16)

Where, assuming that saturation is a function that canbe expressed only by suction, the following equation
is obtained.

This yields the dehydration curve and the water
absorption curve at an arbitrary suction-saturationlevel. The subscript W denotes the water-absorption
curve.

divσ +  g = 0, σ = σ(15)・Continuous conditional expression considering gas
phase

Where, Se is the effective degree of saturation; S r
is the degree of saturation; s is the suction; Src is thedegree of saturation at s →  ; S rf is the degree ofsaturation in s = 0 ; and A, B are fitting
parameters of moisture characteristics (subscript D
indicates dehydration).
The water absorption curve that passes through anarbitrary suction-saturation degree (s1 , Sr1) has a nonconstant convergence saturation at s →  , so unlike
the dehydration curve, two parameters S ra and S rf
must be determined. In other words, it is sufficient tofind S ra* that satisfies the following equation:
S r1 − S ra

(14)

(10)

・Unsaturated elastic-plastic constitutive equation

COMPACTION BEHAVIOR CONSIDERING
SOIL MATERIALsσ  = D : ε − C Se

Analysis Conditions(11)

・Conformity expression
ε=−

1
2

(u )

S

In this study, the coupled soil/water/air finite
element analysis program (DACSAR-MP) was used
to analyze static compaction tests considering
material properties.
As shown in Fig.4, a specimen of 5 cm in length and5 cm in width was assumed for the analysis domain.
To make it easier to see the flow of water, thespecimen was made slightly smaller than a normal
specimen. This specimen was divided into 10
elements.

(12)

・Darcy’s rulev = −k  gradh(13)

・Air Darcy’s rule61

SEE-Mie, Japan, Nov.10-12, 20221
Degree of saturation Sr (-)

Drying
DD
A =-25.86,B =6.5

0.8

0.4

0.4
0.2 Wetting
AW=-16.99,BW=4.91
00 200 400 600 800 1000
Suction s (kPa)1

Degree of saturation Sr (-)

0.8

Drying
DD
A =-24.6,B =5.2

0.8
0.6

0.6

<The head boundary>・Totally undrained
The third level headings[Initial conditions]・ Initial moisture content: w=6%~32% (1%~2%increments)
・Loading load: 100 kPa to 100 kPa increments
・Loading time: 50 min
・Unloading time: 5 min
The material constants used in the analysis areshown in Table 1 for the three cases of clay, siltmixed sand, and sand, respectively. The moistureproperty curves are shown in Fig. 5.
Here, regarding the material parameters,  is the
expansion index;  is the compression index; M isthe limit state parameter;  is the Poisson's ratio; 𝒌𝒂
is permeability [m/day]; 𝒌𝒘 is saturated hydraulicconductivity [m/day]; Gs is the soil particle density;

1
Degree of saturation Sr (-)[Boundary conditions]<The displacement boundary>・Lower side: x, y-axis fixed
Right left side: x-axis fixed<The air boundary>・Upper side: exhaust conditions
・Lower side, right left side: non-exhaust conditions

0.2Wetting
AW=-14.6,BW=4
0
0
100
200
Suction s (kPa)300

Drying
AD=-12.8,BD=3.4

0.6
0.4
0.2 Wetting
AW=-6.88,BW=2.400100
Suction s (kPa)200

Fig.5 Water retention curve (upper left: clay,
upper right: silt-mixed sand, lower left: sand)𝑬𝒄 model parameter; 𝒆𝟎 is the initial void ratio; 𝜸𝒕 is
wet unit volume weight; 𝑺𝒓𝟎 is the critical saturation;𝒏𝑬 is the enlargement ratio of yield surface; m is thesubloading surface parameter; and 𝒑′𝒔𝒂𝒕 is
consolidation yield stress due to unsaturation.
Analysis Results and Discussion

m is the unsaturated permeability coefficient of
Figure 6 shows the compaction curves for eachmaterial obtained from the displacement of thecontact point of the uppermost element in the analysis
domain shown in Fig. 4. The analysis was terminatedat the load at which the pore pressure turned positive
and the compacted soil was confirmed to be in a leaky
condition (1100 kPa for clay, 700 kPa for silt mixed
sand, and 700 kPa for sand). As similarly
demonstrated by Kawai et al, all of the compaction
curves obtained were convex upward along the zeroair gap curve from the elastic region to the plastic

Mualem [10]; a is a magnification parameter ofconsolidation yield stress by unsaturation; n is theCompaction load
⑩
⑨

⑧
⑥

⑤

5cm

⑦

④
③
②

1.6

Exhaust conditions
Drainage conditions

Fig.4 Finite element analysis model

1.5

Table 1. Material parameters (first row: clay,
second row: silt-mixed sand, third row: sand)

1.4
0

1.7

100kPa200kPa300kPa
400kPa500kPa600kPa700kPa
800kPa
900kPa1000kPa
1100kPa

Z.A.V.C

Dry density d(g/cm3)

Dry density d(g/cm3)

①
5cm

10
20
30
Water content w(%)

3

Dry density d(g/cm )

clay
1.6

100kPa200kPa300kPa
400kPa500kPa600kPa700kPaZ.A.V.C

10
20
30
Water content w(%)

Sand
Fig.6 Compaction curves
62

Z.A.V.C

1.5

1.4
0

10
20
30
Water content w(%)

silt-mixed sand

1.5

1.4
0

1.6

100kPa200kPa300kPa
400kPa500kPa600kPa700kPaSEE-Mie, Japan, Nov.10-12, 2022

region as the water content increased from low to high,in line with the laboratory test results. Furthermore,

0

-100
-200
-300
0

silt-mixed sandsand
Water Pressure u(kPa)

Water Pressure u(kPa)

100

w=18%
wopt=20%
w=22%

Water Pressure u(kPa)

clay
200

40

100
w=20%
wopt=22%
w=24%

0

w=22%
wopt=23%
w=24%

20

0

50
100
Time t(min)soil is not fully released due to the characteristics ofthe material, indicating that the compaction effect is
not sufficiently effective.
Finally, we examine the change in suction overtime. The suction expression at unloading was
significantly different between the relatively drierside and the wetter side of the optimum moisture
content ratio. On the wetter side, the change in suction
during unloading was large, and suction dropped to anegative value. This phenomenon occurred even at
the optimum water content ratio, at 700 kPa for siltmixed sand and sand. In the case of clay, pore airpressure also plays a role in suction development, so
suction was positive even at a loading of 1100 kPa.
However, the pore water pressure also turned positive,
indicating that the compaction effect was notachieved.
In the compaction curves shown in Fig.6, theoptimum water content ratio did not change at 1000
kPa and 1100 kPa for cohesive soil and at 600 kPa
and 700 kPa for silt-mixed sand and sand. The factthat the optimum water content ratio did not changeeven when the load was increased indicates that thecompaction effect was not obtained.
The suction effect (pore pressure) results and thecompaction curves show that water leaked during
compaction at 1100 kPa for clay and at 700 kPa forsilt-mixed sand and sand, and that there was nochange in optimum water content. This suggests thatthe specimens were over-compacted as they
approached the saturated state from the unsaturated
state, even though the compaction curve could still bedrawn. Therefore, the analysis shows that the
maximum compaction load that can achieve the bestcompaction effect is 1000 kPa for cohesive soils and
600 kPa for silt-mixed sand and sand.

0

0

50
100
Time t(min)50
100Time t(min)Pore water pressure

100

4

w=20%
wopt=22%
w=24%

Air pressure Pa(kPa)

Air pressure Pa(kPa)w=18%
wopt=20%
w=22%

3
2

0
0

50
100
Time t(min)

0.01

w=22%
wopt=23%
w=24%

0.005

1

0
0

Air pressure Pa(kPa)

200

0

50
100
Time t(min)

0

50
100
Time t(min)Pore air pressure

100
0
0

w=18%
wopt=20%
w=22%

50
100
Time t(min)

0

-100

0

w=20%
wopt=22%
w=24%
50
100
Time t(min)Suction s(kPa)200

Suction s(kPa)

Suction s(kPa)

300
0

-20

w=22%
wopt=23%
w=24%

-40
0

50
100
Time t(min)SuctionFig. 7 Chronological change for each parameterby using a subloading surface model, a smoothcompaction curve could be expressed.
Using the quantities obtained from thecompaction curves, a mechanical interpretation of thecompaction mechanism was attempted. Figure 7
shows the results of various characteristics for eachmaterial at 1000 kPa for clay and 600 kPa for siltmixed sand and sand. The obtained optimum
moisture content ratio was compared with the results
at 2% before and after the optimum moisture content
ratio was reached. The dry side, the optimum
moisture content ratio, and the wet side are black, red,and blue lines, respectively.
First, we examine the change in pore waterpressure over time. For each material, the pore waterpressure remained negative at the optimum watercontent and at relatively drier water contents. On theother hand, the pore water pressure turned to positive
pressure at the relatively wetter side of the optimum
water content ratio. Pore water pressure turned
positive at the optimum water content ratio when theload was 1100 kPa for clay and 700 kPa for silt-mixed
sand and sand. The fact that the pore water pressure
turned positive indicates that the compacted soil wasin a leaky state; the boundary conditions forcompaction were not satisfied; and the compaction
effect was not achieved.
Next, we examine the change in pore airpressure over time. The pore air pressure of clay
remained high after unloading, while that of siltmixed sand and sand showed almost no change frompre-loading conditions. This indicates that the effectof pore pressure is not caused by suction in silt-mixed
sand and sand. In the case of clay, the air inside the

INUNDATION ANALYSIS
To understand the collapse phenomenon
associated with water absorption in unsaturated soils,
this study performed a flooding analysis andcompared the results after inundation with the initialwater content ratio (initial saturation) as an internal
condition to understand the soil’s mechanicalbehavior.
Analysis Method
The maximum compaction load of 600 kPa for thesilt-mixed sand obtained from the compaction
analysis was used to represent the flooding collapseof the specimen by increasing the water head from thebottom surface after compaction. The optimum
moisture content and maximum dry density of thespecimens were 22% and 1.65 g/cm3, respectively.
The initial water content ratios were 8%, 20%, 22%,
24%, and 32%.

63

SEE-Mie, Japan, Nov.10-12, 2022

Analysis Method
0.652

400
300

compaction
inundation

400
300

200

200

400
600
Time t(min)

0
0

800

400
Time t(min)

10
0

600

0.9

0.9

compaction
inundation

Void ratio e(-)

Void ratio e(-)

0.8

0.86

0.7

0.84
0.82
0

200

400
600
Time t(min)

0.6
0

800

0.92
Void ratio e(-)

compaction
inundation

400
Time t(min)

600

0.6

compaction
inundation

0.4
200

400
600
Time t(min)

800

0

200

400
Time t(min)

600

0.96
0

Void ratio e(-)

Void ratio e(-)

Void ratio e(-)

0.66
0.65
0.64

102
logp' (kPa)w = 24%e-logp’ curve (Enlarged view)

In addition to inundation as an external factor, it
is also important to understand strength properties
due to shear for the stability analysis of unsaturated
soils. In the case of unsaturated soil, the influence ofother factors, such as the magnitude of suction in thesoil, exhaust and drainage conditions, and othercharacteristics, are considered. In this study,
compaction was considered as an unsaturated exhaustand undrained compressive deformation, andconstant volume shear was applied to a specimen ofsilt-mixed sand under undrained conditions toanalytically investigate strength properties.

600

compaction
inundation

0.97

0.7

0

102
logp' (kPa)compacion
inundation

CONSTANT VOLUME SHEAR ANALYSIS

0.98

0.8

0.67

600

200
400
Time t(min)

0.99

0.9

w = 21%

From these results, it is necessary to determine thespecific threshold at which collapses are likely tooccur. A comparison of the change in void ratio near
the optimum water content ratio was observed in thewater immersed portion of the e-logp' curve.
Figure 9 shows that the smallest change in void
ratio after compaction and inundation occurred at awater content of 20%. The changes after compaction
at the optimum water content ratio and on the wetterside of optimum were larger than those on the drierside. These results indicates that the strength against
water immersion is slightly higher on the drier side of
optimum than at the optimum water content.

compaction
inundation

Degree of saturation Sr (-)

0.8

102
logp' (kPa)

Collapse Threshold

1

Degree of saturation Sr (-)

Degree of saturation Sr (-)

compaction
inundation

0.66

unsaturation.

Void ratio e
1

1

0.61

Fig. 9

0.9

0.86
0

102
logp' (kPa)wopt = 22%

0.88

200

0.664
0.662

0.62

0.6

Mean effective stress 𝒑′
0.88

0.646

compaction
inundation

0.666

compaction
inundationcompaction
inundation

200
400
Time t(min)0.648

w = 20%

20

200

0.668

0.63

30

100

0
0

50

0.65

0.642

40

200

100

60

0.67
締固め
浸水

0.644

w = 32%
Effective mean stress p' (kPa)wopt = 22%compaction
inundation

Effective mean stress p' (kPa)

Effective mean stress p' (kPa)w = 8%

Void ratio e(-)

The results of the analysis are shown below.
First, we examine changes from different initial watercontent ratios. Figure 8 shows the mean effective
stress p’, void ratio e, and degree of saturation Sr,
respectively.
The results of the mean effective stress p’illustrate that for all initial water content ratios, thevalues are lower after inundation than after
compaction, indicating that strength is reduced due towater immersion.
The void ratio e indicates that at low initial watercontent, the void ratio is smaller than after
compaction, indicating compressive behavior. At the
optimum water content, the void ratio did not changemuch. Swelling behavior was predominant at highwater content.
In addition, examining the degree of saturation,
Sr, confirms that at higher water contents, i.e., watercontents that show swelling behavior, transitions
from an unsaturated to saturated state during
compaction indicate that the initial degree ofsaturation influences the deformation after
compaction.
These results indicate that the responses to thewater table are divided into two groups: one on thecompaction side and the other on the swelling side,
depending on the initial water content (initialsaturation) during the rise of the water table. In thecase of low water content, the behavior is mainlycompressive, and the pore ratio decreases despite thelower effective stress. This indicates the occurrenceof internal fractures(collapses) peculiar to200
400Time t(min)600

Degree of saturation Sr
Fig. 8 Chronological change for each parameter

64

SEE-Mie, Japan, Nov.10-12, 2022

Analysis Method

Deviator stress q(kPa)

500
400

The material parameters, moisture property curves,and analysis domain used were the same as in theprevious section, using silt-mixed sand. Aftercompaction, the specimens were subjected to constantvolume shear by applying strain until failure.

300
200
100

Analysis Results

0
0

600
400

compaction
shear
C.S.L
Yield surface

200

Deviator stress q(kPa)

Deviator stress q(kPa)

Figure 10 shows the stress paths in the compaction
and shear processes. The black line represents the
behavior due to compaction and the red line
represents the behavior due to shear. It can be seen
analytically that the compaction causes the yieldsurface to expand, and the shear process causes it tohit the limit state line, leading to failure. Figure 11
shows the maximum shear strength at each watercontent ratio. Here, it can be seen that the shear
strength increases gradually from the low watercontent ratio toward the optimum water content ratio,
but decreases abruptly when the optimum watercontent ratio is exceeded. Since there is no significant
difference in suction change before and after the
optimum moisture content ratio, it is necessary toinvestigate this factor in the future. However, in thepresent analysis, the strength was shown to be
dangerous because it resulted in a significant decreasein strength on the wet side above the optimum
moisture content ratio.

600
400

compaction
shear

400

C.S.L

Deviator stress q(kPa)

Deviator stress q(kPa)・ soil/water/air coupled finite element analysis
program was used to draw compaction curves
that more closely resemble actual conditions.
・The loading of 1100 kPa for clay and 700 kPa
for silt mixed sand and sand, in relation tosuction, pore water pressure, and the compaction
curves drawn, indicated that it was overcompaction . Although previous studies haveshown this in soil/water coupled analysis, thepresent soil/water/air coupled analysis and theconsideration of air dissolved in thesoil/water/air coupled analysis confirm the overcompaction.
・The collapses associated with flooding are greatly
affected by the initial water content (initialsaturation). At low water content ratios, the soil
exhibits compressive behavior with negligible
volume change, beyond which the soil begins toswell.
・The threshold of collapses was determined, andthe highest strength was obtained at the optimum
moisture content or slightly drier side of the
optimum moisture content. Although the D values
control is defined as 90% or more of the optimum
moisture content, the results indicate that
construction on the dry side is safer against
flooding due to rainfall and flooding.
・ Constant volume shear was expressed
analytically to understand the strength properties.

compaction
shear
C.S.L
Yield surface

w = 20%300

400

CONCLUSION00 100 200 300 400 500
Effective mean stress p'(kPa)w = 16%600

Fig. 11 Relation between water content and shear
strength200

00 100 200 300 400 500
Effective mean stress p'(kPa)

Yield surface

200

compaction
shear

C.S.L

Yield surface

200

In summary, the present study showed that
construction on the dry side is the safer side andexhibits more strength in construction using D values
in the field.

100

00 100 200 300 400 500
Effective mean stress p'(kPa)wopt = 22%

10
20
30
Water content w(%)

00
100 200 300 400
Effective mean stress p'(kPa)w = 24%
REFERENCES

Fig. 10 Stress path[1] Kanazawa
65

S.,

Toyoshima

K.,

Kawai

K.,

SEE-Mie, Japan, Nov.10-12, 2022

Tachibana S. and Iizuka A.: Analysis ofmechanical behavior of compacted soil with F.E.
method, journal of JSCE, No.68 (2), pp.291-298,
2012.
[2] Kawai K., Shibata M., Kanazawa S.: Simulationsof static compaction with unsaturated soil/water
coupled F.E. code, journal of JSCE, No,12,
pp.429-436, 2009.
[3] Ohno S., Kawai K. and Tachibana S.: Elasticplastic constitutive model for unsaturated soil
applied effective degree of saturation as aparameter expressing stiffness, journal of JSCE,
Vol.63/No.4, pp.1132-1141, 2007.
[4] Karube D., Kato S., Hamada K. and Honda M.:
The relationship between the mechanicalbehavior and the state of porewater inunsaturated soil, journal of JSCE, No.535/Ⅲ-34,
pp.83-92, 1996.
[5] Ohno S., Iizuka A. and Ohta H., Two categoriesof new constitutive model derived from nonlinear description of soil contractancy, Journal of
applied mechanics, pp. 407-414, 2006．
[6] Schofield, A and Wroth, P. : Critical State Soil

Mechanics, McGraw-Hill, pp. 1-310, 1968.
[7] Roscoe, K. H and Burland, J. B.: On the
Generalised Stress-Strain Behavior of Wet Clay,Engineering Plasticity eds. J. Heyman and F. A.
Leckie, Cambridge University Press, pp.535-609,
1968.
[8] Kawai K., Wang W. and Iizuka A.: The
expression of hysteresis appearing on water
characteristic curves and the change of stresses inunsaturated soils, Journal of applied mechanics,
Vol.5, pp.777-784, 2002.
[9] Sugii T. and Uno T.: Modeling the New Moisture
Characteristic Curve, Journal of JSCE, pp.130131, 1995.
[10] Awal A.S.M.A, Hosseini H. and Hossain M.Z.,
Strength, Modulus of Elasticity and Shrinkage
Behaviour of Concrete Containing Waste Carpet
Fiber, International Journal of GEOMATE, Vol.
9, Issue 17, 2015, pp. 1441-1446.
[11] Mualem, Y.: A new model for predicting thehydraulic conductivity of unsaturated porous
media, Water Resources Research, Vol.12, No.3,
pp.514-522, 1976.

66

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CORROSION BEHAVIOR ANALYSIS OF SELF-COMPACTING
CONCRETE USING IMPRESSED CURRENT AND RAPID CHLORIDEPENETRATION TEST

1

Stephen John C. Clemente1 and Jason Maximino C. Ongpeng2
Asst. Professor, FEU Institute of Technology, Philippines; 2 De La Salle University, Philippines

ABSTRACT
Corrosion is the leading reason for reinforced concrete structures reduced service life. Structures such as ports
and harbors and bridges and other offshore and near shore are prone to chloride-induced corrosion. This researchevaluates the use of self-compacting concrete (SCC) as an alternative concrete for such structures. In theory, SCC
reduced water content, and high cement and powder content will help protect the reinforcement from chloride
intrusion because of its lower porosity and the alkalinity that the cement provided. Sixteen different mixtures of
SCCs were mixed and tested for rheology, compressive strength, rapid chloride ion penetration test (RCPT), andimpressed current (IC). Water content is the significant factor that affects both RCPT and IC. The segregation of
SCC when too much water-cement ratio is combined with a high amount of superplasticizer resulted in high levelof corrosion in the reinforcement. The formation of cracks accelerates the corrosion due to the increased flow ofcurrent in the IC set-up. The impressed current technique is the suggested method for determining the corrosion
resistance of concrete since it simulated the similar effect of corrosion to concrete which is cracking. It also
stimulates the effect of rust on the flow of current. A rapid chloride penetration test is a good indicator of the
durability of concrete but may be insignificant for predicting the corrosion level of reinforcement for SCC.
Segregation negatively affects the total charge passed in the impressed current and the corrosion level of the rebar.
Keywords: Self-Compacting Concrete, Corrosion, Impressed Current, Rapid Chloride Penetration, Segregation

1. INTRODUCTION

rheological properties, compressive strength, andpore structure of the hardened concrete. Similar tonormal concrete, SCC is prone to segregation becauseof the presence of a superplasticizer [4]. SP should bechecked for compatibility with the cement and otherconstituents of the concrete. Most SPs brand indicatesthe limit for the dosage of SP to ensure that bleeding
and segregation are prevented.
This research explored the use of self-compacting
concrete for marine structures using rapid chloride
ion penetration and impressed current technique foraccelerated corrosion. Different mixtures of SCC
with varying amounts of cement, water, andsuperplasticizer were tested for rheology, 28th-day
rapid chloride ion penetration, and corrosion test.
Linear regression analysis was performed todetermine the effect of materials constituents on the
RCPT and corrosion level of rebar. Segregation
resistance of the SCC was also tested and correlated
to the total charge passed in the impressed current andthe corrosion level of the rebar.

Self-compacting concrete is one of the new typesof concrete that has high workability as compared toconventional concrete. SCC constituents are similar
to normal concrete except for the addition of chemical
admixtures such as superplasticizer (SP) for
improving the flowability and viscosity agent forcontrolling the segregation. SCC can be utilized formost concrete structures that have formworks. It isbest used for structures with high-density
reinforcement such as ports, buildings, and bridges
since it can easily penetrate and flow freely throughthe tight spacing of reinforcement.
Corrosion is one of the problems for reinforced
concrete structures especially for those exposed tohigh chloride environments such as near shore andoffshore structures. Since the concrete has porosity,
the reinforcement inside which is commonly made ofsteel is prone to corrosion. When the steel isconverted to rust which is commonly 3-6 times theoriginal volume of steel [1], this will induce stress on
the concrete. Stress will cause cracking andeventually spalling of the concrete cover. Cracks andspalling will eventually cause acceleration of
corrosion since the reinforcement will not have any
protection [2][3].
Different mixtures of SCC particularly different
amounts of cement, water, and SP will yield different

2. METHODOLOGY
2.1 Design Mix of Self-Compacting Concrete
The table below shows the different design mixesof SCC. Cement was varied between 430 to 500
kg/m3. Water was varied between 210 to 250 liters/
67

SEE-Mie, Japan, Nov.10-12, 2022

m3 and superplasticizer content was between 1% to1.8% by weight of cement. The gravel and sand were
fixed at 780kg/m3 and 830 kg/m3 respectively. The
researchers used a central composite design for thedesign mix of SCC. Plus sign (+) or capital (A)indicates the highest amount or dosage of theconstituents, while the negative sign (-) or small (a)indicated the lowest amount or dosage. Zero (0)indicated the middle amount or dosage. The
researcher used 3/8 inches as the maximum size forcoarse aggregates and river sand. For the cement, thisresearch used Type 1 cement and a polycarboxylate
ether type for SP conforming to ASTM C494 Type G.

saturated vacuum and allowed to be soaked for 18
hours ± 2 hours. After soaking, the samples wereinserted into the cells, the right-side cell is positively
charged and filled with 0.3N of NaOH solution,
meanwhile, the left side has a negative charge with a
3% NaCl solution (See Figure). The cells wereconnected in a 60Volts potential for 6 hours while thereading was taken every half hour. The total charge
passed was computed in Coulombs (C).

Table 1 Design Mix of SCC

Max
Ave.
Min

Cement
(kg)
500
465
430

Water
(L)
250
230
210

SP
(%)
1.8
1.4
1

(a)
(b)
(a) Fig. 1 RCPT Samples with Marine Epoxy on Side(b) Fig. 2 RCPT Set-Up
2.4 Impressed Current Technique

2.2 Rheological Test

To accelerate the corrosion of the reinforcement,
the impressed current technique was used. This
technique accelerates corrosion by increasing the rateof chloride ions flowing with the help of a powersource.
This research used a 100mm cube sample with a
20mm diameter rebar at the center. The rebar is
attached negative charge of a 3V adaptor and a copper
plate on the positive charge side. The samples were
soaked in a 5% NaCl solution as shown in Figure 3.

Rheological tests were performed to check theworkability of the concrete. The researchers follow
the standard of EFNARC with regard to theperformance of these tests. Four different criteria
were considered such as flowability, viscosity,
passing ability, and segregation resistance. Table 2
shows the rheological tests needed for each criterion
including the equipment used and the passing levelfor each test.

3. RESULTS AND DISCUSSION

Table 2 Rheological Tests [5]Criteria
Slump
Flow
Viscosity
Passing
Ability
Segregation

3.1 Compressive Strength Rheological Properties

Rheological
Test

Equipment

Slump Flow

Slump Cone

550mm

T500

Slump Cone

-

L-Box

L-Box

0.8

Segregation

GTM Screen

20%

Passing

As shown in Table 3 are the results of rheologicaltests results and the compressive strength test result.
Since the researchers used a high amount of cement
and sand (830kg/m3), many of the design mixes yield
low flowability and passing ability. SCC with ahigher amount of fine materials (sand and cement)
will have higher viscosity [5]. Only mixtures 1, 5, 8,
10, 12, and 14 passes all requirements for rheology.

2.3 Rapid Chloride Ion Penetration Test

Table 3. Rheological and Compressive Strength

A rapid chloride ion penetration test was used tocheck the durability as well as the porosity of thedifferent design mixes of SCC. The researchers
follow the standard of ASTM C1202, Standard Test
Method for Electrical Indication of Concrete’s
Ability to Resist Chloride Ion Penetration. Using a
100mm diameter by 50mm sample cast from thedifferent design mix of SCC. The samples were
coated at the side using marine epoxy to ensure that
there is no leakage (See Figure 1). The samples were
put in a dry vacuum for 3 hours and then 1 hour for

Mix
No.
SCC1
SCC2
SCC3
SCC4
SCC5
SCC6
SCC7
SCC8
SCC9
SCC10

68

SF
(mm)
610
470
460
540
650
540
300
630
560
630

T50
(sec)
1
8
5
6
2
2
DNR
2
3
2

LBox
0.95
0.12
0.33
0.29
0.85
0.63
0
0.8
0.75
0.8

GTM
(%)
0.3
0.21
0.29
0.75
1.7
5.72
0.2
3.09
0.62
0.77

fc'
(Mpa)
42.35
41.83
35.75
34.17
27.98
17.77
47.71
26.76
33.81
31.18

SEE-Mie, Japan, Nov.10-12, 2022

SCC11
SCC12
SCC13
SCC14
SCC15
SCC16

575
565
540
720
665
470

3
3
2.5
1
1
7

0.57
0.84
0.72
1
0.67
0.41

1.69
0.74
0.47
10.02
9.78
0.23

41.54
36.5
31.84
41.57
22.33
32.45

specimen used for RCPT. Several researchers
explored this but there are still no establishedguidelines about this phenomenon.

Note: DNR- did not reach (since the slump flow isless than 500mm, t50 test cannot be performed).
3.2 Rapid Chloride Ion Penetration Results
All 16 mixes of SCC were tested in RCPT,
mixtures 1, 8, 9, 10, 11, 13, 15, and 16 yield a highchloride permeability which is >4000. This is due tothe high water-cement ratio of these samples which is>0.50. Other mixtures yield moderate chloride
permeability (between 2000-4000) which is typicalfor concrete with a water-cement ratio between 0.40
to 0.50 [6].

Fig. 4

Table 4. RCPT Result

3.2.1 Correlation of RCPT and Material Constituents

No.

Design

SCC1
SCC2
SCC3
SCC4
SCC5
SCC6
SCC7
SCC8
SCC9
SCC10
SCC11
SCC12
SCC13
SCC14
SCC15
SCC16

+++−+
−−−
−−+
A00
a00
+−−
0A0
000
−+−
00A
000
00a
+++
−++
0a0

Total Charge(Actual)
4400
3378
3902
3648
3803
3983
3770
4788
4925
5628
4163
3557
4323
3922
4238
4046

RCPT Graph

Simple regression analysis is performed toanalyze the effect of each constituent on the total
charge passed in Coulombs. As shown in Table 5A,
the linear model derived has an R-squared value of0.6026.

Total Charge(Estimate)4394.173372.153895.143643.053797.34
3975.053762.564778.184924.395622.694159.253555.35
4317.58
3919.35
4237.284040.92

Table 5A. Regression Analysis for RCPT
(Regression Statistics)
Regression Statistics

Value

Multiple R

0.7763R Square0.6026

Adjusted R Square

0.5032Standard Error

403.1950

Observations

16

Although water is the only significant factor witha P-value of less than 0.05, cement and SP may still
be considered substantial factors with P-values of
0.12 and 0.06 respectively. Only water yields a
positive coefficient, meaning increasing its amountwill result in increased charge passed (Coulombs) [7].
For the SP, a higher amount of SP will result in alower charge passed, this result may provide evidence
that a certain range of bleeding in concrete may resultin a denser concrete which resulted in highcompressive strength and lower charge passed
referring to SCC14.

Shown in Figure 4 SCC mix number 10 yields thehighest current flowing for the whole duration of thetest. This mixture has high water content with thelowest cement and SP.
Although other mixtures with high water content
yield lower flow of current, it can be observed thatthese mixtures yield high segregation of about
10.02% for SCC14 and 9.78% for SCC15 have thetwo lowest currents flowing among all mixture with(+ or A) levels of water content. The segregation or
bleeding is due to the high amount of water andsuperplasticizer.
During the experimentation, the researchers
noticed a little bleeding of water on these mixes dueto the high SP content of 1.8% by weight of cement.
This bleeding may contribute to the loss of water inthe mixture during casting and may contribute to adenser concrete. The height of the specimen used for
RCPT which is 50mm may play a big role in diffusing
the negative effect of bleeding and segregation in the

Table 5B. Regression Analysis (Coeff and P-Values)

Intercept
Cement
Water

69

Coeff

S. Errort Stat3048.27
-6.07
21.16

2286.64
3.64
6.38

1.33
-1.67
3.32

Pvalue
0.21
0.12
0.01

SEE-Mie, Japan, Nov.10-12, 2022

SP

-668.50318.75-2.10

current is due to the uneven surface due to highsegregation (See Figure 7). Bleeding and segregation
also cause diluted cement paste and decrease thetransport resistance of the concrete [9].

0.06

The researchers considered a linear correlation
between the water-cement ratio and the total charge
passed in RCPT. Although considered as a moderatecorrelation having an R2 value of 0.432 as shown in
Figure 5, the model suggests that a higher watercement ratio of SCC will yield to higher charge
passed which is an indication of higher porosity in theconcrete [8].

Fig. 7

Fig. 5

Impressed Current (5 days)

SCC 7 which ranks 5th for the highest corrosion
level out of 16 samples shows a crack parallel to thelength of the rebar. The crack started at around 90
hours as shown in Figure 7, the current started to pickup due to the direct path of the current. SCC14 showsa severe crack at the edge and the bottom part which
resulted in a big chunk of reinforcement corroded at
the bottom part. This crack is directly towards thereinforcement that resulted in a high flow of current.
Due to the presence of rust on the surface ofreinforcement and sometimes filling in the voids andcracks, it can alter the flow of current since rust is apoor conductor of electricity [10][11].
Also shown on the graph, the current goes up anddown over time. This is due to the change in theresistance of concrete, and the presence of cracks andrust.

Correlation Between W/C and RCPT

3.3 Impressed Current
3.3.1 Comparison of Corrosion Level
Shown in Figure 5 is the corrosion level of eachsample exposed in impressed current for 5 days and
10 days. Some samples more than doubled after theircorrosion level considering 5 days to 10 days of
exposure due to the presence of cracks anderadication of the passive layer that protects thereinforcement.

Fig. 8Fig. 6 Corrosion Level
3.3.2 Influence of Material Constituents and Cracks
on Impressed Current

Impressed Current (10 days)

A simple regression analysis was conducted toanalyze the relationship between the cement, water,and SP content of SCC to the corrosion level of therebar. As shown in table 6, an R2 value of 0.44 wasderived from the regression model that indicated amoderated correlation.

SCC 7 shows a hairline crack before reaching the
5th day on impressed current. This is due to the very
high current density of around 1.59mA/cm2 for
SCC7. SCC14 which yields the 4th most corrosion
level among 16 mixes exposed to 5 days of impressed

3.3.3 Regression Analysis Corrosion Level
70

SEE-Mie, Japan, Nov.10-12, 2022

Table 6. Regression Analysis for Corrosion Level(Regression Statistics)
Regression Statistics
Multiple R
R SquareAdjusted R SquareStandard Error
Observations

Value
0.66740.44540.30680.013016

Table 7 shows the derived linear regression
model. Water content is the only significant factor
with P-values of 0.05. All coefficients were positive
as shown in the table. A higher dosage of SP will be
induced bleeding, but in this experiment, the dosageof SP is limited to 1.8% by weight of cement which
is below the recommended 2% by the manufacturer.
The segregation was also within the allowed range of
below 20%. SP-induced bleeding for samples with ahigh amount of cement as observed from SCC14 may
result in high compressive strength but the
segregation of coarse aggregates at the bottom
contributed to the pore structure of the concrete, thusincreasing the corrosion on the reinforcement [12].

Fig. 9Impressed Current (10 days)

The result of the RCPT has no significant
correlation to the total charge passed in the impressedcurrent with an R2 value of 0.0206. The RCPT test
results only characterized the concrete’s pore
structure and can be used as a durability indicator.
The corrosion of reinforcement inside the concrete isaffected by other factors such as the passive layer ofprotection, cracks, temperature, etc.

Table 7. Regression Analysis for Impressed Current(Coefficients and P-Values)

Intercept
Cement
Water
SP

Coeff
-0.17590.00020.00050.0126

S.Error
0.07390.00010.00020.0103t Stat
-2.38
1.82
2.20
1.22

Pvalue
0.03
0.09
0.05
0.25

3.4 Correlation Analysis Between Corrosion
Level and Total Charge Passed (RCPT and
Impressed Current)

Fig. 10 Impressed Current (10 days)
3.5 Effect of Segregation on Corrosion and Total
Charge Passed.

The total charge passed is calculated using thearea generated by the current flowing (y-axis) andtime in seconds (x-axis). As shown in Figure 9, a
moderate correlation with an R2 value of 0.48 was
observed between the total charge passed andcorrosion level. In this experiment, the voltage of thepower source is set as a constant. The rate of electron
flowing in the circuit (power source→copper →NaClsolution→porous structure of concrete→steel
reinforcement→power source) serves as theresistance of concrete.

As shown in Figure 11, the model suggests thathigher segregation in SCC resulted in to increase in
the total charge passed in the impressed current setup and also yields higher corrosion levels in thereinforcement with R squared of 0.5539 and 0.2877
respectively.

71

SEE-Mie, Japan, Nov.10-12, 2022

REFERENCES[1] Smith, J. L., & Virmani, Y. P. (2000). Materials andmethods for corrosion control of reinforced andprestressed concrete structures in new construction(No. FHWA-RD-00-081). United States. Federal
Highway Administration.
[2] Concha N, Oreta AW. A model for time-to- crackingof concrete due to chloride induced corrosion using
artificial neural network. InIOP Conference Series:
Materials Science and Engineering 2018 Oct (Vol.
431, No. 7, p.072009). IOP Publishing.
[3] Ghanooni-Bagha, M., Shayanfar, M. A., ShirzadiJavid, A. A., & Ziaadiny, H. (2016). Corrosioninduced reduction in compressive strength of selfcompacting
concretescontaining
mineraladmixtures. Construction
andBuilding
Materials, 113, 221-228.
[4] Clemente, S. J. C. (2015). Artificial neural networkmodeling of rheological parameters and compressive
strength of self-compacting concrete with zeolite
mineral as a partial replacement for cement.
[5] EFNARC, F. (2002). Specification and guidelines for
self-compacting concrete. European federation of
specialist construction chemicals and concrete
systems.
[6] Shi, C. (2004). Effect of mixing proportions ofconcrete on its electrical conductivity and the rapid
chloride permeability test (ASTM C1202 or ASSHTO
T277) results. Cement and concrete research, 34(3),537-545.
[7] Yang, C. C., & Chiang, C. T. (2005). On therelationship between pore structure and charge passed
from RCPT in mineral-free cement-basedmaterials. Materials chemistry and physics, 93(1),202-207.
[8] Ghafoori, N., Najimi, M., Sobhani, J., & Aqel, M. A.
(2013). Predicting rapid chloride permeability of selfconsolidating concrete: a comparative study on
statistical and neural network models. Construction
and Building Materials, 44, 381-390.
[9] Safiuddin, M., West, J. S., & Soudki, K. A. (2008).
Durability performance of self-consolidatingconcrete. JournalofAppliedSciences
Research, 4(12), 1834-1840.
[10] Concha, N. C., & Oreta, A. W. C. (2021). Investigationof the effects of corrosion on bond strength of steel inconcrete using neural network. Computers andConcrete, 28(1), 77-91.
[11] Yoo, D. Y., Gim, J. Y., & Chun, B. (2020). Effects ofrust layer and corrosion degree on the pullout behaviorof steel fibers from ultra-high-performance
concrete. Journal of Materials Research andTechnology, 9(3), 3632-3648.
[12] Gao, X., Zhang, J., & Su, Y. (2019). Influence ofvibration-induced segregation on mechanical property
and chloride ion permeability of concrete with variable
rheological performance. Construction and Building
Materials, 194, 32-41.

Fig. 11 Effect of Segregation on Corrosion
4. CONCLUSION
Water is the only significant factor with P-valueless than 0.05 for both the RCPT test and impressedcurrent (corrosion level). The water-cement ratio is
the leading factor in the porosity of the SCC andincreases the total charge passing in the specimen for
the RCPT test.
The crack in SCC7 increases the flow of current
in the circuit. This is the reason for the high corrosion
level of the reinforcement in that specimen. SCC14
has the highest segregation of 10.02% and theconcrete shows inconsistencies on the surface due to
bleeding. Segregation at the bottom of the specimen
increases the potential for chloride intrusion due tothe pore structure created by the capillary action at thecoarse aggregates.
RCPT is not a good indicator for SCC in
predicting its corrosion resistance. This is due to theother factors present that affect the rate of corrosion
such as cracks and the formation of rust. The
impressed current technique performed in thisexperiment can be a standard for testing the corrosion
resistance of concrete as protection for thereinforcement. It will capture most of the factors suchas the materials constituents, cracks, porosity, andtemperature.
ACKNOWLEDGMENTS
The researchers want to give thanks to the wholeproject team for doing the experiments, Engr. Jaysoon
Macmac, Engr. John Bryan Tiu, Engr. Angelou Faye
Nuñez, Engr. Rafael Reymundo, Engr. Hannah Lou
Argota and Engr. Angel Rose Macapanas. Special
thanks to the Department of Science and Technology
Philippine Council for Industry, Energy, andEmerging Technology Research and Development
for the funding of the project.

72

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

DAMAGE AND SUBMERGED PROBABILITY EVALUATION OF
FLOATING OFFSHORE WIND TURBINES UNDER
WIND AND WAVE ACTIONS
Ken-ichi Fujita1, Harumi Yashiro2
Faculty of Engineering, Nagasaki Institute of Applied Science, Japan;
2
School of Systems Engineering, National Defense Academy of Japan, Japan
1

ABSTRACTThis study presents an evaluation method of damage probability of floating typed offshore wind turbines underwind and wave actions, in addition to submerged probability of blades of the turbines by the inclination of theturbines by the actions. The response of the structure for wind is evaluated by a static analysis, on the other hand,wave response analysis of the structure is evaluated by using a stationary random vibration theory and a wet-mode
superposition method. The random variable of the responses is expressed by linear combination of the results of
response analyses of the structure. The damage probability of the structure is evaluated by using a reliability
evaluation method of structures. Whereas, the submerged probability of blades in the roll motion of the structure
is evaluated by using the results of the response analysis. In the evaluation of the submerged probability, relation
between the stability of the floating base and the inclined moment by wind is used. The dynamic behavior of thefloating wind turbine is analyzed by taking account of a sea water-structure interaction. The sea water region ismodeled by boundary element (BE) and the floating wind turbine is modeled by finite element (FE). Numericalexamples present the damage probability and the submerged probability of large and small scaled floating windturbines for wind and wave actions.
Keywords: Floating offshore wind turbine, Damage probability, Submerged probability, Reliability, Stationary
random vibration
long-term operation.
In this study, to develop a structural risk
evaluation method for wind and wave actions of thewind turbines. an evaluation method of damage
probability of the floating wind turbines andsubmerged probability of blades are presented. The
wind and irregular wave response analyses of thefloating wind turbine are carried out to evaluate theboth probabilities. The wind response is evaluated byusing a static analysis. On the other hand, the irregularwave response is evaluated by using a stationary
random vibration theory and a wet-mode
superposition method [9]. The random variable of the
responses is expressed by linear combination. In the
response analysis, a coupled model of boundary
element (BE) and finite element (FE) is used. The sea
water region is modeled by BE. The offshore windturbine is modeled by FE. In addition, the floatingbase and the tower are discretized by using Mindlin’s
plate elements and beam elements, respectively.
Moreover, the damage probability and the submerged
probability of large and small scaled floating windturbines for wind and wave actions are evaluated.

INTRODUCTION
To promote of utilization of the wind energy is
one of the global goal toward to realization of thedecarbonized society and the carbon neutrality.
Installation of the wind turbines in the sea area
compared with that of on land has several advantage
as follows; no restrictions of scale of wind turbines,
stably utilization of the wind on the sea and extremely
small of the effect of vibration hazard and noisecaused by the rotation of the wind turbine. Moreover,installation at the deep ocean can be available byselecting the floating type.
In planning and design of floating wind turbines,
selection of structural type, evaluations of the motion
and the structural strength are important because thestructures are always oscillating and moving by wind
and wave actions. The dynamic behavior of thefloating wind turbines for wind and wave have been
investigated in many studies [1]-[6]. Moreover, froma view point of long-term operation, dynamic
behavior of floating wind turbine considered partiallydamage of structural element have been studied [7][8]. However, studies on structural risk for wind andwave of offshore wind turbines have not seen, such asa seismic risk evaluation for on structures on land.
The structural risk evaluation of the wind turbine canbe considered to be necessary from a view point of

ANALYTICAL MODEL AND CONDITIONS
The floating wind turbine in this study is shown in
Fig.1. The global coordinate system x-y-z is used. The
73

SEE-Mie, Japan, Nov.10-12, 2022yWind ResponseL

The wind load acting on the floating wind turbine
is evaluated statically. The equation of equilibrium of
the floating wind turbine for wind load is given by

L



O

Wave and winddirectionzx([K S ]  [ KW ]){U }  {FW }where [KS](NPxNP) the stiffness matrix of the windturbine, [KW](NPxNP) is the hydrostatic stiffness
matrix, {U}(NPx1) is the displacement vector of thefloating wind turbine, {FW}(NPx1) is the wind load
vector and NP is the total number of degrees-offreedom of the floating wind turbine.
The wind pressure, PW, acting on the wind turbine
and the wind speed, Vz, at a height of z above the sea
surface are given by the following equations,
respectively.

Wind
DR
LT
H Wave
O
d

(1)

dr

x

D

Fig.1 Geometric parameters of a floating offshore
wind turbine

PW ( z )   AVz2Cd / 2(2)

Vz / V0  ( z / z0 )1 / n(3)where A is the mass density of air, Cd is the dragcoefficient, V0 is the mean velocity at a reference
height z0, 1/n is the exponential of the power row. In
this study, A=1.22kg/m3, Cd=0.7 and n=7 are used.

origin is placed on the still water surface. The floatingbase has a square plane and the base has no moorings.
The tower has cylindrical cross section and uniform
outer diameter. In this figure, L, D and dr are thelength, depth and draft of the floating base,respectively, LT is the length of the tower, DR is thediameter of the rotor, d is the depth of sea water, H is
the wave height and  is the incident angle of wind
and wave.
The analytical conditions used in this study are as
follows:
1) The motion of the floating wind turbines isgoverned by a linear random vibration theory.
2) The sea water is inviscid, incompressible andirrotational.
3) The irregular wave is followed to an ergodic
process with mean value zero.
4) The strength and response of the floating windturbines follows normal distribution.
5) The wind and wave are incident from the same
direction.
6) The wind load is not acted on the floating base.

Irregular Wave Response
Irregular wave and wave spectrum
The profile of incident irregular wave profile of hcan be expressed by sum of a large number of wave
components.
h   2S ( j )
j 1

 exp[i{ j t  k j ( x cos  y sin )   j }] (4)where i is the imaginary unit, t is the time, j, kj andj are the circular frequency, wave number and phaseof j-th wave, respectively, and =j+1-j-1. S() is
Pierson-Moskovitz wave spectrum given by a mean
wind speed V0 at 19.5m height above the sea surface.

S ( )   ( g 2 /  5 ) exp  ( g / V0 )4 

RESPONSE EVALUATION OF FLOATING
WIND TURBINES(5)

where =8.10x10-3, =0.74 and g is the gravitational
acceleration.

The wind response of the floating wind turbine isevaluated by a linear static analysis. The irregularwave response is evaluated by using a stationary
random vibration theory. Sea water-structureinteraction is considered in the wave response
analysis.

Stationary random vibration
The equation of motion of the floating windturbine taking account of the sea water-structure74

SEE-Mie, Japan, Nov.10-12, 2022

{U} and [SF()](NMxNM) is the cross-spectra
density function of the generalized force expressed by
the following equation.

interaction is given by the following equation:([M S ]  [ M W ]){U}  ([CS ]  [CW ]){U }([K S ]  [ KW ]){U }  {FWE }(6)[S F ( )]  E[{Q(i )}{Q* (i )}T ]where [MS](NPxNP) and [CS](NPxNP) are the massand damping matrices of the floating wind turbine,
respectively, [MW](NPxNP) and [CW](NPxNP) are
the added mass and radiation wave damping matrices,
respectively, {FEW} is the wave exciting force and   / t . [MW], [CW] and {FEW} can be evaluated byBE.
The displacement vector, {U}, can be given bymultiplying wet-mode shape matrix [](NPxNM)
obtained by eigenvalue analysis of Eq. (6) andgeneralized coordinate vector {q}(NMx1). In addition,
NM is the number of mode superposition.
{U }  [ ]{q}The variance of the internal force of the floating
wind turbine can be evaluated by the same method.
DAMAGE PROBABILITY EVALUATION OF
WIND TURBINES
The damage probability of the wind turbine forwind and wave is evaluated by using probability
density functions of yield strength and internal force.
The functions can be obtained from random variablesof the yield strength and the internal force.
The damage mode considered in this study is acombined stress of compressive force and bending
moment at the base of the tower. A performance
function, Z, with respect to the damage by the
combined stress can be defined as(7)

The generalized coordinate vector, {q}, is
obtained from the following equation:{q}  [ H (i )]{Q (i )}Z  1  (SC / RC  S B / RB )

(8)

(9)

where [M](NMxNM), [C](NMxNM) and [K](NMxNM) are the generalized mass, damping and stiffness
matrices, respectively.
The variance of the floating wind turbine can beevaluated by integrating the cross power spectrum
density function obtained from Fourier transform of
autocorrelation function of the response over theentire circular frequency region.
The variance, U 2j (j=1,2, … ,NP), of thedisplacement response is obtained from the following
equation:
U 2j 

 S ( )d0

Ujj

SUBMERGED PROBABILITY EVALUATIONOF BLADES
Submerge of the blade is assumed to be occurredin the roll motion (incident direction =90deg) of thefloating wind turbine. The submerged probability inthis study is defined as the probability that the edgeof the blade is on a circular arc of a fan-shaped ofunderwater part as shown in Fig.2. In this figure, B
is the angle between the blades, C is the central angleof the fan-shaped and Rx is the roll angle in the motionof the floating wind turbine.
The submerged probability, pWC, of the blade inthis study can be expressed by the following equation:(10)

where SUjj() is the diagonal component of the crossspectral density function matrix, [SU()](NPxNP),
expressed by the following equation:[SU ( )]  E[{U (i )}{U * (i )}T ] [ ][ H (i )][S F ( )][H * (i )]T [ ]T(13)

where SC and SB are the random variations of thecompressive force and the bending moment at thebase of the tower occurred by wind and wave actions,
respectively, and RC and RB are the random variationsof the buckling strength and the yield bending
strength of the tower, respectively.
SC and SB can be expressed by linear combinationof static and dynamic analyses results. RC and RB are
evaluated by using a statistical data on yield strengthof steel. The damage occurs when Z in Eq. (13)becomes less than zero. The damage probability isevaluated by using an Advanced First-Order SecondMoment (AFOSM).

where {Q(i)}(NMx1) is the generalized force vector
and [H(i)](NMxNM) is the frequency response
function given by the following equation:[ H (i )]  ( 2[M ]  i[C ]  [ K ])1

(12)

(11)

pWC  C /  B

where E[ ] is the expected value, * is the complex
conjugate, {U(i)}(NPx1) is Fourier transform of(14)

The roll angle, C, can be evaluated by sum of the rollangles for wind and wave. The mean value, Rxw, of75

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Specification of analytical model
Item
Length of floating base
Depth of floating baseDraft of floating base

θB

Symbol (Unit)
L (m)
D (m)
d r (m)θC

Poisson's ratio
Total mass of overall structurem S (kg)

6.151×10

Tower length (above deck)
Mass of tower

L T (m)m T (kg)

Mass of nacel, hub and bladesm B (kg)

Steel grade

Tower

LT=70m

SM490

4,000×22mm

962.402×10

670
128×103

160×1032.058×10
0.3
7850
50
1025

11

Mean

Standard deviation

2(N/mm )

(N/mm )

2

361.865

34.421

Wave spectrum

Floating baseL-modelS-modelFig.3 Mesh discretization of analysis model
the roll angle by wave can be described by using thestandard deviation, , of the roll. The probability
density function of the envelope of the wave response
in time domain assumed to be follow Rayleighdistribution.
Rxw  1.253 

100
10
1
0.1
0.01
0.001

Vz=60m/s
50m/s
40m/s
30m/s
25m/s
20m/s
15m/s
10m/s

0.0001
0.01

S-4th, 5th

1000

L-4th, 5th

10000

L-3rd

0deg

25m
S( ) (m2s)

40m●:Set point of tower

S-1st,
2nd
L-1st, 2nd
S-3rd

4,000×25mm
40m

25m

72.5m

4,000×16mm

0deg

5.926×10
0.3

5.789×10
0.3

Table 2 Mean and standard deviation of yieldstrength

Section 4,000×12mm

Wind
and
wave
direction

92

Young's modulus of wind turbine E (N/m2)
 
Poisson's ratio of wind turbine
3
Mass density of tower T (kg/m )Depth of sea waterd (m)3Mass density of sea water
 W (kg/m )Fig.2 Definition of Rx, B, C in evaluation ofsubmerged probability

4,000×19mm

S-model2553.75

E p (N/m ) p 

Young's modulus

Rx

L-model
40
5
3.75

0.1
1
Circular frequecy of wave  (rad/s)

10

Fig.4 Pierson-Moskowitz wave spectrum
and non-operation are shown in Table 1. The wind
and wave directions are zero degrees for the damage
evaluation and 90 degrees for the submerged
evaluation, respectively.
The mean value and standard deviation of SM490
class steel used to the tower is shown in Table 2. The
wave spectrum used in this study are shown in Fig.4.
In this figure, natural circular frequency up to the fifthmode by sea water-structure coupled free vibration
analysis of models is plotted by straight lines.

(15)

EVALUATION RESULTS AND DISCUSSION
Analytical Model
The damage probability of tower and thesubmerged probability of blade are evaluated byusing the proposed method. The target model is 3MW
wind turbine set on two-types floating base (L-modeland S-model) of different scales. The discretization ofanalytical models and the specifications of thefloating wind turbine are shown in Fig.3 and Table 1,
respectively. In the analysis, blades, hub and nacelleof the wind turbine are modeled as one concentratedmass. The wind speeds, Vz, at height of the hub above
still sea surface (HT=71.25m) are 10, 15, 20 and
25m/s for operation and 30, 40, 50 and 60m/s for nonoperation. Projected areas of the rotor in operation

Response Analysis Results
The bending moment distributions in wind on thecenter line in the both models are shown in Fig.5. The
maximum bending moment occurs at the base of thetower. The difference of the bending moment
distribution and magnitude between the both models
cannot be seen. The magnitude of the bending
moment in the operation is larger because the76

SEE-Mie, Japan, Nov.10-12, 2022

Vz=60m/s
Vz=40m/s

Vz=20m/s
Vz=10m/s

Operation70

Non-operation

70z(m), Mx (×10MNꞏm/m)

Wind

50
40
30
20

z(m), Mx (×10MNꞏm/m)

60

60

Wind

50
40
30
20

Vz=60m/s
Vz=40m/s
80

Operation

70

70

60

60

50
40
30
20

Wave

30
20

0

0

0

0

-10

-10

-50-40-30-20-10 0 10 20 30 40 50-50-40-30-20-10 0 10 20 30 40 50-50-40-30-20-10 0 10 20 30 40 50

x(m), My (×10MNꞏm)x(m), My (×10MNꞏm)x(m), My (×10MNꞏm)(a) L-model
Vz=25m/s
Vz=15m/s

70

Vz=20m/s
Vz=10m/s
80

Operation70

V=60m/s
V=40m/s

Vz=25m/s
Vz=15m/s

V=50m/s
V=30m/s

80

Non-operation

70z(m), Mx (×10MNꞏm/m)

Wind

40
30
20

Wind

80

Operation

70

50
40
30
20

40
30
20

10

10

0

0

0

Wave

-10

-10
-50-40-30-20-10 0 10 20 30 40 50-50-40-30-20-10 0 10 20 30 40 50-50-40-30-20-10 0 10 20 30 40 50

x(m), My (×10MNꞏm)x(m), My (×10MNꞏm)x(m), My (×10MNꞏm)(b) S-model

Vz=50m/s
Vz=30m/s

Non-operation

60

50

10

-10

Vz=60m/s
Vz=40m/s

Vz=20m/s
Vz=10m/s

60

60

60
50

(a) L-modelz(m), Mx (×10MNꞏm/m)

80

Wave

10

10

-10

Non
-operation40

10-50-40-30-20-10 0 10 20 30 40 50
x(m), My (×10MNꞏm)

Vz=50m/s
Vz=30m/s

50

10

-10

z(m), Mx (×10MNꞏm/m)

Vz=20m/s
Vz=10m/sz(m), Mx (×10MNꞏm/m)z(m), Mx (×10MNꞏm/m)

80

80

80

Vz=25m/s
Vz=15m/s

Vz=50m/s
Vz=30m/sz(m), Mx (×10MNꞏm/m)

Vz=25m/s
Vz=15m/s

50
40
30
20
10
0

Wave

-10
-50-40-30-20-10 0 10 20 30 40 50
x(m), My (×10MNꞏm)(b) S-model

Fig.5 Bending moment distribution in wind

Fig.6 Standard deviation of bending moment
distribution in irregular wave

projection area of rotor in the operation is large.
The standard deviations of the bending moment
distributions in irregular wave of the models areshown in Fig.6. The bending moment in S-model
becomes larger than that of L-model because of large
motions induced on S-model. In the non-operation,
the difference of the bending moment in the irregularwave is small because the pitch motion in longwavelength becomes small for small scaled floating
structures.

be evaluated by using the cross-sectional
performance of the tower and the random variables ofsteel shown in Table 2. The random variables ofstrengths are shown in Table 3.
The damage probability at the base of the tower ofthe both models for several wind speeds is shown in
Fig.7. The probabilities between L-model and Smodel have difference value though the specificationsof the tower are same. The difference of theprobability depends on the size of the floating base.
The probability becomes high for the both models in
the operation because of large projection area forwind. The probability of the tower on S-model in the
non-operation becomes high because the pitch motion
in relatively small scaled floating structures tends tobe excited easily by wind and wave.

Damage Probability of Wind Turbine
In evaluation of the damage probability of thetower, the random variable of the internal force canbe evaluated by linear combination of the results of
response analysis for wind and wave. The mean value
and the standard deviation can be evaluated by theinternal force obtained by the wind response andirregular response analyses, respectively. The meanvalue and the standard deviation of the strength can

Submerged Probability of Blades
The submerged probability is evaluated by using77

SEE-Mie, Japan, Nov.10-12, 2022

1

Strength
Buckling
RC
BendingRB

MeanStandard deviation

4.535×10MN

0.431×10MN

Operation

L-modelS-model

0.8
0.6
0.4
0.2
0

11.157×10MN·m 1.061×10MN·m

20

Non-operation

1
Damage probability

Submerged probability

Table 3 Mean and standard deviation of allowable
yield strength

30

40
50
Wind speed (m/s)

60

70

Fig.8 Submerged probability of blades

L-modelS-model

0.8

Proceedings of 12th International Conference onWind Engineering, 2007.
[2] Hu C., Sueyoshi M., Liu C. and Liu Y.,
Hydrodynamic Analysis of a Semi-SubmersibleType Floating Wind Turbine, Journal of Ocean
and Wind Energy, Vol.1, No.4, 2011, pp.202208.
[3] Myhr A. and Nygaard T.A., Comparison ofExperimental Results and Computations for
Tension-Leg-Buoy Offshore Wind Turbines,
Journal of Ocean and Wind Energy, Vol.2, No.1,
2015, pp.12-20.
[4] Wehmeyer C. and Rasmussen J.H., Mooring
Response of a Floating Offshore Wind Turbine
in Nonlinear Irregular Waves, Journal of Ocean
and Wind Energy, Vol.2, No.1, 2015, pp.37-44.
[5] Mantadakis N., Loukogeorgaki E. and Karimirad
M., Accounting for Hydroelasticity in the
Analysis of Offshore Wind Turbine Spar-Type
Platforms, International Journal of Offshore andPolar Engineering, Vol.31, No. 1, 2021, pp.121128.
[6] Suzuki H., Xiong J., do Carmo L.H.S., Vieira
D.P., de Mello P.C., Malta E.B., Simos A.N.,
Hirabayashi S. and Gonçavelos R.T., Elastic
Response of a Light-Weight Floating Support
Structure of FOWT with Guywire Supported
Tower, Journal of Marine Science andTechnology, Vol.24, 2019, pp.1015-1028.
[7] Bae Y.H. and Kim M.H., The Dynamic Coupling
Effects of a MUFOWAT (Multiple Unit Floating
Offshore Wind Turbine) with Partially Broken
Blade, Journal of Ocean and Wind Energy, Vol.2,
No.2, 2015, pp.89-97.
[8] Karimirad M. and Michailides., Fault Condition
effects on the Dynamic Response of V-Shaped
Offshore Wind Turbine, Journal of Marine
Science and Technology, Vol.24, 2019, pp.34-45.
[9] Hamamoto T. and Fujita K., Wet-ModeSuperposition for Evaluating the Hydroelastic
Response of Floating Structures with Arbitrary
Shape, Proceedings of the 12th International
Offshore and Polar Engineering Conference,
2002, pp.290-297.

0.6
0.4
0.2
0
0

10

20

30
40
50
Wind speed (m/s)

60

70

Fig.7 Damage probability at base of tower
the roll angle obtained from the response analysis
results. The probability of the both models in the nonoperation is shown in Fig.8.
The probability of S-model becomes large withincreasing of wind speed. However, the probability of
L-model is extremely small. It can be considered thatthe roll motion in large scaled floating structures
tends to be not excited by wind and wave.
CONCLUSIONS
An evaluation method of the damage and thesubmerged probabilities of the floating wind turbine
for wind and wave are proposed. The summary of thisstudy can be drawn as follows.
1) The damage probability of the floating windturbine in operation depends on the size of the
projection area for wind. On the other hand, theprobability in non-operation depends on the scaleof the floating base.
2) The submerged probability of blade depends on
the scale of the floating base. For small floating
base, the probability becomes high withincreasing of wind speeds.
3) Bending moment occurred in wind tower isdominated by magnitude of the roll and pitch
motions of the floating wind turbine.
REFERENCES[1] Phuc P.V. and Ishihara T., A Study on the
Dynamic Response of a Floating Offshore Wind
Turbine System Part 2: Numerical Simulation,78

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

RESILIENCE ASSESSMENT OF A FIVE-STOREY SOCIALIZEDHOUSING USING THE REDI RATING SYSTEMJohn Pol A. Aguilar1, Wilfed A. Chan2, Ted Marius U. Delos Reyes3, *Richard M. De Jesus4, *Rodolfo
P. Mendoza Jr.5 and *Kenneth Roi P. Toral6
1,2,3,4,5,6
Faculty of Engineering, De La Salle University (Manila), Philippines

ABSTRACTSocialized housing is a government-backed initiative to provide affordable housing for the marginalized
sector. Due to their low-cost nature, its structural integrity is often compromised under natural disasters.
Currently, socialized housing in the Philippines is built using the code-based design (CBD) philosophy, where
life safety is the priority regardless of the damage the building will sustain. Therefore, frequent shaking
experienced by the country often leads to irreversible building damage and costly repairs. Resilience-based
design (RBD) extends beyond life-safety by considering the repair consequences under a site-specific, designlevel shaking. This study utilizes the REDi framework to determine the resilience level of the structure, in
conjunction with the software SeismoStruct for structural analysis and PACT for loss estimation. As a casestudy, the standard, five-storey, low-rise socialized housing structure in the Philippines were evaluated for theirseismic resilience using the REDi methodology. The study found that the Philippine low-rise socialized
housing structure is not seismically resilient.
Keywords: Earthquake; Resilience; Infill wall; Sandwich panel; Philippine socialized housing
INTRODUCTION

by the National Housing Authority (NHA) is
analyzed in this study where it follows theprovisions stated in the National Structural Code of
the Philippines. The code-based design lacks theconsideration for building protection and recovery
which is addressed in a resilience-based design(RBD) philosophy.
The REDi Rating System that was developed by
Arup is a tiered ranking approach resilienceevaluation that classifies the seismic resilience of astructure into three levels of increasing resilience –Silver, Gold, and Platinum. The framework isdividedinto
four
resilience
categories:
Organizational Resilience, Building Resilience,
Ambient Resilience, and Loss Assessment. The first
three categories evaluate the seismic resilience ofthe building, the contingency measures within thefacility in case of disasters, and the impact of theenvironment and adjacent structure on thebuilding’s vulnerability to earthquakes. The Loss
Assessment can be further subdivided into the
Direct Financial Loss Assessment for the probablefinancial losses with a design level earthquake, andthe Downtime Assessment which evaluates theperiod where the building would be unusable due torepairs, utility disruption and delays.
This study aimed to identify the seismic
resilience, calculate the expected financial loss,
repair time, injuries, casualties, and estimate the reoccupancy and recovery times of the existing
standard five-storey low-rise socialized housing in
the Philippines based on the REDi Framework.

The Philippines is along the pacific ring of fire
and is frequented by strong earthquakes for the past
decade causing severe infrastructure damage andhigh casualties. Residential structures are found tobe the most susceptible to damage, especially thosethat are not designed to withstand earthquakes [1].
Socialized housing is a kind of residential structurethat are awarded to the poorest of the poor which
are less capable in mitigating seismic risks. As such,natural disasters often result to an increase inpoverty, higher casualties, and a higher amount ofdestroyed dwellings in this sector [2].

Fig. 1

NHA Low-rise
Structure.

Socialized

HousingCaloocan City has the highest share ofsocialized housing units in the Philippines and all ofwhich are classified as a five-storey low-risebuilding [3]. The standard design of such structures
79SEE-Mie, Japan, Nov.10-12, 2022

are assessed from the average damage states forbeam-column joints, masonry wall, stairs, lighting,and distribution panel derived from the PACT loss
assessment, which is formulated in Chapter 3.4.

RESEARCH SIGNIFICANCE
This study can serve as a basis for the
improvement of the housing facility and community
measures to be used on similar projects in the future.
In the societal level, this provides confidence thatthe local infrastructures can secure public
investments and serve the general public’s interestof providing safe and equitable homes for the poor.
The ninth Sustainable Development Goal (SDG)
created by the United Nations is also addressedwhich advocates the creation of resilient
infrastructures,promotessustainableindustrialization, and fosters innovation [4].

Ambient Resilience
Hazard maps were used to identify the possible
earthquake-induced hazards that may affect thebuilding’s seismic performance which wereobtained through Hazard Hunter and the Metro
Manila Hazard Susceptibility Map provided by thePhilippine Institute of Volcanology and Seismology.
Professional interview with the NHA
representative and building contractor was done toinquire for the proximity of surrounding buildings
and non-building installations. Seismic hazards in
Caloocan City were analyzed before assessing theresiliency of the building against such natural
hazards. The design specifically studies the possible
tsunami and liquefaction hazards of the building
which either have a higher ground level for the
possibility of a tsunami or a deeper foundation thatreaches the bedrock for those that are susceptible toliquefaction. In the interview, it was asked if thedesign was adequate and complies with standard
protocols in mitigating damage due to said hazards.

METHODOLOGYAs a case study, a five-storey socialized housingbuilding located in Caloocan City, Philippines isused. The components of the REDi Rating
Assessment are discussed in the following chapters.
Organizational Resilience
Qualified professionals were interviewed toassess the level of contingency planning set in place
for the building occupants. The interviewees werethe contractor of the socialized housing project andthe senior engineer for NHA – Caloocan District
Office which were both knowledgeable with theoperations and protocols employed within thebuilding. A site investigation was done to verify thatthe results of the interview were accurate and were
implemented within the actual building. The
investigation verifies whether the facilities within
the building are still usable and are in goodcondition, the placement of emergency kits within
the building, presence of non-structural component
within that may injure the occupants, and presenceof safe egress space. Evaluating possible areas ofcongestion were identified in the investigation
through the number of occupants per room.

Direct Financial Loss Assessment
The building information model using the
Performance Assessment Calculation Tool (PACT)
is defined to calculate the expected repair costs,
repair time, injuries and fatalities for the structure
under a design level earthquake. This utilizes theMonte Carlo simulation account for uncertainties inthe structural model and its seismic response.

Building Resilience
The structure was modelled using an inelastic
force-based frame element with plastic hinges using
SeismoStruct. Mander et al. [5] concrete andMenegotto-Pinto [6] steel model was used to define
the material properties. Non-linear static pushover
analysis was conducted to determine the structure’s
drift capacity while an Eigenvalue analysis is done
to calculate the building weight and fundamental
period. A site-specific response spectrum based on
the 50-year return period, Design Level Earthquake(DLE) are required as input to SeismoStruct, which
is developed from the geotechnical data andseismicity maps for the site. Component damages

Fig. 2

PACT Building Information Tab

The structure is composed of five stories, with afloor area of 3,997.71 sf and a story height of 8.86
ft. The total replacement cost is USD 959,099.73
while the estimated replacement time is around 240
days. The Multi-Residential population model used
has a peak of 3.1 occupants per 100 sf is used.
Component fragility functions defines theprobable repair costs and time for each sequential
damage state of each damageable component.
Repair cost and time data for common building
components in the Philippines are used in this study80SEE-Mie, Japan, Nov.10-12, 2022[7]. Components are classified as either drift- or
acceleration-sensitive, and fragility quantities per
floor are obtained from the structural plans.
Fragility curves, which models the probabilityof collapse at different values of the spectral
acceleration, are derived from the pushover curves
and generated using SPO2FRAG [8]. This is a
MATLAB-based tool that predicts the Incremental
Dynamic Analysis (IDA) results for an equivalent
single degree-of-freedom (SDOF) system using thestructure’s pushover and Eigenvalue properties.

[10]. Three delay paths were determined in which
the longest governed this downtime source.
Downtime due to utility disruption constitutes
the restoration of electrical, water, and natural gas
systems. In determining the disruption time ofelectrical systems, the REDi methodology suggests
the use of achieving 50% recovery in the disruption
curve. For water and natural gas systems, the peakground velocity (PGV) and dominant seismic wave
(i.e., either R or S-waves) for Metro Manila wasused [11]. This was used to calculate the repair rate
(in repairs/km) which was then used to determine
the disruption times from the disruption curves.
The total downtime was plotted on a Gantt chart
to visualize the downtime schedule for a specific
recovery state.
RESULTS AND DISCUSSION

Fig. 3

The final rating for each resilience categories
were determined by the lowest rating across all thecriteria under each resilience category. For
organizational resilience, as shown in Table 1, it
was rated silver due to the lack of earthquake
preparedness, low-use fixtures, back-up power, andsecurity systems installations as required by FEMA.
For building resilience, Table 2 shows that the
final rating is not resilient. This is due to the residual
drift in a certain floor exceeding the maximum
permissible drift of 0.5%, when subjected to seismic
loads in the X-direction.
For ambient resilience, the governing rating isgold, as shown in Table 3, due to the insufficientvisual and geotechnical tests conducted ascompared to the prescribed rapid visual screening
scoring methodology by FEMA 154.
The loss estimates from PACT will be discussed
below. The median repair cost for the socialized
housing structure under a DLE is USD 42,988. Fig.
4 shows that the highest share in repair costs is due
to damage in the beam-column joints, at 60.89% of
the total repair costs, and is concentrated at the
ground floor only. Masonry walls account for thesecond highest repair cost among building
components, at 38.05% of the total cost. Repair costfor other components is significantly lower than the
repair cost for the frame joints and masonry walls.

Structural Fragility Curve.

Lastly, the story drift ratio and peak floor
acceleration at each floor, when subjected topushover loading at the DLE shaking intensity, aredefined. The structural analysis calculations follow
the Intensity-based Assessment: Simplified
Analysis procedure of FEMA P-58 [9].
Downtime Assessment
Weighted average damage states and thecorresponding repair classes were determined using
PACT’s pre-defined fragility database. For asocialized housing structure, the priority recovery
state is re-occupancy and functional recovery. Reoccupancy indicates that heavy damage that poses arisk to life-safety had occurred to the structural or
non-structural building components. Functional
recovery indicates damage occurred on the nonstructural components only. Although it does notpose a life-safety risk, repair is still required.
The downtime assessment consists of threedowntime sources: due to repair, due to delay, and,due to utility disruption. Downtime due to repairs
constitutes the actual repair time of damaged
components, which is dependent on the repair
sequence and schedule. Initially, the structural andnon-structural repair times were obtained. The
number of workers and repair time distribution per
floor was calculated based on the floor area andrepair sequence.
Downtime due to delays constitutes the delaysin the initiation or completion of repairs.
Professional interviews were conducted todetermine the impeding curve per impeding factor.
Given this, the median delays were determinedbased on the framework by Almufti and Willford

Fig. 4
81

Repair Cost Distribution per Component.

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 REDi Assessment for Organizational Resilience
Resilience Criteria

RatingResilience Workshop

P

Back-up Utility Lines
Low-use Fixtures
Security

G
GS

Long-lead Time Items

P

Food and Water
Preparedness Training

S
G

Remarks
Meetings about structural integrity and insurances were done.
Earthquake drills and safety protocols were conducted.
Back-up power were only for Sewage Treatment Plants (STPs).
No low-flow faucets and bulbs being used were CFL.
No CCTVs nor alarm systems in the building only guards.
STP generator sets can be replaced within 2 weeks to 1 month,and circuit breakers and panels within 1 month.
No readily available supply on site.
Does not conduct earthquake drills, but first aid kits are present.

Table 2 REDI Assessment for Building Resilience
Resilience Criteria
Design Level Earthquake
Code Minimum
Requirements
Design Demands
Minimize Structural
DamageRatingP

P

Remarks
Response spectra is based on DLE (50 YRP from site PSHA).
Structural design is compliant with NSCP 2010. Structure passed
the ASCE 41-17 code check for shear and chord rotation.
Response spectra for pushover analysis is based on the DLE.

S

Average DS for beam-column joints is more than 1 (DS=2.68).

Minimize Residual DriftNR

Minimize Non-structural
DamageP

Equipment Functionality

S

Protect Facades
Anchor Heavy Building
Contents
StairsS

Simulation Model

P

Structural Peer Review

P

Installation of Nonstructural components

P

P

P
P

Residual drift at the 4th floor (along X-axis) is more than 0.5%
(Δ=1.03%).
Average DS for all non-structural components are less than 1.
Maximum average DS at stairs (DS=0.94).
Replacement time for the distribution panel is less than 6 months.
Panel’s shake table qualification cannot be verified.
Average DS for masonry wall is more than 1 (DS=2.00).
Distribution panels, transformers, and fire control systems areanchored to the wall. Compliant with FEMA-E-74 standards.
Average DS for stairs is less than 1 (DS=0.94).
SeismoStruct model is 3D. Analysis follows the performancebased requirements of FEMA P-58 and ASCE 41-17.
Structural engineers and consultants conduct peer reviews during
the planning phase.
General contractor inspects the compliance of completed works
with drawings and technical specifications required by the client.

Table 3 REDI Assessment for Ambient Resilience
Resilience Criteria
Design for Liquefaction
High Liquefaction
HazardRatingP

Other Ground Failures

P

High Tsunami Hazard
Assessment ofSurrounding Building
High Hazard from
Surrounding Building

P

P

G
G

Remarks
Safe from liquefaction hazard.
Not susceptible to liquefaction.
Nearest dam is approximately 7.5 km away. Safe fromLandslides and Ground Rupture. Low flood susceptibility.
Not within inundation area. Less than 0.5 meters flood height.
Initial visual and geotechnical test before construction was done
but not based on the Rapid Visual Screening of FEMA.
No readily available supply on site.

82

SEE-Mie, Japan, Nov.10-12, 2022

Table 4 REDI Assessment for Loss Assessment and REDi Baseline Criteria Objectives
Resilience Criteria
Re-occupancy
Functional Recovery

RatingNR
NR

Direct Financial LossG

Occupant Safety
Utility Disruption

NR
G

Remarks
Re-occupancy of the building would take 247.460 days.
Functional Recovery of the building would take 247.521 days.
The scenario expected loss due to repairs would be 4.63% of thetotal building value.
Injuries are about 8 persons while fatalities are about 3 persons.
Disrupted utility can be restored within 1 month (21 days).

Considering a parallel schedule where repairs
can start simultaneously at all floors, Fig. 5 showsthat the median repair time at the ground floor
governs and is equal to 96.94 days. Masonry walls
and beam-column joints account for majority of therepair time across all floors, at 60.86% and 36.73%
of the total repair time, respectively.

obtaining minimal damage.

Fig. 6

Fig. 5Figure 6 illustrates the total downtime sequence
to achieve re-occupancy. Downtime due to utility
disruption and due to delays can be seen to occur
simultaneously. With this, the latter governs theinitial downtime sequence. Particularly, the second
delay path of post-earthquake inspection, engineer
mobilization/review, and permitting resulted to thelargest delay source, accounting for 145 days. The
downtime due to repair follows. Based on the repair
schedule, the repair downtime resulted to 102.46
days. The cladding repair sequence or repair ofconcrete hollow block (CHB) of this downtime
source was discovered to be the largest among allbuilding components. This indicates that the wallcomponent requires the greatest amount of repair
time. The total downtime for re-occupancy is247.460 days (8 months).

Repair Time Distribution per Component.

Lastly, the expected number of injuries in thebuilding under DLE is equal to 2.27 persons, while
the number of casualties is 7.73 persons.
Table 5 Average Damage State and Repair Class
Component TypeBeam-Column Joint
Masonry Wall
StairsPendant Lighting
Panel Box

Average
Damage State
2.57452.78492.00000.93300.49560.0180Total Downtime for Re-occupancy.

Repair
Class
3
3
1
3
2

Table 5 displays the repair average damage
states and repair classes of the building componentsof the socialized housing. The structural andlighting component resulted to repair class 3. This
indicated that these are the components which needs
to be repaired to achieve a re-occupancy recovery
state. The panel box falls under repair class 2.
Repair of this component is required to achieve
functional recovery. Lastly, the stairs must undergo
repair to achieve full recovery despite only

Fig. 7

83

Total Downtime for Functional Recovery.

SEE-Mie, Japan, Nov.10-12, 2022

REFERENCES

Figure 7 illustrates the total downtime toachieve functional recovery. As mentioned
previously, in order to achieve functional recovery,building components with repair class 2 must also
be considered. With this, the difference between the
downtime for re-occupancy and functional recovery
is the electrical repair sequence only. Downtime
due to utility disruption and due to delays are
similar with the re-occupancy schedule. The total
downtime for functional recovery is 247.521 days
(8 months).
Table 4 shows a final rating of not resilient for
loss assessment and REDi baseline resilienceobjectives. Both re-occupancy and functional
recovery exceeded the silver rating minimum by 65
days. In the criteria of occupant safety, it was also
deemed not resilient since both physical injuries andfatalities will likely occur.

[1] Garciano, L., & Taclibon, P. (2013). The
October 15, 2013 Bohol Island, Philippines
earthquake and its damaging effects: An
investigative report. Japan Society of Civil
Engineers.
[2] Jia, H., Chen, F., Pan, D., & Zhang, C. (2018,
December 10). The Impact of Earthquake on
Poverty: Learning from the 12 May 2008
Wenchuan Earthquake.
[3] Dungca, J., & Macaraeg, C. (2016).
Development of a Reference for Seismic
Amplification: The Case of Metro Manila. 19th
Congress of International Association for
Bridge and Structural Engineering. Stockholm,
Sweden.
[4] United
Nations.
(2015).
Sustainable
Development
Goals.
Retrievedfromhttps://www.undp.org/sustainabledevelopment-goals#industry-innovation-andinfrastructure[5] Mander, J., Priestley, M., & Park, R. (1988).
Theoretical stress-strain model for confinedconcrete. Journal of Structural Engineering, 30,
1804-1826.
[6] Menegotto, M., & Pinto, P. (1973). Method ofanalysis for cyclically loaded R.C. plane frames
including changes in geometry and non-elastic
behaviour of elements under combined normal
force and bending. Symposium on theResistance and Ultimate Deformability ofStructures Acted on by Well Defined RepeatedLoads, 15-22.
[7] Ausan, R., Cabatit, K., Quiaem, M., & De Jesus,
R. (2019). Resiliency of a Four-storey Standard
School Building Using the REDi Framework.
International Journal of GEOMATE, 7.
[8] Baltzopoulos G., Baraschino R., Iervolino I.,
Vamvatsikos D. (2017) SPO2FRAG: Software
for seismic fragility assessment based on static
pushover. Bulletin of Earthquake Engineering.
[9] Applied Technology Council. (2017). FEMA P58: Seismic Performance Assessment of
Buildings. U.S. Department of Homeland
Security, Federal Emergency Management
Agency, Washington D.C.
[10] Almufti, I., & Willford, M. (2013). REDi™
Rating System: Resilience-based Earthquake
Design Initiative for the Next Generation of
Buildings[11] Torregosa, R., Sugito, M., & Nojima, N. (2001).
Strong Motion Simulation for the Philippines
Based on Seismic Hazard Assessment. Journalof Natural Disaster Science, 33-51

CONCLUSIONSInfrastructure damage and structural collapse
due to seismic events are prevalent in thePhilippines. Numerous design paradigms inbuilding construction has paved the way for
different results and improvements in the structural
life and design. In this study, it focused on theresilience-based design. This design paradigm
focuses on the ability of a community to reduce theprobability of structural failure and consequences.
In addition to this, the level of damage associatedwith the repair time has also been consideredespecially in terms of how long it would take thebuilding to perform its original function or purpose.
With the use of the REDi Rating System, thestandard five-storey low-rise socialized housing in
the Philippines was assessed using a design level
earthquake in terms of organizational resilience,building resilience, ambient resilience, and loss
assessment. It was therefore concluded that thebuilding was deemed not resilient based on theREDi Framework. The building failed to achieve a
resilient rating in terms of building resilience andloss assessment, particularly on the downtime
assessment and occupant safety criteria.
ACKNOWLEDGMENTS
The researchers would like to extend their
gratitude to the building contractor, E.M. Cuerpo
Inc., and the National Housing Authority Caloocan
District Office for providing their time andexpertise, which are vital to the completion of thisresearch endeavor.

84

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE EFFECT OF TSUNAMI LOAD ON PRAYOGA FOREIGNLANGUAGE COLLEGE IN PADANG CITY, INDONESIA
Fauzan1, Ferdy Muhammad Ikhwan1, Dyan Adhitya Nugraha M1 and Zev Al Jauhari2
1
Engineering Faculty, Andalas University, Indonesia
2
Department of Civil Engineering, Bengkalis Polythecnic, Indonesia

ABSTRACT
Padang as the capital city of West Sumatra is located on coastal areas and has a high level of tsunami disaster
vulnerability (High Risk Zone). Therefore, public buildings in Padang city must have certain technical engineeringso as to reduce the risk of structural failure. One of the public buildings that needs to be considered as an
educational facility in Padang city is the Prayoga Foreign Language College (STBA) building. Based on the resultsof an evaluation conducted by the Andalas University assessment team, the Prayoga STBA building was designed
without taking into account the tsunami loads. Therefore, it is necessary to re-analyze the building by taking into
account the tsunami loads. In this study, the building was analyzed using ETABS v.18.1.1 software with reference
to current Indonesian building standards such as SNI 2847:2019 for building structural concrete requirements, SNI
1726:2019 for earthquake resistance building design, SNI 1727:2020 for minimum design load for buildings, andinternational standard of FEMA P646-2019 for tsunami loads calculation. The results of the analysis show that thebuilding is able to withstand the earthquake load, but the capacity of the building is insufficient when the tsunami
loads are applied to the structure. The beams and columns on the 1st and 2nd floors do not have strong enoughcapacity to resist the tsunami loads, so there is a possibility of structural failure. The effect of tsunami loads on theinternal forces and other structural responses of the building is also discussed in this paper.
Keywords: Tsunami, Evaluation, capacity, ETABSINTRODUCTION

which is very vulnerable and will have a very impact
if there is a tsunami hit Padang city. Therefore, it isnecessary to know whether the STBA Prayoga
building can withstand the combined earthquake andtsunami loads, as well as the impact that occurred dueto the tsunami loads. Previously, the STBA Prayoga
building had been evaluated by the Andalas
University (UNAND) assessment team using theprevious building codes. Based on previous
evaluation data by UNAND assessment team, thisbuilding was designed without taking into account thetsunami loads. Therefore, a structural evaluation of
the building using the current Indonesian building
codes and international code of FEMA for tsunami
vertical evacuation structure should be carried out by
taking into account the tsunami loads. This study
foccused on the investigation of tsunami loads effecton the STBA Prayoga building.

Prayoga Foreign Languages College (STBA
Prayoga) building is one of the private colleges
located on Padang city. STBA Prayoga is a
development of the Prayoga Foreign Language
Academy (ABA) which is under the auspices of the
Prayoga Foundation. Indonesia, especially the
Padang city, is an area with an earthquake-prone
category [1]. The Padang city itself has been recorded
to have occurred several large earthquakes, one ofwhich was the Padang earthquake on September 30,
2009 [2], [3]. View of the STBA Prayoga Padangbuilding is shown in Fig. 1.

ANALYSIS AND DISCUSSION
The Location of STBA Prayoga Building

Fig. 1

Based on the data observed using Google Maps,
the location of the STBA Prayoga Building on
Veteran Street, No. 8, West Padang is 450.23m
distance from the shoreline. The location of thebuilding is also around urban areas, offices andresidential areas [4].

STBA Prayoga Building in Padang city.

The STBA Prayoga building is close to the beach85

GEOMATE – Bangkok, Thailand, 22-24 November 2022

The Level of Tsunami Vulnerability
The STBA Prayoga building is located on the redzone (high-risk zone) of the tsunami [1] and the areawith a tsunami inundation depth of 5 m [5].

1. The self-weight of structural elements wascalculated directly by the structure analysis
program ETABS.
2. Super imposed dead load was calculated based on
SNI 1727:2020, as shown in Table 1.

Building Data

Table 1 Dead load on the STBA Prayoga building

STBA Prayoga Building is the five-story building
made of reinforced concrete structures with size 48mlength and 12m width. The yield strength of steel (fy)was 240 MPa and 400 MPa for plain and deformed
reinforcements, respectively, while the compressive
strength of the concrete (fc') was 24.5 MPa. The
dimensions of the structural elements are:1. Beam: B1, G1 (35 x 75cm), B2, G2 (35 x 50cm),
B3 (20 x 30 cm), CG1, G3, G4 and G5 (20 x 75cm)
2. Column: K1, K2, K3 (65 x 65 cm) and K4(40 x 40
cm).

Material type
Plaster
BV plafond
BV ceramics
BV wallLive load

Based on article 4.3.1 of SNI 1727:2020,
explaining the living load used for building planningmust use a maximum living load [7]. Table 2 shows
the live loads on the STBA Prayoga Building.

The Modelling of Building Structure

Table 2 The live loads of the STBA Prayoga building

Structural analysis of the STBA Prayoga Building
was carried out using ETABS software. The columns
and beams of the building structure are modeled asframes, the floor plates are modeled as slab elements,
and the structural walls are modeled as wall elements[6]. The 3D modeling of the building structure wascarried out in accordance with the existing conditionof the current STBA Prayoga Building, as shown Fig.
2.

Fig. 2

Load value
42 kg/m2
20 kg/m2
48 kg/m2
250 kg/m2

Room typeClassrooms
1st floor corridor
Corridor above the 1st floor

Load value
1.92 kN/m2
4.79 kN/m2
3.83 kN/m2

Earthquake load
The spectrum response is used as an analysis ofdynamic earthquake loads. The spectrum response
earthquake load is calculated based on SNI
1726:2019 using the 2019 Indonesian Earthquake
Hazard Map [8]. Therefore, the design spectral
acceleration parameter values for medium soil, thevalue of spectral design SD1 and SDS are 1.0g and
0.68g, respectively. Figure 3 shows the spectrum
response of STBA Prayoga in Padang City withmedium soil conditions.

3D structural modeling of STBA Prayoga.

Loading Analysis
Dead load
Dead loads are obtained from the self-weight ofbuilding materials and building components [7]. The
dead load on the building was calculated using theIndonesian Standards Building, SNI 1727:2020 [7].
The dead loads that work on the STBA Prayoga
Building are:Fig. 386

The graph of spectrum response in Padang
City.

GEOMATE – Bangkok, Thailand, 22-24 November 2022

The spectrum response data are inputted into thestructural modeling, then scale factor calculations are
performed on ETABS using Eq. (1):assumed by additional hydrodynamic force anddepends on the thickness of the layer of debris. To
calculate the debris force, use the Eq. (5).

SF = G. I/R

Fdm = 0,5 ρS cd Bd (hu2 )max

(1)

Where, G is acceleration of gravity, I is building
priority factor and R is response modification
coefficient.

6. Impact load
Impact loads are those that result from debris such as
driftwood, small boats, portions of house, or any
object transported by floodwaters, striking against
buildings and structures [9]. As an approach, thisvalue is calculated by the following Eq. (6).

Tsunami loads
Article 8.8 of FEMA P-646 2019 explains thecalculated loads as follows:

Fi = 1,3 umax √k + md(1 + c)

1. Hydrostatic force
Hydrostatic force is the horizontal force that causedby the water pressure against to a surface. The amountof this force depends on the depth of water [9].
Hydrostatic force can be calculated by the Eq. (2).
Fh = 0,5 ρS g b hmax 2

7. Extra gravity load
Due to the high depreciation rate of water is rapid, it
is likely that there will plenty of water suspended in
the floor, causing the addition of a significant
gravitational force on the floor [9]. Potential extra
load of gravity per unit area can be calculated by theEq. (7).

(2)

Fi = ρS x g x hr

2. Buoyant force
The buoyant forces on a structure subject to partial or
total submergence will act vertically through thecenter of mass of the displaced volume [9]. The
buoyant force on the structure can be calculated by
the Eq. (3).

(7)

Where hr is hmax - 1st floor height.
8. Uplift forces on elevated floors
Uplift hydrodynamic force is given on the top floor of
the tsunami inundation affected [9]. This load can becalculated by the Eq. (8).

(3)
Fu = 0,5 C𝑢 ρ𝑆 Af Uv 2

Where V is the volume of water below the maximum
inundation.

(8)

Where Cu is uplift coefficient, Af is tsunami
inundation area and Uv is hydrodynamic uplift force.
The calculation results of tsunami loads are given in
Table 3.

3.Hydrodynamic force
Hydrodynamic force is a combination of horizontal
forces caused by the compressive force of moving
water and the friction caused by the flow around thestructure [9]. Hydrodynamic force can be calculatedby the Eq. (4).
Fhd = 0,5 ρS cd b (hu2 )max

(6)

Where umax is maximum flow, the volume of water
below the maximum inundation.

Where 𝜌𝑆 is tsunami volume weight, g is accelerationof gravity, b is width that accept the pressure and hmax
is maximum of water height above the wall base.

Fb = ρS g V(5)Table 3 The tsunami loads of the STBA Prayoga
building
Load typeHydrostatic forces
Buoyant forces
Hydrodynamic forces
Surge forces
Floating debris impact forces
Debris load
Extra gravity load
Uplift forces on elevated floors(4)

Where cd is the drag coefficient, h is the depth offlow and u is the flow velocity.

Load value
329.946 kN
17.266 kN/m2
84.077 kN
126.116 kN
447.815 kN
517.398 kN
15.107 kN/m2
8.41x10-6 kN/m2

4.Surge force (impulse force)
Surge forces are caused by the leading edge of a surgeof water impinging on a structure and by the water
wave that comes suddenly. Surge force of the buildingis 1.5 times the hydrodynamic force [9].

Load Combination

5.Debris loadDebris impact is caused by a buildup of debris that

The load combination refers to SNI 1726-2019 forthe combination of loading due to the earthquake, and87

GEOMATE – Bangkok, Thailand, 22-24 November 2022

FEMA P646-2019 for the combination of loading due
to the tsunami loads [8], [9]. The load combination
for this analysis is as follows:
1. 1.4 DL
2. 1.2 DL + 1.6 LL+ 0.5 R
3. 1.2 DL + 1.0 LL ± 1.0 EQx ± 0.3 EQy
4. 1.2 DL + 1.0 LL ± 0.3 EQx ± 1.0 EQy
5. 0.9 DL ± 1.0 EQx ± 0.3 EQy
6. 0.9 DL ± 0.3 EQx ± 1.0 EQy
7. 1.2 DL + 0.25 LL + 1 (FB+FU) + 1 Lref
8. 1.2 DL + 0.25 LL + 1 (FH+FHD) + 1 Lref
9. 1.2 DL + 0.25 LL + 1 (FI+FHD) + 1 Lref
10. 0.9 DL + 1 (FB+FU)
11. 0.9 DL + 1 (FH+FHD)
12. 0.9 DL + 1 (FI+FHD)

impact of the tsunami load is more than the increaseof the inter story drift in the Y-direction, because thedirection of the tsunami comes parallel to the Ydirection so that it has more impact on the X-direction.
CROSS-SECTIONAL CAPACITY OF THE
STRUCTURE
Column Capacity
For determining the capacity of the column towithstand the working loads, it can be seen from thecolumn interaction diagram and shear capacity [10],[11]. The calculation results of the interaction
diagram and shear capacity due to tsunami loads [12]– [15] will be explained below.

Inter Story DriftFirst floor column P-M interaction diagram
Based on SNI 1726:2019, the inter story drift (Δ)
must be calculated as using the following Eq. (8) [8].
δ =

Cdδx
Ie

≤ 0,010 hsx

Figure 4 shows the P-M interaction diagram
obtained from structural analysis results with andwithout tsunami loads, respectively.

(8)

Without tsunami load

From Eq. (8), the inter story drift can be obtained.
Tables 4 and 5 show the inter story results in X and Y
direction with and without tsunami loads.

With tsunami load

Table 4 Inter Story drift in X-direction
Displacement - X
With Without
Limit Increased Check
Story tsunami tsunami(mm) ratio (%) Δlimit>Δx
loads
loads
(mm)
(mm)
5
4.671
4.697
35
0.55
OK
4
7.715
7.803
35
1.14
OK
3
10.362 10.828 35
4.49
OK
2
13.416 14.777 35
10.14
OK
1
1.793
1.984
42
10.63
OK

(K1)

(K2)
Table 5 Inter story drift in Y-direction
Displacement - Y
With Without
Limit Increased Check
Story tsunami tsunami(mm) ratio (%) Δlimit>Δx
loads
loads
(mm)
(mm)
5
2.574
2.585
35
0.43
OK
4
4.411
4.429
35
0.42
OK
3
4.217
4.231
35
0.35
OK
2
3.843
3.920
35
2.00
OK
1
0.532
0.554
42
4.14
OK

(K3)

It can be seen from Tables 4 and 5 that the interstory drift of the building in X and Y direction is stillat the permissible range of story drift as required inIndonesian building codes. The increase of the interstory drift in the X-direction that occurs due to the(K4)
Fig. 4
88

First floor column P-M interaction diagram.

GEOMATE – Bangkok, Thailand, 22-24 November 2022

Table 7 Beam flexure capacity at 1st floor and 2nd floor
with and without tsunami

It can be seen from Fig. 4 that the increase ininternal force marked in blue is quite significant, thebending capacity of the columns are able to withstandthe working loads, including tsunami loads.

Without
With tsunami Incretsunami load
load
ased
Stor BeamØMn
Locationratio
y type(kNm) Mu Chec Mu
Check (%)(kNm) k (kNm)

Shear capacity of columns
The shear capacity of the building columns isshown in Table 6.

At support 40.24 16.86
At field 40.24 7.27
At support 276.22 263.80
G1
At field 276.22 111.55
At support 196.35 138.28
G2
At field 196.35 102.26
1
At support 371.97 314.58
G3
At field 371.97 125.33
At support 441.73 396.54
G4
At field 576.62 210.53
At support 267.76 253.33
G5
At field 267.76 108.41
At support 150.42 39.21
B1
At field 198.79 2.54
At support 78.94 37.79
B2
At field 78.94 12.21
At support 67.76 24.56
B3
At field 67.76 9.85
At support 509.95 478.08
CG1
At field 371.97 289.05
At support 340.86 248.84
2 G1
At field 209.81 189.35
At support 165.84 142.04
G2
At field 196.35 57.20
At support 509.95 489.28
G3
At field 300.66 231.65
At support 641.75 578.07
G4
At field 371.97 246.39
At support 441.73 415.96
G5
At field 300.66 221.34
B3

Table 6 Shear capacity columns with and without
tsunami loads
Colu
Story mn
type

1

2

3

K1
K2
K3
K4
K1
K2
K3
K4
K1
K2
K3
K4

With tsunami Increa
loads
sed
ratio
Vu
Vu (kN) Check
Check
(%)
(kN)
475.29 404.24 OK 690.94 Not OK 71
475.29 363.14 OK 517.06 Not OK 42
493.68 275.13 OK 460.75 OK
68
168.61 60.45 OK 123.54 OK 104
475.29 282.48 OK 430.54 OK
52475.29 196.31 OK 407.14 OK 107
493.68 176.24 OK 398.85 OK 126
168.61 64.65 OK 245.64 Not OK 279
475.29 357.82 OK 362.53 OK
1
475.29 216.65 OK 221.49 OK
2
493.68 171.19 OK 171.19 OK
0
168.61 27.93 OK 42.51 OK
52
ΦVn
(kN)

Without
tsunami loads

Based on the results of the shear capacity of thecolumns in Table 6, it can be seen that the shear
capacity of the building without tsunami load is able
to withstand the working loads, while the shear
capacity of the building with tsunami loads showsthat the 1st and 3rd floor columns is not able towithstand the shear force. The increase in shear force
that occurs due to tsunami loads is quite significant,especially for the 1st and 2nd floors with a maximum
increase on the 2nd floor of 279.9%.

OK 27.78 OK
65
OK 13.39 OK
84
OK 288.51 Not OK 9
OK 111.16 OK
0
OK 146.37 OK
6
OK 144.47 OK
41
OK 385.95 Not OK 23
OK 182.83 OK
46
OK 469.11 Not OK 18
OK 286.77 OK
36
OK 347.05 Not OK 37
OK 168.73 OK
55
OK 58.08 OK
48
OK 2.67
OK
5
OK 81.19 Not OK 114
OK 40.35 OK 230
OK 24.28 Oke
0
OK 10.57 Oke
7OK 973.87 Not OK 104
OK 572.62 Not OK 98
OK 538.81 Not OK 117
OK 209.97 Not OK 11
OK 139.77 OK
0
OK 56.33 OK
0
OK 507.43 OK
3
OK 228.99 OK
0
OK 743.51 Not OK 29
OK 243.67 OK
0
OK 405.45 OK
0
OK 212.58 OK
0

Based on Table 8, it is seen that two beam
elements are not able to resist the shear force thatworks when tsunami loads were applied on thebuilding.
The increase that occurred in the shear force of thebeams was not as large as the increase in the columns,
but the increase was still quite significant according
to Table 8, in which the increase that occurred did notexceed 100%.
The checks of mass participation, P-delta andstructural irregularities in the STBA Prayoga Padang
Building have all met the requirements in SNI 17262019 and FEMA P646 [9]. Based on the structural
response results, the STBA Prayoga Padang building
is strong enough to withstand the earthquake load, but
not strong enough in resisting the applied tsunami
loads. The influence of the tsunami loads on the
STBA Prayoga Padang building is significant enoughso that the columns and beams of the 1st and 2nd floorsof the building have the possibility of damage orcollapse [12] – [14].

Beam Capacity
Flexural capacity of beams
The results of the calculation and comparison of
the flexural capacity of beams with and without
tsunami loads are shown in Table 7 [10], [11].
From Table 7, it can be seen that the beam flexural
capacity increases significantly on the 2nd floor beam.
The highest increase of beam flexural capacity
occurred on the B2 beam on 2nd floor, which is230.54%.
Shear capacity of beams
The results of the calculation and comparison of
the shear capacity of beams with and without tsunami
loads is shown in Table 8.
89

GEOMATE – Bangkok, Thailand, 22-24 November 2022

Table 8 Beam shear capacity with and without
tsunamiand 184% for the bending moment, while theincrease is not significant for the columns.
4. The STBA Prayoga building is strong inwithstanding earthquake loads. However, whentsunami loads were applied, the shear capacity of
the column on the 1 st floor and the bending
moment and shear capacity of the beams on the 1st
and 2nd floors are not strong enough in capacity towithstand the working loads.

WithoutWith
IncretsunamitsunamiSto Beam
ØVn
ased
load
load
Locationry type(kN)
ratio
Vu Chec Vu Chec(%)(kN) k (kN) k
At support 75.79 11.49 OK 19.23 OK 67
B3
At field 66.74 16.26 OK 16.26 OK 0
At support 474.32 194.24 OK 215.85 OK 11
G1
At field 329.56 184.27 OK 206.25 OK 11
At support 525.15 109.09 OK 171.12 OK 56
G2
At field 525.15 149.18 OK 149.18 OK 0
1
At support 661.23 187.81 OK 196.64 OK 4
G3
At field 661.23 194.93 OK 194.94 OK 0
At support 661.23 232.41 OK 325.21 OK 39
G4
At field 516.71 233.87 OK 233.87 OK 0
At support 661.23 137.64 OK 171.64 OK 24
G5
At field 516.71 138.04 OK 138.04 OK 0
At support 442.15 54.13 OK 122.21 OK 125
B1
At field 313.47 53.65 OK 145.01 OK 170
At support 176.81 54.13 OK 82.54 OK 52
B2
At field 166.85 53.65 OK 115.02 OK 114
At support 87.85 15.04 OK 15.28 OK 1
B3
At field 78.20 20.76 OK 24.51 OK 18
Not
At support 366.42 222.03 OK 465.37
109
OK
CG1
At field 366.42 6.90 OK 6.90 OK 0
At support 586.91 208.42 OK 492.07 OK 136
2
G1
Not
At field 385.85 195.13 OK 441.75
126
OK
At support 403.50 131.03 OK 131.13 OK 0
G2
At field 403.50 151.14 OK 178.11 OK 17
At support 661.23 230.66 OK 364.03 OK 57
G3
At field 516.71 237.71 OK 381.99 OK 60
At support 661.23 290.35 OK 477.64 OK 64
G4
At field 661.23 294.41 OK 489.92 OK 66
At support 661.23 164.49 OK 225.88 OK 37
G5
At field 516.71 180.51 OK 240.35 OK 33

REFERENCE[1] National Center for Earthquake Studies, Sourceand Hazard Map of the 2017 Indonesian
Earthquake, Ministry of PUPR, 2019.
[2] Boediono B., Dewi N. T. H., Kristalya M., Manik
S. L. C. and Ong. E. H. K., Examples ofEarthquake Resistant Building Designs, ITB,
2017.
[3] Dian O. and Manurung S., Geospatial Model ofPotential Tsunami Vulnerability in Padang City,
BMKG, 2010.
[4] Intan S. U., The Effect of the Tsunami Burden on
the New Building of the West Sumatra
Provincial Parliament, Universitas Andalas,
2017.
[5] Siregar N., The Effect of Tsunami Load on the
Pasar Raya Inpres Block III Building in Padang
City Based on FEMA P-646 / April 2012.
Universitas Andalas, 2017.
[6] Alfianto R. and Rahmat D., Analysis ofCalculation of Buildings with Methods ETABS
Version 9.7.2, Journal of Civil Eng., Building
and Transportation, Vol.2, No.1, 2018, pp28-33.
[7] Indonesian National Standardization Agency,
SNI 1727:2020 Minimum Load for Planning of
Buildings and Other Structures, 2020.
[8] Indonesian National Standardization Agency,
SNI 1726:2019 Seismic Resistance Design
Codes for Building and Other Structures, 2019.
[9] Applied Technology Council, FEMA P646-2019
Guidelines for Design of Structures for Vertical
Evacuation from Tsunami, 2019.
[10] Zaidir, Reinforced Concrete Construction.
Padang: Civil Engineering, Andalas University
Press, 2015.
[11] Indonesian National Standardization Agency,
SNI
2847:2019
Structural
Concrete
Requirements for Buildings, 2019.
[12] Huda Z., The Effect of Tsunami Burden on the
Building of SD Negeri 23/24 Padang,
Universitas Andalas, 2021.
[13] Setiawan A., Design of Reinforced Concrete
Structures (Based on SNI 2847:2013). Erlangga.
2016.
[14] Edyasmar W. P., Planning Structure for Case
Studies: Building, TPTC (Teacher Professional
Training Center) Padang State University,
Universitas Andalas, 2019.

CONCLUSION
Based on the results of the analysis that has been
carried out, the following conclusions can be drawn:
1. The addition of the tsunami load on the STBA
Prayoga Padang building increase the P-delta
value by 0.5%-10% in the X direction and 4% 4% in the Y direction, while the increase in interstory drift in X-direction is 0.5% - 10%, and Ydirection is 0.4%-4%.
2. For the internal force that occurs in the column,
the maximum increase occurred in the 1st floorand 2nd floor columns, which is 67.296% for theaxial force, 279.960% for the shear force, and469.308% for the moment, while there is no
significant increase for the 3rd floor column andabove.
3. A significant increase occurs in the internal forcesof the beams on the 1st and 2nd floors with amaximum increase of 170% for the shear force,90

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

STRUCTURAL EVALUATION OF THE MELATI HOSPITALBUILDING AT SUNGAI PENUH CITY
Fauzan1, Lukman Nulhakim1, Dyan Adhitya Nugraha M1 and Zev Al Jauhari2
1
Enginseering Faculty, Andalas University, Indonesia
2
Department of Civil Engineering, Bengkalis Polythecnic, Indonesia

ABSTRACT
Melati Hospital is one of the health buildings in Sungai Penuh City, Jambi Province, Indonesia. The building,which was previously the main maternity clinic, plans to upgrade its status to a maternity hospital. Based on field
investigations, the concrete compressive strength (fc’) was 15.77 MPa, which did not meet the requirement in theIndonesian building codes. Therefore, a structural evaluation should be done to the building structure. Structural
analysis was performed with ETABS v18 software using two methods, the open frame and the masonry wall infill
frame methods. The performance of the building structure was evaluated in terms of the moment and shear
capacities in columns and beams, as well as the inter story drift in the existing building. The results obtained bymodeling the structure as the open frame found that the capacity of the existing structure was not strong enoughto resist the working loads, especially on the second-floor columns, beams, and inter story drift that did not meetthe permit limit in the building codes. Meanwhile, the modelling of the structure using frame with masonry infilled
frame, this hospital building structure is strong enough to withstand the working loads. From these results, it was
found that the ability of this building to resist earthquake loads largely depends on the walls contribution towithstand lateral loads. The masonry is a brittle material that is prone to crack or fail so that the retrofitting of themasonry wall using ferrocement layers is highly recommended for this hospital building.
Keywords: Hospital building, Structural evaluation, Earthquake loads, Structural elements capacity

INTRODUCTION

reinforced concrete construction is because
considering the function of the building is designed tohave high strength against the influence of externalloads that may occur [4]. This building was located inan earthquake-prone area, which was designed using
previous Indonesian building standard SNI
1726:2012 [2]. In the hammer test result, it was foundthat the compressive strength of concrete was quite
low, which is 15.77 MPa. Therefore, a structural
evaluation should be carried out on the existing
structure of the Melati Hospital Building using thecurrent Indonesian building standards [5].

Health is very important for humans in order tosurvive and do activities properly. To manifest good
health in the community, not only medical personnel
and good medical support equipment are needed but
also a good structural building. So that the healthbuilding can function safely and its strength canensure the safety of the humans in it [1]. It isnecessary to plan the structure in accordance withIndonesian standards building.
In Indonesia, the building standards are always
changing along with the development of science andthe latest circumstances. An example is that in 2012
the regulation on earthquake-resistant buildings wascontained in SNI 1726:2012 [2], but after 7 years, thisregulation had changed along with research on the
response to major earthquakes in Indonesia which
damaged many buildings in Indonesia, so a new
regulation was issued, namely SNI 1726:2019 [3].
The Melati Hospital Building is one of the healthbuildings in the city of Sungai Penuh City, Jambi
Province, Indonesia, as shown in Fig. 1. The building,which was previously the main clinic, wants to
upgrade its status to a maternity hospital. Thishospital was the first maternity hospital in the city ofSungai Penuh. This hospital building is a three-story
building, and the construction uses reinforced
concrete construction. The reason of choosing

Fig. 1

3D modelling of Melati Hospital Building.

STRUCTURE ANALYSIS
Building Data
The three-story Melati Hospital Building is made91

GEOMATE – Bangkok, Thailand, 22-24 November 2022of reinforced concrete structures with the size of
28.16m length and 13m width. The yield strength ofsteel (fy) was 240 MPa and 400 MPa for plain anddeformed reinforcements, respectively, while thecompressive strength of the concrete (fc') was 15.77
MPa. Figures 1, 2 and 3 show the lay-out building andthe beam column position on first, second, and third
floors. The dimensions of the structural elements are:1. Beam: B1, B3 (30 x 40cm), B2 and RB (15 x 20cm)
2. Sloof: S1 (40 x 60 cm) and S2 (15 x 20 cm)
3. Column: K1 (35 x 35 cm), K2 and K3(30 x 400 cm)
4. Slab thickness: 13 cm.

Fig. 2columns and beams are modeled as frame elements,
floor plates as slab elements, and walls as wall
elements with masonry material [6]. The properties ofthe masonry walls are modeled according to Fig. 6.
Modeling of the masonry infilled-frame is carried out
with definition:
1. The compressive strength (fc’) of plaster for thewalls is 5.23 MPa.
2. Specific gravity of plaster 2130 kg/m3.
3. The compressive strength (fc’) of masonry is
assumed 1 MPa.
4. Specific gravity of masonry 1700 kg/m3.

The plan view of the building at 1st floor.

Fig. 3The plan view of the building at 2nd floor.

Fig. 4The plan view of the building at 3rd floor.

Fig. 5Modeling of building structures with anopen frame method.

Fig. 6

Properties of masonry walls.

The results of modeling the masonry infilledframe is shown in Fig. 7.

Structural Modeling
Structural modeling for open frame method
In the modeling of the open frame method,columns and beams are modeled as frame elements,
while floor slabs as slab elements [6]. The modelingis carried out in accordance with the existing
conditions of the Melati Hospital building, as shownin Fig. 5. The spectrum response method was used inanalysis of the earthquake load.

Fig. 7Structure modeling for masonry infilled-frame
methodLoading Analysis

In relation to the results obtained in the modelingof the open frame method, another analysis was
carried out using the frame method with a filler wall[4]. In the modeling of the frame with filler walls

Structural modeling of masonry infilledframe method.

Dead load
The dead load on the building was calculated
based on the Indonesian Standards Building (SNI92

GEOMATE – Bangkok, Thailand, 22-24 November 2022

1727:2020) [3]. The dead load acting on the floor
plate of the Melati Hospital Building at Sungai Penuh
City shown in Table 1.

1. 1.4 DL
2. 1.2 DL + 1.6 LL+ 0.5 R
3. 1.2 DL + 1.0 LL ± 1.0 EQx ± 0.3 EQy
4. 1.2 DL + 1.0 LL ± 0.3 EQx ± 1.0 EQy
5. 0.9 DL ± 1.0 EQx ± 0.3 EQy
6. 0.9 DL ± 0.3 EQx ± 1.0 EQyTable 1 Dead load on the building structure
Load
Floor coverings
Floor plaster
Plafond
Rainwater

Load value
48 kg/m2
42 kg/m2
20 kg/m2
50 kg/m2

Building priority factors
modification coefficient (R)

(Ie)

and

response

Based on SNI 1726:2019, the earthquake
reduction factor (R) is 8 for the frame structure of thespecial moment-bearing frame system, and thebuilding importance factor (Ie) is 1.5 for risk category
IV [3]. The spectrum response data are inputted into
the structural modeling and scale factor calculations
was performed on ETABS using Eq. (1).

Live load
The live load calculated based on SNI 1727:2020
must be the maximum load expected to occur due tothe occupancy and the use of the building [7], but it
must not be less than the minimum load set. The live
load on the building is based on the floor plan:a. Patient Room= 1.92 kN/m2
b. Lobby/corridor= 4.79 kN/m2
c. Lobby above the 1st floor= 3.83 kN/m2
d. Operating room/laboratory= 2.87 kN/m2

SF = G. I/R(1)

RESULTS AND DISCUSSION
Cross-Sectional Capacity for Open Frame Method

Earthquake load

Column capacity

The spectrum response is used as an analysis ofdynamic earthquake loads. The spectrum response
earthquake load is calculated based on SNI
1726:2019 [3]. Based on the design spectral
acceleration parameter values for soft soil in thehospital building location, the value of spectral design
SD1 and SDS are 0.663g and 1.459g, respectively.
Figure 8 shows the spectrum response for Sungai
Penuh City with soft soil conditions.

To determine the cross-sectional capacity of thebuilding structure, it is necessary to review the crosssectional capacity of the columns and beams in theMelati Hospital Building. The review of the structuralelements is grouped by dimensions, type, and positionof those columns and beams. From the results of thestructural analysis, it will be known the crosssectional capacity of the structural elements such as
beam momen capacity, beam shear capacity, column
interaction diagrams and column shear capacity [8].
From the results of this cross-sectional capacity, it
will be known whether the cross section is able towithstand the working load. The cross-sectional
capacity of the column can be seen with the followinginteraction diagram of P-M and shear capacity results.
The calculation results of the interaction diagramof the first floor, second floor, and third floor columnsof the building are shown in Fig. 9.
From the P-M interaction diagram in Fig. 9 above,it can be seen that the columns on the 1st and 3rd
floors are still strongly carrying the working loads on
the structure because the moment and axial do not
cross the permit limit in the P-M interaction diagram.
Meanwhile, the column on the 2nd floor is not strong
enough to carry the working load because there is a
moment and axial that passes the line permit limit in
the P-M interaction diagram.
The shear capacity of the building columns isshown in Table 2. From the table, it is clearly seenthat the column is able to withstand the shear forces
acting on the structure.

Spectrum Response (g)Fig. 8Earthquake response spectrum design ofSungai Penuh City.

Load combination
Based on SNI 1726:2019, to simulate the direction
effect of the random earthquake plan to the structureof the building, the effect of earthquake loading in themain direction determined must be considered to be
100% effective and must be considered to occur
together with the effect of deep earthquake loads witha perpendicular direction to the main direction of theload, with an effectiveness of only 30% [3]. The load
combination for this analysis is as follows:93

GEOMATE – Bangkok, Thailand, 22-24 November 2022

From Table 3, it can be seen that the beams on thebuilding structure are unable to withstand the loads
acting on the structure. Meanwhile, the beam hasenough capacity to resist the shear forces acting on
the structure, as shown in Table 4.

P - M INTERACTION DIAGRAM

Pn
4000

3500

Nominal Momen (Mn)

3000

Planning Momen
2500

Balance
2000

P
1500

1000

Table 4 Shear capacity of beam

500

Mn

0
-20

10

40

70

100

130

160

190

220

250

280

310

340

370

400

(a)
Pn

Type

P - M INTERACTION DIAGRAM

2000

S1 400 x 600 6D19
S2 150 x 200 2D10
B21 300 x 400 6D13
B22 150 x 200 2D10
B31 300 x 400 6D13
B32 150 x 200 2D10
RB 150 x 200 2D13

1800

1600
Nominal Momen (Mn)
1400
Planning Momen

1200

Balance

1000

P

800
600
400
200

Mn

0
0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

(b)
Pn

Dimension Comp. Tensile(mm)rebar rebar

Vr

Vu

(kN)

(kN)

8D19 269.53 77.23
2D10 53.58 7.72
4D13 151.08 112.03
2D10 38.31 11.35
4D13 151.08 103.47
2D10 38.31 10.81
2D13 82.84 16.48

Desc.
OK
OK
OK
OK
OK
OK
OK

P -M INTERACTION DIAGRAM

1800

Inter story drift

1600
1400

Nominal Momen (Mn)1200

According to SNI 1726:2019, the determinationof inter story drift (Δ) must be calculated as thedifference in the drift at the center of mass above andbelow the level under review [3], [9]. Tables 5 and 6
show the results of the inter story drift building for X
and Y directions.

Planning Momen

1000

Balance

800

P

600

400
200

Mn

0
0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

(c)
Fig. 9

Table 5 Inter story drift in X-direction

P-M interaction diagram at 1st floor (a), 2ndfloor (b) and 3rd floor (c) for open frame
method.

Hsx Hei permit
Desc.
(mm) (mm) (mm) mm (mm) (mm)312 4000 33.9 124.3 19.58 40
OK

Story

Table 2 Shear capacity column
Story
1
2
3

Dimension  Space Vn Vu
Description(mm) (mm) (mm) (kN) (kN)

350 x 350 10300 x 300 10
300 x 300 10

100 141.5 60.9
1100 112.2 59.4
100 112.2 11.3

OK
OK
OK

2

8

4000 28.56 104.72 59.39 40 NOT OK

1

44000 12.26 45.32 45.32 40 NOT OK

Base

0

4000

0

0

0

40

OK

Table 6 Inter story drift in Y-direction

Beam capacity

Story

Hsx H
e

i permit
Desc.
(mm) (mm) (mm) (mm) (mm) (mm)Table 3 Flexural capacity of beam3

12 4000 40.38 148.05 -4.65 40

Dimension Comp. Tensile Mn Mu
Desc.
(mm)
rebar Rebar (kNm) (kNm)
S1 400 x 600 6D19 8D19 378.86 77.23 OK
S2 150 x 200 2D10 2D10 7.28 3.86
OK
B21 300 x 400 6D13 6D13 84.05 107.61 NOT OK
B22 150 x 200 2D10 2D10 7.278 6.1
OK
B31 300 x 400 6D13 6D13 84.05 109.08 NOT OK
B32 150 x 200 2D10 2D10 7.28 3.9
OK
RB 150 x 200 2D13 2D13 11.48 11.15 OK

2

84000 41.65 152.7 87.74 40 NOT OK

1

44000 17.72 64.96 64.96 40 NOT OK

Base

0

4000

Type

0

0

0

40

OK

OK

Based on Tables 5 and 6, it can be seen that theinter story drift in X and Y directions does not meetthe permit limit as required on the SNI 1726:2019 [3].
Cross-Sectional Capacity for Masonry InfilledFrame

The cross-sectional capacity of the beam can beseen by comparing the moment capacity and shear
plan with the working moment and shear ultimate [8].

Column capacity
94GEOMATE – Bangkok, Thailand, 22-24 November 2022

Cross-sectional capacity for masonry infilledframe [10] can be seen on the diagram of the P-M
interaction, shown in Fig. 10.

capacity of the beams. As can be seen in these tables,
the beams are able to withstand the working loads.
Table 8 Beam flexural capacityPn

P - M INTERACTION DIAGRAM

4000

Story

3500
3000

Momen Nominal (mn)

2500

Momen Rencana(mm) Rebar Rebar (kN) (kN)S130x40 400 x 600 6D19 8D19 378.8 46.7
S215x20 150 x 200 2D10 2D10 7.3 3.9
B230X40 300 x 400 6D13 6D13 84.1 49.2
B215X30 150 x 200 2D10 2D10 7.3 1.9
B330X40 300 x 400 6D13 6D13 84.1 67.3
B315X30 150 x 200 2D10 2D10 7.3 3.2
RB 150 x 200 2D13 2D13 11.5 4.9Balance

2000

Series5
1500
1000
500

Mn
0

-20

10

40

70

100

130

160

190

220

250

280

310

340

370

Dimension Comp. Tensile Mn Mu

400

(a)
2000
1800

Desc.
OK
OK
OK
OK
OK
OK
OK

1600
Nominal Momen (Mn)

1400

Planning Momen

1200

Table 9 Beam shear capacity

Balance

1000

P

800

Beam Dimension Comp. Tensile Vr Vu
Desc.
(mm) Rebar Rebar (kN) (kN)Type
S130x40 400 x 600 6D19 6D19 269.5 39.5 OK
S215x20 150 x 200 2D10 2D10 53.6 7.7 OK
B230X40 300 x 400 6D13 4D13 151.1 44.8 OK
B215X30 150 x 200 2D10 2D10 38.3 5.2 OK
B330X40 300 x 400 6D13 4D13 151.1 53.8 OK
B315X30 150 x 200 2D10 2D10 38.3 5.1 OK
RB
150 x 200 2D13 2D13 82.8 5.9 OK

600
400
200
0
0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

(b)
1800.000000

1600.000000
1400.000000

Nominal Momen(Mn)1200.000000

Planning Momen

1000.000000

Balance800.000000

P

600.000000
400.000000
200.000000
0.000000
0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

Inter story drift

150

(c)
The calculation results of the inter story drift in
the X and Y directions on the retrofitted building isshown in Tables 10 and 11.

Fig. 10 P-M interaction diagram at 1st floor, 2nd floor
and 3rd floor for masonry infilled-frame.
As seen in Fig. 10, the first, second, and third floor
columns are strong enough to carry the working load
because there are axial moment and compression
force that not passes through the design axial
compression moment line.
Table 7 shows the shear capacity on the columns.
As seen in the table, the column is able to withstandthe shear forces acting on the structure.

Table 10 Inter story drift X direction
Hsx H
emm mm mm3
12 4000 0.61
28 4000 0.53
1
4 4000 1.61
Base 0 4000 0

Story


i permit
Desc.
mm mm mm
2.24 0.3
40
OK
1.94 3.98 40
OK5.92 5.92 40
OK
0
0
40
OK

Table 7 Shear capacity column
From Tables 10 and 11, it is clearly seen that theinter story drift that occur in X and Y directions have
met the permit limit according to Indonesian building
standard.
From the structural analysis results of the two
methods, it can be seen that calculations with open
frame modeling method shows that the Melati
Hospital Building does not have strong enoughcapacity on resist the working loads, especially in thesecond-floor columns, beams, and the inter story drift.
While the calculations with masonry infilled frame
method [11], the structure of the hospital building is

Dimensions Diameter Space Vn Vu
Story
Desc.
(mm) (mm) (kN) (kN)(mm)
1

350 x 35010

100 141.5 10.16 OK

2300 x 300

10

100 112.2 9.28 OK

3300 x 300

10

100 112.2 2.77 OK

Beam capacity
Tables 8 and 9 shows the flexural and shear95

GEOMATE – Bangkok, Thailand, 22-24 November 2022

strong enough to withstand the working load based on
the current Indonesian building standards. However,masonry is a material that is vulnerable and easy toexperience failure (brittle) so strengthening thebuilding wall is highly recommended by using the
mortar containing small wire mesh that was installed
on a masonry wall (ferrocement layer retrofitting
method) [12] – [16].

oral and dental hospital of Jenderal Seodirman
University, Proc. Eng. 171, 2017, pp1025-1034.
[2] Indonesian National Standardization Agency,
SNI 1726:2012 Seismic Resistance Design
Codes for Building and Other Structures, 2012.
[3] Indonesian National Standardization Agency,
SNI 1726:2019 Seismic Resistance Design
Codes for Building and Other Structures, 2019.
[4] Zengin B. and Kocak A., The Effect of the Bricks
Used in Masonry Walls on Characteristic
Properties, Sigma Journal of Engineering andNatural Science, Vol.35, No.4, 2017, pp.667-677.
[5] Putra N.S. A. and Lesmana C., Feasibility
analysis of the structure of a 5-story publicbuilding in the Jakarta City, Jurnal Teknik Sipil,
Vol.14, No.2, 2018, pp180-199.
[6] Alfianto R. and Rahmat D., Analysis ofCalculation of Buildings with Methods ETABS
Version 9.7.2, Journal of Civil Eng., Building
and Transportation, Vol.2, No.1, 2018, pp28-33.
[7] Indonesian National Standardization Agency,
SNI 1727:2020 Minimum Load for Planning of
Buildings and Other Structures, 2020.
[8] Indonesian National Standardization Agency,
SNI
2847:2019
Structural
Concrete
Requirements for Buildings, 2019.
[9] Akbar S. J., Chandra Y. and Yusriansyah,
Analysis of Horizontal Deviation Value (Drift) in
Earthquake Resistant Structures Using theEccentric Bresing Frame System Type Braced V,
Teras Jurnal, Vol.7, No.2, 2017, pp301-312.
[10] Pardeshi S. and Deshpande U. L., Repair,
Restoration and Strengthening of Building,International Journal of Innovations inEngineering Research and Technology (IJIERT)Vol. 4, Issue 3, pp.121-124, 2017.
[11] Boen T., Earthquake Resistant Building Manual.
World Seismic Safety Initiative. 2009.
[12] Barnaure M. and Stoica D. N., Analysis of
Masonry Infilled RC Frame Structures Under
Lateral Loading, Mathematical Modelling in
Civil Engineering, Vol.11, No. 1, 2015, pp.29-39.
[13] Balamuralikrishnan R., AL Madhani M, and Al
Madhani R., Study on Retrofitting of RC Column
Using Ferrocement Full and Strip Warapping, C.
Eng. Journal, Vol.5, No.11, 2019, pp.2472-2485.
[14] Fauzan, Ismail F. A., Zaidir and Amalia S. H.,
Experimental Study on Masonry Building
Strengthened with Ferrocement Layers, Int. J.
GEOMATE, Vol. 14, Issue 45, 2018, pp.84-90.
[15] Alam M. Z., Asif M. M. and Ahsan R., A studyon The Performance of Ferrocement Retrofitted
Masonry Wall Units under Cyclic Loading, Int.
Con. on Adv. in Civ. Eng., 2018, pp. 451-455.
[16] Wang C., Sarhosis V. and Nikitas N.,
Strngthening/Retrofitting
Techniqueson
Unreinforced
Masonry
Structure/Element
Subjected to Seismic Loads: A Literature Review,Vol.12, 2018, pp.251-268.

Table 11 Inter story drift Y direction
Hsx H
emm mm mm3
12 4000 1.14
28 4000 0.87
14 4000 0.46
Base 0 4000 0

Story


i permit
Desc.
mm mm mm
4.16 0.98 40
OK
3.19 1.51 40
OK1.68 1.68 40
OK
0
0
40
OK

CONCLUSION
Based on the structural evaluation of the Melati
Hospital Building, the following conclusions can be
drawn:
1. The compressive strength of concrete in the beam
and column elements of the Melati Hospital
Building is quite low, fc’ = 15.77 MPa (K-190),
lower than that required in Indonesian BuildingStandards (fc' = 17 MPa).
2. The results of the analysis showed that thestructural capacity of the Melati Hospital Building
was not strong enough to resist the working loads,
especially in the second floor column, the beams
and inter story drift that was calculated with anopen frame method. Whereas using modelingwith masonry wall infilled frame method, this
hospital structure is strong enough to withstandthe working loads according to current Indonesianbuilding standards.
3. The ability of Melati Hospital Building towithstand earthquake loads is highly dependent
on the contribution of the wall to resist the lateralloads, so that the connection of the walls to thecolumns and beams should be properly designed
and constructed.
4. Strengthening the walls of buildings withferrocement layer improve the capacity of thebuilding by reducing the internal force on
columns and beams due to the working load on thebuilding. In the observed column, it had a moment
reduction of 16-17%, an axial force of 15-16%,
and a shear force of up to 15%. While the beam
had a moment reduction of 6-18%, and a shear
force of 2-5%.
REFERENCES[1] Haryanto Y., Sudibyo G. H. and Effendi F. C. A.,
Preliminary seismic hazard assessment of the96

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ANALYSIS OF REINFORCED CONCRETE STRUCTURESEMPLOYING KOHONEN SELF ORGANISING MAP
Omar Al Juboori1 and Rabee Rustum2
PEROrient Building Contracting LLC, UAE
2
School of Energy, Geoscience, Infrastructure and Environment, Heriot Watt University, Dubai Campus,
1

ABSTRACTReinforced Cement Concrete (RCC) structure is most widely used in the construction industry alongside othertypes of structures such as steel structures, wooden structures and many other systems used globally. This paper
employed Artificial Intelligent (AI) techniques for modelling the (RCC) elements in the buildings using theKohonen Self Organizing Map (KSOM), A comparison between this technique and other techniques used in thefield, such as the Artificial Neural Network (ANN) has been made. The results showed that the Kohonen Self
Organizing Map (KSOM) is an attractive tool for modelling reinforced concrete structures. Moreover, thistechnique offers a magnificent tool for high-dimensional data visualization.
Keywords: Reinforced Cement Concrete, Artificial Intelligent, Kohonen Self Organizing Map, Artificial Neural
Network
INTRODUCTION

The main technique that will be covered in thispaper is one of the unsupervised techniques, which is
the KSOM network, which was developed to solve
problems such as clustering, visual analytics, andabstract thought, among others. The results reveal thatwhen KSOM and the contiguity-constrained
clustering approach are combined, the clusteringresults are comparable to those of other clustering
methods. Then, using two well-referenced machinelearning scenarios, assess the method's applicability
and compare the findings to those of several famous
statistical clustering methods, referring to figure 1 fora simple illustration of KSOM technique [5], [6].
More information on training and visualization of the
KSOM are available in the literature, and the reader
can refer to Rustum and adeloye (2011) [7].

The global trends nowadays for designing (RC)
Structures as sustainable buildings direct the designer
towards reducing the resources of concrete used in the
structures by conserving the use of the environmental
resources; hence an optimized design is required toestablish any building. Thus, for the time-being, theresearchers are trying to outline new ways, techniques,
methods or procedures for the design to override theold ones [1].
The major limitations of the conventional
methods are the safety factors presumed in thecalculations that may lead to exaggerated material
quantities, which will affect the cost of the buildingin the first place, time for construction and additionalbuilding mass where it will be critical in the seismic
analysis. Futhermore, it requires a huge time fordesigning and analysis especially in complex
buildings.
Subject to the above, the researchers/designers
aim to employ artificial intelligence techniques tosolve these critical issues, such as the artificial neuralnetwork (ANN) and Kohonen Self-Organizing Map(KSOM) [2].

Fig. 1 – Illustration of winning node and its

LITERATURE REVIEW

neighborhood in KSOM [8].

The construction of any building requires a
structural system to carry out the load applied to it;
hence a proper design has to be considered. There are
multiple ways to achieve this target, starting from theconventional methods that are highlighted in theinternational codes; however, nowadays, the main
target is to use the artificial intelligence techniquessuch as but not limited to ANN and KSOM [3], [4].

METHOD AND MATERIALS
Case Study
The methodology followed in this paper wasapplied to several data collected from several pieces
of research for both selected cases, which are beams
with stirrups and beams without stirrups. In bothcases, the results of artificial neural network (ANN)97

SEE-Mie, Japan, Nov.10-12, 2022

and the experimental results for shear force are also
included, and this was used for validation andcomparison between it and the KSOM method.
Furthermore, several software was used to validate
the data to get the most affected parts to the method
in visualized maps.
The model for each case was developed andimplemented using MATLAB Programming
language and Neural Networks toolbox and the SOM
toolbox developed at the CIS laboratory at Helsinki
University of Technology [8].
MATLAB was chosen because neural networks
require complicated matrix computations, and thetools within the software helped to provide acomprehensive design, implementation, andsimulation of the model quickly. It is also flexible
enough to do the necessary customization. The work
was done using the software's package documentationand literature [8].
Microsoft Excel was chosen to visualize the datain figures and perform mathematical calculations to
obtain the minimum, maximum, standard deviation,
average, outlier, and other results needed for thisstudy. The functions and definitions of the terms wereobtained from the software package's documentationand the literature [9].
The parameters used in this are presented in Table
1 and 2 hereinafter.

fyv
Asv
VEXP
PEXP

Table 2 Notations Used for Beams with Stirrups
Case
ID
b
h
d
av
fc
Asl
ρ (%)
fyl

Table 1 Notations Used for Beams with Stirrups
Case
ID
b
h
d
av
fc
Asl
A'sl
ρ (%)
ρ ' (%)

ρv (%)fyl
f 'yl

Transverse
reinforcement
nominal yield stress (MPa)Stirrups reinforcement area
(mm²)
Experimental maximum shear(kN)
Experimental maximum load
(kN)

VEXP
PEXP

Identification
Beam cross-section width (mm)Beam cross-section height (mm)The effective depth of section(mm)
The Shear span of a beam (mm)Concrete compressive strength(MPa)Longitudinal reinforcement area
(mm²)
Compressive
longitudinal
reinforcement area (mm²)
Percentage
oflongitudinal
reinforcement (%)
Percentage of compressive
longitudinal reinforcement ratio(%)
PercentageofTransverse
reinforcement ratio (%)
Longitudinal
reinforcement
nominal yield stress (MPa)Compressive
longitudinal
reinforcement nominal yieldstress (MPa)

Identification
Beam cross-section width (mm)Beam cross-section height (mm)The effective depth of section(mm)
The Shear span of a beam (mm)Concrete compressive strength(MPa)Longitudinal reinforcement area
(mm²)
Percentage
oflongitudinal
reinforcement (%)
Longitudinal
reinforcement
nominal yield stress (MPa)Experimental maximum shear(kN)
Experimental maximum load(kN)

Models Performance Evaluation Criteria
The network should be evaluated and compared toother findings after it has been trained. In this study,
the KSOM was employed and compared to theexperimental and ANN techniques, and the following
evaluation criteria were employed [8].
1. The Average Absolute Error (AAE) [8].
2.

The relative average absolute error (RAAE)
[8].

3.

The normalized root mean squared error(NRMSE) [8].

4.

The mean square error (MSE) [8].

5.

The correlation coefficient (R) [8].

6.

The classification error (CE) [8].

Analysis of Variance (ANOVA) Criteria
1. Sum of Squares (SS) [8].

982.

Mean Square (MS) [8].

3.

The Overall (F) [8].

SEE-Mie, Japan, Nov.10-12, 2022

4. Significance F [8].
Regression Summary Criteria
1. Coefficient: It gives the least squares
estimate [8].
2.

Standard Error [8].

3.

t Stat [8].

4.

P Value [8].

5.

Lower & Upper 95% [8].
Fig. 2 – Affection of the specimen characteristic on

Regression Statistic Criteria
1. Multiple R [8].
2.

R Squared (r ²) [8].

3.

Adjusted R Square [8].

4.

Standard Error [8].

5.

Observations [8].

the results – Case –1 – Set 1

RESULTS AND DISCUSSION
To start the implementation of KSOM technique,two selected cases were used as described earlier,then the results were compared to those generated
from ANN technique and the experimental results tojudge the usefulness of this technique. It is worthy
mentioning that the results obtained for this researchwent through a series of regressions (in sets), notingthat the data analyzed was around 568 for the firstcase (Beams without stirrups) and 296 for the secondcase (Beams with stirrups).

Fig. 3 – Time Series Plot for the regression analysis –Case –1 – Set 1

Beams without stirrups case 1
In this case, the data obtained from the sources[10] were analyzed through 3 sets of regression, each
set obtaining a serial number of results hereinafter,
the results will be shown and discussed.
The below figures explain how each characteristic
can affect the results using MATLAB Software; thehigher the color appears in figure represents more
contribution of this characteristic of the specimen.
The performance of the model is shown in figures
3 and 4, where the correlation between the modelleddata using the KSOM and the experimental results
was over 90%.

Fig. 4 – Scattered Plot between VEXP and VKSOM
techniques – Case –1 – Set 1

Beams with stirrups case 2
In this case the data obtained from the sources[10] were analyzed through 4 sets of regression, each
set obtaining a serial number of results hereinafter,
the results will be shown and discussed.

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And similarly, the calculations were obtained forthe other sets in both cases, comparing all the results
using the criteria described earlier to judge thetechnique for using it in the structural field.

CONCLUSION AND RECOMMENDATIONS
Based on the above calculations, the results foundthat using the Kohonen Self Organizing Map"KSOM" technique which is part of the artificial
intelligence techniques in the structural field, isfeasible and within the acceptable limits bycomparing the obtained results along with theexperimental results and those results obtained byusing ANN, hence it is useful to use this kind oftechnology even when some data were missing, andthe model didn't get affected by these missing data or
the outliers and this one of the most important
advantages of this technique.
The model training, as shown in both cases tested
for this technique, got affected by the sectional
dimension, location of the main reinforcement, andapplied moment on the section, while the effect of thereinforcement percentage or the compressive strengthof the section represents less important for the same.
Moreover, the model could be enhanced byadding other data from other sources to train it betterand enhance it; this will tend to reduce the time
requested to predict an acceptable design and reduce
the time consumed using the conventional method
procedure and the mathematical calculations.
Nevertheless, other types of structural elements
could be entered into the model, train the model to getvarious type of designed elements and test it; the same
will make this technique part of the next revolution in
structural design and other engineering and nonengineering fields.

Fig. 5 – Affection of the specimen characteristic on
the results – Case –2 – Set 1

Fig. 6 – Time Series Plot for the regression analysis –REFERENCES

Case –2 – Set 1[1] Saleem, M.U. and Qureshi, H.J., 2018. Design
solutions for sustainable construction of preengineered steel buildings. Sustainability, 10(6),p.1761.
[2] Lee, S.C., 2003. Prediction of concrete strength
using artificial neural networks. Engineering
structures, 25(7), pp.849-857.
[3] Rustum, R., Adeloye, A. and Simala, A., 2007.
Kohonen self-organising map (KSOM) extracted
features for enhancing MLP-ANN prediction
models of BOD5. In International Symposium:
Quantification and Reduction of Predictive
Uncertainty for Sustainable Water Resources
Management-24th General Assembly of theInternational Union of Geodesy and Geophysics(IUGG) (pp. 181-187).
[4] Kumar, N., Rustum, R., Shankar, V. and Adeloye,
A.J., 2021. Self-organizing map estimator for the

Fig. 7 – Scattered Plot between VEXP and VKSOM
techniques – Case –2 – Set 1

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SEE-Mie, Japan, Nov.10-12, 2022

crop water stress index. Computers andElectronics in Agriculture, 187, p.106232.
[5] Kumar, N., Adeloye, A.J., Shankar, V. andRustum, R., 2020. Neural computing modelling of
the crop water stress index. Agricultural Water
Management, 239, p.106259.
[6] Rustum, R.A.B.E.E. and Adeloye, A.J., 2006,
September. Features extraction from primary
clarifier data using unsupervised neural networks(Kohonen Self Organising Map). In the 7thInternational Conference on Hydroinformatics,
HIC 2006, Nice, France.
[7] Rustum, R. and Adeloye, A., 2011. Artificial
Intelligence modelling of wastewater treatment
plants: Theory, applications and limitations.

[8] Rustum, R., 2009. Modelling activated sludge
wastewater treatment plants using artificial
intelligence techniques (fuzzy logic and neuralnetworks) (Doctoral dissertation, Heriot-Watt
University).
[9] Rustum, R. and Adeloye, A.J., 2007. Replacing
outliers and missing values from activated sludge
data using Kohonen self-organizing map. Journalof Environmental Engineering, 133(9), pp.909916.
[10] Kotsovou, G.M., Cotsovos, D.M., 2017. Analysis
Of Reinfored Concrete Structures Employing
Neural Networks.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXISTING BRIDGE CAPACITY EVALUATION FOR
TRANSPORTATION HAVEY TRAILER
Douangmixay DOUNSUVANH 1, Chanpheng PHOMMAVONE 2
1,2Department of Civil Engineering, Faculty of Engineering, National University of Laos, Lao PDR

ABSTRACTAt the present time, there are many mega projects have been popular constructed in Laos such as Hydropower
Dam Projects. Which these projects require to transportation heavy machines and equipment such as transformers,
generators, etc., crossing many existing old bridges along national roads, and most of bridges are no design
information. It may difficult to bridge engineers to make decision for transportation heavy truck crossing thebridges which ensuring bridge are safe. This study is presenting for existing bridges capacity evaluation fortransportation of heavy machine trailer crossing bridges along transportation routes of 60 km. The transportationroute started from Thai-Lao border to dam project site at Khammuan Province, Lao PDR. All bridges alongtransportation road are no design information, which the allowable normal traffic trucks load is only 40 tones.
However, the machine weight is up to 250 tones (not including trailer weigh). Two critical typical bridges namely
PC-I girder and Steel I-Girder, span length 25m, and 25.5m respectably have been selected for presenting study
bridges capacity and evaluation. The procedure of the bridges evaluation are including detail inspection, fullloading testing by actual twelve wheel trucks, and 3D FEM model for comparing model and selecting proper
tailor configuration ( the total weigh of Machine and trailer weigh is 350 tones). After that the bridge response(Girders strain, deflection and vibration) were monitoring during heavy trailer crossing the bridges. It seen that
this method is safe to bridge structure for carrying heavy trailer. The analysis results of bridge structure by 3D
FEM are match to the actual testing and monitoring.
Keywords: Heavy Trailer, Bridge testing and monitoring, Bridge Capacity Evaluation.

INTRODUCTION

been monitored their respond due to maximum heavy
trailers.

The bridge structure is very vital for highway
engineering system, if it is lack of the capacity tocarry traffic truck loads, consequently many problems
would be occurred such as: structural cracking,successive deflection, shortening bridge service life,
instability of the structural member leading to thewhole structure collapse. Evaluation of the existingbridge is one difficult work for the Bridge Engineer,
especially for the bridge that design and construction
information are not known [2]. This study is forexisting
bridges
capacity
evaluationfortransportation of heavy machine transformer to Damsite, Hydroelectric Power Project in Lao PDR. The
project route for transportation is stating from ThaiLao border to dam project site, 60 km at Khammuan
Province, Lao PDR. Along the project route, there
are 15 bridges and 10 culverts, all bridges are no
design and construction information.
This study is presenting for existing bridges
capacity evaluation for transportation of heavy trailer
crossing bridges along transportation routes. The
maximum transportation weight is 250 tones (notincluding trailer weigh), and 350 tones including
trailer weigh). Two critical bridges along the projectroute are selected for study capacity by analysis
model, actual load testing, after that, the bridges have

BRIDGE ON PROJECT RUTE TRUCKS
The transportation route started from Thai-Laoborder to dam project site which transportation routes
is about 60 km at Khammuan Province, Lao PDR.
Along the project route, there are 15 bridges and 10
culverts. All bridges along transportation road are no
design information, which the allowable normal
traffic trucks load is only 40 tones. Two criticalbridges are selected for study their capacity such as
PC-I girder (Bridge No.5) and Steel I-Girder (Bridge
No.11), span length 25m, and 25.5m respectably forpresenting study bridges capacity and evaluation.
Due to that according to bridge inspection results,
these two bridge are more critical than other bridges
and cultivars along the transportation route.
Selected testing and monitoring bridges
The PC-I girder bridge is simple sport, spans
length is 25m, lane width is 7m, and each spanconsisted of 3 Prestressed Concrete girders as show
in the “Figure 1, PC-I girder bridge.”.

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Fig. 1 PC-I girder Bridge (Brg No.5)
The Steel I-Girder (Brg No.11) is also simple
supported bridge with spans is 25.5m, and consistedof 4 Steel composited I-girders as show in the “Figure
2, Steel I girder bridge.”.

Fig. 2 Steel I-girder (Brg No.11)
The bridges information and material strength are
selecting from actual inspection and assumption fromgeneral standard, for PC the concrete compression
strength is 350.0 kg/cm2, PC ultimate strength ofsteel is fpu = 18, 730.0 kg/cm2; the steel structure theyield strength of steel is 3,250.0 kg/cm2.

Fig. 4 Tow traffics 12 wheel trucks, TT12
Heavy trailer trucks, T350 is main purpose oftransportation for the project, it will transport heavytransformer equipment of 250 tones (250,000 kg).
The carefully special trailer is selected, the special
trailer 32 axles and self weight of 100 tones (100,000kg) is selected, the total weight of heavy trailer trucks,
T350 is become 350 tones (350,000 kg). This heavy
trailer truck therefor is using for both analysis andmonitoring actual bridge respond during transporting
crossing bridges.

Truck Loading and Heavy Trailer
The truck loading to evaluation bridge capacity
are consisted such as AASHTO bridge design truck
HS25-44 [1] (total weight 40,080.00 kg ), tow traffics
12 wheel trucks namely TT12(weights of 65,050 kg
and 67,000 kg, total of 132,050 kg) , and heavy trailer
trucks namely T350( the total weigh of Machine andtrailer weigh is 350 tones)
AASHTO HS25-44 is using for analysis tocomparing analysis model of testing truck TT12 andheavy trailer trucks T345

Fig. 5 Heavy trailer trucks, TT12.
32 Axle trailer with 1.5m spacing, cargo weigh =250 tons + 100 (Trailer weigh) = total weigh 350
tons
BRIDGE ANALYAIA MODEL

Fig. 1 This is the

The evaluation bridges No.5 and No.11 aremodeled for analysis and evaluation capacity by 3D
model FEM model using CSIBridge commercial
software[5]. The loading models for analysis
checking bridge capacity are included AASHTO
truck load HS25-44, actual traffic trucks TT12, andheavy trailer trucks, T350 as indicated in the above.

Fig. 3 AASHTO HS25-44

TT12 is using for calibration analysis model totesting results. Due to that this type of truck is popular
unsung along project route.

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The PC-I girder bridge (Brg. No.5) is modeled as
3 spans, simple supported bridge which each span
length is 25m, bridge lane width is 7m, consisting of
3 PC girder as show in the “Figure 6, PC-I girder
bridge.”.

Table 1 shows the analysis results of total member
forces of bridge No.5 due to three different types oftruck loading. As the results in the table, the resultsof TT12 are higher than results of HS25-44 andresults of T350. And results of HS25-44 are higher
than results of T350. This is indicated that the special
trailer truck configuration is proper selecting, it’s
respond is less than design accrual and design trucks
model. The bridge may safe to using this trailer truck
configuration.
Table 1 Summarized Member forced for Br. No.5
Items
Hs25-44
TT12
T350

Fig. 6 Model of PC-I girder bridge (Brg. No.5)
The Steel I-Girder (Brg No.11) is modeled as one
simple support, spans length 25.5m consisting of 4
Steel composited section as show in the “Figure 7,
Steel I girder bridge.”.

M(Kgm)
573,737.30
617,953.90
515,078.00

V(Kg)104,417.18
110,535.59
90,150.00

Def(mm)
12.2
15.7
11.2

Table 2 shows the analysis results of total member
forces of bridge No.11. The analysis results of bridge
No.11 are similar to that bridge No.5. The results of
TT12 are higher than results of HS25-44 and resultsof T350. And results of HS25-44 are higher thanresults of T350.
Table 2 Summarized Member forced for Br. No.11

Fig. 7 Model of Steel I-Girder (Brg No.11)

Items
Hs25-44
TT12
T350

Analysis Results
Three type of trucks loading namely HS25-44,
TT12, T350, respectively are using to analysis forbridges No.5 and No.11. And all results are compared
to consider bridge respond due to different truck
loading.

M(Kgm)
622,715.00
652,715.00
563,401.00

V(Kg)103,671.71
120,535.95
92,275.00

Def(mm)
16.5
18.1
14.1

BRIDGE TESTING AND MONITORING
To
calibration
analysismodel
beforetransportation heavy trailer trucks, T350, both bridges
have been tested by full loading of TT12 which isconsisted by tow 12 wheel trucks (weights of 65,050
kg and 67,000 kg, total of 132,050 kg) as show in the“Figure 4”. The testing instruments are installed at
midspan bridges. The results of testing than willcompare to analysis models.

The deformation shape of two bridges are shownin the below figure.

After model of bridge analysis due to TT12 havebeen proved with tested results, the bridges are also
monitoring their respond due to heavy trailer trucks,
T350

Fig. 8a Deformation shape of Brg. No.5

Testing and monitoring Bridge No.5
The testing instrument such as LVDT for
measurement bridge deflection, concrete strain gagefor measurement bridge strain, and accelerometer formeasurement truck dynamic load are install at bottom
middle span each PC-I girder.

Fig. 8b Deformation shape of Brg. No.11

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for bridge No.5 and No.11 are show in the Table 3. It
is seen that deflection results from analysis are must
higher that testing results, the strain from testing
results are little comparing to normal allow strain of
PC and steel structure. This is evident that bridge
analysis model is much conservative.
Table 3 Summarized Testing Results, TT12

Fig. 9 Installation testing instruments for Brg. No.5

Items

Strain(Mcro)

Brg. No.5
Brg. No.11

130
240

Def-Test
(mm)
5.4
12.1

Def-Anal
(mm)
15.7
18.1

The monitoring results of the heavy trailer T350
for bridge No.5 and No.11 are show in the Table 4.
The results also similar manner for testing results thatthe monitoring results are less those monitoring
results.

Testing and monitoring Bridge No.11
Similar to the brg. No.5, steel I-girder bridge
No.11 is also installed testing instruments such as
LVDT for measurement bridge deflection, concrete
strain gage for measurement bridge strain, andaccelerometer for measurement truck dynamic load
are install at bottom middle span.

Table 4 Summarized Monitoring Results, T350
Items

Strain(Mcr)Brg. No.5
Brg. No.11

122
230

Def-Test
(mm)
3.4
11.5

Def-Anal
(mm)
11.2
14.1

It note that the results from acceleration are suing forchecking bridge dynamic effect, for low speed track,
the effect of dynamic load compare to static is lessthan 10%.
Fig. 10 Installation testing instruments for Brg.
No.11.

CONCLUSIONSIn this study, there are including analysis resultsby 3D FEM model of three types of truck loading
HS25-44, actual traffic truck loading TT12, andheavy trailer truck loading T350. It is seen that theactual traffic truck produced member forces forbending and shear forces higher than HS25-44 andhigher than heavy trailer T235. And analysis results
HS25-44 are higher than heavy trailer T235. It isevident that selection of special trailer confabulation
is suitable. However, to verify analysis model thebridges have been further conducting actual testing
due to actual traffic truck loading TT12, andmonitoring bridge during crossing heavy trailer T235.
The testing and monitoring results are conservative,
the results are less than analysis. It is evident thatbridge are sate by proper selecting special trailer
confabulation, and carefully evaluation by analysis
and full loading testing.

The testing procedure is done by using actualloading of two 12 wheels trucks, TT12 and two cases
are tested for each bridge such as Test-Case-01: Static
Loading testing by two truck, side by side stop on 5
locations; Test-Case-02: Dynamic Loading testing byrunning truck on one lane. Bridge response obtains
from testing results are included as bridge deflection,strain at bottom midspan girders, and accelerometer.
The monitoring procedure is done after actual
trucks tests results have been proved. The monitoringbridge is record during heavy trailer T350 is crossing
overs bridges. Similar Bridge response of testing arerecord such as bridge deflection, strain at bottom
midspan girders, and accelerometer.
Results of Testing and Monitoring

ACKNOWLEDGMENTS
The testing results of actual truck loading, TT12105

SEE-Mie, Japan, Nov.10-12, 2022

This study is supported by Transportationcompany namely Hansa Meyer Global Tran. Co.,LTD,
and corporation with Technical Division,
Department of Road and Bridge, Ministry of Public
works and Transportation (MPWT), Lao PDR.

[3] Umarani Gunasekaran, et al., Load rating ofbridges – current practices and issues, ATI Applied Technologies & Innovations, Vol. 2,
Issue 2, August 2010, pp. 9-18.
[4] Rafael R. Armendariz, Mark D. Bowman, Bridge
load rating, Joint Transportation Research
Program Publication, 2018.
[5] Peng Keke. and Fikret Necati Catbas,
Comparative Analysis of Bridges with AASHTO
and Florida I-Beam Girders, Journal of Civil
Engineering and Architecture, Feb. 2014,
Volume 8, No. 2, pp. 151-159.

REFERENCES[1] AASHTO., Standard Specification for Highway
Bridge, American Association of State Highway
and Transportation Officials, Washington, DC.,
17 Edition, 2002.
[2] J. M. Stallings, INSPECTION AND RATINGOF TEN BRIDGES, Auburn University
Highway Research Center, 2019.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

AN INTRODUCTION TO LINI APPLICATION FOR EARTHQUAKERESISTANT DESIGN OF BRIDGES IN INDONESIA

1Desyanti1 and Fahmi Aldiamar1
Implementation Unit for Geotechnics, Tunnels, and Structures, Ministry of Public Works and Housing,
Republic of Indonesia

ABSTRACTAs a country that is earthquake prone, the earthquake resistant design is inevitable for infrastructure inIndonesia. Indonesian standard for designing earthquake resistant bridges, SNI 2833:2016, has provided provisions
and procedure, also maps of earthquake hazard at bedrock, for the purposes of earthquake resistant bridge design,
mainly for conventional bridges. The Standard states that the earthquake load is taken as the horizontal force which
is determined based on the multiplication of the elastic response coefficient (Csm) with the equivalent structure
weight modified by the response modification factor (R). The Standard also determines that the earthquake hazardon bridges must be characterized using the earthquake acceleration response spectrum and site factors for theappropriate site class, so that the design response spectrum at ground level is obtained. To facilitate the designers
with this response spectrum, a web-based application called LINI was developed based on the Standard, using thelatest Indonesian seismic hazard map with probability of exceedance 7% in 75 years (equal to earthquake return
period of 1,000 years). LINI strives to always be updated so that it is in line with the latest data and conditions.
The latest update was the seismic hazard level zone maps, which was built based on the Standard, using the latest
Indonesian seismic hazard map with probability of exceedance 7% in 75 years and site classification factors. These
maps are expected to facilitate the designers in early stage of design and the stakeholders in prioritizing the existingbridges to maintain and/or to retrofit.
Keywords: Response spectrum, Earthquake resistant design of conventional bridge, Seismic hazard level zone
maps, Web-based application

INTRODUCTION

Standard also states that the earthquake load is taken
as the horizontal force which is determined based on
the multiplication of the elastic response coefficient(Csm) with the equivalent structure weight modified
by the response modification factor (R). Furthermore,
the Standard determines that the earthquake hazard on
bridges must be characterized using the earthquake
acceleration response spectra and site factors for theappropriate site class so that the design response
spectra at the ground surface are obtained.
To facilitate the designers with the design
response spectra, an application has been developed
based on the Standard.

Indonesia, tectonically speaking, is located amongsome main tectonic plates, i.e., Indo-Australian Plate,Eurasian Plate, and Pacific Plate; not to mention aminor one, the Philippine Plate. This condition makes
Indonesia one of the countries with high-level
seismicity. Earthquakes have occurred for many years
in Indonesia, but the great Sumatra earthquake in2004 had taken the attention of the public, nationwide
and worldwide, as it caused a massive disaster in
affected locations. Death tolls and the collapse ofbuildings and infrastructures were just some impactsof this event.
As a country prone to earthquakes, earthquakeresistant design is inevitable for buildings andinfrastructure in Indonesia. In anticipating earthquake
hazards on bridges, the Indonesian government
already has a standard related to earthquake resistancedesign for bridges, namely SNI 2833:2016, entitled
Bridge Design against Earthquake Loads [1]. It is
stated in the Standard that bridges must be designed
to have a small probability of collapse but can (or beallowed) significant damage and disruption toservices due to an earthquake with a 7% probabilityof exceedance in 75 years (equivalent to an
earthquake return period of 1,000 years). The

BRIDGEDESIGNINDONESIASTANDARDS

IN

Indonesia has had a standard for planning
earthquake resistance for highway bridges since1992. The standard was revised in 2008. Then anotherreview study was carried out to improve theperformance of bridge construction against
earthquakes and to revise the Standard. In 2016, thelatest Standard was published as a replacement for2008 one.
The significant improvement was the return
period and updated earthquake hazard maps used in107SEE-Mie, Japan, Nov.10-12, 2022

the Standard. The 2008 Standard only used one mapof the 500-year return period Peak GroundAcceleration (PGA). Meanwhile, the 2016 one used
three maps of the 1,000-year return period PGA, 0.2sec spectral acceleration (SS), and 1.0-sec spectral
acceleration (S1). The maps used in the 2016 Standard
referred to the Indonesia Earthquake Map which waspreviously prepared by the Indonesian Earthquake
Map Revision Team and published in 2010, which is
expected to represent the state of seismicity inIndonesia.
Another significant change was the developmentof design response spectra. The 2008 Standard used
only PGA to develop the design response spectra,
while the 2016 one used three points, i.e., PGA, S S,
and S1 to develop the design response spectra.

The application home displays some maps thatusers can choose to see. As default, it displays themap of horizontal Peak Ground Acceleration (PGA)
coefficient with 1,000-year return period. The othermaps are horizontal response spectral acceleration
coefficient at period of 0.2 s (SS) with 1,000-year
return period, horizontal response spectral
acceleration coefficient at period of 1.0 s (S1) with1,000-year return period, horizontal Peak GroundAcceleration (PGA) coefficient with 100-year return
period, horizontal Peak Ground Acceleration (PGA)
coefficient with 500-year return period, seismic zones
for all site classes, also cities and active faults lines.
Features

LINI APPLICATION
Location
LINI is a web-based application to determine thedesign response spectra at the ground surface forearthquake return period of 1,000 years. It is a tool
and an integral part of the Standard and wasdeveloped based on general procedure stated in theStandard. The general procedure is the determinationof the design response spectra at ground surface forthe site classes of hard soil (SC), medium soil (SD),and soft soil (SE) with the help of standard maps andamplification factors provided in the Standard.
LINI Application was developed in 2014 tofacilitate the designers in determining the design
response spectra. It is a web-based application with
GIS platform; hence users can use LINI wherever
there is an internet connection.
LINI
can
be
accessedon
https://lini.binamarga.pu.go.id.
Figure 1 shows the home of LINI Application.

Fig. 1Since it is developed with the GIS platform, LINI
can locate any place on land in the Indonesia region.
Meaning that LINI can determine design response
spectra as long as the place is located more than 10km from active faults.
LINI provides both cities and coordinates tolocate the place. Users can choose to pick any city or
input the coordinates (longitude and latitude in
decimal format) to get their desired locations.
Values of acceleration coefficients
LINI provides users with values of acceleration
coefficients without distance restriction.

Home of LINI application
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SEE-Mie, Japan, Nov.10-12, 2022

Site class determination

UPDATE OF LINI APPLICATIONLINI facilitates the users in determining the siteclass of their desired locations as long as they havethe soil data to input (see Fig. 2).

The 2014 LINI used the 2010 Indonesia seismic
hazard maps. In 2017, the National Center for
Earthquake Studies (PuSGeN) published an
Indonesian Seismic Sources and Hazard Maps [2]using additional identified active earthquake sources.
Accordingly, LINI has the urge to be updated to keep
the LINI application in line with the latest data.

Design response spectra
After the site class is obtained, the application
then can give the users with the design response
spectra. Nevertheless, if users have no soil data to
input to obtain the site class, LINI still provides themwith the design response spectra for all site classes(see Fig. 3).

Fig. 2

Page of site class determination on LINI

Fig. 3

Page of design response spectra on LINI

Hazard maps
LINI application adopted the 2017 Indonesia
seismic hazard maps using spline interpolation

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SEE-Mie, Japan, Nov.10-12, 2022

method so it was close to the one in PuSGeN’s. Thismethod estimated the value using a mathematical
function that minimizes the overall curvature of thesurface, resulting in a smooth surface that passes rightthrough the input point.

analysis requirements for seismic effects according toseismic zones. Since LINI already has the seismiczone maps, LINI also provides it to facilitate the users
with which minimum analysis to use whencalculating the seismic effects.
An example of minimum analysis to use is shownin Fig. 5.

Seismic zone maps

CONCLUSIONSThe seismic zone describes the variation ofseismic risk and and is used to determine the methodof analysis. Its maps were developed based onhorizontal response spectral acceleration coefficient
at 1.0-sec period modified by a long-period site factor(SD1) (see Table 1).

LINI application is a systematic, practical, andintegrated solution for knowing the value of seismic
acceleration coefficients for locations located > 10km from the active fault, the location of the seismic
source of the active faults, the seismic zones based on
SNI 2833:2016, the site class of a location, andgetting the design response spectra at ground surface
and determining the minimum analysis requirements
for seismic effects.

Table 1 Seismic zone
Acceleration coefficient, SD1
SD1 ≤ 0.15
0.15 < SD1 ≤ 0.30
0.30 < SD1 ≤ 0.50
SD1 > 0.50

Seismic zone
12
3
4

ACKNOWLEDGMENTS
We thank the National Center for Earthquake
Studies (PuSGeN) for the Indonesia Seismic Hazard
Maps.

LINI application provides seismic zone maps forall site classes, i.e., SA (hard rock), SB (rock), SC(very dense soil and soil rock), SD (stiff soil), and SE(soft soil). An example of a seismic zone map of siteclass SD is shown in Fig. 4.

REFERENCES[1] SNI 2833:2016, Perencanaan jembatan terhadap
beban gempa (Bridge design against earthquake
loads).
[2] National Center for Earthquake Studies(PuSGeN), Indonesian Seismic Sources andHazard Maps 2017.

Minimum analysis requirements for seismic
effects
The 2016 Standard stipulates the minimum

Fig. 4

Seismic zone map of site class SD on LINI

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Fig. 5

An example of the minimum analysis required for seismic effects on LINI

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12th Int. Conf. on Geotechnique, Construction Materials & Environment,
Bangkok, Thailand, 22-24 November 2022, ISBN: 978-4-909106087 C3051

EXPERIMENTAL MEASUREMENT OF THE LOAD-BEARING
CAPACITY OF WIRE HOOKS AND BENDS USED IN GABIONRETAINING WALLS
Radim Cajka1, Kamil Burkovic2, Zdenka Neuwirthova3, Petr Mynarcik4 and David Bujdos5
1,2,3,4,5

Faculty of Civil Engineering, VSB Technical University of Ostrava, Czech Republic
ABSTRACT

Gabion walls are today a very popular and ecological solution for retaining walls in civil engineering. Gabions
are made of stones placed in wire baskets made of galvanized wire, which are interconnected by hooks and bends.
Their advantage is the natural appearance, good conditions for landscaping and catching climbing plants. Unlike
concrete or masonry retaining walls, they cannot have cracks and therefore resist uneven subsidence of the subsoil.
However, the decisive factor for their load-bearing capacity is the quality of the quarry stone, its placement andthe load-bearing capacity of the individual wires and, above all, their joints. In the laboratories of the Faculty of
Civil Engineering of the Technical University of Ostrava, a number of tests of wire basket hook joints were
performed, which were taken from damaged gabions on construction sites. The results of these tests will enable
better prediction of the static effect of gabion walls in their design and implementation in construction practice.
The paper presents the results of these tests and recommendations for their design and planning.
Keywords: Gabion retaining walls, experimental measurement, load-bearing capacity of wire hooks and bends

INTRODUCTION

predict in which part the bearing capacity will bereached.

A gabion is a wire stone element in the shape of acube or cuboid, made of hexagonal steel mesh or
welded steel nets and filled with natural or quarrystone, or suitable recycled material. Gabions are used
for the construction of supporting and anti-erosion
structures, noise barriers, facing walls, etc. The usual
width and height of bonded gabions is 1 m, the length
is a multiple of 1 m. For welded gabions, thedimensions can be arbitrary (according to the
documentation) “Fig. 1”, [1], [2].
For the filling of gabions that have a structuralfunction (retaining walls, securing landslides, etc.),
only solid rock fragments or boulders that are notsubject to weathering, do not contain water-soluble
salts, do not swell and are not brittle must be used.
Rocks with higher specific gravity and low porosity
are preferred. The dimensions of the rock fragments
must be larger than the diameter of the mesh (net) sothat the stone does not fall out. Fragments of min. size
equal to 1.5 to 2 times the diameter of the eye. For the
purposes of the support structure, it is necessary touse clean stone, without admixture of fine-grained
soil.
However, all this affects their load-bearing
capacity and it may be hard to predict the bearing
capacity precisely. Therefore, numerous of scientists
trying to predict and improve designing methods [3],[4]. Precise calculations ensure safe and long-lasting
design and prevents failure [5], [6]. Therefore, several
test were made in the laboratories of the Faculty of
Civil Engineering of the Technical University ofOstrava to help better prediction in the future and to

GABION WALLS DESIGN
There are no standards on how to design a gabion
wall in the Czech Republic. There are only
recommendations, general procedures and technicalregulations.
It is recommended that gabions that fulfill a static
function (retaining or frame wall) are designed
according to the principles stated in Eurocode 7-1(ČSN EN 1997-1) [7].
Gabions that have only an aesthetic function(covering) are assessed together with the supporting
structure. Under normal conditions, the height of thegravity gabion structure should not exceed 6 m. The
gabion lining can also be part of a reinforced soil
structure. In this case, the stabilizing elements arehorizontal reinforcements (extended steel gabion nets
or polymer grids fixed to the gabion basket, or
between the layers of individual baskets) and thegabions fulfill the function of face fortification in thesense of ČSN EN 14475 [8] and TP 97 [9].
Gabions with a static function
For the filling of gabions that have a structuralfunction (retaining walls, securing landslides, etc.),
only solid rock fragments or boulders that are notsubject to weathering, do not contain water-soluble
salts, do not swell and are not brittle must be used.
Rocks with higher specific gravity and low porosity
are preferred. The dimensions of the rock fragments
112

GEOMATE – Bangkok, Thailand, 22-24 November 2022

must be larger than the diameter of the mesh (net) sothat the stone does not fall out. Fragments of min. size
equal to 1.5 to 2 times the diameter of the eye. The
maximum stone size is 2.5 times the mesh width inmm. Stones larger than 2.5 times the size of the meshmesh can occur only occasionally and their total
volume must not exceed 5% of the gabion volume.
Fragments smaller than the diameter of the meshmesh can be used in an amount not exceeding 10% of
the total volume for filling gaps and wedging larger
stones inside the gabions (outside the faces). For the
purposes of the support structure, it is necessary touse clean stone, without admixture of fine-grained
soil.

Fig. 2
Detail of steel wire attachment partiallyunfolded during usage

Gabions without static function
Design problems
The stone used in the face of gabions that do nothave a static function (anti-noise and cladding walls)
must meet the same requirements as gabions with aload-bearing function. Other material can be usedbehind the facing layer of stone according to the
documentation (unsorted stone, concrete fragments,
recycled gravel, etc.). The growth of vegetation canalso be allowed for these gabions.

With this very broad information it is very hard todesign a proper designing method. The main concern
is how to properly design bearing capacity ofanchoring wires which provide the main bearing
function and secure the gabions against overturning“Fig. 2”. Due to lack of designing information andincorrect suggestion it may result even in pull out of
the wire and therefor a construction damage “Fig. 3”.

Fig. 3
Detail of steel wire attachment after
reaching its bearing capacity
LABORATOR TESTS
Fig. 1

Example of gabion wall
In the laboratories of the Faculty of Civil
Engineering of the Technical University of Ostrava
were performed tensile tests of the supplied anchor
wires, which were used for anchoring the gabion wall.
Tested wires
Steel wires with corrosion protection, probably
ZnAl, were supplied for the tests. The exact material
characteristics of the wire were not the subject of the113

GEOMATE – Bangkok, Thailand, 22-24 November 2022

assignment of the assessment. The specimens were
supplied with bends which were used in anchoring thegabion wall. The length of the wires ranged from 680
to 800 mm, with a bend length of 100-110 mm ”Table
1”. The cross-section of the wire is round and smooth,i.e. without ribs, with a diameter of 6 mm.

Table 1
wires

Lengthofthedisplacement of theNo.
crossbar (stretchingof the wire in thebend) [mm]
1
86,7
2
87,9
3
87,8
4
104,2
5
106,3
6
108,8
Minimum tensile force:
Average tensile strength:

Table 1 The shape of the bends of the tested wires

No.

Wire
bend
opening[mm]

Length of thebent part of
the rod fromthe bending
axis [mm]

1
2
3
4
5
6

130
130
70
90
90
150

110
110
110
100
100
100

The shape of the bends of the tested

Length ofthe straightpart of therod from thebend axis tothe jaw
[mm]
190
230
210
250
240
240

Maximum pullforce [kN]
0,84
0,63
1,51
1,32
1,86
0,75
0,63 kN
1,15 kN

Course of the test
The tests were carried out on an EU 40 hydraulicpress with mechanical jaws. A wire with a longer
bend was placed in the upper jaws so that the jaws of
the press would grip both ends of it. The upper wirebasically represented part of the metal structure of thegabion. A wire with a bend was placed in the lower
jaws, which was used on the assessed object, i.e. witha bend length of 100 110 mm. The cross-section of
the wire is round and smooth, i.e. without ribs, with adiameter of 6 mm.
The wire samples showed quite significant shapedeviations from the plane. The largest irregularities
were partially eliminated before the tensile tests
began. Before the test, the shapes of the bends wereroughly measured for individual wires with anaccuracy of 10 mm “Table 1”.
As part of the experimental tensile tests of wire
bends, the loading speed according to ČSN EN ISO
6892-1: Metallic materials – Tensile testing – Part 1:
Test method at room temperature (1/2017) was used.
Table 2 and Figure 4 shows the results of the tensile
tests.
Figure 5 and Figure 6 shows the test itself. Thereis a wire with a hook in the bottom and from the upper
there is a hydraulic press measuring the lead. Figures
are in respective order how it looks during the test.

Fig. 4bends

Working diagram of tensile tests of wire

Fig. 5Progress of the tensile test of wire –
unfolding the bend. (Sample no. 4 at the start of thetest – left, sample no.5 during the test)

114

GEOMATE – Bangkok, Thailand, 22-24 November 2022

This result was obtained with the financial supportof the contribution of the conceptual development ofscience, research and innovation for 2022 VSB Technical University of Ostrava.
REFERENCES[1] Chikute GC, Sonar IP. Gabion wall: Eco-friendly
and cost-efficient retaining wall. Lect Notes Civ
Eng 2021;124 LNCE:229-49.
[2] Lamerdonov, Z. G., T. Yu Khashirova, S. A.
Zhaboev, M. A. Enaldieva, A. M. Chochieva,
and K. Z. Lamerdonov. 2020. "Operational
Experience of Gabion Shore Protection
Structures on Mountain Rivers and some
Suggestions for their Improvement." Ecology
and Industry of Russia 24 (10): 8-12.
doi:10.18412/1816-0395-2020-10-8-12[3] Saravanapriya S. Experimental investigation on
improvement in strength characteristics ofgabion wall. Int J Civ Eng Technol
2018;9(9):628-41.
[4] Zhang H, Liu G, Liu W, Chen Z, Liu Q, Xu G.
Experimental study on failure mode andmechanical characteristics of gabion material.
Constr Build Mater 2022;344.
[5] Carneiro D, Barros PLA, Labaki J. Groundvibration attenuation performance of surface
walls. Comput Geotech 2022;149.
[6] Chikute GC, Sonar IP. Failures of gabion walls.
Int
J
Innov
Technol
ExplorEng
2019;8(11):1384-90.
[7] EN 1997-1 EUROPEAN STANDARD.
Eurocode 7: Geotechnical design. 2004.
[8] European Standard EN 14475:2006. Executionof special geotechnical works - Reinforced fill.
2006.
[9] Technical quality conditions of road
constructions, chapter 30, Special earth
construction, Ministry of Transport, Departmentof Road Infrastructure, Approved: MD-OSI No.
1001/09-910-IPK/1, dated 17/12/2009 witheffect from January 1, 2010, with thesimultaneous cancellation of the second versionof this chapter of the TKP, approved by MDSOPK No. 24610/97-120, Prague, ARCADIS
Geotechnika, a.s., December 2009

Fig. 6
Progress of the tensile test of wire –
unfolding the bend. (Sample no.3 in two different
stages)CONCLUSIONS
Based on the conducted experiments, it can bestated that during the tensile tests, the bends of thewires were straightened at a maximum force in therange of 0.63 - 1.86 kN. The average value of the
maximum tensile force required to straighten the bend
is 1.15 kN. Tensile strength of steel was notexceeding and therefore, the tensile force of
unfolding bend is the bearing capacity of this anchor
element.
At the same time, it is necessary to draw attention
to the fact that the wire connection test was carriedout in free space, in real conditions (when the wire iscovered with aggregate) the bending failure would
probably occur at a higher tensile force.
Considering the bearing capacity of the wire itself
the force opening the bend is the limiting capacity of
the gabion. In addition, this force will be affected bymanner, if and how the eye will be closed and fixed.
In this case, the least load-bearing variant without ties
was verified.

ACKNOWLEDGMENTS

115

Engineering

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

A NEW TYPE OF ELECTROMAGNETIC-VIBRATION PUMP WITH
HIGH EFFICIENCY AND FLOW RATE
* Hiroyuki Yaguchi1, Takuya Watanabe1 and Toshiki Mishina1
1Faculty of Engineering, Tohoku Gakuin University, Japan
ABSTRACT
Small pumps with excellent performance are in demand in various industrial fields. In the present study, a
new type of small underwater insertion pump that combines electromagnetic force and mechanical resonancewas developed. A prototype electromagnetic-vibration pump with a one-valve structure in which the vibration
component and water are separated by a thin film was constructed. The shape of this pump was optimallydesigned for the casing and valves. Rod and piston-type casings have been proposed to effectively use thedisplacement of the vibration component. By the inertial effect of water due to the operating principle, thin film
separation, and shape optimization, the maximum efficiency of this pump was 19.1%, which exceeds that ofpreviously proposed small pumps. In addition, as a normal use of the prototype pump, the pump with an acrylic
pipe attached to the inlet port was improved, and its flow rate characteristics were examined. These two pumps
can be directly driven by the power of a power outlet by tuning the resonance frequency of the vibration
component. The proposed pump can be used in two ways depending on the application.
Keywords: pump, vibration, one-valve pump, optimized shape, pumping head, efficiency, mass flow.

underwater insertion pump that combines
electromagnetic force and mechanical resonance wasdeveloped. This small vibration-type pump converts
the generated resonance energy into kinetic energy
and effectively discharges water. A prototype pumpwith a one-valve structure in which the vibration
component and water are separated by a thin film
was prototyped. The shape of this pump was
optimally designed with respect to the casing andvalves. Rod and piston-type casings have been
proposed to effectively use the displacement of thevibration component. By the inertial effect of water
due to the operating principle, thin film separation,and shape optimization, the maximum efficiency ofthis pump was 19.1%, which exceeds that ofpreviously proposed small pumps. In addition, as anormal use of the prototype pump, the pump with anacrylic pipe attached to the inlet port was improved,
and its flow rate characteristics were examined. It
was clarified that this small vibration-type pump hasa very simple structure and can discharge water witha pumping head exceeding 1,000 mm. Two types ofpump with high performances capable of use in two
ways are described in the present paper.

INTRODUCTION
Small pumps with excellent performance are inhigh demand in various industrial fields, such as thefields of machinery, civil engineering, agriculture,chemical analysis, and medical care. For this reason,
various types of small pumps have been developed.
In particular, the axial flow pump [1], centrifugal
pump [2], and diaphragm pump [3] have been
actively studied. An electromagnetic motor is used
as a drive source for these pumps because theefficiency of the pump depends on the efficiency ofthe electromagnetic motor. Accordingly, due to thelow efficiency of the small motors installed, theefficiency of the small pumps is quite low.
A piezoelectric pump [4 - 6] is a typical pumpthat does not use an electromagnetic motor.
Although this pump is characterized by highefficiency, it has a problem with respect to durability
and is expensive. Even so, the efficiency of the small
piezoelectric pump is less than 5%.
Therefore, considering environmental problemsof note in recent years, pumps and motors areincorporated in many devices, and improving theefficiency of these basic devices is an important
engineering problem.
For this reason, the authors prototyped avibration-type pump [7], in which a drive unit
having a vibration component was inserted into
water, and showed the flow rate characteristics ofthe prototype pump. However, the efficiency of thispump is low, and the operation principle has notbeen clarified.
In the present study, a new type of small

OUTLINE OF THE VIBRATION-TYPE PUMP
Fig. 1 shows a small electromagnetic-vibration
pump for an underwater insertion-type pump. Thisvibration-type pump consists of an acrylic casing, athin silicone rubber film, a vibration component, an
acrylic bar, and a discharge valve. In this pump, athin silicone rubber film with a thickness of h (mm)
was installed on top of the vibration component to117

SEE-Mie, Japan, Nov.10-12, 2022

b

B

b

32 mm

24 mm

2 mm

8 mm
0.05 mm

118

25 mm

2 mm

Φ 6 mm

15 mm

44 mm

80 mm

Acrylic bar

6 mm

15 mm

at the head portion is reduced, water can be sucked
prevent contact between water and the vibration
up from the inlet port. Based on the results of acomponent. The part above the silicone rubber film
previous study [7], a clearance of 1.5 mm wasis defined as the head portion, and the portion below
provided between the rod and the casing so thatthe silicone rubber film is defined as the vibrationwater could flow between them. Water is discharged
portion. As a result, water flows into the headintermittently by repeatedly increasing andportion, and only air is injected into the vibration
decreasing the pressure over one cycle of vibration.
portion. Since the vibration component vibrates in
the atmosphere, no viscous resistance of water isΦ19 mmgenerated. The valve is a one-valve system with only
Φ15 mmdischarge and has a very simple structure.
Outlet
The acrylic rod and piston-type casings haveInletbeen developed to effectively use the displacement
Valveof the vibration component. An inlet port and an
Inlet
outlet port having a diameter of 6 mm are attachedto the head part, as shown in Fig. 1.
Rubber film
The vibration component consists of a ring- Rubber
Φ 28 mmfilm
shaped permanent magnet and a compression coil
Φ33 mmspring. The permanent magnet is a neodymium ringmagnet with an outer diameter of 12 mm, an inner Acrylic
diameter of 9 mm, and a height of 5 mm. As the frame
spring, a compression coil spring with a free lengthof 25 mm, an outer diameter of 12 mm, and a spring Acrylic
base
constant of k = 2,691 N/m was used.
As shown in Fig. 2, an iron core with a bobbinΦ 29 mmshape was used as an electromagnet for exciting thevibration component. A copper wire with a diameterΦ 33 mmof 0.2 mm was wound 1,200 times to make anelectromagnet. By combining a ring-type permanent(a) Outline(b) Head portion andmagnet and the bobbin-type permanent magnet, thephotographelectromagnetic force can be efficiently converted
Fig. 1. Structure of the vibration-type pump.
into excitation force [8]. As shown in Fig. 2, for theΦ12 mmΦRiron disk, the diameter is R = 8 mm, and the
Bobbin-type
9mm
Φ
thickness is b = 1 mm. In addition, the shaft
iron core
Ring-type
diameter is r = 3 mm, and the length is B = 26 mm.
permanent
The acrylic bar was mounted on the vibration
magnetcomponent to increase the effect of pushing up therElectroCoil
water.
magnetFig. 3 shows the structure and dimensions of thevalve. A triangular acrylic support was attached toCoilan acrylic disc with a thickness of 2 mm, an outerspringΦ12 mmdiameter of 19 mm, and an inner diameter of d (mm).
The dimensions of the thin silicone rubber material
Fig. 2. Vibration component and electromagnet.
for the valve are 8 mm wide, 10.5 mm long, and0.05 mm thick. By attaching a thin silicone material
Triangular10.5 mmto the triangular acrylic support, stable bending
acrylic
rigidity in the valve was obtained.
supportHole
This pump is inserted into water, and AC power
is input to the bobbin-type electromagnet to resonate
the vibration component. An acrylic bar with a
Silicon Rubber
diameter of 12 mm and a length of L (mm) attachedto the top of the vibration component via the silicone
Acrylic
1 mm 1.5 mm
rubber film vibrates in the vertical direction. As
plateshown in Fig. 1, when the acrylic bar is displaced
upward, the pressure near the valve increases. TheΦ d mmthin silicone material in the valve is pushed up, andwater is drained. On the other hand, when the acrylic
6.5 mmbar is displaced downward, the pressure near thevalve decreases. For this reason, the valve closes andFig. 3. Structure of the one-valve pump andprevents backflow of water. Thus, since the pressure
photograph.

SEE-Mie, Japan, Nov.10-12, 2022

As shown in Fig. 1, the dimensions of the headportion are when the length of the acrylic bar is 25
mm. The prototype pump has a height of 80 mm, anouter diameter of 33 mm, and a total mass of 41 g.

Mass flow rate (g/s)

8

OPTIMUM DESIGN FOR THE SHAPE OF
THE VIBRATION-TYPE PUMPAs shown in Fig. 1, the shape of the vibrationtype pump for an underwater insertion-type was
optimized for the following three items:(1) Length of the acrylic rod: L (mm)(2) Thickness of the silicone rubber film for water
separation: h (mm)(3) Diameter of the outlet port in the valve: d (mm)The prototype pump was inserted into an acrylictank having a width of 350 mm, a length of 250 mm,
and a height of 200 mm.
As shown in Fig. 4, the pumping head was 200
mm, and the flow rate was measured. An acrylic
pipe with an inner diameter of 6 mm was used as thepipe from the outlet port. The vibration component
was driven at the resonance frequency by a signal
generator and amplifier. The resonance frequency is
70 Hz. The input voltage, current, and power to theelectromagnet were measured using a power● : 0.01 mm▲ : 0.05 mm■ : 0.1 mm

6
4
2

0

0.02

0.04

0.06

0.08

0.1

Input power (W)Fig. 6. Relationship between input power andmass flow rate (thickness of the silicone rubber film).

Mass flow rate (g/s)

8
6
4
2

0

Mass flow● : 3 mm
▲ : 4 mm
■ : 5 mm

0.02

0.04

0.06

0.08

0.1

Input power (W)(2)

Fig. 7. Relationship between input power and mass
flow rate (diameter of outlet port in the valve).

(3)

Pumpinghead, HElectronicbalanceanalyzer. The mass of discharged water wasmeasured for 30 seconds using an electronic balance.
The water temperature was measured as 20 degrees.
The pumping head (H = 200 mm), the diameter(d = 4 mm) of the outlet port in the valve, thethickness (h = 0.01 mm) of the silicon thin film, andthe effect of the length, L (mm), of the acrylic rod
were examined. Fig. 5 shows the relationshipbetween the input power to the electromagnet andthe flow rate per second by changing the length, L(mm), of the acrylic rod to 15 mm, 25 mm, and 30
mm. The highest efficiency was shown when the rod
length was 25 mm. This indicates the existence of an
optimum rod length. As the rod length increases, theeffect of pushing out water increases. However, as
the rod length increases, the contact area between
the water and the rod increases and the viscous
resistance to the vibration component increases.
Therefore, it is considered that the optimum lengthof the rod exists.
The effects of the thickness, h (mm), of thesilicone rubber film for water separation were
examined with the pumping head (H = 200 mm),length (L = 25 mm) of the acrylic rod, and the outlet
port diameter of the valve (d = 4 mm). Fig. 6 shows
the relationship between the input power to theelectromagnet and the flow rate per second byvarying the thickness, h (mm), of the thin silicone

Optimization procedure

Bar

Outlet
Inlet

(1)

Power
analyzer

Water

AmplifierFunction
generator

Acrylic water tankFig. 4. Experimental apparatus and optimization
procedure.

Mass flow rate (g/s)

86● : 15 mm▲ : 25 mm■ : 35 mm

4
2

0

0.02

0.04

0.06

0.08

0.1

Input power (W)Fig. 5. Relationship between input power and mass
flow rate (length of the acrylic rod).
119

SEE-Mie, Japan, Nov.10-12, 2022

Mass flow
Vibration
exciter
Pumpinghead, HElectricalElectronicbalancebalance
Rod 2

Beam 1
PsinωtRod 1
Amplifier

Inlet

Rod 3
Function
generator

Beam 2
Water

Base

Acrylic water tankFig. 8. Experimental setup for the operating
principle.

Laser
displacement
meter

Digitaloscilloscope

Psinωt2a

PsinωtValve

Beam 12arubber film to 0.01 mm, 0.05 mm, and 0.1 mm.
From the figure, the flow rate increases as the input
power increases. When the silicone rubber film
thickness is thin, this pump shows good flow ratecharacteristics. As the silicone rubber film thickness
increases, the viscous resistance of the membranematerial to the vibration component increases.
Therefore, when the silicone rubber with a thicknessof h = 0.01 mm is used, the flow rate characteristics
are the best.
The pumping head (H = 200 mm), the length(L = 25 mm) of the acrylic rod, the silicon thin film
thickness (h = 0.01 mm), and the effect of holediameter, d (mm), at the outlet port in the valve were
examined. Fig. 7 shows the relationship between the
input power to the electromagnet and the flow rate
per second by varying the hole diameter, d (mm), of
the outlet port in the valve as 3 mm, 4 mm, and
5 mm. From the figure, the highest efficiency occurs
when the hole diameter is 4 mm. However, thediameter of the hole in the valve portion isconsidered to be affected by the pumping head.
By examining three items, the value of (1) the
length (L = 25 mm) for the acrylic rod, (2) the
thickness (h = 0.01 mm) for the silicone rubber film
for water separation, and (3) the diameter (d = 4mm) for the outlet port in the valve are selected tomaximize the flow characteristics of this pump.

Rod 2

Rod 3

INERTIA EFFECT DUE TO VIBRATIONDISPLACEMENT OF THE ROD

Beam 2
Fig. 9. Details of the experimental setup.

This pump creates a pressure difference by the
combination of the acrylic rod and the casing. Water
cannot be sucked in and drained if the acrylic rod is
not mounted on the vibration component at thispump. In addition, if the clearance between theacrylic rod and the casing is 0 mm, then watercannot be sucked from the inlet port. As mentioned
above, the clearance between the rod and the casing
was set to 1.5 mm, and the water discharge
characteristics due to the vibration displacement of
the rod were examined.
It is difficult to directly measure thedisplacement of a vibration component inserted inwater with various sensors. The displacement wasmeasured using the experimental apparatus shown in
Fig. 8. In the experiment, the sine wave generated by
the signal generator was amplified by an amplifier,and the exciter was vibrated harmonically. The
vibration part of the exciter, two beams, and threerods were connected and inserted into the casing of
the pump.
As shown in Fig. 9, when forced displacement
is generated by the exciter, rod 3 is displaced. The
acrylic rod attached to the vibration component, androd 3 has the same dimensions. In addition, thecasing and valve have the same dimensions as the
optimized vibration-type pump. The vibration

Ratio of inertia effect

0.9● : 65 Hz▲ : 70 Hz■ : 80 Hz

0.8
0.7
0.6
0.5
0.4
0.4

0.5

0.6

0.7

0.8

0.9

Total amplitude (mm)Fig. 10. Relationship between total displacement
and ratio of inertia effect.
displacement of rod 3 was substituted by measuring
the displacement of beam 1 using a laser
displacement meter and a digital oscilloscope.
When the vibration component vibrates at afrequency, f (Hz), the change in the flow ratecharacteristics due to the displacement amplitude
was investigated. For the purpose of clarifying theoperation of this pump, the ratio of the inertial effectwas defined as follows:
Ir = (Q / f ) / V, V = 2aπd2
120

(1)

SEE-Mie, Japan, Nov.10-12, 2022

8

Mass flow rate (g/s)

Ratio of inertia effect

1
0.8
0.6
0.4
0.2
100

● : 0.5 mm▲ : 0.7 mm■ : 0.8 mm

200
300
Pumping head (mm)

400

2

0.1

0.2
0.3
0.4
Input power (W)

0.5

0.6

Fig. 12. Relationship between input power andmass flow rate (underwater insertion-type pump).

where Ir is the ratio to the volume, V (mm3), when
the acrylic rod with radius d (mm) vibrates with a
total amplitude of 2a (mm) and a flow rate persecond of Q (mm3/s).
Fig. 10 shows the ratio, Ir, of the inertia effectby changing the drive frequency of the exciter when
the pumping head, H, is set to 200 mm. As the total
amplitude increases, the inertial effect increases. In
addition, when the frequency is 70 Hz and the total
amplitude is 0.8 mm, approximately 80% of thevolume, V, of water due to vibration is discharged.
Fig. 11 shows the pumping head, H, and the ratio,
Ir, of the inertial effect by changing the total
amplitude of rod 3 when the drive frequency is 70
Hz. The inertial effect decreases as the pumping
head, H, increases. On the other hand, when thepumping head is H = 100 mm, the ratio Ir of theinertial effect exceeds 90%, and approximately thesame volume of water as the volume due to vibration
displacement can be discharged. The obtained
results are summarized as follows:
1) The inertial effect is proportional to the increase
in drive frequency.
2) As the amplitude of the vibration component
increases, the inertial effect increases.
3) When the pump head, H, is low, even if there isa clearance between the rod and the casing, the sameamount of water as the volume due to the total
amplitude of vibration can be discharged.

Efficiency (%)

20● : 200 mm▲ : 500 mm■ : 1,000 mm

10

0

0.1

0.2

0.3

0.4

0.5

0.6

Input power (W)Fig. 13. Relationship between input power andefficiency (underwater insertion-type pump).
Mass flow

Pumpinghead, H 2

Electricalbalance

Function
generator

Inlet
OutletPumpinghead, H1

AmplifierPoweranalyzer

Water

THE

Fig. 14. Outline of the one-valve normal-type pump.
and t (s) is the measurement time. The mass flow
was measured with an electronic balance.
Figs. 12 and 13 show the relationships between
the inp ut p o wer to the electro magnet and ,respectively, the flow rate per second and efficiency
by changing the pumping head, H. The flow rateincreases approximately linearly as the input powerincreases. Furthermore, when the pumping head is
H = 1,000 mm, approximately 1.8 g of water can bedischarged per second. On the other hand, when the
input power is 0.02 W and the pumping head is

As shown in Fig. 1, an underwater insertion-typepump with three shape optimizations was prototyped
and tested. The drive frequency of the vibration
component is 70 Hz. The efficiency, η, of the pumpis expressed as follows:η = 100 × Mf g H / P t

40

Fig. 11 Relationship between pumping head andratio of inertia effect.

FLOW
CHARACTERISTICSOF
OPTIMIZED VIBRATION-TYPE PUMP

● : 200 mm▲ : 500 mm■ : 1,000 mm

6(2)

where Mf (kg) is the mass flow, g (m/s 2 ) is theacceleration due to gravity, H (m) is the pumping
head, P (W) is the input power to the electromagnet,
121

SEE-Mie, Japan, Nov.10-12, 2022

pump had a maximum efficiency of 19.1%.
Furthermore, the operating principle of this pump
was clarified experimentally, and the effect of theinertial effect of water was clarified.
As a normal application of the prototype pump,an acrylic pipe was attached to the inlet port, and thesuction characteristics of the pump were examined.
The maximum efficiency of this pump was 5.1%,
which was shown to exceed that of commerciallyavailable pumps. This vibration-type pump has avery simple structure and can send water exceeding
1,000 mm to the pumping head.
The proposed pump can be used in two ways
depending on the application. The underwater
insertion-type pump can be applied to circulation inwater tanks and cooling devices, and the normaltype pump can be applied to specific industrial
applications. In addition, these vibration-type pumps
can be directly driven by the power of a power outlet
by tuning the resonance frequency of the vibration
component.

Mass flow rate (g/s)

108● : 500 - 0 mm
▲ : 500 - 100 mm■ : 500 - 200 mm 〇 : 500 - 300 mm◎ : 500 - 500 mm

6
4
2
0

0.5
1
Input power (W)

1.5

Fig. 15. Relationship between input power andmass flow rate (normal-type pump).

Efficiency (%)

6● : 500 - 0 mm
▲ : 500 - 100 mm■ : 500 - 200 mm ○ : 500 - 300 mm◎ : 500 - 500 mm

4

REFERENCES
2

0

0.5
1
Input power (W)[1] S. Momosaki, S. Usami, S. Watanabe and K.
Okuma: ‘Experimental Study on Rotational
Speed Control of Contra-Rotating Axial Flow
Pump’, Journal of TSJ, Vol. 39, No. 2,
pp.119-125 (2011).
[2] T. Shigemitsu, J. Fukutomi, M. Takumi and S.
Masahiro, ‘Unsteady Flow Condition ofCentrifugal Pump for Low Viscous Fluid Food’,
International Journal of Fluid Machinery and
Systems, Vol. 10, No. 4, pp. 432-438 (2017).
[3] C. Cabuz, W. Herb, E. Cabuz and S. Lu,‘The dual diaphragm pump 14th IEEE Int. Conf.
on Micro Electro Mechanical Systems’, DOI:
10.1109/MEMSYS.2001.906593 (2001).
[4] J. Kim, ,C. Kang and Y. Kim : ‘A disposable
polydimethylsiloxane – baseddiffuser pumpactuated by piezoelectric-disc’, Microelectron.
Eng.,Vol. 71, No. 2, pp. 119-124 (2004).
[5] J. Sateesh1, K. Rao, K. Sravani1, K. Guha andR. Kumar : ‘Design and Optimization of MEMS
Based
Piezo-ElectroMicro
Pump’,4th
International Conference on Microelectronics,
pp. 1200-1206 (2017).
[6] Q. Yan, Y. Yin, W. Sun and J. Fu : ‘Advances
in Valveless Piezoelectric Pumps’, Appliedscience, Vol. 11, No. 15, pp. 1-12 (2021).
[7] H.Yaguchi, T. Mishina and K.Ishikawa : A New
Type of Magnetic Pump with Coupled
Mechanical Vibration and Electromagnetic
Force, Journal of Mechanical Engineering andSciences, Vol. 13, No. 3, pp 5212 - 5227 (2019).
[8] H. Yaguchi and S. Sakuma : Improvement of aMagnetic Actuator Capable of Movement on a
Magnetic Substance, IEEE Transactions on
Magnetics, Vol. 52, No. 7, pp.1-4 (2016) ．

1.5

Fig. 16. Relationship between input power andefficiency (normal-type pump).
H = 200 mm, the maximum efficiency of this pumpis 19.1%. This is because the inertia effect of theacrylic rod is acting. Due to the inertial effect, when
the pumping head, H, is low, the efficiency of the
prototype pump is significantly higher than that ofcommercial products.
As a normal application of the pump, an acrylic
pipe with an inner diameter of 6 mm was attached tothe inlet, as shown in Fig. 14, and the flow ratecharacteristics of the pump were investigated.
Figs. 15 and 16 show the relationships between
the inp ut p o wer to the electro m agnet and ,respectively, the flow rate per second and efficiency
by varying the pumping head (H1 = 500 mm) and H2from 0 mm to 500 mm. The prototype one-valve
pump can discharge 2.16 g of water per second at a
pumping head of 1,000 mm. The maximum
efficiency was approximately 5.1% at an input
power of 0.38 W when the total pumping head,
H (= H1 + H2), was 500 mm.
CONCLUSIONS
A small one-valve electromagnetic-vibration
underwater insertion-type pump was proposed, andthe optimum shape of the pump was designed. When
this vibration-type pump was inserted into water, the122

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

GEOPHYSICAL INVESTIGATION OF GROUNDWATER RESOURCES
USING ELECTRICAL RESISTIVITY AND INDUCED POLARIZATIONMETHOD
Jannatul Hasni Omar1, Nordila Ahmad1, and Jestin Jelani1, Zuliziana Suif1 and Maidiana Othman1
Faculty of Engineering, National Defence University of Malaysia, 57000 Kuala Lumpur1
ABSTRACT
Identifying potential groundwater is crucial, especially in the area that faced water stress issue. However, whenutilizing 2-D resistivity and Induced Polarization (IP) survey, it can be challenging to distinguish groundwaterfrom soil particles. When drilling in the subsurface layers, many researchers struggled to determine the exact
position of the aquifer or missed the aquifer's full capacity. In order to assess the potential groundwater in Sungai
Besi, Kuala Lumpur, and to distinguish the saturated zones between an aquifer and unconsolidated sediments, thisstudy combines resistivity and IP analyses. The pole-dipole array was used to build up two resistivity surveylines; 200 metres (m) and 800 metres long. According to the results of the 2-D resistivity and IP survey, lowresistivity values between 10 and 100 m (Ohm-m) and low chargeability values between 0 and 1 millisecond canbe used to identify potential groundwater areas in the subsurface (msec). Silty sand and sandy clay make up
alluvium, which has a resistivity range of 125 to 255 m and a chargeability range of 7 to 10 msec. The presence ofgroundwater may also be indicated by type of soil profile from borehole data in the subsurface. By separating thesoil particles from unconsolidated sediments, the study's finding provides useful information on the presence ofgroundwater. This study is limited to two lines of 2D resistivity and Induced Polarization with 400m and 800m
long.
Keywords: Groundwater, Geophysical, Resistivity, Imaging and Potential.

[6] stated that groundwater is described as waterthat is found in soil pores and rock formation fracturesthat is below the surface of the Earth. Finding theexact position of the groundwater accumulation zone
in the subsurface layer is a challenge for engineers.
The 2D resistivity method is utilized as initial step inany groundwater exploration. With the help of 2D
resistivity inversion and supporting borehole data,reliable groundwater information can be generated.
However, when performing a resistivity survey,
there is uncertainty in distinguishing between soil
particles and groundwater. Therefore, the objective of
this research is to apply the combination of induced
polarization (IP) investigation and resistivity toidentify the groundwater potential in National
Defence University of Malaysia, Sungai Besi, Kuala
Lumpur. The study area has experienced of water
stress issue and it is important to have clean watersupply to the campus. The best option for this issue isgroundwater, and one benefit is that it can continue toexist even when all surface water has dried up or
becoming more scarce.

INTRODUCTION
Water of poor quality is a significant issue
today. Particularly in rural regions, identifying
potential groundwater is crucial. Compared to water
sources above the ground, including lakes and rivers,
groundwater is beneath the ground and higher quality.
When surface water is scarce or poor quality, findinga groundwater supply is one of the primary goals.
Geophysical surveys are one of the most reliable
ways to find a groundwater supply. The common
approach for geophysical survey is resistivity method
where it is able to identify sources of groundwater
potential [1]. This method is based on thecomposition and layering of the subsurface,interpretation of the soil's physical characteristics,
and underground structures, cavities, and bodies fromvarious geological environments [2]. It is also helpful
for figuring out an aquifer's boundary, thickness, anddepth [3].
According to[5], combines 2-D resistivity
techniques with Induced Polarization (IP) imaging for
groundwater exploration in a sedimentary
environment is the most popular geophysicalmethodology for hydrological research. Since bothclay and saturated sand formations have low
resistivity, it might be challenging to distinguish themapart. Through the integration of all available datafrom previous research, boreholes and geology, thelithology of the indicated layers was established [4].

Geological and Study Area
The study area for this research was selected at the
National Defence University of Malaysia in the
Sungai Besi Military Camp in Federal Territory of
Kuala Lumpur, at approximate 3° 3'2.16"N,
101°43'45.16"E, as shown in Fig. 1. The ground level123

SEE-Mie, Japan, Nov.10-12, 2022

elevation of the study area is from 90m to 161m
relative to Mean Sea Level (MSL). There is a tropicalclimate in this region. The rainfall in Kuala Lumpur
is a great deal, even in the driest month. In Kuala
Lumpur, the average temperature is 27.1°C around
80.8°F. The annual rainfall is huge, with 220 rainydays during the year and an average humidity of over
80%, to the tune of 2540 mm (100”) [7]. Geology
formation in National Defence University of
Malaysia, Sungai Besi, Kuala Lumpur is classified as
an intrusive rock of granite as shown in Fig. 2.

Fig. 1

Location of study area

Fig. 2Geological map of study area

exploration in UPNM. Two survey lines conducted at
the proposed area with length of 400m and 800m. The
length of 400m cable was laid with the minimum
spacing between electrode is 5 m and maximum
spacing is 10m. Whereas, for 800m cable was laidwith the minimum spacing between electrode is 10 m
and maximum spacing is 20m. The newest
Terrameter LS2 from ABEM was used formeasurement, which including several equipment asshows in Fig. 3 for the electrical resistivity andinduced polarization survey. Instruments used such as
4 units of multi-purpose cable, 64 units of jumper
cable, 61 units of stainless-steel electrode, 2 units ofcable connector, 1 unit of 12-volt battery, and 1 unitof remote cable. A 2D multielectrode ERI survey
using the instrument in Fig. 3 are conducted using 61
units of stainless-steel electrode connected to a
multicore cable. The electrode cable will be split into
parts of controllable length, which are then attached
end-to-end. Electrodes attach to the cable take-outs
are then placed along a survey line into the ground at
a specified daily interval [8]. The ABEM TerrameterLS2 is set up to measure resistivity and induced
polarization at the same time during data gathering.
Data processing will be conducted using the
RES2DINV software when the data acquisition isfinished [8]. The field data were processed using the
RES2DINV version 4.5.16 software package tocreate a 2D electrical resistivity and induced
polarization image. By using an inversion method, theresistance measurements of earth materials areconverted to apparent resistivity readings. The groundresistivity is affected by a number of geologicalfactors, including mineral and fluid composition,
porosity, and water saturation. Sedimentary rocks areoften more porous and have a larger water content
than igneous and metamorphic rocks, resulting inlower resistivity values. The resistivity contour value
is modified based on geological data that corresponds
to the resistivity range with various colours. Finally,correlations between the borehole record and thecontouring inversion model from this survey will be
made.

MATERIAL AND METHODLOGY
Fig. 3

Electrical resistivity imaging (ERI) and induced
polarization (IP) surveys are two hydrogeophysicaltechniques that have been conducted for groundwater
124

Multi electrode resistivity system tools

SEE-Mie, Japan, Nov.10-12, 2022

metres from the first electrode and up to a penetration
depth of 70 metres. Groundwater is represented byblue at a chargeability value of 0 to 1 milliseconds(msec), alluvium is represented by light green at achargeability value of 1 to 4 msec, and gravel isrepresented by dark green at a chargeability value of
3 to 9 msec [15]. Low chargeability is present in thesecond zone, which extends from a depth of 40 m toa distance of 280 m to 310 m.

RESULTS AND DISCUSSION
Figure 4 depicts how Line 1 was routed from NorthNortheast to South-South west). The borehole was
located 270 m from the first electrode. The resistivity
values were between 125 and 7400 m. (Ohm-m).
According to [9], the resistivity values of the top layer
with soil along the line range from 0.1 to 10 m. High
resistivity values are represented by the dark purple
colour, whereas low resistivity values are represented
by the blue colour. The resistivity values are
influenced by a number of geological factors,
including mineral content and fluid, water saturation,and rock porosity [3]. In accordance with theresistivity distribution, the groundwater potentialzone is located within the distance from 255m to
275m with the depth from 25m to 50m. However, thiswater potential area is not within the fractured zone
in order to exhibit a higher chance of groundwater in
granite formation. In fact, the water potential zone inthis area probably associated with weathered granite
environment. Low resistivity anomalies below 100
Wm have been observed and are thought to be an
aquifer zone or a water-saturated layer [10]; [11].

Figure 5 illustrates the correlation between theborehole record and the results of resistivity andchargeability surveys. From the borehole record,
topsoil was discovered between 0 and 4 m. From 4 to
6 m and 6 - 25 m, sandy clay and silty sandy was
discovered. Next, from 25 - 45 m alluvium was found.
According to [15], alluvium, which is made up of
sandy clay and sand, has resistivity values ranging
from 125 to 255 Wm and chargeability ranges from
7.5 to 10 msec. The chargeability value was out ofrange when compared to the Telford theory range of
1 to 4 msec for alluvium. Sandstone with resistivity
ranges of 170 to 340 Wm and chargeability ranges of
7.5 to 9.75 msec is found at depths of 45 to 55 m, but
the theory of Telford provides a range from 3 to 12
msec. Schist is found with resistivity values of 1200
to 1700 Wm at depths of 55 to 60 m, still overlappedon the resistivity value scale. However, Telford's
theory, which specifies a range of 5 to 20 msec, a little
bit slipped from the measured chargeability for schistfrom 7.5 to 10 msec. The granite layer that makes up
the last layer of the borehole, has resistivity values
ranging from 1700- 5700 Wm at 60–100 m depth,
which is slightly different from Frischknecht andKeller’s range of 2000–1,000,000 Wm, andchargeability values between 7.5 and 12 msec. which
is a little bit outside of the acceptable range for granite
according to the Telford theory, which is 10 to 50
msec

Next, integrated with induced polarization profile,
low chargeability values (<7.5ms) give a supportive
interpretation of water containing zone for this area.
As mentioned before, in water zone, the low values ofchargeability are reflecting to water saturated zone aswater is a poor medium to retain electrical charges.
The chargeability values for induced polarisation
indicate gravel, sandstone or alluvium. In contrast tocoarse soil, such as gravel and sand, fine grain soils
like silt and clay have a substantial composition ofminerals,suchasvermiculite,
kaolinite,and montmorillonite, that makes the current flow
easily and produces low resistivity values [12]. Twozones have low values for chargeability. The initialzone exhibits low chargeability between 20 and 270

Borehole

Fig. 4Inversion model of (a) 2D resistivity and (b) chargeability for line 1
125

SEE-Mie, Japan, Nov.10-12, 2022

0

Resistivity

Depth (m)-20
-40

Chargeability

from the first electrode. The line is straightened up to
800 m long; roughly 250 m is on the region of very
thick shrubs area and from 500 m onwards, is areawith a moderate to steep slope face. Other than that,the area is classify as flat landform. For survey line
2, water containing zone is less potential than the areaof survey line 1. This is because the water containingzone is mainly located in rock formation which isindication of low volume than survey line 1. It is
located at the distance from 580 m to 590 m with thedepth from 20m to 30m only as shown Figure 6. Thissurvey line was carried out on undulating topography.
Hence, the water containing zone probably infiltrated
from high topography (south) and accumulated
towards low topography region (north). Resistivity
value in line 2, at the bottom layer start of from highresistivity at depth 140 m to top layer with low
resistivity value at a depth of 20 m. The resistivity
values vary from 1 Ωm to 9000 Ωm. The layer withthe highest concentration of resistivity is coloured
dark purple based on the results of the resistivity
distribution, indicating the presence of a massive rockat a depth of 140 m, which is interpreted as granitewith resistivity value > 5000 Ωm. At a depth 120 m,
the green and yellow coloured area depicted in thedata as sandstone. Saturated layer presumed as blue
colour in the data at a depth of 20 m until 30 m due to
its low resistivity values of below 100 Ωm. Thissurvey line was carried out on undulating topography.
Hence, the water containing zone probably infiltrated
from high topography (south) and accumulated
towards low topography region (north).

Soil
Sandy Clay
Silty
SiltySandy
Sand
Alluvium
Sandstone
Sandstone-60

Schist-80

Granite-100
Fig. 5 Result of resistivity aligned with the borehole
record at line 1
As a result, the resistivity value was more accurate
than the chargeability value, which had a larger
range. However, the groundwater potential zone thatsituated between 255 and 275 meters distance at a
depth 25 – 50 m is not located within the fractured
zone in order to demonstrate a greater likelihood ofgroundwater in granite formation. Tables 1 and 2
provide a summary of resistivity and chargeability
values based on [15] and [16] 's theories, respectively.
Table 1: Resistivity value for soil and rocks [15]Material
Fresh groundwater
Clay
Sand
Alluvium
Sandstone
Shale
Limestone
SchistGraniteGneissResistivity (Wm)
10 - 100
1-100
60-1000
80-10010-1000
20-2000
50 - 4000
20 - 10,000
2000 – 1,000,000
10, 000 – 3,000,000

The induced polarization in the survey lines,
meantime, indicates some potential groundwater andalluvium. Resistivity values will lowered by thepresent of groundwater, and silt will also bring down
the resistivity value below groundwater. The
subsurface area that has been coloured in dark andlight blue at a depth of 0 to 30 m could be classified
as saturated zone with chargeability from 1 to 5 msec
[14]. Therefore, the maximum depth of potential
groundwater is at depth of 20 to 30 m with distance
580 to 590 m from the induced polarization (IP) at thefirst electrode. The high probability of finding
groundwater was when the chargeability value for the
groundwater was between 0 and 4.5 msec. The lightgreen colour at a depth of 60 -100 m could be consider
as sandstones. High chargeability can be found inorange colour with chargeability value of 20 to 30
msec and it can be represented as gneiss, while yellow
colour at 16 to 20 msec of chargeability value showedschist. The bigger resistivity values between theserocks is the best approach to distinguish a schist to agneiss with the value of resistivity greater than 5000

Table 2: Chargeability value [16]Material
Chargeability (msec)
Groundwater
0-1
Alluvium
1-4
Gravels
3-9
Sandstones
3 - 12
Schist5 - 20Gneiss
6 - 30Granite10 - 50
Limestone
10 - 20Shale
50 - 100
Lines 2 were set up in NWW (North West-west) toSEE (South wast-East), intersecting line 1 at 300 m
126

SEE-Mie, Japan, Nov.10-12, 2022

Ωm. This is consistent with the results of previous
studies conducted within the same geologic
environment [13].

polarization method to support the exploration due toits different chargeability values and not relying
solely on resistivity method only. Table 3 shows thesummary of the lithology in Sungai Besi, Kuala
Lumpur.

Unconsolidated sediments and groundwater in the
study area can be distinguished using induced

Fig. 6Inversion model of (a) 2D resistivity and (b) chargeability for line 2

Table 3 Summary of geophysical and geological of area Sungai Besi, Kuala Lumpur
Study Area
Sungai Besi,
Kuala
LumpurGeology
This area is consisting ofas schist, sandstone andgranite due to the area isin acid intrusive.

Method2-D
resistivity

Inducedpolarization

Values125 - 255 Ωm
0 - 125 Ωm
170 - 340 Ωm
1200 - 1700 Ωm
1700 - 5700 Ωm
0 - 1 msec
1 – 4.5 msec
3 - 12 msec
16 – 20 msec
20 - 30 msec
30 - 40 msec

Lithology
Alluvium
Saturated zone
Sandstone
SchistGraniteGroundwaterAlluvium
Sandstones
SchistGneissGraniteFrom the results, water containing zone interpreted
approximately about resistivity values below 100 Ωmand chargeability values below 7.5 ms. Integrated
with induced polarization profile, low chargeability
values make survey line 1 have more potential in termof water containing zone. Thus, survey line 1 give ahigher chance of groundwater containing zone thansurvey line 2. Also, the porosity and permeability of
sediments; clay, silt and sand indicate presence ofwater due to its water-flow when the area is being
recharged. From the analysis of induced polarization
results, the uncertainty between unconsolidated
sediments and groundwater was able to be deduced.

CONCLUSIONSThis study's primary significance is thecomprehensive investigation of the groundwater
potential zone of granitic formation at National
Defence University of Malaysia, Sungai Besi, Kuala
Lumpur. This study used resistivity and induced
polarisation techniques in granitic rock formation toassess the groundwater potential zone using ageophysical approach called electrical resistivity
survey. At the site, two (2) profile lines ofmeasurements were conducted at the proposed area
within National Defence University of Malaysia.
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SEE-Mie, Japan, Nov.10-12, 2022

Some recommendations for further studies are moreborehole wells purposes should be drilled due forbetter understanding on the groundwater at Sungai
Besi, Kuala Lumpur. This study is limited to twolines of 2D resistivity and Induced Polarization with
400m and 800m long.

[7] Arsene B., Elvis G., Daniel N. (2018).
Investigation for Groundwater Resources from
Electrical Resistivity Tomography and SelfPotential Data in the Meiganga Area, Adamawa
Cameroon. International Joirnal of Geophysics.
Vol, 2018 doi: 10.1155/2018/2697585.
[8] Arjwech and M. E. Everett (2015). Applicationof 2D electrical resistivity tomography toengineering projects: Three case studies.
Songklanakarin Journal of Science andTechnology, Vol. 37, no. 6, pp. 675–681.
[9] Riwayat, A. I., Nazri, M. A., & Abidin, M. H.
(2018). Detection of Potential Shallow Aquifer
Using Electrical Resistivity Imaging (ERI) at
UTHM Campus, Johor, Malaysia. Journal of
Physics.
[10] Amsir and Marwan (2015). The investigation ofgroundwater using geophysical techniques in
Baitussalam Sub district, Aceh Besar District,Aceh province, Indonesia. Electronic Journal of
Geotechnical Engineering, 20(205).
[11] Marsan, D., Azimmah, A., Adli, D, Muthi,
Yuantoro&
Fatkhan(2017).
Aquifercharacterization using 2D Electrical Resistivity
Imaging in Kidangpananjung, Cililin District,
West Java, Southeast Asian Conference on
Geophysics. Earth and Environmental Science, 62.
[12] Zainal A., Raqib A., Aziman M., Azhar A.,
Khaidir A., Fairus Y., Rosli S., Fakhrurrazi and
Izzaty (2017). Preliminary Groundwater
Assessment Method at Quaternary Deposits Area
using Electrical Method at Quarternary Deposits
Area. IOP Conference Series: Materials Scienceand Engineering, 12042[13] Nordiana and Haziq (2002). Evaluation of
Aquifer Potential Using 2D Resistivity andInduced Polarization in Machang, Kelantan.
Journal of sustainability Science and Management.
Vol 17 No 1, 259-270[14] Sowers G. (1979). Introductory soil mechanics
and foundations. Geotechnical Engineering. 4th
Edition. New York: Macmillan Publishing Co.,Inc.
[15] Frischkecht F. and Keller G. (1996). Electricalmethods in geophysical prospecting. Oxford:
Pergamon Press Inc.
[16] Telford W., Geldart and Sheriff R (1976).
Applied Geophysics. Cambridge University.

ACKNOWLEDGMENTS
The authors are grateful to the National Defence
University of Malaysia management, research andinnovation office for providing fund (Project code:
UPNM/2021/GPJP/PK/1) for this research.
REFERENCES[1] Oseji J., Atakpo E and Okolie (2005).
Geoelectric investigation of the aquifer
characteristics and groundwater potential in
Kwale, Delta State, Nigeria. Journal Applied
Science and Environmental Management., 9, 157– 160.
[2] Dor (2011). Verification of surface groundwater
connectivity in an irrigation canal usinggeophysical, water balance and stable isotope
approaches. Water Resources Management, 25(11), 2837 - 2853
[3] Omoyusi G. Adeyemo, A., and Adegoke (2007).
Investigation of groundwater prospect using
electromagnetic and geoelectric scounding at
afunbiowo near Akure, Southwestern Nigeria.
Pacific Journal of Science and Technology, 8, 172- 182[4] Aizebeokhai and Oyeyemi (2014). The use of themultiple-gradient array for geoelectricalresistivity and induced polarization imaging.
Journal of Applied Geophysics, 111, 364 – 376.
[5] Ahzegbobor, Aizebeokhai, Kehinde, Oyeyemi
and Emmanuel, S (2016). Electrical resistivity
and induced polarization imaging for groundwater
exploration convenant. SEG International
Exposition and 87th Annual meeting, 2487 – 2491.
[6] Muchingami I., Hlatywayo D., Nel J., and Chuma
C. (2012). Electrical resistivity sirvey forgroundwater investigations of the basaltic
greenstone formation of the urban Bulawayo
aquifer. Physics and Chemistry of the Earth, Parts
A/B/C, 50, 44-51.

128

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

MACHINE LEARNING MODELS TO DETERMINE THE
COEFFICIENT ANGLE OF FRICTION OF MAKATI CITY,PHILIPPINES SOIL LAYERS
Joenel Galupino1 and Jonathan Dungca1
1

Faculty, De La Salle University, Manila, Philippines
ABSTRACT

Seismic activity in the Philippines is caused by the country's unique geographic location, which results infrequent volcanic and tectonic activity. This has resulted in the varied soil types and irregular soil thicknesses
found throughout the country. As a result, local Geotechnical Engineers face a difficult task, as they require
accurate soil and rock information in order to plan and design geotechnical construction projects in the country.
Only a few borehole logs are conducted due to the project's limited budget and timeline, thus, geological andgeotechnical data can be collected only at the project's location, leaving unknown subsurface data in other locations.
The purpose of this study is to use Machine Learning Regression Models to determine the angle of internal friction
between soil layers in Makati City, Philippines. Linear Regression Model, Tree Regression Model, Boosted Trees
Model, and Artificial Neural Network are the competing Machine Learning Regression Models. Coefficient of
Determination (R2) and Root Mean Square Error (RMSE) values were calculated to compare and validate theregression models. Among the models, the Linear Regression Machine Learning Model had the highest Coefficientof Determination (R2) and the lowest Root Mean Square Error (RMSE), and was used to deploy in the research
locale. Another output was a map of Makati City represented by its internal friction angle.
Keywords: Geotechnology, Geospatial intelligence, Machine learning, Friction Angle, Philippines

since it represents soil shear resistance [27]. Soil
angle of internal friction is a measure of the soil's
resistance to shear forces and corresponds to the angle
between the normal stresses [28] and the resultant
force within the soil that is produced shortly before
collapse owing to shear stresses [29-30].
This study aims to determine the angle of internal
friction between soil layers in Makati City,
Philippines using Machine Learning Regression
Models. The competing Machine Learning
Regression Models are the following: Linear
Regression Model, Quadratic Regression Model,
Tree Regression Model, Boosted Trees Model, andArtificial Neural Network. In addition to describing
the types of soil and evaluating its strength based on
the angle of internal friction, a 3-D soil profile ofMakati City, Philippines will be previewed
representing the degree of angle of internal frictionthat may assist designers, engineers, and decisionmakers in determining the site's appropriateness andthe most suitable form of foundations.

INTRODUCTION
Foundations are frequently buried beneath thesurface layers of soil and their loads affect theunderlying soil strata, this comprehension can beattained through soil investigation tests. Engineers
must fully understand the soil-foundation interactionin order to design and select the most suitablefoundations [1]. The added seismic activity in thePhilippines is caused by the country's uniquegeographic location, which results in frequentvolcanic and tectonic activity. This has resulted in thevaried soil types and irregular soil thicknesses foundthroughout the country. As a result, local
Geotechnical Engineers face a difficult task, as theyrequire accurate soil and rock information in order toplan and design geotechnical construction projects inthe country [2-19]. In general, these examinations arecostly and time-consuming. However, engineers are
not always able to perform these experiments, so they
depend on the findings of earlier studies conducted bytheir peers in nearby locations to estimate
approximate values for certain soil qualities [20].
With the advancement of science and technology, it
is now simpler to interpolate a collection of data to
get values for non-spatial data regions, a techniquethat has been utilized by several researchers acrossthe globe [21-26].
However, there are few researches on the angle ofinternal friction, which is a crucial shear strength
metric for evaluating the stability of soil and slopes

METHODOLOGY
The process of the study is shown in Fig. 1. andexplained in the later sections.
Research Locale
Makati City is a premier, highly urbanized cityin the National Capital Region of the Philippines,
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SEE-Mie, Japan, Nov.10-12, 2022

Start







Train Regression Models
Tree Regression Model
Linear Model
Quadratic Model
Ensemble Model
Neural Network Model

Data to Train (from Literature) Plasticity Index
 Angle of Internal Friction

Input Parameters:
Liquid Limit
Plastic Limit
N-ValueTrain Regression Models
Tree Regression Model
Linear Model
Quadratic Model
Ensemble Model
Neural Network Model

Data to Train (from Literature)
N-Value
Angle of Internal Friction

Compute for Plasticity
Index
Compare R2 and RMSE

Compare R2 and RMSE

Hyperparameter Tuning

PI>12
Clay-Like

Winning Model

What is the
Plasticity
Index?

PI 12
Sand-Like

Hyperparameter Tuning
Winning Model

OutputAngle of Internal Friction

OutputAngle of Internal Friction

End

End

Fig. 1 Methodology of the Studyshown in Fig. 2. In terms of revenue from domestic
sources and per capita income, Makati City remains
the richest local government unit (LGU) in thePhilippines. Makati is the financial hub of thePhilippines, with the biggest concentration of global
and domestic firms. Numerous banks, enterprises,
department shops, and foreign embassies are locatedin Makati. Consequently, structures are being
constructed to house these advancements, and as
noted earlier, soil explorations are required for theseprojects.

Data
The collection of soil borehole logs are fromwithin and around Makati City. The soil profile wasdescribed using a density of one drill log per square
kilometer. The distribution was visually evaluated,and data-deficient regions were identified. Erroneous
logs from boreholes were also removed and discarded[22]. The locations of thirteen (13) boreholes were
mapped based on their official investigation reports,
as shown in Fig. 3. The 13 boreholes have 247 data
layers.
The independent and dependent variables are
displayed in Table 1. The soil data output is a numericparameter, which is ideally suited for a Machine
Learning Model.
Table 1 Dependent and Independent Variables of the
Study
Independent Variable(s) Dependent Variable(s)1. Longitude
1. N-Value
2. Latitude
2. Liquid Limit
3. Elevation
3. Plastic Limit
Angle of Internal Friction and its Relationships
Angle of Internal Friction, ∅The Angle of Internal Friction (Ø) is calculatedusing Mohr's Circle and a graph of the shear stressand normal effective stresses at which shear failure
occurred. The combination of friction angles andslope is based on the connection established by the
Mohr-Coulomb failure criteria, which implies that

Fig. 2 Location of Makati City in Metro Manila

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SEE-Mie, Japan, Nov.10-12, 2022

soil friction angle is a component of shear strength,
shown in Eq. 1:

Various researches on the correlation of Angle ofInternal Friction (Ø) and Plasticity Index values weregathered [31, 38-49]. At each plasticity index,
different values of Ø ' result from the difference inclay size fraction of soils and from the difference in
effective normal stress at which Ø' was measured.
These relationships also underwent machinelearning modeling, with Linear Regression Model,
Tree Regression Model, Boosted Trees Model, andArtificial Neural Network as competing models,Table 2 and Table 3 show the independent anddependent variables for the modeling.
Sand-like or Clay Like
Recent research, such as those by Boulanger andIdriss [50] and Bray and Sancio [51], have provided
valuable information and recommendations for the
management of soils:

Fig. 3 Collected Boreholes for Makati City
𝜏 = 𝑐 + 𝜎 ′ 𝑡𝑎𝑛∅

(1)

Where: 𝜏 is shear strength, c is cohesion, 𝜎 ′ iseffective overburden pressure, and ∅ is angle ofinternal friction.
The Angle of Internal Friction (Ø) can be
determined in the laboratory by the Direct Shear Testor the Triaxial Stress Test. However, due to lack ofresources, the Angle of Internal Friction (Ø) is
sometimes correlated with (1) N-Values forcohesionless soils or sand-like and (2) Plasticity
Index, derived from Liquid Limit and Plastic Limit,
for soils classified as sands but with clay-like
properties.
The most trustworthy approach for determining
shear strength parameters of subterranean soils is soil
sampling coupled with laboratory testing. Due tolimited funds, short deadlines, or a lack of concern,
initiatives may not always obtain adequate laboratory
recommendations. In many instances, however, soil
type, water table depth, and standard penetration test
(SPT) blow counts can be used to assess subsurface
soil conditions. In the absence of laboratory data, it isusual practice to estimate the shear parameters basedon the SPT findings.
Clay also has his own frictional properties.
Among the pure clay minerals, sodium
montmorillonite (composed of filmy particles) has
the lowest Ø' value, while attapulgite (composed ofinterlocking fibers) has the greatest value. The rangeof typical Ø' values for soft clay, stiff clay, and shalecomponents is 25˚ to 35˚, 20˚ to 35˚, and 15˚ to 35˚,
respectively [31].

PI < 12: This group of soils should be
deemed "sand-like" and examined using
either the simplified technique for sands andnon-plastic silts or site-specific studies that
include laboratory testing on high-quality
soil samples.

PI > 12: The behavior of soils categorizedunder this category is thought to be "claylike." Importantly, certain clay soils canexperience considerable strength loss due toseismic shaking; hence, designating thesesoils as non-liquefiable does not mean thatthey are intrinsically stable.

Thus, for PI < 12, Table 2 was used for thecorrelation, while PI > 12, Table 3 was used.
Machine Learning Modelling
Machine Learning Competition
Machine learning automates models for analyzing
soil data by learning from the data, detecting its
patterns, and making judgments with minimum
human input. This study focused on generating thesoil profile of Makati City, Philippines using Machine
Learning Models such as the Linear Regression
Model [52], Quadratic Regression Model [53], Tree
Regression Model [54], Boosted Trees Model [55]and Artificial Neural Network [56-57]

Correlations

Table 2 Dependent and Independent Variables for
Sand-Like Soils RelationshipIndependent Variable(s) Dependent Variable(s)Various researches on the correlation of Angle ofInternal Friction (Ø) and N-values were gathered [3237].

1. N-Value

131

1.

Angle ofInternal Friction

SEE-Mie, Japan, Nov.10-12, 2022

The Matlab Regression Learner program
employed the parameters listed in Tables 1, 2 and 3.
As a foundation for training and verifying regression
models, the program was employed. After training thecompeting models, compare their validation errors
side-by-side to choose the optimal model. The
following is a typical method for training regression
models within the program Regression Learner:

Table 3 Dependent and Independent Variables for
Clay-Like Soils RelationshipIndependent Variable(s) Dependent Variable(s)1.

Plasticity Index

1.

Angle ofInternal Friction

Data Split Ratioa) Selection and Validation of Datab) ML Regression Model Tuning(Hyperparameter Tuning)c) ML Regression Model Trainingd) Assess the ML Regression Model based on the
Accuracy Rates (Competition)f) Implement the chosen ML Regression Model

There are studies that give extensive analysis of
the machine learning training and testing process[58]. Obtaining meaningful data has gotten
increasingly difficult due to the explosion of data. To
make sense of data, the discipline of data mining has
emerged. Data mining is a collection of techniques
used to derive meaning from data [59]. To identify theactivities of a machine learning model, observations
not used during training must be employed.
Otherwise, the model's evaluation will be distorted.
(1) Training Dataset, (2) Validation Dataset, and (3)Test Dataset are the datasets. The split ratio for thedataset is 70% Training Data, 15% Validation Data,and 15% Testing Data.

To calculate the soil stratification of an unknown
location, the software employed the model with thebest rate of accuracy. In addition, it is fine-tuned toevaluate whether the accuracy rates may be enhanced
further, as described in the next section.
Hyperparameter Tuning
The hyperparameters of the chosen model were
adjusted to determine whether the accuracy rates
might be enhanced. The challenge of hyperparametertuning is the selection of the optimal set of
hyperparameters for a machine learning system [62].
The number of neighbors (k) for the k-NN model isan example of a hyperparameter.

Coefficient of Determination (R2) and Root Mean
Square Error (RMSE)
Each model's Coefficient of Determination (R2)were collected. The model with the highest
Coefficient of Determination (R2) among the five (5)competing Machine Learning Models was deployed;
this is also known as a Competition. In thisinvestigation, the approach of Cheng et al. [60] wasutilized. Coefficient of Determination is a tool which
determines and assesses the ability of a statisticalmodel to explain and predict future outcomes., asillustrated in Eq. 2:∑[(𝑋 − 𝑋𝑚 ) ∗ (𝑌 − 𝑌𝑚 )]𝑅2 = {}√∑(𝑋 − 𝑋𝑚 )2 ∗ ∑(𝑌 − 𝑌𝑚 )2

Deployment
At the Barangay/Zone Level, the Machine
Learning model with the best Accuracy Rate was
deployed. To be consistent with the density of 1
borehole per square kilometer, these barangays were
subdivided into zones, as seen in Fig. 4.

2(2)
Geographic Information System was used todetermine the latitude and longitude coordinates ofeach Barangay/Zones's centroid.

Where: X – Data points in Data set X, Y – Data
points in Data set Y, Xm – Mean of Data set X and Ym– Mean of Data set Y

Predicted
Soil
ProfileandInformation System (GIS) Maps

While the Root Mean Square Error (RMSE) is thesquare root of the mean of all errors squared [61],equation is shown in Eq. 3:

𝑹𝑴𝑺𝑬 = √∑𝑵
̂(𝒊)||𝟐
𝒊=𝟏 ||𝒚(𝒊) − 𝒚𝑵Geographic

Once the required data has been imported into a
GIS platform, it may be integrated with other data
layers to generate many unique maps. The soil profileis also delineated isometrically.

(3)

RESULTS AND DISCUSSIONS

Where: N is the number of data points, y(i) is thei-th measurement, and y ̂(i) is its corresponding
prediction.

Accuracy Rates and RMSE of ML Models
Accuracy is the ratio of correct predictions to the132SEE-Mie, Japan, Nov.10-12, 2022

total number of input samples [61], and it isdetermined using Eq. 2. In contrast, the Root Mean
Square Error (RMSE) is the square root of the squaredmean of all errors [62], shown in Eq. 3. Multiple
Machine Learning Models were employed to train thedata, and these models provided various accuracy
rates, as shown in Tables 4 to 8. The model with thegreatest accuracy rate was selected for deployment.
Initial testing utilized the simplest types ofhyperparameters. If the machine learning model had
the greatest rate of accuracy, it was adjusted further.

Plastic Limit
ModelsTree Regression Model
Linear Model
Quadratic Model
Boosted Tree
Neural Network

R2
0.69
0.66
0.65
0.41
0.44

RMSE
0.112420.11668
0.116350.120420.11694

Table 7 Performance of ML Models in Predicting
Angle of Internal Friction for Sand-Like Soils
ModelsR2
RMSE
Tree Regression Model
0.62
3.3497
Linear Model
0.77
3.1337
Quadratic Model
0.76
3.139
Boosted Tree
0.58
3.5096
Neural Network
0.65
3.1828
Table 8 Performance of ML Models in Predicting
Angle of Internal Friction for Clay-Like Soils
ModelsR2
RMSE
Tree Regression Model
0.12
6.8151
Linear Model
0.18
5.8424
Quadratic Model
0.15
5.9295
Boosted Tree
0.01
6.4608Neural Network
0.06
6.2284

Fig. 4 Generated Map of Makati City Zones

For Tables 7 and 8, Linear Regression Model wasused, among all the ML models, it had provided amore stable model compared to the other ML Models.
A linear relationship was also provided by various
studies [27-49] to determine the Angle of Internal
Friction whether it is sand-like or clay-like. The
Machine Learning Models Predicting the Angle ofInternal Friction of Sand-Like Soils and Clay-LikeSoils is shown in Fig. 5 and 6, respectively.

Shown in Tables 4, 5 and 6 are the performances ofthe ML Models in Predicting N-Values, Liquid Limit
and Plastic Limit, the Tree Regression Model wasused for the deployment. The Longitude, Latitude andElevation were the independent variables.
Table 4 Performance of ML Models in Predicting NValue
ModelsR2
RMSE
Tree Regression Model
0.88
7.3277
Linear Model
0.09
20.238Quadratic Model
0.25
18.405
Boosted Tree
0.5
15.088Neural Network
0.46
15.729
Table 5 Performance of ML Models in Predicting
Liquid Limit
ModelsR2
RMSE
Tree Regression Model
0.74
0.10728
Linear Model
0.72
0.10743
Quadratic Model
0.71
0.10771
Boosted Tree
0.44
0.11706
Neural Network
0.23
0.78019

Fig. 5 Machine Learning Models Predicting theAngle of Internal Friction of Sand-Like Soils

These variables do not require normalization and/or
scaling. Tree regression model is very suitable since
the splitting has placed N-values, Liquid Limit andPlastic Limit in their proper subsets.
Table 6 Performance of ML Models in Predicting
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SEE-Mie, Japan, Nov.10-12, 2022

Fig. 8 Liquid Limit Profile Generated for Makati City

Fig. 6 Machine Learning Models Predicting theAngle of Internal Friction of Clay-Like Soils
Generated Angle of Internal Friction Soil Profile
and Geographic Information System (GIS) Map
The western part of Makati City is dominated byhard strata, as shown in Fig. 7, N-values 40-50 isprevalent in these areas. The layers around these areas
are reworked deposits of primary tuff and pyroclasticflow deposits, thus providing a higher value of N. The
Eastern area of Makati are dominated by marine
epiclastic sediments, which can be loose, thus
providing a lower value of N. Almost 59% of the soil
layers have high N-values.
For the Atterberg Limit properties of Makati City,
shown in Figs. 8 and 9, the surficial layers are
dominated by low values of Liquid Limit and Plastic
Limit, this may be attributed by the dominating soil
types in the area. Non-plastic soils are prevalent.
Almost 77% of the layers are non-plastic, while theremaining 23% are plastic soils.

Fig. 9 Plastic Limit Profile Generated for Makati City

Fig. 10 Angle of Internal Friction Profile Generated
for Makati City

Fig. 7 N-Value Profile Generated for Makati City
As validation, shown in Fig. 10, the southeast sideof Makati City experiences a greater shear wave
velocity than the northwest side. This has the same
configuration as the soil profile generated by themodel and depicted in Fig. 11. In these regions,resistance is significantly more formidable. The
PHIVOLCS Shear Wave Velocity Map was utilized
to validate the subsurface soil profile generated by the
Model.

Fig. 11 Shear Wave Velocity Map showing
Makati City [63]134SEE-Mie, Japan, Nov.10-12, 2022

Sciences, 10(15), 6440-6447.
[4] Dungca, J. R., & Galupino, J. G. (2016).
Modelling of permeability characteristics of soilfly ash-bentonite cut-off wall using response
surface method. International Journal of
GEOMATE, 10(4), 2018-2024.
[5] Dungca, J., Galupino, J., Sy, C., & Chiu, A. S. F.
(2018). Linear optimization of soil mixes in thedesign of vertical cut-off walls. International
Journal of GEOMATE, 14(44), 159-165.
[6] Dungca, J. R., Galupino, J. G., Alday, J. C.,
Barretto, M. A. F., Bauzon, M. K. G., &Tolentino, A. N. (2018). Hydraulic conductivity
characteristics of road base materials blended
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CONCLUSION
For the Angle of Internal Friction of Makati City,
shown in Fig. 10, almost 50% of the soil layers havea high Angle of Internal Friction. The higher value ofthe internal friction angle shows the higher of thematerial can withstand the lateral force. The 3-D
profile of Makati City, Philippines for the Angle ofInternal Friction has previewed representing thedegree of angle of internal friction that may assist
designers, engineers, and decision-makers indetermining the site's appropriateness and the mostsuitable form of foundations.
The study aims to determine the angle of internal
friction between soil layers in Makati City,
Philippines using Machine Learning Regression
Models. The competing Machine Learning
Regression Models are the following: Linear
Regression Model, Quadratic Regression Model,
Tree Regression Model, Boosted Trees Model, andArtificial Neural Network.
For the ML Models in Predicting N-Values,
Liquid Limit and Plastic Limit, the Tree Regression
Model was used for the deployment. Tree regression
model is very suitable since the splitting has placed
N-values, Liquid Limit and Plastic Limit in theirproper subsets.
For the ML Models in Predicting Angle ofInternal Friction for Sand-Like and Clay-like Soils,
Linear Regression Model had provided a more stablemodel compared to the other ML Models. A linear
relationship was also provided by previous studies.
Once the all the data has been imported into a
GIS platform, 3-D profile maps were created whichhas previewed representing the degree of angle ofinternal friction that may assist designers, engineers,and decision-makers in determining the site's
appropriateness and the most suitable form offoundations
ACKNOWLEDGEMENT
The authors would like to express their sincerest
thankfulness to Department of Science andTechnology (DOST) for funding their project
Geotechnical Mapping of Metro Manila Subsoil(GEMMMS).
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68th Int. Conf. on Science, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106032 C3051

A STUDY ON VIBRATION AND SOUND SIGNALS OF AN ELECTRIC
VEHICLESuphattharachai Chomphan
Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACT
Nowadays, electric vehicles have been continuously developed and become increasingly popular compared toconventional combustion engine vehicles. Their polluting emissions are less than those of petroleum-powered
vehicles. Moreover, they are expected to produce noticeably less noise and vibration, however, the issue has notbeen concretely conducted. Therefore, an analysis of vibration and sound signals of an electric vehicle driving at
six different engine speeds at three distinct positions within the passenger room to evaluate the quality of service
comparatively has been performed in this paper. The FOMM ONE Y2018 model with a gross battery capacity of
11.84 kWh and a system power of 14 Hp has been selected in this study due to its popularity. The vibration andsound measuring positions are at the right front or driver's seat, the left front seat, and the rear seat. The
measurement is performed at different speeds, i.e., 0, 10, 20, 30, 40, and 50 km/h, using a set of accelerometers
and a microphone, respectively. The experimental data are statistically measured, and subsequently, the dominantfrequency extraction is performed. The experimental results have been finally concluded. From the experiment,
when the electric car starts to work by increasing the speed, its vibration and sound magnitudes measured at three
distinct positions increase accordingly. When comparing the magnitude of vibration and sound occurring at themeasuring locations, it was found that the left seat was the highest and the rear seat was the lowest, obviously at
the standstill.
Keywords: Electric vehicle, Vibration signal analysis, Sound signal analysis, Fast Fourier transform, Dominantfrequency extraction

INTRODUCTION

number of public charging stations caused difficult
decisions for the consumers.
The 3rd trend of popularity from the year 2017
until the present is caused by the problem of
cumulative air pollution. The combustion of internal
combustion engine vehicles has various polluting
effects. Greenhouse gases, dust, and exhaust gases
cause global warming and more severe disasters. The
agreement in the Paris treaty (COP-21) to reducegreenhouse gas emissions by 20-25% by 2030, theadvances in materials science technology
development, and the better battery efficiency
provoked the prevalence of the new electric vehicle
popularity. Electric vehicles are expected to be soldat prices comparable to those of conventional cars inthe same performance [1].
As a result, electric vehicle technology has been
tremendously developed both in terms of related
technology and usage patterns to meet user needs. In
2021, Rolls-Royce YASA and Electro-flight jointly
developed the world's fastest electric aircraft at 480
km/h [2]. Besides, Spark Racing Technology
company of China launched a Formula-E electricmotor racing project with an increasing number ofparticipants [3].
Recently, United Airlines has invested in United
Airlines Ventures with Breakthrough Energy
Ventures and Mesa Airlines in Heart Aerospace

On the path of industrial reform in developing
countries to drive macroeconomics causing enormous
consumption of petroleum products. The incremental
use of petroleum poses a serious threat to theenvironment with the problem of global warming,
The disruptive innovation of electric vehicles (EV)has received a huge pinnacle of attention in thepresent global situation for several decades, A trendof its popularity has occurred intermittently, however
it still can not be used as a replacement for internal
combustion engine vehicles due to price factors,
battery quality and performance (mileage per charge),
the limited number of available electric vehicle
models, as well as the value for resale. The popularityof engine vehicles can be divided into 3 periods asfollows.
First of all, the beginning popularity occurred in
1993, the state of California of the United States
announced the zero-emission vehicle standards.
Owing to the vehicle performance limitations,however, the developed vehicle remains unpopular.
The second wave of popularity resurfaced in2010 with the introduction of Tesla's Roadster,
Mitsubishi's i-MiEV, and Nissan's Leaf models.
Limitations of 200 km on a single charge and the138SEE - USQ, Pattaya, Thailand, Nov.10-12, 2021

company to develop a small electric-powered aircraft
capable of carrying 19 passengers with several
preorders in 2026 [4].
During the transition period, many automotive
manufacturers focused on producing hybrid electricvehicles (HEVs) while gaining the advantages of bothpure electric vehicles and traditional internal
combustion engines. However, the noise andvibration produced during the HEV operation reducethe comfort of the passengers. They also cause stress,
and fatigue, and adversely affect the drivers. The
analysis of the noise and vibration of an HEV has
been studied in 2022 [5].
In particular, competition in the automotive
market is required to have a vehicle's acoustic andvibration dampening properties for optimal
performance [6]. The analysis of vibration and soundsignals has been previously performed for decades.
The external and internal factors which affect theworking conditions of the vehicles have been
continuously studied.
Focusing on the external factors, several
research have been conducted. In 2018, theenvironmental effects of the road surface types andconditions on the traffic flow management mode in
the case of directive management have been
investigated by Novikov et al., [7]. It has been foundthat there is a correlation between the friction
coefficient and the capacity of the managed area
resulting in the change of the traffic lights cycle,
which is also corroborated by the conducted field
experiment on a signalized intersection. Besides, anexternal factor affecting vehicle durability wasstudied by Hu and Zhong in 2019. A conventional
finite element model for linear and nonlinear analysis
for multibody full-vehicle-durability simulation wasapplied. Six different kinds of test road surfaces wereconducted in the simulation, and the study concluded
that the explicit–implicit co-simulation techniques
are efficient and accurate enough for engineering
purposes [8].
In addition, the interaction between the type andtechnical condition of road surfaces, dynamic vehicleloads, and the level of vibration propagated to theenvironment was studied by Czech in 2016 [9]. The
study summarized that the type of road surface, thetechnical condition, and the varied dynamic vehicleloads explicitly affected the level of vibration
propagated to the environment.
In 2019, the discomfort caused by vibration forthree models of micro commercial vehicles runningin four types of road conditions was studied by Huang
and Li, since the main environmental stress ofvibration affected the vehicles implicitly [10].
Furthermore, external factor analysis was conductedby Litak and his colleagues in 2008. They
investigated the chaotic vibration which was theeffect of critical Melnikov amplitude of the roadsurface profile to a quarter car model [11]. Moreover,Blekhman and Kremer also conducted a study of theeffect of road unevenness on the dynamics of theaveraged longitudinal motion of a vehicle in 2017[12].
On the other hand, the internal factor analysis
has been also studied. The studies of detection anddiagnosis of the faults in rotating machinery havebeen tremendously pursued [13]-[15]. Investigating
the associated signal processing for machinediagnosis in 2013, an amount of research on signal
processing adaptation has been performed for fault
diagnosis [14]. In 2012-2013, the discrete wavelet
transform (DWT) was used with the vibration signal
for the engine fault diagnosis of the diesel engine andthe gearbox [14], [15]. The power spectrum analysis
with high order, cepstrum analysis, and neuralnetwork approach was applied with fault diagnosis
and an indication of some of the specific induction
motors in 2013 [16]. Furthermore, the Fouriertransform has been substantially utilized, for instance,
the Fourier transform coefficients were adopted in thefeatures of mel-cepstral HMM-based speechmodeling for speech synthesis in 2009 [17].
Consequently, it was adapted to the correlation
analysis of vibration and sound signals for a gasolineengine car in 2020 [18]. Besides, in 2016 the powerof signal analysis with less time consumption and a
low computational cost was conducted in acomparative study of LPG-modified engines andregular oil-usage engines [19], and also in a fault
diagnosis of rolling element bearings [20]. Moreover,the issue of gasoline substitution with LPG boilingsystem installation caused some significant variationin vibration and sound signals of the modified engines[21]-[24]. In addition, some analysis techniques of thevibration and sound signals were proposed todifferentiate between the LPG-modified engine andthe conventional gasoline engine, accordingly, somesignificant attributes were used to indicate theirregularities of the corresponding engines [25], [26].
In 2019, an internal factor study of vibration andsound signal analysis for a motorcycle and a gasoline
engine with LPG installation and some specified fault
simulations was investigated by Chomphan et al.,LPG installation and the specified faults concretely
affected the engine efficiency degradations [27], [28].
This paper applies engineering knowledge tostudy and analyze the vibration and sound of an EV
car from one worldwide manufacturer of the FOMM
ONE Y2018 model as depicted in Fig. 1. The analysis
applies driving at six different engine speeds at threedifferent positions within the passenger room toevaluate the quality of service comparatively. The
measuring positions of vibration and sound are at theright front or driver's seat, the left front seat, and therear seat, respectively.

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Experimental
DesignData preparation

Experimental
Setup for Signal
analysis of an EV

Fig. 1 EV car of FOMM ONE Y2018 model.
A couple of principle purposes are to compare
the vibration and sound signal attributes with threedifferent measuring positions and different engine
speeds. The Fast Fourier Transform (FFT) is adopted
to extract the signal spectrum and the corresponding
features in the analysis procedure [5], [18], [19], [28].

Measurement ofvibration signal at
3 positions

Measurement ofsound signal at
3 positions

Vibration signal
preparation andcollection

Sound signal
preparation andcollection

Vibration signal
databaseSound signal
database

Vibration signal
feature extraction

Sound signal
feature extraction

MATERIAL AND METHODSIn this section, electric vehicles have been
generally explained in principle. The experimental
procedure modified from the study in [5] has been
illustrated step by step. Finally, the experimental
setups have been therefore presented.

Comparative
analysis
Signal processing

Electric Vehicles

Conclusion

This type of car uses only electric power to drive
the whole body. The way a pure electric vehicle
works is not as elaborate and complex as a petrol car.
There are only three main driving components
contributing to the efficiency of driving. These threecomponents include a battery, an inverter, and anelectric motor.

Fig. 2 Experimental Procedure.
Data Preparation
During the data preparation, the experimental
setup is conducted to retrieve the vibration and soundsignals simultaneously from the experimental carwith six different numbers of engine speeds, i.e., 0,
10, 20, 30, 40, and 50 km/h. Thereafter, themeasurement, preparation and collection, anddatabase implementation are performed respectively.

Experimental Procedure
The experimental procedure consists of a coupleof consequential stages of data preparation and signal
processing sub-procedures as depicted in Fig. 2. A
brief explanation of the procedure is presented asfollows.

Experimental Setup
The vibration and sound signal retrieving setups
have been arranged during the experimental setup
process. Three sets of high-frequency vibration
sensors and a condenser microphone are allocated at
different positions within the passenger room. The
corresponding signals are then transferred into theprocessing computer through a group of NI
interfacing cards.
The vibration sensors and the microphone areallocated at three positions including at the right front
or driver's seat, the left front seat, and the rear seat.
Three vibration sensor wires and the microphone wire
are connected to the NI cards which are attached to
the NI rack. The rack is also connected to thecomputer where the signals are retrieved into theLabview program.

Experimental DesignFirst of all, the experimental design process has
been initiated. All experimental equipment includes
an EV car of the FOMM ONE Y2018 model with agross battery capacity of 11.84 kWh and the system
power of 14 Hp, a number of vibration sensors andtheir peripheral devices, a condenser pre-polarized
CCP free-field QC microphone with G.R.A.S. 40PP
and its complementary parts, an NI 9234 module of
National Instruments corporation with 4-channel,±5V, 24-bit software-selectable IEPE, AC/DC analog
input specifications, NI cDAQ-9171 USB chassis forinterfacing with a computer, and a computational
program for signal processing.

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SEE - USQ, Pattaya, Thailand, Nov.10-12, 2021

Measurement of vibration (sound) signal at 3
positionsbut not least, the observation of the corresponding
features of vibration and sound signals at different
speeds has been conducted to achieve the second
objective of speed comparison.

In the measuring process of signals of the EVcar, three different positions are defined. All of thesensors apply the sampling frequency of 50,000 Hz.
The signals are measured with 10 samples and 5second periods of time at six different engine speedsof 0, 10, 20, 30, 40, and 50 km/h, respectively.

Conclusion
The interpretation of the output comparative
analysis is performed. Finally, the discussion for all
aspects has been completed.

Vibration (sound) signal preparation and collection
EXPERIMENTAL RESULTS
The preliminary process of signal segmentationis performed after the signals arrive at the input ports
through the Labview program. The collection of
signals from all different sensor positions with alldifferent engine speeds is categorized.

In the signal feature extraction process, the FFTtechnique has been adopted to extract the significant
features as described in the previous studies [5]. The
extracted features are consequently utilized in the
final process of the comparative analysis using thestatistical averaging technique. The following bar
charts are constructed and presented in this section.

Vibration (sound) signal database
After signal categorization, a group of databasesof the categorized signal is constructed. Three sets of
categorization include the signals from the right front
seat, the signals from the left front seat, and thesignals from the rear seat. In each set, the signal
portions are divided into six groups corresponding toeach engine speed as mentioned in the previous
section.

0.30
0.25

Magnitude(g)0.20

Signal Processing

seat1
seat2
seat3

0.15
0.10
0.05
0.00

0
10
20
30
40
50
seat1 0.06 0.12 0.09 0.16 0.03 0.02

At the signal processing, the feature extraction
and comparative analysis are performed respectively.

seat2 0.05 0.08 0.11 0.08 0.02 0.07
seat3 0.05 0.11 0.16 0.26 0.23 0.23
Frequency(Hz)Vibration (sound) signal feature extraction
The signal analysis technique of Fast Fouriertransform has been applied to all of the portions of thesignals for all groups within the database to obtain
their corresponding frequency spectrum. From theoutput frequency spectrum, the most dominant peak
appearing in the frequency domain is extracted. The
frequency and magnitude at the peak are analyzed.
Monitoring the frequency spectrum brings aboutsome frequencies at the dominant peak points andtheir corresponding amplitudes. These highest peaks
are assumed to represent the important components ofthe signal inherited from the movement of the EV.
These extracted features are consequently utilized in
the final process of the comparative analysis.

Magnitude

Fig. 3 The averaged magnitude of the emerging peakof the frequency spectrum of the vibration
signal measured at three distinct positions.
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00

seat1
seat2
seat3

0
10
20
30
40
50
seat1 0.70 0.04 0.06 0.07 0.07 0.08
seat2 0.56 0.06 0.05 0.06 0.06 0.07

Comparative analysis

seat3 0.38 0.04 0.05 0.07 0.06 0.07
Frequency(Hz)The extracted features are averaged among all
corresponding samples. Several comparative
analyses are conducted with different aspects. As forthe first objective of position comparison, thecorresponding features of vibration and sound signals
at different positions of sensors are compared. Last

Fig. 4 The averaged magnitude of the emerging peakof the frequency spectrum of the soundsignal measured at three distinct positions.
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SEE - USQ, Pattaya, Thailand, Nov.10-12, 2021

As for vibration comparative analysis, thecomparisons of the averaged magnitude of emerging
peak of the frequency spectrum of the vibration signal
measured at three different positions in gravitational
acceleration unit (g) with different engine speeds arepresented in Fig. 3.
As for sound comparative analysis, the averaged
magnitude of the emerging peak of the frequency
spectrum of the sound signal measured at threedifferent positions with different engine speeds has
been presented in Fig. 4.
From the experiment results, it can be observed
from Fig. 3 that when the engine speed of the EV car
is raised until reaching 30 km/h, the averaged
magnitude of the emerging peak of the frequency
spectrum of the vibration signal trends to increase
accordingly for all three different positions. After
that, the average magnitude gradually decreases.
Moreover, comparing among three different
positions, the averaged magnitudes of emerging
peaks at the left-front seat (seat 1) are higher thanthose of the other positions for the first two speeds (0and 10 km/h), meanwhile, the averaged magnitudesof emerging peaks at the rear seat (seat 3) are mostly
highest than those of the other positions for the otherfour speeds (20 to 50 km/h).
On the other hand, it can be seen from Fig. 4 thatwhen the engine speed of the EV car is raised from 10km/h to 50 km/h, the averaged magnitude of theemerging peak of the frequency spectrum of thesound signal trends to increase accordingly for threedifferent positions. The averaged magnitudes of
emerging peaks at the standstill (speed of 0 km/h) areat the highest levels compared with those of otherspeeds for three different positions. Moreover,comparing among three different positions, theaveraged magnitudes of emerging peaks at the leftfront are mostly higher than those of the otherpositions, meanwhile, the averaged magnitudes of
emerging peaks at the rear seat are mostly lowest thanthose of the other positions.

averaged magnitude of the emerging peak of thefrequency spectrum of the sound signal trends toincrease accordingly for three different positions. The
averaged magnitudes of emerging peaks at thestandstill are at the highest levels compared withthose of other speeds for three different positions. For
further interest, the other popular types of electricvehicles and improved signal processing techniques
will be studied.
ACKNOWLEDGMENTS
The related facilities were arranged by themembers of the Mechanical System and Signal
Processing research group. Besides, this research was
supported by Kasetsart University, Faculty ofEngineering at Sriracha.
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CONCLUSIONSAn analysis of vibration and sound signals of anelectric vehicle at three different positions within thepassenger room has been proposed. The locations ofvibration sensors and microphones are at the left-front
seat, the right-front seat, and the rear seat. The
important frequency spectral features have been
extracted for six different engine speeds, i.e., 0, 10,
20, 30, 40, and 50 km/h. As for the vibration analysis
with positioning focus, the averaged magnitudes of
emerging peaks at the left-front seat are higher thanthose of the other positions for the first two speeds (0and 10 km/h), meanwhile, the averaged magnitudesof emerging peaks at the rear seat are mostly highest
than those of the other positions for the other four
speeds (20 to 50 km/h). As for the sound analysis, the142SEE - USQ, Pattaya, Thailand, Nov.10-12, 2021

of a Passenger Car on Arbitrary Road Surfaces,
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[9] Czech K. R., The Impact of the Type andTechnical Condition of Road Surface on the
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[11] Litak G., Borowiec M., Friswell M. I., Szabelski
K., Chaotic Vibration of a Quarter-Car Model
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1373-1383.
[12] Blekhman I., Kremer E., Vibrational Resistanceto Vehicle Motion Due to Road Unevenness,
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[13] Yujun L., Peter W. T., Xin Y., Jianguo Y., EMDBased Fault Diagnosis for Abnormal Clearance
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[15] Binqiang C., Zhousuo Z., Chuang S., Bing L.,
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[19] Chomphan S., Chaimanatsakun A., Sakornsin R.,
Khumneungratavongsa S., Rattanarat K., A
Comparative Study of LPG-modified Engine andNormal Oil-usage Engine. in Proc. Int. Conf. on
Engineering and Applied Sciences, 2016, pp.
219-225.
[20] Akhand R., Upadhyay S. H., A Review on Signal
Processing Techniques Utilized in the Fault
Diagnosis of Rolling Element Bearings,
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pp. 289-306.
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S.M., Vibration Analysis of a Diesel Engine
Using Biodiesel and Petro Diesel Fuel Blends,
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CONSTANT VOLUME SHEAR TESTS ON COMPACTED SILTY SOIL
UNDER CONSTANT WATER CONTENT CONDITION
Tufail Ahmad1, Riko Kato1 and Jiro Kuwano1
1

Department of Civil & Environmental Engineering, Saitama University, Japan
ABSTRACT

Majority of the earth structures such as embankments, roadways, foundations, slopes and retaining walls arecommonly built above the ground water table whenever possible, which implies that the soil used in constructionof such structures is commonly unsaturated in nature. The behavior of unsaturated soil is less predictable ascompared to saturated soil. Usually, triaxial tests are carried out on unsaturated soils at various net axial stress andmatric suction under constant confining pressure. There is limited research regarding the constant volume, i.e.,
constant void ratio triaxial test on unsaturated soil. In this study a series of triaxial compression tests were
performed under constant water content conditions using a double cell triaxial test apparatus. The samples wereprepared with 80% degree of compaction and at optimum water content of 20%. All the soil specimens wereconsolidated isotropically under three different confining pressures of 100kPa, 300kPa and 500kPa before being
sheared with constant volume. The soil specimen's volume was controlled by manually altering the cell pressureduring the shearing phase (depending on the volume change measurement). A pre-shear infiltration test was also
carried out to understand the influence of matric suction in unsaturated soil when sheared with constant volume.
The results show that the normally consolidated specimen exhibit anomalous behavior of temporary sudden dropin axial stress within axial strain range of 0-2% which can be attributed to the collapse of soil particles held together
by suction.
Keywords: Unsaturated soil, Constant water content tests, Constant Volume, Isotropic Consolidation, Axial strain

INTRODUCTION

confining pressure (low or high) or constant matricsuction conditions. There is limited research
regarding the constant volume, i.e., constant void
ratio triaxial test on unsaturated soil. This study
investigates the mechanical behavior of unsaturated
soil using triaxial tests executed with constant volume
during shearing. Constant water content tests arecarried out in this study to simulate sudden failure
conditions in the field, and a pre-shear infiltration test
is performed to simulate the condition and failure
mechanism of a soil slope following a rainy period inwhich the soil above the water table has been wetted.

For most of their lifespan, earthen structures andslopes that have been engineered remain in
unsaturated state. In recent years, it has become clearthat unsaturated soil mechanics can shed light on how
compacted soils behave in a variety of situations, e.g.,foundation engineering, retaining walls, earthen
embankments and slopes, roads and pavements,
mining engineering and underground pipelines [1-2].
In unsaturated compacted soils, the presence of
matric suction can enhance the soil's shear strengthand decrease its compressibility while also increasing
the soil's effective stress. Additionally, suction helps
to maintain larger void ratios and principal stressratios at a given confining pressure [3]. Numerous
experimental works have already been conducted toinvestigate the behavior of unsaturated soil [4-7].
Since rainfall and water infiltration are closely
related to unsaturated slope failures, a thorough andin-depth seepage analysis is necessary to understandtheir behavior [8]. Both geotechnical andhydrological properties, such as the development ofpore water pressure, rate of water infiltration and therate of change in shear strength, which are influenced
by a change in matric suction, are significant whenstudying the behavior of unsaturated slopes [9].
Usually, triaxial compression tests on unsaturated
soils are carried out under unconfined, constant

TESTING PROGRAMMEThe physical properties of soil, specimen
preparation, test apparatus and procedure will be
discussed in this part.
Physical Properties of Soil
The fine soil used in this study is known
commercially as DL Clay; it has low plasticity. The
color of fresh, loosely deposited DL clay is yellowishbrown. DL clay is homogenous and easy to procure.
It is classed as non-plastic silt (ML) by the USCS
(Unified Soil Classification System) (ASTM D248711 2011) with 90% silt and 10% clay, and it has alarger grainsize than ordinary clay. This soil has a
144

SEE-Mie, Japan, Nov.10-12, 2022

uniform grain size distribution, with a mean grain size
D50 of about 0.03 mm [10].

prepared specimens were 10 cm in height and 5 cm indiameter as shown in Fig. 2.

Fig. 2 Prepared Sample

Fig. 1 Compaction Curve for the studied soil [11]Test Apparatus

This soil is used because, at the same degree ofsaturation, it has a lower initial matric suction thankaolin clay. Table 1 and Fig.1 shows the physicalproperties and compaction curve of DL Clay.

Modern strain-controlled triaxial equipment
suited for evaluating unsaturated soils was utilized forthis research. It is comprised of a double cell, porewater pressure (PWP), cell pressure and pore airpressure (PAP) transducers. Loading system forexerting axial load, Low-Capacity Differential
Pressure Transducer (LCDPT) to measure volume
change, external Linear Variable Displacement
Transducer (LVDT) to measure the verticaldeformation of the specimens and a suitable computer
application to track test sequence and record
experimental results. The triaxial device isadditionally coupled to a balance with an externalload cell to quantify the amount of water drained orinfiltrated into the specimen.

Table 1 Physical Properties of DL Clay
Properties

Unit

Value

Specific gravity

g/cm3

2.635

Percentage of fine content%

99

Consistency-

Non-Plastic

Maximum dry density, dmax

g/cm3

1.55

Optimum water content%

20

Specimen Preparation
To achieve a uniform density along the specimens'
length, the soil was compacted in five layers, eachbeing 2 cm thick, in a cylindrical mold with adiameter of 5 cm using a static compaction machine
having a hydraulic jack [12]. The low energy of staticcompaction can provide a homogeneous density inthe specimen, preventing the formation of a weakerzone [13]. Water was mixed with dry DL clay prior
to compaction to make specimens at optimum watercontent of 20%. The samples were compacted to 80%
degree of compaction and had a dry density of
1.24g/cm3. During preparation, the specimen
underwent a pre-consolidation pressure of about
210kPa and were initially 46.5% saturated with void
ratio of about 1.125. All specimens had initial matricsuctions of ≈19-20 kPa, indicating that the
preparation steps were always meticulously followed
to maintain a suction condition of about 20 kPa. All

Fig. 3 Schematic Diagram of Triaxial Test Apparatus
Figure 3 depicts a schematic representation of thetriaxial system employed in this study. The load cellalong with all the transducers were properly
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SEE-Mie, Japan, Nov.10-12, 2022

calibrated according to standards before commencing
the experiments.
A thin membrane "Supor 450" and a
Polytetrafluoroethylene (PTFE) sheet were used toeffectively control and measure the pore water andpore air. The thin membrane was put on the bottom
pedestal to allow water to flow while blocking the air
passage [14]. It had a pore size of 0.45 μm, a thicknessof 140 μm, and an air entry value of 250 kPa. The
PTFE sheet was glued to the underside of the top cap
to prevent water flow into the top cap (Fig. 4). To
reduce the amount of air in the pore air drainage line,
a solenoid-controlled exhaust air valve is also
installed within the top cap.

controlled by the load control system to keep
deviatoric stress (q) equal to zero.

InitialSuction

ATT

Isotropic
Con.

Shearing

Fig. 5 Test phases involved
Figure 5 depicts the test stages involved in thecurrent research. During shearing, the drainage valve
for the pore water pressure was kept closed while thepore air pressure was continuously drained andcontrolled, and the soil specimens were sheared withconstant void ratio (constant volume) at a strain rateof 0.05 mm/min under constant water content
conditions. When fill materials are compacted in thefield, the excess pore-air pressure that is developed
during compaction will vanish instantly, while theexcess pore-water pressure will dissipate over time.
Constant water content test (CWC) can simulate thiscondition [16]. By adjusting the confining pressure in
response to the specimen's volume change (i.e.,reading of the LCDPT value), the sample volume was
kept constant. The shearing phase was automaticallyterminated when the axial strain reached 15%, in
accordance with standards of Japan GeotechnicalSociety "JGS 0527-2020".
For the pre-shear infiltration test, water in the soil
sample was infiltrated through the waterline from thebottom pedestal, which was connected to a beaker andthe pore water pressure transducer. The beaker was
mounted on an external load cell and enclosed in apressure chamber (balance). The rate of infiltration
was regulated by varying the pressure of air applied
on top of the water surface in the beaker [13], [17].
For this test, when isotropic consolidation wasachieved after initial suction measurement and ATT,the matric suction value of the soil sample was
reduced to 5kPa. This was accomplished by carefully
applying infiltration pressure of 15kPa on the balance
to increase the pore water pressure. When no further
change in the flow of water entering the specimen was
detected, the water infiltration step was completed.
Following the infiltration stage, the pore waterdrainage valve was closed, and the specimen was
subjected to shear under constant water content
conditions.

Fig. 4 Schematic of Top Cap and Bottom Pedestal
Test Procedure
The bottom pedestal was fully saturated before
each test, so that no air bubble is trapped inside theporous stone of the pedestal. The suction pump wasused to apply vacuum pressure to de-air the water inthe exterior upper and lower tanks for at least 24
hours.
After the specimen was prepared, it was wrappedin a rubber membrane using a membrane holder andset over a pedestal with a thin membrane to measure
the initial suction value. After measuring initialsuction, the Axis translation technique (ATT) was
carried to prevent formation of cavities inside thepedestal, which would ultimately affect the reading of
pore-water pressure. To make pore water pressurezero, the pore air pressure and confining pressure
were both increased at the same time, leaving thespecimen volume unchanged [15].
During consolidation, the specimens wereconsolidated isotropically by applying the required
net confining pressures of 100kPa, 300kPa and
500kPa, to get the sample to the desired state before
shearing. The drain valve was kept open throughout
the consolidation phase, to dissipate the excess porewater pressure. The axial stress was automatically146

SEE-Mie, Japan, Nov.10-12, 2022

TEST RESULTS

gradually increases, and decreases again until the
specimen reaches the critical condition. Thisphenomenon may be caused by the abrupt loading
impact during shearing, which may cause the suctionheld soil particles to quickly collapse andsubsequently reorient. However, as the confiningpressure is decreased the peculiar behavior isminimized as can be seen from the stress paths
depicted in Fig. 9. It should be noted that the samples
consolidated with 300 and 500kPa are normallyconsolidated as the confining pressure is greater thanthe pressure experienced during sample preparation
while the sample consolidated with 100kPa is lightly
over consolidated as the confining pressure is lessthan the pressure for sample preparation. The criticalstate line (C.S.L) has a slope of 1.3.

Up to a 15% axial strain, the sample was sheared
at a rate of 0.05% per minute. The water drain valve
was closed while the air drain valve was open so thatthe shearing could be done in constant water content
conditions. The cell pressure was adjusted manuallyin accordance with the LCDPT value to keep the void
ratio of sample constant, since the samples had to be
sheared with zero volumetric strain. Fig. 6 shows theconstant void ratio of samples maintained during
shearing phase.

Fig. 6 Constant Void Ratio during shearing
Figure 7 shows the relationship between
deviatoric stress and axial strain when sheared withconstant volume. It can be observed that thedeviatoric stress reaches a peak value within axial
strain range of 0-2%, and then decreases afterwards
exhibiting post peak behavior. The shear strength isgreater for specimen consolidated under highconfining pressure.

Fig. 8 Effective Stress Vs Axial Strain

Fig. 9 Stress paths of specimen in CWC tests
Throughout the shearing phase, pore water andpore air pressure both reduced, as shown in Fig. 10.
The drop in pore water pressure, however, wasgreater than the drop in pore air pressure. As a result,
there was a modest rise in matric suction as well.
Since the water drainage valve was closed and a fixedvoid ratio was kept during the testing, the degree ofsaturation of the samples remained almost constantthroughout shearing.

Fig. 7 Stress-Strain behavior
Figure 8 show that there is some peculiar behavior
over an axial strain range of 0-2%. The effective
stress gradually grows, then abruptly lowers, then147

SEE-Mie, Japan, Nov.10-12, 2022

It is evident from Fig. 11 that as matric suction
reduces, so does the overall stiffness and strength.
This is due to the effect of matric suction on interparticle contact forces, which tends to maintain thesoil structure. However, with a decrease in matricsuction it can be observed that the peculiar behavior
within axial strain range of 0-2% has reduced. Thisphenomenon can be one of the reasons for the very
sudden failure of slopes following an earthquake
during a non-rainy period.
Fig. 10 Pore Air Pressure and Pore Water Pressureduring shearing

Failure Surface

To authenticate the suction-based assumption
devised for the unusual behavior of effective stressduring 0-2% axial strain range, a pre-shear infiltration
test was carried out. This type of test replicates thestate and mechanism of failure of a soil slope
following a period of rain during which the soil above
the water table undergoes a wetting process [12]. To
reduce matric suction, the pore water pressure wasincreased prior to beginning the shear process.
Attempts were made in a few early trial tests toinfiltrate water into specimens without increasing thepore water pressure; however, only a little volume ofwater could be infiltrated into the specimens, which
was not sufficient. As a result, water infiltration was
conducted by lowering the matric suction (from20kPa to 5kPa). This was attained by exerting 15kPa
infiltration pressure on the balance. The volume of
infiltrated water into the specimen was 23cm3 in atime of 3.5 hours when matric suction was reduced to
20kPa from 5kPa. The degree of saturation wasincreased from 46.5 to 77%.

Fig. 12 Stress paths followed in p’eq space.
Figure 12 depicts a 3D illustration of therelationship between deviatoric stress, mean effective
stress, and void ratio at failure. The state boundary
surface (SBS) is formed by all of the stress paths lying
on the same failure plane. SBS distinguishes between
achievable and impossible stress states. It can also be
noted that the constant volume test generates contourlike lines, which aid in determining the geometry of
the state boundary surface.
CONCLUSIONSIn this study, constant volume shearing tests werecarried out to explore the mechanical behavior ofcompacted silty soil under constant water content
conditions. Following conclusions can be drawn fromthis study:• To maintain constant volume of specimen during
shearing, the cell pressure was adjusted manuallycorresponding to the change in volume indicatedby LCDPT.
• The deviatoric stress reaches a peak value withinaxial strain range of 0-2%, and then decreases
afterwards exhibiting post peak behavior. The
effective stress also exhibits peculiar behavior

Fig. 11 Effect of water infiltration on stress-strain
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SEE-Mie, Japan, Nov.10-12, 2022•••

(increased and decreased twice) within axial
strain range of 0-2%.
The matric suction slightly increased during
shearing due to decrease in pore water pressure.
The overall shear strength decreased withdecrease in matric suction. However, as matricsuction reduces there is a drop in the peculiar
behavior observed within axial strain range of 02%.
Constant volume test present contour lines which
help in defining the state boundary surface.

uniform antecedent rainfall. Landslides Vol. 10,
No. 1, 2013, pp. 15–22.
[10] Chae, Jonggil, Byeongsu Kim, Seong-wan Park,and Shoji Kato., Effect of suction on unconfinedcompressive strength in partly saturated soils.
KSCE Journal of Civil Engineering, Vol. 14, No.
3, 2010, pp. 281-290.
[11] Rasool, Ali Murtaza, and Mubashir Aziz,
Advanced triaxial tests on partially saturated
soils under unconfined conditions. International
Journal of Civil Engineering Vol. 18, No. 10,
2020, pp. 1139-1156.
[12] Rasool AM, Kuwano J, Influence of matricsuction on instability of unsaturated silty soil in
unconfined conditions. International Journal of
GEOMATE, Vol. 14, No. 42, 2018, pp. 1–7.
[13] Melinda F, Rahardjo H, Han KK, Leong EC,
Shear strength of compacted soil under
infiltration conditions, Journal of GeotechnicalEng. Div. ASCE, Vol. 130, No. 8, 2004, pp. 807–
817.
[14] Habasimbi P, Nishimura T, Soil water
characteristic curve of an unsaturated soil under
low matric suction ranges and different stressconditions. International Journal of Geosciences,Vol. 10, No. 1, 2019, pp. 39-56.
[15] Hilf JW, “An investigation of pore waterpressure in compacted cohesive soils” U.S.
Department of Interior Bureau Reclamation
Technical Memo. no. 654, 1956.
[16] Thu, Trinh Minh, Harianto Rahardjo, and EngChoon Leong, Critical state behavior of acompacted silt specimen. Soils and Foundations,Vol. 47, No. 4, 2007, pp. 749-755.
[17] Farooq, Khalid, Rolando Orense, and Ikuo
Towhata, Response of unsaturated sandy soils
under constant shear stress drained condition.
Soils and foundations, Vol. 44, No. 2, 2004, pp.
1-13.

ACKNOWLEDGEMENTS
The Japanese Ministry of Education, Culture,
Sports, Science and Technology (MEXT) is
gratefully acknowledged for research facilities andfinancial assistance.
REFERENCES[1] Kodikara, J., T. Islam, and A. Sounthararajah,
Review of Soil Compaction: History and Recent
Developments. Transportation Geotechnics, Vol.
17, Part B, 2018, pp. 24–34.
[2] Fredlund DG, Rahardjo H, Soil Mechanics for
Unsaturated Soils. New York: John Wiley andSons Inc., Soil Dynamics and Earthquake
Engineering, Vol. 12, No. 7, 1993, pp. 449–450.
[3] Alonso, Eduardo E., Enrique F. Ortega Iturralde,and Enrique E. Romero, Dilatancy of coarse
granular aggregates. Experimental unsaturated
soil mechanics, Springer, Berlin, Heidelberg,
2007, pp.119-135.
[4] Rahardjo, H., Lim, T. T., Chang, M. F., &Fredlund, D. G., Shear-strength characteristics ofa residual soil. Canadian Geotechnical Journal,
Vol. 32, No. 1, 1995, pp. 60-77.
[5] Peters, S. B., Siemens, G., & Take, W. A.,
Characterization of transparent soil forunsaturated applications. Geotechnical Testing
Journal, Vol. 34, No. 5, 2011, pp. 445-456.
[6] Li, L., and Zhang, X., A new triaxial testing
system for unsaturated soil characterization.
Geotechnical Testing Journal, Vol. 38, No. 6,
2015, pp. 823-839.
[7] Bagherieh, A. R., Baharvand, M., Meidani, M., &Mahboobi, A., Prediction of wetting-induced
swelling using effective stress in an unsaturated
kaolin. Iranian Journal of Science andTechnology, Transactions of Civil Engineering,Vol. 43, No. 1, 2019, pp. 59-67.
[8] Yeh, H. F., Lee, C. C., & Lee, C. H., A rainfallinfiltration model for unsaturated soil slope
stability. Sustainable Environment Research, Vol.
18, No. 2, 2008, pp. 271-278.
[9] Mahmood K, Ryu JH, Kim JM, Effect ofanisotropic conductivity on suction andreliability index of unsaturated slope exposed to149

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

NUMERICAL SIMULATION OF ENERGY EXTRACTION FROM A
RESONATING RESERVOIR
Bang-fuh Chen, Hsing-nan Wu and Po-hung Yeh
Department of Marine Environment and Engineering, National Sun Yat-sen University, Taiwan

ABSTRACT
Wave energy harvest can be implemented through wave energy converters (WECs), including oscillating watercolumns (OWCs). Since the working mechanism of present paper bears resemlance to OWC, the possibility togarner energy from a resonant harbor is presented. Firstly, present study is carried out by a small-scaled 2D
numerical wave tank, with a simulated downsized chamber which resembles a harbor reservoir attached to the end
side. Second, the model in is validated by comparison with previous studies. The 3D model simulation whereparametric settings and mesh layout are based on the results in 2D numerical calculation is performed. Fromexperimental dimensional analysis and numerical prediction, it is indicated that the possible velocity inside theconnecting channel can reach up to 1.44 m/s and can be used for future energy excavation.
Keywords: Energy harvest, Resonant harbor, numerical wave tank, OWC

INTRODUCTION

70% [3]. In the work performed by Teixeira et al.
(2013), 40%~50% of average energy capture ratio isreported [4].
However, regarding the front wall geometry, thestudy conducted by Tsai, Ko and Chen (2018)indicates that through a modified device, theincoming flow can form a U-type flow pattern inside
the OWC, thus enhancing OWC’s efficiency [5]. Alsofrom [6], the turbine efficiency obtained by the newgeneration turbine can reach up to 70%-80%.
From what is stated above, it is learned that theefficiency of wave energy transfer from progression
to OWC, also considering the turbine energy
capturing rate, may range from 20% to 30%.
Moreover, Kuo et al. (2017) reported thehydrodynamic efficiency is less than 10%. On
account that their chamber-orifice ratio was smaller,
the efficiency in their research work was lower thanothers. As a result, to capture energy from the NDD
connecting between the tank and the chamber isassumed to be the direct approach [7].
In the following sections, the simulated model isconstructed to begin with, and the problem
description is then made. Research methods isdelineated afterwards, followed by some preliminary
results and discussion. Lastly, concluding remarks are
made in the last section.

Of all types of sustainable energies that can beharnessed from the ocean, wave energy is estimatedto have the most deposit [1]. That is the reason why
the world has been turning more and more attention
toward wave energy excavation. According toEuropean Marine Energy Center Ltd., wave energy
extraction can be classified into several types, which
are attenuator, point absorber, oscillating wave surge
converter, oscillating water column (OWC) and fiveothers [2]. Each type, particularly OWC, has received
more and more attention and researched these years
due to the soaring demand for renewable energy
worldwide. In present study, the possibility to extractenergy from a resonant harbor is to be investigated.
Although our current study doesn’t analyze theaforementioned nine types directly, yet since themodel in this paper bears a striking resemblance to an
OWC, this present work will be availed of the similar
research method used in other wave energy
converters (WECs) to explore the energy acquisition
from both resonant harbors and OWCs.
In contrast to other WECs, OWC has its
advantages over others. Since most OWCs are built
near the coast, the installation is less difficult, which
also makes the upkeep easier. Besides, some OWCs
serve to break waves. It is further estimated that
10%~60% of the wave energy can be collected.
Morris-Thomas, Irvin and Thiagarajan disclosed thatan increase in front wall submergence can reduce thehydrodynamic efficiency in short waves, and so canan increase in front wall thickness. The findings also
reveals that the efficiency vaies with kh (k and h arewave number and wave elevation, respectively), withthe average of 30%, and maximal efficiency being

RESEARCH METHODS
Model description
In view of the geometry being more complicatedin present study, simplification of the harbor needs tobe done in the first place to be fitted in the tank so as
to further help conduct simulation. The constructed150

SEE-Mie, Japan, Nov.10-12, 2022

harvest can be achievable. Size of model components
are also revealed in Fig. 1. The inlet diameter, central
diameter, outlet diameter, total length, chamber
length and water depth are denoted as Din, Dmid, Dout,
LNDD, LC and h0 , respectively.
The computational domain and mesh distribution
in present study is displayed in Fig. 3. The far-viewof the domain is shown in Fig. 3(a), while Fig. 3(a) is
the magnified view of the front part near the pistontype wave maker, which is designated with a green
arrow. The enlarged view of NWT's rear part isdisplayed in Fig. 3(b). Point A is where the virtual
wave gauge is stationed; their respect positions are
10m and 20m away from the wave maker at the left
side. Additionally, as illustrated in Fig. 3(c), a NDD,
namely a nozzle-diffuser duct, is installed between
the tank and the chamber to increase the pressure
difference, thus accelerating the current speed. In
doing so, the energy harvest can be possible.

model is exhibited in Fig. 1. The left region where thewave travels from left to right is analogous to theouter sea. The left-most boundary is likened to thewave maker. The upper in the left is atmosphere; themiddle is the wave zone where the waves progress;
the lower is the water body area. The chamber,
representative of a simplified reservoir harbor, is in
the right region.

(b)

(a)
Fig. 1A(a) Schematic representation of simulation
model; (b) magnified view at the end of the
tank.

(c)
In principle, the atmospheric area is mainly
occupied by air, and water body area is mainly water.
Seeing that the waves propagate chiefly in the wave
zone, the grids in this area are created more densely
in particular. Meanwhile, the waves when traveling inthis area are not made to be so large as to flood intoor even out of the atmosphere area. The connecting
channel is known as the nozzle-diffuser duct (NDD).

Fig. 3 (a) the computational domain. Point A (redline) is the location where virtual wave height meteris set up. The length of the numerical wave tank
(NWT) is 40m. (b) Enlarged view near the front of
the NWT. (c) Enlarged view near the rear part of thetank comprised of a chamber.
Governing equations

Fig. 2

In present study, ANSYS Fluent, a commercial
software in which computational fluid dynamics
method is adopted, is utilized for numerical analysis.
The two fundamental equations, listed in Eq.(1) and(2), are continuity equation and Navier-Stokes
equations, respectively. The equations using SIMPLE
algorithm are solved to obtain the velocity andpressure field. Second-order upwind method is
employed in pursuit of better accuracy.


(3)
+

U=0

t

Culverts serving as caisson breakwaters inconnection with the ocean and the harbor

DU

=

g
−

p
+


U
2

The device of NDD acts to simulate the culvert,
shown in Fig. 2, where the current velocity flowing
through this area can be augmented, so that the energy

Dt

151

(4)

SEE-Mie, Japan, Nov.10-12, 2022

The calculation is also coupled with volume of
fluid (VOF) method in multiphase model, so the freesurface is evaluated, and the wave height can bemeasured. During the computational procedures,
turbulent model is applied as suggested in [8]. Thusin present research work, k- realizible model isadopted.

and the momentum equation to calculate the flow field[12]. Our current paper also follows suit to apply thisvelocity profile into the boundary condition, so thatfurther physical quantities in the flow field can beobtained.
du== +0 sin t
dt
(9)
 a 
 n1 
3−20  −  cos 2t2
 2h0 n1  4sinh kh0  2 

Wave-making theory
In present NWT simulation, the wave-making
should be considered first and foremost. Wavemaking methods are generally categorized into flattype and piston-type. In 1960s, the relation between
wave height H and flap-type wave maker stroke isexpressed as Eq. (10).
H  2 cosh kh0=
Sgk 1 − y / h  cosh k (h − y)dy=
 cosh k (h − y)dy
h

0

0

h

0

0

Boundary conditions
The following boundary conditions provided by
ANSYS Fluent are applied to execute the numericalcalculation.
1. Moving wall: the moving wall acts as thepiston-type wave maker positioned at the left side of
the numerical wave tank (NWT). As mentioned in theprevious section, the piston-type wave-making
movement can be implemented by means of userdefined function (UDF) to be imported to the wallboundary condition. Noteworthy is that the moving
mesh technique is required if piston-type or flap-typewave-making method is used. Nonetheless, if only
stationary boundary is chosen, then velocity profile
needs to be appended and instead of the moving
boundary, which means moving mesh technique is
not needed. In present study, piston-type movement
is used, meaning that moving mesh technique isincluded.
2. Pressure outlet: This boundary condition isapplied on top of the tank for the air be the outlet
connected with the atmosphere, like it is set in the
open-channel flow condition.
3. Wall: the left, right and bottom of the tank andthe chamber (known as the reservoir/harbor) are set
as walls. No physical quantities will penetrate
through this boundary condition.

(5)

2

0

4sinh kh0 kh0 sinh kh0 − cosh kh0 + 1
kh0
sinh kh0 + 2kh0
, where k is the wave number, h0 is the still water
depth, with the velocity as a function of stroke S canbe written in Eq. (6). [9]=U ( y) =1
S 1 − y / h0 
2

(6)

For a small-amplitude wave, Dean and Dalrymple(1991) proposed that given the elevation
 = − a sin(kx − t ) , the wave maker’s displacementwith respect to time can be described as Eq. (7). [10]=−0cos
t
(7)
an

1
2
kh
1
, where 0 =
, n
, and

1
+ 20 
1=

tanh
kh
2
2
kh
0
0
 sinhh0 is the still water depth. a is the wave amplitude,and  is the angular frequency.

RESULTS AND DISCUSSION

The foregoing expression pertaining to thedisplacement and time are revised to be Eq.(8) by
Madsen (1970). [11] =  (1) +  (2)= − 0 cos tPrior to more in-depth investigation, validation ofcurrent model is to be executed. Firstly, gridindependence test has to be done. Afterwards,
comparison between present research and previous
studies are made to lay a foundation for forthcoming
parametric analysis.

(8)

 a 
 n1 
3− 0  −  sin 2t2
 2h0 n1  4sinh kh0  2 

Grid independence test

Differentiating Eq.(8) yields Eq.(9).
In general, researchers often apply this velocity
profile, namely Eq.(9), into the velocity inlet boundary
condition incorporated with the continuity equation

Suggestions brought up in [13] by Lloyd,
O’Doherty and Mason-Jones (2019) is referred to in
the present grid independence test. Their criterion
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SEE-Mie, Japan, Nov.10-12, 2022

outlines that the wave height spans at least 10 grid
points. Besides, Dong and Huang (2004) also statedthat time step size might as well be equaled to or lessthan t/T~0.001. Their description is also taken into
consideration in our present work.
The grid test outcome is presented in Fig. 4. Five
different densities of grid number are used, which are
named from Case A to Case F, with the mesh number
being from 36458, 60391, 61657, 82941, 83656 and
115070 separately. From the figure, as the grid
number increase, the data converge between Case D
and Case E, with the difference being less than 2%.
Therefore, the mesh number of 2D model in present
work is set to range between 80000 and 100000 or so.

Fig. 6 is the comparison between a previous study
conducted by Dong and Huang (2004) and the current
work. It is understood that a general tendency isobserved despite some insignificant discrepancies,
and that both datasets, using Stokes second-orderterms, demonstrate the flattened trough due tononlinear phenomenon.

Fig. 6 Wave elevation comparison with Dong andHuang (2004) (wave condition: water depthh0=0.38m, T=2.75, wave height H=5.7cm)
2D and 3D simulation comparison

Fig. 4After the validation, forthcoming exploration canbe conducted. For starters, the actual size of Hualien
Harbor is scaled down, and so is the wave condition
dimensions. The original wave conditions are
T=8.65s, h0=16m, H=1.19m. After the scaling, themodified wave conditions become T=1.73s,h0=0.65m, H=4.76cm. Downsizing the domain serves
the purpose of comparing the present simulation
result with the experimental data when future tankexperiment is conducted. Once the comparison ofboth datasets is made, the in-situ measuring data canbe predicted.

Grid independence test (wave condition:water depth h0=0.65m, T=1.73s, wave
height H=4.76cm)

Validation
Posterior to the convergence test, validation withother studies is accomplished. First, comparison withanalytical solution is made. The result is presented inFig. 5. From the figure, an overall agreement isrevealed, with the wave shape being basicallyoverlapping. In terms of wave elevation, the result
obtained in present research work approximates theanalytical solution. The difference is less than 2%.

Fig. 7 Time history of wave elevation (0s-28s) at
point A, sketched in Fig. 3. (Wave condition:
T=1.73s; water depth h0=0.65m; wave height
H=4.76cm; flume length=40m.)
Fig. 5

Wave elevation  comparison withanalytical solution (wave condition: water
depth h0=0.4m; T=1.25; wave height
H=1cm)

According to the aforestated wave conditions, 2D
and 3D NWT simulations are carried out. For thereason that 3D simulation requires huge amounts ofcomputational time, 2D result that is complete and153

SEE-Mie, Japan, Nov.10-12, 2022

established serves to lay the benchmark for 3D
calculation. As soon as 2D simulation converges, a
3D model can adopt similar grid layout in 2D as areference to go on further analysis.
Fig. 7 presents the wave elevation comparison.
Broadly speaking, the wave height of 2D and 3D are
4.51cm and 4.55cm individually, both of which show
insignificant disparity of 5% and 4.4% in contrast
with the actual observation value 4.76cm. From thefigure, both 2D and 3D simulation data demonstrate
a trend in agreement despite some discrepancy causedby the reflection from the wall on the right side.

From Table 1, when the velocity is converted to
the real situation in the coast caisson breakwater, thevelocity ranges from 0.79m/s to 1.44m/s. In
comparison with other current velocities in most
locations worldwide running at the speed of 1 to 1.5
m/s, the site of NDD situated in the culvert acting as
caisson breakwaters between the ocean and the harborwhich is discussed previously can be a potential
energy excavation place having stronger current
velocities. That means future energy capture at thislocation can be seen possible.

Simulated velocity in central NDD
Once the data acquired from 2D and 3D
simulation is validated, the simulation case of a 3Dmodel is then performed based on the criteria set in
2D case. The velocity at the entrance and in the
middle of NDD (namely the inlet and mid position in
Fig. 8) is numerically calculated and obtained using
high performance computing cluster since the mesh
number exceeds more than 2 million, thus taking
more time to run a case.
As shown in Fig. 9, where velocities in inlet andmid facets of NDD are exhibited, the simulation caseis only executed 40 seconds (physical time) before thewave reflects from the reservoir (harbor). From thefigure, one can observe the wave reaches the entranceof the NDD at around 15s, and the velocity inside the
NDD attains the steady state after 25s. It is revealed
that after 25 seconds the maximal velocity at the inlet
of NDD is around 0.07 to 0.08 m/s, while the maximal
velocity in the middle reaches up to 0.23 to 0.29 m/s.
That is to say, the middle velocity is more than 3 times
the inlet velocity. It is evident that the NDD has thefunction to accelerate the water current.
The average velocity magnitude during 3 periods
from 30s to 35.25s is taken, the average is measured
to be 0.16 m/s. When the use of Froude scaling,
namely Eq.(10) is applied, the velocity in the center
of NDD in actual ocean condition (Vproto) can bepredicted.
Lsim
Vsim
=
VprotoL protoFig. 8 Part of the facet mesh distribution near
NDD in 3D model.

Fig. 9 Time history of current velocity at theentrance and in the middle of NDD (Wave condition:
T=1.73s; water depth h0=0.65m; wave height
H=4.76cm; flume length=40m.)(10)
CONCLUSIONS, where sim and proto stand for simulation and ocean
prototype. Given Vsim, Lsim and Lproto, then Vproto canbe obtained. The estimated values of Vproto are listed
in Table 1.

After the the investigation is carried out
numerically by a commercial software package, andalso after the model case in present paper is validatedby two different studies, it is known that the present
model is reliable for future numerical prediction.
Also from what has been discussed, 2D
simulation serves to set the mesh distribution
benchmark for the 3D simulation case after 2D cases
converge and are in line with 3D counterparts. It isthen concluded that this carefully chosen 3D case isreliable enough gain good results and then executedby virtue of high-performance computing cluster as it

Table 1 Estimated value of Vproto

AVG
MAX

Vsim
0.16m/s
0.29m/s

Lsim
0.65m
0.65m

Lproto16m
16m

Vproto0.79m/s
1.44m/s154

SEE-Mie, Japan, Nov.10-12, 2022

is computaionally costly. Further, it can be concluded
that the channeling device, i.e. NDD, which acts as aconnecting bridge between the tank (ocean) and thereseroir (harbor), functions to accelerate the current
flow. The accelerated velocity can attain up to morethan three times the original velocity. The estimatedvelocity in the center of NDD ranges from 0.79m/s to
1.44m/s. When compared with the general current
velocity in the ocean at the speed of 1m/s, this makes
the energy harvest from the culvert (casisson
breakwater) feasible.
The result in present investigation has drawn the
blueprint for future roadmap. The energy
transmission efficiency through each component
during wave propagation may be analyzed by virtueof wave incident and reflection, together with wave
energy balance. Once the energy balance mechanism
is established, the method can be broadly used toassess the efficiency of WECs as well as theinstallation possibility.

[5] Tsai C.P., Ko C.H. and Chen Y.C., Investigationon performance of a modified breakwaterintegrated OWC wave energy converter,
Sustainability, Vol. 10, Issue 3, 2018. pp. 643662[6] Falcao A.F.O. and Henriques J.C.C., Oscillatingwater-column wave energy converters and air
turbines: A review, Renewable Energy, Vol. 85,
2016. pp. 1391-1424.
[7] Kuo Y.S., Chung C.Y., Hsiao S.C., and Wang
Y.K., Hydrodynamic characteristics ofOscillating Water Column caisson breakwaters.
Renewable Energy, Vol. 103, 2017, pp. 439-447.
[8] Thompson D.A., Karunarathna H. and Reeve D.,
Comparison between wave generation methods
for numerical simulation of bimodal seas, Water
Science and Engineering, Vol. 9, Issue 4, 2016,
pp. 3-13.
[9] Ursell F., Dean R.G. and Yu Y.S., Forced smallamplitude water waves: a comparison of theory
and experiment, Journal of Fluid Mechanics,
Vol. 7, Issue 1, 1960. pp. 33-52.
[10] Dean R.G. and Dalrymple R.A., Water wave
mechanics for engineers and scientists,
Advanced Series on Ocean Engineering, Vol. 2,
World Scientific, 1991. pp. 172-177.
[11] Madsen O.S., On the generation of long waves,
Journal of Geophysical Research, Vol. 76, Issue
36, 1971. pp. 8672-8683.
[12] Dong C.M. and Huang C.J., Generation and
Propagation of Water Waves in a TwoDimensional Numerical Viscous Wave Flume,
Journal of waterway, port, coastal and oceanengineering, Vol. 130, Issue 3, 2004. pp. 143153.
[13] Lloyd C., O’Doherty T. and Mason-Jones A.,
Development of a wave-current numerical modelusing Stokes 2nd Order Theory, International
Marine Energy Journal, Vol. 2, No. 1, 2019, pp.
1-14.

ACKNOWLEDGEMENTS
The authors would like to express their gratitude
to the Ministry of Science and Technology for thekind financial support of Thousand Mile Horse Grant(Graduate Students Study Abroad Program) under thecontract number 110-2917-I-110-003.
REFERENCES[1] Ocean Energy Technology Overview, 2009 (canbe accessed at http://large.stanford.edu/courses/
2013/ph240/lim2/docs/44200.pdf)[2] EMEC (European Marine Energy Center Ltd.),
2018. (can be accessed at
http://www.emec.org.uk/marine-energy/wavedevices/[3] Morris-Thomas M.T., Irvin R.J. and Thiagarajan
K.P., An investigation into the hydrodynamic
efficiency of an oscillating water column, Journalof Offshore Mechanics and Arctic Engineering,Vol. 129, Issue 4, 2007, pp. 273-278.
[4] Teixeira P.R.F., Davyt D.P., Didier E., Ramalhais
R., Numerical simulation of an oscillating watercolumn device using a code based on NavierStokes equations, Energy, Vol. 62, 2013, pp. 513530.

155

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

DURABILITY PERFORMANCE OF CONCRETE INCORPORATINGDIMENSION LIMESTONE WASTE AS FINE AGGREGATESREPLACEMENT
Jasmin M. Panganiban1 and Mary Ann Q. Adajar2
1
Faculty, University of Rizal System, Philippines;
2
Faculty, De La Salle University, Philippines

ABSTRACTQuarrying and production of dimension limestone produced a considerable amount of solid and slurry waste.
Because of its great potential to be used as alternative material in concrete, these dimension limestone waste(DLW) have been the interest of many researchers. Several studies focus its investigation on the effect of DLW
addition on concrete particularly on its mechanical properties. Although review of related literatures suggested theused of DLW in concrete because of its positive effect on concrete’s mechanical properties, there still remains
doubt on the its acceptability due to the lack of studies regarding its durability performance. Thus, this study aimed
to assess the durability performance of concrete made with DLW as fine aggregate replacement. The investigation
included test for sorptivity and resistance to sulfate attack using specimens with DLW replacements of level of
0%, 20%, 40% and 60%. Sorptivity test reveals that incorporation of up to 60% of DLW as sand replacement
reduces the permeability of concrete. In terms of sulfate resistance, it was found that addition of DLW reduces
length expansion and mass change due to sulfate attack. Furthermore, change in compressive strength test showedthat after 15 weeks of sodium sulfate immersion, DLW concrete exhibited a less than 25% reduction incompressive strength. Based on the findings of this study, it has been concluded that replacement of sand by DLW
can result to concrete having comparable durability performance.
Keywords: Durability performance, Sorptivity, Sulfate resistance, Limestone waste

Limestone is one of the most used dimension stone by
the construction industry. It is often cut into blocks
and slab panel that are used for flooring, cladding,stair thread and many other applications. The
quarrying and processing of these materials produced
considerable amount of solid and slurry waste which
are quite often left dumped in the quarry site. In oneof the local manufacturing plant in the Philippines, it
was reported that an average of 280 cu.m filteredsludge and 112 cu.m solid waste were collected every
month. These wastes are considered a big problem
from the aspects of disposal, environmental pollution,and health hazards. Given that we cannot totally
reduce the amount of waste, neither at the quarrying
stage nor at the dimension limestone production, theindustry is therefore obligated to find a way to utilize
these industrial wastes.
Useful application of solid waste particularly as
substitute for fine aggregates in concrete is apromising solution to avoid severe problem
associated with solid waste disposal and help
construction industry in finding solution to the onset
shortage of sand [2]. Earlier studies showed thatlimestone waste exhibits properties that is nearlycomparable to that of the natural river sand [3]–[4].
Because of this, utilization of dimension limestone
waste (DLW) as fine aggregate replacement becomesa viable solution to address the problem of both the

INTRODUCTION
In a global scale, the construction industry is ingreat demand for raw materials particularly sandwhich is one of the component in making concrete.
According to the United Nations Environmental
Programme, the demand for sand has tripled over thelast two decades as a result of the ballooning
population, expanding urbanization, infrastructuredevelopment and ever-changing consumption
patterns [1]. The estimated global sand consumptions
have reached a volume of more than 20 billion tons
annually, 75% of which is used in concrete
production. Because of this huge consumption, many
regions around the world is bound to face anincreased rate of resource depletion.
In the Philippines, because of the current trend ininfrastructure development, both public and private,
the demand for fine aggregates or sand remains highand is expected to continuously grow. The country isrich in natural resource for raw materials such as riversand, stone and boulders, however over-exploitationof this non-renewable resources will eventually leadto its depletion causing sand scarcity in the country.
The construction industry is therefore compelled tosearch for alternative for natural fine aggregate.
Similar to sand, dimension stone also has anincreasing domestic and international demand.
156

SEE-Mie, Japan, Nov.10-12, 2022

sand and dimension limestone industry.
Review of literatures on the properties of concretewith limestone concludes that, in general,
incorporation of an appropriate amount of limestone
as fine aggregate replacement enhances thecompressive strength [4], flexural strength [3] andsplitting tensile strength [5]. Several researchers havealso reported that limestone aggregate could reduce
the total shrinkage, water permeability and sorptivity
coefficient of concrete [6]. Evaluation of sulfate
resistivity, however, has contradicting results.
Therefore, this study further investigated the
durability performance DLW concrete exposed tosulfate-rich environment which is common in thePhilippines being an archipelagic country where
seawater is abundant. Specifically, this study aims toassess the effect of using DLW as fine aggregate
replacement in the sorptivity and sulfate resistance ofconcrete. It is hoped that the result of this study will
be a valuable input in the development of local
standards to gain widespread acceptance anddeployment of DLW concrete.

of DLW and sand. As shown in the figure, both sandand DLW exhibited a continuous grading. Sandshows a grading that fits within the limit whereas thefineness of DLW exceeded the upper limit set forth in
ASTM C33. DLW has fineness modulus of 1.54
which is 37% lower compared to the 2.44 finenessmodulus of sand, indicating that DLW is a finermaterial compared to sand. Based on ASTM C33, thefineness modulus of fine aggregates generally ranges
from 2.0 to 3.3. In some cases, however, aggregateswith fineness modulus less than 2.0 are used, an
example of which is manufactured fine aggregates
which contains finer natural sand [7].
Table 1 Physical properties of fine aggregates
Property
Specific Gravity (SSD)
Absorption (%)
Fineness Modulus

EXPERIMENTAL PROGRAM
Passing (%)

Materials
DLW concrete test specimens were preparedusing locally available materials. For cementitious
materials, Ordinary Portland Cement Type 1,
complying with PNS 7:2005, was used. Well gradedcrushed gravel with a maximum size of 20mm (3/4in)
were used as coarse aggregates, while fine aggregatesconsist of a combination of sand and DLW. The
mixing water were free from organic material and any
deleterious minerals.
The DLW used as partial replacement for sandwere dry limestone waste in slurry form collectedfrom dump yard of a local dimension stone
manufacturing plant and was sieved for particle size
ranging from 75m to 4.75mm. A comparative
analysis of sand and DLW fine aggregate wasconducted in terms of specific gravity, absorption andfineness modulus.

100
90
80
70
60
50
40
30
20
10
0
0.01

Fig. 1

DLW
2.58
1.42
1.54

Sand
2.72
0.81
2.44

Lower Limit
Upper Limit
DLW
Sand

0.1

1
Seive Size (mm)

10

100

Particle size distribution curves

Mix Proportion
A total of four (4) concrete mixtures were used inorder to evaluate the effect of dimension limestone
waste as sand replacement on the durability
performance of concrete. Design mix proportion of
concrete without DLW, designated as C-L0, as per
ACI specification for a target strength of 20 MPa
normal weight concrete and slump in the range of 5090mm were used as reference or control mixture.
DLW concrete mixtures were then determine bypartially replacing sand with DLW. The replacementlevel investigated were 20%, 40% and 60% by weight
thus each DLW concrete mixture werecorrespondingly designated as C-L20, C-L40 and
C-L60, respectively. In all four mixes, no chemical
admixture has been added and the water-to-cement
ratio used was 0.65. Except for the ratio of dimension
limestone waste and sand, the amount of othermaterials such as cement, coarse aggregate andmixing water were kept constant.
Preliminary tests were conducted to pre-assessed

Properties of dimension limestone waste
The physical properties of DLW and sand were
determined in accordance with ASTM test standards
and the results are presented in Table 1. The specificgravity and absorption of DLW fall within the range
for normal weight aggregates specified in ACI
standard. The specific gravity of DLW is slightly
lower whereas their water absorption is roughly 75%
higher as compared with sand.
The particle size distribution of sand and DLW
was measured through sieve analysis in accordancewith ASTM C136. Figure 1 summarizes the gradation
157

SEE-Mie, Japan, Nov.10-12, 2022

if the design mix are suitable for the experimental
program. Initial compressive strength test has been
carried out on C-L0 mixture to determine if the design
strength of 20MPa were achieved after 28 days ofcuring. Simultaneously, slump test for C-L60 werealso conducted to check if the workability is within
acceptable limit. After the initial test, resulting to
C-L0 having achieved the design strength and C-L60
yielding slump above tolerance level of 25mm, thedesign mix proportions were adopted for the purposeof this study. Table 2 summarizes the details of theconcrete mix proportion used.

measurement of mortar prisms specimens was carriedout in accordance with ASTM C1012. The initiallength measurement was taken before sulfate
immersion and then length change measurement was
taken after 1, 2, 3, 4, 8, 13, 15, 19, 24 weeks of sulfate
immersion.
TEST RESULTS AND DISCUSSION
Sorptivity
Durability of concrete is largely dependent on its
ability to absorb water. Soptivity is widely used tocharacterize the concrete’s ability to absorb water andtransmit it via capillary action. It provides indicationsof pore structure and connectivity which is an
important factor that influences the concrete’s
resistance to attack of aggressive substance when
exposed to severe environment [8]. Increased
sorptivity potential can lead to rapid concrete
deterioration. Figure 2 presents a typical absorption
curve of DLW concrete.

Table 2 Details of concrete mix proportion

Material
CementGravel
Sand
DLW
Water

Mix Proportion in kg/m3
C-L0
C-L20 C-L40
316
316
316
1007
1007
1007
853
682.4
511.8
0
170.6
341.2
205
205
205

C-L60
316
1007
341.2
511.8
205

3.00

Methodology and Test for the Studyy = 0.0018x + 1.1021
R² = 0.9872

Absorption, I (mm)2.50

Durability of DLW concrete in terms of sorptivity
and sulfate resistance was evaluated through series oflaboratory experiments in accordance to ASTM
standard. For each durability test, five replicate
samples per mixture were tested.
To determine the sorptivity e, the standard test
method in accordance with ASTM C1585 wasfollowed. The test was carried out on concrete
specimens having diameter of 100 mm and height of
50 mm after 28 days and 90 days curing period.
Sulfate resistance of DLW concrete was evaluatedin terms of change in length, mass and compressive
strength. For change in mass and compressive
strength, 100mm concrete cube specimens were
fabricated while for length change evaluation, 25mm
by 25mm by 285mm mortar prism specimens wereused as established by ASTM C157M. After the
initial 28-day curing, each concrete specimens were
subjected to sulfate attack by immersing it in a
sodium sulfate solution with a concentration of 5% bymass. The volume proportion of sulfate solution to
concrete specimens was maintained at 4±0.5 toensure full immersion. The sulfate solution was
stirred every week and replenished each month tomaintain same concentration throughout the study.
Compressive strength test in accordance withASTM C39 was performed on concrete cube
specimens at the end of 28 days curing period andafter 2, 4, 8, 13 and 15 weeks of sulfate immersion.
Concurrently, for a set of concrete cube specimens,
weight in saturated surface dry condition were
measured and recorded as basis for mass change
evaluation. Parallel to this, length change

2.00
1.50
y = 0.0062x + 0.1963
R² = 0.9758

1.00
0.50

Initial Absorption
Secondary Absorption

0.00
0

200

400
600
Time, t (s1/2)

800

1000

Fig. 2 Typical absorption curve of DLW concrete(C-L20 at 90 days)
Notice that absorption was more intense during
the first 6 hours of the test, and then tends to gradually
decreases afterwards. The rate of absorption during
the first 6 hours is known as the initial sorptivity
which is equal to the slope of the line that is the best
fit to absorption plotted against the square root of time
and was determined through linear regression
analysis using all the points from 1 minute to 6 hours.
On the other hand, the secondary sorptivity was taken
as the slope of the line that best fitted the plot ofabsorption versus square-root of time using all points
from day 1 to day 8.
The results of sorptivity tests are summarized andillustrated in Figure 3. Comparison of the results
recorded at test age of 28 and 90 days shows that theaddition of DLW generally reduces the sorptivity
values. At 28 days, concrete with 20%, 40% and 60%
DLW exhibits 27%, 20% and 17% reduction,
respectively, in initial sorptivity as compared tocontrol concrete. For secondary sorptivity, 14% and158

SEE-Mie, Japan, Nov.10-12, 2022

10% reduction were observed for replacement levelof 20% and 40%, respectively, which is contrary to
the 32% increase noticed when replacement level is60%. At 90 days testing age, the effect of DLW on
sorptivity is more defined. A consistent reduction inboth initial and secondary sorptivity with increasing
DLW content was observed. The initial sorptivity of
all mixes are comparable, with C-L60 having aslightly noticeable reduction of 9%. In terms of
secondary sorptivity, 19%, 20% and 28% reduction
relative to control concrete was recorded whenreplacement level is 20%, 40% and 60%, respectively.
The reduction in sorptivity was more pronounced in
the 20% replacement level at 28 days and 60%
replacement level at 90 days. It is important to note
that, all concrete mixes are considered acceptable interms of sorptivity property since any value less than
0.10 mm/s1/2 indicates an excellent quality concrete.

incorporated while other scholars found that thepresence of limestone improves sulfate resistance [6].
Results of sulfate resistance evaluation of DLW
concrete are hereby presented.
Change in length
The resistance to sulfate attack is commonly
evaluated through expansion measurements. Figure 4
presents the average expansion of 5 mortar bars
immersed in sodium sulfate solution measured after
1, 2, 3, 4, 8, 13, 15, 19 and 24 weeks of immersion as
per ASTM C1012. During the test, increased
expansion was observed in all mortar samples.
Considering the expansion after 6 months, all tested
mixes expanded less than the ACI stipulated
expansion limit of 0.10%. Among the studied mixes,
control samples exhibited the highest expansions.
0.12

28D Secondary Sorptivity

90D Initial Sorptivity

90D Secondary Sorptivity

0.0080
Sorptivity (mm/s1/2)

M-L0
M-L20
M-L40
M-L60
Limit

0.10
Length Change (%)

28D Initial Sorptivity

0.00600.0040

0.08
0.06
0.04
0.02

0.00200.00

00.00000

Fig. 32040
DLW Content (%)

4

8
12
16
20
Immersion Time (weeks)

24

28

60

Fig. 4

Sorptivity of DLW concrete

Length change of DLW mortar prism

Statistical analysis revealed a significant decreasein length change between each DLW mortar samples
and control samples. The percent decrease in lengthchange were 29%, 19.9% and 16% for M-L20, M-40
and M-60, respectively. This indicates thatincorporating DLW does in fact reduces the length
expansion caused by sulfate attack. Nevertheless, it
is important to note that although samples preparedwith DLW have expanded less than the control
concrete, expansion increases as the amount of DLW
increases. This is because adding limestone in higher
quantity increases the calcite content which also
increases the possibility of ettringite and gypsum
formation that leads to length expansion [10].

Through Analysis of Variance, an overall look at
the sorptivity results reveals that there is no
significant variation in both initial and secondary
sorptivity values due to percent replacement andcuring period. The variation, however small, indicatesthat incorporation of up to 60% DLW as sandreplacement improves the sorptivity. The
improvement
signifiesadenserconcretemicrostructure making them more impermeable
compared to control concrete. This could be
attributed to the filler effect of the much smaller andfiner particles of DLW blocking the interstitial andcapillary pores of the binder phases of the mixture [9].

Change in mass
Mass loss is another indicators of concrete
deterioration. The curve shown in Fig. 5 presents thepercent change in mass measured after immersing
concrete cube sample in sodium sulfate solution for aperiod of 1, 2, 3, 4, 8, 13, and 15 weeks. All samples
demonstrate a similar trend. In the first week ofimmersion, a slight drop in mass was observed, thenfollowed by a gradual increase in the subsequent

Resistance to Sulfate Attack
Sulfate resistance is one of the main concerns interms of durability performance of concrete
containing limestone. It has been previously reported
that addition of limestone in concrete resulted to its
poor performance under sulfate exposure. Somestudies confirmed that expansion of concrete
increased significantly when limestone is159

SEE-Mie, Japan, Nov.10-12, 2022

immersion time. The initial drop in mass can be
attributed to the leaching of hydration products into
the solution while the succeeding increase in mass
was caused by the formation of expansive compound
during the sulfate attack [11].

the corresponding change in compressive strength
were recorded. As depicted in Fig.6, all concrete mix
experienced a continuous compressive strength
development in the first 8 weeks of exposure to
sodium sulfate solution. After that, decrease incompressive strength related to increase in immersion
time was observed. It can therefore be concluded that
sulfate attack affects the compressive strength of
concrete whether or not DLW were incorporated,particularly when exposed for a longer duration. The
initial development of compressive strength evenafter sulfate exposure may be attributed to thecontinuous formation of hydration products and theformation of expansive product from the reaction of
sulfate ions with hydrated cement components [11].
As this reaction product was formed, it filled the poresand strengthened the concrete. But, later on, when theformation of expansive product becomes more
dominant, it induced cracking, spalling and loss ofstrength.

0.30
C-L0
C-L20
C-L40
C-L60

Mass Change (%)

0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
0

Fig. 5

4
8
12
Immersion Time (weeks)

16

Mass change of DLW concrete

Table 3 Compressive strength of DLW concrete

ANOVA showed a significant difference in masschange of DLW concrete and control concrete. The
concrete incorporated with DLW showed a lower
mass change at the increasing stage compared with
control concrete. After 15 weeks of exposure, mass
increase was 39.5% lower for C-L20, 61.3% for
C-L40 and 28.1% for C-L60. By inspection, concretewith 40% DLW has more pronounced effect inreducing mass change. Though the change in mass isrelatively small, the resulting increase in massindicates a formation of expansive compounds due tocontinuous exposure to sulfate. Evidently, from themass and length change test, concrete incorporated
with DLW has improve resistance to sulfate attack.
This can be attributed to the effective reduction insorptivity due to the filler effect of DLW. The reduced
sorptivity decreases the change of sulfate ions ingressinside the hydrated cement matrix whichconsequently improves the resistance to sulfate attack.

Sample ID

% DLW

C-L0
C-L20
C-L40
C-L60

0
20
40
60

28th-day Compressive
Strength (MPa)
24.84
25.00
27.59
27.03

Compressive Strength Change
(%)

40
30
20
10
0

C-L0
C-L20
C-L40
C-L60

-10
-20
0

Change in compressive strength
Prior to sodium sulfate immersion the average 28th
day compressive strength was determined and theresults are shown in Table 3. The compressive
strength of all mixes satisfactorily exceeded thedesigned value of only 20MPa. Furthermore, it isobvious that as the DLW content increases,
compressive strength gradually increases until the
maximum compressive strength was developed at a
replacement level of 40%. On the other hand, eventhough concrete specimen containing 60% DLW
presents a compressive strength lower than the
maximum recorded value, its compressive strength isstill higher than the control specimen.
The compressive strength of concrete after
immersion in sodium sulfate solution for a period of
2, 4, 8, 13, and 15 weeks were also determined and4812
Immersion Time (weeks)

16

Fig. 6 Compressive strength change of DLW
concrete due to sulfate attack
At the end of testing, 15 weeks after immersion,
C-L0 and C-L20 maintained a compressive strength
9.7% and 10.9% higher, respectively, compared totheir respective compressive strength prior to
immersion. On the other hand, mixture with 40% and
60% DLW substitution rate showed an initial
compressive strength reduction of 2.4% and 4.6%,
respectively, after 13 weeks of exposure. After 15
weeks of exposure, C-L40 and C-L60 retained only
96% and 91% of their compressive strength prior to
immersion, respectively. Considering the 25% limit
in strength loss recommended by Mehta [12] forsulfate resistance concrete, it can still be concluded160

SEE-Mie, Japan, Nov.10-12, 2022

that all concrete mixes exhibited good performanceon sulfate resistance despite the observe decrease incompressive strength change.

Environmental Governance of Global Sand
Resources, United Nations Environment
Programme, 2019.
[2] Adajar, M. A. Q., de Guzman, E., Ho, R., Palma
Jr, C., and Sindico, D., Utilization of Aggregate
Quarry Waste in Construction Industry,
GEOMATE Journal, Vol. 12, Issue 31, 2017, pp.
16-22.
[3] Chouhan, H. S., Kalla, P., Nagar, R., andGautam, P. K., Gainful Utilization of
Dimensional Limestone Waste as Fine
Aggregate in Cement Mortar Mixes,
Construction and Building Materials, Vol. 221,2019, pp. 363-374.
[4] Bederina, M., Makhloufi, Z., Bounoua, A.,
Bouziani, T., and Quéneudec, M., Effect ofPartial and Total Replacement of Siliceous River
Sand with Limestone Crushed Sand on the
Durability of Mortars Exposed to Chemical
Solutions, Construction and Building Materials,
Vol. 47, 2013, pp. 146-158.
[5] Omar, O. M., Abd Elhameed, G. D., Sherif, M.
A., and Mohamadien, H. A., Influence ofLimestone Waste as Partial Replacement
Material for Sand and Marble Powder inConcrete Properties, HBRC Journal, Vol. 8,
Issue 3, 2012, pp. 193-203[6] Wang, D., Shi, C., Farzadnia, N., Shi, Z., and Jia,
H., A Review on Effects of Limestone Powder
on the Properties of Concrete, Construction and
Building Materials, Vol. 192, 2018, pp. 153-166.
[7] ACI Committee E701, “Aggregates forConcrete”, ACI Education Bulletin E1-16, 2016.
[8] San Nicolas, R. V. R., Walkley, B., & van
Deventer, J. S. J., Fly Ash-Based Geopolymer
Chemistry and Behavior, Coal Combustion
Products, 2017, pp. 185-214.
[9] Githachuri, K., and Alexander, M. G., Durability
Performance Potential and Strength of Blended
Portland Limestone Cement Concrete, Cement
and Concrete Composites, Vol. 39, 2013, pp.
115-121.
[10] Tosun, K., Felekoğlu, B., Baradan, B., and Altun,
İ. A., Effects of Limestone Replacement Ratio on
the Sulfate Resistance of Portland Limestone
Cement Mortars Exposed to Extraordinary HighSulfate Concentrations, Construction and
Building Materials, Vol. 23, Issue 7, 2009, pp.
2534-2544.
[11] Tang, Z., Li, W., Ke, G., Zhou, J. L., and Tam,
V. W., Sulfate Attack Resistance of Sustainable
Concrete Incorporating Various Industrial Solid
Wastes, Journal of Cleaner Production, Vol. 218,
2019, pp. 810-822.
[12] Ghafoori, N., Diawara, H., and Beasley, S.,
Resistance to External Sodium Sulfate Attack for
Early-Opening-To-Traffic Portland Cement
Concrete, Cement and Concrete Composites,
Vol. 30, Issue 5, 2008, pp. 444-454

CONCLUSIONS
Durability performance measures the concrete
ability to resist the damaging effect of weathering,chemical attack and other deterioration process. In
this study, the effect of utilizing DLW as fineaggregates in durability performance of concrete wasinvestigated through examination of sorptivity andresistance to sulfate attack. Based on the finding of
this study the following conclusions were established.
Replacement of sand by DLW shows good
durability potential. In terms of sorptivity, it was
concluded that incorporating up to 60% DLW fineaggregates slightly improved the permeability ofconcrete. All DLW concretes has sorptivity values
less than 0.10 mm/s1/2, hence DLW concretes can beclassified an excellent quality concrete in terms ofsorptivity.
The reduced sorptivity of DLW concrete gives
way to the improvement of its resistance to sulfate
attack. In terms of expansion, significant decrease inlength change was observed in all DLW concrete ascompared to the control concrete. Similarly, all DLW
concretes showed lower mass change compared with
control concrete. With regards to compressive
strength loss, 20% DLW concrete retained acompressive strength higher than control concrete
while a slight reduction in compressive strength wasobserved in 40% and 60% DLW concrete. Generally,
it was inferred that DLW concrete has better sulfate
resistance than conventional concrete. This wasparticularly evident from the evaluation results oflength and mass change after immersion in sulfate
solution.
Hence, based on the test results it can beconcluded that dimension limestone waste (DLW)
can be used as sand replacement to produced concretewith improved durability performance, reduce
depletion of our non-replenishable aggregate deposits
and alleviate environmental problems associated with
DLW disposal. However, appropriate ratio of DLW
replacement must be considered in order to achieve
an optimum durability performance without any
detrimental effect on strength and workability.
SEM-EDX analysis of DLW concrete before andafter sulfate exposure is recommended to get an idea
about the reactive products formed due to exposure.
Furthermore, other durability parameters such as
chloride permeability, carbonation resistance andcorrosion resistance should also be investigated.
REFERENCES[1] Gallagher, L and Peduzzi, P., Sand andSustainability: Finding New Solutions for161

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

RECYCLING OF FISHERY WASTE AS PLANTING BASE POROUS
CONCRETE AIMED AT ACHIEVING CARBON NEUTRALITY

1

Ayane Yanaka1, Hidenori Yoshida2, Shinichiro Okazaki2, Yui Oyake2, Yoshihiro Suenaga2
Graduate School of Engineering, Kagawa University, Japan; 2 Faculty of Engineering and Design, Kagawa
University, Japan
ABSTRACTThe Paris Agreement was adopted as the international framework against global warming, and the global
movement to reduce greenhouse gas emissions is progressing. On the other hand, the final disposal amount will
be reduced to 13 million tons in 2025 with considering the situation of waste disposal in Japan. Concrete, which
is a typical recycled civil engineering material, is a very useful material for drastically reducing waste, while its
constituent material, cement, emits a large amount of CO2 in its manufacturing process. Additionally, due to theJapanese eating habits, a large amount of fishery waste including fish residues and shellfish are discharged.
Although these are recycled, only about 30% of them are recycled. In this study, because the hydroxyapatite cancontribute to reduction of the amount of cement and the plant growth promoted by phosphorus content, thehydroxyapatite produced from fish bones (Fishbone Powder, FbP), which is a fishery waste, is adopted as analternative material to cement of planting base porous concrete. In addition, from the viewpoints of various
physical properties (porosity, permeability and compressive strength), plant growth conditions and CO 2 emission
reduction, the potential of recycling FbP as a binder for planting base porous concrete is also examined. As theresult, CO2 emission of about 2.6 kg per 1 m3 of porous concrete can be reduced by using FbP as a binder forplanting base porous concrete. Additionally, the plant growth ability is also improved while the compressive
strength is maintained above 10 N/mm2.
Keywords: Carbon neutrality, FbP, recycling, planting base porous concrete, CO2 emission reduction

INTRODUCTION

of CO2 in its manufacturing process. In order toreduce the environmental load and CO2 emission,“Low-carbon concrete”, in which industrial waste andby-products such as fly ash, blast furnace slag andsilica fume instead of cement are used, is noticed [2].
In addition to the wastes mentioned above, due to theJapanese eating habits, approximately 3.86 million
tons of fishery waste, including fish residues such as
bony parts of fish and shellfish such as scallops andoysters excluding those discharged by households,
are discharged annually. Although these are recycled
into feed and fertilizer, only approximately 30% ofthem are recycled [3]. Against this background, inorder to reuse fish bones, which are discarded
drastically at fish farms and fisheries processing
plants, the hydroxyapatite produced from fish bones
was developed by some of the authors, and its use as
an adsorbent was proposed. In previous studies, theauthors have clarified that the hydroxyapatite
produced from fish bones has ability to adsorb forheavy metals such as zinc (Zn2+), cadmium (Cd2+),
mercury (Hg2+) and manganese (Mn2+), andradioactive substances such as strontium (Sr2+) in
solution [4][5]. However, the use of adsorbents alone
will not lead to a significant reduction in fishery
waste. Additionally, the main component ofhydroxyapatite produced from fish bones is calcium
phosphate containing phosphorus which is one of thethree major nutrients of plants.

The current global average temperature isapproximately 1°C higher than that before theindustrial revolution. In Japan, the averagetemperature in 2020 is the highest since records began
in 1898, and the global warming is still becoming
unstoppable. In response to serious global warming,“The Paris Agreement” was adopted as a new
initiative to replace the Kyoto Protocol in order toreduce greenhouse gas emissions after 2020 at the
21st Conference of Parties (COP21) to the United
Nations Framework Convention on Climate Change
which was held in Paris, 2015. The global movement
to achieve carbon neutrality is progressing with the
adoption of the agreement. In 2020, Japanese
government declared that “Greenhouse gas emissions
would be reduced to zero as a whole by 2050”. On theother hand, in Japan, the final disposal amount ofJapan will be reduced to 13 million tons in 2025 withconsidering the situation of waste disposal in recent
years [1]. As an effective means to reduce the amountof final disposal, construction wastes, industrial byproducts, general wastes (incinerated ash, moltenslag, etc.) and sewage sludge are used as recycledcivil engineering materials. Concrete, which is atypical recycled civil engineering material, is a very
useful material for drastically reducing waste, while
its constituent material, cement, emits a large amount162

SEE-Mie, Japan, Nov.10-12, 2022

Thus, in this study, because the hydroxyapatite
can contribute to the reduction of the amount of
cement and the plant growth promoted byphosphorus, the hydroxyapatite produced from fishbones (Fishbone Powder, FbP), which is a fishery
waste, is adopted as an alternative material to cementof planting base porous concrete. In addition, fromthe viewpoints of various physical properties(porosity, permeability and compressive strength),plant growth conditions and CO2 emission reduction,
the potential of recycling FbP as a binder for planting
base porous concrete is also examined.

amount of organic matter residues. Therefore, in thisstudy, CO2 emission in the manufacturing process of
FbP is almost zero, and the reduction of CO2 emissionin using FbP as a binder is calculated.
TEST METHOD
Mix design and test specimen preparation
Table 1 shows the mix proportions of porous
concrete in the test. The mix proportions are
determined with reference to the study by Nakamura
et al. [8]. The water-cement ratio is 25% and thetarget porosity is 26%. “BLANK” represents anordinary porous concrete (porous concrete without
FbP), and “FBP” represents porous concrete in which
FbP is mixed as a binder (1% replacement of cementmass). Ordinary Portland cement is used for cement,
No. 5 crushed stones of 13 mm to 20 mm in diameteris used for coarse aggregate, and polycarboxylic acidbased air entraining (AE) and water-reducing
admixture is used for chemical admixture. In
addition, 1% is added to the cement mass as AE water
reducing admixture. Cement, FbP and crushed stones
are mixed in a concrete mixer, and then water inwhich chemical admixture is dissolved is put into themixer. Then, the mixer is rotated to mix the materials.
After that, the materials are put into a cylindricalmold of 100 × 200 mm (diameter × height), and struck
with rods and wooden hammers at each time. The sizeof the sample for the grass growth test is 100 × 180
mm. Five specimens are prepared for each physicalproperty test and cured in water for 7 or 28 days. On
the other hand, four specimens are prepared for thegrass growth test and cured in water for 28 days.

FISHBONE POWDER (FbP)
Hydroxyapatite is one of the typical apatites, thatare a group of crystalline compounds with
M10(ZO4)6X2 as a basic composition, and is a basic
calcium phosphate represented by Ca10(PO4)6(OH)2
as chemical formula. The manufacturing method of
the hydroxyapatite produced from fish bones(Fishbone Powder: FbP, see Fig. 1) is as follows.
First, fish residues with organic matter adhering tofish bones are immersed and boiled in hightemperature water. Next, the organic matter residues
are removed from the fish residues by spraying highpressure water, and the fish bones from which organic
matter residues are removed are forced to dry at
200°C. After that, the fish bones are burned at 700900°C in a heating furnace, and the burned fish bones
are pulverized with a ball mill [6]. Here, in order tocalculate the reduction of CO2 emission in porous
concrete for planting base using FbP as a binder, it isnecessary to take into account CO2 emission in the
manufacturing process of FbP. However, Wada et al.
[7] report that the temperature for the combustion
reaction of the solid component (carbide) is 400540°C in the oxidative pyrolysis reaction of foodwaste such as carbohydrate, protein and fat. In otherwords, the temperature at which organic matter
residues are burned and CO2 is emitted is 400-540°C.
The organic matter residues, such as fish meat, areremoved from the fish bones in FbP production.
Additionally, even if a small amount of organic
matter residues adheres to the fish bones, the drying
temperature before burning is lower than the
combustion temperature at which the CO2 is emitted.
Furthermore, even though the fish bones are burned
at 700-900°C, CO2 is hardly emitted due to the small

Physical property test
The porosity, permeability and compressive
strength tests are conducted to confirm the physicalproperty of porous concrete in which FbP is mixed asa binder. Porous concrete used as a planting base in
the embankment is classified as “Strength emphasistype” or “Plant growth emphasis type”. The porosity
and strength for these two classifications aredifferent. In the test, referring to “Plant growthemphasis type” of porous concrete, 21-30% of
porosity, 2.5-5.0 cm/s of permeability, and 10 N/mm2
of compressive strength are set as target values. As areference to the report of the committee on the
Table 1 Mix proportions (kg/m3)
BinderG
A
C
FbP
BLANK 84
337
1547 3.37
FBP
84 337.63 3.37 1547 3.37
*W: Water, C: Cement, G: Coarse Aggregate, A:
Chemical admixture
W

Fig. 1 Fishbone Powder (FbP)
163

SEE-Mie, Japan, Nov.10-12, 2022[10], leaf length is measured at five places one perporous concrete specimen, and the average of fivemeasured length is defined as the leaf length in the
porous concrete specimen. The average of each leaf
length in four porous concrete specimens is adopted
as the test result for the whole case. In addition, thepH value of the soil cover and inside the porous
concrete is measured after the grass growth test
because it is considered that the soil pH value of theplanting base influences the growth of the plant [11].
The mixture of soil 1 to distilled water 2.5 is shaken
for 30 minutes. In the test, 6g of soil and 15mL of
distilled water are used. After then, the measured pHof the supernatant is defined as the pH of the test soil.

establishment of design and construction methods ofporous concrete of the Japan Concrete Institute [9],the porosity test is conducted according to thevolumetric method, and the constant head
permeability test is conducted. In addition, the upper
end surface of the specimen is covered with gypsum
in order to smooth the loading surface, and theuniaxial compression test is conducted in compliancewith the compressive strength test method of concrete(JIS A 1108).
Grass growth test
In order to examine the plant growth ability ofporous concrete in which FbP is mixed, a growth testof western grass is conducted on porous concrete
without FbP (BLANK) and porous concrete in which
FbP is mixed as a binder (FBP). The test period is 42
days from November 17 to December 29, 2021, andthe test is conducted in the vinyl greenhouse installed
outdoors. The cylindrical porous concrete of 100 ×180mm (diameter × height) is filled with peat moss inslurry type by a water-powder ratio of 1: 1 as theplanting base (see Fig. 2). Fig. 3 shows the crosssection of the planting base specimen. Since the test
period is winter season, the blend of cold-district typeturfgrass of Kentucky bluegrass, tall fescue, bent
grass and others are selected as the test plant. The peatmoss of 2 cm thickness is covered on the porous
concrete. In order to make the western grass uniform,
the seeds are added to the soil covering part at theratio of 1 g per one porous concrete. Water is supplied
once a day, around 11:00 a.m. after seeding. Leaf
length is measured once a week from 14 days after
seeding. Referring to the study by Tsukioka et al.

RESULT AND DISCUSSION
Results of physical property test
As the results of the porosity test, Fig. 4 and Fig.
5 show the total and continuous porosity,
respectively. The horizontal and vertical axes in Fig.
4 and Fig. 5 are the curing period and porosity of theporous concrete, respectively. Fig. 4 and Fig. 5 showthat the porosity of both BLANK and FBP are higher
than 26% of the target porosity in the design, and theporosity at 28 days of curing is above 21-30% of theapplication range for the plant growth emphasis type,
except for the BLANK of the continuous porosity.
According to Saito et al. [12], it is indicated that in
the porous concrete filled in the mold, the continuous
porosity in the vicinity of the mold increases, because
the filling property of coarse aggregate is deteriorated
near the form surface. It is considered that themeasured values exceed the target value due to thewall effect of the mold. On the other hand, Koshi etal. [13] state that the porosity is affected by the
specimen size, and the larger the aggregate size, thatthe larger the void size near the surface in contact withthe mold, and that the continuous existence of voids
also increases the porosity. In this study, the No. 5
crushed stones are selected to ensure suitable voidsfor the growth of plant roots in porous concrete.
However, the No. 5 crushed stones are slightly larger
than the specimen size of porous concrete. This is also
considered to be the cause of the actual porosity
exceeding the target one. In general, the porosity ofporous concrete tends to decrease as the curing days
pass because cement hydration products become
dense, while, the results obtained in the test differ
from the general tendency. Further investigation isneeded to obtain more detailed information on theporosity of porous concrete. Furthermore, the ratio of
the continuous voids to total voids is calculated andthe ratio of both BLANK and FBP exceeds 99%. It is
confirmed that most of the voids in those porous
concrete are continuous voids. It can be said that bothFig. 2 Planting base used in grass growth test

2cm

Soil cover(Peat moss)

18cm

Porous concrete
Peat moss

Nonwoven fabricFig. 3 Cross section of planting base specimen
164

SEE-Mie, Japan, Nov.10-12, 2022

maintained above 10 N/mm2 despite an increase inporosity as the curing period progresses. It isnecessary to examine the extent to which FbP
contributes to strength from the relationship between
the replacement ratio of FbP and the strength ofporous concrete by changing the replacement ratio of
FbP to cement mass.

BLANK and FBP are the porous concrete suitable forplant growth.
Fig. 6 shows the results of the permeability test.
The horizontal and vertical axes in Fig. 6 are thecuring period and permeability coefficient of theporous concrete, respectively. Fig. 6 shows that thepermeability coefficient in the test deviates from 2.55.0 cm/s of the target range, except for the BLANK
which is cured for 7 days. As with the porosity, it isconsidered that the results are due to the wall effect.
Additionally, the permeability coefficients of both
BLANK and FBP increase with the curing period.
The permeability coefficient is strongly affected by
the porosity. As the porosity in the test increases withthe curing period, the permeability coefficient is alsopresumed to increase.
Fig. 7 shows the results of the uniaxial
compression test. The horizontal and vertical axes inFig. 7 are the curing period and compressive strengthof the porous concrete, respectively. Fig. 7 shows thatboth BLANK and FBP are satisfied with 10 N/mm2of the target compressive strength, while thecompressive strength of FBP is slightly lower thanthat of BLANK. This may be attributed to the fact thatthe amount of cement in the FBP is less than in the
BLANK. In addition, the compressive strength of
BLANK decreases with the curing period. Since thecompressive strength is affected by the porosity aswith the permeability coefficient, it is presumed thatthe results are due to an increase in the porosity. On
the other hand, the compressive strength of FBP is

Results of grass growth test
The measurement result of the leaf length of grass
growth and the condition of each specimen at the endof grass growth test are shown in Fig. 8 and in Fig. 9,
respectively. The horizontal and vertical axes in Fig.
8 are the elapsed period and leaf length, respectively.
Fig. 8 shows that the leaf length of FBP is longer thanthat of BLANK consistently from the beginning to theend of the measurement of leaf length. In addition, thegrowth rate of leaf length in FBP is higher than thatin BLANK. FbP contains phosphorus that is one of
the three major nutrients of the plant. It is suggested
that the phosphorus in FbP mixed in the porous
concrete is supplied to it, which brings about apositive effect on the grass growth. It is necessary toanalyze the amount of phosphorus contained in thegrass growth test in which porous concretes mixed
with and without FbP as planting base so as toconfirm that the phosphorus in FbP is supplied toporous concrete. Additionally, Fig. 9 seems that FBP
is slightly superior to BLANK regarding the root
thickness, root length and root quantity of the grass
6.5

30.85

31.0
30.0
29.0

30.08

6.0

30.10

5.5

28.98

28.0

4.5

13.0

Compressive strength(N/mm2)

Continuous porosity (%)

BLANK
FBP

Fig. 6 Permeability test results

32.0

12.82

12.5

30.67
29.93

4.29

7
28
Curing period (day)Fig. 4 Porosity test results (Total porosity)

30.0

5.60

4.0

7
28
Curing period (day)

31.0

5.51

5.0

BLANK
FBP

27.0

6.17

Permeability coefficient(cm/s)

Total porosity (%)

32.0

12.0

29.80

11.68

11.5

29.0

28.71

28.0

11.0

7

Curing period (day)

10.86

10.5

BLANK
FBP

27.0

10.66

BLANK
FBP

10.0

7
28
Curing period (day)28

Fig. 7 Uniaxial compression test results

Fig. 5 Porosity test results (Continuous porosity)165

SEE-Mie, Japan, Nov.10-12, 2022

comparing BLANK and FBP. Yoneyama et al. [14]report that there is a proportional relationshipbetween the root mass of plant and the absorbed
amount of phosphorus. The growth of roots ispresumed to be promoted by the supply ofphosphorus contained in FbP. In the future, it isneeded to conduct the quantitative investigations suchas measurement of root dry mass.
The results of the pH value in the soil is listed inTable 2. Table 2 shows that the pH value in the coversoil of FBP is almost the same as that of BLANK. In
addition, there is only about 0.1% difference between
soil pH inside the void of BLANK and that of FBP.
The difference is a category of error. Calcium
phosphate, the main component of FbP, is fromneutral to weakly alkaline, and it is presumed that thesoil pH of BLANK and FBP is almost the same dueto the use of FbP. Yokozeki et al. [15] indicates that
there is a relatively high correlation between the soil
pH and the volume of plant growth, and that the lower
the pH, the better for plant growth. In order to further
improve the growth amount of plant, it is necessary to
5
4.37

Leaf Length (cm)

4.5

4.71

3.98

4.07

3.89

3.5

By applying FbP mixed in porous concrete to an
actual revetment, CO2 emission reduction is
calculated. Here, the Aizawa river embankment
repair work in Yamagata Prefecture [16] is referred.
CO2 emission in manufacturing FbP is notconsidered, as described in Chapter 2. By substituting
1% of FbP for cement mass, it is possible to reduce
cement content by 3.37 kg per 1 m3 of porous
concrete. According to the Japan Federation ofConstruction Contractors [17], roughly 770 kg of CO2
is emitted in the production per 1 ton of cement.
Compared with conventional porous concrete, CO2
emission by approximately 2.6 kg per 1 m3 of porous
concrete can be reduced when FbP is used as a binder.
The volume of the porous concrete used in the repair
work is estimated to be 900 m3 considering theconstruction scale and thickness of the embankment.
Thus, CO2 emission by approximately 2,335 kg canbe reduced. Saiki et al. [18] states that a gasoline
automobile emits 2.38 kg of CO2 per 1 L of gasoline.
Applying this to the repair work mentioned above, theamount of CO2 emission reduced by substituting
cement for FbP in porous concrete is equivalent to theamount of CO2 produced when about 981 L ofgasoline is consumed in a gasoline automobile. In thecase of the automobile which runs 20 km per 1 L ofgasoline, it can run approximately 19,620 km with
981 L of gasoline. This is equivalent to half a world’s circumference. Therefore, it is expected that the useof FbP as a binder for the planting base porous
concrete brings useful results toward achievingcarbon neutrality.

3.54
2.70

2.5
2

Calculation of CO2 emission reduction

3.87

4

3

4.55

examine a method of decreasing pH.

BLANK
FBP

2.41
14

21
28
35
Elapsed period (day)42

Fig. 8 Grass growth test results

CONCLUSIONSIn this study, the hydroxyapatite produced fromfish bones (Fishbone Powder, FbP), which is a fishery
waste, was focused on an alternative material to thecement of planting base porous concrete, and thepotential of recycling FbP as a binder for planting
base porous concrete was examined. The findings
obtained are as follows.
 Porous concrete in which FbP was mixed has thephysical properties required for “Plant growthemphasis porous concrete” used as a planting basein a revetment.
 The compressive strength of porous concrete inwhich FbP was mixed as a binder was lower thanthat of porous concrete without FbP. Although thecompressive strength of porous concrete without
FbP decreased with the curing period, that of theporous concrete in which FbP was mixed did notdecrease and was maintained above 10N/mm2.
 The leaf length of grass in the porous concrete in

Fig. 9 Planting base specimens at the end of grass
growth test (left: BLANK, right: FBP)
Table 2 Measuring soil pH value test results
Cover soil
Inside of concrete
Peat moss (Original)

BLANK
FBP
8.00
7.99
8.00
8.08
7.39
166

SEE-Mie, Japan, Nov.10-12, 2022

K., Hydroxyapatite produced from fish bone,
JP6351008B2, 2018-07-04.
[7] Wada Y., Norose Y., Iwabuchi K. and Taniguro
K., Pyrolysis Characteristics of Food Wastes,
Journal of the Japan Society of Material Cycles
and Waste Management, Vol. 22, No. 3, 2011, pp.
225-230.
[8] Nakamura K., Ishikawa Y., Yanagibashi K andAndo S., An Application of Porous Concrete to
the Bank of Reservoir, Concrete Journal, Vol. 43,
No. 4, 2005, pp. 41-45.
[9] Japan Concrete Institute, Report of the researchcommittee on the establishment of design andconstruction methods for porous concrete, 2003.
[10] Tsukioka S., Yonemoto T., Growth Experimentof the turf Grass Using the Vegetation TypeConcrete, Journal of the Japanese Society of
Irrigation,
Drainage
andReclamation
Engineering, Vol. 74, No. 2, 2006, pp. 127-130.
[11] Research Committee of Japanese Institute ofLandscape Architecture, Ground Maintenance
Manual in Landscape Planting, Journal of theJapanese Institute of Landscape Architecture, Vol.
63, No. 3, 2000, pp. 224-241.
[12] Saito T. and Demura K., INFLUENCE OF
WALL EFFECT OF MOLD FOR SPECIMENONVOIDSDISTRIBUTIONANDCOMPRESSIVE STRENGTH OF POROUS
CONCRETES, Cement Science and Concrete
Technology, Vol. 70, No. 1, 2016, pp. 290-296.
[13] Koshi T., Shimazaki I., Kunieda M. and Rokugo
K., Evaluation of Void Ratio and Void
Distribution of Porous Concrete, Proceedings of
the Japan Concrete Institute, Vol. 21, No. 1, 1990,
pp. 259-264.
[14] Yoneyama T., Horie H., Takebe M., Tanno F.,
Absorption of Phosphorus from Soil by Crops: II.
The Relationship between Root Mass andPhosphorus Absorption, Journal of the science ofsoil and manure, Japan, Vol. 61. No. 4, 1990, pp.
382-385.
[15] Yokozeki K., Torichigai T., Takayama H.,
Higuchi T., Study on Improving Plant Growth
Capacity of Porous Concrete, Proceedings of theJapan Concrete Institute, Vol. 35, No. 1, 2013, pp.
1405-1410.
[16] Japan Federation of Construction Contractors,
Towards Promoting of Low Carbon Concrete –Contributing to the Construction of a Low
Carbon and Recycling Oriented Society-, No.
0237, 2016

which FbP was mixed was longer than that inporous concrete without FbP. It is suggested that
phosphorus in the FbP mixed in the porous
concrete has a positive effect on the grass growth.
 CO2 emission by approximately 2.6 kg per 1 m3of porous concrete can be reduced by using FbP
as a binder. When porous concrete in which FbP
is mixed is applied to the Aizawa riverembankment repair work in Yamagata Prefecture,
it is expected to reduce CO2 emission byapproximately 2,335 kg.
In the future, in order to investigate the effect of
FbP on the strength of porous concrete, it is necessary
to examine the relationship between the replacement
rate of FbP to cement and its strength. Additionally,
it is needed to analyze the amount supplied ofphosphorus in the grass and measure the dry mass of
the leaves and roots of the grass so as to quantitatively
evaluate that FbP influences plant growth.
ACKNOWLEDGMENTS
This work has been supported by JSPS
KAKENHI Grant Number JP20K04684. Also, incarrying out this study, Nihon Kogyo Co., Ltd.
provided FbP. We express our gratitude here.
REFERENCES[1] Ministry of the Environment, Annual Report on
the Environment, the Sound Material - Cycle
Society and Biodiversity in Japan 2021, 2021, pp.
183-202.
[2] Kobayashi T., Ichise K. and Namiki K.,
Technical Report, Low Carbon Emission
Concrete “Crean-crete”, Report of Obayashi
Corporation Technology Research Institute, No.
80, 2016, pp. 1-4.
[3] Demura M., Current Status and Issues of Fishery
Waste Disposal –Focusing on the Recycling ofFish Residue-, Monthly review of agriculture,
forestry and fishery finance, Vol. 57, No. 11, SN.
705, 2004, pp. 666-680.
[4] Shibata K., Yoshida H., Matsumoto N. and
Suenaga Y., Study on adsorption ability ofhydroxyapatite for strontium in solutions,Japanese
GeotechnicalSociety
SpecialPublication, Vol. 14, No. 7, 2016, pp. 163-167,
DOI: 10.3208/jgssp.v04.j26.
[5] Shibata K., Yoshida H., Inoue T., Matsumoto N.
and Suenaga Y., STUDY ON ADSORPTIONPERFORMANCE OF FOOD WASTES FORVARIOUS HEAVY METALS, Vo. 16, Issue 55,
2019, pp. 46-52, DOI: 10.21660/2017.34.2661.
[6] Kagawa University, NIHON KOGYO CO., LTD.
Suenaga Y., Yoshida H., Honjo T., Tada K.,
Ichimi K., Matsuyama T., Kameyama T., Yamaji[17] Asano K. and Sato K., Construction of Cast-in-place
Porous Concrete, Proceedings of JCI Symposium on
Design, Construction and Recent Applications ofPorous Concrete, 2003, pp. 127-130.
[18] Saiki Y. and Nakazawa M., CO2 Emission from
Gasoline Vehicle of Running Mode, Journal of Japan
Society for Atmospheric Environment, Vol. 25, No. 4,
1990, pp. 287-293.

167

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXAMINATION OF SEDIMENT GRAIN-SIZE MEASUREMENT
AND CALUCULATION AT MULTIPLE POINTS ON THE
SANDBAR IN CLASS B RIVER
1,2,3

Yoshitaka Jiken1, Kazuya Watanabe2 and Noritoshi Saito3
Graduate School of Engineering Science, Akita University, Japan

ABSTRACTIn recent years, flood damage was occurring frequently by the flow rate of rivers has increased due to heavy
rains such as typhoons in Japan. Therefore, understanding the particle size distribution of riverbed materials wasan important factor in river planning and sediment outflow forecasting. However, in many cases, the grain size
considered in numerical calculations was only for the surface layer because collecting sediment heavy labor, andit has not been studied much in the depth direction. In this study, sediment was collected from multiple locations
on the sandbar in the middle reaches of the Babamegawa River, which was a Class B River in Akita Prefecture.
Then, the particle size analysis was performed in the cross-sectional and longitudinal directions. Sediment wascollected twice to see the change in grain size before and after the flood. At the results, the D50 of the sedimentcollected after the flood tended to be larger than that of the sediment collected before the flood in both the crosssectional and longitudinal directions. In the depth direction, it was confirmed a layer in which the particle sizechanges and a layer in which the particle size does not change.
Keywords: Babamegawa River, sandbar, particle size, diameter50, numerical calculation

INTRODUCTION

particle size have not been performed. Therefore,
numerical calculations were performed using particle
size distribution and exchange layer thickness
obtained from actual riverbed materials, and thecalculation results of uniform particle size and mixed
particle size were compared.

Flood damage caused by typhoons and heavy
rains has occurred frequently in Japan [1]. The
particle size distribution of riverbed materials in riverroads was also an important index from the viewpointof sediment management [2]. In addition, the average
particle size obtained from the particle size
distribution was also used for grasping thecharacteristics of rivers and river planning using
numerical calculations in recent years. The particle
size distribution of riverbed materials has been widely
carried out in past studies [3][4]. However, thecollection of sediment was a heavy labor, and it was
costly to use heavy machines [5]. Therefore, there
were many things related to the surface layer of theriverbed in consideration of the particle size. The
examination of the riverbed material in the deeper
point has not been done much. In this study, sediment
was collected from multiple locations on the sandbar
in the middle reaches of the Babamegawa River [6],which was a Class B River in Akita Prefecture. Then,the particle size analysis was performed in the crosssectional and longitudinal directions. Sediment wascollected twice to see the change in grain size before
and after the flood. In addition, the numericalcalculation of the studies using the middle basin of
the Babamegawa River as the calculation area was
reproduction calculation of the flow in which theroughness coefficient of Manning was changed
depending on the location [7], Study on the Behaviorof sandbar using UAV (Unmanned Aerial Vehicle)[8][9], but numerical calculations set for the mixed

RESERCH AREA
500km

Fig. 1

Study Area.

Fig. 1 was shown the Babamegawa River flowed
into the Sea of Japan and was the largest Class B The
calculation area was shown in Fig.2. It was
Babamegawa River at Hiranoshita area. The
calculated area was an extension of about 850 m
section of the Babamegawa River middle basin flat,
168

SEE-Mie, Japan, Nov.10-12, 2022

and the survey data of the river improvement work in2014 was used for the topographical condition. The
river width is about 40 m in all sections, and from theembankment to the riverbed was about 4 m. In thisstudy, in order to compare with the calculated result,three measuring lines (No.1~3) were determined asshown in Fig.2.
RESEARCH METHODSRiverbed Material Survey
Riverbed materials were collected from thesandbar indicated by the red frame in Fig.2(top). The
details of the collected point were shown below. Allseven stations(0~6) in Fig.2(bottom) were surveyed,
and the points collected in November, 2020 were St.0,
and the points collected in 2021 were St.1 to 6. St.1
to 3 were cross-sectional directions and St.4 to 6 werethe longitudinal directions.
Fig. 3 was shown the river discharge variation of
the Babamegawa River at the Kubo Observatory,
which is several kilometers downstream from thesurvey site, from August to November, 2021. A floodof river discharge over 40 m3/s has occurred twice
during that period. Sediment samples were collected
twice before and after the flood of river discharge 40
m3/s shown in Fig. 3
At seven sites, about 6,000 g of riverbed material
was collected from each layer, about 50 cm squarefrom four layers of surface layer, depth of 30 cm, 50
cm, and 70 cm. In addition, the collected earth andsediment was dried, and the sifting test was carriedout according to JIS A1204 [10] using about 4,000 g
as a sample.

Cross-sectional direction
longitudinal
direction

Particle Size Analysis Results and Discussions

Fig. 2

Aerial photograph by UAV(August, 2021).

Fig. 3

River discharge variation from August to
November, 2021.

Vertical Direction
Figs.4 and 5 were shown grain size accumulation
curve and the occupancy of the sample stopped ineach sieve of St.0 sediment. When the median
diameter(D50) of each hierarchy was compared, it
was about 13 to 14 mm in the range of 19 mm in thesurface layer and 30 to 70 cm deep. The peakoccupancy values were 9.5 to 26.5 mm. The grain size
accumulation curve of St.0 did not difference in thegrain size accumulation curve in the range of 30 to 70
cm deep. However, when the particle size addition
curve of the riverbed material collected in August to
November, 2021 is seen, the tendency by the depth
like St.0 were almost non-existent.
In addition, the thickness of the exchange layer
has not been formulated mechanically at present fromthe particle size distribution. Therefore, the grain size
accumulation curve in the middle basin changes
greatly depending on the time and position.

Fig. 4

169

Grain size accumulation curve at St.0.
(November, 2020).

SEE-Mie, Japan, Nov.10-12, 2022

Particle size Comparison before and after the Flood
Fig. 6 was shown D50 in the cross-sectional
direction of August and December, 2021. St.3 locatedon the shore showed a tendency to have a coarser
particle size in December than in August at a depth of
30 cm and 70 cm. The D50 of the sediment collectedin August ranged from 6.1 to 13.6 mm, regardless ofthe sampling point or depth. On the other hand, when
the sediment collected in December was compared,
st.1 was 6.9 to 9.5 mm, and St.2 and 3 were more than
10 mm. D50 after the flood tended to be larger than
before the flood. it was thought to be due to the floodof a river discharge of over 40 m3/s that occurred in
the second half of August and the first half ofNovember, and a small particle sediment flowed outof the sandbar. St.3 significantly increased particle
size change and became coarser. As a reason, since
the shore side was not flooded at normal times, it wasconsidered that more fine sediment was washed away
than other points.
Fig. 7 was shown D50 in the longitudinal
direction of August and December,2021. D50 inAugust was 5.0 to 13.0 mm regardless of the locationand depth of collection. On the other hand, D50 in
December showed st.4 was 8.1 to 10.0 mm, while St.2,
5 and 6 were 9.5 to 19.0 mm except for depth 50 cm.
D50 was bigger after the flood tendency to become
the same as the cross-sectional direction, but there
was no change as much as the cross-sectional
direction.
In the longitudinal direction, the grain size tended
to be coarse in the upper part of the sandbar and finein the middle and downstream areas in the Tamagawa
River of the Class A River[11].

Fig. 5 Occupancy of sediment at St.0.
(November, 2020).

right

left

Numerical Calculation
Calculation Model

Fig. 6 Cross-sectional direction in 2021(D50).

In this study, the two-dimensional calculation
model was used based on the past studies[7]-[9]. The
continuous equations and equations of motion used
this time were shown in equations (1) to (3).
𝜕ℎ 𝜕(ℎ𝑢) 𝜕(ℎ𝑣)
+
+
=𝑞+𝑟
𝜕𝑡
𝜕𝑥
𝜕𝑦
𝜕(𝑢ℎ)
𝜕𝑡
𝜕(𝑣ℎ)
𝜕𝑡

+
+

𝜕(ℎ𝑢 2 )𝜕𝑥
𝜕(ℎ𝑢𝑣)
𝜕𝑥++

𝜕(ℎ𝑢𝑣)𝜕𝑦𝜕(ℎ𝑣 2 )𝜕𝑦culvert, gutter, and pump per unit area, r was theamount of rain, g was the gravitational acceleration,
H was the water level, τx was the riverbed shear force
in the x direction, τy was the riverbed shear force inthe y direction, and ν was the density of water.

(1)
𝜕𝐻

𝜏

𝜕𝐻

𝜏

= −ℎ𝑔 𝜕𝑥 − 𝜌𝑥 + 𝐷 𝑥= −ℎ𝑔 𝜕𝑦 − 𝜌𝑦 + 𝐷 𝑦

Calculation Case
The typical particle size used for numericalcalculation of uniform particle size was generallyusing the central particle size D50 of the surface
layer. However, the difference was large between thepeak value of the occupancy and the D50, and theparticle size distribution of the surface layer wasdifferent depending on the collection time. In thisstudy, we used the particle size distribution obtained
numerical(2)(3)

Where h was the water depth, t was the flow
velocity in the x direction, v was the flow velocity inthe y direction, q was the amount of inflow by the170

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Particle size input patternpattern

Particle size
setting

particle size

Uniform
particle size

7.8 mm (2020/10 D50)
14.3 mm (2020/10
occupancy)
19.0 mm (2020/11 D50)
23.5 mm (2020/11
occupancy)

Mixedparticle size

Deep 50 cm（2020/11）

1
2
a

3
4

b

1

Table 2 Calculation conditions

downstream

Fig. 7

upstreamLongitudinal direction in 2021(D50).

Uniform
particle size

Mixedparticle size

Manning number

riverbed 0.03
other 0.04

riverbed 0.03
other 0.04

Time step

0.1s

30 cm

Sedimentary layer
Number of layer
thicknesses

40 cm
25

No.3
Upstream
Downstream

Fig. 80.1s

Exchange layer

Elevation change during peak river discharge.
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SEE-Mie, Japan, Nov.10-12, 2022

calculations of 5 patterns shown in Table 1 based on
the past study. The input particle size values used theD50 and occupancy peak values of the surface layerof sediment collected in October and November 2020.
Table 2 showed the calculation conditions. The
boundary conditions at the upstream end were 24
hour river discharge from 6:00 p.m. 24th to 6:00 p.m.
25th August, 2018 at the Observatory.
In this study, the longitudinal direction interval
was set to 5 m and the cross-sectional direction was
set to 10 divisions, and a computational lattice wascreated using a non-positive lattice.
Calculation Results and Discussions
Fig. 8 showed the change in the riverbed height at
the peak river discharge. The numeral was displayedfor each cell relative to the downstream end of thecalculation area. The red color of the figure shows
sedimentation and blue shows scour. When pattern awas compared as a whole, the larger the particle size,
the smaller the fluctuations in the riverbed. However,
the tendency of the scoring and deposition was
similar regardless of the particle size. On the other
hand, the amount of riverbed variation in pattern b
was smaller than that of pattern a. And sedimentation
was observed on the right bank of pattern a near theline, but no deposition was observed in pattern b.
The following meandering part where the flow
velocity difference occurred was examined by paying
attention. There was no difference visible from theflow velocity in numerical calculations of uniform
particle size and mixed particle size around the peakriver discharge (11 hours later). In addition, the riverdischarge was almost the same without approaching
the size of the particle size even if it was compared bynumerical calculation of uniform particle size. Only
the calculation result of the mixed particle size (b-1)
after 15 hours shown in Fig. 9 showed that the flow
velocity did not come out on the right bank of thedownstream end, and the tendency of the deposition
was able to be read.
Fig. 10 showed the calculation results of a-1, a-2,
and b-1 in No. 3 and the cross-sectional map of theresearch area. In the calculation result of pattern a, thescouring in the left bank was seen, while in pattern b,
The shape of the riverbed remains the same as theinitial state and the riverbed decreased overall.
When the survey results were seen, there was notendency of scouring and sedimentation, and it was
the same tendency as pattern b. Furthermore, when a1 and a-2 were compared, a-1 had a smaller particle
size, so the scoring and sedimentation were large.
In the case of numerical calculations in mixed
particle size, the entire riverbed sediment not only did
the Volume Conservation law hold, but also satisfies
the Volume Conservation rule in the soil and sand ofeach particle size hierarchy constituting the particle
size distribution. Therefore, in places where the

Velocity(m/s)
5Flow velocity (after 15 hours).

Fig. 91elevation(m)measured
initial
a-1
a-2
b-1

left

0
-1

right

-2
-3
-4
-5
0

Fig. 10

10

20
distance(m)3040Cross section map in No. 3

particle size distribution varies, such as in the middle
reaches of rivers, mixed particle size seems to havebeen able to reproduce the fluctuation tendency.

172

SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSIONSREFERENCES

In this study, riverbed material was collected fromthe middle basin of the Babamegawa River in theplane direction and the vertical direction, and theparticle size distribution was examined.
And numerical calculations were carried out at themixed particle size and uniform particle size using theobtained particle size distribution and exchange layer
thickness.
As a results of particle size analysis of riverbed
materials,⚫ There was no tendency due to depth at mostpoints, and the exchange layer could not be
considered. It was thought to be because theparticle size accumulation curve varies greatly
depending on the collection time and position.
⚫ Both the cross-sectional and longitudinal
directions tended to increase the D50 of the earthand sand collected after the flood than the earthand sand collected before the flood. It seems tobe due to the outflow of sediment with a small
particle size from the sandbar with the flood
flow rate of 40 m3/s.

[1] Japan Meteorological Agency, Ministry ofLand, <http://www.jma.go.jp/jma/index.html>(accessed on May 23, 2021).
[2] Harada D, Chibana T, and Agus SANTOSO.,

As a results of the numerical calculations on
sediment transfer at uniform particle size and mixed
particle size using local particle size,⚫ In the middle river basin, where the particle size
distribution varies, it seems that the mixed
particle size was able to reproduce thefluctuation tendency of the riverbed rather thanthe uniform particle size.
⚫ In the case of a uniform particle size assuming
all riverbed sediment as the same particle size,
the peak value of the occupancy is closer to thesetting condition than the D50 value, and it wasconsidered that it approaches the real
phenomenon as a result of calculation.

pp.59-63， (in Japanese)．
[6] Akita Prefecture. Class B River Babamegawa
River water system River maintenance basic
policy,<http://www.pref.akita.lg.jp/pages/arghiv
e/10601> (accessed on April 23, 2021).
[7] Hagiwara T, Aita S, and Kazama S., A study on
the variation calculation considering the particle
size in the Babamegawa River, Conference of
Tohoku Branch of Japan Society of Civil
Engineering, 2015(in Japanese) (CD-ROM).
[8] Taniguchi J, Watanabe K, Saito N, and Fujisawa
N., Study on the Behavior of Sandbar in a River
Channel at the Babamegawa River, 6th Int. Conf.
on Structure, Engineering & Environment (SEE),
2020, pp.149-154.
[9] Taniguchi J, Watanabe K, and Saito N., Study on
the Behavior of Sandbar in a River Channel at theBabamegawa River, International Journal of
GEOMATE, 2020 Vol.20, Issue 78, pp.115-120．
[10] JISA1204:2020<https://www.kikakurui.com/a1/
A1204-2020-01.html> (accessed on April 25,2021).
[11] Tadatsu T, Shimojo Y, Uchida T, Fukuoka S,
Particle size composition of sandbars in gravel
rivers and movement and deformation ofsandbars due to flood flows, Kanto Branch is oneof the Branches of JSCE, 2011,Ⅱ-26.

Characteristics of grain size distribution ofriverbed and their determining factors,
Proceedings of the Japan Society of Civil
Engineers Paper B2, Vol.73, No.4, I_931-I_936,
2017(in Japanese).
[3] Pan B, Pang H, Zhang D, Guan Q, Wang L, Li F,
Guan W, Cai A, and Sun X., Sediment grain-size
characteristics and its source implication in the
Ningxia–Inner Mongolia sections on the upper
reaches of the Yellow River, Geomorphology,
Volume 246, 2015, pp.255-262.
[4] Abeshu G W, Li H Y, Zhu Z, Tan Z, and Leung
L R., Median bed-material sediment particle size
across rivers in the contiguous US,Earth Syst. Sci.
Data, 14, 2022 pp.929-942,.
[5] Murakami M., Riverbed Material Survey,

Journal of the Japan Society of Erosion
Control Engineering, Vol.71, No.6, 2019,

In this study, the reproducibility of sediment
movement was qualitatively improved by calculating
at the mixed particle size, but it was considered that itis necessary to consider factors other than particle
size to quantitatively evaluate it in the future.
ACKNOWLEDGMENTS
This research was partially supported by the
Ministry of Education, Science, Sports and Culture,
Grant-in-Aid for Scientific Research (A), (20H00256,
So Kazama)

173

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

RESIDUAL STRUCTURAL CAPACITY EVALUATION OF BRIDGEPIERS AFFECTED BY THE LOCAL SCOURING WITH A WATERLEVEL FORCASTING MODEL USING MACHINE LEARNING
Ryosuke Takahashi1, Takuma Kadono2 and Shinichiro Okazaki3
Graduate School of Engineering, Kagawa University, Japan; 2Department of Creative Technology
Engineering, Course of Civil Engineering Lecturer, National Institute of Technology, Anan College, Japan;
3
Faculty of Creative Engineering Associate Professor, Kagawa University, Japan
1

ABSTRACTIn recent years, damage and subsequent destruction of bridge piers due to localized scouring has frequently
occurred in many parts of Japan as one of the most serious heavy rain disasters. To properly maintain and manage
infrastructures against such disasters, the residual capacity of piers affected by local scour should be evaluated todetermine the health of the piers, and preventive measures against local scour should be implemented after
assessing the risk caused by local scour. In this study, an evaluation method for the residual structural capacity ofpiers affected by localized scouring was proposed. The model is based on a machine-learning model for predicting
river water levels using effective rainfall as an explanatory variable, and a model for evaluating the residual
structural capacity of piers in response to fluctuations in river water levels and the development of local scour,using existing formulas for calculating pier bearing capacity.
Keywords: Machine learning, Effective rainfall, Prediction of river water level, Bridge pier, Evaluation of residual
structural capacity

INTRODUCTION

evaluating the soundness of local piers around piersthat fluctuate depending on rainfall conditions, etc. in
the future. In addition to proposing a model thatpredicts fluctuations in river water level, we also
propose a model that evaluates the residual strengthof piers according to the predicted river water level.

In recent years, damage to bridge piers due to the
local scouring and the resulting failures have becomefrequent in several parts of Japan, as one of the most
severe heavy rainfall disasters. Once this type ofdisaster occurs, it is necessary to limit the use ofbridges according to the situation and secure
evacuation routes for neighboring residents. In
addition, the "Paris Agreement" adopted by the
Conference of the Parties to the United Nations
Framework Convention on Climate Change (COP21)
states that the global average temperature rise should
be kept below 2 ° C as a long-term goal common to
the world. According to the Ministry of Land,
Infrastructure, Transport and Tourism's estimation,
when the temperature rises by 2 ° C, the rainfall
increases 1.1 times. Furthermore, focusing on therainfall and flow rates targeted in the current riverplanning, it is estimated that the frequency of floods
will double. In this way, although global efforts tocombat global warming have been clearly shown,further extreme heavy rainfall and associateddisasters are expected in Japan in the future.
Therefore, even in the case of a local pier scouring
disaster caused by heavy rain, it is necessary toestablish appropriate maintenance and methods andimplement rational disaster prevention measures.
Therefore, in this study, machine learning is usedfrom the observed meteorological information for the
purpose of constructing a method for quantitatively

MAIN ARTICLE
Predicting River Water Level using Machine
Learning
Study methods
Support vector regression (SVR) [1], which is oneof the machine learning algorithms suitable formultivariate nonlinear regression problems, is used toconstruct a river water level prediction model. The
objective variable was the future river water level ofriver X (basin area 155.5 km²) observed during themonth of July 2018 and was calculated from therainfall observed several hours ago in the catchment
area of the target river. The effective rainfall [2] [3][4] was used as the explanatory variable. The
explanatory variables [5] [6] used in the river waterlevel prediction model in previous studies generally
include the river water level. On the other hand, if theriver water level is used as an explanatory variable, apermanent water level gauge is required, which
requires a large cost. Therefore, we considered
whether it would be possible to predict the river water174

SEE-Mie, Japan, Nov.10-12, 2022

level using only rainfall information and focused on
the effective rainfall that can be calculated from thehourly rainfall.
Where, the effective rainfall is calculated by
reducing the influence of past rainfall on theoccurrence of sediment-related disasters with thepassage of time, and the calculation formulas are asshown in Eq. (1) and (2).

there is. The part where the non-linear relationshipremains is between 100 hours and 200 hours in Fig. 1
where the river water level is rising due to the heavy
rain in July 2018. It was confirmed that therelationship was non-linear.

𝒙

𝑹𝒕 = 𝒓𝒕 + ∑ 𝒂𝒏 𝒓𝒕−𝒏 = 𝒓𝒕 + 𝒂𝟏 𝒓𝒕−𝟏 + ⋯ + 𝒂𝒙 𝒓𝒕−𝒙 (𝟏)𝒏=𝟏𝒂𝒏 = 𝟎. 𝟓𝒏⁄𝑻

(2)

Where, Rt is the effective rainfall at time t, rt is thehourly rainfall at time t, an is the reduction coefficientn hours ago, rn is the hourly rainfall n hours ago, andT is the half-life. Rt approximately expresses theamount of water in the soil and indicates that thedecrease coefficient decreases with the passage oftime, resulting in the loss of water from the soil due
to runoff and evapotranspiration. By setting the limit
effective rainfall for the occurrence of slope failures
such as landslides, the risk of landslide disasters canbe evaluated from the evaluation of dangerous slopes
during heavy rains, and from the precipitation
including cumulative and regional characteristic dataof topography, geology, and land use. Evaluation is
being carried out. In the railway field in Japan,
effective rainfall with half-life of 1.5, 6, 24 and 72
hours is the standard for train operation regulation.
Fig. 1 shows the positional relationship map ofriver X and each observation site store. This is a plotof each observation point, etc. on the Geographical
Survey Institute map released by the Geospatial
Information Authority of Japan. Fig.2 shows the time
history of the effective rainfall calculated from theriver water level for one month in July 2018 observed
nearby Bridge A crossing River X and the actual
rainfall observed at the rainfall observatory located in
the catchment area of the river. The half-life ofeffective rainfall shown in the figure is calculated as
1.5 hours, 6 hours, 24 hours, and 72 hours, which is
the half-life mainly used in the risk assessment of
sediment-related disasters. This is for reference. Of
the half-lives shown in Fig. 2 , the outline of the halflife of 24 hours is considered to be the closest to theoutline of the time history of the river water level.
Next, Fig. 3 shows the relationship between theeffective rainfall and the river water level with a halflife of 24 hours. This uses the data observed at the
points in Fig. 1. The correlation coefficient r is also
shown in the figure. Focusing on the relationshipbetween effective rainfall and river water level shownin Fig. 3, the correlation coefficient r is 0.921, andthere is a strong positive correlation, and althoughsome non-linear relationships remain, the relationshipbetween the two is linear as a whole. It turns out that

Fig. 1 Positional relationship map of river X andeach observation site store

Fig. 2 Time history of the effective rainfall and theriver water level

Fig. 3 Relationship between the effective rainfall
and the river water level
When predicting the river water level, it isimportant to set the explanatory variables
appropriately. As shown in Table 1, we decided to set
up a case in which the effective rainfall range, which
is an explanatory variable, was changed, andexamined it.
175SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Consideration case of predicting the riverwater level
Explanatory variable

Case

Effective rainfall

Half-life

1

-12

2

-11,-123-10,-11,-12

4-9,-10,-11,-12

5-8,-9,-10,-11,-12

6-7,-8,-9,-10,-11,-12

7-6,-7-,8-,-9,-10,-11,-12

Additional study methods

8-5,-6,-7-,8-,-9,-10,-11,-12

In order to examine whether the constructed riverwater level prediction model can be applied to otherrivers, the same water level prediction was performed
for river Y (basin area 113.2 km²) and river Z (basin
area 60.2 km²). The positional relationship diagrams
are shown in Fig. 5 and Fig. 6. In addition, thesefigures are also plotted each observation point etc. on
the Geospatial Information Authority of Japan map
published by the Geospatial Information Authority ofJapan.

24

Fig. 4 Time history of water level prediction result(river X)

Note: The "-" notation in the table means to use theeffective rainfall n hours before the time you want topredict.
Study results
Table 2 shows the prediction results of the riverwater level. It was found that the coefficient ofdetermination became higher as the explanatory
variables were increased. The highest prediction
accuracy was obtained when the effective rainfall
calculated with the half-life of Case 8 as 24 hours wasused as the explanatory variable from 5 hours to 12hours before the time to be predicted. Fig.4 shows thetime history of the water level prediction results. The
continuity of the river water level was almost
reproduced, and the coefficient of determination was
0.927. Furthermore, the prediction error of the
maximum value of the river water level was 0.05 m,
and it was confirmed that the prediction accuracy was
sufficient even assuming that it would be used inpractice.
Table 2
level

Fig. 5 Positional relationship map of river Y andeach observation site store

The results of predicting the river water

Case

Predicted value (Maximum)

R²

1

2.30

0.554

2

2.46

0.701

3

2.91

0.777

4

3.09

0.830

5

3.19

0.867

6

3.36

0.889

7

3.41

0.908

8

3.43

0.927

Fig. 6 Positional relationship map of river Z andeach observation site store

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SEE-Mie, Japan, Nov.10-12, 2022

Additional study results
The prediction results are shown in Fig. 7 andFig. 8. For river Y, the fluctuation of the river waterlevel could be reproduced, and the coefficient ofdetermination was 0.973. In addition, the prediction
error of the maximum value is 0.05 m, which showsthat the prediction can be made with sufficientaccuracy for practical use. On the other hand, river Z
is considered to have been affected by the ebb andflow of the tide because the water level observation
point is located near the estuary (about 0.6 km
upstream from the estuary).

Fig. 9 Relationship between tide level and riverwater level
Evaluating Residual Structural Capacity ofBridge Piers
Study method
For the purpose of evaluating the safety of thepier with the progress of local scouring of the pier, thesafety is evaluated according to the predicted future
river water level. Fig. 10 shows a conceptual diagramof the action of the pier and the limit value. Where, hin the figure is the water level, Df is the effective
penetration depth, Rvd is the design vertical structural
capacity of the direct foundation (kN), Rhd is thedesign horizontal structural capacity of the direct
foundation (kN), and Mmd is the maximum design. It
is the resistance moment (kN ・ m). Rvd, Rhd, and Mmd
were calculated from Eq. (3) to (11) [7] [8].

Fig. 7 Time history of water level prediction result(river Y)

𝑅𝑣𝑑 = 𝑞𝑣𝑑 + ̅̅̅̅𝐷
𝛾𝑒2 𝑓 𝐴′

(3)

Where, qvd is the design vertical structural capacity ofthe direct foundation against increased load (kN / m2),
and A' is the effective area of the footing bottom
surface (m2). The effective area A' and the effective
width B' of the direct foundation were calculated by
the following Eq. (4) and (5).
Fig. 8 Time history of water level prediction result(river Z)
Therefore, the relationship between the tide level
and the river water level observed near the mouth ofriver Z is shown in Fig. 9, and when focusing on thefluctuation of the tide level and the river water level,
it is found that the cycle of the rise of the river waterlevel and the high tide are almost the same.
From these results, it was found that the proposed
river water level prediction model can predict theriver water level with sufficient accuracy in places
where the river water level fluctuates gently, such as
river X and river Y. On the other hand, it was foundthat it is necessary to add the tide level to the
explanatory variables in the place where the riverwater level is affected by the tide level, such as riverZ.

𝐴′ = 𝐵′ 𝐿(4)

𝐵′ = 𝐵 − 2𝑒𝑥(5)

Where, ex is the eccentricity (m) of the point of actionof the resultant force on the bottom of the footing andwas calculated by the following Eq. (6).
𝑀

𝑒𝑥 = 𝑉 𝑑𝑑(6)

Where, Md is the design moment (kN ・ m) acting on
the center of the footing bottom, and Vd is the design
effective vertical load acting on the footing bottom.
𝑅ℎ𝑑 = 𝑓𝑟𝑏 𝑅ℎ𝑏 + 𝑓𝑟𝑝 𝑅ℎ𝑝(7)

Where, Rhb is the horizontal structural capacity (kN)of the bottom surface of the footing, Rhp is thehorizontal structural capacity (kN) of the front surface
177

SEE-Mie, Japan, Nov.10-12, 2022of the footing, and frb and frp are the ground resistancecoefficients for the horizontal structural capacity. The
horizontal structural capacity Rhb on the bottom of thefooting and the horizontal structural capacity Rhp on
the front surface of the footing were calculated by thefollowing Eq. (8) and (9).
𝑅ℎ𝑏 = 𝑉𝑑 tan 𝛿𝑏

We decided to calculate the risk of subsidence,sliding, and tipping by varying the penetration depth
Df to the bottom of the footing, assuming the riverwater level. The degree of risk is defined as the ratioof the response value acting on the pier to the limit
value, and if this value is less than 1, the response
value is below the limit value, so it is safe, and if it
exceeds 1, the response value exceeds the limit value.
Therefore, it is judged to be dangerous.

(8)

Where, Vd is the design effective vertical load (kN)acting on the bottom of the footing, and δb is thefriction angle (degrees) between the bottom of thefooting and the support layer.
𝑅ℎ𝑝 = 𝛼ℎ 𝐿(∑ 𝑝𝑝𝑖 𝐻𝑖 cos 𝛿𝑝𝑖 )Study results
Fig. 11, Fig. 12, and Fig. 13 show the transition of
the degree of risk according to the fluctuation of theeffective embedding depth when the flow velocity is
assumed to be 5 m / s for each subsidence, sliding,and tipping. The figure shows the cases where theriver water level is 1m, 3m and 5m, and if the danger
level exceeds 1, it is judged to be dangerous. Fromthese results, in each case, the degree of risk decreases
as the effective rooting depth increases. It was foundthat the change in the degree of risk was relatively
small for sliding, and the effect on safety was small.
On the other hand, it was found that the risk ofsubsidence and falls increases as the effective rooting
depth decreases, which has a large effect on safety.
After obtaining the flow velocity of the river fromthe results of this calculation, the effective rooting
depth is reduced as the local scour progresses, and thecalculation is performed according to the water level
predicted by the examined river water level prediction
model. The degree of risk is calculated. In otherwords, it is possible to connect the judgment result of
whether the risk level exceeds 1 to the safety
evaluation of the pier.

(9)

Where, αh is the shape coefficient of the front surfaceof the footing, ppi is the passive soil pressure level (kN/ m2) of the front surface of the footing at the centerof the layer of interest, and δpi is the front surface ofthe footing and the soil in the layer of interest.
Friction angle (degrees). The passive soil pressure ppi
in front of the footing at the center of the layer ofinterest was calculated by the following Eq. (10).
𝛾
̅̅̅̅𝐻

𝑒𝑖 𝑖
𝑝𝑝𝑖 = (𝛾̅̅̅ℎ
) 𝐾𝑝𝑖 + 2𝑐𝑖 𝐾𝑝𝑖 1⁄2
𝑒𝑖 𝑖 +

2(10)

Where, ̅̅̅
𝛾𝑒𝑖 is the average effective unit volume
weight (kN / m3) above the section, hi is the effective
penetration depth to the upper surface of the layer ofinterest (m), and Hi is the layer of interest. Thickness(m), Kpi is the passive earth pressure coefficient in thelayer of interest, and ci is the degree of soil adhesion(kN / m2) of the layer of interest.
𝑀𝑚𝑑 =

𝐵V𝑑
2

𝑉2

− 2𝑞𝑑 𝐿𝑑(11)

Where, qd is the design vertical structural capacity(kN / m2) considering the effects of eccentricity andinclination.

Fig. 11 Transition of risk level according tofluctuation of effective rooting depth (subsidence)

Fig. 10

Conceptual diagram of piers
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SEE-Mie, Japan, Nov.10-12, 2022

determination was the total water level, which was
determined by moving the most.
In the evaluation of the residual strength of thepier, the degree of risk associated with the fluctuationof the effective embedding depth was calculated byexpressing the progress of local scouring by thedecrease of the effective embedding depth. As a result,it was found that it is possible to quantitatively
evaluate the decrease in the safety of piers due to theprogress of local scouring and the increase in riverwater level.
ACKNOWLEDGEMENTS
Fig. 12 Transition of risk level according tofluctuation of effective rooting depth (inclined)

This research was carried out by the Cabinet
Office's Strategic Innovation Creation Program"Disaster Prevention / Disaster Mitigation Function
Enhancement" (Representative: Yoshiyuki Kaneda).
We would like to express our gratitude here.
REFERENCES[1] Koji Tsuda, What is a support vector machine,
Journal of the Institute of Electronics, Information
and Communication Engineers, Vol.83, 2020,
pp.460-466.
[2] Naomasa Honda, A Study on Setting the Half-Lifein Effective Rainfall as a Debris Flow Generation
Criteria, JSCE Proceedings B1 (HydraulicEngineering), Vol.73, No.4, 2017 pp.I_247-I_252.
[3] Shiro Hayashi and Takashi Yamada, Regarding
the characteristics of the effective rainfall
coefficient in recent sediment-related disasters,
Journal of Japan Society of Erosion Control,
Vol.66, No.2, 2013, pp.31-39.
[4] Takuya Takeda, Haruka Tokuda, Toshiyuki
Oyama, and Shigeru Koyama, Risk assessment of
sediment-related disasters using effective rainfall
and regional information, JSCE Proceedings F6(Safety Issues), Vol.69, No.2, 2013, pp.1_811_86.
[5] Masayuki Hitokoto, Masaaki Sakuraba, andYuichi Kiyoichi, Development of River Water
Level Prediction Method Using Deep Learning,
JSCE Proceedings B1 (Water Engineering),
Vol.72, No_4, 2016, pp. 1_187-1_192.
[6] Masayuki Hitokoto and Masaaki Sakuraba,
Hybrid river water level prediction method
combining deep neural network and distributedmodel,
JSCE
Proceedings
B1(WaterEngineering), Vol.73, No.1, 2017, pp.22-33.
[7] Railway Technical Research Institute, DesignStandards for Railway Structures andExplanations: Basic Structures, 2012, pp148-155.
[8] Railway Technical Research Institute, DesignStandards for Railway Structures andExplanations: Concrete Structures, 2004, pp55-58.

Fig. 13 Transition of risk level according tofluctuation of effective rooting depth (fall down)
From these results, it was shown that the residual
strength of the pier can be calculated from thepredicted future river water level and the safety canbe evaluated. It was confirmed that the greater the
local scour depth of the pier, the greater the risk level,leading to the judgment of danger. For this reason, if
any one of the three items shown in the figure exceeds
1, it is necessary to restrict the use of railway bridges
and road bridges and to reinforce the riverbed.
CONCLUSION
In this study, we used SVR, which is one of themachine learning algorithms, and created a riverwater level prediction model using effective rainfall
as an explanatory variable. Therefore, it was shownthat the structural capacity of the pier can becalculated from the predicted future river water level
and the safety evaluation can be carried out.
The water level prediction model was possible,
and the coefficient of determination was thecoefficient of determination for the overwater level at
the moment of land rainfall. The coefficient of179

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

TIME, STRESS AND STRAIN DEPENDENCY OF PILE STIFFNESS:
IMPACT ON PILE BEHAVIOR AND STATIC PILE LOADING TESTSRESULTS
Fabien Szymkiewicz1, Wassim Mohamad1, Nader Elayni1 and Carlos Minatchy1
1
Université Gustave Eiffel, France

ABSTRACT
Static pile loading tests are carried out for different purposes: feed extended databases from which design
bearing capacity of piles are derived, control the design, develop new piling methods, but also in some cases
better understand the behaviour of a deep foundation submitted to additional solicitations such as temperature
variations, in the case of geothermal foundations systems. These tests are conducted on any type of piles,
themselves made from very different materials. For cast-in-place piles made of a combination of cementitious
materials (either cement paste, mortar or concrete for example) and steel, the stiffness of the pile is acombination of the stiffnesses of the different materials. Furthermore, cementitious materials are well known tobe evolutive materials, especially regarding their strength. By contrast, the strain-, stress- and time- dependencyof the stiffness of the cementitious materials and therefore of the cast-in-place piles is not so well known, andtherefore generally not taken into account when analysing static pile loading tests. The aim of this publication is
to impart the importance of the evolution of pile stiffness with time and under stress, through different practicalexamples, and comparisons are made with results obtained with more classical analysis methods.
Keywords: deep foundations, time-dependency, stress-dependency, stiffness, pile load tests

solicitation, with very small deformations achieved
through one or multiple loading cycles [6].
Furthermore, the formulation of the concrete has
to be taken into account. Following Eq. (1), it ispossible to estimate the concrete modulus from its
uncompressive strength (Eurocode 2):

INTRODUCTION
Determination of the bearing capacity is the main
purpose of a static load test carried out up to thefailure, in which case the test is called a conformity
test. However, another purpose can be the study ofthe behavior of the pile under a certain load, usually
under SLS load, or slightly higher. Some tests,
called control tests, are carried out on the express
purpose of assessing the settlement under this load.
Furthermore, piles are often instrumented,
whether it be to determine the load distribution
along the shaft or to study their behavior underparticular conditions such as the boring of a tunnel
nearby [1] or a thermal loading [2].
Therefore, to be able to evaluate the evolution of
the loads at different depth, as well as to be able topredict the settlement of a pile in any given situation,
it is necessary to know its stiffness under any levelof stress [3].
This stiffness can be in a first approach assumed
to be equal to 20 GPa for a short term solicitations or
10 GPa for long term behavior [4].
However, concrete is a non-linear elastoplastic
material, its execution conditions affect its
homogneneity. Results achieved on cored samples
shows the great variability of the modulus of pileconcrete [5]It is also important to keep in mind that moduli
determined in laboratory are often determined using
a test method non representative of the pile

=

(

/

) ,

(1)
However, it is also necessary to take into accountthe reinforcing steel bars of the cage inside the pile.
The French standard NF P 94-150-1 [7] proposes theequivalent modulus method, taking into account themodulus of each material in the pile as well as theirrespective cross sectional area. This method is
however often non-representative of the stiffness ofthe pile. Indeed, and as stated before in the case ofcored samples, the values of the concrete modulus
are given for a unique strain level, generally verysmall, leading to modulus values higher than inreality and, if used as it is, to incorrectinterpretations.
This paper focuses on the stress, strain and timedependency of pile stiffness: it presents several
examples highlighting the importance of theadequate consideration of the stiffness variability fora correct exploitation of the results of a static load
test, as well as the assessment of a pile behavior.

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SEE-Mie, Japan, Nov.10-12, 2022

calculations carried out with a pile stiffness kept
constant along a pile, realized in a multi-layered soil,
but ranging for 20 to 50 GPa. It is clear that while
the impact on the bearing capacity of the pile is null,as the overall shape of the curve is minimally
impacted, it is on the contrary of the upmost
importance around the SLS load.
On this example, the SLS load of the pile, which
would be in part defined as a fraction of the bearing
capacity and by the tolerated displacement of thestructure, would vary from 3800 kN to 5300 kN.

STRESS AND STRAIN DEPENDENCY OF
PILE STIFFNESSDesign Calculations
Taking into account the evolution of the pile
stiffness in relation to the level of stress (or strain)
has a big impact on the theoretical loaddisplacement curve.
Indeed, Fig. 1 shows the results of multiple

Fig. 1

Load-settlement curves for a same pile with different modulus (with a focus on the first part of thecurve)
behavior. However, it can be seen on Fig. 2 that thedifference at the base is negligible, while for thelayers above, and more importantly for the first layer,
it may be important in some cases to have thisinformation in mind.
On Fig. 2c and Fig.2e, which represent
mobilization of the shaft friction under its SLS load,
it is possible to note that the difference, in terms ofmobilization of qs, can go as high as 20 kPa, in thisparticular case, which is approximately 10% of theqs;max.
Regarding the base resistance, under the SLS
load, the effect of the modulus is negligible, as thebase is barely solicited. Furthermore, from Fig. 2b, it
can be concluded that the mobilization of qb isbarely impacted by a change in modulus. This canbe explained by the fact that the friction of the firstlayers is fully mobilized approximately when thebase
beginstobereallysolicited.

Furthermore, it is interesting to look at thetheoretical mechanism of load distribution.
Mobilization of the unit shaft friction qs and basepressure qb depends on displacement, which is dueto the settlement of the pile as well as thedeformation of the shaft.
The order of mobilization of the layers
resistances also depends on the pile stiffness. Goingon with the same example as before, it is clear that ahigher modulus will imply a faster solicitation of the
deep layers and of the base resistance, while thesurface layers will not be solicited at first. This isdue to the fact that with a shaft being stiffer, theshaft does not strain enough to allow for themobilization of the qs. Figure 2 clearly shows thistrend. It is important to note that the shape of thecurves is due to the shape of the t-z curves.
Of course, each geotechnical model is different,so that it is difficult to generalize the impact of this181

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 2abcd

Mobilization of qs (a) and qb (b) in function of the load applied at the head, and mobilization of qs infunction of the depth ((c) and (d)), depending on the pile stiffness
From what has been said above, it is clear that it
is of the upmost importance to take into account thestrain-dependency of pile stiffness. This is a crucial
point when calculating the pile load-displacement
curve. However, it is not so true when trying toassess the actual mobilization of unit shaft friction
for each layer, as seen above, and even more as thedispersion of this value is quite large. Thisvariability alone has a bigger impact on theincertitude of the mobilization of the friction along
the shaft than the incertitude caused by the choice ofthe modulus.

Finally, Fig. 3 shows the distribution of the axial
load along the pile, under SLS load. The differenceof pile stiffness between a very stiff pile (50 GPa)
and a soft pile (20 GPa) results in a change of load
distribution, as expected from the Fig. 3. However,this difference is not so pronounced, with amaximum difference load at any given depth lessthan 400 kN, or 8% of the load applied at the pile
head.

Pile Load Tests Analysis

Fig. 3As stated in the introduction, determination of
the pile stiffness through laboratory tests achievedon cored samples is not representative of the actual
stiffness of the pile: neither the level of stress nor the
representativity of the material is pertinent in thiscase.
Therefore, it is mandatory to take into accountthe strain-dependency of the modulus to analyze thedata of the strain gauges (or assimilated) used during
a pile load test. To do so, multiple authors proposed
different methods, summarized by Lam and Jefferis(2011). Of these methods, the one proposed by

Axial load distribution in a pile under SLS
load, in function of its stiffness.

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SEE-Mie, Japan, Nov.10-12, 2022

Fellenius (2001) seems one of the most commonly
used.
However, a simpler method would be to use, thefirst level of strain gauges to assess the stiffness ofthe pile, in function of the applied load. Then,knowing the cross sectional area of the pile, themodulus can be easily estimated.
Figure 4 shows the evolution of the modulus
derived from the strains measurements at the pile
head, for four similar piles, realized on the same site,with the same machine and the same concrete
formulation. The discrepancy in the results implies
that it is necessary to carry out this study every timea pile is tested, even on if multiple piles are tested on
the same site.
The purpose of an instrumented pile load test is
mainly to differentiate the shaft resistance from thebase resistance: therefore, an accurate estimation of
the load distribution along the shaft is needed. The
loads at different depths are derived from the strains
measurements at each level, and from the strain
measured at the pile head, as stated above.

Fig. 4

Continuing to use the pile example first used on
Fig. 1, Fig. 5a shows the differences in terms ofaxial load distribution caused by the choice of pile
stiffness. The most accurate hypothesis is to use astrain-dependent modulus to derive the axial load ateach strain level: the evolution of the modulus canbe established by segments or using a polynomial fit
curve that relates the modulus to the strain level.

aFig. 5

Evolution of strains and modulus duringload test for four similar piles realized on
the same siteb

Axial load distribution in two piles: comparison between calculated values and measured values, withdifferent choices of pile stiffness under SLS load (a) and at failure (b)Figure 5 shows a clear difference between theuse of a modulus equal to 30 GPa (a common
practice) and the adaptation of the modulus value infunction of the depth (and therefore the stain level).
While, under SLS load, the main difference isobserved along the shaft, with almost no difference
for the base pressure (as it should be, as SLS load isonly a fraction of the bearing capacity), at failure,
the differences are much more notable, with the basepressure being impacted too, by the modulus choice.
Differences can amount for more than 1 MN at
certain depths, with the solution of using a constantmodulus of 30 GPa clearly over-estimating the baseresistance as well as the shaft friction at the deeper
levels,andtherefore
overestimating
andunderestimating qs values by as much as 35%.
It is therefore of the upmost importance toanalyse the data of a pile load test, having in mind
the strain dependency of the pile stiffness.
Other factors related to this issue should also betaken into account, such as the age of the pile at thedate of the test or the formulation of the concrete of
the test pile, as the cementitious materials are getting
stiffer as days goes by, and performing a test on sucha pile at a young age or with a formulation different
from the formulation which will be used during theactual project could lead to the overestimation of thepile head displacement, and could therefore lead to
overdesign of the piles for a project.
The example showed on Fig. 1 can also be
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SEE-Mie, Japan, Nov.10-12, 2022

scrutinized on from the ‘time’ point of view, as it
relates in some way to the hardening process of theconcrete.
TIME DEPENDENCY OF PILE STIFFNESSCreep Strains
As stated above, concrete, as well as othercementitious materials, is an evolutive material that
hardens with time, up to a point.
Another important point to take into account isalso creep, or time dependent deformation.
As piles are subjected to creep, the calculation of
their deformation, and therefore of their settlement,
shall take into account this phenomenon. This ispartly done, for example in France, where the longterm modulus of a pile should be considered equal to
10 GPa, as stated above.
A pile was subjected to a constant loading(equivalent to the SLS load) for more than 4 months,
and strains at different levels were monitored (Fig.
6). The pile was loaded gradually, with load steps ofequal magnitude. An automated hydraulic pump
kept the load constant on top of the pile. Slightvariations were caused by the differences intemperatures, which impacted the pump as well as
the load cell.
It can be seen on Fig. 6 that the strains neverstopped increasing, whether at the levels close to thesurface or more in depth. However, the rate of strain
was different, depending on the depth: the lower thelevel, the slower the rate of creep

Fig. 6

Therefore, at the end of the four months loading
period, it was seen that the pile had been subjected
to creep, with a maximum accumulation of strains of
100 µm/m at the pile head (Fig. 7a).
For the lowest levels, the creep strains weremuch lower, as they were subjected to smaller loads.
Therefore, it seems that the creep strains were verymuch dependent on the load level.
However, when looking at Fig. 7b, which
represent the ratio between creep strains andinstantaneous strains, it is clear that the creep is
independent from the load level, as all the strain
gauges (here vibrating wires) recorded the sameratio creep strains over instantaneous strains. Thisratio is on average equal to twenty percent.
The two lowest levels present somewhat
abnormal values because of the low level of strain
they recorded to begin with: a slight variation of thestrain measurement creates a larger than reallymeasured ratio.

aFig. 7

Strains in function of time, for a pile loaded
under SLS loadbcreep strains (a) and creep strain / instantaneous strain ratio at different levels, for a pile under SLS loadfor 4 months
Pile Stiffness Adaptation

From these measures, it is clear that the impact
on the way to analyze the data for long-term pile
monitoring has to be adjusted.

Figure 8 shows the initial axial load distribution
along the pile, as well as the calculated distribution
after four months of loading, using the initial184

SEE-Mie, Japan, Nov.10-12, 2022

mandatory, as values given in the codes are default
values, not taking into account the exact formulationof the cementitious material as well as the overall
context (soil humidity, execution conditions, etc.).
Therefore, it was shown it this publication that
this is of particular importance when deriving loads
from strains.
However, it is not so important for design studies
such as the distribution of loads along the shaft
under SLS load, for example, as other variables aremuch more impacting. Also, while estimating themodulus of the pile precisely is very important forthe prediction of the load-settlement curve, it is notmandatory to take into account its strain-dependency.
Finally, for long-term studies of a pile behavior,
the time dependency of the pile stiffness shall betaken account and studied in details.

modulus of the pile.

Fig. 8

Axial load distribution just after loading
and after four months of loading

REFERENCES
Looking at the new distribution, it seems obviousthat the pile stiffness needed an adjustment, so as tofit with the initial distribution. Indeed, as creep
occurs, strains are increasing while the applied loadstays the same. Therefore, it means that the pile
stiffness has to be decreased to keep the axial load
distribution along the shaft constant, as the pile was
not subjected to any other solicitations.
Creep strains over instantaneous strains ratio
being fairly constant along the length of the pile, it isclear that the degradation of the pile stiffness mustalso be of the same magnitude, at every levels.
This is in accordance with the Eurocodes [8],which states that creep should be taken into account,and that creep is depending on the ambient humidity,
the dimensions of the concrete element considered,
the age at the moment of the loading and the type of
cement.
For long term considerations, creep strains equal
two times instantaneous strains, meaning that thepile stiffness must be degraded by a factor of three.
Incidentally, in this study, it can be seen that aloading of a pile for four months does not represent
at all a long term behavior of the pile, creep strains
only equaling for 20% of the instantaneous strains.

[1] Mohamad, W.; Bourgeois, E.; Le Kouby, A.;
Szymkiewicz, F.; Michalski, A.; Branque, D.;
Berthoz, N.; Soyez, L.; Kreziak, C. Full scale
study of pile response to EPBS tunnelling on a
Grand Paris Express site. Tunnelling andUnderground Space Technology. Vol. 124, 2022
[2] Bourne-Webb, P. J.; Amatya, B.; Soga, K.; Amis,T.; Davidson, C. and Payne, P. Energy pile test at
Lambeth College, London: geotechnical andthermodynamic aspects of pile response to heat
cycles. Géotechnique 59:3, 2009, pp.237-248[3] Lam, C. and Jefferis, S.A.. Critical assessment ofpile modulus determination methods, Canadian
Geotechnical Journal, 48, 2011, pp.1433-1448.
[4] AFNOR. NF P94-262: Justification of
geotechnical work - National application
standards for the implementation of Eurocode 7 Deep foundations, 2012, design standard.
[5] Szymkiewicz, F.; Sanagawa, T.; Nishioka, H.
and Le Kouby, A. Feedback on static axial pileload tests for better planning and analysis, 2021,
Proceedings of the Second International
Conference on Press-in Engineering, Japan.
[6] AFNOR, NF EN 12390-13: Testing hardened
concrete - Part 13 : determination of secant
modulus of elasticity in compression, 2021, test
standard.
[7] AFNOR. NF P94-150-1: Essai statique de pieu
isolé sous effort axial en compression, 1999, test
standard.
[8] AFNOR. NF EN 1992-1-1. Design of concrete
structures Part 1-1: General rules and rules forbuildings, 2005, design standard.

CONCLUSIONS
Static pile load tests are expensive, long tests, theresults of which can considerably impact the designof the foundations of a structure or building.
Because of these high stakes, it is a priority toplan thoroughly these tests, and to carry them out inthe best conditions, but also to analyze the data inthe best possible way.
Taking into account the strain dependency of thematerial constitutive of the pile is therefore

185

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

A STUDY ON THE PROPERTIES OF CONCRETE WITH FLY ASH
AND GARBAGE MOLTEN SLAG FINE AGGREGATE
Zihao Liu1, Koji Takasu1, Hidehiro Koyamada1, and Hiroki Suyama1
Dept. of Architecture, Faculty of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino
Wakamatsu, Kitakyushu, Fukuoka 8080135, Japan

ABSTRACTThis experiment investigated the properties of fly ash concrete replacing sand with garbage molten slag fineaggregate. The time development of compressive strength, elastic modulus, drying shrinkage, creep and pore
structure were tested. The relationship between pore structure and compressive strength, relationship between pore
structure and drying shrinkage were analyzed. A total of 4 mixes of concrete were prepared: the control concrete,
one mix including cement replaced with fly ash (30% by strength contribution rate), two mixes including sandreplaced with garbage molten slag fine aggregate (25%, and 50% by volume). The experimental results showedthat by replacing cement with fly ash according to the strength contribution rate, the early strength (7d, 28d) ofconcrete not decreased, and the 91-day strength increased. Incorporation of recycled fines reduced drying
shrinkage and creep. The pore volume in the range of 0.003 ㎛ to 0.1 ㎛ is considered to have a large effect on thedrying shrinkage of concrete.
Keywords: Fly ash, Garbage Molten Slag, creep, Drying shrinkage, Pore structure

INTRODUCTION

garbage molten slag and fly ash.

With the rapid development of industrialization
and urbanization, concrete was widely used in theconstruction industry, around 10 billion cubic meterof concrete was used every year [1], aggregate
accounts for about 60% to 80% of the concrete
volume [2]. As a result, a large amount of natural
aggregate is consumed [3]. In 2012, the amount of
direct incineration of general waste in Japan was
33.99 million tons per year, of which 12.35 million
tons, or 36%, was melted to produce 790,000 tons ofmolten slag. The manufactured molten slag is used as
road aggregate, concrete aggregate, ground
improvement material, and the like. The garbage
molten slag (GMS) generated from the melting
facility for general waste is being effectively usedfrom the viewpoint of recycling and quality stability,
but the utilization rate as an aggregate for concrete iscurrently low. Therefore, with the aim of increasing
the amount of molten slag used, it is necessary toconsider a formulation that exhibits the same
performance as when using natural aggregate. In
another hand, the world produces about 900 million
tons of fly ash every year, of which only about 53.5%
is effectively utilized [4]. Many scholars have studied
the properties of fly ash concrete, pointing out that theapplication of fly ash can improve the working
performance of concrete, improve durability, reduceshrinkage, and improve the microscopic pore
structure [5-9]. However, the research on the effect of
fly ash on concrete containing recycled aggregate is
not enough. Therefore, in this study, we evaluated the
durability of concrete with different mixing ratios of

MATERIALS AND EXPERIMENT METHOD
Materials and mix proportion
Table 1 shows the physical properties of thematerials used in this experiment. As the cement,
ordinary Portland cement was used, sea sand andgarbage molten slag were used as fine aggregate, andcrushed stone was used as coarse aggregate. Fly ashcorresponding to Class II in JIS A 6201. Table 2
shows the mix proportions, and the unit water volume
was 170 kg / m3, the water-binder ratio was 45.5% for
the control concrete, and 52.3% for the concrete withfly ash. Keep the compressive strength of concrete at
28d remain the same as the control group, cement
replaced with fly ash (30% by strength contributionrate). In addition, the unit coarse aggregate bulk
volume was set to 0.5 m3 / m3 to make it a highfluidity concrete, target air volume is 5.0 ± 1%.
Experiment method
Measurement items are compressive strength, drying
shrinkage and creep properties. The compressive
strength test was conducted according to JIS A 1108,
the drying shrinkage test was conducted according to“Method of measurement for length change of mortar
and concrete” of JIS A1129-2, and 100 × 100
×400mm prismatic specimens were produced. Aftercasting, they were demolded at 1 day of age, thencured in water at 20 ° C for 7 days or in a constanttemperature room with a temperature of 20 ° C and a186

SEE-Mie, Japan, Nov.10-12, 2022

humidity of 60%. Specimens were taken out of thewater at 7 days of age, and a stainless-steel chip was
attached to both end faces of the specimens, and thenboth end faces were sealed to measure the base length.
The specimens for measuring the drying shrinkage
were cured in a constant temperature and humidity
room with a temperature of 20 ± 1.0 ° C and a relative
humidity of 60 ± 5%. In the creep test, the strain wasmeasured according to JIS A 1157 “Method of test forcompressive creep of concrete”. This constanttemperature room could not strictly control the initial
one-month humidity. The creep test uses a loading
device of a separate type of hydraulic jack. Three test
specimens were stacked vertically. The loading load
was set to 1/3 of the maximum load of compressive
strength at 28 days, and loading started from 28 days.
Three strain gauges were attached to three places in
the center of the test specimen, and the average valueof the three strain gauges was taken as the total
measured strain of the test specimen. And the averagevalue of three test specimens was taken as the totalstrain of the mix proportion. In order to calculate thecreep strain, measuring the no-load strain by preparing
two pieces no-load specimen of Φ100 x 200 mm in eachmix proportion similar to the creep test, attaching thestrain gauges, and storing in a constant temperatureroom where the creep test is performed, and themeasurement was performed with a data logger
simultaneously with creep strain.

hydration reaction was stopped by immersion in
acetone, and vacuum drying for 72 hours, then thesample was used. The measurement was performed
with a mercury intrusion porosimeter (MIP).
RESULTS AND DISCUSSION
Compressive strength
Figure 1 shows the results of compressive strength.
At 7 days of age (in water), the higher the substitution
rate of both FA and garbage molten slag, the lower
the compressive strength tends to be, but at 28 daysof age (in water), FA0-0, FA30-0, FA30-25
compressive strength showed similar values.
Therefore, it can be said that the strength contribution
rate of 30% by compounding was appropriate. FA300 has the largest increase in strength after 28 days ofage. This considered the increase in strength due tothe pozzolan reaction. In addition, FA30-25 andFA30-50 were also expected to have a pozzolan
reaction due to the inclusion of FA, but the increasein strength did not increase as much as FA30-0. From
this, the effect of suppressing the increase in strength
after 28 days of age was observed by mixing the
garbage molten slag. For concrete with fly ash, up to
28 days of age, the compressive strength increase waslarger in the air curing, at 28-91 days of age, water
curing tends to increase strength more. From this, it isconsidered that water curing has the effect ofenhancing the pozzolan reaction by fly ash ascompared with air curing.

Table 1 Properties of materials used in experiment
Materials

Type

Properties

SymbolCementPortland cement

Water

Tap water

Density 3.16 [g/cm3 ]
-

W

C
70
91d
56d
28d
7d

Oven-dried density 2.59[g/cm3 ]Sean sand

Water absorption 1.14%

60

S
2

Compressive strength(N/mm )Soild content 62.1%
Fineness modulus 2.35
Fine aggregate
Oven-dried density 2.79[g/cm3 ]Garbage molten slag

Water absorption 0.81%

RS

Soild content 59.7%
Fineness modulus 2.75
Oven-dried density 2.55[g/cm3 ]Coarseaggregate

Crushed stone

Water absorption 0.50%

G

50

40

30

20

Soild content 61.34%
Fineness modulus 7.16
10

Density 2.20 [g/cm3]
FA

Agent

AE water reducer

FA0-0

alkyl ether anionic surfactant

Fig. 1

Table 2 Mix proportions

FA30-0FA30-25

air

water

air

water

air

0

water

LOI 2.1%
Specific surface area[3.41cm2 /g]

air

Fly ash (adapted to JIS Ⅱ)

water

Admixture

FA30-50

The compressive strength of concrete

Drying shrinkage

unit mass[kg/m3]
W/B W C FA S RS G
FA0-0 0.455
374 0 952 0
FA30-0325 139 828 0
170
814
FA30-25 0.523
325 139 621 220
FA30-50325 139 414 439
SymbolFigure 2 shows the development over time in thedrying shrinkage. Comparing FA0-0 and FA30-0, it
was found that the drying shrinkage when fly ash was
mixed tended to be reduced. In addition, FA30-25
showed a larger strain and FA30-50 showed a smaller
strain than FA30-0. From this, it is considered that the
replacement rate of garbage molten slag does nothave the effect of suppressing shrinkage at 25%, but

For porosity measurement, a specimen(φ100×200mm) that had been cured in water to thetarget material age was crushed, and a sieve was used
to make a particle group of 2.5 to 5.0mm, and then the187

SEE-Mie, Japan, Nov.10-12, 2022

the replacement rate of 50% has a certain effect ofsuppressing shrinkage. Figure 3 shows the mass
reduction rate. Compared with Fig. 2, it can be seenthat mass decreases with strain. The results show thatdrying shrinkage is not only related to water
evaporation, but also related to the replacement rateof fly ash and aggregate.

the experimental values. The predicted value of
FA30-50 was a result close to the experimental value.
While the AIJ formula is applied to ordinary concrete,
the test specimen of this study is positioned in highstrength concrete with a water-bonding material ratioof around 40%, so it is considered that the result issignificantly lower than the prediction formula. In
addition, the prediction accuracy in the numericalprediction problem is evaluated using the RMSE
value, which indicates how much the predicted values
obtained from these prediction formulas deviate fromthe experimental values. When using high-strength
concrete, by regression analysis we examined thecorrection factor to match the predicted value with theexperimental value. Table 3 shows the correction
coefficients analyzed, FA0-0 was 0.52, FA30-0 was
0.56, FA30-25 was 0.60, and FA30-50 was 0.95. As
a result, in the AIJ formula, when calculating thepredicted value when fly ash is mixed, and garbage
molten slag is replaced with high-strength concrete,
the predicted value can be calculated more accurately
by using the above correction coefficient.

0

FA0-0
FA30-0FA30-25
FA30-50

Drying shrinkage ( μ)

-100

-200

-300

-400

-500

-600
0

20

40

60

80

100

Days

Fig. 2 The development over time in drying shrinkage.

FA0-0
FA30-0FA30-25
FA30-50
FA0-0 AIJ
FA30-0•
EFA30-25•
EFA30-50 AIJ

1

0.995

2

Specific creep（μ/N/mm ）Mass reduction rate（%）

60

FA0-0
FA30-0FA30-25
FA30-50

0.99

0.985

0.98
0

20

40

60

80

50

40

30

20

10

0

100

0

10

20

DAYS

30

40

50

60

70

DAYS

Fig. 3 The mass reduction rate over time

Fig. 4 The change over time in specific creep strain.

Creep

Table 3 The correction coefficients

Figure 4 shows the change over time in the unit creep
strain. FA30-0 and FA30-25 have lower creep strain
than FA0-0. From this, it was confirmed that mixing
FA has the effect of suppressing creep strain.
However, the strain of FA30-50 showed a larger
value than the strain of FA0-0. Therefore, when thereplacement rate of molten slag is 25%, the effect on
strain is small, but when it is increased to 50%, thestrain tends to increase.
In this study, we investigated the correspondence
between the experimental results of creep obtained by
the experiment and the predicted value obtained by
the creep strain prediction formula shown in theprevious studies. The predicted results of the AIJ
formula (Architectural Institute of Japan proposed)
has been reported to have the highest adaptability forordinary concrete [10], so we only analyzed the AIJ
formula. The predicted values of FA0-0, FA30-0, andFA30-25 tended to be overestimated with respect tocoefficients

FA0-0

FA30-0FA030-25

FA30-50

0.52

0.56

0.6

0.95

The relationship between pore structure andcompressive strength or drying shrinkage
Fig. 5 shows the pores volume of concrete.
Comparing the amount of decrease in pore volume
between 7 and 91 days of age, the amount of decreasein concrete with fly ash showed a larger decrease. In
addition, when combined with the results ofcompressive strength, it is supported that the increasein the strength of the FA mixture after 28 days of age
is due to the pozzolan reaction. Moreover, since nosignificant difference can be confirmed even whencomparing FA30-25 and FA30-50, it is consideredthat the effect of the substitution rate of garbage
molten slag on the pore structure is small. Figure 6
shows the relationship between the pores volume andthe compressive strength. It was found that there is no188

SEE-Mie, Japan, Nov.10-12, 2022

relationship between the compressive strength andthe pore volume regardless of whether the porevolume is 50 nm or more or the total pore volume.
Therefore, we think that the compressive strength of
concrete is affected by the aggregate material in
addition to the pore structure. Figure 7 shows the
2μm～
relationship between
0.1μm～2μm the pore volume and the dry
0.01μm～0.1μm
shrinkage. The0～0.01μm
pore volume showed a particularlyhigh correlation in the range of 0.003 ㎛ to 0.1 ㎛.
Therefore, it is considered that the pore volume in thisrange has a large effect on the drying shrinkage ofconcrete.
0.14

2.

3.

7d

4.

0.1

0.08

70
0.06

Compressive strength（N/mm2）

Pore volume(ml/g)

0.12

0.04

0.02

0

FA0-0

FA30-0FA30-25

FA30-50

0.14

28d
2μm～
0.1μm～2μm
0.01μm～0.1μm
0～0.01μm

0.12Pore volume(ml/g)

garbage molten slag, the effect of suppressing theincrease in strength after 28 days of age wasobserved.
Regarding the drying shrinkage strain, it was
found that the drying shrinkage when fly ash was
mixed tended to be reduced. And the shrinkage
reduction effect by replacing the molten slag was
better than fly ash.
Regarding the unit creep strain, it was confirmedthat the strain tends to be suppressed by mixing
fly ash in concrete. It is considered that the creep
strain tends to increase when the replacement
rate of the molten slag is increased to 50%,although the effect on the creep strain is small at
25%.
Regarding the pore volume, the mixtures with fly
ash showed a larger decrease in the age of 7 to 91
days.

0.1

0.08

65

60

55

R2=0.44
50

45

40

35

more than 50nm

30
0.02

0.06

0.025

0.03

0.035

0.04

0.045

Pore volume（ml/g）

0.04

Compressive strength（N/mm2）

70
0.02

0

FA0-0

FA30-0FA30-25

FA30-50

0.14

91d
0.12

2μm～
0.1μm～2μm
0.01μm～0.1μm
0～0.01μm

0.1

0.08

0.06

0.04

0.02

FA30-0FA30-2560

55

R2=0.53
50

45

40

35

Total pore volume

30
0.06

0.065

0.07

0.075

0.08

0.085

0.09

0.095

0.1

Pore volume（ml/g）

0

FA0-0

65

FA30-50

Figure 6 The relationship between the pores volume
and the compressive strength.

Fig. 5 The pores volume of concrete.
CONCLUSIONACKNOWLEDGMENTS
1.

Regarding compressive strength, FA30-0 has thelargest increase in strength after 28 days of age.
This is considered the increase in strength due tothe pozzolan reaction. Furthermore, by mixing

The authors acknowledge the assistance in this work
provided by Eiji Mikura. This work was supported by
KAKENHI (20H02300).
189

SEE-Mie, Japan, Nov.10-12, 2022

[2] L. Evangelista, M. Guedes, J. de Brito, A.C. Ferro,
M.F. Pereira, Physical, chemical and mineralogicalproperties of fine recycled aggregates made fromconcrete waste, Construct. Build. Mater. 86 (2015)
178–188.
[3] Kumar, G. S. (2019). Influence of fluidity on
mechanical and permeation performances of recycled
aggregate mortar. Construction and Building
Materials, 213, 404-412.
[4] Heidrich, Craig, Hans-Joachim Feuerborn, andAnne Weir. "Coal combustion products: a global
perspective." World of coal ash conference. 2013.
[5] De Maeijer, P.K.; Craeye, B.; Snellings, R.;
Kazemi-Kamyab, H.; Loots, M.; Janssens, K.; Nuyts,
G. Effect of ultra-fine fly ash on concrete
performance and durability. Constr. Build. Mater.
2020, 263, 120493.
[6] Moghaddam, F.; Sirivivatnanon, V.; Vessalas, K.
The effect of fly ash fineness on heat of hydration,
microstructure, flow and compressive strength ofblended cement pastes. Case Stud. Constr. Mater.
2019, 10, e00218[7] Saha, A.K. Effect of class F fly ash on the
durability properties of concrete. Sustain. Environ.
Res. 2018, 28, 25–31.
[8] Moffatt, E.G.; Thomas, M.D.; Fahim, A.
Performance of high-volume fly ash concrete inmarine environment. Cem. Concr. Res. 2017, 102,
127–135.
[9] Kristiawan, S.A.; Aditya, M.T.M. Effect of High
Volume Fly Ash on Shrinkage of Self-compacting
Concrete. Procedia Eng. 2015,125, 705–712[10]Liu, Zihao, et al. "A study on engineering
properties and environmental impact of sustainableconcrete with fly ash or GGBS." Construction and
Building Materials 316 (2022): 125776.

Drying shrinkage（μ）

-460

-480

-500

R2=0.93-520-540

0.003μm～0.1μm

-560

-580
0.025

0.03

0.035

0.04

0.045

0.05

Pore volume（ml/g）
-460

-480

-500

2

R =0.66-520-540

Total pore volume

-560

-580
0.06

0.062

0.064

0.066

0.068

0.07

0.072

Pore volume（ml/g）
Fig. 7 The relationship between the pore volume andthe dry shrinkage.
REFERENCE[1] Meyer, Christian. "The greening of the concrete
industry." Cement and concrete composites 31.8
(2009): 601-605.

190

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

LABORATORY STUDY OF PHYSICAL AND THERMAL PROPERTIESOF CONCRETE MIXED WITH BAKELITE
Sitthiphat Eua-apiwatch1 and Worasit Kanjanakijkasem2
Department of Civil Engineering, Faculty of Engineering, Burapha University, Thailand;
2
Department of Mechanical Engineering, Faculty of Engineering, Burapha University, Thailand
1

ABSTRACTThis research aims to study the physical and thermal properties of concrete blocks mixed with Bakelite. The
main goal of this research is to use Bakelite plastic to replace the total mass of concrete blocks. The laboratory
tests include compressive strength test, density test, water absorption test, and thermal conductivity test. The
concrete blocks are mixture of Portland cement type one, dust stone, sand, and Bakelite plastic. The mixing ratioof concrete blocks with a binder to total mass is 1:5 by weight. The percentage of plastic varies from 0% to 20%
and the curing method of concrete blocks is air curing for 7, 14, and 28 days. The compressive strength anddensity tests were conducted after the completion of each curing period, while the water absorption test was
conducted only for the curing period of 28 days. Two groups of concrete block samples, 50x50x50 mm3 and65x125x145 mm3, were used in the physical properties tests, while 10x10x10 cm3 concrete block samples withthe curing period of 28 days were used in the thermal conductivity test. The result shows that an increasing in thepercentage of Bakelite decreases the compressive strength and density of concrete block samples. The water
absorption is in proportion to the increasing of percentage of Bakelite. Finally, an increasing of Bakelite ranging
from 0% to 20% roughly reduces the thermal conductivity of concrete block samples from 0.5 W/m-K to 0.3
W/m-K.
Keywords: Bakelite plastic, Compressive strength, Density, Water absorption, Thermal conductivity

INTRODUCTION

In this study, Bakelite will be used as an elementof aggregate for concrete block forming to be an
approach to reduce Bakelite waste. Then, the basic
physical properties and thermal conductivity ofconcrete block samples mixed with Bakelite areinvestigated to obtain basic information for using
such concrete blocks as a construction material.

The total amount of plastic waste generated in
Thailand is approximately 2 million tons per year,
and only about 0.5 million tons per year can berecycled. The remaining 1.5 million tons is a singleused plastic and cannot be recycled. Most of themwill be disposed of as solid waste and continuously
increasing. In 2020, a study on the amount of plastic
waste [1] stated that there was approximately 6,300
tons of plastic waste per day during the coronavirus
disease 2019 epidemic, or a 15% increase in plastic
waste compared to the same period under normal
circumstances in 2019. Due to the epidemic situation,
people have changed their behaviors in using online
shopping services coupled with less waste sortingfor recycling due to fear of infectious waste that was
mixed with community solid waste.
In 1907, a Belgian chemist, Leo Baekelanddeveloped polyoxybenzylmethylenglycolanhydrideor Bakelite [2]. It has gotten more important role in
the industry because it can be manufactured withless effort and its cost is low. While its properties
such as low thermal conductivity and low electricalconductance can satisfy various requirements ofseveral products. To eliminates the Bakelite waste, It
is prohibited from direct disposed to the landfillingand open burning [3] therefore the cost of Bakelite
waste treatment is very high.

MATERIAL AND ITS PROPERTIES
Bakelite
Bakelite is the commercial name of athermosetting phenol formaldehyde resin formed
from the condensation reaction of phenol withformaldehyde. Its main chemical components
consist of carbon, hydrogen, and oxygen.
Compounds found in Bakelite by X-Ray diffraction(XRD) technique are reported in Table 1 which
calcium oxide is the main compound with a small
amount of silica and sulfur trioxide. The specificgravity of Bakelite used in this study is ranging from
1.3 to 1.4.
Table 1 Chemical compounds in Bakelite.
Compound
CaO
SiO2
SO3
191

Percentage by weight (%)
94.23
5.14
0.33

SEE-Mie, Japan, Nov.10-12, 2022

Aggregate
Quarry dust, sand, and ordinary Portland cement
type 1 used in forming concrete blocks have specificgravity of 2.70, 2.65, and 3.13, respectively. The
particle size distribution of quarry dust is shown in
Fig. 1.

Fig. 1

Particle size distribution of quarry dust.

Fig. 2

Sample of concrete blocks

Fig. 3Sample concrete
properties testing.

blocksforphysicalMETHODOLOGY

Thermal Conductivity Testing

Physical Properties Testing

The mixtures of concrete blocks in the physicalproperties testing are also used in the thermal
conductivity testing. The dimension of concrete
block samples for this purpose is 100x100x100 mm3
with a curing period of 28 days and three concrete
block samples are employed for each mixture. Fivethermocouples of type K, calibrated at the melting
point and boiling point of distilled water, wereplaced on the middle plane of the concrete block
sample and equally spaced along the vertical line
passing through its centroid as shown in Fig. 4.

Physical properties testing includes compressive
strength testing, density testing, and water
absorption testing. Sample concrete blocks for all
tests were prepared using one kilogram of Portland
cement type 1 mixed with quarry dust, sand, andBakelite. The mixtures of concrete block samples
are shown in Table 2.
Table 2 Mixtures of concrete block samples.

No.
1
2
3
4
5

Mass (kg)
Quarry
Sand
Dust
(kg)
(kg)
4.00
1.00
3.80
0.95
3.60
0.90
3.40
0.85
3.20
0.80

Fine
Bakeliteplastic
(kg)

Water
(cc.)

0
0.25
0.50
0.75
1.00

800
900
1000
1100
1200

Sample concrete blocks were formed with adimension of 100x1250x250 mm3 as shown in Fig. 2
and were cured for 7, 14, and 28 days. After the
curing period, they were cut into concrete block
samples with dimensions of 50x50x50 mm3 asshown in Fig. 3. For each mixture, five concrete
block samples were tested. Firstly, their densities
were found. Then, they were dried at a temperature
ranging from 105oC to 110oC and immersed in waterfor 24 hours to find water absorption. Finally, thecompressive strengths of concrete block samples
were tested by a concrete compression machine.

Fig. 4
192

Locations of thermocouple installation.

SEE-Mie, Japan, Nov.10-12, 2022

The concrete block sample was three-layer
insulated on all vertical surfaces as shown in Fig. 5and on the top surface (not shown in Fig. 5) toprevent heat losses to ambient air. On the top surface,a heat flux sensor was placed at its centroid. Afterassembling all stuff, it was heated from the bottom
surface by a compact heater.

Fig. 5Consequently, the thermal conductivity of theconcrete block sample, k, can be computed from
Fourier’s law of conduction [4] in Eq.(1).

qx = −k 

dT
dx

(1)

The temperature gradient along the vertical line
passing through the centroid of the concrete block
sample can be computed via the method of
undetermined coefficients [5]. It starts by writing thefirst derivative of a function at any point, x, as asummation of the weighted of that function at five
points in Eq.(2). Then, all terms on the right-handside are replaced by Taylor series expansion about apoint, x , as in Eq.(3). Finally, a system of equations
in Eq.(4) is set up from the coefficients of the first
five terms of all series, i.e., the coefficients of f ( x),Heating of concrete block samples.

f ( x), f ( x), f (3) ( x), f (4) ( x). This can yield thePlacing of all thermocouples as explained resultsin obtaining temperature distribution along thevertical line passing through the centroid of theconcrete block sample which can be considered as
one-dimensional conduction heat transfer. The
temperature gradient at steady state, dT dx , can becomputed from temperatures at five locations, while
the corresponding heat transfer rate on the top
surface, q x , can be obtained by the heat flux sensor.

formula for numerical differentiation after obtaining
all weighting factors from the system of equations.
After putting the location, x, of the top surface into
the formula, the temperature gradient can be
immediately computed. It should be noted that thelocations of thermocouples will be a part of the input
for this approach, so it is not necessary to beseriously concerned about precision in equallyspacing them.

f ( x) = a  f ( x1 ) + b  f ( x2 ) + c  f ( x3 ) + d  f ( x4 ) + e  f ( x5 )

(2)

1
1


f ( x) = a   f ( x) + f ( x)  ( x1 − x) +  f ( x)  ( x1 − x) 2 +  f (3) ( x)  ( x1 − x)3 + ...
2!
3!


1
1


f ( x) = + b   f ( x) + f ( x)  ( x2 − x) +  f ( x)  ( x2 − x) 2 +  f (3) ( x)  ( x2 − x)3 + ...
2!
3!


1
1


f ( x) = + c   f ( x) + f ( x)  ( x3 − x) +  f ( x)  ( x3 − x) 2 +  f (3) ( x)  ( x3 − x)3 + ...
2!
3!


1
1


f ( x) = + d   f ( x) + f ( x)  ( x4 − x) +  f ( x)  ( x4 − x) 2 +  f (3) ( x)  ( x4 − x)3 + ...
2!
3!



(3)

1
1


f ( x) = + e   f ( x) + f ( x)  ( x5 − x) +  f ( x)  ( x5 − x) 2 +  f (3) ( x)  ( x5 − x) 3 + ...
2!
3!


1

 x −x1 2!1  ( x1 − x) 2
13
 3!  ( x1 − x)
 1  ( x1 − x) 4
 4!

1
x2 − x2
1
2!  ( x2 − x )3
1
3!  ( x2 − x )4
1
4!  ( x2 − x )1x3 − x2
1
2!  ( x3 − x )3
1
3!  ( x3 − x )4
1
4!  ( x3 − x )1x4 − x2
1
2!  ( x4 − x)3
1
3!  ( x4 − x)
4
1
4!  ( x4 − x)

1931
  a  0 
x5 − x   b  1 
   2  1
  c  = 0 
2!  ( x5 − x )
3 
1
 
3!  ( x5 − x )   d  0 
41
 e  0 
4!  ( x5 − x )  (4)

SEE-Mie, Japan, Nov.10-12, 2022

RESULTS

Water Absorption

Compressive Strength

From Fig. 8, it was found that water absorptionof concrete block samples increased with respect topercentage of Bakelite. This is because higher
percentage of Bakelite had caused the concrete block
samples to have higher porosity from the expansionof Bakelite due to the hydration reaction of cement
and water. The lowest absorption is at 9% for theconcrete block sample with no mixing of Bakelite

From Fig. 6, it was found that the compressive
strength of concrete block samples increased withrespect to the curing period but decreased withrespect to the percentage of Bakelite by weight. The
compressive strength of the concrete block sample
without mixing of Bakelite with a curing period of
28 days is 261 ksc which is the highest compressive
strength of the concrete block sample in this study.

Fig. 8Relationship between water absorption andpercentage of Bakelite.

Thermal Conductivity
Fig. 6

Relationship between compressive strengthand percentage of Bakelite.

Three concrete block samples with curing periodof 28 days were tested for each mixture. Each case
was lasting about 3 to 8 hours to reach steady stateof heat conduction, i.e., the temperature of thelocation closest to the heater was constant about 10
minutes. This location was selected because it could
have the largest temperature change from room
temperature. Or it can be said that the temperature at
this location is the most sensitive one among all fivelocations. Although the precision in placing all
thermocouples was not the issue to be concerned
with, they were equally spaced in this study and all
the results are shown in Table 3. The format ofsample name is the combination of the percentage of
Bakelite and number of samples, e.g., sample 0-1
means sample number 1 of concrete block with 0%of Bakelite, sample 5-1 means sample number 1 ofconcrete block with 5% of Bakelite, etc.
Thermal conductivities of all concrete block
samples computed from temperature gradients andheat fluxes in Table 3 are presented in Table 4 andas bar chart in Error! Reference source not found..
It was roughly found that thermal conductivities ofconcrete block samples linearly decreased from 0.5
W/m-K to 0.3 W/m-K with respect to the percentage
of Bakelite ranging from 0% to 20%.

Density
From Fig. 7, it was found that the density ofconcrete block samples decreased with respect to thepercentage of Bakelite. This resulted from several
tiny voids that occurred after the setting of concrete
block samples. The curing period of 28 days whichis the longest curing period in this study seems toyield the lowest density of concrete block samples
for all mixtures. While the curing period of 7 and 14
days tends to yield a comparable density of concrete
block samples and is higher than that of concrete
block samples with a curing period of 28 days.

Fig. 7

Relationshipbetweenpercentage of Bakelite.

densityand

194

SEE-Mie, Japan, Nov.10-12, 2022

Table 3 Temperature distributions along the line passing through the centroid of concrete block samples andtemperature gradients at the top surface of concrete block samples.
Temperature ( C) at Locations along x-axis

SampledT dx

qx  2S.D.

( mW2 )

1.67 cm

3.33 cm

5.00 cm

6.67 cm

8.33 cm

K
(m
)

0-1

79.21272.73070.05067.89564.486-258.369

136.820 ± 0.639

0-2

76.72571.43069.41567.56864.610-211.506

113.216 ± 0.370

0-378.53073.40070.69768.44065.640-191.981

97.740 ± 0.385

5-1

78.55374.79042.54670.30964.456-191.427

88.700±0.402

5-2

78.52072.95570.79068.65365.715-181.545

83.020±0.379

5-3

77.20872.78069.20066.74763.980-232.899

107.320±0.485

10-1

77.67073.59469.14066.58763.550-317.369

129.382±0.494

10-2

76.96374.35570.48167.79065.065-246.627

97.797±0.445

10-3

76.93772.40869.01266.89964.427-221.367

90.460±0.315

15-1

76.38372.58467.29063.88260.947-265.49

90.992±0.313

15-2

76.96172.33867.17064.96062.520-320.081

112.963±0.410

15-3

77.78972.93268.19065.95063.700-261.65

90.991±0.233

20-1

74.77268.44566.67664.94360.427-388.442

112.963±0.420

20-2

76.38269.87066.01363.40060.154-261.591

83.291±0.303

20-3

73.69068.61964.91061.92158.051-308.610

95.997±0.363

Table 4 Thermal conductivity of concrete block samples.

Fig. 9Thermal Conductivity ( mWK )Percentage of
Bakelite(%)

Sample 1

Sample 2

Sample 300.529553 ± 0.002473

0.535286 ± 0.001751

0.509113 ± 0.002023

50.463362 ± 0.002100

0.457297 ± 0.002087

0.460801 ± 0.002083

100.407671 ± 0.001556

0.396538 ± 0.001804

0.408643 ± 0.001424

150.342732 ± 0.001179

0.352920 ± 0.001280

0.347758 ± 0.000891

20

0.290810 ± 0.001082

0.318402 ± 0.001580

0.311063 ± 0.001770

Bar chart of thermal conductivity of concrete block samples.

195

SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSIONSREFERENCES

Physical properties testing and thermal
conductivity testing of concrete mixed with Bakelite
are carried out in this study. The experimental
results reveal that the increasing in the percentage of
Bakelite bring about the decreasing in compressive
strength and density of the concrete block samples,while the water absorption of the concrete block
samples is heightened. Additionally, the increasingof Bakelite ranging from 0% to 20% roughly
reduces the thermal conductivity of the concrete
block samples from 0.5 W/m-K to 0.3 W/m-K.

[1] Pollution Control Department, Situation of
Municipal solid waste in Thailand (in Thai). 2021.
[2] Dharanidharan S., Srivithya N., and Meena N.,
Experimental Study on the Flexural Behavior of EWaste Plastics in Concrete. International Journal ofEngineering Science & Research Technology, Vol.
4, No.11, 2015, pp. 660-669.
[3] Seree T., Nopagon U., and Sirawan R.T., A
Study Bakelite Plastics Waste from Industrial
Process in Concrete Products as Aggregate.
International Journal of Structural and Civil
Engineering Research, Vol. 6, No.4, 2017, pp. 263267.
[4] Incropera F.P., DeWitt D.P., Bergmann T.L.,
and Lavine A.S., Fundamentals of Heat and Mass
Transfer. 6th ed., Wiley, 2006.
[5] Kanjanakijkasem W., Numerical Methods (inThai). 2nd ed., 2020.

ACKNOWLEDGEMENTS
This research is partly supported by the Research
Fund No. PJ 6/2563 from Faculty of Engineering,
Burapha University
Equation Section (Next)

196

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ELECTROCHEMICAL EVALUATION OF CORROSIONPROTECTION OF REINFORCING STEEL BARS USING SUGARS
Yoko Sakakihara1, Kiyofumi Yamagiwa2, Kyosuke Isoda3, and Shinichiro Okazaki3
1
Graduate School of Engineering, Kagawa University, Japan;
2
Faculty of Life & Environmental Sciences, Teikyo University of Science, Japan;
3
Faculty of Engineering and Design, Kagawa University, Japan
ABSTRACTThis study reports the effect of adding sugars to prevent corrosion of reinforcing bars. The reducing sugars
aldose (sugar with an aldehyde group) and, ketose (sugar with a ketone group), and a non-reducing sugar and syrup
with an expiration date were used in the experiments. Fehling’s reaction, Benedict’s reaction, and cyclic
voltammetry (CV) tests were performed to investigate the effect of the various sugars on the reductive ability.
Because the electrochemical oxidation of sugars requires electro-catalysts, electrodes containing particulate CuO
catalysts were used in the experiments. The measurements were performed under alkaline conditions to, simulatea reinforcing bar in the concrete. The experimental results revealed the influence of different types of sugars on
the reductive ability. In Fehling’s reaction, fructose was observed to be highly reductive, and its reaction rate washigh. In Benedict's reaction, waste syrup (WS) obtained results similar to those of fructose, thereby confirmingthat WS can be used as a reducing sugar. The oxidation initiation potentials in the electrochemical experiments
were lower for fructose, WS, and glucose, in that order, which was the same as the order of the reaction rates in
Benedict’s reaction.
Keywords: Corrosion protection, Cyclic voltammetry, Fehling’s reaction, Benedict’s reaction, sugar
durability of a structure.
In recent years, amidst calls for a shift to a
recycling-oriented society, reusing waste syrup (WS)
has been in focus from the perspective of sustainable
development goals and recycling [7]–[9]. By mixing
sugar waste from the food industry into concrete, we
aim to not only reuse the waste, but also have thesecondary effect of preventing rebar corrosion causedby the reducing performance of sugar [10]. Currently,
there is no admixture that increases corrosion
resistance; therefore, reducing sugar was selectedwith the expectation that adding a reducing agent
would
have
a
sacrificial
anodeeffect.
Electrochemical experiments were conducted toinvestigate the reducing ability of sugar and its
potential use in corrosion protection of rebar.
In this study, we first investigated the reduction
performance of WS and other sugars in the Fehling’s
reaction and Benedict’s reaction, and then throughcyclic voltammetry (CV) measurements. By
comparing the results of these three experiments, theinfluence of the reduction power of sugars on theelectrochemical properties of rebar was confirmed.

INTRODUCTION
Several structures were built during the rapid
economic growth period in the 1960s in Japan for
infrastructure development. The life span ofreinforced concrete (RC) structures is generally
around 50 years, and many structures currently
require inspection and repair [1]. The decrease in the
durability of RC structures is primarily owing tocorrosion of the reinforcing steel bars [2], [3].
Because reinforcing bars are generally locatedinside concrete, and the pore solution in concrete isalkaline, a nonconductive film is applied on thesurface of the reinforcing bars to prevent corrosion.
However, this non-conductive film can be destroyedby the carbonation of concrete and intrusion ofchloride ions, and when both water and oxygen reachthe film, the steel starts to corrode. As the rebar
corrodes, its volume expands by a factor of two or
more, and the expansion force destroys the concrete.
Additionally, water and oxygen penetrate throughcracks and accelerate the corrosion. Controlling
corrosion is the key to maintaining the durability ofconcrete.
Methods such as using a thicker concrete cover ora lower water–cement ratio have long been employed
to control the corrosion of steel bars [4]. A surface
impregnating material is also commonly applied toprevent water from penetrating into the steel [5], [6],but it is preferable to omit such laborious methods anduse a corrosion-preventive admixture to maintain the

MATERIALS AND METHODS
Materials
Referring to the study by Inoue et al [11], glucose
was selected as the reference substance. The WS usedin the experiment consisted of 75% solids and 25%
197

SEE-Mie, Japan, Nov.10-12, 2022

water. The main component of the WS was glucose,
constituting approximately 40% of sugars. Fructose
was the next most abundant component, constituting
approximately 30%. The remaining 30% contained a
few percent each of other sugars. Fructose wasselected as one of the materials because the maincontents of the WS were glucose and fructose.
Sucrose was added as a material for comparison
because it was known as a non-reducing sugar.

Benedict's Reaction
Benedict’s solution is a commercially available
reagent (Hayashi pure chemical Inc., LTD.) and issold for clinical testing. Two milliliters of Benedict’s
solution were added into a test tube containing 9 mgof sugar (12 mg in case of WS). The test tubes werecovered with Parafilm and the tube was immersed inwater heated to 80 °C for 1, 2, 3, and 5 min. Thereafter,
the solution was filtered through the filter paper,
which was then dried and weighed.

Fehling’s Reaction
As shown in Fig. 1, fructose, and glucose have thesame alcohol configuration from the third to sixth
carbon positions. These four sugars including sucrose
and WS were used in the experiment.
Distilled water was used as the solvent to prepare
the reagents and in the experiments. Fehling's
solution A was prepared by dissolving 6.92 g ofcopper (II) sulfate pentahydrate in water to make 100
ml of solution. For Fehling's solution B, 34.6 g ofpotassium sodium tartrate tetrahydrate and 10.0 g of
sodium hydroxide were dissolved in water to make100 ml of solution [12]. One milliliter each of
Fehling’s solutions A and B were added into a test
tube containing 9 mg of sugar (12mg in case of WS)
to completely dissolve the sugar. The test tubes werecovered with Parafilm and heated in a water bath at
80 °C for 1, 2, 3, and 5 min, and then filtered througha filter paper (No. 5C). The filter paper was then driedand quantified.
The WS was set to 12 mg because it contains 75%
sugars and 25% water.

D-Fructose

Electrochemical Measurements
CV measurements were performed to characterize
the reducing properties of sugars. CV measurements
require an electro-catalyst that facilitates theoxidation of sugars [13]–[16]. Recently, it has been
discovered that metal oxides such as copper oxide(CuO) catalyze the electrochemical oxidation ofsugars, especially under alkaline conditions; therefore,a CuO-based catalyst was used in this experiment.
The CuO-based catalyst was synthesized by heattreating a carbonate mineral containing Cu [17]. The
catalyst and carbon paste (conductive material) weremixed with a dispersant to form a slurry, which waspoured onto a carbon paper and dried to form
electrodes.
D-glucose (aldose), D-fructose (ketose), sucrose(non-reducing sugar), and WS were used to study theelectrochemical behaviors of the sugars. The
concentration of D-glucose, D-fructose, and sucrose
in 0.1 M NaOH solutions was 10 mM. The
concentration of WS was also set the same. The
composition of the WS was 75% sugars and 25%
water. All sugars of WS were assumed to bemonosaccharides, and the WS solution was set tohave a concentration of 10 mM in 0.1 M NaOH
solution.
The CuO electrode was used as the working
electrode. A saturated silver-silver chloride electrode(Ag/AgCl) was used as the reference electrode, and aplatinum electrode was used as the counter electrode.
The measurements were performed in a threeelectrode cell with a potentiostat (Hokuto Denko
model HZ-7000). A cyclic voltammogram was
obtained in the potential range of -0.1 to 0.6 V. The
electrode was then changed, and measurements were
performed in the range of -0.1 to 0.2 V. In all cases,
three cycles with a scan rate of 10 mV s-1 wererecorded. The third cycle was used for evaluation.
The electrochemical measurements were performed
at 25 °C and without stirring.

D-Glucose

SucroseFig. 1

Molecular structures of sugars.

198

SEE-Mie, Japan, Nov.10-12, 2022

(a)

RESULTS AND DISCUSSION
Fehling's Reaction
The experimental cases are shown in Table 1. The
amounts of Cu2O formed by the reactions of glucose,fructose, sucrose, and WS with Fehling's solution
were compared (the blanks indicate the case where
only distilled water was used as the sample).
Figure 2 shows a photograph of the precipitation
obtained through Fehling’s reaction after 5 min. As
shown in Figs. 2 and 3, Cu2O was not formed fromsucrose. For validation through a blank case, anexperiment with only water was also performed,
which showed similar results.
Figure 3 shows photographs of the experiment.
From left to right: fructose, WS, glucose, sucrose, andblank. After 1 min, a color change began in fructose
and WS, followed by a color change in glucose, andafter 5 min, fructose, glucose, and WS turned red [18].
The results of the reaction of Fehling's solution
with sugars that exhibited reducing properties areshown in Fig. 4. In the reduction reaction of Fehling's
solution, Cu2O was produced from fructose, glucose,and WS, in that order. It was obtained the fastest fromfructose, indicating a high reaction rate.

(b)

(c)

Table 1 Weight of sugars used in the experiment.
Cases
1
2
3
4
5

SucroseSugarsFructose
GlucoseSucroseWS
Blank

Weight of sugar
9 mg
9 mg
9 mg
12 mg
-

(d)

GlucoseFig. 3

The filterd amount ofmetals (g)Fructose

Blank

WS

Color changes in Fehling’s reactions. (a:after 1 min, b: after 2 min, c: after 3 min, d:after 5 min)
0.035
0.030
0.025
0.020
0.015

GlucoseFructose
WS

0.010
0.005
0.000
0

1

2

3

4

5

Time (min.)Fig. 2

Photograph of precipitation obtained
through Fehling’s reactions after 5 min.

Fig. 4
199

Increase in the weight of filter papers after
Fehling’s reactions.

SEE-Mie, Japan, Nov.10-12, 2022

Fructose reacted the fastest in Benedict’s reaction,
similar to Fehling's reaction. In Benedict's reaction,
WS and glucose, in that order, yielded Cu2O. As
shown in Fig. 5, sucrose did not oxidize [18]. For
validation through a blank case, an experiment with
only water was also performed, which showed similar
results.

Benedict's Reaction
Figure 5 shows photographs of color changes in
Benedict's solution. From left to right: fructose, WS,
glucose, sucrose, and blank. The weights of the
precipitates obtained via Benedict's reaction are
shown in Fig. 6. Although the results for the
reductions using fructose, glucose, and WS were
marginally different in Fehling’s reaction, there wasa marked difference between them in Benedict's
reaction. Fehling's solution is a strong alkali with a
pH of 14, whereas Benedict’s solution has a pH ofapproximately 10, which indicates that Benedict's
reaction is gradual. Although glucose was easily
oxidized in Fehling's solution, Benedict's reaction
was slightly slower [19]. This result is similar to thatreported by Inoue et al. [11].

Results of CV Measurement
We performed cyclic voltammetry to confirm thefunctionality of the CuO electrode. The cyclic
voltammogram of glucose is shown in Fig. 7. The
system with glucose shows that an oxidation current
originating from the electrochemical oxidation of
glucose is at high potentials, and a significant
oxidation current density of ~3 mA cm-2 is observed
at 0.6 V. The measurement of the oxidation current of
glucose using a CuO electrode has been reported inother studies [20], [21], and similar results wereobtained in this experiment, wherein its function as acatalyst for glucose oxidation was confirmed.
The cyclic voltammograms of the CuOcontaining electrode in each sugar solution (potential
range: -0.1 to 0.6 V (vs. Ag/AgCl)) are shown in Fig.
8. Significant oxidation currents were observed at 0.6
V for all carbohydrates. Sucrose, similar to the othersugars, also showed oxidation currents. The details of
the reaction mechanism of the electrochemical
oxidation are still unclear. Although there was no
significant difference in the current density, theexperiment showed that the oxidation initiation
potentials differed among the different sugars.
Fructose showed a rise in oxidation current from alower potential than WS.
The cyclic voltammograms of the CuOcontaining electrode in each sugar solution (potential
range: -0.1 to 0.2 V (vs. Ag/AgCl) are shown in Fig.
9. The order of the fastest rising oxidation initiation
potentials was fructose, WS, and glucose, which issimilar to that in the Fehling's reaction.

(a)

(b)

(c)

The filterd amount of metals
(g)

0.025

(d)

Fructose
WS
Glucose

0.020
0.015
0.010
0.005
0.000
0

Fig. 5

Color changes in Benedict’s reactions. (a:after 1 min, b: after 2 min, c: after 3 min, d:after 5 min)Fig. 6

200

1

2

3

Time (min.)4

5

Increase in the weight of filter papers after
Benedict’s reactions.

SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSIONS

4.0
GlucoseWithout sugar

j / mAcm-2

3.0

The Fehling’s reaction, Benedict's reaction andelectrochemical experiments were used glucose,fructose, sucrose, and WS. In Fehling’s reaction, it
was observed that fructose was highly reductive andits reaction rate was high. The result of WS was
similar to that of fructose and glucose. In Benedict’s
reaction, the differences were observed in the amountof precipitation and the reaction rate. Fructose was
fastest, next was WS, and glucose. The reaction rateof Fehling's solution is a strong alkali with a pH of 14,
whereas Benedict’s solution has a pH ofapproximately 10, which indicates that Benedict's
reaction is gradual. Although glucose was easily
oxidized in Fehling's solution, Benedict's reaction
was slightly slower. The oxidation initiation
potentials in the electrochemical experiments werelower for fructose, WS, and glucose, in that order,
which was the same as the order of the reaction rates
in Benedict’s reaction. To our knowledge, no study
has yet obtained the same order of reaction intensity
in electrochemical redox as in the Fehling and
Benedict reactions. The results of the Fehling’s
reaction, Benedict’s reaction, and electrochemical
experiments indicate that WS has a reducing ability
similar to that of fructose and glucose.
The Fehling’s reaction, Benedict’s reaction, andelectrochemical experiments were all conductedunder alkaline conditions. In the electrochemical
experiments, inorganic catalysts that function underalkaline conditions were selected instead of enzymes;
therefore, the conditions were more similar to thoseof concrete. In the comparison at -0.1 to 0.2 V, boththe low oxidation initiation potential and the current
density at 0.2 V confirmed an ordering that
corresponds to that of the Fehling's and Benedict's
reactions. It can be expected that the electrochemical
viewpoint can also help in the selection of the best
sugar to add reinforced concrete.

2.0
1.0
0.0
-1.0
-0.1

Fig. 70.1
0.3
0.5
E / V vs. Ag/AgCl

Cyclic voltammograms of the CuOcontaining electrode in the glucose solution(electrolite: 0.1 M NaOH, 10 mM glucose).

4.0

FructoseWS
SucroseWithout sugar

3.0
j / mAcm-2

0.7

2.0
1.0
0.0
-1.0
-0.1

Fig. 80.1
0.3
0.5
E / V vs. Ag/AgCl

0.7

Cyclic voltammograms of the CuOcontaining electrode in each sugar solution(potential range: -0.1 to 0.6 V (vs.
Ag/AgCl)).

0.6

j / mAcm-2

0.5
0.4
0.3

Fructose
WS
GlucoseSucroseWithout sugar

0.2
0.1
0.0
-0.1
-0.10

0.00

0.10

0.20

E / V vs. Ag/AgCl
Fig. 9Cyclic voltammograms of the CuO-containing electrode in each sugar solution (potential range: -0.1 to
0.2 V (vs. Ag/AgC

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SEE-Mie, Japan, Nov.10-12, 2022

ACKNOWLEDGMENTS
This research was supported by the Regional
Innovation Ecosystem Program of the Ministry of
Education, Culture, Sports, Science, and Technology,
Japan.
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Zairyo-to-Kankyo, Vol. 59, No. 4, 2010, pp. 111116.
[4] Otsuki N., Miyazato S., Shibata T., Hisada M., Md.
Tarek U. and Nagataki S., The influence of W/C
on corrosion mechanism near bending crack,
Journal of Jaoan Society of Civil Engineers, No. 66,
1998, pp. 63-73.
[5] Someya N. and Kato Y., Fundamental study on
modification effect and penetration mechanism of
silicate-based surface penetrants, Concrete
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[6] Date S., Goryozono Y., Hahimoto S. and Miyazato
S., The evaluation of performance of hydrophobic
impregnation –comparison with European Norm
(EN 1504-2)-, Journal of Advanced Concrete
Technology, Vol. 50, No. 4, 2012, pp. 331-337.
[7] Niida R., Nitta H. and Nishizaki I., Method for
reducing hexavalent chromium eluted fromrecycled base courses material using reducing
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

PHYSICAL AND MORPHOLOGICAL PROPERTIES OFPOLYURETHANE MODIFIED BITUMEN UNDER
AGEING CONDITIONS
Faridah Hanim Khairuddin1, Siti Zubaidah Mohd Asri2, Noor Aina Misnon3,
Nur Izzi Md Yusoff4, and Ahmad Nazrul Hakimi Ibrahim5
1,2,3
Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, 57000, Malaysia
4,5Faculty of Built and Engineering, Universiti Kebangsaan Malaysia, 43600, Malaysia

ABSTRACTThe aim of this research is to evaluate the effects of ageing on 60/70 penetration grade bitumen modified withpolyurethane (PU). Effects of ageing were evaluated by performing consistency test through ageing index andmorphology evaluation. The results of these tests show that adding 3 wt% of PU stiffens the bitumen in comparison
to base bitumen. A very high increase in viscosity was observed due to the hardening effect of PU. The computed
ageing index shows that this alternative material reduces ageing effects on the physical properties of the bitumen,
as indicated by the lower ageing index value of physical testing subsequent to ageing. Therefore, the addition of
PU results in improved bitumen resistance to oxidative ageing. Optical microscopy shows the sample washomogeneously blended. Atomic Force Microscopy (AFM) was conducted to evaluate the catana phase, peri phase,and para phase topography images of PU modified bitumen. Topography image from AFM test indicates that theinclusion of PU and ageing conditions has decreased the bee-like structures of the bitumen, showing larger
dispersion in the sample.
Keywords: Polyurethane Modified Bitumen, Ageing, Atomic Force Microscopy, Morphology, Topography

INTRODUCTION

improvementin
temperaturesusceptibility,
penetration, ductility, flash and fire points, fluidity,
and m-value, along with a decrease in the bitumen’ssoftening point, rotational viscosity, and creep
stiffness A research using bio-oil generated fromwaste wood source found that the bio-binders lower
the mixing temperature of bituminous mixtures andimproved the performance of the bitumen.
Khairuddin et al. [6] conducted a study on bitumen
modification using polyurethane (PU). The outcomesof this study show that the addition of PU atintermediate and higher temperatures has stiffened
the bitumen properties and increased resistance tofatigue and rutting.
Besides investigating the physical and chemical
properties of the modified bitumen, theinterrelationship of structure-property is important toobtained the bitumen optimum performance byinterpretation the morphology using microscopic
method. Surface morphology using Atomic ForceMicroscopy (AFM) is widely used by researchers to
study the topography, roughness, adhesion and local
mechanical properties of the bitumen [3] ­ [7]. As
bitumen consist of ‘bumble bees’ structures, it isimportant to investigate the effect of modifier in termof dispersion and matrix domains [8].
One of the causes of road pavement deteriorationis bitumen oxidation [9]. Short-term ageing (STA)
occurs during the mixing and compacting of
mixtures, where higher temperatures results in higher

The past several decades has witnessed hot mix
asphalt (HMA) being used as the primary material in
the paving industry, where bitumen is used as a
coating for aggregates. Bitumen is a sticky, darkbrown or black, semisolid material and is highly
viscous at ambient temperature [1]. A strong bond
between bitumen and aggregate is required toaccommodate traffic loading. This is to ensure thatpavements are strong and durable, and provide asmooth surface for road users. However, the increasein traffic volume, pressure and load in recent years
had an adverse impact on pavement performance. In
order to deal with these problems, the quality ofexisting pavements have to be improved. Additionsof modifier or replacement to bitumens are done toimprove its resistance to rutting, fatigue, andtemperature susceptibility [2]. Recent research has
shown that bio-binders can be used as modifiers(<10% bitumen replacement), extenders (25% to 75%
bitumen replacement), or 100% replacement forbitumen [3].
One study investigated the effects of using waste
cooking oil and spent coffee ground as a modifier on
the physical and chemical properties of bio-binders.
Results showed that longer oxidation time improved
the viscoelasticity of the waste oil [4]. A study
conducted by Al-Omari et al. [5] used waste
vegetable oil as a modifier; the researchers observed
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SEE-Mie, Japan, Nov.10-12, 2022

oxidation rate. Long-term ageing (LTA) occurs
during the service life of a pavement. Oxidation
occurs when bitumen reacts with oxygen diffused in
the air voids on aggregate surface [10]. The higher
viscosity caused by oxidation process increase thestiffness of pavements, which then causes cracking[11]. As ageing occurs, the physical and chemical
properties of bitumen alter the behavior of bitumen
significantly. Ageing affects the physical propertiesof bitumen, such as penetration, viscosity, ductility
and stiffness [9]. Therefore, investigation of ageing
process and its effect on modified bitumen is very
important in real application.
This study seeks to evaluate the physical,
morphological and ageing effect of a new material,
palm kernel oil polyol (PKO-p) and 2,4diphenylmethane diisocyanate (MDI) under STA andLTA conditions. The addition of these two materials
will form PU. The morphology of the modified
bitumen was observed to evaluate the homogeneity,
separation and dispersion of bee-like structure in thebitumen with the inclusion of the new material. The
following section will present a comprehensive
discussion of the tests and their results.

minutes until it turned liquid. PU in the amount of 3%
by weight of bitumen was used to produce thepolyurethane modified bitumen (B-PU) [6],[12]. This
optimum percentage of 3 wt% PU was predeterminedby Design Expert Software using Response Surface
Method. PKO-p and MDI were then added at a ratioof 1:0.6 by weight of PU. The PKO-p and bitumen
were blended for 15 minutes at 110°C and 2000
revolutions per minute using shear mechanical mixer;
MDI was then added and blended using the same
parameter. Prior to obtain a homogeneous blend,
penetration and softening point results weremonitored until consistent results were obtained andtaken as indicators of a well-blended mix.
Laboratory Testing
Penetration test
The penetration test was conducted in compliancewith ASTM D5. The value of penetration isdependent upon the hardness or softness of a bitumen.
Higher value of penetration measured in tenths ofmillimetre indicates a bitumen with softer
characteristic.

METHODOLOGY
Softening point and storage stability
Materials
The softening point test was carried out tomeasure the temperature at which the bitumen starts
to flow. It was carried out in compliance with ASTM
36. For bitumen with a given penetration (determinedat 25 ºC), higher softening point indicates lower
temperature sensitivity. Storage stability test was
conducted to evaluate the homogeneity of a blend as
well the stability during storage. This test was
conducted in compliance with ASTM-D5976 (2000).

In this study, a 60/70 penetration grade bitumen
was used as the control sample. The physicalcharacteristics of the control sample is given in Table
1. The sample was modified by adding PU to thebitumen. In order to produce PU, pre-polymerization
method of PKO-p from palm kernel oil were done atfirst stage. Next, polymerization will occur during
mixing process of PKO-p with MDI that willproduced PU.

Viscosity test at 135 ℃
Table 1 Physical properties of control sample
Physical
test
Penetration (0.1 mm)
at 25 °C
Softening point (°C)
Ductility (cm) at
25 °C
Viscosity (mPa.s) at
135 °CSpecific
gravity(g/cm3) at 25 °C

Evaluation of bitumen’s viscosity at hightemperature is important to determine the optimal
temperature for the mixing and compacting ofbituminous mixture at site. It indicates the extent towhich the bitumen can be pumped through bitumen
plant. This test was conducted in compliance withASTM D4402.

Bitumen Grade 60/70
Value Specification
66
60-70(ASTM D5)
49
47-52
(ASTM D36)
100
100
(ASTM D113)
550(ASTM D4402)
1.03
1.0-1.06(ASTM D70

Ageing of bitumen
To simulate STA, the samples were preparedusing the Rolling Thin Film Oven procedure inaccordance with ASTM D2782. STA of a bitumen
occurs during the production of bituminous mix at theplant. Simulation of LTA were carried out using thePressure Aging Vessel method in accordance withASTM D6521. LTA is an indication of the service lifeof a pavement.

Sample preparation
Modification of the bitumen was carried out by
heating the base bitumen (B-B) at 145°C for about 30

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SEE-Mie, Japan, Nov.10-12, 2022

Ageing Index

previous findings made by another researcher that theaddition of PU had a hardening effect on the bitumen.

The effects of ageing on B-PU were measured
using the penetration, softening point, and rotational
viscosity tests, and the results were compared with the
B-B. The ageing index (AI) for each test wascomputed using Eq. (1) below to evaluate the ageing
susceptibility.
𝑨𝑰 = 𝑻 𝒖𝒏𝒂𝒈𝒆𝒅

Penetration (0.1 mm)

𝑻 𝒂𝒈𝒆𝒅

80

(1)

70

68

B-B
63

60

B-PU

56
50

50

39

40

35

30

20
10

where
Taged
is
the
penetration/softening
point/viscosity test value of the aged sample andTunaged is the penetration/softening point/viscosity test
value of the unaged sample.

0
UA

Fig. 1STA

LTA

Penetration values for UA, STA and LTA.

Softening point and storage stability test

Microscopic DINO-LITE

Figure 2 shows the softening point values for B-B
and B-PU under UA, STA, and LTA conditions. The
general trend shows that adding PU to bitumen
improves softening point by 10% for UA, 8.5% for
STA, and 7.6% for LTA. This indicates the extent towhich the bitumen hardened after modification andageing. The increase in softening point is due to thechange in the structural molecules in the bitumen’scontent of fraction during the ageing process [13].
In addition, storage stability test conducted shows
the differences between the top and bottom section
for softening point value of B-PU is 0.50 °C which isless than 2.2 °C. This result indicates that there is no
separation occurred between the top and bottom
section and the B-PU sample are homogeneously,
storage stable blended [14].

The morphological property of B-B and B-PU
were observed using the optical microscope DINOLITE Pro Digital, 500X. The sample was heated at
145°C until it turned viscous. Then, the sample was
dropped on a glass slide to form an even surface andleave for 30 minutes before being viewed under amicroscope. The DINO-LITE is capable to capture
high image resolution and good image quality of asample.
Atomic Force Microscopy
To further investigate the morphology
characteristics of B-B and B-PU sample, AFM test
was conducted using the XE-10 AFM from Park
Systems Corporation. To evaluate the surface and bee
characteristics of the bitumen, heat cast method wasapplied where sample were heat until it turned liquidand dropped on a glass slide. For this study, 20 x 20
μm area at 1 Hz scan rate was selected. The sample
was tested using a silicon cantilever tip sized < 10 nm
tip radius by non-contact mode method, at 0.2 N/mconstant force for the quantifications of sample
surface.

Softening point (°C)

70.0
60.0
50.0

49.0 50.6

54.7

55.3

59.5

50.4

B-B
B-PU

40.0
30.0
20.0
10.0

RESULT AND DISCUSSION

0.0
UA

STA

LTA

Physical TestingFig. 2
Penetration test

Softening point values for UA, STA andLTA.

Viscosity test

Penetration test was used to evaluate the fluidity ofbitumen before and after modification with PU underunaged (UA), STA, and LTA conditions. Figure 1
shows the results of the penetration tests for B-B and
B-PU. The addition of 3% of PU to bitumen
decreased the penetration value by 7.3% for UA,
10.7% for STA, and 10.3% for LTA. This shows thatthe samples become stiffer subsequent tomodification and ageing. This is consistent with the

Figure 3 shows the experimental value forviscosity at 135 °C, which is the average mixing andcompaction temperatures for bituminous mixture.
The addition of PU markedly increased viscosity by
64% for UA, 22% for STA, and 12% for LTA. This
increase is still within specification permitted by theStrategic Highway Research Program which statesthat the increase in viscosity should not exceed 3000
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SEE-Mie, Japan, Nov.10-12, 2022

mPa.s [10]. The increase in viscosity occurred due tothe increase in bitumen stiffness which limited
molecule movement during the test. The addition of
PU is the contribution of higher viscosity value [14].

Viscosity (m.Pas) at 135°C

1400

B-PU used in this research. No separation wasobserved in the microscopy images. Fig. 4(b) shows
clearly the image of a homogeneous blend of the BPU, which indicate that the PU has been uniformly
dispersed and evenly spread during the mixing
process. There are no lumps observed after mixing 3
wt% PU with bitumen at selected parameters showing
analogous mix was formed. This is in agreement withthe result of storage stability test.

B-B
1146

1200

B-PU

1025
1000

913
842

800
600

750

513

400
200
0
UA

Fig. 3

STA

LTA

Viscosity value for UA, STA and LTA.

(a)Ageing Index
Table 2 shows the penetration aging index (PAI)
computed using AI equation. The table shows that thevalue of PAI decreased after STA and LTA, whichindicate that B-PU has a higher ageing resistance incomparison to B-B. The softening point ageing index(SPAI) is listed in Table 3 showing an increased value
due to the change in the structural molecules in thebitumen’s content of fraction during the ageing
process. Thus, the addition of PU improved thebitumen’s resistance to oxidative ageing [15]. Table
4 presents the viscosity aging index (VAI). It showsthat VAI decreased with the addition of PU, thus
reduce the ageing sensitivity.

(b)
Fig. 4

Atomic Force Microscopy test
The typical bee structure was clearly found in both
unmodified and modified sample with reduction off
bee lines with ageing condition. As stated by Lyne etal. [7] there are three phases observed in bitumen
namely the catana phase, the peri phase and the paraphase respectively as shown in Figure 5(a). The
catana phase represents the black line like a bee
structure that indicate the high and low of the
topography image, the peri phase that is outerpart tothe catana phase while the para phase is alongside theperi phase. In bitumen, the bee structure occurredbecause of the crystallization of the wax composition
as well dispersion of the molecule [16]. The existenceof various nonpolar alkane chains together with the
wax are the contribution factors to the ‘bee-likestructures’ appearance in bitumen [8].
Figures 6(a)-(f) and Figures 7(a)-(f) represent the
2D and 3D topography images of B-B and B-PU
before and after ageing, respectively, obtained from
AFM test. The presence of bee-like structures orcatana phase for UA sample can be clearly seen inaccordance with Fig. 6(a) and Fig. 7(a). This indicatesthat the addition of PU did not affect the bitumen beelike structures. The dispersion in the aged samples,

Table 2 PAI for B-B and B-PU
Bitumen
B-B
B-PU

STA
0.825
0.807

LTA
0.568
0.566

Table 3 SPAI for B-B and B-PU
Bitumen
B-B
B-PU

STA
1.029
1.080

LTA
1.129
1.175

Table 4 VAI for B-B and B-PU
Bitumen
B-B
B-PU

STA
1.462
1.084

Optical Microscopic for (a) B-B, (b) B-PU.

LTA
1.998
1.361

Morphological properties of Bitumen
Optical microscopic test
Figures 4(a) and (b) show the image of B-B and206

Catana
phase
Para
phase

SEE-Mie, Japan, Nov.10-12, 2022
Peri
phase

however, decreases remarkably, particularly for both
B-B and B-PU samples after ageing. This showed thatduring STA and LTA there was a great interaction of
the distributed domains in bitumen. It can be clarified
that oxidation leads to the reduction of the differencein chemical properties between the distributed
domains and the matrix during STA and LTA. The
domains can spread in the matrix gradually before
ageing, but not after ageing [17].
The topographic image in Fig. 7(c) and 7(e) showsthat after STA and LTA for the B-PU sample, thedimension and quantity of bee-like structures are
significantly reduced. The bee-like structures seem tofloat much and obviously spread throughout as seenin Fig. 7(e). In addition, with the inclusion of PU, atcertain points in STA and LTA, it is noted that thedimension of bee-like structures is reduced comparedto the B-B sample in Fig. 6(c). This shows that theaddition of PU and the hardening of bitumen fromageing have led to the substantial decrease in the beelike structure as well as the absence of the boundary.
This outcome is comparable to the research
performed by Zhang et al. [18] using AFM to perform
morphology analysis on unmodified and modified
organo-montmorillonite bitumen. The findings
showed that bitumen showed a 'bee-like' structure
and, with the introduction of the organomontmorillonite, the dimension of the 'bee-like'structures was reduced to some degree. Due to theincreased solubility of microcrystalline waxes (>C40)
and waxy molecules in bitumen during ageing, which
can impede their crystallization, the dimension andquantity of 'bee-like' structures have been reduced
after ageing.

(a)

(b)

(c)

(d)

(e)

(f)

Peri
phase
Para
phase

Catana
phase

Peri
phase
Para
phase
Catanaphase

1Fig. 6

2D & 3D topography image of B-B for (a)(b) UA, (c)-(d) STA and (e)-(f) LTA

Catana
phase
Peri
phase
Para
phase
(a)

(b)

(c)

(d)

(e)

(f)

Peri
phase
Para
phase

Catanaphase

Catana
Phase
Peri
phase

Para
Phase

Peri
Phase

Catana
phase
Para
phase

1

Fig. 5

Sample showing the catana phase, peri phaseand para phase in bitumen structure.
1

Catana
phase
Para
phase

2D & 3D topography image of B-PU for (a)(b) UA, (c)-(d) STA and (e)-(f) LTA

CONCLUSION

Peri
phase

(a)

(b)

(c)

(d)

The present study evaluates the effect of ageingon the physical and morphological properties of BPU and compares the results with those of
conventional bitumen. Result reveals that the additionof PU to B-B decreased the penetration value, whichshows that harder bitumen has been formed whilesoftening point value increased with the addition of
PU. This is consistent with the results of the

Peri
phase
Para
phase

Catana
phase

Peri
phase

Fig. 7207

SEE-Mie, Japan, Nov.10-12, 2022

penetration test, where stiffer bitumen increases themelting point of the bitumen. The AI for both
penetration and softening point indicate that the BPUs have higher ageing resistance in comparison to
B-B. Besides, viscosity test shows that the addition of
PU significantly increased viscosity value at 135 °C;
the lower VAI shows that addition of PU reduced theageing sensitivity of the bitumen. Image analysis
from optical microscopic test shows that noseparation occurred in the B-PU sample. This showsthat the sample has been homogeneously blended anduniformly dispersed during the mixing process. The
topography images from AFM test indicate that theinclusion of PU and ageing conditions has decreased
the bee-like structures of the bitumen, showing larger
dispersion in the sample.

Response Surface Methodology. Fuel, 2019,254.
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ACKNOWLEDGMENT
The authors would like to express their gratitude
to Ministry of Education Malaysia and Universiti
Pertahanan Nasional Malaysia for the financial
support
for
this
work
(FRGS/1/2020/TK0/UPNM/03/4).
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

PUSHOVER ANALYSIS OF RC FRAMES WITH SUBSTANDARD
BEAM-COLUMN JOINTS

1

Zaidir1, and Syafri Wardi2
Faculty of Engineering, Andalas University, Indonesia; 2Faculty of Engineering, Padang Institute ofTechnology, Indonesia

ABSTRACT
Recent earthquakes in developing countries showed that the failure of substandard beam-column joints often
contributes to heavy damage or collapse of reinforced concrete (RC) buildings. Static nonlinear pushover analysis
is one of the methods to evaluate the seismic capacity of RC frames/buildings. However, the pushover analysis
commonly neglects the failure at beam-column joints because of the complex behavior. In this study, a nonlinear
pushover analysis procedure considering the failure of exterior beam-column joints without shear reinforcement
is presented. Specifically, the performance limit is assumed as a point at the failure of beam-column joints fromthe literature of experimental study and a simplified backbone of joint shear stress-strain response. The proposed
analysis procedure is applied to one RC frame with substandard beam-column joints representing a collapsedbuilding due to a recent earthquake in Indonesia. The proposed analysis procedure is applicable to estimate theseismic capacity of RC frames considering the failure of exterior beam-column joints.
Keywords: Beam-column joint failure, Plastic hinge, Reinforced concrete, Seismic capacity evaluation

INTRODUCTION
The beam-column joints that do not satisfy therequirements of the standard for seismic detailingoften caused severe damage or collapse of RC
buildings, as observed in recent earthquakes indeveloping countries [1]–[3]. Figure 1 shows acollapsed RC building with failure on the beamcolumn joint, in which the joint area had no shear
reinforcement. The previous study by one of theauthors [4], [5] also showed that beam-column joints
without shear reinforcement still exist in newly built
construction in an area that had experienced
significant damage due to a past earthquake (Fig. 2).
These indicated that many stocks of RC buildings
with substandard beam-column joints exist in
developing countries in earthquake-prone areas.

Fig. 1

Fig. 2

Substandard detail of exterior beam-column
joint in construction [4].

The behavior and seismic capacity of existingbuildings need to be evaluated using non-linear
analysis, i.e. static nonlinear pushover analysis.
Pushover analysis of RC frames/buildings commonly
considers the nonlinear behavior of beam and column
members, assuming rigid beam-column joints.
However, this assumption may mislead the analysis
results in the case of substandard beam-column joints,
because the failure of the joint may occur.
Many literatures (e.g. [6]–[8]) have developed
detailed numerical models for the analysis of RC
beam-column joints. However, the models are noteasy to be used by a practical engineer. Therefore, thisstudy presented a simplified nonlinear pushover
analysis procedure to evaluate the seismic capacity ofRC frames with sub-standard beam-column joints,
assuming the performance limit of the frames is at the
failure of beam-column joints observed in previous
experimental studies from the literature ofexperimental study and a simplified backbone of joint
shear stress-strain response.

A collapsed building and its damaged
exterior beam-column joint [2].

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SEE-Mie, Japan, Nov.10-12, 2022

REVIEW ON PERFORMANCE LIMIT OF SUBASSEMBLAGE BEAM-COLUMN JOINTSWITH SUBSTANDARD DETAILS

numerical modeling.

Many experimental studies have been conductedon the seismic performance of substandard beamcolumn joints. This section focuses on theexperimental studies of exterior beam-column,
without shear reinforcement in which the joint shear
failure occurred before yielding of adjacent beam [1],[9]–[11]. This kind of failure exhibited brittle failure,
where the strength and the deformation capacity ofthe specimens significantly drop after the peakstrength was observed. Therefore, in the current
study, the drift ratio at the peak strength is assumed
as the performance limit for the exterior beamcolumn joint without shear reinforcement.
Table 1 summarized the drift ratio at the peakstrength of the sub-assemblage exterior beam-column
joint specimens without shear reinforcement from theliterature on experimental study. The data used intable 1 was restricted only to the case of subassembled exterior beam-column joint specimens
which were given static cyclic load at the beam end.
The data was also restricted for the specimens with
deformed bars with standard hooks; thus, anchorage
failure of beam reinforcement in the joint did notoccur.

Fig. 3

MODELLING OF SUB-ASSEMBLAGE BEAMCOLUMN JOINTS WITH SUBSTANDARD
DETAILS
A commercial finite element-based software
Seismostruct is used for modeling the structure. The
column and beam members are modeled using an
inelastic force-based flexure type element (Fig. 4),that used the force-based finite element formulation[13], [14] in modeling geometric nonlinearity andmaterial inelasticity of the member.

Table 1 The drift ratio at peak strength of subassemblage exterior beam-column joints
Specimen ID
as-is joint [9]Drift ratio at
peak strength
2,0%C1 [10]C2 [10]
Test#1 [11]

2,3%
1,8%
1,5%

J2 [2]

1,5%

Drift ratio at the peak strength in theexperimental database [12] (some notes in
the figure were added by authors)

Case study
1960s buildingin the US.
Poorly detailed joint.
The 1960s1990s building
in Italy.
Indonesianbuilding.

The experimental results in table 1 showed thatthe conservative value of drift ratio at peak load of thespecimens is 1,5%. This value is also confirmed as
the median value of drift ratio at peak joint shear
strength of unconfined exterior beam-column joint in
the database used in a study by Hassan [12], in whichmost of the specimens with joint shear failure had adrift a peak strength around 1% - 2% as shown in
Figure 3. In the figure, data for specimens with joint
shear failure is indicated by a red open circle and a
red solid circle.
In the next section, one sub-assemblage beamcolumn joint specimen representing an Indonesianbuilding with the drift ratio at peak strength of 1,5%
was used as the reference for verification of theFig. 4210

Modeling of columns and beams.

SEE-Mie, Japan, Nov.10-12, 2022

This study used a simplified modeling techniqueto model the failure of the beam-column joint in one
sub-assemblage beam-column joint specimen in theliterature, specimen J2 [2]. The joint panel was
idealized as rigid links with a rotational spring at thecenter of the joint, as shown in Fig. 5. This model wasused widely in the literature (e.g. [15], [16]).

Fig. 5

specimens exhibit a brittle failure after this point.
Therefore, the backbone curve for the post-peak
behavior is not considered.
The simplified backbone curve used in this study
is shown in Figure 7. The backbone of the tensilestress–shear response was converted into a momentrotation response by applying the equations by Celik
and Ellingwood [15].

Beam-column joint modeling.

The rotational spring at the center of the joint isdefined by the backbone of joint shear stress – shear
strain response. The backbone is generally controlled
by four damage states: cracking of concrete, pre-peakstrength, peak strength, and residual strength, asshown in Figure 6. These damage states were adopted
in many constitutive models in the literature (e.g.
[11], [17], [18]).

Fig. 5

Fig. 6

Backbone of shear stress-strain [11]Fig. 7

Simplified principal tensile stress–shear
deformation (adapted form [11], modified
by authors).

Backbone of the joint shear stress-strain anddamage states.

This study considered a backbone of the joint
shear stress-strain developed by DeRisi [11], asshown in Figure 6. The model was developed for
unreinforced exterior beam-column and verified withthe experimental database. The summary of the key
parameters defining the shear stress ( 𝜏𝑗 ) of the
backbone curve for the exterior beam-column withjoint shear failure before yielding of the beam isshown in Table 2. However, in this study, thebackbone curve is simplified as follows:
1. 𝜏𝑗,𝑚𝑎𝑥 is determined as a conservative value ofTable 2 Summary of the key parameters defining theshear stress (𝜏𝑗 ) of the backbone curve forthe exterior beam-column [11]Backbonepoint
Cracking(𝜏𝑗,𝑐𝑟 ) [22]Pre-peak(𝜏𝑗,𝑝−𝑝 )Peak(𝜏𝑗,𝑚𝑎𝑥 ) [23]0,42 √𝑓𝑐 ′ . This value is used widely in theliterature (e.g.[19]–[21]) as a conservative valueof shear stress of unreinforced exterior beamcolumn joint with beam rebars bent into joint.
2. The performance limit of the joint is assumed as
the first point when the maximum shear stress isachieved because the literature of theexperimental studies (e.g. [2], [9]–[11]) showedthat the unreinforced exterior beam-column

Residual

211

𝜏𝑗
𝑃

𝜏𝑗,𝑐𝑟 = 0,29√𝑓𝑐 √1 + 0,29 𝐴𝑗𝜏𝑗,𝑝−𝑝 = 0,85 𝜏𝑗,𝑚𝑎𝑥 if J-failureln(𝜏𝑗 , 𝑚𝑎𝑥 ) = −0,81 + 0,46 ln(𝑓𝑐)+ 0,50 ln(𝜏𝑑 ) + 0,68ln(𝐽𝑃)+ 0,62 ln(𝑇𝐵) − 0,25ln(ℎ𝑏 ⁄ℎ𝑐 )+ 0,08 ln(𝑀𝑅 ) + 0,14ln(𝜃)0,43 𝜏𝑗,𝑚𝑎𝑥

SEE-Mie, Japan, Nov.10-12, 2022

The modeling technique explained above wasapplied to a sub-assemblage beam-column joint
specimen from the literature [2] using static pushover
analysis. Figure 8 shows the comparison between the
numerical modeling with pushover analysis (red line)
and the experimental hysteretic curve (black line)from the literature.
The numerical pushover curve was close to theexperimental results, especially in estimating thestiffness. The numerical pushover curve also
conservatively estimates the peak strength and thedrift at the peak strength. This shows the soundnessof the proposed modeling procedure in simulating the
behavior of the sub-assemblage exterior beamcolumn joints without shear reinforcement in the
joint; thus, it can be applied for pushover analysis of
RC frames/RC buildings with such kind of details in
the joints.

Fig. 8Fig. 9A collapsed building due to the 2018 Palu
Earthquake and damage to the exterior
beam-column joints. (Photo courtesy of
Syafri Wardi)

Numerical pushover results vs experimental
hysteretic curve for specimen J2 [2]PUSHOVER ANALYSIS OF RC FRAMESWITH
SUBSTANDARD
BEAM-COLUMN
JOINTCase Study
A plane frame of a three-stories office building inIndonesia is examined in this study. The building
collapsed due to the 2018 Earthquake in Palu [24].
The photos from the field investigation in Figure 9
show that no shear reinforcement was installed in theexterior joint and buckling of column longitudinal
reinforcement was observed in the joint. This
indicated that the collapse of the building might occur
because of the failure of the joint.
The plane frame of the building and the details of
the structural member is shown in Figure 10. In thisstudy, the analysis is conducted only for one planeframe of the focused building, because the building
has a similar plane frame in both directions of thebuilding. The design strength of concrete used in thebuilding is 22.8 MPa for concrete. The specified yieldstrength of reinforcement is 390 MPa and 240 MPa
for longitudinal and transverse reinforcement,
respectively.

Fig. 10 Plane frame of the building and the details of
the structural member.
Analytical Assumptions
Seismostruct 2022 is used for modeling the planeframe. The assumptions for modeling are similar to
those in the modeling of sub-assemblage beamcolumn joint specimens in the previous section of thisarticle. Two models were analyzed in this study. The
first model is the frame without nonlinear modelingof the beam-column joint, in which the beam-column
212

SEE-Mie, Japan, Nov.10-12, 2022

joints were assumed as a rigid zone. The second
model is the frame with non-linear modeling of theexterior beam-column joints with the same
assumption as those in the analysis of the subassemblage beam-column joint in the previous
section. For the second model, interior joints are also
idealized as rigid links with a rotational spring, but
the rotational spring is as assumed as linear elastic.
The gravity load of the building was calculated
based on the Indonesian code [25]. The distributionof lateral load for pushover analysis was assumed as
an inverted triangular distribution and the analysis
was performed using a displacement control approach.
The performance limit of the frame was set to thepoint at the failure of the exterior beam-column joints.
The failure of exterior beam-column joints is morecritical than interior beam-column joints, asconfirmed in literature by Priestley [19].

CONCLUSIONSThis study presented a nonlinear pushover
analysis procedure considering the failure of exterior
beam-column joints without shear reinforcement, inwhich the performance limit of the frames is assumed
as a point at the peak strength of the joints. A
simplified numerical modeling assumption for thejoints was presented and verified to a sub-assemblage
exterior beam-column joint. The numerical pushover
curve had a good agreement in estimating thestiffness and conservatively estimates the peakstrength and the drift at the peak strength of the subassemblage exterior beam-column joint.
The pushover analysis procedure was applied to
one RC frame with substandard beam-column joints
representing collapsed buildings due to the 2018
Earthquake in Palu, Indonesia. Application of theanalysis procedure is applicable to estimate theseismic capacity of RC frames/buildings considering
the failure of beam-column joints, especially in thecase of the unreinforced beam-column joints using
deformed bars and beam rebars bent into joints with
sufficient anchorage length.

Analysis Results
The capacity curve (base shear vs roof
displacement) relationship of the first model withoutmodeling the beam-column joints is shown in Figure
11 The figure also includes the target displacements
at the performance level of life safety (LS) and
Collapse Prevention (CP) under the earthquake
hazard level of BSE-1E and BSE-2E, according to
ASCE 41-17 [26]. The capacity curve shows that theframe maintained its strength and ductility exceeding
the target displacement. This result misleads the
behavior and seismic performance of the building.

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Fig. 12 Base shear vs. roof displacement for theframe without joint modeling.
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

LIFE CYCLE ASSESSMENT IN THE PRODUCTION PROCESS OF
CRUDE PALM OIL (CPO) ON PALM OIL PLANTATION AND MILLS
Deffi Ayu Puspito Sari1, *, Malikhatun Nikmah1 and Nugroho Adi Sasongko 2
1
2

Universitas Bakrie; malikhatunnikmah97@gmail.com; deffiayu@gmail.com
National Research and Innovation Agency; nugroho.adi.sasongko@brin.go.id* Correspondence: deffiayu@gmail.com
Abstract

Life Cycle Assessment (LCA) could be used to assess the environmental impact. The purposes of this research
are: 1)to collect data of energy and material inventory used in oil palm plantations and mills of PT Y in 2019; 2)toanalyze the results of LCA and Crude Palm Oil (CPO) production with several impact categories such as Global
Warming Potential, Acidification, and Eutrophication, and 3)to provides the recommendation on reducing
emissions from CPO production based on the LCA results. To processed data, this research use SimaPro and excell
base with CML-IA Baseline method. The system boundary used is cradle to gate. The result showed that thebiggest emission comes from the Mills with Global Warming Potential impact value is 21,655,029 kg CO 2-eq/kg
CPO/year, Acidification value is 177,462 kg SO2-eq/kg CPO/year, and Eutrophication value is 6,958 kg PO4-eq/kg
CPO/year.
Keywords: oil palm plantations and mills; life cycle assessment; global warming potential; acidification;
eutrophicationand Eutrophication which can be harmful to theenvironment. Waste from palm oil mills is in the form
INTRODUCTION
of solid and liquid waste. Liquid waste comes fromOil palm plantations are starting to develop very
the sterilization and clarification process orquickly in Indonesia. Of the 34 provinces incommonly called Palm Oil Mill effluent (POME),
Indonesia, oil palm plantations are growing in 22
this POME can trigger climate change because it
provinces. This oil palm plantation can generate theproduces methane gas (Sari, Fadiilah, & Azizi, 2019).
largest foreign exchange for Indonesia. The potential
PT Y's palm oil mill has a production capacityof oil palm plantations in the economic field is veryof 60 tons of fresh fruit bunches/hour. Therefore, thislarge and Indonesia is the largest exporter of oil palm
research will be conducted on PT Y's plantations and(Masykur, 2013).
palm oil mills using the Life Cycle Assessment
Currently, the demand to land for oil palm
(LCA) method. The method can assess theplantations is increasing, this has led to theenvironmental impact associated with each product,
construction of many palm oil mills with large
process and activity (Ciambrone, 1997). Life Cycle
production capacities. To reduce the amount ofAssessment can be used to determine the amount ofagricultural land and production forests can use
energy, costs, and environmental impact caused bybiomass. Types of biomass, namely those from soil,
the stages of the product life cycle. Starting from theforest and cultivated plants (Falatehan & Sari, 2020).
time of taking raw materials until the product is
The most economical and reliable source of energy isfinished being used by consumers (Susanto, Santoso,hydroelectric power. Efforts to reduce dependence on& Suwedi, 2017). The reliability and adequacy of thethe use of fossil fuels can be done by increasing
object data inventory to be assessed is very influential
renewable energy production capabilities (Bahtiar,
for the LCA results. The Life Cycle Assessment
Falatehan, Sari, & Thamrin, 2019). Electrical energy(LCA) has four stages, namely the purpose and scope
can also be said to be energy that is very easy to use
definition stage, the inventory analysis stage, thebecause it is easy and efficient in converting electricalimpact assessment stage and the interpretation stage.
energy into other forms (Thamrin, Sari, &Setyoningrum, 2019).
MATERIALS AND METHODS
Palm oil mills produce emissions from eachprocess, one example of which is the emission ofThis research was conducted with the Life Cycle
greenhouse gases such as carbon (CO2), methane
Assessment (LCA) approach which has 4 stages,(CH4), nitrous oxide (N2O) and other gases (Sari,
namely data collection, life cycle inventory, life cycle
Mutaqin, Pawenary, & Majlan, 2019). In palm oil
impact assessment, life cycle assessment andmills, the production process, energy consumption,interpretation. The data used in this study are
and the waste degradation process can produce
secondary data obtained from routine company
greenhouse gases (Sari, Fadiilah, Azizi, & Pawenary,
reports in 2019. The method used is the CML-IA2019). Other environmental impact are Acidification
Baseline. This method is an LCA methodology215

SEE-Mie, Japan, Nov.10-12, 2022

developed by the Leiden University Center for
Environmental Sciences (CML) in the Netherlands
and released by CML in April 2013 and has beenstandardized by the IPCC.
In this study, using 3 impact categories, namely
Acidification, Climate Change, and Eutrophication.
The system limit used is Cradle to gate which covers
all processes from raw material extraction through the
production stage, used to determine theenvironmental impact of a product's production.
Analysis through the LCA approach by entering
inventory data derived from the cultivation process
and the processing of oil palm in the SimaPro andMicrosoft Excel software. Based on the analysis
carried out, environmental impacts will be generated
and alternative improvements in each production
activity will be obtained.

Life Cycle Inventory
The data obtained in this research are secondary
data obtained from routine reports of PT Y's
plantation and palm oil mill companies. The data arein the form of material and energy usage data in eachprocess of oil palm cultivation to produce crude palm
oil for one year, namely in 2019.
Table 1. PT Y's oil palm plantation and mill inventory
data for 2019.

ActivityType ofactivityTypeamount unit

NPK 15-7-24-1 618
Kg
Dolomite
293
Kg
Herbicide
Glyphosate
1414 liter
D 1048 AAF
3687 liter
D 8178 DT
1513 liter
D 8643 EJ
7087 liter
Transportation
BBM Energy
D 8808 EZ
5927 liter(Solar)D 8809 EZ
7223 liter
D 8807 EZ
8393 liter
Loader27600 liter
Excavator
14433 liter
PLN (20%)8648 kWhCummins 2
Electrical
Biomass (80%) 34591 kWh
EnergyPLN (20%) 808719 kWh
TurbineBiomass (80%) 3234876 kWh
Shell
12415304 kg
Fuel
Fiber
20560264 kg
Factory
Water energy
9747
m3
washing water
Biomass
Boiler feed
78177 m3
Process108626 m3
Domestic
113939 m3
Boiler78177 m3
TM
Maintenance

RESULTS
Palm oil plantation and mill PT Y
PT Y's garden is divided into 4 Afdeling.
Afdeling I area of 1,057 hectares, Afdeling II area of
709 hectares, Afdeling III covering 626 hectares andAfdeling IV covering 782 hectares. The land of PT
Y's oil palm plantations before being turned into oilpalm plantations was a rubber plantation. Meanwhile,geologically, the oil palm plantation area of PT Y is
included in the tertiary formation (S3) with clay rockand sandstone (Randa, 2011). The process ofcultivating oil palm at PT Y is as follows:

Fertilization

Life Cycle Impact Assessment
Impact Assessment is carried out on PT Y oilpalm plantations and mills by multiplying inventory
data with characterization factors. The multiplication
is done using SimaPro software and Excel base. The
following is a table of Life Cycle Assessment (LCA)
results on Global Warming Potential, Acidification,
and Eutrophication at PT Y's oil palm plantations andmill:

Figure 1. Flow chart of the process of oil palm cultivation
at PT Y (SOP of PT Y Oil Palm Plantation).

Fresh fruit bunches that have been harvested arethen transported by truck to the factory to be used as
crude palm oil (CPO). The following is a diagram ofthe process of processing fresh fruit bunches into
CPO at the PT Y palm oil mill:

Figure 2. The process of processing fresh fruit bunches into
crude palm oil at PT Y's palm oil mill (SOP of PT Y Palmoil processing).

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SEE-Mie, Japan, Nov.10-12, 2022

Table 2. Life Cycle Assessment (LCA) Results on Global Warming Potential, Acidification, and Eutrophication at PT Y.

ActivityType ofactivityType

NPK 15-724-1
TM Maintenance
Dolomite
Herbicide
Glyphosate
D 1048 AAF
D 8178 DT
D 8643 EJ
Transportation
BBM Energy
D 8808 EZ(Solar)D 8809 EZ
D 8807 EZ
LoaderExcavator
PLN (20%)
Cummins 2
Biomass(80%)
Electrical Energy
PLN (20%)
TurbineBiomass
(80%)
Shell
Fuel
Fiber
Factory
Water energy
washing
Biomass
water
Boiler feed
Process
Domestic
Boiler
Source: calculation results.

Impact factor
GWP
Acidification Eutrophication(kg CO2 eq/kg (kg SO2 eq/kg (kg PO4 eq/kg
cpo/tahun)
cpo/tahun)
cpo/tahun)
2384

12

4

13
7941
50733
20819
97517
81556
99388
115488379776
198598
8907

0
53
202
83
388
325
396
460
1512
791
51

0
38
48
20
92
77
94
109
358
187
40

1584

26

4

8329814763

3712

1481572439

343

899563

7616

2759

82795

248

59

66407092271796784821655029

1988
2762
2897
177462

475
660
692
6958

Fertilizationenergy needs in palm oil mills. The following are theresults of networking using SimaPro software in PT
Y's oil palm plantations and mills:

Table 2. shows the results of the multiplicationof inventory data for 2019 with the characterization
factor of the Global Warming Potential,
Acidification, and Eutrophication in PT Y's oil palm
plantations and mills which produce impact factor
values. In oil palm plantations which have the biggest
impact on the 3 impact categories are the use ofglyphosate herbicides, which is 7,941 kg CO2-eq / kg
cpo / year on Global Warming Potential, amounting
to 53 kg SO2-eq / kg cpo / year against Acidificationand 38 kg PO4-eq / kg cpo / year to Eutrophication.
Glyphosate type herbicides in oil palm plantations areused to eradicate weeds. Weed is one of the pests thathas the potential to reduce the productivity of oil palm
plants.
Whereas at the palm oil mill which has thebiggest impact is the use of boilers that is equal to21,655,029 kg CO2-eq / kg cpo / year on Global
Warming Potential, amounting to 177,462 kg SO2-eq/ kg cpo / year on Acidification and 6,958 kg PO4 -eq/ kg cpo / year against Eutrophication. Boilers areclosed vessels for turning water into high pressure
steam with the help of heating obtained fromcombustion. The fuel used by PT Y's palm oil mills isshells and fibers. Boilers are the main provider of

Figure 3. Results of SimaPro networking software on oilpalm plantations on Global Warming Potential (calculation
results).

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SEE-Mie, Japan, Nov.10-12, 2022

Figure 8. Results of SimaPro networking software on apalm oil mill for Eutrophication (calculation results).

Figure 4. Results of SimaPro networking software on oilpalm plantations on Acidification (calculation results).

The results of networking for oil palm
plantations show differences in the thickness of the
red line. The thickness of the line shows thepercentage of volume or material flow ratio, whichmeans that the process or stage has more use than theother processes and has the greatest impact on theenvironment.
DISCUSSION
After an LCA analysis, it is known that thebiggest impact produced from such an activity. The
following are the linkages between the activities of
the activities and their impacts, as well as providing
alternative improvements in the future.
Palm Oil Plantation
In oil palm plantations, herbicide use activities
are activities with the greatest environmental burden.
This herbicide use activity is an activity to eradicate
weeds. Where this weed will potentially cause adecrease in productivity of oil palm plants. Herbicidewith active glyphosate is widely used by farmers andplanters in Indonesia because it is effective,
inexpensive and safe.
However, excessive use of herbicides will cause
soil fertility is reduced and can give symptoms tofarmers such as eye irritation, blurred vision, burningor itchy skin, nausea, sore throat, asthma, difficulty
breathing, headaches, nosebleeds and dizziness. An
alternative that can be used to reduce the use ofherbicides is to pay attention to the dose used.
Farmers need to be educated to provide farmers withknowledge about the selection, preparation, handlingand application of herbicides on oil palm lands.
Palm Oil MillAt the palm oil mill, the use of boilers is theactivity with the greatest environmental burden. The
use of steam boilers has the greatest impact on global
warming potential, one example of which can cause
greenhouse gases. Climate change can cause losses
for farmers because it can cause land drought,
reduced water sources, crop failure and unpredictable
rainfall (Sari, Falatehan, Irawan, Sedana, & Rahim,
2018). Alternatives to reduce the use of this boiler
need further research.

Figure 5. Results of SimaPro networking software on oilpalm plantations for Eutrophication (calculation results).

Figure 6. Results of SimaPro networking software on palm
oil mills on Global Warming Potential (calculation results).

Figure 7. The results of SimaPro networking software on
palm oil mills against Acidification (calculation results).

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SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSIONSThe conclusions that can be drawn from thisstudy are: 1) Inventory data on oil palm plantations in
the form of fertilizer and herbicide use. Fertilizers
used during 2019 are NPK 15-7-24 with 618 kg and
293 kg of dolomite. The herbicide used was 1,414
liters of glyphosate type herbisisda; 2) Inventory dataon palm oil mills in the form of solar energy,
electricity, fuel and water energy; 3) The results of thelife cycle assessment of oil palm plantations and mills
which have the greatest impact on Global Warming
Potential, Acidification, and Eutrophication are theuse of boilers in the amount of 21,655,029 kg CO2eq/kg cpo/ year for the Global Warming Potential
impact factor, 177,462 kg SO2-eq /kg cpo / year for
impact factor Acidification and 6,958 kg PO4-eq/kg
cpo/year for impact factor Eutrophication; 4)
Hotspots that have the greatest impact on theenvironment on PT Y plantations are on the use ofglyphosate herbicides; 5) Hotspots that have thegreatest impact on the environment at the PT Y plant
are on the use of boilers.

REFERENCES

RECOMMENDATION
From this research, it can be given
recommendation that are expected to be useful forcompanies, among others, as follows:
The use of glyphosate type herbicide during
2019 has the greatest impact on the environment,
namely 7,941 kg CO2-eq/kg cpo/year for Global
Warming Potential impact factors, 53 kg SO2-eq/kg
cpo/year for Acidification impact factors and of 38 kg
PO4-eq/kg cpo/year for the Eutrophication impact
factor, so it is necessary to educate farmers about theuse of herbicides for oil palm land.
The use of boilers during 2019 had the greatest
impact on the environment, amounting to 21,655,029
kg CO2-eq/kg cpo/year for Global Warming Potential
impact factors, 177,462 kg SO2-eq/kg cpo/year for
impact factors Acidification and of 6,958 kg PO4eq/kg cpo/year for the impact factor Eutrophication,
it is necessary to use an air filter in the boiler chimney
so that emissions released are more environmentallyfriendly.
Recommendations for further research
The need for interrelation of all parties to ensure
the availability of complete data. Complete data in theform of material and energy use data and emission
loads released.
Further research needs to be done on
alternatives that can be used to reduce the impact on
the environment.

6. Sari, D. A. P., Fadiilah, D., Azizi, A., & Pawenary.
(2019). Energy Sector CO2 Emission In Palm Oil Mill.
Journal of Physics: Conference Series, 1364, 012003.
https://doi.org/10.1088/1742-6596/1364/1/012003

1. Bahtiar, R., Falatehan, A., Sari, D., & Thamrin, S.
(2019). Economic Impact of Microhydro Power Project
in
Jambi
Province,
Indonesia.
1–6.
https://doi.org/10.4108/eai.18-7-2019.2288677
2. Falatehan, A. F., & Sari, D. A. P. (2020).
Characteristics of Peat Biomass as an Alternative
Energy and Its Impact on the Environment. Solid State
Technology, 63(5), 4700–4712. Retrieved fromwww.solidstatetechnology.us
3. Masykur. (2013). Pengembangan Industri Kelapa Sawit
Sebagai Penghasil Energi Bahan Alternatif dan
Mengurangi Pemanasan Global. Jurnal Reformasi, 3,
96–107.
4. Randa, D. G. (2011). Penjadwalan Transportasi
Tandan Buah Segar dan Tandan Kosong Kelapa Sawit.
5. Sari, D. A. P., Fadiilah, D., & Azizi, A. (2019).
Utilization of palm oil mill effluent (Pome) for biogas
power plant; its economic value and emission
reduction. Journal of Advanced Research in Dynamical
andControl
Systems,
11(7),
465–470.
https://doi.org/10.31227/osf.io/bhfd9

7. Sari, D. A. P., Falatehan, F., Irawan, D. S., Sedana, G.,& Rahim, R. (2018). Mitigation and Adaptation
Analysis of the Climate Change Impact Using
Sustainable Livelihood Model. International Journal ofEngineering & Technology, 7(2.5), 108–114.
https://doi.org/10.14419/ijet.v7i2.5.13963
8. Sari, D. A. P., Mutaqin, P. A. Z., Pawenary, & Majlan,
E. H. (2019). Methane capture installation forgreenhouse gasses emission reduction in palm oil mill.
Journal of Advanced Research in Dynamical andControl
Systems,
11(7),
459–464.
https://doi.org/10.31227/osf.io/n5x3j
9. Susanto, J. P., Santoso, A. D., & Suwedi, N. (2017).
Perhitungan Potensi Limbah Padat Kelapa Sawit untuk
Sumber Energi Terbaharukan dengan Metode LCA.
JurnalTeknologi
Lingkungan,
18(2),
165.
https://doi.org/10.29122/jtl.v18i2.2046
10. Thamrin, S., Sari, D. A. P., & Setyoningrum, A. (2019).
Energi Baru dan Terbarukan.pdf (A. H. Tambunan,Ed.). Bogor: Universitas Pertahanan.

ACKNOWLEDGEMENT
This research has been funded by Ministry Education,
Culture, Research and Technology, Indonesia (PTUPT
Scheme), with contract number 234/E4.1/AK.04.PT/2021;
3585/LL3/KR/2021; 115/SPK/LPP-UB/VII/2021 andUniversitas Bakrie with contract number 130/SPK/LPPUB/VII/2021.

219

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

SEDIMENT EXPERIMENTAL STUDY ON BARK STRIPPINGPROCESS USING DRIFTWOOD MODEL
Kazuya WATANABE 1, Noritoshi SAITO 2 and Yoshitaka JIKEN 3
1
Graduate School of Engineering Science, Akita University, Japan

ABSTRACTDue to heavy rain such as typhoons, landslides and slope failures are caused, and driftwood occurs along withdebris flows. Since the bark of driftwood peels off during flow, elucidating the bark peeling process will lead tothe estimation of the source of driftwood. It is also considered to be useful for river management. In this study, adriftwood model was created using the bark of grown cedar (Cryptomeria japonica) and fixed in a waterway for
peeling experiments. As a result, when fresh water and earth and sand were circulated, the bark peeling rateincreased in the order of upstream side, side surface, downstream side due to the collision of earth and sand.
Furthermore, the separation rate on the riverbed side was higher than that on the water surface side. We confirmed
two cases, one in which the peeling progressed mainly in the place where the peeling occurred due to friction withthe earth and sand, and the other in which the bark mass peeled off.
Keywords: driftwood, bark, separation, cedar (Cryptomeria japonica), circular waterway, image analysis

INTRODUCTION
As the influence of the heavy rains such as
typhoons, the landslide and slope failure were caused.
As a result, driftwood occurs with a debris flow. Anddamage such as bank rip, flooded, the collapse of thehouse was caused in the downstream by driftwood
flowing down. The damage that it looks like it occurs
frequently [1] [2]. The driftwood is flowing down,
and the bark exfoliates. Elucidating a bark exfoliation
process may lead to an outbreak source estimate ofthe driftwood. It is useful for river management.
Previous studies were as follows. It was gotten
three main conditions about outbreak of the driftwoodcaused by hydraulic experiment and field survey witha debris flow [3]. In addition, the rotating cylinderelucidated segregation phenomenon of the driftwood
during a debris flow [4]. As stated above, the study ofdebris flow and the driftwood were conducted fromvarious viewpoints. Furthermore, it was consideredusing a plane circulating water channel about the bark
exfoliation process of the driftwood [5]. However, touse branch of the cedar (Cryptomeria japonica) as adriftwood model, there was the problem that the bark
was easy to exfoliate than real driftwood thinly.
In this study, made a driftwood model using thebark of the cedar which grew up enough. The
driftwood model was locked to the channel and thebark exfoliation experiment was carried out.

side view

upper

Fig. 1 The bark of the cedar (Cryptomeria japonica)

DRIFTWOOD MODEL(1) The choice of the tree class
It was the flood that occurred in Omono River of
Akita in July, 2017, and cedar deposited on a bridgeand farmland as driftwood [6]. A cedar was more
likely to flow out in Akita that had abundant cedar
forest [7] and used the bark of the cedar for adriftwood model in this study.
The bark of the cedar was shown Figure 1. The
cedar was a product in Akita-City Iwami, three of40~50 years old. It was 1m in width, 1m in height,
thickness 6.7mm and specific weight was 0.348 [8].
(2) Manufacture of the driftwood model
The driftwood model was made using except thenode. Driftwood model was shown Figure 2.
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SEE-Mie, Japan, Nov.10-12, 2022

bark
Core
Core
bottom
4.2

bark
bark

2.4

3.6

3.0
Core

side

Fig. 4

Grain size accumulation curve

Fig. 5plane circulating water channel

unit：cm

Fig. 2Driftwood model

10 mm

Fig. 3

Gravel and sediment at Babamegawa River(2) Experiment channel

The bark of the driftwood model was cut into a
strip of paper form and made a prism. (4.2*3.6cm inwidth, 17.0cm in height)
As a result of having carried out a preliminary
experiment using the driftwood model, it was difficult
to confirm the bark detachment by visual observation.
Therefore spray of the white was applied to the model
before an experiment to make an exfoliation point
clear. In addition, the model was applied thinly as
possible because there might be influence in
exfoliation when spray was too thick.

In this study, it was performed using a planecirculating water channel [5] about the bark
exfoliation process of the driftwood. Plane circulatingwater channel was shown Figure 5. It is 129.0cm inwidth, 49.4cm in depth of the whole waterway,
circumferential 280.0cm in length of the waterway,
81.5cm in length of the straight line, curve part58.5cm, waterway 11.5cm in width. The current
produces by drainage pump, but the water level of
ponding water area decreases to continue drawing
water. Therefore the overflow weir at the curve part
exit of the channel was made to ponding water area.
The system was such that the water was circulated
through. The pump to circulate water used three.

OUTLINE OF EXPERIMENT(1) Condition of sand(3) Method of experiment

Sand were gathered by Babamegawa River.
Image of sand was shown Figure 3 and grain size
accumulation curve was shown Figure 4. Sand wereconstructed by sand and gravel. Gravel was about
60%. In addition, it was maximum particle size
31.5mm, uniformity coefficient was 7.60.

The diminishing scale of the driftwood model
assumed it 1/7 from the ratio of a circumference ofthe bark and the length of four sides of driftwoodmodels. And the speed of the plane circulationwaterway is 0.91m/s and is equivalent to 2.4m/s in the221

SEE-Mie, Japan, Nov.10-12, 2022

conversion speed. However, as for the speed of thisstudy, it was the value that was slightly lower than adebris flow．Because the speed of the debris flow in
the actual phenomenon was 3~10 m/s [9]. The
driftwood model fixed it to the plane circulating water
channel (Figure 6). The setting side of the model
assumed a side of upper reaches, the downstream side,
the orthogonality direction side 1 and 2 for a current.
The current mixed for water and sand was producedfor 480 minutes. Then the image analysis of
exfoliating stopped a pump every 30 minutes to be
performed. The experiment performed 2 patterns. It
was a case only for fresh water and a case of thewaters and sand.

RESULT OF EXPERIMENT AND DISCUSSION
In this study, the experiment performed 2 patterns.
It was a case only for fresh water and a case of thewaters with sand. The exfoliation rate of the bark was
calculated, and the exfoliation situation was observed.
(1) Case only for fresh water
As the case that only for fresh water circulated,water level was experimented on as 18.0cm.
Relations of experiment time and the exfoliation rate
was shown Figure 7 and the exfoliation situation of
the driftwood model (the upper side) was shown
Figure 8. The exfoliation rate of upper reaches was
0.03% passed for 480 minutes and other sides were0.00%. In addition, the change except the exfoliation
including abrasion and the breaking was not seen
when looked at the side of the driftwood model ofupper reaches every 30 minutes. There was the sametendency to other three. Therefore, it was revealed
that the fluid power did not influence the bark
exfoliation.

(4) Image analysis
The image of each plane of driftwood model weretaken pictures. Then the area of the exfoliation was
calculated by image analysis. Exfoliation rate
calculated from Eq (1). The driftwood model was
evaluated from exfoliation rate.
𝑒𝑥𝑓𝑜𝑙𝑖𝑎𝑡𝑖𝑜𝑛 𝑎𝑟𝑒𝑎

𝑓𝑜𝑙𝑖𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑖𝑜 = ( 𝑑𝑟𝑖𝑓𝑡𝑤𝑜𝑜𝑑 𝑎𝑟𝑒𝑎 ) × 100(1)

Fig. 7
Fig. 6

The fixed situation of the driftwood model

Relations of experiment time and theexfoliation rate (fresh water)

Fig. 8 The exfoliation situation of the driftwood model222

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 9time(mim)

Experimental condition
0

60

120

Fig. 10 Relations of experiment time and theexfoliation rate
180

240

300

360

420

upper

side1

side2

riverbed

Fig. 11 The exfoliation situation of the driftwood model (fresh water and water with sand)
223

480

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 12

The time history of exfoliation rate (upper)

Fig. 14

Fig. 13

The time history of exfoliation rate (side1)

Fig. 15 Time history of exfoliation rate (riverbed)(2) Case of the waters with sand.

The time history of exfoliation rate (side2)

The exfoliation situation of the driftwood model
was shown Figure 11. Bark exfoliation occurred on
the upper side near a riverbed 60 minutes later, andexfoliation progressed to spread after it around thepoint where exfoliation occurred first. On the other
hand, the increase of the exfoliation rate was seen by
one piece of the bark exfoliating with the side 2 120
minutes later. Sand got into the gap of the bark whenobserved exfoliation point in detail. Therefore thepossibility that the bark exfoliation progressed wassuggested by not only the outside but also the insideby the small sand of the particle size.

Influence of the installation surface
Experiment condition at the waters with sand wasshown Figure 9. The depth of the water was 18.0cm
same as only fresh water ．The sand spread layer
thickness 4.0cm in the channel. Time history of
exfoliation rate was shown Figure 10. Exfoliation wasseen in the upper side and the side 2 soon after theexperiment start. As for the upper side where the sandcollided with most, it was 25.4% when exfoliation
rate 480 minutes later, as for the side 1 that drifted sothat the upper s side and sand after having collided
rubbed against the bark for 2.5%, the side 2 was
13.4%. Furthermore, as for the downstream sidewhich friction produced by the complicated basin
including the countercurrent [10] having been formed,
it was in 1.4%. It was revealed that the influence ofthe sand was dominant as for the bark exfoliation of
the driftwood to greatly vary in a detachment rate thana result of Figure 7.

Influence of the depth direction
The calculation of the exfoliation rate was carriedout with driftwood model as a riverbed and surface
side.
The time history of exfoliation rate on the upper
was shown Figure 12. A exfoliation rate rose 390
minutes later, and the surface of the water side
became 1.8% 480 minutes later, but a exfoliation rate224

SEE-Mie, Japan, Nov.10-12, 2022

Ministry of Education, Science, Sports and Culture,
Grant-in-Aid for Scientific Research (A),
（20H00256, So Kazama）.

rose to the riverbed side from after for 120 minutes,
and it was 23.7% 480 minutes later.
Time history of exfoliation rate on side1 wasshown Figure 13. The surface side, the increase of the
exfoliation rate was small together a riverbed side, as
for surface of the water side 0.4% of 480 minutes later,
the riverbed side was 2.0%. Although the exfoliation
rate was different, in comparison with a side to shownin Figure 12 of upper, the tendency that the
exfoliation rate on the riverbed side grew larger than
the surface of side were agreed. Because exfoliation
rate became around 2% on the surface side, the small
sand to float with a strong flow were a few, but it
became clear that it was a factor to cause exfoliation.
The time history of exfoliation rate on side2 wasshown Figure 14. As for 0.1%, exfoliation rate of theriverbed side, it was 13.3%, and exfoliation rate of thesurface side 480 minutes later was greatly different
from a result of the side 1 to show to Figure 14.
Time history of exfoliation rate on downstream
was shown Figure 15. As for 0.1%, exfoliation rate of
the riverbed side, it was 13.3%, and exfoliation rateof the surface side 480 minutes later was greatly
different from a result of the side 1 to show to Figure
14. Time history of exfoliation rate on downstream
was shown Figure 15. As for 0.4%, exfoliation rate of
the riverbed side, it was 0.1%, exfoliation rate of thesurface side 480 minutes later became small in four
driftwood models most both.

REFERENCES[1] Yuichi SUZUKI, Yasuharu WATANABE,
BEHAVIOUR OF DRIFTWOOD IN THE
SARU RIVER DURING TYPHOON NO.10,
PROCEEDINGSOFHYDRAULICENGINEERING, Vol. 48, pp.1633-1638, 2004.
[2] Ministry of Land, Infrastructure, Transport andTourism. Preliminary Figures for Summary of t
he earth and sand disaster caused by the July, 20
17 North Kyushu heavy rain <http://www.mlit.go.jp/river/sabo/h29_kyushu_gouu/gaiyou.pdf >(in Japanese) (accessed on July 1, 2022).
[3] Yoshiharu ISHIKAWA, Takahisa MIZUYAMA
and Makoto FUKUZAWA, Generation and Flow
Mechanisms of Floating Logs associated with
Debris Flow, Journal of the Japan Society of
Erosion Control Engineering, Vol. 42 No. 3(164),
pp.4-10, 1989. (in Japanese)[4] Kentaro Matsumura, Kazuki Saito, Toshiyuki
Horiguchi and Satoshi Katsuk, Segregation ofwater and gravel using large ball mill device withroughness bed, Japan Society of Civil Engineers,
Journal of structural engineering. A., Vol.62 A,
pp.1097-1110, 2016. (in Japanese)[5] JUNYATANIGUCHI,KAZUYAWATANABE,
NORITOSHISAITO:
EXPERIMENTAL STUDY ON PROCESS OF
EXFOLIATION FROM DRIFTYWOODS INFLOODATOMOTOGAWA
RIVER,
Proceedings of APD-IAHR Congress, 1-5-5,
2020.
[6] Toshinori
OGASAWAR
andYurikoMATSUBAYSHI, Report of the ResearchMission on the Heavy Rain Disaster of 2018,
Survey of the Omono River tributary Yodogawa
River, Japan Soc. of Civil Engineers, pp29-36,
2018.
[7] Third natural environment preservation basic
research, Vegetation working papers, Ministry of
the Environment, 7p, 1988.
[8] Yutaka ISHIMARU, Yuzo FURUTA and
Masaki SUGIYMA, Physics of wood, Kaiseisha
Press, 210p, 2017.
[9] Hiroshi IKEYA, Debris flow disaster, Iwanami
Shoten, 221p, 1999.
[10] Shoji FUKUOKA, Tomohiro MIYAGAWA and
Masaru TOBIISHIMeasurements of Flow and
Bed Geometry around a Cylindrical Pier,
PROCEEDINGSOFHYDRAULICENGINEERING, Vol. 41, pp.729-1734, 1997.

CONCLUSIONSIn this study, the driftwood model was madeusing the bark of the cedar which grew up and theexfoliation experiment circulated fresh water andwater with sand was performed. The conclusion wasshown as follows.
(1)As the case that only for fresh water circulated, it
was revealed that the fluid power did not influence
the bark exfoliation.
(2) Then only for fresh and water with sand circulated,
exfoliation rate grew large in order of upper side >side view > downstream side. In addition,
regardless of the setting side of the driftwoodmodel, exfoliation rate of the riverbed side was thetendency that became larger than surface side.
(3) From observation of the progress of the
exfoliation confirmed two cases, exfoliation
produced by the friction with sand and lump of thebark exfoliates.
ACKNOWLEDGMENTS
This research was partially supported by the2258th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

BUDGET PRIORITIZATION OF RURAL ROAD MAINTENANCE
USING THE INTEGRATED AHP – TOPSIS METHOD TO DECISIONSUPPORT SYSTEM.

1*Pawarotorn Chaipetch1, Chisanu Amprayn1 Paijit Pawan1 and Vatanavongs Ratanavaraha2
School of Engineering, Sripatum University, Thailand; 2Suranaree University of Technology, Thailand

ABSTRACTThe Department of Rural Roads (DRR) in Thailand is responsible for road maintenance of 48,974 kilometers.
The budget prioritization is primarily based on two factors: traffic volume and the international roughness index(IRI). The benefits of low-volume roads will not be enough to justify the benefit, many sections of rural roads with
low traffic volumes were ignored. As a result, road agencies are unable to effectively develop and maintain roads
within their responsibilities. A decision support system is necessary for decision makers to decide on the evaluationand strategy for overcoming budget constraints by identifying appropriate projects. The Analytical Hierarchy
Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodologies
were used in this study's decision support system to analyze and allocate performance scores to DRR’ decisionmaking process for road maintenance, as well as performance score ranking considering factors such as economic,
engineering, environmental, and social factors. The AHP method is used to determine each factor's weight, and
TOPSIS methodologies were used to analyze the performance score in order to select the most appropriate roadproject for maintenance and rehabilitation. Finally, the findings are expected to the decision-makers were able toidentify the most important roads from a large network of roads due to this prioritization and the suggested the
projects. Implementation of the project has become important for the state road network and reached at areasonable approach to the project selection as well as the best usage limited resources.
Keywords: Prioritization, AHP, TOPSIS, Low Volume Road, Decision Support System, IRI
INTRODUCTION

Any facility's performance degrades with time asa result of hard environmental conditions and several
inherent characteristics, as shown in fig. 1.
Maintenance planning used to be limited tocontingency planning in the case of an emergency,
resulting in excessively high maintenance costs. [7]Road accessibility allows people to be connected
to public facilities such as hospitals, schools, police
stations, temples, and transportation hubs.
Furthermore, road infrastructure contributes to abetter society, such as poverty reduction andeconomic development. [1] Communities candevelop local economies as transportation
infrastructure improves, allowing them access toresources, capital, goods, and the labor market. [2] In
addition, road improvements influence land use andmarket expansion, as well as encourage investment
and employment. [3]The Department of Rural Road (DRR) in Thailand
is responsible for road maintenance of 48,974
kilometers, which includes 2,563 kilometers ofconcrete, 45,868 kilometers of asphalt, and 542
kilometers of gravel. [4] The deterioration of
pavement is in exponential function and is affected bypavement age, traffic volume, the volume of heavy
trucks, rainfall, and topographical gradient. [5,6]DRR allocated funding for road network maintenanceby road strategies and the nation's development
policy, including strategies for logistic and integrated
transport systems, tourism, reducing traffic
congestion in urban areas, and developing
transportation to strengthen competitiveness and rural
economic development.

Time

Fig. 1

Performance with time for different
maintenance scenarios.

Maintenance is necessary throughout the facility'splanned service life to prevent loss of performance at
acceptable levels. The efficient and planned
execution of maintenance actions also helps to asustainable built environment by reducing thedemand for new facilities and optimizing the use ofresources available. In addition, the planning andimplementation of these strategies must be cost226

SEE-Mie, Japan, Nov.10-12, 2022

effective without compromising the users' safety andcomfort, and a maintenance program must be
established on a short, medium, and long-term basis.
Because maintenance budget is constantly
limited, it is necessary to prioritize and select thealternatives that are most aligned with the asset
management governance's objectives, which in thecase of infrastructure, should also reflect publicdemands. It can be shown in many countries that
present maintenance spending was much less thanwhat is required to keep public ownershipinfrastructure in good condition. The annual funding
for maintenance in the European Union (EU), which
would ensure that road infrastructure functions
properly, is estimated to be between 1% and 2% of
the total asset value. Particularly in the budget
allocation of DRR, it was found that DRR was
allocated a budget that was less than the requirement

Fig. 2for maintenance in the past 10 years. The budget istypically allocated 60-65 percent of the total budget
requirement as shown in fig. 2. [4] As a result, theallocated budget for maintenance needs in each area,
especially the low-volume roads, may be insufficient
or inadequate.
The budget prioritization is primarily based on
two factors: traffic volume and the internationalroughness index (IRI). The benefits of low-volume
roads will not be enough to justify the benefit, many
sections of rural road with low traffic volumes wereignored. As a result, road agencies are unable toeffectively develop and maintain roads within their
responsibilities. A decision support system isnecessary for decision makers to decide on theevaluation and strategy for overcoming budget
constraints by identifying appropriate projects.

The Annual Budget Report for Maintenance of Department of Rural Road.
(Department of Rural Road, 2020)

Due to the widespread road network, aconsiderable investment in maintenance is required tomaintain a acceptable level of service. However,
because the funding is limited, DRR must plan
carefully to define road priorities and allocate thebudget proportionally for maintenance in roadstrategies and the nation's development policy.
A decision support system is required to provide
support in the decision-making process for a moreobjective and on-target evaluation of road priority.
This study had to use a performance score to evaluate
and allocate budget to DRR's road maintenancedecision-making process, as well as the addition offactors such as cost and financial aspect, roadcondition, and socio-economic aspect, among others.
The Analytical Hierarchy Process (AHP) and theTechnique for Order Preference by Similarity to Ideal
Solution (TOPSIS) were used as analytical methods
in this research. The AHP method is used todetermine each factor's weight, and TOPSIS

methodologies were used to analyze the performance
score in order to select the most appropriate roadproject for maintenance and rehabilitation. Moreover,
it is expected that findings will assist thepolicymakers
and agencies
in developing
transportation appraisal methods that are both costeffective and beneficial to the region.
OBJECTIVE
The study's objective was to use the AHP andTOPSIS to analyze and allocate performance scoresby considering economic, engineering, and social
factors to prioritize road sections for appropriate
budget allocation on Thailand's Department of Rural
Roads' Strategic Driving Plan.
A LITERATURE REVIEWThe decision-makers in Multi-Criteria Decision227

SEE-Mie, Japan, Nov.10-12, 2022

•
•
•
•
•
•
•

Making (MCDM) problems are provided with a set ofalternatives and various types of criteria, and each one
has varying degrees of importance. As a result, multicriteria enables decision makers to weigh various
criteria for a large number of options at the same time.
To put it differently, MCDM analysis assists decision
makers in making better decisions and selecting thebest possible options from current candidates basedon a variety of criteria. [8]Population density.
Tourist spots.
Government office.
School, colleges, and university.
Hospital.
Business center and market.
Industrial area and warehouse.

ANALYSIS
Factor to Prioritization Road Maintenance
Weighting the evaluation criteria
Criteria are qualitative and quantitative properties
that performance of the road maintenance is evaluatedaccording to factor. This study evaluated the factor
that should be considered when prioritizing roadmaintenance, and it is divided into three groups basedon the findings of a literature review. [9,10]

Pavement Maintenance Prioritization Using Multi– criteria Decision Approach. The main multi –criteria decision making approach is the AHP which
was a structured method for organizing and analyzing
complex decisions that are based on math andpsychology. It was created in the 1970s by Thomas L.
Saaty [11] and it has been extensively studied andrefined since then.
It is a precise method of quantifying the weights
of decision criteria. Pair-wise comparisons are used
to estimate the relative magnitudes of factors basedon individual experts' experiences. Using a speciallydesigned questionnaire, each respondent compares
the relative importance of each pair of items. With
these rating values as elements of matrix aij of thecriteria i and j (where aij are the geometric mean valueof responses), a pairwise comparison matrix A has
been developed as follows Eq. (1)Economic factor
It is an evaluation of all of the costs and benefitsof projects to determine their monetary value. The
most important monetary benefits are reduced vehicle
operating costs, travel time savings, and accident
reduction cost compared with maintenance andrehabilitation cost. As a result, the benefit-cost ratio
must be greater than one.
Engineering factor
It's a direct factor in the design, management,
maintenance, and rehabilitation of a road, and it
includes physical, functional, distress, condition,connectivity, and accident data. For example,• International Roughness Index (IRI) is astandardized roughness measurement used todefine as a serviceability.
• Traffic Volume and Volume of Heavy truck.
• Volume Capacity Ratio (V/C ratio).
• Lifeline Road is a way of transportation forwhich there is no substitute or for which thesubstitute requires a significant increase intime or money. It has a significant impact on
a community's social or economic viability,
especially in a disaster situation.
• Connectivity to the road network represents
the significance of a road about the existingroad network, which may include national
highways, rural roads, and local roads.
• Accident data.

𝟏

𝐚𝟏𝟐 … 𝐚𝟏𝐧
𝟏 … 𝐚𝟐𝐧𝐀 = 𝐚𝟏𝟐… … …. …
𝟏
𝟏
… 𝟏 ]
[
𝟏

𝐚𝟏𝐧

(1)

𝐚𝟐𝐧

The next stage is to evaluate the weight of each
evaluation criterion after the criteria have been
identified. The relative and overall importance of a setof criteria is indicated by their weight compared to allother criteria. As a result, it is an important part of theanalysis. The value of such weights is difficult toascertain because the requirements are given inseveral measurement units. In this regard, reasoning,
and the use of tried-and-true elicitation procedures aid
in determining the weights' values. When experts
have in-depth knowledge of the criteria, including
their relative values and the connections between
them, the weights are set in accordance with theirprofessional judgements.
In this study, the weight assigned to the employed
criteria are determined by the AHP as described indetail by Chaipetch et al. (2021) [12], that was
purposive in the authority of budget planning andprioritization on road maintenance of decision –making authority on planning policy, which is 20
respondents.
Their values are presented in Table 1. It can beSocial factor
It’s a direct factor that is related to social,environmental, land use, community area, andattractive point of Interest within 2 kilometers on bothsides of the road. As an example,
228

SEE-Mie, Japan, Nov.10-12, 2022

seen that facility rating is considered the mostdecision process.
important factor to be taken into account in the
Table 1 Summary of the analysis of Priority Factor by AHP method.
LIS
TCA
Priority
Priority
Factor/Strategic
Value
Value
27
27
Economic (B/C)
46
40
Engineering
29
28
IRI
V/C Ratio (VC)
17
24
Traffic Volume (TV)19
21
The volume of Heavy Truck (HV)
21
Lifeline (LL)
Connectivity to the road network (CN)23
24
Accident data (ACC)2031Social25
32
Population density (PPD)
19
29
Tourist spots (TS)18
20
Business Center (BC)23
26
Hospital (HOS)
Industrial Area (INA)
40
25
𝑥11
𝐷 =[ ⋮
𝑥𝑚1

Ranking and Prioritization
TOPSIS, an MCDM model developed by Hwang
and Yoon in 1981 [13], is an ideal point technique thatranks alternatives according to their proximity to thepositive ideal solution and distance from the negative
ideal solution. This method is rational, intuitive, andrelatively easy to comprehend; it also lacks the strictassumptions of other MCDM models and provides a
cardinal value. The general step of the TOPSIS
method includes alternative selection; defining
evaluation criteria; weighting the evaluation criteria;
normalizing the criteria value; ranking; andprioritization of alternatives.
The selected item will be ranked based on a value
so that the alternative with shortest distance with an
ideal positive solution is the best alternative item.
Alternative with bigger score is the best to choose.
The TOPSIS method is based on the Euclidean
distance-based idea of proximity to the ideal
solutions. In other words, alternatives are suggested
as the best options that are close to both the positive
and the negative ideal solutions at the same time or in
the opposite direction. The collection of optimal
performance values for each criterion represents theideal solution. The following methods are usedsystematically in the TOPSIS methodology toevaluate and prioritize road maintenance.
1. The process begins with the formation of adecision matrix D in Eq. (2), which is arectangular matrix mn, where m is the numberof alternatives, and n is the number of criteria.
For all elements of the decision matrix to be
expressed in dimensionless size, it is necessary
to normalized the matrix using the Eq. (3).

𝑟𝑖𝑗 =
2.

𝑥1𝑛
⋮ ]
𝑥𝑚𝑛

𝑥𝑖𝑗

(2)

(3)

2
√ ∑𝑚
𝑖=1 𝑥𝑖𝑗

𝑟11 𝑤1⋮
𝑟𝑚1 𝑤1⋯ 𝑟1𝑛 𝑤𝑛⋱
⋮ ]⋯ 𝑟𝑚𝑛 𝑤𝑛(4)

Determine both positive and negative ideal
solutions. The best performance value of eachcriterion, as shown in Eq. (5), provides the
positive ideal solution (B+). Whereas the negative
ideal solution (B-) is determined from the lowest
performance value as indicated in Eq. (6). The
calculation's result is shown in Table 8,

𝐵+ = 𝑚𝑎𝑥 {𝑣1+ , 𝑣2+ , . . . , 𝑣𝑖+ , . . . , 𝑣𝑛+ }(5)

𝐵− = 𝑚𝑖𝑛{𝑣1− , 𝑣2− , . . . , 𝑣𝑖− , . . . , 𝑣𝑛− }

(6)

4.

229

⋯
⋱
⋯

CED
Priority
Value
24
45
20
17
15
14
27
27
35
25
26
27
22

Calculate weighted normalized decision matrix(vij). The weight of the criterion (wj) from the
AHP technique is multiplied by the normalized
matrix(rij),
which
is
shown
in
Eq (4). The weighted normalized decision
matrix is showed in Table 2.
𝑣 =[

3.

TSM
Priority
Value
22
43
23
13
21
16
25
25
33
17
40
23
20

Calculate the Euclidean distance between ideal
solutions. The closeness of each alternative to thepositive ideal solution can be measured by the ndimensional Euclidean distance using Eq. (5).
Similarly, Eq. (6) indicates the separation of eachalternative from the negative ideal solution isSEE-Mie, Japan, Nov.10-12, 2022

shown in table 3.
𝑆𝑖+ =√∑𝑛𝑗=1(𝑣𝑖𝑗 − 𝑣𝑗+ )2

𝑆𝑖− = √∑𝑛𝑗=1(𝑣𝑖𝑗 − 𝑣𝑗−)2

Table 2 Example of the weighted decision matrix of each road maintenance section
Road
Km.
B/C
VC
TV
HV
CN
ACC
PPD
TS
ID
AY.
7 - 8 0.0019 0.0002 0.0001 0.0001 0.0004 0.0000 0.0002 0.0001
2005
SP.
4 - 5 0.0181 0.0020 0.0019 0.0011 0.0047 0.0000 0.0018 0.0002
4002
CM.
2 - 3 0.0029 0.0001 0.0001 0.0001 0.0003 0.0003 0.0001 0.0000
3002
NS.
4 - 5 0.0003 0.0003 0.0002 0.0000 0.0003 0.0000 0.0002 0.0000
3022
SK.
2 - 3 0.0160 0.0002 0.0004 0.0007 0.0004 0.0000 0.0001 0.0000
2017
AD.
5 - 6 0.0061 0.0002 0.0002 0.0002 0.0003 0.0000 0.0002 0.0000
3072
Table 3 Positive – ideal (B+) and negative – ideal
solution (B-) for each criterion
Criterion
BB+
B/C
0.00000.0181VC
0.00000.0025TV
0.00000.0023
HV
0.00000.0059CN
0.00040.0000ACC
0.00000.0048PPD
0.00000.0018TS
0.00000.0019BC
0.00000.0052INA
0.00000.0111
5.

BC

INA

0.00000.00100.00430.00940.00000.00000.00000.00030.00040.00010.00000.0002

critical to select values that represent both a positive
and a negative ideal solution. Based on these data, then-dimensional Euclidean deviation from the positive
and negative ideal points is calculated. The relative
distance from the ideal solution gives a ranking list of
sections of the road network according tomaintenance priorities. The best alternative is the one
whose value of the relative distance to the alternativeis close to 100, while the other alternatives are ranked
in descending order.
DISCUSSION AND CONCLUSION
Because maintenance budget is constantly
limited, it is necessary to prioritize and select thealternatives that are most aligned with the asset
management governance's objectives, which, in thecase of infrastructure, should also reflect publicdemands. Particularly in the budget allocation of the
DRR, the budget is typically allocated 60-65 percentof the total budget requirement. As a result, theallocated budget for maintenance needs in each area,
especially the low-volume roads, may be insufficient
or inadequate.
In this study presented a methodology overview
on the use of multi-attribute decision making using
AHP and TOPSIS for the prioritization of roadmaintenance section alternatives. By considering
economic, engineering and social factor, the approachenable decision makers to capture the complex roadmaintenance prioritization procedure, in a moreobjective way for example based on DRR’ Strategic
Driving Plan.
As it was mentioned, TOPSIS method is based on
aggregating function that representing the closenessto ideal solutions and the remoteness from thenegative ideal solution simultaneously or reverse. In
this study, the “similarity index” was defined by
combining the proximity to the positive – ideal.

Calculate similarity indexes (Ci) implies therelative closeness to the ideal solution and it will
be used for the prioritization of road maintenance.
It is obtained by Eq. (7) and range in the intervalfrom zero to one hundred. Prioritizing the roadmaintenance section list is made with respect to Ci
values in descending order. The Euclidean
deviation, the relative distance of alternatives
from ideal solutions, and the final rank ofmaintenance priorities in the first iteration are
shown in Table 4.

Ci = Si+ / (Si+ + Si-)

(6)

(5)

(7)

Table 4 Example of S+, S- and Ci of each roadmaintenance section
Road IDKm.
SS+
Ci
AY. 2005
7-8
0.0022 0.0202 9.7609
SP. 4002
4-5
0.0689 0.0659 51.1058
CM. 3002
2-30.0003 0.0222 1.4617
NS. 3022
4-50.0006 0.0219 2.5062
SK. 2017
2-3
0.0255 0.0236 51.9323
AD. 3072
5-6
0.0061 0.0175 25.7195
When using the TOPSIS method to calculate, it is230

SEE-Mie, Japan, Nov.10-12, 2022

The results of this study are expected to assist
policymakers
and agencies
in developing
transportation appraisal methods that are both costeffective and beneficial to the region. The similarity
index, comprising of thirteen different indexes,
helped in identifying the priority of road maintenancethat will result in a better road network system as awhole and is vital to the socio-economic growth of
the region. The economic factor reflects the value of
an investment. Second, the engineering factors
provide network connectivity and ensure traffic
continuity. Transporting goods and services andmaking public services and attractive places moreaccessible increases the quality of traffic flow andcongestion, particularly in urban areas. Finally, social
factors have a variety of socioeconomic benefits
associated with their development; for example,
increased economic activity in terms of connectivity,
accessibility, regional growth, and a key componentof rural development, such as public service access,which is important for both goods movement andlabor markets and is a contributing factor to higher
income.
The decision-makers were able to identify themost important roads from a large network of roads
due to this prioritization method and the suggested
phasing of the projects. Implementation of the project
has become important for the state road network
because of the strategic value of the identified roadsections, improvement treatments, and theirsatisfactory feasibility results. The decision-makers
reached at a reasonable approach to the project
selection as well as the best usage limited resources
due to the screening process of the road sections.

University, Bangkok, Thailand.
[3] Amornchaisakda C., and Subsompon W.,
Analytical Framework of Road Serviceability
Level Corresponding to Road Strategies,
Proceeding of the 14th National Civil Engineering
Convention, Engineering Institute of Thailand,
2009, pp. 635-642.
[4] Department of Rural Road, Annual Report of
Bureau of Road Maintenance, 2020, Thailand.
[5] Subsompon W., et. al., Road Deterioration Model
based on International Roughness Index (IRI),
Proceeding of the 6th National Civil Engineering
Convention,
Engineering
InstituteofThailand,2000, Bangkok Thailand.
[6] Subsompon W., and Chaipetch P., Work
Estimation Model for Pavement Routine
Maintenance, Research and Development Journal,
Vol.21, No.4., 2010, pp. 57-64.
[7] Miyamoto A., Konno M., Nakmura H., andBruhwiler E., Maintenance plan optimization
system for existing concrete bridge groups,
Structure and Infrastructure Engineering, Vol.2,
No.2, 2006, pp. 91-115.
[8] Teng J., and Tzeng G., A multiobjective
programming approach for selecting nonindependenttransportation
investment
alternatives, Transportation Research Part B:
Methodological, Vol.30, No.4, 2015, pp. 291-307.
[9] Moya M., Gallego E., Garcia A. I., and Ayuga F.,
A Proposed Methodology for the Management of
Low-Volume Roads in Spain, The Baltic Journalof Road and Bridge Engineering, Vol. 6, No. 3,
2011, pp. 153-162.
[10] Menendex J. R., Budget Allocation Planning for
Small Road Systems in Peru, Proceedings of the25th World Road Congress - Seoul 2015: Roads
and Mobility - Creating New Value fromTransport, 2015.
[11] Satty, L. T., Fundamentals of Decision Making
and Priority Theory with The Analytic Hierarchy
Process, 2014, RWS Publication, USA.
[12] Chaipetch P., Amprayn C., Pawan P., andRatanavaraha V., Analytical of multi-criteria
approach for identifying the weight and factor of
rural
road
maintenanceprioritization,
International Journal of GEOMATE, Vol.22,
Issue 91, 2021, pp. 70-79.
[13] Hwang C., and Yoon K., Multiple attributedecision making: methods and applications: astate-of-art survey, 1981, Springer, USA.

ACKNOWLEDGMENTS
I would like to thank the Bureau of Road
Maintenance, Department of Rural Road and Centerof Excellence in Infrastructure Management,
Chulalongkorn University for their valuable data,expert opinion, and constructive suggestions.
REFERENCES[1] Walle D. V. D., Choosing Rural Road
Investments to Help Reduce Poverty, World
Development, Vol.30, No.4, 2002, pp. 575 – 589.
[2] W. Sangthammkijkul, “Determining Rural Roads
Importance Degree”, M.S. Thesis, 2014,
Department of Civil Engineering, Kasetsart

231

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FIXATION OF SOYBEAN EXTRACT METHOD FOR BIOCATALYSTIN CALCITE PRECIPITATION METHOD AND ITS APPLICABILITY
AS A SOIL IMPROVEMENT TECHNIQUE
Heriansyah Putra1*, Baiq Heny Sulistiawati 2,3, Hideaki Yasuhara2, Minson Simatupang4, and Dede Heri
Yuli Yanto5
1
Department Civil and Environmental Engineering, IPB University, Bogor, 16680, Indonesia
2
Department of Civil and Environmental Engineering, Ehime University, Matsuyama, 790-8577, Japan
3
Faculty of Civil Engineering, State Polytechnic of Semarang, Semarang, 50275, Indonesia
4
Department Civil Engineering, Halu Oleo University, Kendari, 93232, Indonesia
5
Research Center for Applied Microbiology, National Research and Innovation Agency (BRIN), Bogor,
16911, Indonesia
ABSTRACTThis study evaluated the extraction method of soybean as a plant-derived urease enzyme. The soybean powder
was prepared in a suspension and extracted in two different ways, namely filtered and centrifuged, to separate theparticle and solution and thus obtain the purified soybean solution. The efficacy of purified soybean as the
biocatalyst was evaluated using a test-tube experiment to obtain the hydrolysis rate of urea and production of
precipitated materials. The unconfined compression strength (UCS) tests evaluated its effect on soil strength atvarious curing times. The highest hydrolysis rate was obtained using 50 g/L of soybean extract in both extraction
methods of the centrifuge and filtered with the rate of 1100 u/g and 500 u/g, respectively. The maximum
precipitation ratio of 100% was achieved using a soybean concentration of 20 g/L, and thus constantly, even thesoybean concentration was increased. This study shows that both extraction methods result in a similar UCS value
ranging from 300 to 400 kPa. In conclusion, the soybean concentration of 20 g/L prepared by a simple extraction
method of filtration has a great potential to apply in the calcite precipitation technique for soil improvement.
Keywords: Calcite precipitation, Centrifuged, Filtered, Soil improvement, Soybean extract

INTRODUCTION

promote the advantages of less energy during the
production process, such as the calcite precipitation
methods [17].
Calcite precipitation methods are the bio-grout
technique that utilizes the reagent and bio-agent toproduce calcite crystal after the biochemical reaction[18], [19]. Many previous studies have investigated
the applicability of this technique using the catalyst
derived from bacteria and purified enzyme tohydrolyze the urea and thus, promote the carbonate
ion [20]–[22]. The use of bacteria as bio-agent in the
calcite precipitation method has several limitations,especially related to controlling the bacteria growthand its activities [22], [23]. Yasuhara et al. [23] utilize
the purified enzyme extracted from jack bean insteadthe bacteria called enzyme-induced calcite
precipitation (EICP). These methods promoted thesignificant improvement of soil strength parameters
and were applied for various purposes such asliquefaction prevention, erosion control, and bearing
capacity improvement [10], [24]. However, jack beanurease is reported as ineffective material due to its
high production cost caused by the high purity levelof the urease enzyme [25]–[27]. Using urease enzyme
extracted by jack bean consumed about 90% totalmaterial cost to produce the calcite solution [13], [14],[26].

In recent years, many soil improvement
techniques have been developed for their application
to various soil problems, such as geotextile [1], [2],aggregate piers [3], [4], deep soil mixing [5], [6], andgrouting with chemical compounds [7], [8]. A variety
of substances can be applied to chemical grouting,consisting of cement, lime, or other chemicalsolutions, depending on the stabilization and soil’s
characteristics. Recently, bio-grout-based ground
improvement practices have been proposed as apotential and effective technique, especially for soil
strengthening under the existing building [9]–[11].
Bio-grouts are produced by various mineralformations caused by chemical reactions, managed
and controlled through biological activities [12].
However, these techniques are related to major
environmental issues such as CO2 emissions and highenergy costs for production and applications [13],[14]. Furthermore, the reagents for bio-grout are
produced at relatively low temperatures compared toordinary cement that involves heating ingredients totemperatures up to about 1500oC [15], [16]. Therefore,
many alternative methods and materials of biogrouting have been proposed to extend its
applicability, reduce the environmental impact, and232

SEE-Mie, Japan, Nov.10-12, 2022

Several studies using the urease enzymes of plantorigin to replace the jack bean urease enzyme havebeen developed in recent years, such as legume
varieties from melons, flask, the pine family,
watermelon, pumpkin, and soybean [12], [28]–[30].
A mixture of urea and crude extract of watermelon
seeds that produces a reagent solution can effectively
produce the deposition of the calcium phosphate
compounds [30]. After a curing time of 28 days, amaximum UCS of 125.6 kPa was achieved by thismethod [30]. Recently, the examination of soybean
extract for the source of urease enzyme wasconducted [27], [31], [32]. The UCS strength oftreated soil was increased by more than 100% with asingle injection [26]. Pratame et al. [26] used thecentrifuged method to extract the soybean andcollected the purified soybean solution, thus mixing itwith the reagent to produce the calcite precipitation.
However, using the centrifuged method for large
applications is challenging due to its quantity andtime-consuming.
This work evaluates the applicability of soybean
powder as the replacement of commercial urease
enzyme with two extraction methods, namely
filtration and centrifugation. The experimental work
included the extraction of soybean and testing thehydrolysis rate of urea and CaCO3 precipitation. In
addition, XRD tests were used to verify the
microstructures of the deposited materials to observe
the effects of soybean crude extract on the substanceof the precipitated materials. Finally, the selectedconcentration of reagent solution in both extraction
methods is applied to the soil samples and cured forvarious curing times prior to the unconfinedcompressive strength (UCS) tests.

centrifuged and filtered method. The centrifuges
process was conducted following the method
proposed by Gao et al. (2019) with a rotation rate of
3,000 rpm for 15 minutes. Meanwhile, in the filtration
method, the soybean solution was filtered using sieve
No. 200 (0.0075 mm). The purified soybean solution
was obtained and thus, prepared for mixing with thereagent solution composed of urea and calcium
chloride.

MATERIALS AND METHODS

The calcite precipitation was conducted in clear
test tubes to assess the amount of the precipitation
mass as a result of the chemical reaction of the reagent
and biocatalyst of soybean extracts. The solution ofreagent and the extract of soybean were preparedseparately and mixed thoroughly with distilled water
to a total volume of 30 mL for each sample. The
soybean solutions were prepared in two extract
methods, namely centrifugation and filtration. The
tubes containing the improving solution were treatedat room temperature for five days to allow for the
precipitation process.
The amount of precipitation was examining thenumber of the particles remaining in the tubes.
Firstly, the tube was filtered using a filter paper No
40 (size 0.02 mm) and dried at 60℃ for 24 h toeliminate the water and obtain the precipitatedmaterial. Next, the mass of the deposited substance
was assessed by associating the mass of the deposited
substance stored in the test tubes with that residing on
the strainer paper. Two similar tests were performed
for each substance to verify for a duplicate. In thisHydrolysis Rate
The rate of hydrolysis was carried out to assess theability of crude soybean extract as a urea biocatalyst.
The procedure introduced by Whiffin [33] is followedin this study. Firstly, a standard curve was created by
calculating the conductivity generating from thereplete hydrolysis of several urea concentrations. The
varying concentration of purified soybean crude
extracts resulted in both methods being prepared andmixed with urea. The rate was measured immediately
after mixing using a conductance meter of Hanna
Edge Multiparameter 230. The rate of hydrolysis wasdetermined by calculating the slope of the
conductivity change gradient with time, which isexpressed as Eq (1).
𝑢
𝜃𝑚𝑠
(1)
𝐻𝑦𝑑𝑟𝑜𝑙𝑦𝑠𝑖𝑠 𝑟𝑎𝑡𝑒 ( ) =. 𝑣. 𝑁𝑔
𝜃𝑠𝑐
Where θms is the slope of the measured sample
gradient; θsc is the standard curve gradient slope; v isthe sample volume (L), and N is the final
concentration of ammonia (mMol/L).
Test-Tube Experiments

Materials
The treatment solution in this study was preparedusing pro analysis grade of urea reagent (CO(NH2)2)and dihydrate of calcium chloride (CaCl2 • 2H2O),
which are obtained from EMSURE® ACS, Reag. Ph.
Eur. Soybean powder was obtained from PT. Gasol
Pertanian Organik, Indonesia. The sandy soil of
graduated sand SO-404, classified as poorly gradedsand (SP) with emax, emin, coefficient of uniformity(Cu), and specific gravity (Gs) of 0.802, 0.543, 2.26,
and 2.61, respectively, is using as soil sample is thisstudy.
Plant-Derived Urease Enzyme
Various concentrations of soybean were preparedand thus extracted in two methods, namely filteredand centrifuged. Firstly, the soybean powder was
mixed with distilled water and stirred for 5 minutes.
Then, the suspension was eliminated using the233

SEE-Mie, Japan, Nov.10-12, 2022

were performed for 10 min, and the results wereplotted on a curve for the measured conductance. The
one mol of urea was prepared and mixed with various
concentrations of soybean powder of 10 - 50 g/L—
the change in conductance with time for both
extraction methods of filtration and centrifugation.
The hydrolysis rate in various concentrations ofsoybean extract was calculated using Eq (1), which isshown in Fig. 1. As is apparent, the activity waslinearly related to the increase in the concentration ofsoybean. The rate result in centrifuged method showsa higher value than in the filtered method. The
hydrolysis rate of 1100 u/g (note that one u of activity
corresponds to 1 µmol/L of urea hydrolyzed per
minute) was obtained using 50 g/L of soybean extract
centrifuged. This result revealed that the use of 1 g/Lof soybean extract was estimated to be around 25 u/g.

study, the varying soybean concentration of 10 g/L to
50 g/L with two extraction methods of filtration andcentrifugation were combined with the reagent
solution was used at one mol/L. The experimental
condition of tube experiments is shown in Table 1.
Table 1. Various concentrations of the solution for
precipitation tests.
Concentrations
SoybeanCase CO(NH2)2
CaCl2.2H2O
extract(mol/L)(mol/L)
(g/L)
1
1.0
1.0
10.0
2
1.0
1.0
20.0
3
1.0
1.0
30.0
4
1.0
1.0
40.0
5
1.0
1.0
50.0

1200

Hydrolisis rate [u/g]The precipitation mass is expressed as the ratio of
precipitation. This is the percentage of the realamount of the deposited substance, and the maximum
amount of the calcite deposited theoretically.
Unconfined Compressive Strength Test
Unconfined compressive strength tests wereconducted using a sample of 5 cm and 10 cm indiameter and height, respectively. The PVC cylinders
were prepared, and the sandy soil with emin, emax,
Cu (uniformity coefficient), and Gs (specific gravity)of 0.818, 0.586, 1.533, and 2.643, consecutively,
were poured into the mold with the density relative(Dr) of 50%. The persistent solution volume was
grouted into the formed sand columns. Two
extraction methods of soybean, i.e., filtered andcentrifuged, were applied to prepare the purified
soybean prior mixed with the reagent. The grouting
amount was boundaries by the amount of porevolumes (PV), one PV being ~80 mL. The sandcolumns were treated by single injection with various
curing times, e.g., 7, 14, and 28 days. After curingtime, the handled samples were taken out from the
PVC tubes. The surface of the specimens was leveled
before the UCS tests were performed. Two tests werecarried out for each condition to verify the duplicate.
The UCS tests were performed under wet conditions
to prevent any unexpected deposition that may
happen when specimens are consciously dried out.

Filtered soybean
Centrifuged soybean

1000
800
600
400
200
0

0

10

20

30

40

50

60

Soybean [g/L]

Fig. 1 Hydrolysis rate with various concentrations ofsoybean extract
The hydrolysis rate results in both soybean
extraction methods lower than the rate resulting in thecommercial urease of jack bean reported by Putra etal [34] and relatively higher than previous
investigations especially seated on crude solutions
extracted from crushed seeds of watermelon [14],[27], [30]. In addition, the higher hydrolysis rate wasreported as the main factor in reducing of uniformityof calcite distribution within the soil. Hence, reducing
the rate may improve the uniform distribution of
precipitated material within the treated soi [35].
Precipitation Test
Precipitation tests were conducted to examine theefficacy of soybean crude extract as a replacement forcommercial urease enzyme in producing calcite
precipitation. The effect of the extraction method, i.e.,
filtration and centrifugation in various concentrationsof soybean, was evaluated in this study. The reagentscomposed of urea and calcium chloride of 1 mol/L
were combined with soybean varying from 10 – 50
g/L. The summary of test results is displayed as theratio of precipitation, which is the percentage ofobtained mass during the experiment, and the
maximum theoretical mass of the CaCO3, which isshown in Fig. 2.

RESULT AND DISCUSSION
Hydrolysis Rate
The hydrolysis rate analysis was performed to
examine the influence of the crude extract methods on
the urea hydrolysis rate. A standard curve forhydrolysis was prepared by the maximum
conductance values. The conductance measurements
234

SEE-Mie, Japan, Nov.10-12, 2022

The results indicated that both extraction
methods, filtered and centrifuged, were effective in
producing the purified enzyme result in soybean
powder. Fig. 2 shows that soybean with aconcentration of 20 g/L can produce a maximum
precipitation ratio of 100%. The amount ofprecipitation increases significantly at low
concentration soybean of 10 g/L to 20 g/L. Then, theamount is stable at the maximum value. Therefore,
the addition of the crude extract concentration does
not significantly affect the mass of precipitationmaterials. Considering to the amount, these results
may indicate that the soybean of 20 g/L is the
optimum concentration for precipitated calcite
production. Pratama et al. [26] reported that the highconcentration (more than 10 g/L) of soybean preparedby the centrifuged test is high enough to be used as a
bio-catalyst in the EICP method.

14000

Intensity [cps]

C

10000
8000
6000
4000

V
2000
0

C
0

10

20

30

C

C

C

C

40

50



14000
C : Calcite
V : Vaterite

Centrifuged soybean 20 g/L

Intensity [cps]

12000
10000
C

8000
6000
4000

100

Precipitation ratio [%]C

Deviation angle, 2   

V

2000
0

C

C
0

10

20

30

C

C

40

CC
50



Deviation angle, 2   

80Fig. 3 X-Ray Diffraction (XRD) results

60

40

Shear Strength Improvement

20

Filtered

The unconfined compressive strength (UCS) tests
were performed to evaluate the impact of soybean
extract methods on improving the soil strength. The
optimum soybean concentration of 20 g/L was
prepared using both extraction methods of filtrationand centrifugation. Thus, mixed them with a reagent
to produce the treatment solution. The soil samples
were treated by a single injection of 1 pore volume
and incubated for varying curing times of 7, 14, and28 days to assess the impact of time elapsed on soil
improvement. The UCS result in Fig. 4 shows thesimilar relative strength for the whole varying
samples. The UCS ranging from 340 - 400 kPa wereachieved with the maximum strength obtained by thefiltered method in curing times of 14 and 28 days.

Centrifuge
0

C : Calcite
V : Vaterite

Filtered soybean 20 g/L
12000

0

10

20

30

40

50

Soybean [g/L]

Fig. 2 Precipitation ratio of precipitated calcite
XRD tests were performed to assess the mineral
types of calcites generated during the precipitation
stage. The mineral types of the precipitated material
are indicated by the intensities of the primary peaks
in XRD patterns, as shown in Fig. 3.
The result shows that the precipitated minerals aremainly composed of calcite—the extraction methodsof filtered and centrifuged result in a similar trend of
XRD pattern for all samples. Calcite is the most stablecarbonate mineral and polymorph of calcium
carbonate [36]. The vaterite form was also detected in
XRD result in both of treatment. The using of highconcentration of soybean may be promoted moreundissolved organic matter and thus, hamper the
calcination process. Konopacka-łyskawa et al. (2020)
reported that the presence of organic solvent
promoted the vaterite form in addition to calcite.
However, this study has not yet conducted a detailed
analysis of the amount of each mineral in precipitatedminerals. It should be considered essential in further
study.

500
Centrifuged
C
F
Filtered

UCS [kPa]

400

300

200

100

0

7

14

28

Curing time [day]Fig. 4 Results of UCS tests with various curing time235

SEE-Mie, Japan, Nov.10-12, 2022

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[17] Akiyama M, Kawasaki S. Microbially mediatedsand solidification using calcium phosphate
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CONCLUSION
The plant-derived urease enzyme was examined
to assess the potential new urease enzyme source,
especially soybean powder. The extraction ofsoybean was conducted by two different methods,e.g., filtered and centrifuged methods. The effect ofthe preparation for crude extract was examined interms of rate of hydrolysis, precipitation ratio, type,and shape of mineral. The hydrolysis rate increases
with the increase in soybean concentration. A
hydrolysis rate of 1100 u/g was obtained using 50 g/Lof soy powder. Thus, the soybean had a high-enoughhydrolysis rate to be used instead of commercial
urease enzymes as the biocatalyst in the calcite
precipitation method. The precipitation test results
show that the method of preparation of crude extract
using filtered and centrifuged method has no
significant impact on the precipitation mass. The
precipitation ratio significantly increased when thesoy powder concentration was increased from 10 g/L
to 20 g/L in both extraction methods. Using soybeanof more than 20g/L results in the maximum
precipitation ratio of 100% and thus is selected as an
optimum concentration of soybean. The UCS test
result also shows that the extraction method has no
significant effect on soil strength. A single injectionin the treated sample achieved a relatively similar
UCS ranging from 340 to 400 kPa. The varying
curing time resulted in a similar trend, with amaximum strength of 0.4 MPa in 14 days. Hence, thisstudy confirms that soybean's filtration extraction
method may be a more effective and applicabletechnique to prepare the catalyst in the calcite
precipitation method cause its impact and simplicity.
ACKNOWLEDGMENTS
The research described in this paper was
financially supported by the Minister of Education,
Culture, Research, and Technology of the Republic ofIndonesia, grant number 082/E5/PG.02.00.PT/2022
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M. Experiments and predictions of physicalproperties of sand cemented by enzymaticallyinduced carbonate precipitation. Soils Found.
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K. State-of-the-Art Review of the Applicability
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237

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

PERFORMANCE COMPARISON OF GEOMETRIC SHAPE OF
DESILTING BASIN RECTANGULAR AND VORTEX DESILTING
BASIN*Muhammad Isnaeni1, Muhammad Syahril Badri Kusuma2, Joko Nugroho2, Mohammad Farid2, andMuhammad Cahyono2
1

Doctoral Program of Water Resources Engineering, Faculty of Civil and Environmental Engineering,
Institut Teknologi Bandung, Indonesia; 2Water Resources Engineering Research Group, Faculty of Civil andEnvironmental Engineering, Institut Teknologi Bandung, Indonesia*Corresponding Author, Received: 00 June. 2022, Revised: 00 June. 2022, Accepted: 00 June. 2022
ABSTRACT: Vortex desilting basins have inherent advantages over other types of sediment-removal desilting
basins. The advantage is that they require smaller dimensions and a lower removal discharge to achieve specificsediment removal efficiency. An increase in the incoming velocity generates a powerful centrifugal forced
vortex, resulting in higher hydraulic efficiencies of the basin. The streamlines and velocity vectors in thehorizontal superimposed sections were drawn and analysed then for incipient motion of sediment. This study
presents the results of experimental research that was accomplished in a vortex desilting chamber to observe
the slope orifice chamber with 1:10, 1:5 and 1:2. The method uses numerical methods with CFD simulations
by Ansys R.21 Student to similarity geometric, kinematics and dynamic, then laboratory experiments with amodel scale 1:40 prototype to an undistorted 3-D physical model. Comparing the magnitude of the velocity
and streamlined path in horizontal sections with the occurrence of secondary in radial sections revealed thatthe flow in the vortex direction plays a higher role in the removal efficiency of the desilting basin. In comparing
the performance, as a result, the slope orifice chamber of 1:5 is further effective in case of deposition andremoval faster than other slope chamber types; in the same time model scale, 4 days in a prototype similar to
11 hours on the model scale settled 82.12% sediment and within 4 hours which is similar to 35 minutes on themodel scale or more effectively 87.91% of the chamber slope of 1:2 and 1:5.
Keywords: Vortex desilting basin, sediment removal, removal efficiency, deposition, undistorted 3-D physicalmodel.

1. INTRODUCTION

water flow in the canals may erode the soil anddisperse the agrochemicals adsorbed to thesediments in the environment [7]. Therefore,
evaluation of the transport process requires
improved techniques to determine sedimentconcentration in the narrow, concentrated flow ofirrigation canals, especially if the bed andsuspended loads are to be evaluated separately.
Similar improvements are required in flow velocity
determinations [8].
While fresh sediment deposits are often close to
fluid mud, older and deeper riverbed sediments tend
to be consolidated, with the state of consolidation
higher for deeper sediment. These vertical gradientscomplicate the modelling of sediment erosion,transport, and deposition [9], [10].
A considerable effort is required to improveirrigation operations and modernise them. A
desilting basin is a temporary sediment control
structure to intercept sediment-laden runoff andretain the sediment. It aims to detain sediment-laden
runoff from the disturbed area for sufficient timeand allow most deposits to settle within thesediment trap [11]. Decrease the flow velocity in thebasin to assure the sediment particle's remaining

Rapid land-use change during the last decades
has resulted in a decrease in irrigation areas and anincrease in urban/developed areas. Although water
demand for irrigation areas tends to decrease asaffected by land-use change, even East Tarum canaland irrigation infrastructures are still in the same
dimension [1], [2]. Land-use change on the mainisland of Indonesia is inevitably increased due to thedemographic growth and regional development
activity in the last two decades [3], [4].
One of the primary constraints to sustainableagricultural production is a lack of irrigation watersupplies. In recent years, the development ofalternative water sources and the application ofirrigation water-saving technologies are two key
strategies to alleviate the scarcity of agricultural
water resources [5], [6]. Nowadays, surface
irrigation is the most extensively used irrigation
method due to its long tradition and low energy
consumption. However, this method may pose more
erosion and pollution risks than drip or even semitechnique irrigation methods. The concentrated
238

SEE-Mie, Japan, Nov.10-12, 2022

time is longer than the settling time is the primary
design idea of settling basins. This phenomenon
results in the flow of water for irrigation requiredthat is diverted through the weir, resulting in adecreased supply of irrigation water [7]. Water
flowing in the canal taking off from head works onsuch rivers also carries sediment load, the canal getssilted if it receives sediment load over its
transporting capacity, and effective measures are
not taken for its control. This results in a decreasein the discharge carrying capacity of the canal.
Further, the canal slope is generally smaller than themain river; hence, sediment always tends to bedeposited in the irrigation canal [12]. To address it,
the weir as a head structure requires a sediment trapthat can deposit non-cohesive type sediments andquickly remove out because the water required for
irrigation is complicated to stop during the cropping
pattern because farmers need it.
Previous authors investigated the vortex settlingchamber; Cecen and Bayazit (1975), Curi et al.
(1975), Ogihara and Sakaguchi (1984),
Sanmuganathan (1985), Mashauri (1986), Paul et al.
(1991), Athar (2000), Athar et al. (2002), Athar etal. (2005), Keshavarzi et al. (2006), Ansari (2008)
and Ansari and Athar (2013) The vortex settlingchambers can also separate solids from theirtransporting fluids, such as in treating sewage andindustrial wastes. However, the development by theprevious study is to deposit sediment in a power
plant and electrical energy to avoid a larger
diameter of non-cohesive sediment entering theturbine drive system. In irrigation, sedimentgradation allowed and neglected to enter theirrigation canal is cohesive type sediment whose
diameter is < 0.06mm [9]. It is challenging todeposit this type of sediment because it issuspension sediment that moves with the water flow[13], [14].
As a case study for head structure in the weir for
sediment traps, the Macan weir was designed in anarrow space located in Subang Regency, WestJava Province, Indonesia. This weir services atechnical irrigation area of 9,670 ha, where thecurrent condition of the wet perimeter section area
is reduced by ±35%, caused by sedimentation. The
existing conventional plan will construct
rectangular sediment traps located right side of thehead structure [15].
The present research examines and develops themodern shape of sediment traps as a proposed toreplace sediment traps with conventional geometricshapes for the future. This research aims to improvethe vortex desilting basin sediment trap
performances, depositing non–cohesive sediment >0.06mm and removing out sediment fraction as
trapped settling basins.

Fig. 1 Macan Weir, Located in West Java, Indonesia
The slope orifice chamber of 1:5 is further
effective in case of deposition and removal fasterthan 1:10 and 1:2 slope chamber types.
The shape of the sediment trap must meet thehydraulics rules, design criteria and standardised.
So that, non – cohesive sediment is deposited, andincreasing removal efficiency to the maximum
requires different characteristics and velocity. If
hydraulically it can be fulfilled, then the aspect ofoperational costs is undoubtedly a consideration as
well as research significance. This proposed
geometric shape is recommended for a weir that
does not yet have sediment traps and can only bebuilt in a narrow space.
2. METHODS
2.1 Sediment Properties
2.1.1 Primary data extracted
This research started and was carried out by
taking sediment properties obtained by primary data
in 2019 and tested at the Laboratory of Engineering
Geology, Padjajaran University in Bandung, toobtain sediment properties and physical properties.

Fig. 2 Samples extraction on site (2019).
The sediment particle was tested by comparing
the data around the study site, such as on the Cibeet239

SEE-Mie, Japan, Nov.10-12, 2022

and Ciasem rivers, and sediment properties in the
Macan weir sediment trap were taken at upstream(3 samples) and downstream (3 samples) sampling
points, with laboratory test results at 20°C watertemperatures [16].
2.1.2 Sediment's laboratory test for the physicalmodel test (2022)
There are four key classifications of
sedimentation processes, each characterised bydifferent settling behaviour; describes these as [13],[17]:a) Type I: Discrete particle settling – particles
settle individually without interaction withneighbouring particles.
b) Type II: Flocculant settling – flocculation
causes the particles to increase in mass and settle
at a faster rate.
c) Type III: Hindered or Zone settling – a mass ofparticles tends to settle as a unit with individual
particles remaining in fixed positions withrespect to each other.
d) Type IV: Compression settling – theconcentration of particles is so high that
sedimentation can only occur throughcompaction of the structure.

Fig. 3 Equivalent weighing of test sediment samplesa) Ex. Field Sediments, b) Passed sieve #400
Ex. Stone Crusher, c) Passed sieve #400 Ex.
Coal, and d) passed sieve #400 Ex. Brick in
the Fluid Laboratory ITB (2022)

Discrete particle settling occurs in dilute
mixtures where there is no particle interaction, withdiscrete particles being defined as particles whose
size, shape and specific gravity do not change withtime [18]. The settling velocity of a single sphericalparticle undergoing discrete settling under laminarconditions [19]. Using a settling tube ( Settling
Tube), an effective settling velocity is measured,
which can be converted into an equivalent particle
diameter. Parameters C1 and C2 are taken at valuesof 18 and 0.3 for fine-grained particles but
somewhat higher values for natural particles, as
discussed later. For particles that can be considered
redundant, so the following equation is obtained:Vs =ρs gD218 μ + √0.3 ρs ρgD3

Fig. 4 Field sample testing (Prototype), a) initialdeposition, b) sediments deposition(1)
Fig. 5 Deposition rate test Ex. Brick's sample passed
sieve #80, #200, and #400. a) initialdeposition, b) sediments deposition

Where, 𝑉𝑠 deposition velocity, 𝑔 acceleration
gravity, D spheres particles diameter, 𝜌𝑠 sedimentdensity, 𝜌 water density, 𝜇 viscosity. Before theresults of the sediment deposition rates are
obtained, this settling tube is carried out as shownin Fig.3, Fig.4 and Fig.5 as below:

Referring to Eq.1, the analysis results are calculatedusing four (4) formulas and calibrated by laboratory
tests with four (4) samples. As a result, thedeposition rates result of 0.735cm/s with acomparative curve as follows:240

SEE-Mie, Japan, Nov.10-12, 2022

mass, force, temperature, etc. These relations must
be so structured that dependent and independent
quantities are combined so as to yield dimensionallycorrect formulas [23]. Dimensional analysis cansometimes provide a complete set of dimensionlessproducts constructed from the pertinent process
variables [2], [24]. Similitude by dimensional
analysis requires that the dimensionless products
have the same value in the prototype as in the model,
the similarities that have been tested in this study
are geometric, kinematic and dynamic [25].
2.4 Experiment Set-up in Laboratory
Fig. 6 Comparison curve as calculated four (4)formulae versus settling tube test inlaboratories

Physical model tests are performed toinvestigate the hydraulic behaviour of the entire
sediment trap or each component. Physical model
tests often solve fluid mechanics and hydraulics
problems to discover the hydraulic behaviour not
obtained in numerical models with CFD [26]. This
physical model test is intended to test or check the
performance of sediment traps in the efficiency ofdeposition and desilting that have been previously
tested in numerical analysis with CFD.

The analysis has calibrated the results of differencesin values from the predictions of a model as an
estimate of the observed values, as shown in Fig.6.
Root Mean Square Error (RMSE) results from thesquare root of the Mean Square Error. The accuracyof the measurement error estimation method ischaracterised by the presence of a small RMSE
value. Estimation methods with a smaller Root
Mean Square Error (RMSE) are more accurate thanestimation methods with a more significant Root
Mean Square Error (RMSE).

2.4.1 Accessories of the Experimental Set-up
Simple ADV performance interface, enabling
fast data collection by a data logger by a computer.
Laboratory test used 2 unit Micro ADV 16MHz
down and side-looking, 1 unit Probe Propeller
Current Meter H33 with data logger and 8 unit
Camera Highspeed DSLR.

2.2 Numerical Analysis by Computational Fluid
Dynamic (CFD)
In recent years, the growing availability ofcomputational sources and progress in the accuracyof numerical methods has helped researchers tosolve fluid mechanics. The method used in CFD toanalyse the flow behaviours is a numerical approach.
CFD complements testing and experimentation,
reducing the efforts and costs required forexperimental procedures and data acquisition [20],[21]. This simulation will be carried out bymodelling three fluid phases, namely air, water, andsediment or mud so that the sediment's flow
characteristics can be obtained against time(transient). Because in this simulation, several
fluids have different phases (air, water, and mud),multiphase modelling must be used. For flows witha clear separation between one phase and another,
the Volume of Fluid (VoF) model is used. Thismodel is also relatively simple and efficientcompared to eulerian or mixture [22].

2.4.2 Schematic of Laboratory Test
A 3-D test of this physical model was carried out
in the hydraulics laboratory of the Faculty of Civil
and Environmental Engineering Institut Teknologi
Bandung (ITB), and an undistorted scale 1:40 3dimension physical model was conducted fromFebruary to May 2022 (see Fig.7). The
determination of the scale model in the analysis of
the relationship between scales prototype to model,
considering: space in a laboratory, accuracy,facilities/accessories, and visual view of theundistorted physical model with a scale of 1:40.

2.3 Dimensional Analysis
Dimensional analysis is formulating fluid
mechanics problems in the case of non-dimensionalvariables and parameters. Physical problems aredescribed by relations, which are determined byquantities having a certain dimension—length, time,
Fig. 7 View of undistorted 3-D lab physical model.
241

SEE-Mie, Japan, Nov.10-12, 2022

2.4.3 Experimental Procedures
The sediment removal efficiency of the vortex
settling/desilting basin used was measured bysystematically varying the inlet discharge,
underflow removal discharge, sediment size,
underflow outlet orifice diameter and the width ofthe channel. The sediment trap efficiency is definedas the ratio of deposited sediment to the total
sediment inflow for a given period within thesediment trap economic operation [27], [28].
2.6 Limitations

Fig. 8 Undistorted physical model test scaling 1:20
for conventional rectangular sediment trap

In this study, the authors limited several
variables so that the focus of the study became clear
and not pseudo; here are the limitations of theresearch: a). Laboratory 3D Physical Model,
Undistorted Scale 1: 40; b). Inlet Irrigation Main
Canal length at Model: 5.5 m equal Prototype 220m and static with 0.2m in model equal to 8.00 m at
prototype; c). A circular cylindrical type of vortex
settling basin having a diameter at model 1.00m
equal to 40m at prototype was used forexperimentation in the present study; d). Sediment
to be deposited cohesionless type > 0.07mm, and<0.07mm neglected and allowable enter to the main
system; e). Water depth has variations based on Q
50%, 100% and 120% by NFR; f). The underflow
outlet orifice static diameter is 0.025 m, equal to adiameter of 1.00m; g). Cohesion-less uniform
sediments having sizes 0.008 mm to 0.825 mm wereused, and: h). Suspended sediment concentration in
the vortex settling basin varied from 11,200 ppm to
190,000 ppm by weight.

In such irrigation systems, sediment in canalstructures has both technical and economic
implications in developing and utilising water
resources; hence, its control is essential. With asimilar location and parameters, due to the Macan
main canal's alignment in the irrigation system's
direction, if it is built on a space with curvedalignment is not optimal in terms of performance.
The alignment of sediment traps on the curved line
leaves significant sedimentary fractions in the innercurve and under sluice, see Fig. 9 and 10. The
results of physical modelling on conventional
sediment trap forms with a model scale of 1:20 are
not very optimal, the deposition efficiency ismeasured at 69.12%, and this deposited
sedimentary fraction can only be removed by
53.33%, see Table 2.

3. RESULTS AND DISCUSSIONS
Decrease of the flow velocity in the basin toassure the sediment particle remaining time longer
than the settling time is the main design idea of thesettling basin. To achieve this goal, the common
procedures are widening the basin width andlowering the basin bottom. However, different
combinations of length, width, and depth may attainthe same deposition efficiency. The economic
design of the settling basin with the specificefficiency is the focus of this study.

Fig. 9 Unremoved sediment at under sluice space

3.1 Rectangular Shape Sediment Trap
The performance of a sediment trap is expressedin how effectively it is depositing and quickly
removing the sediment fraction. As a comparison,in 2018, there was an undistorted 3-D of physicalmodel of the rectangular shape of sediment traps in
the Hydraulics Laboratory of PUSSAIR Bandung,(see Fig. 8).

Fig. 10 Fraction of sediment on dashed line – break
the red circle in rectangular sediment trap.
242

SEE-Mie, Japan, Nov.10-12, 2022

In the Design Criteria (KP-02, 2015) issued by
the Ministry of Public Works and Housing,sediments deposited in diameter >0.07mm, fordiameters <0.07mm are allowed to be neglected andthen move the irrigation system with operationalroutine and periodic maintenance conditions
extracting [29].

Table 2 Performance of Rectangular Conventional Sediment Trap, 2018

3.2 Simulation for Approach Geometric Shapeby CFDThe equation of momentum in the direction of thex-axis:In all 22 runs were conducted for sedimentremoval efficiency of vortex settling/desilting basin
by varying slope chamber of underflow outlet,
whereas 44 runs were conducted for this study.
Here are the inputs used in boundary conditions:
Mass-flow-Inlet: a). In the inlet section, it is defined
as a mass flow inlet either for water or mud. b).
Wall: On walls, it is defined as a wall with a no-slip
condition to represent the friction between the fluid
and the wall. c). Surface: At the top of the domain,
the effects of wall friction are removed to represent
atmospheric air, and d). Outlet: The outlet section isdefined as a pressure outlet representing the flow's"exit".
Computational Fluid Dynamics (CFD) is the artof transforming fluid dynamics set equations in theform of integrals and derivatives into discrete
algebraic forms, which a computer can solve toobtain the values of the flow field at a particular
discrete point or time. As for the regulatory
equations in fluid dynamics: the continuity
equation, the momentum equation and the energy
equation [20], [21]. Here are the equations used in
CFDs;
Continuity equation of integral forms:
∂
∂t

⃗⃗ =0
⃗⃗ ∙dA∭Ѵ ρdѴ + ∬A ρV

∂(ρu)
∂t

∂t

⃗ ∙V
⃗⃗ =0
+ρ∇

(3)

The equation of momentum in the direction of they-axis:∂(ρv)∂t⃗ ∙(ρvV⃗⃗ )=- ∂p + ∂τxy + ∂τyy + ∂τzy +ρfy
+∇
∂y

∂x

∂y

∂z

(4)

The equation of momentum in the direction of thez-axis:∂(ρw)∂t⃗ ∙(ρwV⃗⃗ )=- ∂p + ∂τxz + ∂τyz + ∂τzz +ρfz
+∇
∂z
∂x
∂y
∂z

(5)

The energy equation is written in the form ofinternal energy:
V2

∂

V2

∂(ρp) ∂(vp)⃗ ∙ [ρ (e+ ) V⃗⃗ ] =ρq̇ [ρ (e+ 2 )] +∇- ∂y ∂t
2
∂x
∂(wp)
∂z

⃗⃗
+ρf∙V

(6)

Where, ρ is Liquid density (kg m-3), A is mass area,⃗⃗ is Velocity vector (m s-1) or velocity fluid parcel,Ve for internal energy, three velocity components are⃗ vector, f any vector function. The𝑢, 𝑣, 𝑤, ∇solution of a partial differential analytical equation
results in a continuously closed-form dependent
variable expression across domains. In contrast, thesolution of numerical equations can only give(1)

The continuity equation of the differential form:∂ρ⃗ ∙(ρuV⃗⃗ )=- ∂p + ∂τxx + ∂τyx + ∂τzx +ρfx
+∇
∂x
∂x
∂y
∂z

(2)
243

SEE-Mie, Japan, Nov.10-12, 2022

values to discrete points in the domain, also called
grid points. As a shaping approach to the vortex
geometric shape settling/desilting basins proposed,
as shown in Fig. 11, then input all the hydraulicvariables and applying Eq.1 – Eq. 6 above in CFD
resulted shape as follows:

fraction can be drained. Leaving approximately
30.69% in cyan colour cannot be remove-out due tothe position of the sediment in the transition of thefree vortex flow to the forced vortex.
3.3 Result Laboratory Undistorted 3-D PhysicalModel Test
The geometric approach of the vortex
settling/desilting basin with a numerical approach
to its results was tested with a physical model in thelaboratory.
After the dimensional analysis, stages arecarried out, and geometric, kinematic, and dynamic
similarity tests and the available space, a model
scale of 1:40 is determined.
Table 3 Summary of geometry similitudeFig. 11 Wall shear contour, in valve-way closed
condition
As shown in Fig.11, it showed that the wall
shear contour on the free vortex flow along theforced vortex flow side of the chamber is relatively
high and states that sediment is well deposited, thepercentage of sedimentary volume deposited fromsediment transport within continues flow in 7 daysof flow amounting to 82.11%. On the longitudinal
section of this sediment trap is shown a fraction of
sediment deposited present by the predominance of
red in the following Fig.12 below:

The following equation
deposition efficiency value:
V -V

Tef = inV out ×100

calculates

the

(7)

in

Where Tef is trap efficiency (%), Vin is the volumeof sediment entering the sediment trap, Vout isvolume of sediment as remove at outlet.
To calculate the efficiency of removing/desilting,use the following equation:
ŋ0 =Ws removed+Ws Settled
Total Ws Feeding

×100

(8)

Where ŋ0 is removal efficiency (%), Ws removed
is the volume of a sediment chamber, and Ws
Settled as sediment deposited. Ws feeding the total
amount feeding of sediment transport rates [23],[30].

Fig. 12 Sediment volume fraction – longitudinal
section view (deposition time)

Fig. 13 Sediment volume fraction – longitudinal
section view (desilting time)
In addition, the rheological process of sedimentary
sediments also exerts an influence on theclassification of this type of sediment. Of the82.11% of sediment deposited, as shown in Fig. 12
and Fig. 13, a total of 69.31% of the sedimentFig. 14 Deposition time condition in 3.25 of 12hours running.
244

SEE-Mie, Japan, Nov.10-12, 2022

6. REFERENCES[1]

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Silasari, "Preparedness Effort toward Climate
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Manoj K. Jain, Umesh C. Kothyari, andKittur G. Ranga Raju," J. Hydraul. Eng., vol.
133, no. 7, pp. 843–844, Jul. 2007, doi:Fig. 15 Measurement of sediment fraction in 8.25 of
12 hours running
As shown in Fig. 14 and Fig. 15, 11 runs wereconducted for this study and feeding the sedimentthrough a sediment feeder to determine the volume
of deposition and the removal efficiency refer toEq.7 and Eq.8. The maximum result for chamber
1:5, with the effectiveness, deposited 84.90%>80%.
Of these sediment fractions, 87.90% were removed
within 0.3 hours and left a sediment fraction of
12.1%. The deposition conditions yielded the
maximum, with flow conditions Q=0.53lps,
V=8.18cms, water level height 8.23cm in flume and
Fr 0.98. A regulator is required on the operationgate to maintain and implement this parameter.
4. CONCLUSION
Present research for steady, vortex, and open
channel flows over smooth, rough, and movablebeds, independent and based on Reynolds andFroude numbers. As a comparison of 2 different
geometric shapes of sediment traps with hydraulicparameters such as discharge, the exact
characteristics of sediments to deposition andremoved-out, the running results showed anincrease in the number of volumes that could besettling from 69.12% to 84.90%. Meanwhile, forremoval, the sediment fraction of 53.33% increases
to 87.90% from the deposited can be removed. For
future research, it is optimising the geometric shapeof the chamber to be optimum based on the diameter
ratio chamber effect.
5. ACKNOWLEDGMENTS
This study aims to develop a 3-D rectangularsediment trap to a vortex desilting/settling basin
shape. The authors would like to thank the Ministryof Public Works and Housing for their assistanceregarding the data collection required for this paper.
Furthermore, the authors would also like to express
gratitude to this research, the Water Resources
Engineering Research Group of the Faculty of Civil
and Environmental Engineering Institut Teknologi
Bandung, for supporting this publication.
245

SEE-Mie, Japan, Nov.10-12, 2022

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CASE STUDY AND EVALUATION OF ROAD LANDSLIDE OVER
TUFF-MATERIAL
Fahmi Aldiamar1, and Dea Pertiwi3
Implementing Unit for Geotechnical, Tunnel and Structures, Directorate General of Highway, Ministry of
Public Works and Housing, Indonesia

1,2

ABSTRACT
Muara Tebo-Sei Bengkal National Road in Jambi province are constructed over Kasai Formation consisted oftuff sandstone, clay, gravel and thin layer of coal according to regional geological map. This formation usuallyconsists of young loose fine-grained material that is porous and easily eroded when infiltration and surface
runoff due to raining is occurred. In 2018, longitudinal cracks, which were propagated creating crown oflandslide on road shoulder, were occurred in this road section. Geogrid-reinforced earthwork was constructed toovercome this problem. Unfortunately, this construction did not work well due to inundation of embankment toe
during high intensity rainfall, and sliding plane developed below geogrid-reinforced earthworks (MSE Wall)construction. Evaluation on the depth of sliding plane was conducted using inclinometer measurement and reevaluation on soil stratification according to soil testing across the road section. Sliding plane was predicted todevelop down to 7 meters depth which is the interface between impervious material (clay) that underlie below
surface material (silty sand) which is more porous. It is indicated that softening of the embankment toe triggered
progressive instability to the road embankment and geogrid-reinforced earthworks, acted as additional loadcausing the sliding occurred faster. Evaluation on this case showed that meticulous examination on geotechnicalaspects will provide a more thorough determination on problems, and bored-pile using retaining wall as a slope
stabilization solution is more effective when dealing with deep sliding plane.
Keywords: Road landslide, Tuff material, Geogrid reinforcement, Bored pile

INTRODUCTION

geotechnical analysis involves soil characterization,water level, displacement and main cause of roadlandslide were evaluated to draw conclusions andpresent the solution for the failure in theconstruction [4].

Volcanic tuffs are very porous rock and areprone to weathering [1]. Tuff is pyroclastic rocks
produced by volcanic eruptions due to endogenous
forces. The material forms the volcanic eruption
were deposited before being transported by water [2].
Residual tuff soil was formed by weathering process
and become relatively soft especially in saturated
condition.
Road construction over volcanic tuff material
should be design carefully especially when surface
water run-off was uncontrollable and ground waterlevel are high. When landslide occurred on National
Road, disruption to road user and traffic jam weremajor problems especially when the National Road
are strategic and the only connection road between
district.
Tebo district economic income were depend on
palm and rubber farm also mining such as coal,crude oil and small-scale gold mining. Jambi is aprovince of Indonesia that is located on the east
coast of central Sumatra. National road connecting
Tebo district and Jambi province were vital due toits strategic trading route.
In this paper, forensic geotechnical investigation
using numerical method were conducted to utilize,
simulate and analyze landslide behavior [3]. The

CHRONOLOGY OF ROAD LANDSLIDE AND
PREVIOUS COUNTERMEASURE
In 2018 erosion at embankment slope surface
due to surface water runoff induced instability ofroad embankment at Muara Tebo-Sei Bengkal
National Road in Jambi province (Fig. 1).

Fig. 1 Slope surface instability due to water runoff

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SEE-Mie, Japan, Nov.10-12, 2022

Since the instability were indicated shallow andonly influenced roadside, Mechanically Stabilized
Earth (MSE) Wall consist of compacted backfill andsoil reinforcement using uniaxial geogrid were
design and constructed as seen in Fig. 2 until Fig. 5.

Unfortunately, in 2019, cracks at roadside follow
by large displacement occurred at the MSE Wallconstruction is shown in Fig. 6.

Fig. 2 Design drawing of MSE Wall

Fig. 6 Large displacement at MSE Wall
Evaluation on rainfall intensity for the past 3
years from 2017 until 2019 showed that when thelandslide occurred in November 2019, heavy rainfallwith intensity until 60 mm/day happened. These
intensities were the largest in the range of
observation data (Fig. 7).

Fig. 3 Soil reinforcement using uniaxial geogrid

Fig. 7 Rainfall intensity data from 2017 until 2019REGIONAL AND LOCAL GEOLOGY OF THE
REGION

Fig. 4 Compaction of embankment above soil
reinforcement

Muara Tebo-Sei Bengkal National Road in Jambi
province are constructed over Kasai Formation(QTk) consisted of tuff sandstone, clay, gravel andthin layer of coal according to regional geologicalmap (Fig. 8). This formation usually consists ofyoung loose fine-grained material that is porous andeasily eroded when infiltration and surface runoff
due to raining is occurred.
Evaluation on the outcrop of tuff material at toeof the embankment (Fig. 9) show that the material
was saturated, loose and some places show
waterway that indicated material erosion due tosurface runoff.
Fig. 5 Finished construction of MSE Wall
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SEE-Mie, Japan, Nov.10-12, 2022

Piezometer-1

BH.1

Inclinometer

N-SPT

BH.2

Displaced MSE Wall

0.000

10 20 30 40 50 60

N-SPT

Piezometer-2

20.00020.00025.00025.00020.00025.00015.00015.00015.00030.00010.00010.00010.00035.000

5.000

5.000

10 20 30 40 50 60

5.000

40.000

10 20 30 40 50 60

N-SPT
0.000

45.000Fig. 8 Geological map of Muarobungo, Sumatera [5]

0.000

BH.3

50.00030.00030.00025.00020.00030.00010.000LEGEND:
Soft - Medium Stiff Tuff

Very Stiff Silty Sand

Stiff Sandy Silt

Very Stiff - Hard Clay

Hard Sandy Silt

Fig. 10 Soil stratification and condition of displaced
MSE Wall
IDENTIFICATION OF SLIDING PLANE
ACCORDING TO INSTRUMENTATIONMEASUREMENT
According to piezometer measurement, groundwater level were expected at -12.0 m below
pavement elevation, while sliding plane wereindicated at 2 (two) position i.e. shallow sliding
plane at -1.50 m and deep sliding plane at -7.0 m
below surface elevation of BH-2 as seen in Fig. 11
and Fig. 12.

Fig. 9 Visualization of tuff material at toe ofembankment
SOIL STRATIFICATIONA
Roadside-100

To evaluate the cause of landslide, three (3) soil
investigation (BH-1, BH-2 and BH-3) conducted in2020 at different position crossing the landslide(Fig. 10). After completion of drilling work,
instrumentation to define position of sliding plane
namely inclinometers were installed at BH-2
according to National Standard method [6], while
instrumentation to measure elevation of groundwater level i.e., open standpipe piezometers were
installed according to National Standard method [7],at BH-1 and BH-3.
Five (5) layers of soils were identified according
to National Standard method [8], as seen in Fig. 10.
Thickness of surface layer that is soft-medium stiff
tuff were ± 5.0 m, while interlude of silty sand,sandy silt and clay are identified below the tuff
material. Surface elevation measured at that time
indicated that lateral displacement of MSE Wall
were around 11m, while vertical displacements wereapproximately 5m.

cumulative displacement (mm)
40

90

B
A
Toe ofRoadsideembankment

140

Incremental readings (mm)B
Toe ofembankment

40

90

-10

190

0

1

1

2

2
3

3

Shallow Sliding plane

4

4

5

5

6

6

7

7

Deep Sliding plane8

Depth (m)

8
9
10

9
10

11

11

12

12

13

13

14

14

15

15

01-Mar-20 Morning

01-Mar-20 Afternoon

01-Mar-20 Evening

02-Mar-20 Morning

02-Mar-20 Afternoon

02-Mar-20 Evening

03-Mar-20 Morning

03-Mar-20 Afternoon

03-Mar-20 Evening

19-Mar-20 Morning

19-Mar-20 Afternoon

19-Mar-20 Evening

Fig. 11 Cumulative and Incremental displacementfrom inclinometer readings
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SEE-Mie, Japan, Nov.10-12, 2022
Hard Sandy Silt

Soft - Medium Stiff Tuff

Very Stiff Silty Sand

Stiff Sandy Silt

Very Stiff - Hard Clay

Sliding plane

Table 2 Geogrid parameters

Piezometer-1

BH.1

Inclinometer

N-SPT

BH.2

Displaced MSE Wall

0.000

10 20 30 40 50 60

N-SPT
0.000

BH.3

50.000

Piezometer-2

45.000Uni-axial geogrid

Tensilestrength(kN/m)

Elongation
at break(%)

EA(kN/m)

100

13

12.7

20.00020.00025.00025.00020.00025.00015.00015.00015.00030.00010.00010.00010.00035.000Description

5.000

5.000

10 20 30 40 50 60

5.000

40.000

10 20 30 40 50 60

N-SPT
0.000

30.00030.00025.00020.00030.00010.000LEGEND:
Soft - Medium Stiff Tuff

Very Stiff Silty Sand

Hard Sandy Silt

Stiff Sandy Silt

Very Stiff - Hard Clay

Ground water level from piezometer readings
Sliding plane from inclinometer readings

Fig. 12 Position of ground water level and sliding
plane according to monitoring readings
This information confirms that sliding plane
were below MSE-Wall base construction. The
prediction of the sliding place is at the boundary of aslightly impermeable layer (tuff material) that is
above the porous layer, namely sandy silt.
It is estimated that the groundwater table
saturating the toe of the slope that resulted inweathering of the tuff material and reduce the shear
strength. The landslide were progressive, starting at
the toe of the embankment slope that softened due toweathering and saturation.

Fig. 13 Correlation between cohesion reduction to
decreasing of FoS
Analysis by reducing tuff cohesion parameter
conducted to closely represent soil softening and as
seen in Fig. 14, sliding plane are relatively close to
the actual displacement measured at field. In thisillustration we can confirmed that the actual sliding
plane were deep below the position of MSE Wall.
Furthermore, for this kind of situation it is also
concluded that retaining structure are not effective toovercome deep sliding plane. The weight of theretaining structure could give an extra weight ordead load in the slope that trigger large displacement,
especially when the shear strength at toe ofembankment were reduced due to softening by
surface water runoff.

SOIL PARAMETER AND STABILITYANALYSIS RESULT
To
identify
theappropriate
landslidecountermeasure for road embankment over tuff
material, mechanism of embankment failure wasanalyze using back analysis methodology and finite
element numerical modelling.
Soil parameters used in the stability analysis
were based on N-SPT correlation for sandy soils [9]and tuff [2]. Back calculation analysis conducted
only on Soft-Medium Stiff Tuff parameter byreducing cohesion (c’) until Factor of Safety (FoS)
nearly 1 (one) (Fig. 13) and the sliding plane
represent the actual condition as seen in Fig. 12.
Soil parameter resulted from back calculation
analysis and geogrid used in the MSEW finite
element
methodmodellingusing
Plaxis2-Dimension software were resumed in Table 1 andTable 2.

FoS = 1.09

Fig. 14 Sliding plane according to back calculation
analysis
Since the depth of sliding plane are 7.0 m below
position of BH-2, the expected depth of piles for
slope reinforcement are minimum 14.0m or twotimes the depth of sliding plane. Since the locationof the research are in rural area, and there are
difficulties to get large diameter of boring machine.
The diameter of bored piles that used in thisevaluation are 0.8 m based on the availability of
local machinery close d to the project area. To avoid
visco-plastic flow [10] between piles, spacing ofpiles evaluated were 2 times diameter of piles (1.6 m
spacing center to center) and reinforced concrete
retaining structure are constructed above pile cap.

Table 1 Soil parameters
Description
Soft-Medium Stiff
Tuff
Stiff Sandy Silt
Very Stiff Silty Sand
Very Stiff – Hard
Clay
Hard Sandy Silt
Embankment(kN/m3)
18

5000

c‘
(kPa)
0.1

’
(deg)
27

18
19
17

10000
28000
35000

1
5
15

30
35
30

18
17

27000
25000

5
15

32
25

E (kN/m2)

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SEE-Mie, Japan, Nov.10-12, 2022

First evaluation (Fig. 15) show that after
application of 14 m length of bored pile below
concrete retaining structure and 15 kPa traffic load,
the FoS increased into 1.2 and sliding plane moved
at toe of embankment. This condition indicated thatthe embankment condition relatively stable after
application of bored pile and retaining structure. To
evaluate the global stability of road embankment,
regrading at toe of embankment slope wereconducted in the second evaluation (Fig. 16) toreduce the acting force and check the overall
stability, especially at roadside. According to theresult on the second evaluation, FoS increased into
1.28 which is above the minimum required by
National Standard [11] 1.25.
Evaluation using combination of bored pile andretaining structure also regrading at toe ofembankment shown good result and recommended
to use as deep landslide problem of embankment
over tuff material.

could help engineer to evaluate the cause of
instability of road embankment construction.
Thorough forensic geotechnical investigation
using numerical method will provide a more clear
determination on landslide problems and how toincrease the stability of the embankment using theappropriate reinforcement.
According to the numerical simulation,
reinforcement of slope using bored-pile combinewith retaining structure and slope regrading at toe ofembankment could solve the deep sliding plane andincrease the slope factor of safety.
ACKNOWLEDGMENTS
Author would like to thanks Implementation Unitof National Road, Jambi and Institute of Road
Engineering for sharing of knowledge and data
sharing throughout the landslide evaluation process.
REFERENCES[1] Torok A., Basri A., Bogoly G., Lovas T.,
Somogyi A., and Gorog P., Slope Stability andRockfall Asessment of Volcanic Tuffs Using
RPAS with 2-D FEM Slope Modelling. Nat.
Hazards Earth Syst. Sci., 18, 583-597, 2018.
[2] Asniar N., Purwana Y. M., Surjandari N. S.,
Tuff as Rock and Soil: Review of The
Literature on Tuff Geotechnical, Chemical andMineralogical Properties Around.
AIP
Conference Proceedings, 2114, 050022, 2019.
[3] Naveed A. M., Ali Z., Qadir A., Latif U. N.,
Hamid S., Sarwar U., Geotechnical Forensic
Investigation of a Slope Failure on Silty Clay
Soil. Front. Struc. Civ. Eng., 14, 501-517,
2020.
[4] Clough G. W., O’Rouke T. D., Construction
Induced Movement of in-situ Walls. ASCE
Conference Proceeding on Performance ofEarth Retaining Structures, Geotechnical
Special Publication No. 25, ASCE 439-470,
1990.
[5] Simandjuntak T. O., Budhistrisna T., Surono.,Gafoer S., Amin T. C., Geological Map of The
Muarabungo
Quadrangle,
Sumatera,
Geological Research and Development Centre,
1994.
[6] National Standardization Agency, Guidance ofInclinometer Installation and Monitoring the
Horizontal Movement of the Ground,Indonesian Standard, SNI 3404:2008, 2008.
[7] National Standardization Agency, Guidance ofSoil Pore Water Pressure Measurement using
Open Standpipe Casagrade, IndonesianStandard, SNI 8134:2015, 2015.
[8] National Standardization Agency, Guidance ofRecording and Identification on Core Drilling
Result, Indonesian Standard, SNI 2436:2008,

FoS = 1.20

Fig. 15 Sliding plane according to back calculation
analysis

FoS = 1.28

Fig. 16 Sliding plane according to back calculation
analysis

CONCLUSIONS
Softening of tuff material at the embankment
toe could triggered progressive instability to the roadembankment and shallow reinforcement such as
geogrid-reinforced earthworks (MSE Wall). MSW
wall or retaining structure could acted as additionalload to the embankment slope and when theembankment slope saturated could cause instability.
Evaluation on this case showed that meticulous
examination on geotechnical aspects, especially withgood soil investigation and proper instrumentation
placement such as inclinometer and piezometer

251

SEE-Mie, Japan, Nov.10-12, 2022

2008.
[9] Hatanaka M., Uchida A., Empirical Correlation
Between Penetration Resistance and Internal
Friction Angle of Sandy Soils, Japanese
Geotechnical Society, Soils and Foundations
Vol. 36, No 4, 1-9, 1996.
[10] Firat S., Stability Analysis of Pile-Slope
System, Scientific Research and Essay vol. 4(9), pp. 842-852, 2009.
[11] National Standardization Agency, Geotechnical
Design Requirement, Indonesian Standard,
SNI 8460:2017, 2017.

252

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FIELD PERFORMANCE EVALUATION OF ENVIROMENTALLYFRIENDLY PREFABRICATED VERTICAL DRAIN (PVD)
Dea Pertiwi
Geotechnical, Tunnel, and Structure Division, Ministry of Public Works and Housing, Indonesia

ABSTRACTThe application of natural materials for soil improvement has recently been highly considered. PrefabricatedVertical Drain (PVD) is widely used in Indonesia to accelerate the process of settlement of soft soil. PVD madefrom jute fibers tend to decompose easily in the soil after the service period is over, thus not storing plastic waste
underground. After providing good hydraulic and mechanical performance when tested in the laboratory, jute PVD
was tested in the field, which is in a small pond area in Kendal Regency, Central Java. The depth of the soft soil
is 20-24 m and is still influenced by tides. Through the installation and monitoring of geotechnical instrumentation,
it turns out that up to 120 days (4 months) after construction, the consolidation rate in natural and synthetic PVD
areas has reached > 90%. Under preloading, the settlement is estimated 10% greater than the synthetic PVD area.
Monitoring results also predict the effective depth of jute PVD installation is 14 m, in the transition from soft silty
clay to clayey sandy silt with the largest permeability coefficient (k) of 9 x 10-8 cm/s and consolidation coefficient(Cc) of 0.86. At this depth, the largest value of vertical compression and excess pore pressure were detected. It canbe concluded that in a limited (very small) experimental scale area, the installation of pre-construction
instrumentation must consider the effect of heavy equipment loads working on the instrumentation points because
it will greatly affect the accuracy of the monitoring results.
Keywords: PVD, Natural materials, Field performance, Geotechnical instrumentation

INTRODUCTION

PVD model with the best technical performance [2]and [3]. In 2018, verification of the model studied in2017 was carried out through the creation of a trial
scale physical model to monitor actual performancein the field and compare it with synthetic PVD [4].

Prefabricated Vertical Drain (PVD) technology
made from polymer has been widely recognized as
one of the soil improvement technologies with its
main function of dealing with the problem ofsettlement on soft soil by accelerating theconsolidation process. The demand for the use of
PVD technology in Indonesia is very large because
the soft soil area in Indonesia covers 10 million
hectares or about 10% of Indonesia's land area [1].
Preloading with PVD is one of the technologies used,beside other soil improvement technologies.
In addition to synthetic PVD, natural PVD is also
widely used, especially outside Indonesia (Japan,
Korea, Bangladesh, India) mainly because ofenvironmental preservation considerations. The
advantages of PVD made from natural materials are
non-toxic, recyclable, high liquid absorption,
relatively fast disintegration time in the soil due to thenature of the material that is easily biodegradable.
Thus, in less than a year the PVD material has
decomposed in the soil. This is very suitable for dense
urban areas because the location of the former PVD
installation can be used for other undergroundconstructions.
In 2015 to 2017 a study was conducted on natural
fibers that have the potential as raw materials formaking PVD on a laboratory scale with a variety ofnatural materials and PVD geometries to obtain a

LOCATION OF OBSERVATIONS
Figure 1 shows the geological map of Kendal
regency. From the map, it is known that there arerecent alluvial deposits consisting of sand and gravel
along the main rivers. The Holocene Formation is avery soft grey clay containing layered shells and is in
the form of a sand lens towards the highlands in thesouth.

Kaliwungu

Fig. 1 Geological condition
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SEE-Mie, Japan, Nov.10-12, 2022

The location of observations is in Kaliwungu
district, located at Kendal Regency port highway andis ± 2.5 km before the Kendal port location so that theponds around the site are still affected by the tides.
Consideringitshydrogeological conditions,
Kaliwungu is an area that often experiences floodingwith a flood water level that is regulated so that it canirrigate rice fields of residents (Fig. 2).

Embankment

Very soft clay
Soft clayey
sandy silt

Soft clayey
sandy silt

Firm clayey
sandy silt

Fig. 4 Cros section of observation area

Residence
Road

Residence

PREFABRICATED VERTICAL DRAIN (PVD)

Pond
Road

Pond

The type of PVD installed is natural PVD. The
filter blanket material is woven jute fiber, while thecore material is coconut fiber. PVD is 9.5 cm wide
and 11 mm thick. Synthetic PVD as a comparison inthis study is made of non-woven geotextile material
and polypropylene core with a width of 5.25 m and a
thickness of 1.2 mm. PVD is installed up to a depthof 23.5 m with an installation space of 1.2 m using a
triangular pattern. The working platform is 1.0 mhigh; sand (horizontal drainage) is 0.5 m thick, andthe embankment (preloading) is 1.5 m high, which
has considered the critical embankment height.
Layout of PVD installation and instrumentation
modified from [6] and given in Fig. 5.

Pond

Fig. 2 Area of observation
The soil layer investigated from two boreholes,
BH-1 and BH-5 data are grey soft clayey sandy siltwith very soft consistency to a depth of 6.00 meters.
Underneath there is a grey clayey sandy silt with asoft consistency to a depth of 20.50 – 21.00 meters.
Borehole 1 (BH 1) indicates grey clayey sandy silt
was found with a firm to stiff consistency, up to adepth of 30.00 meters.
Three locations of Cone Penetation Test (CPT)
are plotted into a correlation graph for mechanicalsondir [5] and showed in Fig. 3 and Fig. 4. From CPT1 up to a depth of 16.40 meters found very soft to soft
clayey sandy silt with a predicted value of undrained
shear strength (cu) 12.5 to 25 kPa. At a depth of 16.60– 21.20 meters found clayey sandy silt with softconsistency and a predicted cu of 25 to 30 kPa, andbelow it is followed by silty clay and sandy silt withfirm consistency and a predicted cu of 50 kPa.
Estimation of undrained shear strength refers to [1].

1.
2.

Embankment (preloading)
Horizontal drainage andworking platform
3. PVD
4. Soft soil
5. Permeable soil
6 and 7 Instrumentation(settlement plate, piezometer,
and extensometer)

Fig. 5 PVD and instrumentation layout
CPT-1 & Vane Shear
Borehole-1

CPT-3

FIELD OBSERVATIONS

Embankment

Very soft clay

Instrumentation installation aims to observe thefield performance of embankment after being
improved with PVD and preloading. The procedure
follows the Indonesian Standard for Geotechnical
Design Criterias [7], PVD specification [8], andinstrumentation specification [9]. Figure 5 illustrates
the layout of the instrumentation installation.
Piezometers are installed to determine the porewater pressures that occur at different layer depths
and are positioned between the installed PVDs (seeFig. 5). The number of installations is a minimum of
one observation point in each layer [10].

Soft clayey
sandy silt

Pond

Pond

Soft clayey
sandy silt

Firm clayey
sandy silt

Fig. 3 Longitudinal section of observation area

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SEE-Mie, Japan, Nov.10-12, 2022

The inclinometer is installed at the toe of theembankment to determine the lateral direction of soil
movement with the installation procedure that refers
to [11] and [12]. The inclinometer must be installedon the part of the embankment slope that is mostprone to stability or with the inclinometer depth
entering to a hard soil layer where lateral soil
movement will not occur.
Settlement plates are installed at distance of 50
meters above the original soil surface and 3 (three)points are installed in a cross section at the centre of
the embankment and both left and right sides to
describe the settlement contour. The installation of
fixed reference points on soil conditions that are notaffected by subgrade subsidence aims to determine
the subgrade settlement of soft soil. The monitoringof the settlement plate aims to observe the magnitudeof the settlement when PVD and preloading areconstructed [9].
Extensometers or deep settlement probes are
installed to determine the movement in each soil layer
in the vertical direction. The extensometer is placedin each soil layer which has different soil properties
and soil consistency [9].

vertical compression in this layer is 55 cm and is thelargest post-construction compression.
Post-construction spider magnet readings insynthetic PVD area occurred in Extensometer-3 at a
depth of 3.5 m, in very soft clay layer. Similar with
Extensometer-1, the last reading on the spider magnet
at a depth of 11 m, 16 m and 21 m was only able totake before PVD installation and preloading. It issuspected that heavy equipment traffic above theextensometer point caused the hole to be clogged withsand, because the hole was not properly protected.
However, the Extensometer-3 in the area between
natural PVD and synthetic PVD can still bemonitored until the end of construction. The reading
results indicate that the data fluctuates during the
PVD installation process, and the compression of soft
soil gradually becomes consistent after both types of
PVD installation and preloading (Fig. 6).

RESULTS AND DISCUSSION

Fig. 6 Compression of soft soil by extensometerreading in PVD area

Prediction of post-construction settlement using
the ASAOKA method as well as the actual reductionof geotechnical instrumentation monitoring results
indicate that up to 120 days (4 months) postconstruction, consolidation in natural PVD andsynthetic PVD areas has reached > 90%. However,monitoring was continued for up to 210 days (7months). Predicted settlement 7 months after
construction is 104 cm.

Fig. 7 Monitoring average depth of Extensometer-1(area of natural PVD)

Settlement plates and surface markers
Under preloading, the settlement of natural PVD
is estimated 10% greater than the synthetic PVD.
Monitoring of settlement plates and surface makers in
the natural PVD installation area, showed that thesurface settlement at the embankment ranges from 90– 100 cm, while at the toe of the embankment 20 cm.
In the synthetic PVD installation area, the surface
settlement at the embankment is between 70 – 90 cm,
while at the toe of the embankment it is 40 – 50 cm.

InclinometerAt this observation site, the inclinometer is placed
at toe of the embankment. The lateral movement in
the transverse direction of the embankment or A-B
direction (Southeast) is 56.11 mm (in very soft clay at
a depth of 2 m) with an incremental displacement of
13 mm per month (Fig. 8). Meanwhile in thetransverse direction of the embankment or C-D
direction (Southwest) is 76.05 mm (on very soft soil
at a depth of 4 m) with an incremental displacementof 20 mm per month. Readings are taken preconstruction, during construction and postconstruction.

Magnetic extensometers
In natural PVD area the largest verticalcompression due to PVD installation andembankment filling occurred in Extensometer-1 at a
depth of 14 m, in the transition between very soft tosoft clayey sandy silt with cu = 19 kPa, ' = 24, thelargest permeability coefficient (k) of 9 x 10-8 cm/s
and consolidation coefficient (Cc) of 0.86. The
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SEE-Mie, Japan, Nov.10-12, 2022

The findings from field observations are
summarized as follows:
1) Seven months after construction, both types of
PVD showed great field performance andprovided a significant settlement acceleration.
2) Installation of PVD is effective up to a depth of
14 m, in the transition from soft silty clay toclayey sandy silt with values of cu of 19 kPa and' of 24°, the largest coefficient of permeability,
k is 9 x 10-8 cm/s and Cc of 0.86.
3) The vertical compression in this layer is 55 cm
and is the largest post-construction compression.
4) The results of monitoring excess pore waterpressure show that the largest excess pore waterpressure during construction and post
construction occurs at a depth of 10-15 m. In
addition, the calculation of the stress distribution
using the Boussinesq analysis gives the greatest
increase in effective stress occurring up to adepth of 15 m.

Fig. 8 Inclinometer readings
Piezometers
Four months after construction, equilibrium
conditions have been reached in the natural PVD area.
However, data collection still continues to sevenmonths. Constant pore water pressure near zero in
Piezometer-1 at reaches values of -159 kPa (10 m
depth), -4 kPa (20 m depth), and -3 kPa (30 m depth).
In the synthetic PVD installation area which wasmonitored using a Piezometer-2, equilibrium
condition has also been reached with constant porewater pressure approaches zero at values of -19 kPa(5 m depth), 1.2 kPa (15 m depth), and -14 kPa (25 m
depth).
The largest excess pore water pressure occur at a
depth of 10-15 m. Below that, the effect of PVD
installation and embankment filling did not appear
too significant. As with the extensometer, thepiezometer tip cannot be read after PVD installation.
It is suspected that heavy equipment traffic above thepiezometer point caused the borehole to be cloggedwith sand, because it was not properly protected.
Figure 9 illustrates pore pressure reading before,
during, and 3 to 7 months after the PVD installationand preloading. Final fully instrumented embakment
shown in Figure 10. The procedure for embankment
filling and preloading refers to Division 3 of theGeneral Specifications of Highways [13].

Fig. 10 Final area of embankment

CONCLUSIONSIn field application natural PVD can match theperformance of synthetic PVD. On a laboratory scale,
PVD made from natural materials has also been
proven to have good properties.
Observations of external factors such as
fluctuations in rainfall and the influence of tides
should be considered in determining the design
parameters, and they are easier to simulate throughnumerical modeling. Direct field observation ispossible by making an observation pipe to getgroundwater level fluctuations during theconstruction period until the service period is
exceeded.
The installation of instrumentation must pay
attention to the effects of construction work to avoid
damage to the instrument due to heavy equipment
traffic during construction. The security of theinstalled instrumentation must be done properly.
It can be concluded that in a limited (very small)experimental scale area, the installation of pre-Fig. 9 Piezometer reading256

SEE-Mie, Japan, Nov.10-12, 2022

construction instrumentation must consider the effectof heavy equipment loads working on the
instrumentation points because it will greatly affectthe accuracy of the monitoring results.

Balkema/Rotterdam/Brookfield/1996.
The
Netherlands. 1996.
[6] BSI. 2007. BS-EN: 2007 Execution of Special
Geotechnical Works – Vertical Drainage. BS EN
15237:2007. British Standard. United Kingdom.
[7] National Standardization Agency. Geotechnical
Design Requirement, Indonesian Standard, SNI
8460:2017. 2017.
[8] Directorate General of Highways. SKh-2.3.6.
SpecialSpecification(Interim-2)
ofPrefabricated Vertical Drain (PVD). February
2017.
[9] Directorate General of Highways. SKh-1.3.7
Special Specification (Interim) of Geotechnical
Instrumentation. December 2015.
[10] National Standardization Agency (BSN). SNI
6461:2012. Procedure for Installation andReading of Vibrating Wire Piezometer. 2012.
[11] National Standardization Agency (BSN). SNI
3404:2008.
Guidanceof
Inclinometer
Installation and Monitoring the Horizontal
Movement of the Ground. 2008.
[12] TRB. Use of Inclinometers for Geotechnical
Instrumentation on Transportation Project.
Transportation
Research
Board.
http://onlinepubs.trb.org/onlinepubs/circulars/ec
129.pdf. 2018.
[13] Directorate General of Highways. GeneralSpecifications for Road and Bridge Construction
Works. September 2018.

ACKNOWLEDGMENTS
The author would like to thank the Geotechnical,
Tunnel, and Structure Division for providing theopportunity to write down the results of research,development, and evaluation of the field performanceof natural PVD, so it can be used as a lesson learned.
REFERENCES[1] Ministry of Settlement and Regional
Infrastructure. Pt T-08-2002-B. Geoguide 1 –Occurrence and General Nature of Soft Soils,
Guideline of Road Embankment on Soft Soils.
2002.
[2] Moelyani, D. The Development of Local
Materials for Prefabricated Vertical Drain (PVD)
Technology. ISBN: 978-602-264-141-4. Road
and Bridge Research and Development Center(Pusjatan). December 2015.
[3] Pertiwi, D., Iqbal, M., Aldiamar, F. Performance
Evaluation of Natural-Based Indonesian Made
Prefabricated Vertical Drain (PVD). ISBN: 978602-264-136-6. Road and Bridge Research andDevelopment Center (Pusjatan). December 2017.
[4] Pertiwi, Dea. Trial Scale of Natural-Based
Indonesian Made Prefabricated Vertical Drain(PVD). Road and Bridge Research andDevelopment Center (Pusjatan). December 2018.
[5] CUR. Building on Soft Soils. A.A257

8th Int.
on Structure,Engineering& Environment(SEE),(SEE),
8thConf.
Int. Conf.
on Structure,Engineering& EnvironmentMie, Japan,
Nov.10-12,
2022, 2022,
ISBN:ISBN:
978-4-909106094
C3051C3051
Mie, Japan,
Nov.10-12,
978-4-909106094

AN APPROACH STUDY OF REDUCING THE SUB-BALLAST
THICKNESS OF RAILWAY USING GEOTEXTILES
Prof.Dr. Saad F.I. AL-Abdullah1, Mr. Zaman T. Teama 2, Maysaloon A. Zaidan3 and Dr.Suha Aldahwi 4
1

B.Sc., M.Sc., PhD (CE).MISSMGE.M.I.ASCE, Faculty of Engineering. Isra University, Jordan
2
3

B.Sc., M.Sc., Baghdad University, Baghdad, Iraq2

B.Sc. Faculty of Engineering, Mustansiriyah University, Baghdad, Iraq
4

B.Sc., M.Sc., PhD Faculty of Engineering. Isra University, Jordan
ABSTRACTThe Iraq transportation system suffers from poor and deformation in railways due to less maintenance andupdating of the railroad. The country needs thousands of kilometers of new railways to develop thetransportation system to transport goods and people. This paper will investigate the behavior of railways whenchanging the thickness of the sub-ballast and use geotextile above ballast, ballast/ sub-ballast interface, andsub-ballast/ subgrade interface through using the finite element approach by simulating the railway by the
ABAQUS program. The sub-ballast thicknesses used are; 150, 200, 250, 300, 350, and 400 mm with 200mm
ballast thickness and 4 m subgrade thickness. The results showed when the thickness of the sub-ballast
increased by 50 mm it led to a reduction in deformation of about 7.2 %. Also illustrated that the best position
to reduce deformation in the railway was when putting a geotextile above the ballast. The results illustrate thatusing geotextile above the ballast layer Equivalent to increasing the thickness of the sub-ballast layer by about
3.57 cm in decreasing deformation in the rail track.
Keywords: ABAQUS; Railway, Sub-ballast, Geotextile, Sub-ballast, and Equivalent Thickness
INTRODUCTION

The investigation aims to estimate the effect ofusing geotextile instead of increasing the thicknessof sub-ballast layers and studying the structuraleffect of using geotextile at different positions inrailway structure on deformation, verticalsettlement, and lateral displacement of the railway.
The laboratory tests do not provide acomprehensive understanding of what happens andthe mechanisms of stresses, strains, anddeformations distribution in the layers of therailway when the train passes over the rail, so thenumerical analysis (FEM) approach was used 15
to illustrate the effect of using geotextile of railway
stability.

Iraq considers a growing country, and its
infrastructures suffer from destruction due to thewars and the absence of maintenance and updatingof its railways. Iraq needs to construct a newrailroad to improve the transportation system andcarry people and heavy goods. So we need a stablerailway able to resist track degradation and lateral
instability, which may become a complex problem
if we construct a weak railway structure underconditions of railroad loading 1.
The railway ballast layer consists of particles ofcourse, aggregate due to the repeated heavy load oftrain become deteriorated let to increasing
compressibility 2345. The effectiveness ofgeosynthetics in railroad tracks has signified
investigated in the past, and it's established thatgeosynthetics generally increase road performanceby decreasing the deformation and degradation ofballast 67891011121314. Limited
research has studied the interaction between
geosynthetics ballast aggregates when large strain
happens due to heavy repeated loading 1516.
Suiker and de Borst 16 were studied by A
numerical model to demonstrate the maximum
plastic deformations produced during repeatedloading. The effect of geotextile on improving
railway was investigated by 111217 18 19.

ESTABLISHMENT OF FINITE ELEMENTMODELThe FE approach has been established to be auseful and valid method for predicting the responsesof railway structures under loading conditions
12021. The researchers have used the FE
approach to investigate the behavior of rail track
response below heavy loads by numericalsimulations, which focused on
the behavior ballasts layer with and without
geotextile 12 15 21.

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MODELING

EFFECT OF CHANGE THICKNESS OF SUBBALLASTABAQUS has proved its validation in the analysis
ofgeotechnicalproblems2223.Inthis
investigation, a three-dimensional finite element
model was built by simulating the railway with allits parts, multi-layer geotechnical material,
including subgrade, sub-ballast, ballast, sleeper, andrail, as illustrated in Fig 1.
The rail track was simulated in the model withdimensions. The width and height of the subgrade
are 12 and 4 m, respectively. For studying the effectof change thicknesses of the sub-ballast layer, fivemodels were built with five sub-ballast thicknesses,
200, 250, 300, 350, and 400 mm, and the thicknessof ballast and sleeper was 200 and 150 mm,
respectively, for all models. For investigating theeffect of geotextile and its position in the behaviorof railroad, four models were built with layer
thicknesses of sub-ballast. Ballast and sleeper were200, 200, and 150 mm, respectively, with different
positions of placing geotextile.
The gauge between the two rails of the track is 1.68
m, and the length of the sleeper is 2.5m. The rail is
simplified as a rectangle with a width of 16 cm anda height of 5cm to ensure that the total area isequivalent to a 60 kg/m rail 2124.

To investigate the effect of change thickness of the
sub-ballast layer in decrease deformation, verticalsettlement, and lateral displacement the railway five
thicknesses of the layer were used which are 200,
250, 300, 350, and 400 mm.
Use at most three levels of headings that correspondto chapters, sections and subsections. The first level
headings for chapter titles should be in 10pt, bold,
justified, and upper case font. Leave one blank line
before and after the first level headings, respectively.
EFFECT OF USING GEOTEXTILEThe effect of using geotextile in decrease
deformation, vertical settlement, and lateraldisplacement of railway investigate by putting thegeotextile layer in different positions; at subgrade/
sub-ballast interface (above subgrade), at subballast/ ballast interface (above sub-ballast), and at
ballast/ sleeper interface (above ballast) andevaluate which position gives minimum
deformation, vertical settlement, and lateraldisplacement in the rail track.
ELEMENT TYPE AND MESH SIZE

MATERIAL PROPERTIES FOR MAINCOMPONENTS
The input material properties of the ABAQUS
models play important role in the results of the
program. Table 1 illustrate the material properties
used in the railway simulation, which are used in
finite element analysis for railways 21 The linear
response is used for simulating the subgrade,
granular layers, and geotextile 1322.

All parts of the models were used finite element
type 8-node continuum three-dimensional brickelement (C3D8R) 22. The mesh size of elementschanges from medium for subgrade to fine for rail
as shown in Fig.2.
LOAD CALCULATION
The load which used in the simulation of train load
was dynamic wheel load is empirically expressed as
the static load wheel, with the value of 178.71 KN
was considered to simulate a train speed of 80 km/h
and a wheel diameter of 970 mm,21 2526.

Fig.1 ABAQUS Model Geometry
Table 1 Input Materials Properties
Sub
Property
Subgrade Ballast
Modulus ofelasticity (N/m) 125𝟏𝟎𝟓 800𝟏𝟎𝟓
Density (Kg/m3) 1632
1700
Poisson's Ratio
0.4
0.35

Ballast1200𝟏𝟎𝟓
1590
0.25

Fig. 2 mesh size of FE model259

SEE-Mie, Japan, Nov.10-12, 2022

displacement and thickness of sub-ballast for
thicknesses 200,250,300,350 and 400mm

RESULTS AND DISCUSSIONS
Effect of Change Thickness of Sub-Ballast

Figs. 6-9. Shown the relationship between the
deformation, vertical settlement, and lateraldisplacement in railtrack and thickness of the subballast layer which illustrated that the deformations
decrease as the thickness of sub-ballast increased.

The deformation, vertical settlement, and lateraldisplacement were measured at the surface of theballast layer under the sleeper which plays a very
important role in the stability of the railway and safe
pass of the train, for each thickness of sub-ballast
layers which are 200,250,300, 350 and 400 m. The
results of the analysis illustrated that theincreasesing the thickness of sub-ballast lare led todecreases in deformation, vertical settlement, andlateral displacement of rail track as shown in Figs
3-5 respectively.

Deformation in m

0.00750.007
0.00650.006
0.0055
0.005
150

250

350

450

Sub-ballast thickness in mm
Fig. 6 Shows the relationship between deformationand sub-ballast thickness
Effect of Using Geotextile
to investigate the effect of geotextile in reduce
deformation, settlement, and lateral displacement inrail track the geotextile was putted in three positions,above subgrade, above sub-ballast, and above
ballast layer, the result shows that the maximum

Vertical Settlement in m

Fig.3 Shows the relationship between deformationand thickness of sub-ballast for thicknesses
200,250,300,350 and 400 mm

Fig. 4 Shows the relationship between verticalsettlement and thickness of sub-ballast for
thicknesses 200,250,300,350 and 400 mm

0.008
0.00750.007
0.00650.006
0.00550.005
0.0045
0.004

150

250

350

450

Thickness of sub-ballast in cm

Fig. 8 Show the relationship between the lateraldisplacement and sub-ballast thickness
Effect of geotextile in reducing deformations andvertical settlement was when putting it above theballast layer as shown in figs. 9-10, respectively.
The results also show that the putting of geotextile
above sub-ballast layer was less effective thanputting it above ballast in decrease deformationsand vertical settlement and the putting geotextile
above subgrade was given minimum effect in

Fig. 5 Shows the relationship between lateral260

SEE-Mie, Japan, Nov.10-12, 2022

reducing deformation as illustrated in Figs. 9-10.

so close each one to other, one of the models with athickness of sub-ballast 25 cm which has
deformation 0.00682 m and another one with
geotextile reinforcement was putted above a ballast
layer which has deformation 0.00693 m.
Fig. 12 shows the vertical settlement for all models,illustrating that the change in thickness of subballast was more effective in reducing verticalsettlement than geotextile. Also, the figure showsthat the least deformation, vertical settlement, andlateral displacement in rail track were for rail trackwith a sub-ballast thickness of 40 cm. The rail trackwith large deformation (excluding the reference
model), was in rail track with reinforcing geotextile
above subgrade.
Fig.13. Shown the lateral displacement for all
tracks, the figure is illustrated that the use of
geotextile led to an increase in lateral displacement
at the surface of the ballast, while the increased
thickness of the sub-ballast led to a decrease inlateral displacement.

Deformation in m

0.00740.00730.00720.00710.007

0.00690.00680.0067
with out
geotextile

Geotextile
above
subgrade

Geotextile
above
subballast

Geotextile
above
BallastFig. 9 shows the relationship between the positionof geotextile and deformation in the rail track

Vertical settlement in m

0.00740.00730.00720.0071
0.007

Percentage of Reduction in Deformations

0.00690.0068Fig. 14. Shown the percentage of reduction in rail
track deformation for each model illustrated that themodel with a sub-ballast thickness 40 cm has thelargest percentage of reduction in deformation andthe model with reinforcement at subgrade has thesmallest percentage of reduction in deformation

0.0067
with out
geotextile

Geotextile above Geotextile
Geotextile
subgradeabove subballast above Ballast

Fig. 10 shows the relationship between the positionof geotextile and vertical settlement on the rail track
Comparison between models

The Sub-Ballast Thickness that Geotextile
Equivalent it

thickness of sub-ballast and the effect of position ofreinforcement of geotextile in reduce deformation,
vertical settlement, and lateral displacement of rail
track. The Colum with the red color shown in the
figures represents a railway without reinforcement
and with a sub-ballast thickness of 20 cm, which isconsidered a reference (origin) model forcomparison between all models,Fig. 11. Demonstrated the deformation for allmodels, from the figure, we can see the increase inthickness of the sub-ballast layer effected indecreasing the deformation of the rail track, the fig.
11. illustrated that are two models with deformation

This part will determine how much geotextile isequivalent to the thickness of sub-ballast in reduce
the same value of deformation, the value of
deformation obtained from using geotextile was
0.00693 when putting the reinforcement above
ballast layer, from the relationship between
deformation and The thickness of sub-ballast
thickness, we can find that geotextile is equivalent
to 3.57 cm of sub-ballast thickness as shown in Fig.
15. Table 2 shown the equivalent thickness of the
sub-ballast and the position of the geotextile

Fig. 12. Shown the vertical settlement

Fig. 11 Shows the deformation for all models

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SEE-Mie, Japan, Nov.10-12, 2022

2.

3.
Fig. 13. Shown the vertical settlement
4.

5.

Fig. 14. percentage of reducing deformation in rail
track

6.

7.

8.

Fig. 15. Shown the calculation of equivalent
thickness of sub-ballast
Table 2. Illustrate the Geotextile position equivalent
to the thickness of sub-ballast
Geotextile position
Above ballast
Above sub-ballast
Above subgrade

9.

Equivalent to sub-ballast
thickness (cm)
3.57
2.85
N/P

The increase of the sub-ballast layer led toa decrease in the vertical settlement in therail track through an increase in the
distribution of loads come from the train.
As the thickness of the sub-ballast increase
the lateral displacement decrease throughdecrease the stress at sub-ballast/ subgradeinterface.
The use of geotextile reinforcement atballast (sleeper/ ballast interface) led to adecrease in the deformation in the rail trackby about 5.71 % through the distribution of
the stresses at the sleeper/ ballast interface.
The use of geotextile at ballast/ sub-ballast
interface led to a decrease in the
deformation about 4.65%
The using of geotextile at sub-ballast/
subgrade interface (above subgrade) led todecrease deformation about 0.68 %.
The maximum useful position of
geotextile as reinforcement layer to reduce
deformation in rail track was above ballast
layer and the minimum influence of
position reinforcement was in above a
subgrade layer
The maximum percentage of reduction in
deformation was for rail track with subballast thickness 40 cm and the minimum
percentage of reduction deformation waswhen reinforcing the rail track with
geotextile above subgrade layer.
The use of geotextile as a reinforcement
layer at the sleeper/ballast interface
equivalent to increasing the thickness ofthe sub-ballast layer by about 3.57cm.

LIMITATIONS OF THIS STUDY
The properties of geotextile play a very
important role increase the benefit of using it, in thispaper the modules of elasticity of geotextile was
120 MPa, the geotextile which has a modulus ofelasticity less than 120 MPa not evaluated The
result and conclusion represented in this paper
shows that we need more investigation before used
geotextile above subgrade, sub-ballast, and ballast.

CONCLUSIONSThe simulation of railway track has investigated the
behavior of rail track under train loading when the
sub-ballast layer change thickness and the behaviorof track when reinforced by a geotextile. The
following conclusions are obtained from thisresearch;
1. The increase in the thickness of the subballast layer by 5 cm decreases thedeformation by about 7.2% by reducing
the stress reaching the subgrade andincreasing the track's strength and stability.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EVACUATION RISK ASSESSMENT OF FLOODED SLOPING ROAD
IN THE CITY OF KAMAISHI

1

Yuriko Matsubayashi1 and Mako Ebina2
Faculty of Science and Engineering, Iwate University, Japan; 2 Aomori, Japan

ABSTRACTAs heavy precipitation due to climate change increase, need of quantitative assessment of flood risk gain in
importance. Studies have been made on evacuation risk evaluation of flooded road. However, there is little
agreement on risk assessment of flooded sloping road. The purpose of this work is to establish method of estimatingrisk of evacuation on flooded, water flowing slopes.
In the hazard map of the city of Kamaishi, hazardous areas in the events of heavy rain, such as flooded area,
debris flow and steep slopes are shown. It also describes the danger of water flow running over the sloping roads,
which prevented evacuation in the past disaster. However quantitative risk assessment of the sloping roads is not
performed. This paper presented risk evaluation of evacuation on foot on the slopes, using fluid force calculatedusing estimated velocity and water depth with the maximum rainfall in the past. Velocity and water depth are
estimated using rational runoff formulae and velocity formulae,
As a result, more than 30% of the 86 sloping roads described in the hazard map are unsuitable for evacuationroute and a positive correlation is observed between the risk and upstream area.
In conclusion, a simple evacuation risk assessment on sloping road with water flow could be performed withcalculating fluid force using estimated velocity and water depth.
Keywords: Flood, Inundation, Sloping road, and Evacuation

INTRODUCTION
On 12th, October, 2019, Hagibis made landfall on
Izu Peninsula in Shizuoka prefecture, Japan. After
that, Hagibis made its way to northward, weakened toan extratropical cyclone by 12 a.m 13th. Heavy rain
induced by Hagibis caused great damages especiallyin Tohoku region in Japan. 105 people are killed byflood and sediment disasters and 3 people are missing.
In Iwate prefecture, At Fudai forecast point in northarea of Iwate, rainfall of 95.0mm per hour is recorded.
3 people are killed and 7 people are injured by disaster
induced by Hagibis.
We carried out an interview survey for residents
in Iwate prefecture. The result of the survey showsthat people are exposed to danger during evacuation.
At Touni town in city of Kamaishi (Fig. 1 and 2),
several evacuees obstructed by water flow on thesloping road. As shown in Fig.2, the sloping road isevacuation route to Touni elementary and junior highschool, which is the designated evacuation shelter andrefuge place. Around 0 a.m. on 13th, the sloping road
was inundated. As water was flowing over like awaterfall, some residents couldn’t arrive at theevacuation shelter.
In the city of Kamaishi, they GIS hazard map
published on the internet. The hazard map shows
predicted flood, sedimentary disasters, tsunami
hazard and the designated evacuation shelters andrefuge places [4]. The map also shows past disaster
information caused by heavy rains. The past disasterFig. 1
Location of the city of Kamaishi in
Iwate prefecture, Japan.
An arrow and text are added on map [5]Fig.2
Sloping road at Touni town.
Arrows and text are added on map [5]264SEE-Mie, Japan, Nov.10-12, 2022

information is collected from local resident. It shows
many sloping roads which water or debris had flown
over while past heavy rain disaster. The sloping roaddanger in Touni town has been indicated in thehazard map as past disaster information; nevertheless,evacuees were exposed to danger.
It is well known that evacuation under flooding
condition is affected by water depth and velocity,
Suga et al [1] investigated safety threshold of water
depth and velocity．They proposed evaluation index
using fluid force, buoyant power and friction force [1].
Asai et al [2] use specific power to calculate safetyindex for evacuation. Dias et al [3] carried out anexperimental study to investigate human walking
behavior under inundation.
Although there are studies of evacuation underflooding conditions, there are few knowledge about
the danger of walking on sloping road under flooding.
In this study, we assessed evacuation risk using
estimated water depth and velocity calculated withrunoff volumes, slope and width of roads. We
extracted roads which are pointed out past inundationin the hazard map in the city of Kamaishi.
Precipitation data at Kamaishi station of AMeDAS
from 12th to 13th in October in 2019 are used for
estimation. There are various reasons for inundation
or water flow over sloping roads. We categorized theroads by reasons and determined catchment areas tocalculate runoff volumes in the catchment basin.
The results indicate that 30% of the roads shown
as flooded in the past are at risk for impassable during
heavy rain.

Fig. 3 Location of extracted roads.
Markers and dot lines are drawn on map [5]Table 1 road numbers in areas

METHOD
We extract 86 roads from the hazard map whichflooded in the past. Fig. 3 shows location of targetedroads in 7 areas which are Unosumai, Kurihashi,
Nakatsma, Kasshi, Kosano, Kamaishi and
Hirata/Touni. The gradation shows elevation. 7 areas
are administrative districts in the city of the Kamaishi.
Each area has geographical characteristic. Unosumaiarea includes lower reaches of Unosumai river andcape, while Kurihashi area is in upper reach of
Unosumai river. Kasshi, Nakatsuma, Kosano andKamaishi areas are located along Kasshi river. Most
houses are built in floodplain of Kasshi river or on
steep slopes along tributary rivers. Hirata/Touni area
is in the south of the city. Houses are built along small
rivers or on a hill.
All targeted roads are paved with asphalt. The
roads have gutters for drainage, stream flowing alongroads or culvert installed under the road.
The roads are categorized by area, number ofhouses along the road and cause of flooding. The
specifications of roads, length, width, elevation slope,
number of houses along the roads and detour route for
evacuation, are calculated from GIS map [5]. Table 1
shows the categorized road number. A road without

Area name

Total

Unosumai
Kamaishi
HirataKurihashi
Kasshi
Nakatsuma
Kosano

14
15
13
8
23
6
7

No
catchment
area
0
0
1
1
7
1
3

Total

86

13

No
house
2
1
4
3
1
0
0
11

catchment area is inundated by Kasshi river flooding
or due to poor drainage. A road without house along
it has low possibility being used for evacuation route.
For the 86 roads, most causes of flooding areaccording to overflowing of stream along the road or
culvert under the road. With heavy rainfall, increasingof flow rate or clogging by debris make water
elevation higher, therefore overflown water run over
the road. Hence, in this paper, we consider predictedrunoff volume of stream along or under a road as flowrate flowing over the road.
In the example of Touni town, a river flowing
under the road clogged therefore water flow over theroad. As the slope of the road is steep, water ran downover the road at high speed, thus evacuees are265

SEE-Mie, Japan, Nov.10-12, 2022

14

precipitation[mm / 10 min]

12
10
8
6
4
2

19:00
19:20
19:40
20:00
20:20
20:40
21:00
21:20
21:40
22:00
22:20
22:40
23:00
23:20
23:40
24:00
00:20
00:40
01:00
01:20
01:40
02:00
02:20
02:40
03:00
03:20
03:40
04:00
04:20
04:40
05:00

0

AMeDAS rainfall at Kamaishi station. p.m.9, 12th, October ~ a.m.5, 13th OctoberFig. 4
obstructed evacuation.

very wide channel, we regarded 𝑅 as ℎ.

Velocity and water depth on the roads

Assessment of evacuation risk

Evacuation risk of each road is indicated in two
ways using estimated velocity and water depth on theroads.
Velocity and water depth of water flow on theroads are estimated with runoff volume calculatedwith rational formulae (Eq. (1), (2) and (3)) using
catchment area and precipitation data shown in Fig. 4[6].

We compared results of risk assessment
calculated with comparison between fluid force andresistance force [1] and specific force per unit width[2].

1

𝑄 = 3.6 × 𝑓 × 𝑟 × 𝐴𝑡=

Fluid force and resistance force
Suga et.al. [1] compared fluid force and resistanceforce (hereinafter this is called 2𝐷 − 𝐹) to evaluate
risk for walking under water flow. We calculated
fluid force with Eq. (6) Resistance force is friction
force between shoe sole and the ground, calculatedwith Eq. (7). Eq. (8) is criterion. We added terms
considering slope effect to the equations shown in
Suga et.al.[1].

(1)

30√𝐴

(2)

√2
1

𝐿

𝑇 = 3600 × 𝑊(3)

𝐷 = 𝐶𝑑 ×

Where 𝑞 is unit width flow rate, 𝑓 is dischargecoefficient, 𝑟 is the design rainfall intensity, 𝐴 iscatchment area, 𝑡 is inlet time, 𝑇 is flow time, timeof concentration is summation of 𝑡 + 𝑇, 𝐿 is Lengthof river channel from its outlet point to its farthest
point, 𝑊 is flow velocity by Kraven’s formulae.
We obtained velocity and water depth with
Manning’s formula for rectangular channel (Eq. (4)and Eq. (5)) on the assumption of that the roads arevery wide rectangular channel with constant widthand slope.
𝑄

1

𝟐

ℎ=(

1

)

+ 𝐺0 sin 𝑖

(6)

(7)

𝐹 ≥ 𝛼𝐷(8)

Where 𝐷 is fluid force, 𝐶𝑑 is drag coefficient forhuman body, 𝜌 is density of water, 𝑢 is walking
speed (0.4 m/s in this study), 𝑎 is projected area of
human body, 𝐺0 is body weight (60kg ×9.8 m/s2 inthis study), 𝐹 is resistance force, 𝑊 is buoyant force
and 𝛼 is safety factor. 𝛼 is set to 2 following Suga et.
al. [1](4)

Specific force per unit width

2

𝑛𝑄 5

2

𝐹 = 𝑓 × (𝐺0 sin 𝑖 − 𝑊 )𝟏

𝑣 = 𝑏ℎ = 𝑛 × 𝑅𝟑 × 𝑖 𝟐

𝜌(𝑢+𝑣)2 ×𝑎(5)

We calculate specific force per unit 𝑀(hereinafter this is called 𝑀) with Eq. (9) to evaluate
risk of walking under flooding following Asai et. al.
[2]. Where 𝑔 is gravity acceleration. Table 2 shows
the criterion of 𝑀 classified for man in twenties,

𝑏𝑖 2

Where 𝑣 is flow velocity, 𝑏 is width of road, 𝑛 is
Manning’s roughness coefficient, 𝑅 is hydraulicradius and 𝑖 is slope. As the roads are considered as
266

SEE-Mie, Japan, Nov.10-12, 2022

woman in twenties, elderly man and elderly woman,proposed by Asai et. al. [2]
𝑣 2ℎ

ℎ2

𝑀= 𝑔 + 2

slopes on both side of Kasshi river, induce flooding
on roads.
Table 3 shows the results of risk assessment withwater depth, 2𝐷 − 𝐹 and 𝑀 value, for each area. The
assessment results are different for each method.
Estimated water depth are sufficiently low for on-footevacuation under flooding condition on most oftargeted roads. With the assessment using 2𝐷 − 𝐹, 28
roads are considered not safe for on-foot evacuation.

(9)

Table 2 Criterion of specific force per unit [2]Male 20s
Female 20s
Male senior
Female senior

Safe forevacuation
𝑴 < 𝟎. 𝟏𝟐𝟓

Obstruction
from flooding
𝑴 > 𝟎. 𝟐𝟓𝟎

𝑴 < 𝟎. 𝟏𝟎𝟎

𝑴 > 𝟎. 𝟐𝟎𝟎

𝑴 < 𝟎. 𝟎𝟖𝟎

𝑴 > 𝟎. 𝟏𝟔𝟎

20
18
16

number of roads

RESULTS
Catchment area and road slope are importantelement for flow condition. Fig. 5 shows relationshipof catchment area and slope of roads. The developing
standard of steep slope is fixed by law in Japan. Fromthe viewpoint of concern for the wheelchair,installation criterion of slopes at public spaces has
been decided. Sloping path steeper than 1/12 needs
arm rail on both side of the path. Sloping path insteadof stairs in buildings must be milder than 1/8.[7]We see from Fig.5 that most roads are milder than
1/15 and have small catchment area. 1/15 slope isenough gentle for walking in dry condition, however
it’s steep as river slope. Fig. 4 shows that target roads
include many roads laid along or over the steep riveror mountain stream.
To compare the characteristics of each area, Fig.
6 shows road slope in each area. In Kasshi area, 15 of
23 roads are milder than 1/15. Although the roads are
gentle, water flow from catchment area lying on steep

14

12
10
8
6
4

2
0

catchment area
~1/15

1/15~1/12

Fig. 5

1/12~1/8

Catchment area and road slope

15

16

Number of roads

14
12
10

8

7

8
6

5

5

4

4
2

7

6

1

2

22

5

5

2

3
1

4

~1/15
1/15~1/12

11

1/12~1/8
1/8~

0Name of area
Fig. 6

Road slope in each area
267

1/8~

SEE-Mie, Japan, Nov.10-12, 2022

Table 3Result of evacuation risk assessment
water depth> 0.3mComparison between
fluid
force
and
resistance force

M > 0.123

M > 0.100

M > 0.08

Unosumai

1

8

8

9

10

Kamaishi

1

4

4

4

5

Hirata/Touni

1

7

7

7

8

Kurihashi

0

3

5

5

5

Kasshi

1

2

3

4

4

Nakatsuma

0

3

3

3

4

Kosano

1

1

1

1

2

total

5

28

31

33

38

specific force per unit width

Maximum velocity (m/s)

12

10
8
2D < F and M < 0.08

6

2D < F and M > 0.08
4

2D > F and M > 0.08

2
0
0

0.1

0.2

0.3

0.4

0.5

Maximum water depth (m)Fig. 7 Maximum velocity, maximum water depth and results of assessment
With the assessment using 𝑀 , 38 roads are
considered not safe for on-foot evacuation of elderly
women. The results of roads in Touni (Fig. 2) are safe
assessed by water depth while not safe using 2𝐷 − 𝐹
and 𝑀.
We compared the assessment results with 2𝐷 − 𝐹
and 𝑀 . Fig 7 shows the relationship between
maximum velocity and maximum water depth of eachroad. The roads are categorized by results of two risk
assessment method, 2𝐷 − 𝐹 and 𝑀. Fig. 7 shows thatcriterion of 𝑀 is stricter than 2𝐷 − 𝐹 . In Fig.7, anoutlier data is excluded. Maximum velocity andmaximum water depth of the excluded road are
15.1m/s and 0.72m since the catchment area is muchlarger than others. Besides, the road with outlier data
is in Kasshi area and not safe for risk assessment with
2𝐷 − 𝐹 and 𝑀.

DISCUSSION
This paper describes the result of risk assessmentof on-foot evacuation under flooding condition in thecity of Kamaishi. The assessment is carried out forroads extracted from hazard map. The studies
introduced a simple method to assess evacuation riskof sloping road with catchment area. The results show
the different between the assessment method andevaluated disaster scales of evacuation route.
Therefore, from the point of view of risk assessmentof inland flooding and publishing hazard map, it isrecommended to establish cause of flooding andeffect of sloping roads so that the risk would be
adequately estimated. On the other hand, because of268

SEE-Mie, Japan, Nov.10-12, 2022

work cost and smallness of disaster-scale, only few
hazard maps present accurate disaster prediction forinland flooding. In addition, as the assessment in thispaper includes assumptions concerning estimation offlow rate over the roads, it needs further study toenhance accuracy.

Evacuation in Flood Disaster, Annual journal of
hydraulic engineering, JSCE. 1995 Volume 39
Pages 879-882. in Japanese[2] Asai Y, Ishigaki T, Baba Y and Toda K,Safety
Analysis of Evacuation Routes Considering
aged Persons During Underground Flooding,Annual journal of hydraulic engineering, JSCE.
Volume 53 Pages, 859-864. in Japanese

CONCLUSIONS[3] Dias. C., Rahman, N. A., Zaiter, A., Evacuation
underfloodedconditions:
Experimental
investigation of the influence of water depth on
walking behaviors, International Journal ofDisaster Risk Reduction, 58(2021) 202192[4] The city of Kamaishi, Kamaishi city floods andIn the city of Kamaishi, roads flooded in the pastdisaster are shown in hazard map. Many of theflooded roads are sloping and have streams along or
under them. On-foot evacuation risk of the roads
under heavy rain condition is estimated, under theassumption that these inland flooding are occurred by
overflowing of river, stream, or culvert along or undereach road. The results show difference of theassessment results between assessment methods.

landslidehazardmap ,https://kamaishi.nigedoki-map.com/ , inJapanese[5] Ministry of infrastructures, Transport andTourism Geospatial information Authority ofJapan, GIS MAPs, https://maps.gsi.go.jp, inJapanese[6] Kagoshima prefecture, Design Criteria of River
Works
https://www.pref.kagoshima.jp/ah07/infra/kasen-sabo/kasenseibi/sekkeikijyun.html, in Japanese.
[7] Ministry of infrastructures, Transport andTourism Japan Meteorological Agency,
https://www.jma.go.jp/jma/index.html , inJapanese.

ACKNOWLEDGMENTS
The author would like to thank to all members ofconstruction division of Kamaishi city hall for helpful
suggestions and approval for survey.

REFERENCES[1] Suga K, Uesaka T, Yoshida T, Hamaguchi K,

Chen Z, Preliminary Study on Feasible Safe269

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXPERIMENTAL STUDY ON ECO-BINARY MORTAR AT
HIGH -TEMPERATURE EXPOSURE
R.A Malek1,2 and S. Gooven2
Centre of Excellence for Frontier Materials Research, Universiti Malaysia Perlis, Jalan Kangar-Alor Setar,
Kampung Seriab, 01000 Kangar, Perlis, Malaysia
2
Faculty of Chemical Engineering Technology, Universiti Malaysia Perlis, Taman Muhibbah, 02600 Jejawi,
Perlis, Malaysia
1

ABSTRACT
Concrete or mortars exposed to high temperatures has impact in their strength and durability. One of thestrategies to overcome this issue is by replacing cement with other alternative pozzolanic materials. In this study,
the non-beneficial agricultural waste, namely rice husk ash (RHA), which has high silica content under controlledburning conditions makes it appropriate to be used as partially replacement in mortar. The addition of RHA ranging
5 to 20 wt. % has significantly influenced the appearance of mortars as they perform darker grayish color as theincreasing amount of RHA. Unexpectedly, this study revealed that greater compressive strength was obtained
almost doubled the value for 5 wt.% addition of RHA followed by 10 and 15 wt.% addition of RHA, respectively.
However, addition of 20 wt.% RHA was not a preferable mixture as it achieved only 12.49 MPa of compressive
strength which is below than the conventional mortar. Due to high temperature exposure up to 1,093 °C, the process
influenced the moisture content in the cement paste and change the appearance of the sample into whitish-graycolor as well as their physical and residual mechanical properties. All samples recorded relative strength values
between 0.35 and 0.16. All these findings have correlation with thermal analysis conducted for all samples. Overall,
the samples has started to evaporate the free water contained in the cement past at temperature of 82 to 140 °C
followed by decomposition of Ca(OH)2 at 445 to 454 °C. It can be concluded that, 5 wt.% of RHA addition
provided reasonably good properties in comparison to other mixture. This study exhibited the consumption ofthese economical and feasible agricultural waste materials is acceptable to be implemented in concrete industry
and thus bearable to solve dumping and environmental issues.
Keywords: rice husk ash, high temperature, mortar, supplementary cementitious materials

INTRODUCTION
Supplementary cementitious materials (SCM) withpozzolanic properties, such as blast furnace slag,
silica fume, fly ash, and rice husk ash, have played an
important role and are widely adopted in theconstruction industry nowadays. Among SCM
candidates, it was found that more researchers havebeen involved in the possibility of using rice husk ash(RHA) than other agricultural waste and otherbyproducts due to high siliceous content ranging from85 to 95% [1] with pozzolanic or hydraulic properties
in proper controlled burning conditions [1]–[3].

bearable to overcome a few issues related toenvironment and disposal of RH in landfills.
Table 1 Comparison data on rice production andarea harvested in the South Asian Region [4].
Area
Population Production
Country
harvested
3
(10 )
(MT)
(103 ha)World
7,466,964
501.5
162,521
Asia
4,462,677453.2
143,072
Indonesia
261,11545.6
13,870Philippines
103,320
12.1
4,722
Vietnam
94,56928.1
7,743
Thailand
68,864
21.6
10,780
Malaysia
31,1871.8
700

It was reported by [4] that the amount of riceproduction globally had hit 501 million tons (MT),involving more than 160 thousand hectares of
harvested area in 2016. By comparing the South
Asian countries as presented in Table 1, Malaysia has
a relatively small production of rice as it only covers
0.21% of Malaysia’s land area. However, data
provided by [1] shows a significant increment of 56%
growth rate in paddy production as well as RHA
between 2002 and 2022. To some extent, theutilization of no-beneficial use of RH to produce
secondary byproducts has been spotlighted as it isAmong these justifications, a major concern on theireffect to sustain good strength during fire exposure
could be considered since utilization of RHA in
mortar or concrete would impact their properties.
When exposed to high temperatures, the chemicalcomposition and physical structure of the concretechanges considerably due to dehydration released bybound water of calcium-silicate-hydrate (C-S-H)
starting at 200 °C, disintegrates calcium hydroxide270

SEE-Mie, Japan, Nov.10-12, 2022

(Ca(OH)2) and C-S-H breakdown at 400-600 °C,
followed by loss of strength, durability andmicrostructural changes as it reaches temperatures
greater than 1,000 °C [1], [2].
RESEARCH SIGNIFICANCE. RHA has been
identified as an acceptable pozzolans replacement forcement in mortar. However, utilization of RHA as
supplementary cementitious materials that arecapable of resisting high temperatures has been given
far too little attention by previous researchers.
Therefore, it is important to understand if thealteration in mortar composition would affect theproperties of the mortar at high temperatures.

(a)(b)
Fig. 1 The (a) outer and (b) inner parts of RHA after
completed burning process at 650 °C for 1 hour
duration observed using scanning electron
microscopy (SEM).

EXPERIMENTAL PROCEDURES

Intensity(a.u)

RAW MATERIALS. Materials used in this study
were ordinary Portland cement (OPC), fine aggregate,
and rice husk ash. Rice husks (RHs) are locallyavailable in the Northern state of Malaysia, Perlis,
sourced from a rice milling factory known as Kilang
Beras BERNAS Sdn. Bhd., Simpang Ampat, Perlis,
Malaysia.

10

RICE HUSK ASH (RHA) PREPARATION AND
CHARACTERIZATION. RH was prepared undercontrolled burning conditions at 650 °C for 1 hourwith a heating rate of 10 °C/min, followed bygrinding and sieving processes to obtain 63 µm
particle size. The RHA was analyzed using X-ray
Fluorescence (XRF) technique for chemicalcomposition, which are listed in Table 1. Meanwhile,
the outer and inner epidermis of RHA and theirrespective XRD patterns that proved the ashes
contained mostly amorphous silica phase are shownin Figures 1 and 2.

30

50

70

2-Theta (deg.)
Fig. 2 XRD pattern of RHA
MIXING PROCEDURES. The amount of RHA,
OPC, fine aggregates, and water required for the cube
mold with a dimension of 50 x 50 x 50 mm wascalculated as shown in Table 2. The first mixture wasthe control sample, while the subsequent mixtures,
identified as M1 to M4, were mortar that was mixed
with RHA at different compositions between 5 and
20% to be used for comparison. Water to binder (w/b)
ratio demand was set at 0.4 for all mixtures. All the
mortar mixtures were de-molded after 24 hours andthen water cured for 28 days.

Table 1 The necessary details of Perlis RHA used in
the study.
Parameters
RHA
SiO2 (wt.%)
88.991
Al2O3 (wt.%)
0.050
Fe2O3 (wt.%)
0.117
CaO (wt.%)
1.177
MgO (wt.%)
0.596
K2O (wt.%)
6.499
Na2O (wt.%)
0.048
SO3 (wt.%)
0.713
Other (wt.%)
1.809
Mean Particle size (µm)
386.4
Specific gravity
0.360

Table 2 Designations and mix proportions of mortar
mixtures.
Fine
Mixture
OPC
RHA
Water
AggregateID(wt.%) (wt,%)(kg/m3)
3(kg/m )
Control
100
…
544
170
M1
95
5
544
170
M2
90
10
544
170
M3
85
15
544
170
M4
80
20
544
170
TESTING ON FIRE RESISTANCE. The mortars
were heated up to 1,093 °C in an electric muffle
furnace by following the ASTM E119 (ASTM
International, 2020). This test method provides a
standard time-temperature curve to which materials
271

SEE-Mie, Japan, Nov.10-12, 2022

and components are exposed to evaluate theirresistance to fire as presented in Fig. 3.

completing the curing procedure (denoted as Massrate I), and secondly, the mass difference after
completing the heating procedure (denoted as massrate II). For mass rate I,
BeforeAfterLong cracklineFig. 3 Standard time-temperature curve according to
ASTM E119 fire exposure.

(a) Control sample

RESULTS AND DISCUSSION
The forensic analysis by comparing the surface ofmortar usually starts with visual observation of color
change, cracking, and spalling of mortar surface thathave been conducted to all samples after exposure tohigh temperature. Fig. 4 shows the mortar surfaces
before and after exposure to high temperature. Colorchanges affected by high temperature can be easily
identified by means of visual inspection. Before firing
the samples, it can be seen obviously that samples
with addition of RHA appear darker greyish color
compared to the control sample. As the amount of
RHA increases, a darker gray color will be obtained.
However, discoloration occurred in all samples after
the firing process was completed, which gave a final
color of whitish-gray.

Long crackline(b) M1 sample

As per the abovementioned findings, it resulted inphysical and chemical modification in the heatedsamples. As a consequence, cement paste
experienced moisture evaporation or dehydration as
well as shrinkage or mass loss; and thermal expansion
characteristics between aggregate and cement pastecaused samples to crack when exposed to hightemperature. Detailed investigation by [5] found thatwater removal from the calcium-silicate-hydrate (CS-H) structure has a relationship between waterbinding energy and solids. Therefore, water containedin C-S-H structure will be eliminated starting from
evaporation of free water followed by capillary waterand physically bound water. There were voids spottedon all mortar surfaces, but long external cracking
lines were visible for the control and M1 samples. As
the amount of RHA increased greater than 5 wt. %,only shorter external cracking lines appeared.
Surprisingly, no thermal spalling occurred that broke
samples into pieces when heated up to 1,093 °C for
all mixtures.

(c) M2 sample(d) M3 sample(e) M4 sample
The effect of high temperature gave variations inmass loss at different mixtures in this study. By
referring to Table 2, two different types of mass rates
were calculated. Firstly, the mass difference afterFig. 4 Comparison on surface texture before andafter exposed to 1,093 °C.

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SEE-Mie, Japan, Nov.10-12, 2022

it shows that there was no mass loss during the curing
process, but all the samples gained mass throughout
the process as expected since the porous structure of
RHA tends to absorb more water during the curing
procedure. The sample ranging from 0 to 15 wt. % of
RHA replacement showed comparable mass gain but
increasing the amount of RHA up to 20 wt.% has
resulted in more than double adsorption of water in
C-S-H structure. Meanwhile, a similar trend in massrate II was recorded ranging 4.9 to 6.3% as all thewater binds in C-S-H structure were gradually
removed during the heating process. To some extent,
this finding fits well with the outcome of the visualobservation.

compressive strength values of the concrete wasrecorded ranging 0.35 to 0.16 in parallel to theamount of RHA.
This trend is somehow related to the formation of
portlandite at the early stages of the hydration
reaction between cement and water. The amount of
RHA replacement up to 20% in this study seemed toaffect the efficiency of silica from the RHA reactingwith free portlandite [2]. Nonetheless, the overall
unheated compressive strength result in this study
signifies that the mortar mixtures, regardless of theamount of RHA replacement, are superior for use as
mortar for construction purposes.
Overall, it can be seen that the heated samples losemassive compressive strength with losses ranging
from 64% up to 88%. The ranking is M1 > Control
sample > M2 > M3 > M4, respectively. The relative
strength was obtained as the percentage retained
strength with respect to the unheated strength. The
relative strength of concrete significantly decreased
after high temperature exposure as expected since themoisture evaporation during high temperature
exposure would have altered their mechanicalproperties [6], [7].
Compressive stregnth (MPa)50

Table 2: Calculated data of mass loss in different
conditions.
Mixture ID Mass loss rate I Mass loss rate II(%)(%)
Control
0.6
5.1
Sample
M1
0.6
5.2
M2
0.6
4.9
M3
0.6
5.4
M4
1.7
6.3

1.0
0.8
0.6

25
0.4

Relative stregnth

The density variation in the RHA-based andconventional mortars could create the variation incompressive strength. Based on the experimental
results of density, it was found that the control sample
was denser than RHA containing mortars. As theamount of RHA increases in mortar, a greater amountof water will be absorbed in RHA porous particles.
As water gets evaporated during the heating process,it forms voids that contribute to less dense mortars.
The density of the control sample was 2.14 gcm-3 anddiminished to 2.10, 1.97, 198, and 1.82 gcm-3 for M1
to M4 samples, respectively. Consequently, thesevoids that are filled with air will lead to detrimental
effects on their strengths.

0.2
0

0.0
Control M1
sampleM2

M3

M4

Mixture ID
Unheated

Post-heatedRelative strength

The influence of RHA replacement on thecompressive strength development of hardenedmortar paste in two different conditions, namely
unheated and post-heated, are presented in Fig. 5. It
is evident from the results that the compressive
strength of unheated samples in the control sample
gave an average value of 25.73 MPa. This value isconsistent with the conventional mortar made of a full
mixture of ordinary Portland cement (OPC).
Remarkably, the addition of RHA showed greater
compressive strength values reaching 43.10 MPa for
5 wt. % RHA addition, followed by 37.22 MPa and28.37 MPa for 10 and 15 wt. % RHA replacement,
respectively, compared to the control sample.
However, replacement of 20 wt. % showed that themortar had drastically lost its compressive strength bymore than half of the control sample. The relative

Fig. 5 Compressive strength of unheated and postheated mortar samples at various RHA replacement
amount.
All explanations on the effect of high temperature canbe linked to the thermal analysis. Cement paste plays
a vital role in the strength of mortar exposed to hightemperatures. All the mortar samples were tested
using thermogravimetric analysis (TGA) to
determine the reaction of the samples at elevatedtemperatures and the results were compared andanalyzed as presented in Fig. 6. After all the TGA
patterns were compared with the control mix, it was
found that mortars containing 5% to 15% RHA had asimilar pattern with the control sample. However, the273

SEE-Mie, Japan, Nov.10-12, 2022

sample containing 20% RHA showed an inconsistentpattern.
For the control mix, the first endothermic peak was
observed at 48 °C, while for the M1 sample, the first
endothermic peak was at 55 °C. For samples M2 andM3, their first endothermic peak was observed at 49°C and 47 °C, respectively. This shows that theevaporation of free water takes place earlier in thecontrol, M2, and M3 samples compared to the M1
samples. Another endothermic peak appeared
denoted as (B) for all samples, except the M4
samples, which occurred at a temperature of 82 °C,
85 °C, 83 °C, and 140 °C, respectively. This showsthat the dehydration of water still continues after the
first endothermic peak due to further release of waterfrom the samples.

(a)

In addition, all the samples experienced exothermic
peaks within a certain temperature. The control andM1 samples had a single exothermic peak, with theexothermic reaction having a maximum peak at 224°C and 321 °C, respectively. However samples of M3
and M4 had multiple exothermic peaks which ranged
from 118 °C to 436 °C. This reaction indicates thatgas was released from the samples.
The third endothermic peak (C) is considered thecalcium hydroxide peak [8]. For this peak, all samples
experienced the third endothermic peak at similar
temperatures, which were at 445, 455, 454, and 454°C, respectively. This peak is important as it indicatesthe decomposition of Ca(OH)2 [9]. From the results,
it was determined the decomposition of Ca(OH) 2
initiates faster in the control mix compared to othermortars containing RHA. The last peak is indicated as(D), and is the fourth endothermic peak (D) that
represents the dehydration of C-S-H gel in thesamples, which occurs at temperatures ranging from
692 to 710 °C and shows the possible generation of
new phases due to high temperature.

(b)

Enormous mass changes were also found for all thesamples. At the early stage (i), control samples had amass loss of about 5%, followed by M1 (7.5%), M2(6%), and M3 (10%) because of free water
evaporation. The next mass loss (ii) takes place at atemperature range of 500 °C to 850 °C. During thistemperature, the control sample had a mass loss of
6.7%, M1 sample had a mass loss of 5.8%, M2
sample had a mass loss of 5.5%, and M3 sample had
a mass loss of 6%. This mass loss is due to thedecomposition of CaCO3. The sample containing
20% RHA (M4) could not be analyzed as it does nothave any proper peaks. The TGA graph that was
obtained showed a fluctuating pattern withendothermic and exothermic reactions that had takenplace repeatedly. The mass loss was also continuousand the sample seemed to have a mass reduction of
20% throughout the process.

(c)

(d)
Fig. 6: TGA graphs for (a) control sample (b) M1(c) M2 (d) M3 and (e) M4 of RHA replacement.

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SEE-Mie, Japan, Nov.10-12, 2022

Ministry of Higher Education (MoHE), Malaysia.
REFERENCES
[1]

[2]

[3]

(e)
Fig. 6 (cont.): TGA graphs for (a) control sample(b) M1 (c) M2 (d) M3 and (e) M4 of RHA
replacement.

[4]

CONCLUSIONSThis paper presented an experimental investigationon the effects of mortar to high temperature exposure
with different amounts of RHA replacement. In
general, this study generated an acceptable mortar
property produced by using RHA as SCM that gives
higher compressive strength and denser mortar since
the porous structure of RHA increased the water
demand in cement paste. However, exposure to hightemperature revealed the color changes of theappearance of mortar from darker grayish towhitish-gray influenced by dehydration of cement
paste. The residual compressive strength reduced
more than half of the initial value as consequence of
dehydration that altered their mechanical properties.
Overall, the addition of 5 wt.% of RHA poses goodcharacteristics and has potential to be used inconstruction fields.

[5]
[6]

[7]

[8]
[9]

ACKNOWLEDGMENTS
The authors would like to acknowledge the support
from the Fundamental Research Grant Scheme(FRGS)
under
grant
numberof
FRGS/1/2019/TK06/UNIMAP/02/6
from
the

275

M. Amran et al., “Rice husk ash‐based
concrete composites: A critical review of
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2021.
M. Thiedeitz, W. Schmidt, M. Härder, and T.
Kränkel, “Performance of rice husk ash as
supplementary cementitious material after
production in the field and in the lab,”
Materials (Basel)., 2020.
L. Hu, Z. He, and S. Zhang, “Sustainable useof rice husk ash in cement-based materials:
Environmental evaluation and performance
improvement,” J. Clean. Prod., 2020.
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Industry
in
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https://www.researchgate.net/publication/35
1223058_The_Status_of_the_Paddy_and_Ri
ce_Industry_in_Malaysia (accessed Jul. 05,2022).
I. Hager, “Colour Change in HeatedConcrete,” Fire Technol., 2014.
F. M. Nazri, S. Shahidan, N. K. Baharuddin,
S. Beddu, and B. H. Abu Bakar, “Effects ofheating durations on normal concrete residual
properties: Compressive strength and massloss,” 2017.
K. Selvaranjan et al., “Thermal andenvironmental impact analysis of rice husk
ash-based mortar as insulating wall plaster,”Constr. Build. Mater., 2021.
O. Arioz, “Effects of elevated temperatureson properties of concrete,” Fire Saf. J., 2007.
W. H. Wang, Y. F. Meng, and D. Z. Wang,“Effect of rice husk ash on high-Temperature
mechanical properties and microstructure ofconcrete,” Kem. u Ind. Chem. Chem. Eng.,2017.

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FAULT DETECTION USING PALSAR-1/2 IMAGE DATA FOR
GROUNDWATER ANALYSIS (STUDY AREA: CENTRAL AND
SOUTHWEST OF DJIBOUTI)
Yessy Arvelyna1, Sawahiko Shimada2, Sergio Azael May Cuevas2, Fadoumo Ali Malow3
12

Remote Sensing Technology Center of Japan, Tokyo, 105-0001, Japan
Faculty of Regional Environment Science, Tokyo University of Agriculture, Tokyo, 156-8502, Japan
3
The World Bank in Djibouti

ABSTRACT
Fault detection analysis on PALSAR-1/2 data has been observed using the implementation of a series ofadaptive and gradient filters to derive a Relief Image. This method is applied to delineate good resolution faults
distribution, and to add and revise faults mapping derived from existing geology maps over the Djibouti region.
Fault mapping is done in order to observe the possibility of fault-driven groundwater flow into the fault systems.
Study areas are located in central and southwest of Djibouti, where faults exist because of continental platemovements, contact of geological formation and tectonics activities. The result shows that the processed Relief
Image can delineate the fault lines and remove artefacts from PALSAR-1/2 data. The Geology Setting Index is
introduced in this study to analyze the correlation of groundwater data with the geology setting of borehole sites
such as geological formation, fault system, distance to rivershed, type of aquifer, etc. It is shown that the occurrenceof fault systems possibly increases the groundwater volume of boreholes at study areas. The proposed study isuseful to locate the potential area for groundwater resources in Djibouti.
Keywords: ALOS-2, PALSAR-2, Fault Detection, Groundwater Analysis, Djibouti.

1. INTRODUCTION

distribution on the Relief Image processed using thegradient filter method. The location of boreholes andboreholes data are analyzed to retrieve the correlationof the faults and groundwater resource characteristics.
This study is done under the project on “Advanced
and Sustainable Methods on Water Utilization
Associated with Greening Potential Evaluation”
aimed to create sustainable agropastoral practices inthe Djibouti desert through developmental
management of water resources, designated by Tokyo
University of Agriculture, Japan, from FY2018 for a
5 years period [5].

Fractures in volcanic aquifers have been analyzed
as the main water resources in Djibouti, as shown by
the pumping test data, which consist of major basaltic
series, e.g. the Stratiform series (3.4 Ma to 1 Ma) andthe Dalha series (9 Ma to 3.4 1 25 Ma) with athickness more than 200 m [1]. The geochemical andisotopic surveys in the southwest of Djibouti show acommon evolutionary pattern of groundwater i.e., arecharge from wadi-rivers flown into the alluvium
layer, then, circulated downward into the basalt layer
through major faults, and mixed with a moregeochemically evolved groundwater [2]. Affected bysemi-arid and arid weather, Djibouti has low rainfall,
about 130 mm/year, which mostly evaporates to theair (83.5 %) and the rest flows on the ground surface(6 %), penetrates into sub-surface (5.5 %) and subground (5 %), form the renewable groundwater
resources estimated about 300 Mm3/year [3].
Therefore, it is necessary to delineate the faults
distribution in order to locate areas with highpossibility of groundwater resources. On Synthetic
Aperture Radar (SAR) image data, fault distribution
can be detected by using the interpretation of brightand dark signatures of backscattering data [4]. This
study aims to detect the distribution of fault systems
using open and free data products of PALSAR-1/2(Phased Array type L-band Synthetic Aperture
Radar) image data over Djibouti by analyzing fault

2. DATA
2.1. SAR Image Data
SAR (Synthetic Aperture Radar) data has been
widely used in volcanic and tectonic terrains. Because
imaging radar is sensitive to changes of slope, roughground surface scatters higher radar signals on thefront, while lower radar signals are backscattered on
the back slope [4]. Thus, fault lines and theirassociated topographic scarps are emphasized byhighlight (whitish feature) and shadow (blackishfeature) on a SAR image [6]. In the SAR image, athrust fault can be detected by different trends ofunderlying rocks, and strike-slip faults are often
shown by aligned notches, shutter ridges, linear
terraces and offset stream channels [4]. The
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SEE-Mie, Japan, Nov.10-12, 2022

advantage of using a SAR image is that a radar signal
can penetrate clouds and observe the ground surfacenight and day; thus, it can produce image data without
cloud problems. Radar backscatters, derived fromsatellite observation with high look angle, canproduce an extreme topographic distortion, hence, itneeds geometric terrain correction to produce a good
image data. The processed PALSAR-1/2 data in thisstudy are described below.

The geology map over Djibouti (Fig.1) [13][14] isused to observe the geological formation of borehole,e.g., basaltic or sedimentary formation, the distanceto rivershed (wadi), type of nearby fault system andtype of aquifer that correlate with the production levelof groundwater.
2.3 Borehole Data
The source of borehole data analyzed in this study
is a collection of past boreholes data in Djibouti
obtained by a FAO project [15]. Spatial distributionof borehole site and groundwater discharge data foreach borehole are used to analyze the impact of fault
distribution into groundwater resources. The
description of borehole data for the target area isnoted below.

2.1.1. PALSAR-1 ASF RT1 data
PALSAR-1 sensor was aboard on Japanese ALOS
(Advanced Land Observing Satellite) for land
observation using L-band frequency with the main
objective to contribute on cartography, regional
observation, disaster monitoring and resources
surveying [7]. The Alaska Satellite Facility (ASF) has
processed Radiometrically Terrain Corrected (RTC)
ALOS PALSAR products which are accessible tousers on GeoTIFF format since 2014 [8].
The PALSAR RTC product has been corrected forgeometry terrain by correcting geometric distortions
that lead to geolocation error, and radiometriccorrection by removing topography influence onbackscatter values [9]. This study selected 8 scenes of
RT1 high-resolution product which has gammanaught power on pixel data with 12.5 m resolution
over Djibouti region. For the Djibouti region, thegeometric correction uses SRTM GL1 DEM (Digital
Elevation Model) data up-sampled 30-m mapping
function to 12.5 m mapping function. The RT1 image
data can be downloaded from ASF Data Portal under
Product License Agreement and Citation [10].

Tadjourah

Ambouli
Hanle

Fig. 1

Geology map of Djibouti and study area

3. STUDY AREA
2.1.2. PALSAR-2 global mosaic data
3.1. Ambouli Watershed
Started in 2014, the ALOS-2 PALSAR-2 data is
the continuation of the PALSAR-1 program ended in
2011. The PALSAR-2 Global Mosaic Data is aseamless mosaic of the backscattering coefficients of
PALSAR-2 image with 25 m resolution within 10x10degrees in latitude and longitude released by JAXA
in 2018. Geometric distortion correction (orthorectification) and topographic effect on image
intensity (slope correction) are applied [11].
Temporal interval of the mosaic is generally 1 year.
This data is aimed for understanding and responding
to global environmental changes such as global
warming and loss of biodiversity, timely assessmentof deforestation and forest degradation. Users canaccess for free and open dataset with a registration on
JAXA site under specific JAXA’s Terms of Use of
Research Data [12]. This study has acquired 4 scenesof PALSAR-2 Global Mosaic data over the Djibouti
region.

The Ambouli watershed is located in thesouthwest of Djibouti city, whose main water
resource came from the wadi Ambouli. The aquifers
at the Ambouli watershed are mainly composed ofvolcanic aquifers and part of sedimentary aquifers.
Normal faults with throw less than 20 m and faults
without throw are mostly observed in NW-SE, W-E
and NESW direction [14]. About 58 boreholes are
distributed in the Ambouli watershed and from these,
36 boreholes with groundwater discharge data wereused for groundwater data analysis.
3.2. Hanle Watershed
The Hanle watershed is stretched from the west
into the southwest of Djibouti. The aquifers in the
Hanle watershed are mainly composed of thesedimentary aquifers and regional volcanic aquifers.
In this region, the formation of older basalt of Stratoid
series (βD), middle Stratoid basalts of the Afar (βSII), and the Dalha basaltic series (βD) are widely

2.2 Geology Map

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SEE-Mie, Japan, Nov.10-12, 2022

covered and in some parts are overlaid by younger
sedimentary layers of alluvial deposits (Qa, A3 -A5)
observed from the north into south part region of thewatershed [14] with depth about 100 m [16]. From 30
boreholes located in the Hanle watershed, only 9boreholes, which have groundwater discharge data,
were analyzed in this study.

applied on PALSAR-1/2 data to reduce speckle noiseon the image. Adaptive filters use standard deviationof pixels within a moving window/box to calculate
new pixel values. Enhanced Lee filter can be used toreduce speckles in SAR images while preserving
texture information [18]. The filtering process utilizes
the Damping Factor, an exponential damping in theweighted average for heterogeneous class, wherelargerdamping
produces
lessaveraging.
Homogenous is the pixel value replaced by theaverage of the filter window and Heterogeneous is the
pixel value replaced by a weighted average.

3.3. Tadjourah Region
In the Tadjourah region, complex fault systems
are observed, such as in the Asal rift zone, central partof Djibouti. The aquifers at this region are mainlycomposed of volcanic aquifers and minor
sedimentary aquifers. The geology setting showscomplex layers from basaltic series of Dalha (βD) in
the north side, basalts of external margins of the Asal
(βG1, recent Quartenary) in the central part, initialbasalt series of the opening of the gulf of Tadjourah(βi) along the coastal area and in between overlaid
with recent sedimentary formations (Qa) from upper
Pliocene to middle Pleistocene era [14]. Normal
faults and faults without throw are observed mostly in
NW-SE and NE-SW direction, respectively (Fig.1).
Twenty boreholes are distributed in this region.

4.2. Fault Detection Analysis using the Relief
Image
Since the fault lines on SAR image are associatedwith the dark-light transition, this feature contains
edges that possess gradients with a large magnitude
on the X-Y plane [19]. Therefore, it can beemphasized using gradient filters. In this study, fault
distribution is delineated from the processed Relief
image composed by applying gradient filter on orthorectified PALSAR-1/2 image data to emphasize therelief features of fault lines. On ENVI ver. 5.5.3, thisprocess can be done by applying Convolution High
Pass Filter with 3x3 Kernel Size on X and Y direction
by applying Kernel in X direction: [-1, 0, 1]; [-2, 0,2]; [-1, 0, 1] and Y direction: [1, 2, 1]; [0, 0, 0]; [-1, 2, -1].
Then, the Relief image is derived by composing
the X and Y direction gradient filtered image (b1+b2),
such as the Band Math of ENVI or the raster tool of
ArcMap. Fault detection analysis is done byoverlaying the Relief image derived from gradientfiltering of PALSAR-1/2 data on geology map overDjibouti using ArcMap ver.10.6 with transparency
setting about 45%. The correlation of the fault linefrom geology map over study area and the Relief
image are observed under image scale from 1:30,000
or higher scale.

4. IMAGE PROCESSING METHOD
4.1. Preprocessing
On pre-processing, the PALSAR-1/2 data are reprojected to have the same datum and projection, e.g.,
WGS 1984 Lat/Long. The PALSAR-1 ASF RT1 datauses WGS 1984 datum and UTM 37N projection and
the PALSAR-2 global mosaic data uses WGS1984
latitude/longitude. Therefore, the RT1 data is reprojected into WGS 1984 Lat/Long. The DN pixel
value of backscattering of RT1 image (HH or HVband) can be converted into gamma naught values indB (decibel) using the equation [8] as follows,
dB = 10*Log10(sqrt(DN))

4.3. Scoring Index for Geology Setting Analysis of
Borehole Site

(1)

The PALSAR-2 global mosaic data products are
stored as the DN number in unsigned 16 bit and theconversion into gamma naught in dB can be doneusing following equation [12]:dB = 10*Log10<DN2> + CF

The correlation between the groundwater volume
from borehole and the geology setting of borehole site
are analyzed using the Geology Scoring Index which
is designed according to the information derived fromthe geology map over Djibouti, e.g., basaltic or
sedimentary formation, the distance to rivershed(wadi), type of nearby fault system and type ofaquifer that correlate with the production level ofgroundwater (Table 1). The borehole data at study
area, i.e., groundwater volume and deep profile,borehole elevation, etc., are analyzed and visuallycompared using graphs.

(2)

Where, CF is a calibration factor (value is -83 dB
for PALSAR-1 mosaic data), and < > is the ensemble
averaging.
Since SAR data is filled with speckle noise due tothe interferences during signal transmission [17],adaptive filters, such as Enhanced Lee Filter, etc., are

5. DISCUSSION AND ANALYSIS
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SEE-Mie, Japan, Nov.10-12, 2022

site
5.1. Fault Detection Analysis
The proposed method of the Relief image byapplying gradient filter on PALSAR-1/2 image data
was capable of delineating the fault system at study
area. This method can enhance the difference ofbackscattering data from ground surface occurred byfault system retrieved as higher backscattering
coefficients. The Relief Image shows that fault linesand dry rivers are associated with rugged features on
image (Fig.2, top), where the fault line appears as
straight lines and the river system as curved lines.

Group

No

Class

Index
Name

Index

I.
Geologyformation1

Sedimentary
formation

SedF_i22

Basaltic
formation

BasF_i

1

Rv_i

2

Rv_i

1

F_i

3

F_i

2

F_i

1

SedAq_i2

II.
Rivershed

3
4
5

III.
Fault

6
7

IV.
Aquifer
type

8

Dry
rivershed
Near dry
rivershedAlong
normal
fault
Along
fault
Possibly
along fault
Local
sedimentaryaquifer

Category

The capacity
to absorb
water

Distance to arivershed

Correlation
to fault

The capacity
to absorb
water

Fig. 2 Processed the Relief image derived fromPALSAR-1 ASF RT1 data at the Asal rift zone (top),
is overlaid with geology map (bottom) to extract fault
lines (orange).
The overlay with the geology map (Fig. 2, bottom)
shows that the extracted fault lines from the Relief
image are consistent with fault lines from thegeological map. Normal faults such as in the Asal riftzone, appear as a straight and deep relief. Additional
several fault lines were delineated from the Relief
image which can add the fault system distribution
from the geology map. The source data for the Relief
image, e.g., orthorectified image data of PALSAR-1
RT1 and PALSAR-2 Global Mosaic data, canproduce accurate position of fault lines from theRelief image, which can improve the fault lines
distribution from the geology map over Djibouti.

Fig. 3 Borehole data for study area: a) groundwater
discharge per hour (Q); b) depth profile (m); c)
groundwater static level (NS in m); d) conductivity(μs/cm); and e) elevation (Z in m).

Fig. 4 Geology Setting Index for borehole sites
introduced by this study

Table 1. Geology Setting Index (GSI) for borehole279

SEE-Mie, Japan, Nov.10-12, 2022

5.2. Boreholes Data Analysis

linearly with the width and the number of fractures(faults) and decrease linearly with the increase indepth [21] and the magnitude of fluctuation increase
to depth [22].

The result of the Geology Setting Index (GSI) of
boreholes introduced by this study (Table 1) showsthat it is capable of evaluating the correlation ofgeology setting of borehole sites and groundwater
resources at the study area (Fig. 4). It is revealed thatthe boreholes at study areas are mostly located at ornear dry river bed of wadi (blue) and more than halfof borehole sites are located at the fault systems(orange).
At the Ambouli watershed, higher conductivity
level with range between 2850 and 5300 μs/cm, isshown for borehole data located at basaltic formation(RG1-RG3, RG5), in comparison with boreholes dataat sedimentary formation (E1-E5) with range 2240 3625 μs/cm (Fig.3.d). At the Hanle watershed, theborehole data (Dikhil6, Dikhil11) from volcanic
aquifers at basaltic formation in fault regions also
show high conductivity level 1950 – 2900 μs/cm.
High conductivity shows mineralization ofgroundwater from water-rocks interaction in basalt
formations. In Djibouti, the recharge of basaltic
aquifers is involved with downward circulation of
surface water into deeper basalt layers through major
faults [2].
For borehole sites closer to the Djibouti city,
higher conductivity levels are retrieved. The highest
conductivity is shown at the EDD borehole located in
Djibouti city. This result possibly shows the salinization of groundwater. The observed conductivity levelof groundwater of some boreholes exceed the WHO
standard for drinking water (< 1,500 μS/cm) and FAO
standard for water quality agriculture, i.e. >700
μS/cm is slightly restricted to use and >3000 μS/cm
is strictly restricted to use and assumed inadequate for
irrigation from past field survey in Dikhil region [20].
The occurrence of large fault system possibly
increases the groundwater resource as shown at
PK20-8 (Q=30 m3/h) and PK-201 (Q=41 m3/h)
boreholes, which are located in a fault region, incomparison with borehole sites without the impact of
fault system, such as Chabelley-1 and Chabelley-2(Q=6 - 20 m3/h) in the Ambouli watershed (Fig. 3).
Those boreholes are located about in the sameelevation and depth profile (150 - 157 m). The
borehole data of N-Goubet at elevation of 183 m in
the Tadjourah region, e.g., deep depth profile (183 m),
low groundwater discharge (13.33 m3/h) and thehighest NS data (122.76 m) show the possibility ofhigh fluctuation of the groundwater in faults region.
High fluctuation of the NS data is also shown forboreholes data on at the Hanle watershed (Kouri
Koma III, Liliya Iburi Cheikati, Dikhil 6 and Dikhil8) with deep depth profile (41 – 120 m), highelevation (184 – 474 m) and low discharge (2.2 – 30m3/h).
These results correlate with past studies that show
the groundwater discharges in faults region increase

6. CONCLUSION
This study demonstrates that the proposed
application of the Relief Image for fault detection
using PALSAR-1/2 image data and the Geology
Setting Index analysis are useful to locate an area withhigh possibility of groundwater resources. By
evaluating the correlation between the geology
setting of borehole sites, e.g., geological formation,
occurrence of fault system, aquifer type, etc. withborehole data, i.e. groundwater discharge,
conductivity, depth profile, etc., potential sites forgroundwater resources can be mapped. In study areas,potential groundwater resources are located in or near
dry rivershed (wadi), sedimentary aquifers andregions where fault systems exist. From theobservation of study area in the southwest and centralof Djibouti, the fault regions in the west part (i.e., siteof Weha 3, Weha 5, Weha 13) and the north part (PK20-8, PK 20-1, PK 20-12) of the Ambouli watershed
and the southwest of Djibouti city (site of Agader 2)
show good potential of groundwater for irrigation anddrinking water. At these regions, the groundwater
discharge ranges between 25 - 62 m3/h, depth profile
of boreholes 24 – 67 m and conductivity of boreholedata below 1500 μS/cm.
ACKNOWLEDGMENTS
This study acknowledged the copyright notice for
ALOS PALSAR RTC © NASA [2006-2007],
includes material © JAXA, METI [2006-2007]. The
PALSAR-2 Global Mosaic data have been provided
by the Japan Aerospace Exploration Agency. The
copyright of the Relief image and fault analysis
products (includes the Geology Setting Index
analysis) derived from PALSAR-1/2 data overDjibouti is belong to RESTEC and the usages isgranted to Tokyo University of Agriculture/
SATREPS JST/JICA project through “Fault detection
analysis using PALSAR-1/2 image data throughout
Djibouti” project in FY2020.
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281

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE EFFECTS OF RICE HUSK ASH DOSAGE ONCOMPRESSIBILITY AND MICROSTRUCTURAL DEVELOPMENT OFSTABILIZED CALCITE-RICH RIVER SLUDGE
1

Alex Otieno Owino1, and Zakaria Hossain1
Graduate School of Bioresources, Mie University, Japan
ABSTRACTThe maintenance and construction operations along riverways often lead to large amounts of river sludge thatcan cause severe environmental pollution problems if not disposed of properly. To reduce the risk of suchenvironmental concerns, alternative handling methods such as stabilizing the river sludge are effective in
improving the geotechnical properties of such wastes, making them useful in the construction industry. This study
aims to chemically stabilize river sludge using control-burnt rice husk ash with high amorphous silica content. The
study experimentally investigated the effects of different rice husk ash dosages on the compressive strength (q u),
modulus of deformation (E50), microstructural developments, and the ultimate chemical compositions in thestabilized river sludge specimens during the curing period. The methods applied in this study to reveal the intrinsic
mechanisms included an unconfined compressive strength test, scanning electron microscopy test (SEM), and Xray powder diffraction (XRD). The results showed maximum peaks of calcium aluminosilicate hydrates gels
(CAH-gels) at 5%RHA, a pozzolanic reaction product, which formed strong cementation bonds in the river sludgeRHA composite. Identifying CSH gels and the firmly cemented microstructure provided an insightfulinterpretation for the strength evolution of RHA stabilized river sludge. This proposed stabilization methodology
proved to be an essential parameter in solving the uncontrolled disposal of river sludge and as a conservation
measure in saving RHA and river sludge disposal costs. Additionally, the innovative incorporation of RHA wasan efficient and sustainable approach to justifying river sludge's potential use as subgrade material for designing
light-duty farm roads and footpaths.
Keywords: River sludge, Unconfined compressive strength, Modulus of deformation, RHA, SEM, XRD
INTRODUCTION

alternatives such as rice hush ash is gaining
tremendous attention in the construction industry
owing to its pozzolanic reactivity, the abundance ofrice husks worldwide, and the low carbon footprints
in its production [8][9][10][11]. As discussed in thisstudy, the above advantages permit rice husk ash to
be applied as a stabilizing additive. The excellent
characteristics of RHA, specifically abundantmicropores and large specific areas, can rapidly
influence the moisture content of river sludge or soil
and improve the compaction characteristics hence
showing a great potential of its application ingeotechnical engineering. Furthermore, previous
studies have shown that the main chemicalcomponents of RHA are SO2 and carbon dioxide. It
also includes metallic and non-metallic oxides suchas CaO, AL2O3, Fe2O3, K2O, MgO, P2O5, and MnO,
depending on the rice husk combustion temperatures[12]. When rice husks are subjected to combustion
temperatures between 600-700 °C, the morphology of
the SO2 mainly consists of amorphous silica particles
that exhibit very high pozzolanic reactivity [14]. The
high pozzolanic reactivity proves that RHA has thepotential to generate cementitious gels such as
calcium silicate hydrates that can be used asstabilizing agents for river sludge instead of theadditives with high carbon footprints.
Several researchers have used RHA combinedwith conventional stabilizers such as cement and lime

The maintenance and construction operations
along riverways often lead to large amounts of riversludge generation, and their disposal poses vast
challenges worldwide. Due to the serious
environmental concerns associated with river sludge
pollution (from toxic substances to dust when dry),illegal dumping should be significantly discouraged[1][2][3]. Also, the accumulation of river sludge inrivers and waterways can cause a significant decreasein the downstream river water flow capacities [4]. The
poor geotechnical properties, high water content, andorganic matter have disfavored its application inengineering construction works [5]. However, withthe current developments in material science
technologies, the practicality of pioneering riversludge as a construction material is rising. Some of
the recent research has utilized sludge treatment
procedures, including the introduction of additives
such as phosphor-gypsum, slag, cement, lime, fly ash,blast furnace slag, and magnesium oxychloride
cement, among others [1][4][6][7].
However, it is essential to establish a suitableapproach for river sludge stabilization to counter
further environmental degradation concerns on
matters of carbon footprints associated with the
manufacture of some of these treatment additives.
Currently, the use of amorphous silica-based282

SEE-Mie, Japan, Nov.10-12, 2022

to stabilize soils. These combinations indicated adecrease in soil's maximum dry density and increased
optimal moisture content [14][15]. Concerning thecompressibility of RHA stabilized soils, studies
showed that the unconfined compressive strength(UCS) increased then decreased with increasing RHA
content. For instance, Owino (2022) suggested thatthe optimal contents of RHA with nominal dosages of
cement (3% cement) was 5%, above which the UCS
reduced significantly [16]. Similar developments in
UCS with RHA stabilization have also been recordedin other studies [17][18][19][20][21]. Additionally,
through micro-structure analysis (SEM, EDS, and
XRD), several studies recorded that the structure of
the ultimate RHA stabilized soils was mainlycomposed of hydrated calcium silicate (C-S-H) andsodium-based aluminosilicate (N-A-S-H) at low
RHA contents, justifying the structural developments
reflected in the improved UCS [9][22][23]. However,in literature, there is little to almost no researchdemonstrating the effects of RHA dosages on thecompressive
strengthandmicrostructuraldevelopments in stabilized river sludge.
To address the shortcoming of the available pieces
of research, the main objective of this study was tocomprehensively evaluate RHA's feasibility instabilizing river sludge. A thorough experimental
analysis through a series of unconfined compression
tests was performed to investigate the compressive
strength of the stabilized river sludge considering thecuring period. Also, further examinations by scanningelectron microscopy (SEM) and X-ray diffraction(XRD) tests were conducted to identify pore structureand hydration products, respectively, to reveal the
associated micro-mechanisms of RHA stabilized
sludge with the curing period. The obtained findings
provided a basic framework for developing anappropriate and eco-friendly stabilization technology
for the usage of river sludge.

classification systems, the river sludge was classified
as silty and clayey gravel sand, A-2-5 (0). The
modified Proctor compaction tests showed that the
optimum water content and maximum dry density
were 33% and 1.25 g/cm3, respectively. It was also
noted that the chemical composition of river sludge
was mainly quartz (SO2) and calcite (CaO) with sometraces of iron sulfates (FeOHSO4), as shown in Figure
3a.
Rice husk ash (RHA)
Make Integrated Technologies Ltd, Osaka; Japan
provided the RHA used in this study. RHA wasproduced through a combustion process withtemperatures between 600 and 700 °C and a burning
time of 27 hours. The particle distribution chart
showed an average particle size between 0.001 and
0.3 mm, as shown in Fig. 2. The main chemicalcomponents of RHA were SO2 and carbon dioxide. It
also included some metallic and non-metallic oxides
such as CaO, AL2O3, Fe2O3, K2O, MgO, P2O5, and
MnO in varied proportions, as illustrated in Table 2.
The wide SO2 peak from XRD tests, shown in Figure
3b, justified the high concentration of amorphoussilica content, a fundamental parameter in pozzolanic
reaction processes during river sludge stabilization.
Table 1 Properties of river sludge
Property
Specific Gravity
Maximum dry Density
Optimum water content
Liquid limit, LL
Plastic limit, PL
Plasticity Index, PI
AASHTO classification

Value
2.15
1.25 g/cm3
33%
62.31%
52.27%
10.04%
Silty and Clayey
Gravel sand A-2-5 (0)MATERIAL AND METHODS
Table 2 Properties of RHA
Materials
Physical properties
Specific gravity
Average Particle Size,
Loss of Ignition
Silica (SiO2),
Carbon dioxide (CO2)
Potassium Oxide (K2O)
Calcium Oxide (CaO)
Iron Oxide (Fe2O3)
Alumina (Al2O3)
OthersRiver sludge
The sludge was dredged from a river in Saga
prefecture, Japan. The collection point and processing
steps are shown in Fig. 1a-c. The sludge was black
due to organic matter and became light gray during
the open-air dewatering process. The river sludge was
air-dried before evaluating the specific gravity,
particle size distribution, and the Atterberg limits
following the Japan Industrial standards JIS 1204, JIS
1205, and JIS 1202, respectively [24][25][26]. The
characterization of the dewatered river sludge isillustrated in Table 1 and Fig. 2. As specified by theAmerican Association of State Highway andTransportation
Officials(ASSHTO)
soil

Values1.47
0.001 to 0.30 mm
4.00-6.00
91.10%
4.35%
2.40%
0.57%
0.05%
0.03%
1.50%

Testing methodology
The experimental procedures to analyze the283

SEE-Mie, Japan, Nov.10-12, 2022

stabilization of river sludge included determining

optimum water content (OMC) and maximum dry

Fig. 1 (a) Location of river sludge collection, (b) River sludge processing on-site, (c) River sludge test specimen.
RS
RS+5RHA
RS+10RHA
RS+15RHA

100% Finner

80
60River Sludge : A-2-5(0)Rice Husk Ash (RHA)

100
100
100
100

0
5
10
15

33
40
31
36

1.237
1.135
1.329
1.209

Note: RHA amount = i% weight of the dry weight of river sludge

RESULTS AND DISCUSSION
40

Compaction characteristics

20
0
0.001

0.01

0.1

According to Japan Industrial standards JIS 1210,
the standard Proctor compaction tests wereconducted, and the compaction curves were plotted asshown in Fig. 4 [28]. The optimum moisture content(OMC) increased sharply by 7% for the RS+5%RHA
specimen due to the high-water absorption capabilityof RHA compared to the control specimen.
Additionally, the maximum dry density (γdmax)
decreased to 1.135 g/cm3 for the RS+5%RHA
specimen due to the replacement of the dense riversludge particles with lightweight RHA particles uponstabilization and chemical reactions taking place inthe compacted specimen. The replacement
phenomenon decreased the weight of the proctor
molds containing the compacted river sludge-RHA
mixtures, lowering the γdmax. These observations
agreed with the findings of previous studies [29[ [30][31].
However, for the RS+10RHA and RS+15RHA
specimens, the OMC and γdmax results were found tobe irregular. The irregularity was attributed to themore significant differences in the particle sizes in thestabilized river sludge specimen due to the excess
accumulation of fine materials and the differences inthe specific gravities between river sludge and RHA.
Basha (2005) and Harichane (2011) also observed asimilar deviating trend in OMC and γdmax while
examining the compaction responses of RHA
stabilized residual soils [32] [33]. Moreover, thecompaction curves did not pass the saturation line
(Sr), demonstrating the accuracy of the relationships
between OMC and γdmax.

1

Particle Size, D (mm)Fig. 2 Particle size distribution for river sludge andRHAdensity (MDD) of each mixing scheme, specimen
preparation, compressive strength evaluation, andmicrostructure analyses. The air-dried river sludge
was sieved through a 2mm sieve and mixed with
RHA following the schemes illustrated in Table 3.
The dry aggregates were then mixed by hand for 10
minutes to achieve a homogeneous mixture, after
which water was added according to the OMC, as
shown in Table 3. Next, the mixture was compacted
in three layers inside a mold, measuring 5cm indiameter and 12.5 cm in height using a 1 kg rammer
at a falling height of 30 cm. A record of 20 blows was
registered for each layer to maintain constantcompaction energy. Subsequently, the molded
specimens were placed in a desiccator and wet cured
at a standard temperature of 25°C for 1 day, 7 days,and 28 days.
The unconfined compressive strength test (UCS)
was done using the uniaxial compression tester witha maximum loading of 500N at a axial displacements
rate of 1mm per minute. All the UCS testingprocedures followed the Japan Industrial standards
JIS 1216 [27]. Upon completion of the tests, 50 gramsof river sludge-RHA composite was taken from eachspecimen to evaluate the specimen morphology andmineralogical compositions through SEM and XRD
analyses.
Table 3 Specimen mixing schemes
MixingRiver
RHA OMC
schemesludge(%)(%)(%)

Unconfined compressive strength test results
To understand the bearing capacity of the stabilized
river sludge, the variation of compressive strength of
RHA stabilized river sludge with curing time ispresented in Fig. 5. The full stress-strain curves can

MDD(g/cm3)284

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Dry unit weight of compaction, γd (g/cm3)

evaluate parameters such as the maximum strain andthe unconfined compressive strength. The stressstrain relationship of the control specimen (riversludge only) is also provided in the plots for a better
comparison.

dosage and the curing period.
For instance,
significant improvements in qu were noticeable for
specimen RS and RS-5%RHA with values 427.14
and 420.61 kN/m2, respectively, after 28 days curing
period. The increase in qu was attributed to theflocculation and cementation processes in the calciterich river sludge and the enhanced pozzolanic
reactions at low RHA contents in the stabilized
matrix.
However, for higher RHA contents, thepozzolanic reactivity of the stabilized matrix was
insubstantial due to the accumulation of excess
porous RHA within the specimen, producing a highly
compressible matrix hence the reduction incompressive stresses. On the other hand, the strain at
the maximum compressive stress (qu) decreased
noticeably with the curing period, as shown in Fig.
6b. Generally, the variation of the RHA dosage had
minimal effects on the axial strain development
across all the tested specimens, with an almost
constant strain value ranging between 1.20% to
1.58%.
For the sake of calculating the modulus ofdeformation (E50), the values corresponding to the
50% compressive strength (qu/2) and thecorresponding axial strain (ε50) values were
calculated for all the tested specimens. The equivalent
E50 values considering RHA dosage and curing period
were determined Using Eq. (1) and plotted as
illustrated in Fig. 6c.

Sr = 100
RS
RS+5RHA
RS+10RHA
RS+15RHA

1.8
1.6
1.4
1.2
1.0
0.8
10

20

30

40

50

60

Moisture content (%)

Fig. 4 Compaction characteristics

Compressive stress (kN/m2)

500
RS-1 DAY
RS+5%RHA-1 DAY
RS+10%RHA-1 DAY
RS+15%RHA-1 DAY

400

300

RS-7DAYS
RS+5%RHA-7DAYS
RS+10%RHA-7DAYS
RS+15%RHA-7DAYS

200

RS-28 DAYS
RS+5%RHA-28 DAYS
RS+10%RHA-28 DAYS
RS+15%RHA-28 DAYS

100

𝒒𝒖

𝑬𝟓𝟎 = 𝜺𝟐 ∕ 𝟏𝟎
𝟓𝟎

0
0.0

0.5

1.0

1.5

2.0

2.5

3.0

(1)

Where; E50 is the modulus of deformation of thestabilized river sludge in MPa and ε50 is thecompressive strain at 50% compressive strength(qu/2). It was evident that the moduli of deformations(E50) increased remarkably with the curing period for
all the RHA dosages. Similar results were obtained by
Muntohar (2013) [37] and Jongpradist (2018) [10]while studying the effects of RHA on E 50 during thecuring period. It was also noted that the RHA dosages
greatly influenced the E50 in the stabilized riversludge. For example, the modulus of deformation for
specimen RS, RS-5%RHA, RS-10%RHA, and RS15%RHA was 49.67 MPa, 4.052 MPa, 26.82 MPa,and 27.98 MPa, respectively.
This study proposed using 5%RHA content forriver sludge stabilization as it proved to be an
essential parameter in solving the uncontrolled
disposal of river sludge. Additionally, using riversludge-5%RHA composites can reduce disposal costs
and act as an environmental conservation measure to
reduce the carbon footprint obtained frommanufacturing conventional stabilizer agents.

3.5

Vertical strain (%)

Fig. 5 Stress-strain relationship with curing period
It was observed that the compressive stresses
increased with the axial strains, but the increment ratevaried depending on the RHA content and curing
period. A similar relationship between compressive
stress, axial strain, and curing period has also beenrecorded in other studies [1] [34] [35] [36]. It was also
noted that the maximum compressive stresses wereachieved after 28 days of curing across all specimens.
Additionally, increasing the RHA content reduced
the compressive stresses due to the structuralmodifications of the stabilized river sludge and thelimited pozzolanic activity associated with theaccumulation of excess RHA in the specimen matrix.
Furthermore, the maximum axial strains werereduced by 0.4% after 28 days of moist curing due tothe increased stiffness in the specimens duringstabilization.
In Fig. 6a, the variation of the compressive
strength (qu) with the curing period was presented.
Evidently, the rate of qu development in RHA
stabilized river sludge was influenced by the RHA
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SEE-Mie, Japan, Nov.10-12, 2022

500

Compressive stress (kN/m2)

6a427.14

Fig. 7 Specimen failure patterns after 28 days curing
period

1 DAY
7 DAYS
28DAYS420.61

400

Specimen failure patterns
In this study, it was observed that the failuremodes of the tested specimens under the unconfinedcompressive strength tests varied depending on theamount of RHA in the stabilized river sludge matrix.
The failure modes after 28 days of curing are shownin Fig. 7. A simple shear failure pattern was evident
for specimen RS, RS-5%RHA, and RS-10%RHA ataxial strains of 1.20%, 1.19%, and 1.18%,
respectively. Further increase in RHA dosage to 15%
led to a tensional failure pattern at a corresponding
axial strain of 1.18%, as indicated by the almost axial
failure plane. Moreover, it was observed that for all
specimens tested, no diagonal cracks were evident
during the early stages of testing until the maximum
axial strains were attained, indicating theconsiderable development in shear strength with
RHA stabilization.

280.74300

256.97251.86238.78197.59236.75200

172.17214.09187.50180.68

100

0

5
10
RHA content

15

2.5
1 DAY
7DAYS
28 DAYS

6b

1.5

1.18

1.58

1.44

1.18

1.59

1.17

1.20

1.59

1.20

1.21

0.5

1.20

1.0

1.47

Vertical strain (%)

2.0

Microstructure analyses
This section emphasized understanding thestructural and mineralogical characterization of the
RHA stabilized river sludge through SEM and XRD
tests. The SEM images for the specimen stabilizedwith 0%RHA, 5%RHA, 10%RHA, and 15%RHA,
and the corresponding XRD graphs were presented
and analyzed.
It was observed that the control specimen's
microstructure after 28 days of curing consisted ofcoarser and angular particles and a porous
morphology, as shown in Fig. 8a. Additionally,
secondary particles dominated the microstructure due
to flocculation and agglomeration during thehydration processes within the calcite-rich riversludge. On the other hand, the microstructure of the
RS-5%RHA specimen displayed the development ofa more compact and highly cemented stabilized riversludge matrix, as shown in Fig. 8b. Through XRD
analyses, the observed microstructural evolutions
were justified by the presence of high peaks ofcalcium aluminosilicate hydrate gels (CAH-gels)alongside calcium silicates for specimen RS andRS+5%RHA as shown in Fig. 8c and Fig. 8d,
respectively. The dominant peaks of CAH-gelsenhanced interparticle attractions that ultimately
increased the compressive strength, as shown in Fig.
5a. These results were consistent with the RHA
stabilization results reported by previous researchers[38][39][40].
To further evaluate the effects of RHA dosages,
the representative SEM images and XRD plots for
RHA content of 10% and 15% are shown in Fig. 9.
The SEM micrographs revealed that the higher RHA
dosages led to the development of smaller packets of

0.0

0

5
10
RHA content

15

6c 50

1 DAY
7 DAYS
28 DAYS

45
40

27.98
12.91

26.82
12.66

5

16.47

20.53

10

19.23

15

18.69

20

14.57

25

40.52

49.67

30

27.73

E50 (MPa)

35

0

0

5

10

15

RHA content

Fig. 6 (a)Relationship between qu and RHA
content(b) Relationship between ε and RHA content(c) Relationship between E50 and RHA content

286

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aggregates, and larger pore spaces graduallydeveloped in the specimen structure, as presented inFig. 9a and 9b. The larger pores existed because of
the limited production of hydrated products that was
validated by the detection of the reduced high peak of
CAH-gels for specimen RS+10%RHA and increased
peaks of calcium silicates in the XRD graphs asshown in Fig. 9c. Similarly, a higher concentration of

un-hydrated calcium silicates was also detected for
the RS+15%RHA specimen, as shown in Fig. 9d.
This significant finding coincided well with the UCS
results, thus providing a reasonable explanation forthe strength reduction in the RHA stabilized riversludge as indicated earlier in Figure 5a.

8c 1500

8d 1500

CSH

Calcium Silicate Hydrates:
Ca47(Al96Si96O384)•108(H2O)
Silicates:
Ca0.3Na0.6Al1.5Si2.4O8

CaO3

CaO3
SiO2
SiO2
CSH
CaO3

CSH
CaO3
Silicates
SiO2

CSH
Silicates

SiO2
CSH

CSH

500

CSH
SiO2
Silicates

1000

CSH1

SiO2

KAlSi3O8
CaO3
CaO3
CSH2
SiO2

SiO2

Ca3SiO5SiO2Ca3SiO5500

RS+5RHA (28 DAYS)

SiO2Intensity (cps)Calcium Silicate Hydrates:
Ca0.6Na2.6K2.2Al6Si10O32•12(H2O)
Ca2Al4Si8O24 •12(H2O)
Silicates:
Ca3SiO5 ; KAlSi3O8
CSH1

1000

CSH1
CSH2

Intensity (cps)SiO2

RS (Control) (28 DAYS)

30

40

50

0

0
10

20

30

40

50

10

60

20

2θ (°Degree)2θ (°Degree)

Fig. 8 (a) SEM image for the RS (control) specimen (b) SEM image for the RS+5%RHA specimen (c) XRD
graph for the RS (control) specimen (d) XRD graph for the RS+5%RHA specimen

287

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SEE-Mie, Japan, Nov.10-12, 2022

9d 1500

RS+10 RHA (28 DAYS)

0

SiO2

1

Calcium Silicates:
Ca0.4Na0.7Al1.5Si2.554O8
Mg1.0(SiO3)
CaAl2Si2O12

Mg1.0(SiO3)
CaO
Silicates13
Silicates1

CaAl2Si2O12
Silicates1
Silicates SiO2

CaAl2Si2O12
SiO2

500

CSH
CaO3
SiO2

CaO3

1000

CaAl2Si2O12

Intensity (cps)Silicates2
SiO2
CSH

500
Silicates1

RS+15RHA (28 DAYS)

Calcium Silicate Hydrates:
Ca0.5Na0.6Al1.5Si2.5O8•13(H2O)
Silicates:1). CaAl2Si2O12 ; 2). Ca(SiO3)

SiO2
Silicates1

1000

Silicates1

Intensity (cps)9c 1500

0
10

20

30

40

50

10

60

20

30

40

50

60

2θ (°Degree)2θ (°Degree)Fig 9 (a) SEM image for the RS+10%RHA specimen (b) SEM image for the RS+15%RHA specimen (c) XRD
for the RS+10%RHA specimen (d) XRD graph for the RS+15%RHA specimen
CONCLUSION

through Mie University, where this study was
conducted. This research was also supported by Make
Integrated Technology Limited, which provided
experimental materials.

An eco-friendly material, rice husk ash, was utilized
to stabilize river sludge and proved effective in
improving the geotechnical and microstructuralcharacteristics. The influence of RHA dosage andcuring time was systematically investigated by aseries of unconfined compression, SEM, and XRD
tests. The findings drawn from the investigation weresummarized as follows:
1. The UCS of the RHA stabilized river sludge wasgreatly affected by the RHA content and curing
period. Specimen mixing schemes RS andRS+5%RHA improved the compressive strength,with values 427kN/m2 and 411kN/m2,
respectively, after 28 days curing period. These
conditions proved to be the appropriate
parameter values to improve the mechanicalresponse of RHA stabilized river sludge.
2. SEM analyses showed a dense structural
framework in the new composite material
containing 5%RHA, indicating strength
development. Identifying the less porous
morphology by SEM provided a reasonable
explanation for the improved compressive
strength in the RHA stabilized river sludge.
3. The XRD results demonstrated that the strength
development at 5%RHA was due to thedevelopment of Calcium Aluminosilicate
Hydrates minerals in the hydration products ofthe studied RHA stabilized river sludge.
Additionally, river sludge had a dominantcrystalline phase containing Calcite (CaO3) andSiO2, which had the capacity to precipitate within
the spaces between particles, forming a hardmass within the specimen.

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ACKNOWLEDGMENTS
The authors would like to acknowledge the Japan
Ministry of Education, Culture, Sports, Science andTechnology for providing the MEXT scholarship
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[29] Kumar, A. and Gupta, D., Behavior of cement-stabilized
fiber-reinforced pond ash, rice husk ash–soil mixtures.
Geotextiles and Geomembranes, 44(3), 2016, pp.466-474.
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biochar and coal fly ash on some physical properties of
expansive clayey soil (Vertisol). Catena, 114, 2014,
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natural pozzolana and lime additives on the temporalvariation of soil compaction and shear strength. Frontiersof Earth Science, 5(2), 2011, pp.162-169.
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https://doi.org/10.4081/jae.2022.1315[7] Said, I., Missaoui, A. and Lafhaj, Z., Reuse of
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Kongkitkul, W. and Jamsawang, P., Efficiency of ricehusk ash as cementitious material in high-strength
cement-admixed clay. Advances in Civil Engineering,2018. 11pages https://doi.org/10.1155/2018/8346319[11] Taiwo, L.A., Obianyo, I.I., Omoniyi, A.O., Onwualu,
A.P., Soboyejo, A.B. and Amu, O.O., Mechanicalbehaviour of composite produced with quarry dust andrice husk ash for sustainable building applications.
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utilization of rice husk ash waste for ground improvement.
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[35] Shibi, T. and Ohtsuka, Y., Influence of applying
overburden stress during curing on the unconfinedcompressive strength of cement-stabilized clay. Soils andFoundations,61(4),
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Engineering properties of silty soil stabilized with lime
and rice husk ash and reinforced with waste plastic fiber.
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http://dx.doi.org/10.28991/cej-202003091533

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ANAYSIS OF UNREINFORCED CONCRETE BEAMSONSOIL BY FINITE ELEMENTS⁎

Radhi Alzubaidi ,Husain M Husain1 and Samir Shukur3
University of Sharjah,Civil Engineering Department, Sharjah
1
University of Baghdad, Civil Engineering Department, Baghdad, Iraq,
2
University of Kufa, Civil Engineering Department, Najif, Iraq.
⁎

ABSTRACT
Using unreinforced concrete foundations in construction building leading to a distinctive reduction in cost. A
nonlinear three-dimension finite element analysis has been used to predict the load -deflection behavior of unreinforced
concrete beams on soil by using a computing program (ANSYS5.4). The 8- nodded brick elements with 24 degrees of
freedom is used to represent the concrete and soil. Nonlinearities of material due to cracking, crushing of concrete andsoil are taken into consideration during the analysis. The model by Willam , K and Warnke (1975) been used to represent
the concrete behavior while the modal by Drucker- Prager been used to represent the soil[1]. The nonlinear equationsof equilibrium have been solved using an incremental- iterative technique operating under load procedure. The
modified Newton-Raphson method is used for nonlinear solution algorithm and force or displacement criteria beenused as a convergence criterion. Four applications are analyzed and a comparison is made with experimental andtheoretical load deflection curves, where a good agreement been observed. The effects of some parameters ,like depths,
width and length of foundations, modulus of elasticity of soil and Poisson’s of soil on load -deflection behavior beenstudied , where these parameters showed distinctive effects on the results. The finite element used in present showed agood agreement with experimental results. The results showed some differences of 6% in the ultimate load prediction
and 15.6% in deflection when using interface element and critical state model.
Keywords: Finite element, One-way slab, Foundation, Deflection, Load
1. INTRODUCTION
The development in analysis and design of various
type of foundations has led to the concept oftransmitting the load to soil through a special members
system, which resists the load through direct stress.
The types of foundations are varied according todifferent requirements. The problem of the beam orplate rest on soil has attracted the attention of both
structural and geotechnical engineers and it merges theeffect on both superstructure and substructureelements. Winkler (1967) [2] presented his theory of
the modulus of subgrade reaction, the basic
assumption of this model is the relation between theapplied surface pressure and the vertical surface
deflection at every point[2]. Rao et al (1995) studiedinteraction analysis for the design of open plane frame
resting on soil, the soil has been modeled as 4-nodeisoparametric element, a plane strain approach isadopted for representing the soil. A comparison ismade between the more realistic half-space continuum
and the plane-strain approach to examine theapproximation involved in the letter type ofrepresentation of the soil. They concluded sagging
moments in superstructure beams as obtained using
plane-strain model were always greater than thoseobtained from the elastic half[3]. Boudaa et al (2019)presented a finite element modeling of beam resting on
a two-parameter layered soil, in their model analysis,
they consider the strain energy solutions, the shear
strain of the beam element and soil foundation. They
concluded that the shear deformations showed crucial
influence on the beam, on the structure and on theinterface behaviors[4]. Deb and Dhar (2013) studied
the development of a methodology for theidentification of optimal design parameters for asystem of beams resting on a stone column–improved
soft soil. They conducted a finite difference–based
simulation model and an evolutionary multiobjective
optimization model. In their study tried to minimize
the settlement at the center of the beam and the
maximum shear force. They concluded that theevaluation of the system showed that stiffness of thestone columns or modular ratio and flexural rigidity ofthe beam are the most important parameters for
optimal design[5]. Haldar and Basu (2016) presented
a developed method for nonlinear analysis of EulerBernoulli beams resting on heterogeneous291

SEE-Mie, Japan, Nov.10-12, 2022

multilayered soil. They obtained the governing
differential equations for beam and soils
displacements using the virtual work, the equations
been solved using one-dimensional finite-element andfinite-difference methods, the analysis showed thatbeam responses with accuracy comparable with thoseobtained from equivalent two-dimensional finiteelement analysis are obtained within seconds[6]. AI etal (2014) studied a boundary element method toanalyze the elastic foundation finite beams on 2D
plane-strain and 3D multilayered isotropic soils. They
tried to explore the solution of multilayered elastic
soils that obtained to be a kernel function of BEM
analysis. They found that with the displacement andstress condition of coordination between beam andsoil, the solution is acquired for beams resting on
multilayered soils [7]. Zhang et al (2011) studied thebeam-soil interface resistance and developed adeformation governing differential equation for a finite
beam resting on the Winkler elastic foundation. In theirsolution the coupling effect between vertical andhorizontal displacement is considered [8]. Kousik (2012)
presented soil –structure interaction analysis for beam
resting on multilayered granular fill reinforced withgeosynthetic. The governing differential equations
been solved by finite difference techniques. He
concluded that using the reinforced geosynthetic is notvery effective for maximum settlement reduction andalso not effective for shear force reduction for very
rigid beam. The multilayered reinforced system foundvery effective for bending moment and differential
settlement reduction[9]. Naeij et al (2021) used theiterative finite element method in the field differences
to design a safe steep slopes in a cut. They also showed
that, for steep slopes and vertical cuts, the method
showed a distinctive underestimate the factor of safetycompared to the Limit equilibrium methods [10].
Bayatet al (2018) developed a semi-analytical solution
for nonlinear vibration of Euler- Bernouli beams
resting on linear elastic foundation. The study include
the effects of many parameters on the ratio of
nonlinear to linear frequency of the system. They
concluded that the results were compared withnumerical solution and showed that the maximum andminimum approach can extended in nonlinear partial
differential equations [11]. Mohebkhah (2017) studied
a two-dimensional numerical model utilizing thediscrete element method to predict the ultimate loadbearing capacity of a strip footing on weak clay
reinforced with stone masonry trench. The study
showed that using a stone masonry trench of optimum
dimension I a weak clay can increase the bearing
capacity of a strip foundation up a factor of 3.5[12] .
Khatri et al (2017) investigate into the behavior of thePressure-settlement of square and rectangular skirted
footings resting on sandy soil where the footing issubjected to a vertical load. They carried out load tests
on samples using a model tank and the results showed
when using skirt structures a distinctive increase inbearing capacity and a decrease in settlement[13].
Friswell et al (2007) proposed a non-local viscoelastic
foundation model to analyze the dynamics of beams
with different boundary conditions using the finite
element method. They conclude that the case study,
predicted that the finite element technique is efficientfor the dynamic analysis of beams with non-local
viscoelastic foundations [14]. Verma and Mohanty(2018)
investigate into behavior of shallow
foundation resting on multi layered and homogeneous
soil under dynamic loading[15].

2. FINITE ELEMENT REPRESENTATIONOF INTERFACE
The present study describes a technique for solving
two and three dimensional interface problems. The
elements (contact 52) shown in Fig. 1 are adopted inpresent research.

Figure. 1 CONTAC52 3-D point–to–point (ANSYS
Manual 1997)

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The interface element includes normal and sliding
forces ( [16] and [17] ). This element has one of two
condition if the elastic COULOMB friction is used :Where :
fn = normal force
fs = stick force (in y and z direction)

1- Stuck element (no sliding)µ|fn |˃|fs |Where:µ= coefficient of friction
fn= normal force
fn= Kn (un,j – un,i + d ){∆} =Kn = normal stiffness
un,j=displacement of node j in normal direction
un,i= displacement of node i in normal direction
d= distance between nodes.
Also
fs = Ks (us,j – us,i –uo )fs= sliding force
Ks=sticking stiffness
us,j= displacement of node j in sliding directionus,i= displacement of node i in sliding direction

[K]=

ui
vi
wi
uj
vj
wj

(3)

kn 0 0-kn

0

0 ks 00- ks

0-kn 0 0kn

0

0

0 - ks 0

0

ks

0

0

0

0

ks

0 -ks

0

(4)

uo= distance that nodes i and j have slidewith respect to each other
1. Sliding element

Writing:{F}= [K]{∆}

If

(1)

µ|fn |=|fs |Then sliding occurs in both directions, the stiffness
matrix (in element coordinate) is:

F}=

fn
fsy
fsz
- fn
- fsy
- fsz

[K]=

(2)

kn 0
0 0
0 0
-kn 0
0 0
0 0

0 -kn
0 0
0 0
0 kn
0 0
0 0

0
0
0
0
0
0

0
0
0
0
0
0

(5)

,bond slip, temperature change ,with 165 different
elements conducted in the program.

3.ANSYS COMPUTER PROGRAM

4.NUMERICAL APPLICATIONS[18] in the present study used a computer program
ANSYS 5.4 to analyze plain concrete beams rested on
soil. The program has the capacity to solving linear andnonlinear problems including the effect of cracking,crushing, yielding of reinforcement (if existing) ,creep

Numerical actual cases are conducted to compare theresults obtained by the present method of finite
elements with those obtained from experimental or
analytical solutions.

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A number of numerical examples have been also
analyzed by the computer program ANSYS 5.4. The
examples also used to check the validity of the material
models used and the applicability and capability of theanalysis method adopted in present research where
different types of elements are employed. The
theoretical study is approximate in nature due todifferent factors mainly:
1- Approximation in the material modeling of concreteand soil.
2- Approximation inherent in discretization in finite
element technique.
3- Approximation in the integrations used in the
numerical analysis.
4- Approximation introduced due to the type ofprocedure used in solving the nonlinear system of
equations.
The main results obtained by the solution introduced
through present study are the load –deflection
response, crack propagation and stress distribution.

A two way unreinforced concrete slab withdimension 2.67 m x 2.67 m x 0.762 m was tested underuniform distributed pressure by [19] , details of theconcrete slab are shown in Table. 1. The geometry of
the slab is modeled by (144) 8 brick elements (solid65). Figure.1 shows the details of the finite element
mesh for the two way- slab.
Table.1 Material properties of Two-Way SlabMaterial proper

SymbolValueties and material
parametersYoung
modulus`s

Two-Way Slab

The distributed of load was lumped to nodes, the load
deflection curve for center point is shown in Fig. 2.The
deflection increases as the load increases. The maximum
deflection was found equal to 67.7 mm at maximum load of
10 kpa, after which no convergence was possible.
1210

Load(Kpa)

4.1. Two- Way Concrete SlabFigure 1 Finite Element Mesh of

8
6

pres
en…

4
2

Ec
(N/mm2)

29000

0
0

Compressive
Strengthf`c(N/mm2)

20.67

Tensile strengthft2(N/mm )

2.067

Poisson `s ratio

υ

0.2

20

40

60

80

Deflection (mm)Figure 2 Load –Deflection Curve atCenter of Two- Way SlabResults of finite element give a good agreement withthe experimental results of Mosallam et al (2000).

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4.2 Rigid Footing on Soil
A cast rigid circular footing was tested
experimentally by [20] by resting the footing in arectangular metal filled with sand. Due to symmetry,
only a quarter of the footing system is modeled by the
8 node brick elements (solid 45) and by interface
elements (contact 52). The soil considered ashomogenous sand, underlain by the rigid bottom of thetank. The boundary condition of the structure- soil
problem is considered as the bottom of the tank is fixedwith no movement in x, y and z- directions. The main
purpose of studying this test, is to verify the behaviorof the soil under footing by the present soil model.
Material properties are given in Table 2.

80

Load (KPa)

60
40

Present(withinterface)

20
0
0

10

20
30
Deflection (mm)40

Figure 3 Load –Deflection Curve of Rigid Footing

The load- deflection curve for the circular footing isshown in Fig.3. The present study results showed agood agreement with experimental works of Rasheed(1998).
Table 2 Material Properties of Rigid Footing
Soil

Young`smodulus

E (N/mm2)

10Poisson`s
ratio

υ

0.25

CohesionC (N/mm2)

0

Ø

39.5

Angle
Internal
friction
SteelInterfaceof

Figure 4 Geometrical and loading details of Slab –Beam Foundation
Table 3. Material Properties of Slab –beam foundation
Concrete

Ec(N/mm2)

21560

20000

Young` s
ModulusCompressive
strengthf`c(N/mm2)28

TensileStrengthft(N/mm2)

1.75

Poisson`s Ratio

υ

0.15

Young`
Modulus

s

Eso

15

Poisson`s Ratio

υso

0.3

CohesionC(N/mm2)0Young`smodulusEs (N/mm2)

Yield stressƑy (N/mm )295

Factorfriction

µ

0.25

of

2

Soil

4.3 Slab-Beam Foundation
The case of slab-beam foundation of [21]is consideredand solved by (ANSYS 5.4) program. The dimensionsof the foundation is shown in Fig.4, and the propertiesof the properties of soil can be shown in Table 3. Dueto symmetry of loading and geometry, only one half ofthe slab –beam foundation is analyzed by using (2316)
elements as shown in Fig. 5 . The load - deflection
response at the position of column on slab is shown in295

SEE-Mie, Japan, Nov.10-12, 2022

Interface

Angle
Internal
Friction

of

Ø

36

Factorfriction

of

µ

0.3

(a)TopView(b) Side View

Figure 7 Crack Patterns of Slab – Beam Foundation
at Final Load (1000 KN)

Shown in Fig. 7 . The first crack initiates at a load of
about 375 KN. The cracks separate in all three
directions of the beam, through the increase of load
levels.
5. PARAMETRIC STUDY

Figure 5 Finite Element Mesh of Slab-Beamfoundation

The influence of some parameters on the behavior of
the same slab- beam foundation under static load isstudied. These parameters include the effect ofthickness of foundation, modulus of elasticity andPoisson's ratio of soil.

in Fig.6 ,the computed deflection shows a good
agreement with the theoretical results , the crack
patterns of the slab – beam at different load levels are

5.1 Effect of Foundation Thickness
1200

The effect of foundation thickness is investigated(slab and beam), three values of thickness 0.3, 0.5, and
0.8 m were considered at constant value of Poisson's
ratio (0.2) for soil with different values of modulus ofelasticity of soil of 10,17,24 MPa . Figure 8 shows therelation between the maximum displacement beneaththe foundation and the modulus of elasticity of soil fordifferent values of thickness foundation. It can be seenthat the increase of thickness would considerably
decrease maximum displacement.

Load (KN)

1000
800
600

400

Present200

Al-Erris

0

0

20
40
Deflection (mm)60

5.2 Effect of Modulus of Elasticity
The effect of modulus of elasticity of soil also
investigated, three values for the modulus of 10, 17 and
24 MPa used for three values of thickness of 0.3,0.

Figure 6 Load – Deflection Curve of Slab – Beam
Foundation

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displacement of the foundation for all values. This may
attributed to the increasing of the rigidity of the soil.

Maximum
Displacement (mm)E=
1…

Maximum Displacement (mm)

60
50
40

Thickness (m)Figure 8 Effect of Foundation Thickness
Maximum Displacementonand 0.8 m with constant passion's ratio of 0.2 andanalyzed numerically. The results showed that theincrease in the values of modulus lead to a distinctive
decrease in the displacement for all values ofthickness. This is due to the increase in the rigidity or
stiffness of the soil as can be seen in Fig.930

Thickness=0.3 m20

Thickness=0.5 m10
00.20 0.23 0.25 0.28 0.30 0.33 0.35 0.38
Poisson's Ratio

60
Fig.10 Effect of Poisson's Ratio of Soil on
Maximum Displacement

Maximum Dispacement (mm)Thicknes
s=0.3 mThickness =0.5 m

50
40

6. CONCLUSSIONSThe present research developed a numerical methodof analysis, include the analysis of unreinforced
concrete foundations under static load. 8-nodes brickelement has been used to model the concrete
foundation. Also ,8-node brick element has been used
to model the soil ,while the interaction between the soil
and the concrete foundation is simulated by contact
interface element. Based on the present finite element
developed program ,which been conducted through thepresent work , the following conclusions can be drawn
as follows:

30
20

10
0
10

15

20

25

Modulus of Elasticity (MPa)Figure 9 Effect of Soil modulus on
Deflection

1- The ability of using unreinforced concrete beams in
the foundation with a good performance even after
occurrence some cracks.
2-The results obtained from the present finite element
method showed that the computational model adopted
in present research is suitable for prediction of loaddeflection behavior of unreinforced concrete
foundation under static load. The comparison between
the numerical and the available experimental results
showed a good agreement.
3- The comparison of the numerical results obtained byusing the present solution with experimental testing of
two way slab. The deflections increase as the loads

Maximum

5.3 Effect of POISSON'S Ratio
To investigate the effect of Poisson's ratio for thesoil, three values are adopted 0.2 ,0.275 and 0.35 at
three values of thickness 0.3 ,0.5 and 0.8 m , while themodulus of elasticity for the soil is constant at value of
10 MPa . Fig.10 shows when increasing the values ofPoisson's ratio lead to distinctive decrease in297

SEE-Mie, Japan, Nov.10-12, 2022

increase. The results of the finite element showed agood agreement with experimental results.
4- The results of the load –deflection finite element
solution showed a considerable agreement with theexperimental results of a cast –iron rigid circularfooting.
5- The slab – beam foundation tested load –deflection
results showed a good agreement with finite
element solution developed in presented study.
6- The numerical results obtained when taking into
account the effect of using contact interface
element showed a better simulation to theinteraction between the soil and the concrete
foundation. It is found that the behavior offoundation will be softer when the interface
behavior is neglected.
7- The parametric studies showed that there is adistinctive effect when increasing the length, depth,
and width of the concrete beam and Poisson's ratio
and modulus for the soil. These parameters showed
different effects on load – deflection behavior of
the foundation.
8- The effects of foundation thickness, Poisson’s ratio
and modulus of elasticity of soil are found to havethe most distinctive factors that affect the load –deflection behavior of slab-beam foundation, whenthese parameters increase the rigidity of the soil
increase.
7. REFERENCES[1] Willam , K and Warnke (1975) , Constitutive Model
For The Triaxial Behavior of Concrete , Proceeding
International Association for Bridge and StructuralEngineering ,Vol.19, Issue 15,Bergam, Italy[2] Winkler (1967), E. “Die Lehre Von Der
Elastizitatune Festigkeit “ Dominicus, Prague,
1976.
[3] Rao, P, Rambabu, K.V, and Allam, M.M, (1995)“Representation of Soil Support in Analysis ofOpen Plan Frames”, Computers and Structures,
Vol.56, No.6, pp.917-925[4] Boudaa, S, Khalfallh, S, and Bilotta, E. (2019)“Static interaction analysis between beam andlayered soil using a two-parameter elastic
foundation. International Journal of Advanced
Structural Engineering volume 11, pp21–30.
[5] Deb, K and Dhar, A. (2013) “ Parameter estimation
for a system of beam resting on stone column-

reinforced soft soil. International Journal of
Geomechanics ,vol.13 ,issue 3.
[6] Haldar ,S and Basu , D (2016) “ Analysis of Beams
on Heterogeneousand Nonlinear Soil “.International Journal of Geomechanics , Vol.16 ,Issue 4.
[7] AI,Z , Li, Z, and Cheng ,Y(2014) “ BEM analysis
of elastic foundation beams on multilayered
isotropic soils “ Soils and Foundations ,Vol.54,
Issue 4,pp667-674[8] Zhang ,L, Zhao, M and Xiao , Y. (2011) . “Nonlinear
analysis of finite beam resting on Winkler foundation
with consideration of beam-soil interface resistanceeffect”. Structural Engineering and Mechanics ,Vol.38,
Issue 5,pp 573-592.
[9] Kousik, D (2012) “ Soil-structure interaction analysis
of beams resting on multilayered geosyntheticreinforced soil, Interaction and Multiscale Mechanics,Vol.5, Issue 4[10] Naeij , M, Ghasemi, D,Ghafarian ,D andJavanmardi,Y, (2021) Explicit finite element
analysis of slope stability by strength reduction,
Geomechanics
andEngineering,Vol.26,Number2 pp133-146[11] Bayat, M, Bayat, M, Kia ,M , Ahmadi , H and
Pakar, I (2018) Nonlinear frequency analysis ofbeams resting on elastic foundation using maxmin approach , Geomechanics and Engineering,Vol.16,Number 4 ,pp355-361.
[12] Mohebkhah, A (2017) Bearing capacity of strip
footing on a stone masonry trench in clay,
Geomechanics and Engineering,Vol.13,Number
2 ,pp255-267[13] Khatri, V, Debbarma, S , Dutta ,R and
Mohanty , B (2017) Pressure-settlement
behavior of square and rectangular
Skirted footing resting on sandGeomechanics and Engineering ,Vol.12,
No.4 ,pp 689-705[14[14] Friswell. , M, Adhikari. , S and Lei,Y (2007) ,Vibration analysis of beams with non-local
foundations
using
the
finiteelement
method.International journal for numerical methods
in engineering,Vol.71,pp 1365-1386.
[15] Verma ,A and Mohanty ,S. (2018) Finite element
analysis of foundation on layered and homogeneous
soil deposit under dynamic loading. Indiangeotechnical conference, Bengaluru, India

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[16] Mazurkiewics, M, and Ostachowicz, W (1983)“Theory at Failure Element Method for Elastic
Contract Problems of Solid Bodies” Computers andStructures, 17(1)[17] ANSYS Manual (1997) ,Version 5.4 , Swanson
Analysis System ,Inc., Houston , Pennsylvania.
[18]Shukur ,S (2002) Analysis of Unreinforced
Concrete Beams on Soil By Finite Elements, MSc
thesis ,College of Engineering ,University of Kufa,
Iraq.
[19] Mosallam, A., Kreiner, J., Lancey , T,. Haroun, M.

and Elsandedy ,H.,(2000)
Experimental andNumerical Analysis of Two Concrete Slabs
Repaired with Polymer Composites ,Division ofEngineering California State University – Fullerton.
Ca 92834, USA .
20] Rasheed, K, (1998) . A Study of the Behavior of
Conical and Inverted Spherical Shell Foundations.
PhD thesis, University of Baghdad, Baghdad, Iraq.
[21] AlEriss, H ,(1982), Interaction of Soil –Footings
Connected by Grade beams . MSc thesis, universityof Technology, Baghdad, Iraq.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXPERIMENTAL STUDY ON RETROFITTING OF HOLLOW BRICK
MASONRY HOUSES USING A FERROCEMENT LAYER
Fauzan1, Jonathan Vincensius Osman1, Geby Aryo Agista1, Naurah Daffa Carol1 and Yundha Syah Putra1
1

Engineering Faculty, Andalas University, Indonesia
ABSTRACTAn experimental study on a hollow brick masonry house with and without a ferrocement layer was carried out
to investigate the effect of retrofitted houses using ferrocement layer. Two specimens of the hollow brick masonryhouse with the scale 1/4 of the actual size (104 cm x 110 cm) were prepared. The first specimen (B1) is a hollow
brick house without retrofitting and mortar plastering, which is tested to suffer heavy damage, while the second
specimen (B2) is a brick wall house retrofitted using a ferrocement layer with bandage system on both sides of thespecimen wall. Both specimens were tested on a shaking table of 304cm x 190cm with a load variation of 0.3g 1g. The first test aims to make B1 specimen severely damaged, where the heavy damage occurs when the input
load is 0.6 g with an additional evenly distributed load is 200 kg. After testing, the cracked B1 specimen was
repaired and retrofitted using ferrocement layer with bandage system. The second test is then carried out on the
retrofitted B1 and B2 specimens. The test result shows that no visible damage was observed on both specimens up
to a variation of the input load of 1 g with an additional uniform load of 500 kg. This proves that the ferrocement
layer with bandage system can be applied for retrofitting the damaged hollow brick houses after an earthquake,
which significantly improves the seismic behavior of hollow brick houses.
Keywords: URM house, Hollow brick, Earthquake, Shaking table, Ferrocement layer

INTRODUCTION
Indonesia is a country that often experiences
natural disasters, especially earthquakes. Major
earthquakes that have occurred in Indonesia such as
Aceh earthquake in 2004, the West Sumatra
earthquake in 2009, Lombok and Palu earthquakes in
2018, Mamuju Earthquake in 2021 and West
Pasaman Earthquake 2022. These earthquakes caused
enormous losses, not only claimed many lives but
also damage to infrastructure and buildings,
especially simple houses/community houses, ranging
from minor-to-major damage.
Community houses are generally built using
unreinforced masonry (URM) buildings. This house
is not strong against earthquake loads, because thebuilding does not have structural elements such as
beams and columns, while the walls thickness are notin accordance with earthquake resistant housestandards [1]. The house was usually built without
involving construction experts such as Architects andCivil Engineers [2]–[4].
The behavior of the brick/hollow brick material
makes this house brittle and has almost no ductility
that makes the brick wall does not have the resistanceto horizontal loads or earthquake loads. When an
earthquake occurs, this simple unreinforced hollow
brick building can suffer light damage to heavy
damage, as shown in Fig. 1.

Fig. 1

Damage to brick wall houses due to the 2022
West Pasaman earthquake [5].

In order to retrofit the damage houses, manymethods had been published, one of them is
Ferrocement layer method. Ferrocement is a type ofplaster (mortar) that is reinforced with woven wire.
Many studies have been conducted on the use
Ferrocement layer as retrofitting method for thedamaged non-engineering buildings such as houses[6]–[8]. Testing results of the brick house retrofittedwith ferrocement layer showed that the retrofitting
method improve the capacity of the house, which was
effective in preventing wall collapse during anearthquake [9]–[12].
In this research, an experimental study on hollow
brick masonryhouses with and without aferrocement layer was carried out to investigate theeffect of the retrofitted damage house using
ferrocement layer with a bandage system. The house300

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specimens were tested on a shaking table test, which
apply the earthquake load to these specimens.
TEST SPECIMENS

Fig. 2

Plans and sections of B1 and B2 specimens.

Fig. 4

Fig. 3

View and details of B2 specimens.

In this study, two hollow brick masonry house
specimens were prepared. The first specimen (B1) isa simple hollow brick house, which is tested until it
suffered heavy damage and then, it retrofitted with aferrocement layer with a bandage system. The second
specimen (B2) is a simple hollow brick house madeusing a ferrocement layer with bandage system asshown in Fig. 2. Both specimens are scaled 1/4 fromthe original house size. These two specimens werescaled due to the limitations of the shaking table used
to test the two specimens.
Both specimens with the size of 1.04m x 1.1m
were constructed, as shown in Figs. 2 to 4. The hollow
brick material used was 100 x 50 x 25mm, which isthe scale of the actual material size. The compositionof the cement and sand mixture to make the materialis 1 : 5 by volume. The mortar used for spacing andplaster has a 1 : 4 mixture of cement and sand by
volume. The thickness of the spacing is 5mm. The
width of the ferrocement layer is 125mm. The
thickness of plaster for coating the woven wire is
5mm. Material properties such as compressive
strength of hollow brick and plaster ranged from 2.5
MPa and 9.9 MPa which were tested at the Materials
and Structural Laboratory, Department of Civil

View and detail of B1specimens.

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Engineering, Andalas University. The process ofmaking B1 and B2 specimens can be seen in thefollowing figure (Fig. 5 and Fig. 6).

G-TraceFig. 7
Fig. 5

Set-up of specimens on shaking table.

TEST PROCEDURES

Process of B1 specimen.

In this study, both specimens were tested using ahorizontal uniaxial motion shaking table at the Soil
Mechanics Laboratory, Andalas University [14].
Table 1 shows the input motions of this test withvariations in earthquake frequency, such as Moderate
Earthquake (ME), Strong Earthquake (SE), and Very
Strong Earthquake [10]. The input motion of 0.6g is
the Peak Ground Acceleration (PGA) of Padang City
based on the 2019 Indonesia Earthquake Map. The
excitation given to the test object: a = 2.94 m/s2, 5.88
m/s2, and 9.81 m/s2.
Table 1 Variation of input earthquake load
Type of input motions
ME (0.3g)
SE (0.6g)
VSE (1g)

Fig. 6a (m/s2)
2.94
5.88
9.81

B1 dan B2 specimens were tested on a shaking
table, in which the test was stopped when the B1
specimen is severely damaged. This test (P1) consistsof 3 times of loading, namely: 0.3g – no load, 0.3g –200 kg additional uniform load, and 0.6g – 200 kg
additional uniform load. After B1 specimen was
severely damaged, the specimen was repaired andstrengthened using a ferrocement layer with abandage system.
Both specimens were tested again on the shaking
table. This retest (P2) consists of four times ofloadings, namely: 0.3g – 400 kg additional dead load,
0.6g – 400 kg additional dead load, 0.6g – 500 kg
additional dead load, and 1g – 500 kg additional deadload. The additional dead load referred to is the loadusing a sand-filled sack placed on top of thespecimen, as shown in Fig. 8. In this research phase,the earthquake load given also refers to the September
30, 2009 Padang Earthquake.

Construction process of B2 specimens.

According to the Indonesian Seismic Standard(SNI 1729–2019), clause 7.5.3 stated that the load isapplied separately in all two orthogonal directions.
The effect of the most critical load due to the directionof application of earthquake forces on the structure isconsidered fulfilled if the components andfoundations are designed to carry the load
combination specified as follows: 100 percent of theforce for one direction plus 30 percent of the force forthe perpendicular direction [13]. Therefore, the slopeof the specimen is set at 16˚ towards the positive xaxis, as shown in Fig. 7.

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Sand

Both specimens in this test were given an
earthquake load of 0.3 g with an additional uniform
load of 200 kg. The test result shows that the two
specimens also did not suffer damage.

Sand

Tests with an input motion of 0.6 g and an additional
uniform load of 200 kg (P1-C)

Fig. 8In this test, both specimens were given an
earthquake load of 0.6 g with an additional uniform
load of 200 kg, where the results of this test show thatB1 specimen suffered heavy damage on all sides ofthe specimen wall, as shown in Fig. 10, while B2
specimen did not suffer any damage. The condition ofdamage as in B1 specimen is stated as the conditionof the specimen experiencing severe damage.

Specimen with additional uniform loadusing sacks filled with sand (sandbags).

RESULT AND DISCUSSION
The test results from this experimental study
include failures such as crack patterns that occur inthe specimen and the maximum acceleration obtained
from the readings of the G-Trace vibration reader.
This experimental study was divided into 2 tests,
namely testing B1 specimen until it was severely
damaged (P1) and testing after B1 specimen was
strengthened using a ferrocement layer with bandage
system.
The Test of B1 Specimen Until It Was Heavily
DamagedThis test aims to make B1 specimen severely
damaged to see whether the retrofitting using
ferrocement layer can be applied to strengthen houses
that have suffered heavy damage due to theearthquake.
Test with input motion of 0.3g and no additional
uniform load (P1-A)
In this test, both specimens were subjected to an
earthquake load of 0.3g and no additional load. From
the test result, it appears that the two specimens did
not suffer any damage because the earthquake
strength was not enough to damage the building, asshown in Fig. 9.

Fig. 9Fig. 10. Specimens that have been tested with Input
motion of 0.6 g and an additional uniform
load of 200 kg.
Testing B1 Specimen After Retrofitting
Due to B1 specimen having been severely
damaged, B1 specimen is then repaired and retrofittedusing ferrocement layer with bandage system, which
was tested again on the shaking table.
Both specimens were subjected to an earthquake
load of 0.3 g with an additional uniform load of 400
kg (P2-A), 0.6g with additional uniform load of 400
kg (P2-B) and 500 kg (P2-C), 1g with additional
uniform load of 500 kg (P2-D). The test results showsthat there is no damage was observed on both
specimens after each test until P2-D test, as shown in
Fig. 11. This is because the contribution offerrocement layers in improving the specimen
capacity to withstand earthquake loads. This result
also proves that the retrofitting using ferrocement
layer can be applied to houses that has been damaged

Specimens that have been tested with 0.3g
input motion and no applied additional load.

Tests with an input motion of 0.3g and an additional
uniform load of 200 kg (P1-C)
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by the earthquake. The retrofitted house can be safe
without damage and cause no casualties when anotherearthquake occurs. This test is only carried out until
this stage due to the limitations of the shaking tableequipment.

Fig. 13 Graph of acceleration response for shaking
table (b), B1 and B2 specimens with anearthquake load of 0.6 g and an additional
uniform load of 200 kg.

Fig. 11 Specimens that have been tested with an
input motion of 1g and an additional uniform
load of 500 kg.
Comparison of Cracks Pattern That Occurred
During Testing
Figure 12 shows the crack pattern on B1 specimen
tested until it is severely damaged. From the figure, it
can be seen that the cracks occurred at an earthquake
load of 0.6g with an additional evenly distributed loadof 200 kg. From the acceleration reading obtainedusing G-Trace shown in Fig. 13, the maximum
acceleration (amax) of B1 specimen when the cracks
occur is 2.5g at t = 2.5 seconds.
After retrofitting the B1 specimen, the test is
continued until the input motion of 1 g and additional
uniform load of 500 kg. For this test, neither thereinforced B1 specimen nor the B2 specimen
experienced cracks, as shown in Fig. 14. The amax of
the B1 and B2 specimens at this test were 2.52g and1.27g, respectively, as shown in Fig. 15. The test was
carried out for 30 seconds, but there was no damage
to both specimens, although the acceleration that
occurred in both specimens was quite large.

Fig. 14 Schematic of cracks pattern of the retrofitted
B1 specimen until the end of the test.

Fig. 15 Graph of acceleration response for vibratingtable (b), B1 and B2 specimens with anearthquake load of 1 g and an additional evenload of 500 kg.
CONCLUSION
Based on the experimental results carried out on
the retrofitting the hollow brick houses using
ferrocement layer, the following conclusions can be
drawn:

Fig. 12 Schematic of cracking pattern on B1
specimen until it is severely damaged.
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1. B1 Specimen suffered heavy damage at the input
motion of 0.6g and an additional evenly
distributed load of 200 kg because the damage
occured on all sides of the hollow brick wall of thespecimen.
2. No damage or cracking was observed in both
specimens until the input motion of 1g and an
additional uniform load of 500 kg when the testing
was conducted after retrofitting the B1 specimen.
3. The maximum acceleration (amax) of B1 specimen
when the cracks occur was 2.5g at t = 2.5 seconds,
while the amax of the retrofitted B1 specimen at theend of the test was 2.52g without any crack
appeared on the specimen.
4. The results of this study prove that ferrocement
layer with a bandage system can be used for
retrofitting the damaged hollow brick houses after
an earthquake, which can significantly increase
the seismic behavior of hollow brick houses.

gempa-pasaman-barat-103-rumah-rusak-berat.
Retrivied 21 September 2022.
[6] Ferrocement Technology., Definition of
Ferrocement.http://tebeceria09.blogspot.com/20
12/12/technology-ferrocement.html. Retrieved
10 May 2018.
[7] Sandeep K., Ferrocement Materials forConstruction,
International
JournalofEngineering Research and Applications, 2018,
Vol. 8, No. 3, pp.53-55. ISSN: 2248-9622.
[8] Al-Rifaie WN, and Mohammad K, Load
Carrying Capacity of Clay Brick Masonry Wall
Encased by Ferrocement, International Journalof Emerging Engineering Research andTechnology, 2017, Vol. 5, No. 4, pp.26-35. ISSN
2349-4395 (Print) & ISSN 2349-4409 (Online).
[9] Boen T, Brief Report of Shaking Table on
Masonry
Building
Strengthened
withFerrocement Layer, 16th World Conference on
Earthquake, 2017, Paper no. 1393.
[10] Fauzan, Ismail FA, Hakam A., Zaidir, andAmalia SH, Experimental Study on Masonry
Building Strengthened with Ferrocement Layers,
International Journal of GEOMATE, May.,
2018, Vol. 14, Issue 45, pp.84-90.
[11] Fauzan, Hakam A., Ismail FA, and Osman JV,
Experimental Investigation of Hollow Brick
Unreinforced Masonry Building Retrofitted by
Ferrocement
Layers,
4th
International
Conference on Science, Engineering &Environment (SEE), Nagoya, Japan, Nov. 12 –14, 2018, ISBN: 978-4-909106018 C3051(Proceeding).
[12] Asif MM, Alam MZ, and Ahsan R., An
Experimental Investigation of Ferrocement
Retrofitted Masonry Wall Units Subjected to
Cyclic Loading, Proceedings of the 5thInternational Conference on Advances in Civil
Engineering (ICACE 2020), 4-6 March 2021,
CUET, Chattogram -4349, Bangladesh.
[13] National Standardization Agency, Earthquake
Resistance Planning Procedures for Building
Structure and Non-Building Structure (SNI
1726-2019), 2019, Jakarta.
[14] Hakam A., Ismail FA, and Fauzan, Liquefaction
Potential Assessment Based on Laboratory Test,
International Journal of GEOMATE, Oct., 2016,
Vol. 11, Issue 26, pp.2553-2557.

REFERENCES[1] Gumilang AA, and Rusli M., Seismic
Performance of earthquake resistant simple
residential confined masonry house structure
based on PUPR regulation No. 5 of 2016
specification, 2nd International Conference on
Disaster and Management, 2021, 708 012085.
[2] Boen T., Learning from Earthquake Damage:
Non-Engineered Wall Buildings in Indonesia,
Yogyakarta: Gadjah Mada University Press,
Indonesia: 2016 (In Bahasa).
[3] Ismail FA, Asmirza MA, Hakam A., Fauzan,
Ferrocement – Brick Sandwich Wall Applied to
Non – Engineered Houses, International Journalof GEOMATE, April., 2018, Vol. 14, Issue 44,
pp.47-51.
[4] Hakam A., Fauzan, Ismail FA and Istijono B.,
Capacity Building of Local Home Builders on
Application of Earthquake Safe House forDisaster Risk Reduction, 4th Annual meeting ofIndonesian Disaster Expert Association, May
2017, Jakarta.
[5] CNN Indonesia., 8 Meninggal Akibat Gempa
Pasaman Barat, 103 Rumah Rusak Berat,
https://www.cnnindonesia.com/nasional/202202
26122239-20-764392/8-meninggal-akibat-

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

LABORATORY INVESTIGATION ON WATER QUALITY OF SPRINGWATER FOR SMALL COMMUNITY FOR WATER SECURITY
Mohamad Nazrul Hafiz1, Maidiana Othman1, Noor Afiza Mat Razali1, Zuliziana Suif1, Jestin Jelani1 andNordila Ahmad1
1Faculty of Engineering, Department of Civil Engineering, National Defence University of Malaysia,
Malaysia

ABSTRACT
Water has become a necessity in our daily life. The lack of clean water will be forced people to drinks unsafe
water and lead to more diarrhea cases which is the second leading cause of death for children. The impact of unsafe
water on the consumer is critically alarmed and has contributed human health problem. An alternative clean water
sources as a water supply should be sustainable solution to overcome this problem. Malaysia is located at theequator to have rain and hot weather along the year. Therefore, the possible use of spring water as an alternative
clean water source will improve the quality of water consumption especially for small community in rural areaand provides a benefit to surrounding flora and fauna. The aim of this study is to investigate the performance ofspring water sources located in National Defence University of Malaysia (NDUM) campus to support the Green
Campus champaign. The spring water analysis was performed for various physicochemical during February 2020
to May 2020. Temperature, pH, electrical conductivity, total dissolved solid, total suspended solid and dissolved
oxygen were measured to generate water quality index. The results demonstrated the water samples were found tobe suitable for use were within permissible limits except pH were close to or exceeded the permissible limit ofstandards, which indicates that requirement of treatment prior to use. The outcome of this study may contribute topropose the new way of monitoring water quality in campus by using real-time system. In addition, the outcome
also to provides the baseline information about water quality for the welfare of society, support the Green campus
campaign and that may also help in future water security and sustainability planning for the NDUM campus area.

Keywords: Spring Water, Water Quality Monitoring, Sustainability, Water Security.

INTRODUCTION

support three theme which is to minimize thecontaminant in groundwater, implement integrated
water management at all planning levels and to
maximize water efficiency and adapt withdrawals towater availability (Stefan Siepman, 2022).
Besides natural water resources like stream, lake,
and river basin, alternative water sources are also
started eagerly by human to overcome the scarcity ofwater in the future. By exploring the new water
resources and invent new technologies, the current
agencies generate extra or replace current watersupply to reach the water demand for current situationand future generation (Li and Boyle, 2010).
In Malaysia, surface water and groundwater are
the main source of water supply for drinking,domestic, industrial and agricultural purposes. Springwater is one of the most important for human as asource of fresh water, especially in arid regions whichhave relatively lac of annual rainfall. Spring is an
opening at or near the surface of the Earth for thedischarge of water from underground sources ordirectly into the lake, sea or steam.
The quality of spring water sources varies widely,depend on the location and environmental factors.
The quality of water discharged by a spring depends

Water has become a necessity in our daily lives.
In 2013, the average usage of water per day for
Malaysians is 210 liters, while in 2014 the value
increase by 2 which means 212 liters or about 141
bottle of 1.5 liters water bottle (Abdullah, 2015).
However, the amount of water usage in 2018 has
increase to 300 liters per person. The value set by
United Nations (UN) is 165 liters per person. The
amount set by UN is enough for a person’s basic dailyneeds and yet Malaysians use almost double thatvalue. The trend of excessive usage of water in
Malaysia might rise water shortage problems. The
lack of clean water will be forced people to drinks
unsafe water, this will lead to more diarrhea cases
which is the second leading cause of death in children.
World water day celebrate water and raises
awareness of the 2 billion people living without
access to safe water. It is about taking action to tackle
the global water crisis. The main focus is to support
the achievement of Sustainable Development Goal
(SDG) 6: Water and sanitation for all by 2030. This
year, 2022 theme is “Groundwater is invisible, but its
impact is visible everywhere”. This event is to307

SEE-Mie, Japan, Nov.10-12, 2022

on the type of aquifer and rock strata through which
the water has passed, the temperature along the routeand the volume of circulating water, past and present(Britannica, 2020). Water quality expresses thesuitability of water for various application including
drinking, industrial water supply, irrigation andgeneration of hydro power. Water quality is indicatedby various physical parameters such as pH, total
solids, total dissolved solids (TDS), total suspended
solid (TSS), hardness, chlorine content many otherparameters related. Recently, several studies havefocused on monitoring spring water quality in
Malaysia (Simon et al. (2019), Razali et al. (2017),
Awang (2015), Ngadiman et al. (2015), Zaini et al.
(2013)). In Malaysia, spring water quality evaluationand monitoring have received little attention,
therefore, these types of analyses are needed tounderstand the physiochemical and quality changesof spring water.
Green campus campaign has been introduced in
NDUM campus as one of efforts to support
sustainable development goal set by United Nation.
Several studies have been performed to identify thepotential of natural and environment resources in
NDUM campus for further action including wetland(Othman et al. 2021a), recycle waste (Othman et al.
2021b), solar energy (Hashim et al. 2021) and otherstudy related (Jelani et al. 2021) This study supports
the green campus campaign in UPNM by providing
the initial data collection for water security andsustainability planning in future.
In this study, the water quality of spring waterlocated in NDUM campus were measured andclassified based on National Water Quality Standard.
Five parameters (Dissolved Oxygen, Temperature,
Total Suspended Solids, Total Dissolved Solids andpH) is chosen as the initial factors in determining thespring water quality.

from February to April 2020 in between wet(Northeast Monsoon from October to March) and dry(Southwest Monsoon from April to September). The
water samples were placed in 500 ml bottles rinsed
with distilled and later washed with the sample’s
water. These bottles containing water samples werelater transferred into a cooling box and stored in arefrigerator at 20oC for water quality analysis.

Fig. 1The location of NDUM and the spring water

The water quality analysis involved several
parameters including temperature (°C), pH, electricalconductivity (EC), total dissolved solid (TDS), totalsuspended solid (TSS) and dissolved oxygen (DO) in
accordance with the procedures delineated in thestandard guideline described by WHO (2011) and
NSDWQ (2004). Electrical conductivity (EC) and pHof each water sample were measured in-situ. The
water quality assessment from other water resources
around UPNM (i.e. groundwater (Omar (2021), tapwater (Jamid (2018) and rainfall (Munikanan et al.
(2019)) was used as a control. Table 1 shows thetechnical and methods used for the analysis ofdifferent parameters, along with the instruments andunits used in this study.

MATERIAL AND METHODS
Study area and sampling sites(a) Temperature
Temperature is one of the factors that affect thewater density and dissolved oxygen levels inwater. Moreover, temperature control rate
reactions and growth of living organism in water.
The variation in temperatures may influence byvarious condition along its path to the surface.
WHO (2011) stated that there is no requirement
for temperature as it changes depending on thelocation of the water source.
(b) pHpH refers to the degree of acidity or alkalinity ofa water.
(c) Electrical conductivity
The conductivity in water is the ability of water to
conduct an electric current. This is proportional
to the ion concentration in the water.
(d) Total suspended solids
TDS is a measure of the dissolved combined

The study area is located in the NDUM campus
area situated near Sg. Besi at a distance of 10 km fromcity of Kuala Lumpur, Malaysia. The community inthe campus has about 3000 persons. The map and thelocation of the investigated springs are presented inFig. 1. Sg. Besi is a town and suburb area, and theclimate is considered humid weather throughout theyear. The average daily temperature is between 21 oC
and 32oC. The area receives an annual rainfall of 750900 mm. The major water sources are streams, rivers
and groundwater. Spring water sampling points werespotted in the NDUM campus.
Sampling and sample analysis
A total of 16 water samples were collected fromthe spring water points. Sampling was undertaken
308

SEE-Mie, Japan, Nov.10-12, 2022

content of all inorganic and organic substancespresent in a liquid in molecular, ionized, or microgranular (colloidal sol) suspended form. TDS also
used as a parameter to evaluate the quality ofdrinking water.
(e) Dissolved oxygen
The amount of oxygen dissolved in water isreferred to as dissolved oxygen (DO). The
atmosphere and aquatic vegetation both provide
oxygen to water bodies. Running water, such as afast-moving stream, dissolves more oxygen thanstagnant water, such as that found in a pond orlake.

spring water and groundwater was around 30 to 300
mg/L and nearly the same reading. The mean TDS
was 206 mg/L with standard deviation of 10.8. These
values are acceptable based on recommended values
by WHO (2011) which is within 1000 mg/L and 500
mg/L for NDWQS (2000).
Similar trends of result were obtained by Hamzah
et al. (2013) but Razali et al (2017) recorded lower
concentration of TDS in ground water samples in
Selangor, Malaysia. Usually, EC and TDS are
directly related to each other. The more the numberof ions, the more will be the value of TDS andfurthermore will be the EC (Rusydi, 2018).

Table 1 The Method used for the analysis thedifferent parameters
Parameters

Unit

Reference Method
Of Analysis

Total Dissolved
mg/L

TDS Meter

pH

unit

pH meterTemperature°C

Solids (TDS)

Temperature
Conductivity

Conductivity

Fig. 2

S/m
Meter

Dissolved
mg/L

The results of pH values for spring water sampling
was in range of 6 to 6.4 as shown in Fig. 3. The
recommendation of drinking water pH range stated by
WHO (2011) is in between 6.5 and 8.5. The mean pH
was 6.3 with standard deviation of 0.6. Most of thedata are around the mean value. Overall, the samples
sites and controls were found to be acceptable. These
values aligned with the finding by Simon et al. (2019)
and Razali et al. (2017) for spring water flow fromfractures in granite rocks in Semenyih, Malaysia withpH range of 6.7. Hamzah et al. (2013) and Simon etal. (2019) reported that the pH of water sources in hot
spring around Selangor, Malaysia are characterized asalkaline and this might be due to geologicalcomposition of the region. Ngadiman et al. (2015)
tested a spring water from the hill of Ulu Yam also
shows the pH value for hill water is 6.8 and almost
neutral.
The temperature of spring water as shown in Fig.
4 were consistent with other types of water resourcesin UPNM campus with 25°C with standard deviationof 1.5. the error bar also show the result is significant.
The present study shows similar results on range oftemperature of spring water flow from fractures in
granite rocks near SILK Highway in Malaysia
reported in Razali et al. (2017). Hamzah et al. (2013)
and Simon et al. (2019) reported the high temperature
in hot spring water with temperature range between
36°C to 68°C. The difference in temperature may due
to the geothermal heating. The temperature values inthis study is within the normal temperature.

DO MeterOxygen (DO)RESULTS AND DISCUSSION
The water quality analysis of spring water wasdetermined. The summary of parameters measured
are presented in Table 2.
Table 2 Water quality of spring water in UPNM
Recommended
Parameters

Unit

Range

Mean

Std

WHO

NDWQS

Dev

(2017)(2000)

206

10.8

1000

500

6.3

0.6

Total
Dissolved

30mg/L

Solids

300

(TDS)
6.5pH

6-6.4

6.5-9.0
8.5

Temperature°C

Conductivity

µS/cm

22-27

25

1.5

-

-

52

5.8

400

1000

6.5

0.8

7

-

10100
Dissolved
Oxygen

mg/L

5-8.5

NDUM campus spring water TDS(DO)

The results of TDS for the spring water samples
shows in Fig. 2. The results reflected that the TDS for309

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 5 show the results of conductivity for thespring water in NDUM campus. The graph shows thevalue for the location fluctuate slightly throughout thetesting period. The conductivity values in all
sampling were in the range of 10 μS/m to 100 μS/m.
The highest conductivity recorded is 100 μS/m. On
the other hand, the lowest data recorded is 10 μS/m.
The low value of conductivity indicates a smaller
number of ions present in the water sample, making
it suitable to consume. The similar trend was found in
the work conducted by Razali et al. (2017). The
research conducted by Hamzah et al. (2013) shows anaverage results of 505.9 μS/m. According to Simon etal. (2019) the spring water has an average
conductivity value of 443 μS/m. The average value
for the conductivity for this spring water is within thelimit of NDWQS (2000) and WHO (2011).
Therefore, it is safe to be use for consumption.

Fig. 3Fig. 5

The graph (Fig. 6) shows the value for the springwater locations fluctuate slightly throughout thetesting period. The DO values in all sampling were in
the range of 5.00 mg/L to 8.50 mg/L. The highest
turbidity recorded is 8.50 mg/L. On the other hand,
the lowest data recorded is 5 mg/L. Therefore, thespring water for this source is safe for consumption as
the results the within limit set by WHO and NDWQS.
The DO value in the present study shows that it ishigher compared to values reported in Simon et al.
(2019). The turbidity of spring water flow from thespring water in Jordan by Al-Khashman shows thatthe DO value of 4.63 mg/L. A study on hot spring in
Selangor by Hamzah et al. (2013) shows a lower DO
value with an average of 3.38 mg/L.

NDUM campus spring water pH.

Fig. 6
Fig. 4

NDUM campus spring water Electricalconductivity (EC)NDUM campus spring water temperature

UPNM campus spring water DO

CONCLUSION AND RECOMMENDATION
The present study has been conducted todetermine the quality of spring water in NDUM
campus based on several parameters. The water
samples were found to be suitable for use were within
permissible limits except for pH were close to or
exceeded the permissible limit of Malaysia standards,
which indicates that requirement of treatment before
can be safely consumed. The outcome of this study
may contribute to propose the new way of monitoringwater quality in campus by using real-time system.
In the future, the biological and chemical testing310

SEE-Mie, Japan, Nov.10-12, 2022

should be conducted in order to fully assess thequality of the spring water to be used for drinking.
However, it is also important to investigate otherpotential water contamination such as microbial andradiological for longer period to assess the overallwater quality of NDUM.

Environment Programme and the World HealthOrganization, 1996
[10] Othman, M., Suif, Z., Jelani, J. Ahmad, N., Che
Osmi, S.K., M. Nadzri, M, N.
(2021a).
Performance of Pilot-scale Constructed Wetland
for Treating Stormwater. Jurnal Kejuruteraan SI
4(2) 2021: 141-145. UKM.
[11] Razali M. F., Roslan F., Ismal F. I. and Noor
W.S.A.W.M. Analisis kualiti air bawah Tanah di
Lebuhraya SILK Kajang Sungai Long, Hulu
Langat, Selangor. Undergraduate Research
Journal for Earth Sciences ISSN, 2017, 2600 –
8009.
[12] Engineering Services Division, Ministry of
Health Malaysia, National Standard for Drinking
Water
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Kementerian
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Malaysia, 2004.
[13] American Public Health Association (APHA),
Standard Methods for the Examination of Water
and Wastewater, 22nd edition, 2012.
[14] Ngadiman N., Kaamin M. and Hamid N.B.
Water Quality of Hills Water, Supply Water andRO Water Machine at Ulu Yam Selangor. IOP
Conf. Series: Materials Science and Engineering,
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[15] Zaini, H., Abd Rani, N.L., Saat, A. and Wood, A.
K. Determination of Hot Springs PhysicoChemical Water Quality Potentially Use For
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Sciences, 2013, Vol 17 No 3 : 436 – 444.
[16] Al-Khashman O.A., Ainawafleh H.M, Jrai A.A.
and Al-Muhtaseb A.A. Monitoring andAssessing of Spring Water Quality inSouthwestern Basin of Jordan. Open Journal ofModern Hydrology, 2017, Vol 7, 331-349.
[17] Hashim, F.R., Nagappan, P., Ishak, M.T., Joini,
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[19] Aaruththiran M., Yujia Z. and Bagherian M. A.
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[20] Munikanan, V, Mon, A.A., M. Sahkrin, N.N.S,
Md Nor, M.A., Yahya, M.A. Yusof, M.A. andE.Jing, F.L. (2019). Alternative Water Resourcesin UPNM. International Journal of Recent
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2277-3878, Vol. 7, Issue-5S4.

ACKNOWLEDGEMENT
The authors wish to thank the Department of Civil
Engineering, Faculty of Engineering and Researchand Innovation Centre (PPPI) at National Defence
University of Malaysia especially for their support.
This work is also supported by National Defence
University of Malaysia under Short Term Grant
Project entitles “Sustainable Spring Water Treatment
System for Small Community” with grant number
UPNM/202/GPJP/PK/1. The appreciation is also
extended to my beloved parents, family, lecturers andfellow colleagues for their continuous help andsupport.
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[21] Othman, M., Ahmad, N., Suif, Z., Jelani, J.
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312

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

POTENTIAL FOR DESCENDING METEORIC WATER RECHARGE IN
HYDROTHERMAL SYSTEMS AS A PATHWAY FOR CARBONDIOXIDE SEQUESTRATION

1John Victor Smith1
Faculty of Engineering, RMIT University, Australia

ABSTRACTThe disposal of carbon dioxide (CO2) by sequestration in geological zones below the ground surface has been
identified as an important potential contributor to maintaining climate stability. Most attention has been on
reservoirs which are depleted in oil or gas or in saline aquifers more generally. Pumping carbon dioxide into basalt
host rocks to promote carbonate mineralization is also being undertaken. In this paper another environment inwhich CO2 is naturally introduced into geological materials and stored below ground is reviewed. The
environment is the natural hydrothermal systems which are commonly found in magmatically active locations. In
these areas it is common for the cool near-surface (meteoric) water to descend as a replacement (recharge) of thewarm or hot magmatic water in the hydrothermal-magmatic system. The role of CO2 in such modern and ancienthydrothermal systems is reviewed. Examples of hydrothermal systems, particularly in the western Pacific, show
the common occurrence of naturally descending meteoric water recharge in hydrothermal systems. It is also notedthat the descending waters are commonly enriched in CO2. The descending CO2 can react with existing rocks andminerals to form carbonates of calcium and other cations. Studies of modern and ancient hydrothermal systems
show the ways in which formation of carbonate can occur. It is proposed that introduction of CO 2 into naturally
descending meteoric water recharge in hydrothermal systems may be a mechanism for CO2 sequestration bymineral trapping. Further investigation of this process and its potential is proposed.
Keywords: CO2 Sequestration, Hydrothermal Systems, Meteoric Water, Recharge

INTRODUCTION

history including the formation of greenstone belts.
Such belts, surrounded by extensive granite, may be
300 m to 12 km wide and 100 to 700 km long and thepresence of carbonate minerals in greenstone belts iswell known [6].
In this paper it is proposed that introduction of
CO2 into naturally descending meteoric water, which
commonly recharges hydrothermal systems, may be
a mechanism for CO2 sequestration by mineraltrapping. Further investigation of this process and its
potential is proposed.

One of the responses to an increase in carbon
dioxide (CO2) in the atmosphere is to sore it
underground in a process referred to as geologicalsequestration [1]. The various ways this can beachieved are being studied and implemented in many
countries [2]. Understanding the natural cycle of CO2
in the Earth may provide additional opportunities forgeological sequestration.
Water plays an important role in the transfer ofheat and matter in geothermal systems [3]. CO2 canbecome fixed within carbonate minerals, for example
calcite,dolomiteandmagnesitethroughhydrothermal alteration, which is a common
occurrence in many parts of the Earth’s crust [4].
Water also plays a significant role in the transfer ofpressure and the initiation of movement on brittle
structures [5]. In this way water can contribute to afault-valve cycle and once fluid pressure exceeds thelithostatic load, accumulating shear stresses trigger
failure on faults. This is supported by observed
relationships of faults and other evidence of fluidpressure cycling within gold veins and other metallic
deposits [5].
The process of hydrothermal alteration whichtransforms large volumes of rock into different
mineral assemblages has occurred through geological

FORMATION OF CARBONATE MINERALS
Geothermal systems such as Wairakei in New
Zealand have been observed to form deposits ofcalcite mineral scale in wells [7]. Some other wells in
geothermal systems produce no calcite scale and are
inferred to be a result of waters entering the wells
being undersaturated in CO2 or suitable cations. It isinferred that, during recharge of shallow water deeper
into the geothermal reservoir, an insufficient quantityof CO2 was transported into the system to saturate thewater with calcite. [3].
Carbonate minerals are commonly found within
the rocks affected by hydrothermal systems. Theseminerals are found over a wide range of pH andtemperature conditions. Carbonates are also found in
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SEE-Mie, Japan, Nov.10-12, 2022

association with a wide range of other minerals(Table 1). The types of carbonate minerals, as
determined by their cations, can also vary withincreasing fluid pH. This effect has been observed aszoning of carbonate minerals as has been observed insome hydrothermal systems [8]. Based on theseobservations, it has been inferred that Fe, Mn and Mg
become less mobile as pH increases toward neutral.
The solubility of carbonate minerals in an aqueous
solution at pH 4-8 can be represented by Eq. (1):

METEORIC WATER RECHARGE IN
HYDROTHERMAL SYSTEMS

Table 1 Associations of carbonate and clay minerals[8]
Carbonatecations
Fe, MnCa, Mn,Mg, FeCa, MgMineralnames
Siderite,rhodocrosite
Rhodocrosite,ankerite,kutnahorite,
dolomite
Dolomite,
calciteAssociatedminerals
Kaolin,illiteIllitic andchloritic
clays

pH
conditions
Low

Chlorite,
calcsilicates

Neutral

MCO3+CO2+H2O=M2++2HCO3-

Mod.

(1)

Geothermal systems can be characterizedaccording to the chemistry of the water emanatingfrom a magma intrusion. Geothermal systems canalso be characterized by the depth of the magma
intrusion and therefore the distance from the heatsource to the geothermal activity observed near thesurface. The class of geothermal systems known as‘epithermal’ refer to the significant distance that canexist between the heat source (magma intrusion) andthe ground surface. The epithermal system refers to
the areas in which near surface waters circulate
through the ground such that the chemistry of thewaters is a mixture of juvenile magmatic water andgroundwater known as ‘meteoric’ water. In theseepithermal systems it is common for CO2-rich water
to descend from above an intrusion and mix withmagmatic fluids in the conduits [8]. The conduits of
fluid flow may be permeable rocks or structures suchas faults. The magmatic fluids typically containdissolved reactive gases. The chemistry of the fluids
can be affected by interaction with rock and dilution
by the circulating meteoric waters. The meteoric
waters typically capture a significant amount of themagmatic gases, including CO2, as the mixing occurs[8].
Mineral Deposition

Where M represents the cations: Ca, Mn, Mg, Fe.

The cool, descending, low pH, CO2-rich meteoric
water mixes with hot, silica-saturated, deep magmatic
fluids resulting in deposition of carbonates in
response
toincreasing
temperatures[8].
Hydrothermal systems are commonly located in
tectonically active areas such that major fracturezones and faults can be periodically reopened by fluidpressure permitting both the ascent of magmatic
fluids and the descent of meteoric water toprogressively deeper levels [5].
Where mineral precipitation occurs in permeable
rocks, the rock is described as ‘altered’. Where
mineral precipitation occurs in fractures the rocks aredescribed as ‘veined’. The overall effect of theseprocesses is to seal the most permeable zones by
precipitation of minerals including carbonates.
A review of geothermal systems in the Philippines
showed that cool, low pH, CO2-rich water has been
detected as deep as 2000 m [8]. Evidence that these
CO2-rich waters have mixed with warmer magmaticwaters include the precipitation of carbonates with arange of cations including dolomite (Ca, Mgcarbonate), siderite (Fe-carbonate) and ankerite (Mg,Ca, Fe-carbonate).
Observations of the occurrence of various
carbonate minerals at depths of 600-1200m in the
Broadlands hydrothermal system in New Zealand arealso considered to be indicative of the drawing down

At pH less than 4 carbonates are dissolved. At
temperatures less than 100oC and neutral conditions(pH 6-7) bicarbonate dominates over CO2. The
controls on carbonate solubility under hightemperature saline conditions is the subject of current
research.
Carbonate minerals are present in all levels inhydrothermal systems from low temperature surficial
conditions to deep magmatic conditions. The
dominant control on carbonate deposition isincreasing temperature. In comparison, dilution andpressure drop are secondary factors in affecting
carbonate deposition. Therefore, the heating ofdescending CO2-rich waters leads to carbonate
mineral deposition [8].
If a fluid with significant concentrations of
dissolved CO2 undergoes boiling, carbonate
deposition can also occur. The most common causeof boiling in nature is the reduction in pressure rather
than an increase in temperature. Such a reduction inpressure can occur gradually by ascending fluids
having decreased overburden or rapidly by faulting orlarge-scale landslides [8].
A comprehensive review of hydrothermal systems
in the southwest Pacific rim [8] showed that many ofthese systems incorporate meteoric water recharge.

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SEE-Mie, Japan, Nov.10-12, 2022

of CO2-rich waters into a saline aquifer dominated bymagmatic water [8]. At Rotakawa in New Zealand,
the occurrence of Mn-carbonates has been inferred tobe the result of deep circulation of CO2-rich surficial
waters [8].
In summary, calcium carbonate (calcite) can bedeposited from either magmatic or meteoric waters.
However, magmatic fluids are typically depleted inmagnesium and therefore the presence of Mgcarbonates (dolomite, ankerite) at deep levels in
active geothermal systems is inferred to be related tothe incursion of CO2-rich meteoric waters into deeper
parts of magmatic hydrothermal systems [8].

water.
An example of descent of water toward a zone ofconvective hydrothermal alteration is the Tongonansystem also located in northern Leyte, Philippines. In
that system the magma is within 1 km below surface(Fig. 2). There is deep meteoric water recharge frommultiple kilometers around the magma intrusion toaround 2 km depth in the system. Concurrently, inshallower parts of the system, meteoric water
descends hundreds of meters along major faults.
An example of near-surface water being drawn
down to deeper levels is the Palinpinon geothermal
field in southern Negros, Philippines. This final stageof geothermal waning occurs as the pluton cools. In
this stage cool dilute meteoric waters and shallow,
low pH and CO2-rich waters descend to considerable
depth within the reservoir of saline groundwater. The
Palinpinon geothermal field and surrounding
geothermal activity is driven by the intrusion andcooling of a large monzonite intrusion [8].

Evolution of Hydrothermal Systems
Hydrothermal systems pass through a series ofstages, principally driven by the cooling of the
intrusive pluton. According to [8] the stages areevidenced by the following features: 1) contact
metamorphism, 2) release of a magmatic volatile
plume, 3) convective hydrothermal alteration and 4)
draw down of surficial waters.
Meteoric waters can be involved in each stage but
become more dominant as the system evolves. In theearlier stages the descent of surface water occurs
farther away from the thermal center and in the final
stage the descent of water can occur directly on top of
the waning thermal system [8].
This evolutionary model of hydrothermal systems
provides a framework for studying and understanding
individual examples of hydrothermal systems. The
evolutionary model applies to active hydrothermal
and geothermal systems and ancient systems
preserved in rock. Both active and ancient systems
are of great interest as they are a common host to theformation of metallic mineral deposits. Many of theancient systems can be hosted within activehydrothermal areas. For example, a magmatic
intrusion which has become fully cooled will besurrounded by its fossil hydrothermal system. If
further magmatic intrusions occur, complex
overprinting of the rock alteration and mineralogy
will occur.
A summary of active and ancient hydrothermal
systems in which evidence of descending meteoric
waters has been observed is provided in Table 2.

Table 2 Examples active and fossil hydrothermal
systems with descending CO2-rich/meteoric
water [8]Country
Philippines, northern
Leyte
Philippines, southern
NegrosPhilippines, southern
Luzon
Philippines, eastern
Mindanao
Sumatra, Indonesia
PNG, Lihir Island
Australia, Queensland
Indonesia, Kalimantan
PNG
PNG
PNG, Woodlark Island
PNG
PNG
Solomon Islands

SystemAlto Peak,Tongonan
Palinpinon

A/FA

BaconManito
Amacan

A

A

A

Miwah
A
LadolamA
KidstonF
KelianF
PorgeraF
MorobeF
BusaiF
ManiapeF
Mt Kare
F
Gold
F
Ridge
New Zealand,
GoldenF
Coromandel
Cross
Japan, Kyushu
HishikariF
A=active geothermal system, F= fossil hydrothermal
systemComposite Volcanic Terrains
An example of descent of water toward amagmatic volatile plume is the Alto Peak system innorthern Leyte, Philippines. In that system themagma is over 2 km below surface (Fig. 1). There is
deep meteoric water recharge from multiple
kilometers around the magma intrusion to around 2
km depth in the system. Concurrently, in shallower
parts of the system meteoric water descends hundredsof meters to form a wide-spread zone of CO2-rich

One of the characteristics of a waning geothermal
field is that CO2-rich water can be descending directlyat the center of the field as is occurring in the fault
zones that mark the focus of the Palinpinon
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SEE-Mie, Japan, Nov.10-12, 2022

Fig. 1 Alto Peak (Philippines) hydrological model [8]. Descending meteoric waters shown in blue arrows.
CO2-rich waters shown in blue.

Fig. 2 Tongonan (Philippines) hydrological model [8]. Descending meteoric waters shown in blue arrows.

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SEE-Mie, Japan, Nov.10-12, 2022

Fig. 3

Bacon-Minato (Philippines) hydrological model [8]. Descending meteoric waters shown in blue arrows.

geothermal field. A pluton emplaced during the
Miocene initiated the system and progressively
cooled.
Smaller and younger intrusions haveoccurred on tectonic structures. These younger
intrusions and deeper extensions of them, provide thecurrent heat source for the geothermal field.
In the Palinpinon geothermal field, meteoric
waters also move laterally through permeable strata
toward the center of the geothermal field. According
to [8] the Palinpinon geothermal field is in an earlystage of waning or thermal collapse such that cool
CO2-rich meteoric waters are descending in response
to pressure draw down. The dilute nature of the fluids
in the central part of the system show that themeteoric waters are dominant over the residual
presence of magmatic water.
The Bacon-Manito geothermal field in southern
Luzon, Philippines, has a complex volcanic andintrusive geological history which has beeninterpreted as a waning system (Fig. 3). It has been
observed that CO2-rich waters move down structuresand caldera margins to depths exceeding 1,500 m.
This descent of cool waters into hotter environments
has resulted in widespread deposition of carbonatesand other minerals. As a consequence of mineral
precipitation, the upper 1000 m is relatively low inpermeability [8].

cordillera are also associated with hydrothermal
activity. In the Philippines, the northern Luzon andeastern Mindanao regions can be considered to becordillera-style hydrothermal systems. In these areas
upflow of magmatic water can be restricted to verticalchannels. Mixing of magmatic fluid and CO2-richsurficial water occurs near the surface.
An example of a Cordillera-style geothermal
system is the Amacan geothermal system eastern
Mindanao, Philippines. Abundant bicarbonate
springs with as much as 4 wt% CO2 occur in the area.
This is inferred to be the result of meteoric waters
intercepting CO2 from the magmatic source andredistributing it within the geothermal system [8].
FOSSIL HYDROTHERMAL SYSTEMSOne of the most significant sources of information
on hydrothermal systems is from those systems wheremetals have been deposited. Many of these systems
are extinct or nearly extinct so they can be considered
to be fossil hydrothermal systems.
Meteoric water played a significant role in manysuch hydrothermal systems. Of the mineral depositforming processes the epithermal or more specifically,
the low sulfidation porphyry system is one
environment in which meteoric water interaction ismost crucial.
An example of such a system is the Ladolam gold
mine on Lihir Island, Papua New Guinea. The gold
mineralization is understood to have formed in an

Cordillera-style Hydrothermal Systems
Volcanic mountain chains, commonly called
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SEE-Mie, Japan, Nov.10-12, 2022

earlier phase of the evolving geothermal field. The
current geothermal system is inferred to be in awaning stage. Currently, low pH, CO2-rich waters arebeing drawn down into the geothermal system. Thesewaters are understood to be groundwaters that haveabsorbed gases from the earlier magmatic systems.
The temperature and pH of the water near the surface
allowed dissolution of carbonate and later redeposition of the carbonate deeper in the system as
the descending water was heated [8].
The Kidston gold mine in Queensland Australia ishosted by a Permo-Carboniferous age volcanic
breccia pipe. The sequence and distribution ofminerals shows that descending cool, low pH, CO2rich waters descended into the hydrothermal systemand deposited carbonate minerals [8].
There is an entire class of mineral deposit known
as carbonate-base metal-gold systems. These systems
have characteristics similar to other hydrothermal
systems including the importance of the mixing ofrising magmatic water with meteoric CO2-rich water.
The fluid flow model for these deposits involves
hot mineralized fluids which evolve from coolingintrusions. The fluids rise along permeable zones
which may be fracture systems. At depth, these fluids
mix with circulating meteoric waters. Gases evolvefrom these upwelling fluids by boiling and vapor loss
and are absorbed by groundwater near the surface toform CO2-rich waters. Cooling of the intrusions leads
to draw down of these fluids deep into thehydrothermal system. Carbonate minerals are
precipitated as a result.
An example of these processes is the Kelian mine,
Kalimantan, Indonesia. In this system carbonate
minerals are zoned with depth. Fe and Mn carbonates
are encountered at shallow depth whereas Mg and Ca
carbonates are found deeper in the deposit [8].
The Porgera deposit in Papua New Guinea is alsoclassified as a carbonate-base metal-gold deposit.
Carbonate minerals are zoned in a similar manner tothe Kelian deposit. Carbon and oxygen isotope datafrom carbonates at Porgera support the model ofprogressive mixing of magmatic and meteoric waters
to produce the observed zonation of carbonate
minerals [9].

are typically not in a critical state and water can bepresent with the gas.
It is proposed in this paper that the existing
downward flow of meteoric water in naturalgeothermal systems introduces the possibility ofusing a syphon system to introduce CO2 to the ground.
This means that highly pressurized pumping may not
be needed for the gas and/or gasified water to be
introduced to the ground. It is anticipated that a wellwould be required to ensure that the gas becomes
entrained in a downward flow. The depth of the wellwould depend on the nature of the natural flows.
It is anticipated that meteoric waters that are notcurrently saturated in CO2 would be the mostfavorable for disposal of CO2. Identification ofsuitable sites for CO2 disposal would require a
detailed understanding of the geothermal system.
This assessment would include assessment of thepresence of rock with sufficient cation potential forthe formation of carbonate minerals in combination
with the introduced CO2.
Exploration of geothermal systems is a welldeveloped field of research including the use ofgeochemistry [12] and geophysics [13]. The concept
of using existing downward flowing water tosequester CO2 through mineralization has not beenpreviously considered and may have significant
barriers and limitations. It is hoped that this review
may prompt further investigation into this possibility.
CONCLUSIONS
Descending water with CO2 occurs naturally andis common in areas of geothermal activity. It is
known that carbonate minerals form abundantly inmany of these systems.
It is proposed that active geothermal systems inwhich descending waters are not saturated in CO2
could accommodate the introduction of CO2 for the
purpose of reducing atmospheric carbon. Because
these are naturally down-flowing waters there ispotential to use the syphon effect to draw water
enriched in CO2 into the descending flow without therequirement for highly pressurized pumping.
ACKNOWLEDGMENTSDISPOSAL OF CO2
Discussions on carbon sequestration withcolleagues at RMIT University and CMW
Geosciences are acknowledged.

It is known that geothermal systems can undergo
steam eruptions due to changes in pressure [10-11].
Therefore, any ground engineering activities in ageothermal system must be conducted with carefulrisk assessment being applied.
Disposal of CO2 usually involves pumping water
through wells. In disposal into oil fields and saline
reservoirs the depths of CO2 introduction are very
deep and the gas is in a supercritical state and dry ofwater. Shallower injection of CO2 gas can be used
where mineral carbonation is the aim. These gases

REFERENCES[1] IPCC, 2022: Climate Change 2022: Impacts,
Adaptation, and Vulnerability. Contribution ofWorking Group II to the Sixth Assessment
Report of the Intergovernmental Panel on
Climate Change. Cambridge University Press.

318

SEE-Mie, Japan, Nov.10-12, 2022

[9] Richards JP, Kerrich R. The Porgera gold mine,
Papua New Guinea; magmatic hydrothermal toepithermal evolution of an alkalic-type precious
metal deposit. Economic Geology. 1993, Vol. 88,
Issue 5, pp. 1017-52.
[10] Hedenquist JW, Henley RW. Hydrothermal
eruptions in the Waiotapu geothermal system,
New Zealand; their origin, associated breccias,
and relation to precious metal mineralization.
Economic geology. 1985, Vol. 80, Issue 6, pp.
1640-68.
[11] Global Volcanism Program, Report on Yakedake(Japan) (Wunderman, R., ed.). Bulletin of the
Global Volcanism Network, 20:2. Smithsonian
Institution. 1995. https://doi.org/10.5479/si. GVP.
BGVN199502-283070.
[12] Ii, H., Kanbara, H., Kawabata, Y., Geothermaland Hot Spring Water Origin Determination
Using Oxygen and Hydrogen Stable Isotope in
The Toyohirakawa Catchment, Hokkaido, Japan.
International Journal of GEOMATE, 2017, Vol.
13, Issue 37, pp. 127-132.
[13] Rokhmatuloh, S., Sobirin, R., Suhanto, E., The
Effect of Gravity Measurement Distribution
Points on Interpretation of Gravity Data in the
Gunung Endut Geothermal Prospect Area,
Indonesia International Journal of GEOMATE,
2018 Vol.14, Issue 41, pp.60-67.

[2] Kelemen P., Benson S.M., Pilorgé H., Psarras P.,
and Wilcox J., An Overview of the Status andChallenges of CO2 Storage in Minerals andGeological Formations. Frontiers in Climate, Vol.
15, 2019, pp. 1:9.
[3] Arnórsson S. Deposition of calcium carbonate
minerals from geothermal waters—theoreticalconsiderations. Geothermics. 1989 Vol. 18, Issue
1-2, pp. 33-9.
[4] Gorczyk W, Gonzalez CM, Hobbs B. Carbon
dioxide as a proxy for orogenic gold source. Ore
Geology Reviews. 2020, Vol. 1, Issue 127, pp.
103-29.
[5] Sibson RH, Robert F, Poulsen KH. High-angle
reverse faults, fluid-pressure cycling, andmesothermal gold-quartz deposits. Geology. 1988,
Vol. 16, Issue 6, pp. 551-5.
[6] Elmer FL, White RW, Powell R. Devolatilizationof metabasic rocks during greenschist–
amphibolite facies metamorphism. Journal of
Metamorphic Geology. 2006, Vol. 24, Issue 6, pp.
497-513.
[7] Mahon WA. Chemistry in the exploration andexploitationofhydrothermal
systems.
Geothermics. 1970, Vol. 2, Issue 13, pp. 10-22.
[8] Corbett, G.J., and Leach, T.M. Southwest Pacific
Rim gold-copper systems: structure, alteration,and mineralization. Vol. 6. Colorado: Society of
Economic Geologists, 1998.

319

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CU,ZN,FE AND MN CONCENTRATIONS OF SOME GASTROPODS IN
THE WAKAGAWA ESTUARY TIDAL FLAT
Kazuko Kubo1 and Hiroyuki Ii2
1

2

641-0033, Imabuku, Wakayama City
Faculty of Systems Engineering, Wakayama University, Japan

ABSTRACT
Mudflat is an important place for changing organic material into inorganic compound. Benthos in mudflat playa big role of decomposing organic material. In the past, factory wastewater such as dyes and the chemical industries
flowed into the Wakagawa River, which is located in the northern part of Wakayama Prefecture, and the estuary
was severely polluted. After that, the inflow of contaminated water was restricted by various measures, and theorganic pollution of the tidal flats gradually decreased. However, it is thought that various metallic elements remainin the tidal flats and affect benthos. Some of them, especially detritus-feeder, might accumulate metals and could
be index organism of environmental contamination. In this study, Cu, Zn, Fe, Mn concentrations of some snails
sampled on January-September 2016 were measured using ICP-AES. No clear difference was found between thecollection points in this tidal flat, and the accumulated elements differed depending on the species. The Zn
concentration was higher in the detritus feeder than in the algae feeder.
Keywords: Snails, Batillaria, Pirenella, Clithon, Heavy metals

INTRODUCTIONSTUDY AREA

Wakagawa estuary is located in the northern partof Wakayama prefecture. The tidal flat area is about
35 hectares. It is thought that more than 300 speciesof benthos and fish inhabit there, and it has been
selected as one of the "500 Important Wetlands inJapan" by the Ministry of the Environment (Ministryof the Environment Nature Conservation Bureau2001)[1]. However, during the period of higheconomic growth, there was terrible contamination
due to wastewater from factories (leather, dyes,
chemical industries, etc.) and domestic wastewater.
Since then, the environment in the estuary has
improved considerably due to drainage regulationsand various measures[2]-[4]. However, it is presumed
that the factory effluent at that time contained various
metals, and most of these may remain on the tidal flatsin some way, affecting benthic organisms.
Many papers have attempted to evaluate metal
pollution in environmental water and soil using
seaweeds, river insects, and river plants[6-10].
However, there are not many surveys of metal
pollution using various benthic animals on tidal flats.
In this study, the metal concentrations of somegastropods (snails) of the Wakagawa estuary tidal flat
were measured. The gastropods investigated weremainly three species of genus Batillaria and Pirenella
nipponica, which are detritus feeders, and Nerita
japonica and Clithon oualaniensis, which are algae
feeders.

Wakagawa Estuary Tidal Flat is located in thenorthern part of Wakayama Prefecture. Fig. 1 shows
the location of the Wakagawa estuary on a map, andFig. 2 shows the sampling points. Fig. 2 is a part ofthe photo that seems to have been taken at low tide.
At high tide, all sampling points sink into the sea,leaving small islets with a plus mark and bridges. The
area around the islet is sandy, and the mud increases
as it gets closer to the water's edge. The front andsouth sides of the small islet are relatively sandy, andthe wide area on the north side is relatively muddy.
Site E is a little low across the channel from Site Front,
it’s difficult to walk there unless it is at the lowest tide.
Sampling was mainly performed at Site Front, andwas also performed at Site S, N, E as a reference.

(Map form Geospatial Information Authority of Japan)

Fig. 1 Study area320

SEE-Mie, Japan, Nov.10-12, 2022

Since the number of samples is small, statisticaltests have not been performed.
N

300

Front
Site E
Site N

250

Cu ㎍/g

S
E

150
100
50
0
1
2
2016 Jan.

Fig. 2 Sampling site

3
4
5
6
Mar.
Apr.
May

7

8

9 10
Sep.

Fig.3-b Cu concentrations of Batillaria mulutiformis

METHOD300

The snails were collected at Site Front on January
12, 2016, May 24, and September 18, 2016 at low tide.
On March 22nd, in addition to Site Front, Site N andS were also used as references. On April 11th, only
Site E was used for collection. After washing off themud, the snails brought back were fasted in 50%
artificial seawater for about a week to expel thecontents of the digestive tract. Then, the whole snail
was ultrasonically cleaned, and then the soft bodies
was carefully taken out and washed with Millipore
water. After sufficiently drying them in a dryer at 60 °C, they were weighed and dissolved withconcentrated nitric acid. After filtering with the
0.45μm membrane filter, the concentrations of Cu, Zn,
Fe, and Mn were measured using ICP-OES(AMETEK Inc. SPECTRO ARCOS). For somesamples, the previous model Seiko Instruments Inc.
SPS1700HVR was used.

Front
Site E
Site N
Site S

Cu ㎍/g

250
200
150
100
50
0
1
2 Mar.
3 Apr.
4 May
5
62016 Jan.

7

8

9 10
Sep.

Fig.3-c Cu concentrations of Batillaria zonalis
120

Front
Site E
Site N
Site S

Cu ㎍/g

100
80
60
40
20

RESULTS AND DISCUSSION

0

20162

Figure3-(a) to (e) show the distribution of Cu
concentrations of Batillaria cumingii, B.mulutiformis,
B.zonalis, Pirenella nipponica, and Clithon
oualaniensis resupectively. For the four species
except Batillaria cumingii, no significant differencein Cu concentration was observed depending on thecollection site and collection month. For B. cumingii,
the concentration at Site E seems to be slightly low(Fig. 1-a), but the difference between the mean values
is 57.8, which is smaller than the variation in themeasured values(Max.-Min.=66.0).

Cu ㎍/g-dry

200

300
250
200
150
100
50
0

3 Apr.
4 May
5
Mar.

6

7

8

9
10
Sep.

Cu ㎍/g-dry

Fig.3-d Cu concentrations of Pirenella nipponica
30
Front
25
Site E
20
15
10
5
0
2016
2
3 Apr.
4 May
5
6
7
8 Sep.
9 10
Fig.3-e Cu concentrations of Clithon oualaniensis
Figure 4 shows the Cu concentrations of all snails
investigated. Six species from Batillaria to Clithon
oualaniensis showed lower values than Littorinidae
and Rapana venosa measured for comparativereference. Among these 6 species, the genus
Batillaria tended to show higher values than
Pirenella nipponica and 2 species of family Neritidae,
Nerita japonica and Clithon oualaniensis. No

Front
Site E
2
2016

3
Mar.

4
Apr.

5
May

6

Fig.3-a Cu concentrations of Batillaria cumingii
321

SEE-Mie, Japan, Nov.10-12, 2022

significant difference was found among the three
species of the genus Batillaria. The Cu value of
Batillaria cumingi was about the same as that ofNakatsu tidal flat of [5] and slightly lower than thatof Banzu tidal flat (about 300 ㎍ / g). However, caremust be taken in the comparison, as they remove thestiff muscles of the foot and use only the internalorgans (they call it soft tissue) for measurement.

1200

Zn ㎍/g-dry

800
600
400
200

0
1
2 Mar.
3 Apr.
4 May
5
62016 Jan.

1200
1000

7

8

9 10
Sep.

Fig.5-c Zn concentrations of Batillaria zonalis

800

1000

400

800

Zn ㎍/g600

Rapana venosa

Nodilittorina radiata

Littoraria sinensis

Clithon oualaniensis

Nerita japonica

Pirenella nipponica

Batillaria cumingii

0

Batillaria zonalis

200

Batillaria multiformis

Cu μg/g dry weight

Front
Site E
Site N
Site S

1000

Front
Site E
Site N
Site S

600
400

200
0

20162

3
4 May
5
6
Mar.
Apr.

7

8

9
10
Sep.

Fig.5-d Zn concentrations of Pirenella nipponica

Fig. 4 Cu concentrations of all snails investigated300

Zn ㎍/g-dry

200
150
100

50
0
2016
2

Apr.
4 May
5

3

6

7

Sep.
9

8

10

Fig.5-e Zn concentrations of Clithon oualaniensis

1000

Front
Site E
Site N

1000
800
600

Fig. 6 Zn concentrations of all snails investigated

400
200
0
1
2
2016 Jan.

Rapana venosa0

Fig.5-a Zn concentrations of Batillaria cumingii
1200

200

Nodilittorina radiata

6

Littoraria sinensis

5
May

Clithon oualaniensis

4
Apr.

Nerita japonica

3
Mar.

400

Pirenella nipponica

2
2016

600

Batillaria zonalis

Front
Site E

100

Batillaria multiformis

200○ is over the upper
limit of measurement

800

Batillaria cumingii

3000

Zn ㎍/g-dry

Front
Site E250

Zn μg/g dry weightZn ㎍/g-dry

Figure5-(a) to (e) show the distribution of Zn
concentrations of Batillaria cumingii, B.mulutiformis,
B.zonalis, Pirenella nipponica, and Clithon
oualaniensis, resupectively. At the Site N, Some
individuals showed high values in B.mulutiformis,and B.zonalis, In Pirenella nipponica, the variation of
the value was very large at the Site N, and many ofthem showed higher values than the other sites, andthe highest value was 952 ㎍ / g. No difference wasfound between the E point and the Site Front in all
four species.
400

3
4
5
6
Mar.
Apr.
May

7

8

Figure 6 shows the Zn concentrations of all snails
investigated. The Zn value of Batillaria cumingii wasabout the same as or slightly higher than that ofNakatsu and Banzu tidal flat of [5]. Several
individuals of Batillaria mulutiformis, B.zonalis and

9 10
Sep.

Fig.5-b Zn concentrations of Batillaria mulutiformis

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SEE-Mie, Japan, Nov.10-12, 2022

Pirenella nipponica
concentrations.

showed

very

high

Zn

3000
Front
Site E
Site N
Site S2500

Fe ㎍/gFigure7-(a) to (e) show the distribution of Feconcentrations of Batillaria cumingii, B.mulutiformis,
B.zonalis, Pirenella nipponica, and Clithon
oualaniensis resupectively. No significant differencein Fe concentration was observed depending on thesite. Some individual of B.zonalis showed rather highvalues. At Site N, one individual of Pirenella
nipponica showed extremely high value.

2000
1500
1000
500

0

20162

3 Apr.
4 May
5
Mar.

6

7

8

9
10
Sep.

Fig.7-d Fe concentrations of Pirenella nipponica
400

Fe ㎍/g-dry

200
100

Front
Site E

800

600
400
200

0
5May

6

0
2016
2

Fig.7-a Fe concentrations of Batillaria cumingi

100

8

9 10
Sep.

Fig.7-b Fe concentrations of Batillaria mulutiformis

Fe ㎍/g-dry

1200

1000
800

600

Front
Site E
Site N
Site S2500

Fe μg/g dry weight

1400

400

200
0
7

8

9 10
Sep.

2000
1500
1000
500
0

Batillaria cumingii

12 Mar.
3 Apr.
45
62016 Jan.
May

10

Fig.7-c Fe concentrations of Batillaria zonalis

Rapana venosa

7

Nodilittorina radiata

3
4
5
6
Mar.
Apr.
May

Sep.
9

8

Figure 8 shows the Fe concentrations of all snails
investigated. Some individuals of Batillaria zonails,
Pirenella nipponica and Clithon oualaniensis
showed very high Fe concentrations. Especially,one
individual of Pirenella nipponica
showedextremely high value. These three species are Near
Threatened Species or Endangered Species II.
Batillaria multiformis is also Near Threatened
Species, but it showed similar concentrations to thecommon species Batillaria cumingii. None of thereference species Littorinidae and Rapana venosa,
showed high concentrations. For Fe, no clear
relationship between concentrations and eating habits
was found.

200

0
1
2
2016 Jan.

7

Littoraria sinensis

Fe ㎍/g-dry

300

6

Fig.7-e Fe concentrations of Clithon oualaniensis

Front
Site E
Site N

400

Apr.
4 May
5

Clithon oualaniensis

500

3

Nerita japonica

4
Apr.

Pirenella nipponica

3
Mar.

Batillaria zonalis

2
2016

Batillaria multiformis

Fe ㎍/g-dry

1000

Front
Site E300

Fig. 8 Fe concentrations of all snails investigatedFigure 9-(a) to (e) show the distribution of Mn
323

SEE-Mie, Japan, Nov.10-12, 2022

concentrations of Batillaria cumingii, B.mulutiformis,
B.zonalis, Pirenella nipponica, and Clithon
oualaniensis resupectively. There was no clear
difference between the Sites in any species except
Batillaria cumingi. In this species, Site E showed aslightly higher concentration than Site Front, but thedifference was less than 250 ㎍, which is not large
compared to the variation in values in other species.

600

Front
Site EMn ㎍/g-dry

500

400
300
200
100

0
2016
2

3

200

7

8

Sep.
9

10

1000

400

200

Batillaria cumingii

0

Front
Site E
Site N

150
100

Fig. 10 Mn concentrations of all snails investigated

50

0
1
2
2016 Jan.

Rapana venosa

200

Nodilittorina radiata

Fig.9-a Mn concentrations of Batillaria cumingi

600

Littoraria sinensis

6

Clithon oualaniensis

5

May

Nerita japonica

4

Apr.

Pirenella nipponica

3

Mar.

Batillaria zonalis

2800

Batillaria multiformis

100
2016

Mn ㎍/g-dry

6

1200

0

3
4
5
6
Mar.
Apr.
May

7

8

Figure 10 shows the Mn concentrations of all snails
investigated. The genus Batillaria, Pirenella
nipponica, and family Neritidae tended to show
higher Mn concentrations than the reference species
Littorinidae and Rapana venosa. In particular, several
individuals of Batillaria zonails and Pirenella
nipponica, and one individual of Clithon oualaniensis
showed very high Mn concentrations. As with Fe, noclear relationship between concentrations of Mn andeating habits was found.

9 10
Sep.

Fig.9-b Mn concentrations of Batillaria mulutiformis
1200

Front
Site E
Site N
Site S

1000

Mn ㎍/g-dry

Apr.
4 May
5

Fig.9-e Mn concentrations of Clithon oualaniensis

Front
Site E300

Mn μg/g dry weight

Mn ㎍/g-dry

400

800
600
400
200

CONCLUSIONS

0
1
2
2016 Jan.

3
4 May
5
6
Mar.Apr

7

8

9 10
Sep.

Regarding the Cu, Fe, Mn concentrations of snails,
no clear difference was found between the sites in the
tidal flats at the mouth of the Wakagawa River.
The Cu concentration of the three species of thegenus Batillalia did not differ greatly from the values
reported by [5] (about 300 ㎍/g). Pirenella nipponica,
which also detritus feeder, showed lower values (lessthan 100 ㎍/g ) and was similar to algae feeder Nerita
japonica.The genus Batillaria may have somecharacteristics regarding the accumulation of Cu.
Contrary to the concentration distribution of Cu,
the reference species Littorinidae and Rapana venosashowed lower concentrations in Fe and Mn. Amongthe genus Batillalia, some individuals of B.zonalis
showed high concentrations of Fe and Mn. Pirenella
nipponica also showed the same tendency as

Fig.9-c Mn concentrations of Batillaria zonalis

Mn ㎍/g

1000

800
600

Front
Site E
Site N
Site S

400
200

0
2
3
4
5
6
2016
Mar.
Apr.
May

7

8

9
10
Sep.

Fig.9-d Mn concentrations of Pirenella nipponica
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SEE-Mie, Japan, Nov.10-12, 2022

B.zonalis. However, the relationship between theconcentrations and the species rarity, relatives or
feeding habits could not be seen.
The Zn concentrations of Batillaria cumingii(mean 201 ㎍/g) were similar to or slightly higher
than those of the same species in Nakatsu and Banshu
tidal flats [5]. Compared to these values, very high Zn
concentrations were shown by several individuals of
Pirenella nipponica, Batillaria mulutiformis andB.zonalis. Especially high values were found in Site
N, where is partially surrounded by land, and thewater flow is poor compared to other sites. Therefore,
when the pollution was severe, the area just below thesurface of the mud flat at this site was in an anaerobic
state, and even a little digging of the mud smelled likehydrogen sulfide. Currently, there is almost no suchbad odor, but there are many muddy places.
Regarding the Zn concentration, the variability wasmuch larger in the detritus feeders than in the algae
feeders, and many individuals showed extremely highvalues. From these results, it is possible that there ispartial Zn contamination of the mud in places wherewater and mud tend to stay in the Wakaura tidal flat.
On the other hand, among the detritus feeders, only
Batillaria cumingii didn’t show an extremely highconcentration. Batillaria cumingii thrives on tidal
flats across the country, even where other species of
the genus Batillaria are declining due toenvironmental deterioration. It is said that thisspecies is resistant to environmental pollution
because it has direct development and does not havea floating larval stage. Zn is an essential element forliving organisms, but overdose shows toxicity toliving organisms. They may have some mechanism toprevent excess Zn from accumulating in the body.

[2] Kinki Regional Development Bureau, Ministry ofLand, Infrastructure, Transport and Tourism.
History of environmental maintenance.
[3] Wakayama River National Highway Office
About efforts to improve the water quality of the
Daimon River by introducing environmental
water[4] Wakayama Prefectural Land Development
Department. Removal of Wakagawa "temporary
weir" and construction of rubble revetment.
[5] Akari F.,Motoo U.,Kunihiro O.,Takaaki S.,An
Assesment of the Batillaria Snails,Batillaria
cumingii, as an Indicator of Heavy Metals
Contamination in Banzu and Nakatsu
Tidalflats,Japan. Japanese Society of Water
Treatment Biology,Vol.43,No1,2007, pp.1-8[6] Hiroyuki Ii, As,Sr,Zn,Fe,Mn,Pb and Cu
Concentrations of Seaweed at the Kii
Peninsula,Japan. International Journal of
GEOMATE, Vol. 10, Issue 22, 2016, pp. 20362042.
[7] Kubohara T and Ii H., Cu,Co,Cr and Ni of River
Insect and Water Plant in the Kinokawa River
Catchment, International Journal of GEOMATE,
Vol. 10, No.1(Sl.No.19),2016, pp. 1600-1606.
[8] Kubohara T and Ii H., Cu,Co and Ni
Contamination Index for River Using River
Insects and Water Plants, International Journal of
GEOMATE, Vol. 11, Issue 26, 2016,pp. 26512658.
[9] Kubohara T and Ii H., Evaluation of Metal
Contamination for River Using Bryophyte in the
Kinokawa River Catchment, International Journalof GEOMATE, Vol. 13, Issue 37, 2017, pp. 108115.
[10] Zn and Fe Contamination Index for River Using
River Insects and Water Plants in the KinokawaRiver Catchment, International Journal of
GEOMATE, Vol.19, Issue 75, 2020,pp.76-83.

REFERENCES[1] Ministry of the Environment Nature Maintenance
Bureau 2001 "500 Important Wetlands in Japan"
https://www.env.go.jp/nature/important_wetland/
index.html

325

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EFFECTIVENESS OF COMPACTED POLYURETHANE-CLAY AS A
SANITARY LANDFILL LINER
Cielo Frianeza1 and Mary Ann Adajar2
Civil Engineer, De La Salle University, Philippines; 2Faculty, De La Salle University, Philippines

1

ABSTRACTSanitary landfill is a waste disposal facility that has control over the potential impact of solid waste by using
impermeable liners to prevent contamination of the environment. Several studies improved the impermeability ofcompacted clay liners by adding bentonite. However, bentonite is an expansive soil susceptible to volume changethat would cause the deterioration of the sanitary landfill liner. Hence, the study aimed to investigate theeffectiveness of compacted clay mixed with polyurethane as a sanitary landfill liner since polyurethane is apolymer known for its stability and impermeability. Through experimentation using a rigid wall permeameter, it
was inferred that the hydraulic conductivity of the compacted polyurethane-clay is acceptable as a sanitary landfill
liner. On the other hand, the compacted clay with the same void ratio as the compacted polyurethane-clay is not
an acceptable landfill liner. Thus, the changes in the soil structure induced by adding polyurethane to thecompacted clay has a significant effect on the permeability characteristics.
Keywords: Polyurethane, Clay, Sanitary Landfill Liner, Permeability

INTRODUCTION

into the soil matrix of a local clay, which would yielda hydraulic conductivity that is acceptable as an SLF
liner based on the standard design criteria. Suchmaterial that may be incorporated into the soil matrix
are polymers.
Polymers stabilize soil through the reduction of
the rate of water invasion into the soil structure [4].
The effectiveness of polymers in increasing thewater-stable aggregation is related to the strength ofinterparticle bonding induced by the material [4].
Polyurethane (PU) is a polymer formed from thechemical reaction between polyol and isocyanate that
produce the repeating unit in the polymer, urethane[5]. Polyurethane is widely used in the constructionindustry for ground improvement of expansive soils.
Inclusion of polyurethane foam in the soil mass
through mixing successfully increased the shear
strength of marine clay, a soil characterized byexcessive volume change [5]. Application ofpolyurethane also includes decreasing soil settlement
when used as a grout; moreover, polyurethane grout
micro piles improve the response of the ground to
dynamic forces [5]. A study has also shown thatpolyurethane foam, when injected into the ground, isfound to improve strength, stiffness, and bearing
resistance [5]. Aside from the ground improvement interms of strength, polyurethane injection was alsoinferred to lower permeability of cracked expansive
soils. A study about the effects of polyurethane resin
injection in desiccated expansive soil mass showedthat the veins of the injected polyurethane resin acted
as a moisture barrier better that intact clay; in
addition, the injected polyurethane resin did notincrease the swelling of the soil mass [6].

It was believed that the leachate produced fromthe degradation of waste was filtered by the soil;
however, several studies showed that leachate
contaminates the surrounding soil and eventually willcontaminate the groundwater system [1]. Thus,
sanitary landfill (SLF), a waste disposal facility, wasdeveloped to have an impermeable layer that prevents
the infiltration of leachate and the contamination of
the surrounding environment [1].
There are different kinds of impermeable
materials that may be used as an SLF liner, such asclay, geomembrane, geotextiles, geosynthetic clay
liner, geonet, or a combination of these materials [1].
Among these materials, compacted clay liner ispreferred due to the abundance and availability ofnative clay. A layer of clay used as an SLF liner iscompacted to lower the hydraulic conductivity, ameasure of permeability, and to remold the soil
aggregates into a homogenous soil mass. Different
factors such as moisture content of the clay, methodof compaction, and compactive effort influence thehydraulic conductivity of the compacted clay liner[2]. In actual practice, the hydraulic conductivity ofclay is further reduced by incorporating bentonite. It
was inferred that the addition of bentonite in thenative clay mixture is effective in reducing thepermeability of bentonite-modified clay [3].
However,bentonite,which
consistsofmontmorillonite minerals, increases the shrinkage
capability of the soil mixture when subjected to adecrease in moisture content [3]. Thus, the study aims
to incorporate an impermeable and stable material
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EXPERIMENTAL PROGRAM

The two components of the compacted
polyurethane-clay include the local clay and the rigid
polyurethane foam. The expansive soil used in the
study was from a proposed SLF site in Kauswagan,
Lanao del Norte and was excavated at least 2 meters
below the ground to ensure that no organic matter ispresent in the soil mass. ASTM standards were used
to determine the different soil properties necessary forcomputational purposes and to analyze the control
specimen, the compacted local clay. The soil
properties of the excavated soil from Kauswagan,
Lanao del Norte is tabulated in Table 1.

local clay. In which, the trial specimen for this study
was targeted to have a similar hydraulic conductivity
with the specimen from the study of Tiongson andAdajar [7] that used the same type of expansive soil
from the same site in Kauswagan, Lanao del Norte.
The compaction moisture content established fromthe trial tests was 46.5%, which was used in the mix
proportion of the specimens used in theexperimentation to obtain the hydraulic conductivityof the compacted polyurethane-clay. The mix
proportion of the two kinds of specimen, local clay
and polyurethane-clay is tabulated in Table 3,
wherein the mass of the rigid polyurethane foam is
0% and 3% of the dry mass of the specimen. In
addition, the mixing ratio for the rigid polyurethane
foam is 1 part polyol and 1 part isocyanate by weight.

Table 1 Soil properties of local clay

Table 3 Sample mix proportion

Materials

Standard
D698
D854
D4318
D4318
D4318
D4943
D4253
D4254
D2487
D7928

Soil property
Optimum moisture content
Specific gravity
Liquid limit (%)
Plastic limit (%)
Plasticity index (%)
Shrinkage limit (%)
Maximum void ratio
Minimum void ratio
Soil classification
D60 (mm)PU
content
0%3%31.15%
2.41
73
47
26
28
1.55 [7]1.07 [7]MH
0.00480

PU
(kg)
0.00
2.04

Dried clay
and PU (kg)
68.26
68.26

Water
(kg)
31.74
31.74

Mixing and Curing
The local clay used to produce the specimen wasoven-dried to ensure that the water in the mixture iscontrolled. The rigid polyurethane foam wassynthesized in a single step by directly mixing thepolyol and isocyanate. Mixing of the polyurethanecomponents was conducted within the cream time
before the dried local clay was added. The dry mixingof the rigid polyurethane foam and the dried local clay
was done as fast as possible to prevent thesolidification of the polyurethane before it is evenly
integrated into the local clay matrix. The
polyurethane-clay mixture was placed in an airtightcontainer for 20 minutes before adding the amount ofwater required to meet the compaction moisture
content, so that further reaction between components
may occur. The mixture of polyurethane, clay, andwater was cured for at least 24 hours in a plastic bag
before it was compacted to ensure that the water isevenly distributed in the mixture. The same
methodology was applied to the local clay used to
produce the compacted local clay specimen with 0%
polyurethane content with the exclusion ofincorporating the rigid polyurethane foam.

The rigid polyurethane foam used in the study waspurchased from Polymer Product (Phil.), Inc. The
rigid polyurethane foam is produced from the twocomponents, polyol and isocyanate. The properties
and reaction data of the rigid polyurethane foam isshown in Table 2.
Table 2 Polyurethane properties
Property
Specific gravity
Viscosity at 25°C
Cream time
Gel time
Tack free time

Dried
clay (kg)
68.26
66.22

Value
1.1 to 1.2
100 cps to 400 cps
19 seconds to 27 seconds
117 seconds to 130 seconds
230 seconds to 262 seconds

Mix Proportion
The obtained optimum moisture content of thelocal clay was 31.15%, which served as a basis todetermine the moisture content upon compaction thatwould yield the desirable hydraulic conductivity of
the compacted local clay. According to previous
studies, compacting the specimen at a higher moisture
content would yield a lower hydraulic conductivity[8]. Thus, five trials were conducted to approximate
the compaction moisture content that would yield an
acceptable hydraulic conductivity of the compacted

Manual Compaction
The soil properties of the polyurethane-clay
mixture are tabulated in Table 4. Based on thetabulated soil properties of local clay andpolyurethane-clay, it can be observed that the liquid
limit of the local clay is higher than the liquid limit of
the polyurethane-clay. In addition, the liquid limit andplasticity index of both local clay and polyurethane327

SEE-Mie, Japan, Nov.10-12, 2022

clay intersect below the “A” line of the plasticity chartin ASTM D2487. Thus, both soils are classified as
MH or elastic silt; however, the polyurethane-clay
consists of 16.5% sand, which denotes that its
classification is elastic silt with sand. Furthermore, it
can be observed that the specific gravity of the local
clay and polyurethane-clay differs, which are 2.41
and 2.86, respectively. The difference denotes that
there will also be a difference in the void ratio of thelocal clay and polyurethane-clay specimen whencompacted with the same effort. Hence, twocompaction efforts were applied that yielded threekinds of compacted specimen labeled as compacted
clay liner (CCL), clay liner (CL), and compacted
polyurethane-clay liner (CPCL). The summary of thevoid ratio and the description of the manualcompactive effort applied for the three kinds ofcompacted specimen are tabulated in Table 5. The
compactive effort that produced the CCL, with an
initial void ratio of 1.06, compaction moisture content
of 46.5%, and an acceptable hydraulic conductivity
based on the study of Tiongson and Adajar [7] thatused the same type of soil, was applied topolyurethane-clay that produced the CPCL. CPCL
had the same compactive effort as CCL, but a higher
void ratio of 1.44. Less compactive effort was applied
to the third type of compacted specimen, CL, toobtain the same void ratio as CPCL, which is 1.44.
All test specimens were cured for 24 hours after
compaction in the airtight permeameter mold. After
curing, all specimens were saturated for 14 days toinitiate the permeability test.

test included the flow measurement system and arigid wall permeameter as shown in Fig. 1. In addition,
the falling head method was used with a hydraulicgradient of 1.07. Since the expected hydraulicconductivity is low, it was anticipated that a single
run of the experiment would take approximately 60
days; thus, each run was conducted simultaneously.
The diameter of each specimen is 63.5 mm, and theheight is 110 mm. The hydraulic conductivity of eachspecimen tested in a rigid wall permeameter under thefalling head system was calculated using Eq. (1).

Fig. 1k=

Table 4 Soil properties of polyurethane-clay
ASTM
D854
D4318
D4318
D4318
D4943
D2487
D7928

aL
At

Rigid wall permeameter setuphln ( 1 )h2(1)

Where k is the hydraulic conductivity in m/s, a isthe cross-sectional area of the standpipe in m2, L is
the length of the specimen in m, A is the crosssectional area of the specimen in m2, t is the time
between determination of h1 and h2 in seconds, h1 is
the head loss across the specimen at time t1 in m, andh2 is the head loss across the specimen at time t2 in m.

Soil property
Specific gravity
2.86
Liquid limit (%)
68
Plastic limit (%)
48
Plasticity index (%)
20
Shrinkage limit (%)
29
Soil classification
MH with Sand
D60 (mm)0.02025TEST RESULTS

Table 5 Compaction effort and initial void ratio

XRD Analysis

Specimen
CCL
CPCL
CL

The x-ray diffraction (XRD) analysis of the local
clay and polyurethane-clay are shown in Fig. 2 andFig. 3, respectively. The XRD analysis determinedthat aluminum silicate hydroxide and silicon oxide,
which are also known as Kaolinite and Quartz, arepresent in both local clay and polyurethane-clay.
Furthermore, the multiplot of both soil types have thesame trend and spikes, denoting that the soil types are
similar in composition; however, it should be notedthat the amount of polyurethane in the polyurethaneclay mixture is only 3% of the dry weight of thespecimen, which may not be a significant amount toproduce a change in the spikes plotted.

PU
0%
3%
0%

Initial void ratio
1.06
1.44
1.44

Compaction
Standard
Standard
Less

Permeability Test
The ASTM standard test method used in the study
to determine the hydraulic conductivity is ASTM
D5856 [9], or the standard test method formeasurement of hydraulic conductivity of porous
material using a rigid wall, compaction-moldpermeameter. The components used to conduct the328

SEE-Mie, Japan, Nov.10-12, 2022

soil erosion because of the improved capability of thesoil mass to hold particles together [13]. Therefore,
based on the elemental distribution establishedthrough the EDX analysis that exhibited an increasein carbon content, it can be inferred thatpolyurethane-clay is more stable than local clay.
Table 6 EDX analysis of uncompacted specimen
Element
Fig. 2Oxygen
SiliconBromineCarbonIron

XRD analysis of local clay

Weight Percentage
Local Clay
Polyurethane-clay
44.69
41.26
14.69
14.29
28.73
27.29
2.99
9.96
8.90
7.20

SEM Analysis

Fig. 3The scanning electron microscope (SEM) imageof the local clay and polyurethane-clay are shown in
Fig. 4. It can be observed that both soil types are
clustered and have intergranular and intragranularvoids. However, it can be observed that the SEM
image of polyurethane-clay exhibits sphericalparticles on the surface of the clay particle, which isinferred to be polyurethane foam based on theexisting SEM image of polyurethane foam. The SEM
image of pure polyurethane foam is shown in Fig. 5,
in which spherical particles are predominant.

XRD analysis of polyurethane-clay

One of the minerals found on both soil types is
Kaolinite, which is a non-swelling, soft clay mineralthat is plastic in nature; moreover, Kaolinite is
assumed to be the least reactive among the clay
minerals [10]. It can also be noted that the obtained
plasticity index of local clay and polyurethane-clay
when tested using the ASTM standard reflected ahighly plastic property, which agrees with the highly
plastic characteristic of Kaolinite [10]. The othermineral detected through XRD analysis is Quartz,
which is a mineral present in almost all parent
materials and inherited by silt and sand [11].
Considering the classification of the local clay andpolyurethane-clay, which is elastic silt and elastic siltwith sand, it can be inferred that the presence ofQuartz agrees with the soil classification.

PolyurethaneFig. 4

Image of (a) clay and (b) polyurethane-clay

Fig. 5SEM images of (a) polyurethane [14], (b)Kaolinite [15], and (c) Quartz [16]

EDX Analysis
The energy dispersive x-ray (EDX) analysis of thelocal clay and polyurethane-clay detected traces ofoxygen, silicon, bromine, carbon, and iron, tabulated
in Table 6. The dominant elements in the analysis areoxygen and silicon, which are commonly found insoils. Moreover, it can be observed that polyurethaneclay has more carbon than local clay; thus, it can beinferred that incorporating polyurethane into the soil
matrix of the local clay increases the carbon content
of the mixture. An increase in carbon content denotesthat the soil mass has a more stable structure and abetter water holding capacity [12]. Thus, a higher
carbon content in the soil mass also results in reduced

SEM images shown in Fig. 4 also exhibit
characteristics of Kaolinite and Quartz, which werethe elements detected on the local clay andpolyurethane-clay through XRD analysis. Kaolinite,which is described as thick, rigid, and plate-like witha hexagonal shape [17], appears flaky and plate-likeon Fig. 4. On the other hand, the spheroidal particles
observed in Fig. 4 are inferred as Quartz based on thesimilarity of the particle shape shown in Fig. 5. It can
329

SEE-Mie, Japan, Nov.10-12, 2022

be observed in Fig. 4 that more spheroidal-shaped
particles are found in polyurethane-clay, which agreewith the grain size distribution established for the
polyurethane-clay that shows more sand particles ascompared to the composition of the local clay.

determined. The actual hydraulic conductivity of
CCL is similar to the predicted value for specimen inwhich the Standard Proctor effort of 600 kN-m/m3
was applied as the compactive effort. On the other
hand, the predicted hydraulic conductivity of CL is
two orders of magnitude lower than the actual
hydraulic conductivity of CL as shown in Table 8.

Hydraulic Conductivity
The hydraulic conductivity obtained from theexperimentation for the three kinds of compacted
specimen are tabulated in Table 7. Hydraulicconductivity is one of the major parametersconsidered to determine if a material is a suitable SLF
liner; thus, CL and CPCL, were comparedconsidering that the two specimen types haverelatively the same void ratio. It was opted that thevoid ratio would be held constant instead of thecompactive effort because a constant void ratio
denotes that the volume of voids that water could
occupy between soil particles are also constant for
both specimen types, CL and CPCL.

Table 8 Predicted hydraulic conductivity

CCL
CL
CL

PU

Void ratio

CCL
CL
CL
CPCL
CPCL

0%
0%
0%
3%
3%

1.09
1.38
1.42
1.50
1.53

Actual k(cm/s)

1.09
1.42
1.38

2.27×10-8
6.47×10-5
8.08×10-5

Predicted k (cm/s)
Reduced Standard
Proctor
Proctor
2.07×10-8 2.29×10-8
1.50×10-7 2.39×10-7
1.17×10-7 1.78×10-7

Thus, this indicates that the compactive effort of
CL is considerably smaller than the compactive effortof CCL. Moreover, it should be noted that the manualcompactive effort applied on CCL is relatively thesame as the manual compactive effort applied on
CPCL. Therefore, it can be inferred that the manualcompactive effort applied on CPCL may also be theStandard Proctor effort.

Table 7 Hydraulic conductivity
Specimen

Void
ratio

Hydraulicconductivity, k
2.27×10-8 cm/s
6.47×10-5 cm/s
8.08×10-5 cm/s
2.36×10-8 cm/s
3.44×10-8 cm/s

Effectiveness of CPCL as SLF Liner
Most of the related literature that discussed thesuitability of landfill liner material utilized amaximum hydraulic conductivity of 10 -7 cm/s.
Furthermore, the said hydraulic conductivity wasutilized by most studies to ensure that the landfill liner
material is less permeable to avoid the contaminationof the surrounding environment. The lowest
permeability required for a compacted SLF liner in
the Philippines is 10-7 cm/s or 10-9 m/s [18]. Thus, fora material to be considered as a suitable SLF liner for
all SLF categories, the obtained hydraulicconductivity should be equal to or lower than 10-9 m/s.
Based on the design standards, it can be inferredthat the compacted polyurethane-clay liner is asuitable SLF liner for all SLF categories with regards
to its permeability. Moreover, the clay specimen
compacted to have the same initial void ratio as CPCL
is not a suitable SLF liner for any SLF category.
One-way analysis of variance was used tostatistically compare the hydraulic conductivity of
CPCL and CL. The result of the analysis of variance,
tabulated in Table 9, indicates that the model and thepolyurethane content are significant since the Pvalues are less than 0.05. Thus, incorporating
polyurethane into the soil mixture, statistically, has aneffect on the hydraulic conductivity. It can be inferredthat the polyurethane in the soil mixture decreased thehydraulic conductivity of the specimen, which can beconsidered as a suitable SLF liner as opposed to thecompacted clay without polyurethane that have thesame initial void ratio as CPCL.

The decrease in hydraulic conductivity as
polyurethane was incorporated into the soil matrix ofthe local clay may be due to the impermeable natureof polyurethane. A previous study inferred thatpolyurethane, in its pure form, is relatively water
resistant due to the closed porosity of its
microstructure; in addition, polyurethane injected
into cracked clays are observed to have a low
permeability of 10-8 cm/s [14]. Therefore, thepolyurethane improved the impermeability of thepolyurethane-clay mixture based on the comparison
between the hydraulic conductivity of CPCL and CL,
which are specimens with the same void ratio.
However, the difference in hydraulic conductivity of
CL and CPCL may also be attributed to the differencein compactive effort applied. The compactive effort
applied on CPCL and CCL is greater compared to thecompactive effort applied to CL, since thecompactive effort used on CL had an objective toattain the high initial void ratio of CPCL.
Estimated Compactive Effort
By utilizing the model proposed by Tiongson andAdajar [7] to predict the hydraulic conductivity forthe same local clay, the compactive effort of themanually compacted specimen in the study may be
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SEE-Mie, Japan, Nov.10-12, 2022

Table 9 Statistical analysis of hydraulic conductivity
SourceModel
Polyurethane content

P-value
0.01200.0120[5] Saleh, S., Yunus, N. M., Ahmad, K., & Ali, N.,
Stabilization of marine clay soil using
polyurethane, MATEC Web of Conferences,
2018.
[6] Buzzi, O., Fityus, S., & Sloan, S. W., Use of
expanding polyurethane resin to remediate
expansive
soil
foundations,
Canadian
Geotechnical Journal, 2010, pp. 623-634.
[7] Tiongson, J. M., & Adajar, M. A., Compaction
characteristics of a fine-grained soil potential for
landfill liner application, International Journal of
GEOMATE, 2020, pp. 211–218.
[8] Wagner, J. F., Chapter 9 Mechanical Properties ofClays and Clay Minerals, In Developments inClay Science, Vol. 5, 2013, pp. 347-381.
[9] ASTM International, ASTM D 5856-95: standard
test methods for measurement of hydraulicconductivity of porous material using a rigid-wall,compaction-mold permeameter, In Annual bookof ASTM standards 1995, 1995, pp.1-8.
[10] Pourhakkak, P., Taghizadeh, M., Taghizadeh, A.,& Ghaedi, M., Adsorbent, Interface Science andTechnology, 2021, pp. 71–210.
[11] Gutiérrez-Castorena, M. del., Pedogenic
siliceousfeatures,InterpretationofMicromorphological Features of Soils andRegoliths, 2018, pp. 127–155.
[12] Rice, C. W., Carbon cycle in Soils | Dynamics
and management, Encyclopedia of Soils in theEnvironment, 2005, pp. 164–170.
[13] Pimentel, D., & Burgess, M., Maintaining
sustainable and environmentally friendly fresh
produce production in the context of climatechange, Global Safety of Fresh Produce, 2014, pp.
133–139.
[14] Buzzi, O., Fityus, S., Sasaki, Y., & Sloan, S.,
Structure and properties of expanding
polyurethane foam in the context of foundation
remediation in expansive soil, Mechanics ofMaterials, 2008, pp. 1012-1021.
[15] Namdar, A., Kaolinite Chemical Composite andMorphology in Geotechnical Engineering,
Advances in Natural and Applied Sciences, 2011,
pp. 93–99.
[16] Baawuah, E., Fosu, B., Ofori-Sarpong, G., &Addai-Mensah, J., Influence of Alkaline Type on
Quartz Pulp Particle Interactions and Interfacial
Chemistry in Aqueous Media, In 3rd Biennial
UMaT International Mining and Mineral
Conference, 2021, pp. 220–227.
[17] Rouquerol, F., Rouquerol, J., & Sing, K.,
Adsorption by clays, pillared layer structures andzeolites, Adsorption by Powders and Porous
Solids, 1999, pp. 355–399.
[18] Department of Environment and Natural
Resources Administrative Order No. 10, 2006.

Significant
Significant

CONCLUSION
Bentonite-modified clay is often used in theindustry as sanitary landfill liners; however, thecharacteristic of bentonite makes the clay susceptible
to deterioration due to volumetric changes. Thus, thelocal clay was mixed with polyurethane, a polymer
often used to stabilize soil. Changes in the soil
structure induced by incorporation of thepolyurethane into the soil matrix, such as increase incarbon content, improved the water holding capacityof the compacted specimen when compared to thecompacted local clay with the same void ratio.
Furthermore, the impermeable nature of polyurethane
was inferred to have contributed to the decrease in
hydraulic conductivity. Thus, the compacted
polyurethane-clay was classified as a suitable landfill
liner in accordance with the Philippine design
standard for all sanitary landfill categories.
RECOMMENDATION
Since excessive volume change could deteriorate
the impermeability of SLF liners made fromexpansive soil, it is recommended that future studies
explore the shrinkage resistance of polyurethane-clay.
Furthermore, it is recommended that future studies
explore the unsaturated hydraulic conductivity ofpolyurethane-clay since SLF liners are not always
saturated in actual conditions.
REFERENCES[1] National Solid Waste Management Commission,& Japan International Cooperation Agency,
Technical Guidebook on Solid Wastes Disposal
Design, Operation and Management (Second ed.)(Philippines, National Solid Waste Management
Commission), National Solid Waste Management
Commission Office of the Secretariat, 2010.
[2] Daniel, D. E., Case Histories of Compacted ClayLiners and Covers for Waste Disposal Facilities,
International Conference on Case Histories inGeotechnical Engineering, 1993.
[3] He, J., Wang, Y., Li, Y., & Ruan, X., Effects ofleachate infiltration and desiccation cracks on
hydraulic conductivity of compacted clay, Water
Science and Engineering, 2015, pp. 151-157.
[4] Fink, J., Chapter 8 - Clay stabilization, HydraulicFracturing Chemicals and Fluids Technology,
2020, pp. 119-139.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FEASIBILITY OF OYSTER SHELL PERVIOUS CONCRETE WITH
DIFFERENT PARTICLE SIZE AS A SEAWEED BED
Shuta Hiura1, Itaru Horiguchi2 and Yoichi Mimura3
Advanced course, National Institute of Technology (KOSEN), Kure College, Japan;
2,3National Institute of Technology (KOSEN), Kure College, Japan

1

ABSTRACT
Global warming, due to a large amount of greenhouse gas emission, is one of the most important issues for theentire world. Japan has already pledged to achieve net zero greenhouse gas emissions, carbon-neutrality, by 2050.
The use of plants is one of the measures being used to solve the problem because plants utilize carbon dioxide byphotosynthesis. In this study, the feasibility of pervious concrete (OyPC) used oyster shell aggregates withdifferent particle size as a seaweed bed was investigated because the oyster shells of about 90,000 tons are annually
produced as a by-product in Hiroshima Prefecture. The porosity, compressive strength, and water permeability of
OyPC were also studied. From the test results, OyPC using aggregates ranged from 5.0 to 0.3 mm (Oy5003) had
the lowest porosity, resulting in the highest compressive strength and relatively low water permeability. Oy5003
would be effective as a seaweed bed because thick seaweeds grew densely on Oy5003 with graded aggregatescompared with the other OyPC with single-sized aggregates from the results of immersion tests with cylindrical
specimens.
Keywords: Oyster shell pervious concrete, seaweed bed, porosity, compressive strength, water permeability

INTRODUCTION
Global warming due to a large amount ofgreenhouse gas emission is one of the most important
issues for the entire world. Japan has already pledged
to achieve net zero greenhouse gas emissions, carbonneutrality, by 2050. The use of plants is one of themeasures being used to solve the problem because
plants utilize carbon dioxide by photosynthesis.
Recently, carbon captured by the world’s ocean andcoastal ecosystem is receiving a lot of attention for
carbon sequestration, which is called “blue carbon”.
Coastal blue carbon ecosystems include seaweed
beds, mangroves, tidal marshes, and so on [1], [2].
Hiroshima Prefecture is famous for its high oyster
productivity, contributing 17,928 metric tons or
64.6% of Japan’s total production levels (27,742
metric tons) for 2019 [3]. The production of oysters
generates oyster shells as a by-product. Oyster shells
are used commercially as livestock feed for chickens,pigs, and cows and as a soil conditioner. However, thereuse of oyster shells remains limited. Pervious
concrete is a special concrete in which single-sized
aggregates are bound together with a cement paste or
mortar. Pervious concrete has a large volume ofinterconnected pores ranging from 15 to 30%. In
previous researches, the plat-growing performance of
pervious concrete (OyPC) containing crushed oyster
shell aggregates was investigated, and OyPC was
found to have higher plat-growing performance thancrushed stone pervious concrete [4], [5].
In this study, the feasibility of OyPC used oyster

Fig. 1 Storage facility of oyster shells.
shell aggregates with different particle size as aseaweed bed which was one of coastal blue carbon
ecosystems was investigated. The porosity,
compressive strength, and water permeability of
OyPC were also studied.
MATERIALS AND METHODS
Materials
In this study, oyster shells were collected from astorage facility in Kure City, Hiroshima Prefecture(Fig.1). The oyster shells were washed by a tilting
mixer to eliminate impurities such as salt andseaweeds attached to shells, which could adversely
affect the cement hydration. The washed oyster shells
were dried in the sun and crushed by a shell crusher(Fig.2). The crushed oyster shells were sieved to332

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Physical properties of the oyster shell aggregates.

Table 2 Proportions of materials in each mixture.

Fig. 3 Specimens for the immersion test in the Sea.
mixtures, the water to cement ratio by mass (W/C)
was 25%, and the cement paste to aggregate ratio by
volume (p/a) was 30%. An omni mixer of which
capacity was 10 liters was used for the mixing. First,
aggregates and cement were mixed for 30 seconds inthe mixer. Next, water with the admixture was put
into the mixer and mixed for 90 seconds. The
cylindrical specimens of Φ100×200 mm were used
for the porosity, compressive strength, and water
permeability test. On the other hand, cylinder of Φ100
×150 mm and plate of 300×300×100 mm wereused for the immersion test in the sea (Fig. 3). A
polyvinyl chloride (PVC) pipe of which inner, outer
diameter, and length were 13, 18, and 300 mm,
respectively, was inserted in the center of thecylindrical specimen. Two hooks bent round steel
bars of 6mm diameter were mounted on the plate
specimen.
Each mixture was filled into a mold in a single
layer for both cylindrical and plate specimens. The
specimens were compacted with a table vibrator for
10 seconds, and the surfaces of specimens wereleveled using an external vibrator. Once placed in theFig. 2 Shell crusher.
prepare for 4 types of single-sized aggregates, ofwhich particle sizes were 0.6 to 1.2 mm, 1.2 to 2.5mm, 2.5 to 5.0 mm, 5.0 to 10.0 mm, and gradedaggregates of 0.3 to 5.0 mm. Saturated surface dryoyster shell aggregates were used for production of
specimens. The oyster shell aggregates were
immersed in water for 24 hours and the excessive
water was removed from the wet aggregates by left
into sandbags for more than 24 hours. To dry thesurface of the aggregates in the sun, the aggregateswere spread on plastic sheets. The saturated dry
surface condition of aggregates was decided by theflow cone method based on JIS A 1109.
Table 1 shows the physical properties of oyster
shell aggregates. In this study, Portland blast-furnace
slag cement-type B was used as cement to reduce theamount of alkaline components which may inhibit
seaweed growth. Tap water and air-entraining andhigh-range water-reducing admixture were also used.
Table 2 shows mixture proportions of OyPC. For all333

SEE-Mie, Japan, Nov.10-12, 2022

molds, the specimens were covered with wet gunnybags and plastic sheets for 24 hours to prevent drying
before consolidation. The specimens were demoldedand placed in 20±2℃ water for 6 and 27 days.
Test method
The porosity and the water permeability
coefficient were measured according to JCI-SPO2-1
and JCI-SPO3-1, respectively. The specimen was
weighed in casting and the porosity (At, %) was
calculated using the following Eq. (1)𝑾𝟏⁄𝑽
𝟏𝑨𝒕 = (𝟏 − 𝑾𝟐

⁄𝑽𝟐

) × 𝟏𝟎𝟎(1)
Fig. 4 A schematic diagram of water permeability
test.

where W1 (kg) and V1 (m3) are the weight andvolume, respectively, of the specimen, and W2 (kg)and V2 (m3) are the total weight and volume,
respectively, of water, cement, aggregate, andadmixture used in 1m3 of pervious concrete.
The water permeability test was performed byusing the apparatus provided in Fig. 4. A specimen
was set into a PVC pipe with an inner diameter of 100
mm and a pipe collar was connected to the pipe. A
sponge rubber sheet was wrapped around the side of
the specimen to prevent water from permeating theinterface between the specimen and the pipe. The pipe
collar had a drain outlet for keeping the water level of
40 mm. The amount of water permeated the specimen
for 30 seconds was measured three times. The water
permeability coefficient could be calculated by Eq.
(2)
𝑸

𝒉

𝑲 = 𝑻𝑨 × 𝑯(2)

where K (cm/sec) is the water permeability
coefficient. Q (cm3) is the amount of water flow
within T, and T (sec) is the test time. A (cm2) is the
cross section of a specimen, h (mm) is the height of a
specimen, and H (mm) is the water head.
The compressive strength test was carried out
based on JIS A 1108. The specimens cured for 7 and
28 days were tested by using an Amsler type universal
testing machine at a loading speed of 0.01 N/mm2/sec
until the specimens were damaged. Sulfur mortar was
prepared for capping the ends of specimens to prevent
stress concentration.
The immersion test in the sea was started at an
oyster farm in Kure City, Hiroshima Prefecture from
November 5, 2021 and is still ongoing (Fig. 5). Fourtypes of cylindrical specimens, which were Oy5003,
Oy10050, Oy5025, and Oy2512, were prepared in thetest. Seven specimens for each of the mixtures wereconnected at intervals of about 350 mm with apolyethylene rope. The connected specimens weresuspended carefully from a bridge across shore to afloating pier (Fig. 6). The distance between a top

Fig. 5 Immersion test in the sea at an oyster farm.
surface of a topmost specimen (No. 7) and the seabed
was about 3 m; however it was fluctuated because thepier sank and floated due to tidal action.
Five types of plate specimens, which were
Oy5003, Oy10050, Oy5025, Oy2512, and Oy1206,
were also immersed in the sea. The hooks mounted
on the plate were tied to a heavy steel wire basket witha polyethylene rope in order not to wash away bywaves. Both of the cylindrical and the plate
specimens were temporarily pulled up from the sea
for the visual observations at 31 and 84 days after thestart of the test.
334

SEE-Mie, Japan, Nov.10-12, 2022

RESULTS AND DISCUSSION
Porosity, compressive
permeability

strength,

and

water

The porosity of specimens for the compressive
strength and water permeability test are shown in Fig.
7. According to Fig. 7, Oy5003 with gradedaggregates had the lowest porosity of about 35%.
While the porosities of Oy10050, Oy5025, Oy2512,
and Oy1206 with different size of single-sized
aggregates were almost the same value of 45%, which
was higher than that of Oy5003.
Figure 8 shows the compressive strengths of
OyPC curing for 7 and 28 days. Regardless of thecuring age, Oy5003 with graded aggregates showed
the highest strength of about 2.5 N/mm2 among all of
the specimens. While the strengths of Oy10050 withthe largest single-sized aggregates were 1.1 and 1.0
N/mm2 at 7 and 28 days, respectively, which were as
small as 40% of that of Oy5003. The 28-day strengthsof OyPC were higher than the 7-day strengths, withthe exception of Oy10050; although these differenceswere small due to the significantly low strength ofoyster shell aggregate.
Figure 9 presents the water permeability
coefficients of OyPC. As shown in Fig. 9, the water
permeability of OyPC with single-sized aggregatesdecreased while decreasing the particle size, andOy1206 had the lowest water permeability coefficientof 0.21 cm/sec. The water permeability coefficient of
Oy5003 with graded aggregates was 0.81 cm/sec
which was similar to that of Oy2512.
The compressive strength and the water
permeability of pervious concrete depend on its pore
structure, such as porosity, pore diameter andtortuosity, which is determined by the particle size
and the shape of aggregates and the amount of cement
paste. Pervious concrete with smaller single-sized
aggregates generally has smaller pores and a more
tortuous pore structure than pervious concrete withlarger aggregates. Compared with pervious concretewith single-sized aggregates, pervious concrete withgraded aggregates has fine pore structure because of
the high packing density of aggregates. Therefore,
Oy5003 with graded aggregates had the lowest
porosity, resulting in the highest compressive
strength and relatively low water permeability.

Fig. 6

Cylindrical specimens suspended from abridgeFig. 7 Porosity of specimens for the compressive
strength and water permeability test.

Fig. 8 Compressive strength of OyPC curing for
7 and 28.

The immersion test results
The appearance of cylindrical specimens No. 1, 2
3, and 4 immersed in the sea for 31 and 84 days isshown in Fig. 10. From the visual observations nochanges were observed in specimens No. 5, 6, and 7
where distance from the seabed was over 1.4 m.
According to Fig. 10, surfaces of the specimens
immersed for 31 days turned light brown regardlessof particle size, although the color changes occurredFig. 9 Water permeability coefficient of OyPC.
335

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 10 Appearance of cylindrical specimens immersed in the sea for 31 and 84 days.

Fig. 11 Appearance of plate specimens immersed in the sea for 31 and 84 days.
partially. Very tiny seaweeds were found on the top
and the side of Oy5003 No. 2, 3, and Oy5025 No. 1.
Seaweeds grown on the specimens were observed
for all of specimens immersed for 81 days. In
particular, specimens No. 1 and 2 for all of the
mixtures which were close to the seabed had a lot ofseaweeds. Thick seaweeds grew densely on Oy5003
No. 1 and 2 with graded aggregates compared withthe other OyPC with single-sized aggregates. The
specimens No. 1 and 2 of Oy5025 and Oy2512 hadseaweeds grown densely, however those were slightly
thin. Seaweeds grew sufficiently on the top of

Oy10050 No. 1 and 2 while there was a small numberof seaweeds on the side of specimens.
The results of the immersion test with cylindrical
specimens suggested that Oy5003 with gradedaggregates would be effective as a seaweed bed. The
reason why seaweeds could grow on the OyPC has
not been clear, however the water retention of the
OyPC would strongly affect on the growth ofseaweeds on the specimens. In this immersion test,
sea level was lower than the bottom surface of thelowermost specimen (No. 1) at low tide. Therefore,
seaweeds became easy to dry on the specimens with
336

SEE-Mie, Japan, Nov.10-12, 2022high water permeability, namely low water retention,
resulting in the inhibition of seaweeds growth.
Additionally, seasonal changes in sunlight andseawater temperature also have an effect on thegrowth of seaweeds, and further observations over
one year will be needed.
Figure 11 shows the appearance of plate
specimens at 31 and 84 days. The top surface of all
specimens at 31 days after the start of the test became
partially green, and green colored area spread widely
at 84 days regardless of mixtures. In contract to thecylindrical specimens, no seaweed grown on the plate
specimens could be found. This is because the plate
specimens were immersed in the shallow sea and theimmersion time of the plate specimens was shorter
than the cylindrical ones.

(2) The results of the immersion test with plate
specimens showed that the top surface of all
specimens became green; however no seaweedgrown on the plate specimens could be found.
(3) Compared with OyPC with single-sized
aggregates, Oy5003 with graded aggregates had
the lowest porosity, resulting in the highest
compressive strength and relatively low water
permeability.
REFERENCES[1] Ministry of Land, Infrastructure, Transport andTourism, The white paper on land, infrastructure,transport and tourism in Japan, 2021
[2] Nellemann C., Corcoran E., Duarte C. M., Valdes
L., De Young C., Fonseca L., Grimsditch G., Blue
carbon. A Rapid Response Assessment. United
Nations Environment Programme, GRID,
Arendal, 2009[3] Hiroshima Prefectural Agriculture, Forestry and
Fisheries Department, Guidelines for production
and shipping of oysters in Hiroshima, 2021
[4] Hiura S., Horiguchi I., Mimura Y., Matsubara S.,
The evaluation method of the void structure andthe water pumpability of oyster shell porous
concrete with different particle size. Journal ofJapan Society of Civil Engineers Chugoku region
branch, Vol. 62, 2021, pp. 365-366[5] Horiguchi I., Mimura Y., Monteiro P. J. M., Plantgrowing performance of pervious concrete
containing crushed oyster shell aggregate.
Cleaner Materials, Vol. 2, 2021, 100027

CONCLUSIONSThe present study investigated the feasibility of
OyPC used oyster shell aggregates with different
particle size as a seaweed bed which was one ofcoastal blue carbon ecosystems. The porosity,
compressive strength, and water permeability of
OyPC were also studied. The main conclusions of thisstudy are highlighted below:(1) Oy5003 would be effective as a seaweed bed
because thick seaweeds grew densely on Oy5003
with graded aggregates compared with the other
OyPC with single-sized aggregates from theresults of immersion tests with cylindrical
specimens.

337

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

PHYSICAL PROPERTY AND HEAVY METAL LEACHING
BEHAVIOR OF CONCRETE MIXED WITH WOODY ASH

1Takuto Ueno1, Ayane Yanaka1, Shinichiro Okazaki2, Naomichi Matsumoto2 and Hidenori Yoshida2
Graduate School of Engineering, Kagawa University, Japan; 2 Faculty of Engineering and Design, Kagawa
University, Japan

ABSTRACTIn recent years, the woody biomass power generation attracts a lot of attention since woody biomass is analternative energy source to fossil fuels. In the future, further implementation of woody biomass power generation
is expected, and a large amount of woody ash will be discharged. Several studies have been conducted on theeffective use of woody ash for construction materials. However, woody ash has not been practically used becauseof concerns about the leaching of heavy metals from concrete mixed with woody ash. If the above problem can besolved, a large amount of woody ash is expected to be used. In this study, the fresh property and hardened
properties, such as compressive strength and length change were measured to evaluate the feasibility of using
concrete mixed with woody ash. Furthermore, a heavy metal leaching test was conducted to assess theenvironmental impact caused by concrete mixed with woody ash. As the result, the concrete mixed with woody
ash has the slump and air content similar to that of normal concrete, the compressive strength meeting the standard
durability design strength in Japan, and the shrinkage is similar to that of normal concrete. Additionally, theconcentration of heavy metals exceeding the soil environmental quality standards in Japan was partially detected,
but the leaching amount of heavy metals from the concrete mixed with woody ash was similar to that from normal
concrete.
Keywords: Woody ash, Recycling, Concrete admixture, Heavy metals

INTRODUCTION

and [6], the leaching of heavy metals which arecontained in the woody ash is worried due after theservice. On the other hand, as shown in [7], hardened
cement has the performance of preventing theleaching of heavy metals contained in the waste andit is most commonly used in solidification andstabilization processes. Therefore, if wood ash can beused as a concrete material, a large amount of woodash can be reused. Although the physical andchemical properties of woody ash are influenced by
species of tree and tree growing regions, a decrease in
the strength of concrete mixed with woody ash has
been reported, as shown in [5]. Therefore, if woody
ash is mixed into the concrete, the strength of theconcrete may be lower than the strength required forthe structure. In this study, the fresh property andphysical properties after hardening, such as strengthand length change were measured to evaluate thefeasibility of using concrete mixed with woody ash.
Furthermore, a heavy metal leaching test was
conducted to assess the environmental load caused by
concrete mixed with woody ash.

In recent years, global energy consumption has
been increasing due to population growth andeconomic growth in developing countries. On theother hand, most of the energy resources consumed in
the world are fossil fuels, and the reduction of carbon
dioxide emissions generated by power generation has
become an issue. As the initiative to reduce carbon
dioxide emissions, the parties to the United Nations
Framework Convention on Climate Change(UNFCCC) have set a long-term goal in the Paris
Agreement to hold the increase in the global averagetemperature to well below 2 °C above pre-industrial
levels and pursuing efforts to limit the temperature
increase to 1.5 °C. Woody biomass is a renewable
resource and absorbs carbon dioxide throughphotosynthesis during growth. In addition, woody
biomass is an alternative energy resource to fossil
fuels. For these reasons, the spread of woody biomass
power generation attracts a lot of attention in recent
years. In the future, further implementation of woody
biomass power generation is expected, and a large
amount of woody ash will be discharged. As reported
in [1], about 70% of the woody ash generated iscurrently landfilled. As shown in [2], [3], [4], and [5],several studies have been conducted on the effective
use of a large amount of woody ash for fertilizer andconstruction materials. However, as reported in [2]MATERIALS
Cement, Aggregate and Chemical Admixture
Ordinary Portland cement (3.16 g/cm3 of density)
specified in JIS R 5210 Japanese Industrial Standards
338

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Concentrations of heavy metals leachedfrom woody ash (ppm)

was used for cement. Mountain sand with 2.5 mm of
maximum grain size and 2.57 g/cm3 of surface dry
density for fine aggregate and crushed stone with 12
mm of average particle size and 2.62 g/cm3 of surface
dry density for coarse aggregate were used,
respectively. The air entraining and water reducing
agent (AE-WRA) whose main components are acomplex of a lignin sulfonic acid compound and apolycarboxylic acid ether was used for chemical
admixture.

Woody
bottom ash
0.166
0.413
1.465

As
Cr (VI)F

Soil environmental
quality standards
0.01
0.05
0.80

Woody Ash
Incinerated ash discharged from woody biomass
power plants is classified into bottom ash and fly ash.
As described in [8], most of the ash generated in theincinerator is bottom ash, which comprises about
80% in total. Therefore, in order to reuse a large
amount of woody ash, it is important to examine thefeasibility of using concrete mixed with woody
bottom ash. In this study, woody bottom ash
generated from a woody biomass power plant inKochi Prefecture, Japan, was used as a concrete
admixture. The woody bottom ash contained manycoarse particles with 9.5 mm of a maximum grain size.
Therefore, in order to obtain a suitable shape forconcrete material, woody bottom ash was dried at
100°C for 24 hours and ground in a ball mill until
there were no coarse particles. Fig. 1 shows the
woody bottom ash after crushing. The density of theground bottom ash is 2.47 g/cm3. Next, thecomposition of the woody bottom ash was analyzed
by XRD (X-ray Diffraction) analyzer. Fig. 2 shows
the spectrum of the woody bottom ash analyzed by
XRD analysis. As a result of XRD analysis, thecomposition of the woody bottom ash was 56.5% of
SiO2, 23.7% of CaCO3, 11.6% of Fe2O3, 7.9% of
MgO and 0.4% of CaO by weight. Although thewoody ash contained SiO2, it was not amorphouswhich promotes the pozzolanic reaction. In addition,in order to confirm the leaching of heavy metals fromwoody ash, the leaching test was conducted based on
the Environmental Agency Notification No.46. The
heavy metals analyzed in the leaching test werearsenic (As), hexavalent chromium (Cr (VI)) andfluorine (F), which are confirmed to be contained intrees in Japan. Cr (VI) and F were analyzed by amonomericwater
analyzer
basedon
diphenylcarbazide spectrophotometry, and As wasanalyzed by ICP-AES. Table 1 shows theconcentration of heavy metals leached from woody
bottom ash, and all concentrations exceeded the soil
environmental quality standard values in Japan.

Fig. 1

Woody ash
500

Intensity

400
300
200
100
0
0

Fig. 2

20

2θ

40

60

Spectrum of woody bottom ash by XRDTEST METHOD
Concrete Mix Design
As reported in [9] and [10], woody ash mixed into
the concrete may absorb water and the workability ofconcrete may decrease. Therefore, when woody ash
is mixed into the concrete, it is necessary to increase
the unit water volume in concrete in order to achieve
the same level of workability as normal concrete. In
this test, all concrete mixes were designed with water
cement ratio and fine aggregate ratio at 55% and 43%,
respectively. In addition, the workability of theconcreate mixed with woody ash equivalent to that ofa normal concrete was ensured by changing theaddition quantity of the air entraining and water
reducing agent. Table 2 shows the concrete mix
proportions in the test. “Blank” and “WBA” represent
normal concrete (concrete without woody bottomash) and concrete mixed with woody bottom ash,respectively. The woody bottom ash mixed into theconcrete was woody bottom ash in which heavy
metals were leached at concentrations exceeding the339

SEE-Mie, Japan, Nov.10-12, 2022

soil environmental quality standard values in Japan in
the leaching test. In this test, 10% of the mass of
cement used in Blank concrete was replaced with thewoody bottom ash. In order to make the workabilityof the two types of concrete equivalent, the amount of
the air entraining and water reducing agent added tothe cement mass was 1.0% for Blank concrete and1.8% for WBA concrete. Concrete preparation was
carried out based on Japanese Industrial Standard JIS
A 1138. The order in which the materials werecharged into the mixer was a half amount of aggregate(coarse aggregate and fine aggregate), cement, andthe remaining aggregate, to prevent the floatation of
powder. The woody bottom ash was mixed into
cement in advance and charged into the mixer. Aftercharging the materials into the mixer, the mixer was
rotated for 30 seconds to mix the materials. Then, thewater added with AE-WRA was poured into themixer and mixed for 90 seconds.

to air bubbles in the fresh concrete by operating an air
meter, which causes volume change. Then, the aircontent in the concrete sample was measured to theorder of 0.1% based on Boyle's law. In this test, thetarget slump value and air content value were set at
12 ± 2.5 cm and 4.5 ± 1.5%, respectively.
Preparing of Test Specimens for ConcreteA 100 × 200 mm cylindrical specimen was
prepared for compressive strength test based onJapanese Industrial Standard JIS A 1132. A
cylindrical specimen was removed from the mold,and after that, the specimen was cured in water fromthe time of specimen preparation until 28 days later.
The loading surface (upper surface) of cylindrical
specimen was ground with a polishing grinder so thatthe specimen loading surface (upper surface) became
flat. In addition, a 100 × 100 × 400 mm prismatic
specimen was prepared for length change
measurement. The prismatic specimen was removed
from the mold, and then cured in water for 7 days
from the time of specimen preparation.

Slump Test and Air Content Test
The slump test and air content test were conducted
immediately after the fresh concrete was made.
The slump test and air content test were conductedbased on Japanese Industrial Standards JIS A 1101
and JIS A 1128, respectively. In the slump test, first,
the fresh concrete was filled into the slump cone inthree times. The fresh concrete in each layer was
struck 25 times with a rod, and after the fresh concretein the third layer was struck, the fresh concrete wasmade flat to match the top edge of the slump cone.
When the top surface of the fresh concrete was lower
than the that of the slump cone, the same concrete
sample was added into the slump cone. Next, theslump cone was quickly lifted vertically at a constant
speed, and the slump value was measured 0.5 cm unit
in the center of the concrete. In the air content test,
the air content in fresh concrete was measured basedon the air chamber pressure method using a
Washington-type air meter. As a method of aircontent test, fresh concrete was filled into the aircontent measuring container in the same way as theabove-mentioned slump test, and the side of container
was tapped with a wooden mallet. The fresh concrete
protruding from the container was removed and the
top of the concrete was leveled. Next, after the lid was
attached to the container, high pressure was applied

Compressive Strength Test
After 28 days in water curing of the specimens,
the compressive strength test was conducted based onJapanese Industrial Standard JIS A 1108. The
compressive strength was calculated by the following
Eq. (1).
𝑓𝑐 (N⁄mm2 ) =𝑃
π𝑑 2 ⁄4(1)

where “fc” is the compressive strength, “P” is the
maximum load, and “d” is the diameter of thecylindrical specimen measured by a caliper. The
compressive strength test was conducted three times
for each mix, and the mean value was adopted for thetest results.
Length Change Measurement
The length change of concrete due to drying
shrinkage was measured based on the contact gauge
method of Japanese Industrial Standard JIS A 1129.
As the procedure of the length change measurement,
contact tips were affixed to the specimen after curing
so that the base length of the tips was 100 mm near
the center of the specimen. The contact chips wereTable 2 Mix proportions of concrete (kg/m3)

Blank
WBA

Water

Cement

175
175

318
286

Woody
Bottom Ash
0
32
340

Fine
Aggregate
734
731

CoarseAggregate
992
988

AE-WRA
3.18
5.73

SEE-Mie, Japan, Nov.10-12, 2022

affixed at two locations on both sides of each sideadjacent to the concrete placing surface of thespecimen. After that, the concrete specimens werestored in a room at 20°C and the length change of theconcrete specimens was measured. The length change
measurement was conducted at 1, 7, 14, 28, and 56
days after the specimens were cured in water. Fig. 3
shows the specimen after contact tips were attached.

Table 3 shows the slump value and the air content
value of Blank concrete and WBA concrete. The
slump value and the air content value for both fresh
concretes were within the target range. From theresults, it was found that when 10% of the mass of
cement used in Blank concrete was replaced with thewoody ash, the slump value of WBA concrete
equivalent to that of Blank concrete could be ensured
by adding 0.8% more the air entraining and water
reducing agent than the Blank concrete. Fig. 4 andFig. 5 show the shapes of Blank concrete and WBA
concrete after the slump test, respectively. When the
shapes of Blank concrete and WBA concrete werecompared after the slump test, there was not any
significant difference. Therefore, from the results ofthe slump test and the air content test, it can be said
that WBA concrete has a slump and air content
without any problems in construction. These facts are
consistent with those described in [9] and [10].

Fig. 3 The specimen after contact tips wereattached

Table 3 Slump value and air content value for Blank
and WBA concretes

Heavy Metal Leaching Test
As has mentioned above, the concrete has theperformance to prevent the leaching of heavy metals.
However, there are few studies on the leaching ofheavy metals from concrete mixed with woody ash
when it is demolished. Therefore, in this study, theheavy metal leaching test on the crushed concrete wasconducted based on the Environmental Agency
Notification No.46. First, a concrete specimen was
crushed with an electric hammer. The crushed one
was subjected to sieving with a 2 mm mesh opening,
and the one which passed through it was utilized as asample for the leaching test. Next, 50 mL of distilledwater was poured into the centrifuge tube, and 5 g of
the sample was also added into the centrifuge tube. It
was defined as the specimen in this test and shaken
for 6 hours at 200 rpm at 20°C. After shaking, thespecimen was allowed to stand for 30 minutes andthen centrifuged at 3000 rpm for 20 minutes. Aftercentrifugation, the supernatant solution of the sample
was filtered through a membrane filter with 45 µm ofpore size, and the concentration of heavy metals in thefiltered solution was analyzed. Cr (VI) and F wereanalyzed by a monomeric water analyzer based on
diphenylcarbazide spectrophotometry, and As wasanalyzed by ICP-AES. The solution analyzed by ICPAES was acidified by adding a small amount of nitricacid as a pretreatment. The leaching test was
conducted three times, and the mean value ofconcentrations analyzed was adopted as the test
result.

Blank
WBA

RESULTS AND DISCUSSION

Slump value
(cm)
12.5
14.0

Fig. 4

Shape of Blank concreteFig. 5

Shape of WBA concrete

Air content value
(%)
5.5
5.5

Result of Compressive Strength Test

Slump and Air Content of WBA ConcreteFig. 6 shows the compressive strengths of Blank
341

SEE-Mie, Japan, Nov.10-12, 2022

concrete and WBA concrete. The compressive
strength of WBA concrete decreased by about 19%
compared to that of Blank concrete. The reason why
the compressive strength of WBA concrete decreased
is considered that the binding force between
aggregates decreased by the reduction of cement
content in concrete. From the result, it was confirmedthat the woody bottom ash did not contribute to thedevelopment of compressive strength for the concreteat the age of 28 days. However, the compressive
strength of WBA concrete is 25.6 N/mm2, which
exceeds 24 N/mm2, one of the standard design
strengths applied to concrete structures in Japan.
Therefore, even when 10% of the mass of cement
used in ordinary concrete is replaced with the woody
ash, it is possible to use WBA concrete in the same
way as ordinary concrete. According to the report[11], even though the amorphous components were
not detected in the woody bottom ash, the long-term
strength of the mortar mixed with woody bottom ash
increased and exceeded the strength of the normal
mortar. Therefore, it is considered that further
examination such as the long-term water curing of
concrete is needed to obtain more clear knowledge on
the strength development of WBA concrete.

Compressive strength（N/mm2）

35.0

Fig. 7 Result of length change measurementof measurement, respectively. This suggests that thedrying shrinkage of concrete can be suppressed byreplacing cement used in concrete with woody ash.
However, it is necessary to clarify the relationshipbetween the amount of woody ash substitution for
cement and drying shrinkage in the future because it
is not clear how much cement to be replaced withwoody ash is rational and economical.
Result of Heavy Metal Leaching Test
Table 3 shows the concentrations of As, Cr (VI)and F leached from each concrete. From Table 3, it
can be seen that the leaching amount of heavy metals
from WBA concrete is equivalent to that from Blank
concrete. This fact suggests that there is no significant
difference in the amount of leached heavy metals
between concrete with and without woody ash
containing heavy metals. The soil environmental
quality standard values in Japan for As, Cr (VI) and F
are 0.01 ppm, 0.05 ppm and 0.80 ppm, respectively.
In this test, the concentrations of As and Cr (VI)leached from all concretes sample exceeded the soil
environmental quality standard values in Japan. In
this study, it is considered that the concentrations ofheavy metals exceeding the soil environmental
quality standard values in Japan were leached because
the leaching test was conducted for the finely crushedconcrete. These facts are consistent with thosedescribed in [12]. Therefore, when WBA concrete isdemolished, it is considered that the treatment to
reduce the leaching amount of heavy metals fromWBA concrete is needed.

31.4

30.0

25.6

25.0
20.0
15.0
10.0
5.0

Table 3 Result of heavy metal leaching test (ppm)

0.0
Blank

Fig. 6WBA

As
Cr(VI)F

Result of compressive strength test (28 days)

Results of Length Change Measurement
Fig. 7 shows the length changes of Blank concreteand WBA concrete. From Fig. 7, the shrinkage ofWBA concrete was about 20% and 7% smaller thanthat of Blank concrete on 14 and 28 days after the start

Length Change（×10-6）

WBA
0.23
0.05
<0.40

CONCLUSION
In this study, the fresh property and physicalproperties after hardening, such as strength and lengthchange were measured for ordinary concrete (Blank)and concrete mixed with woody bottom ash (WBA)to examine the feasibility of using WBA concrete.
Furthermore, the heavy metal leaching test was
conducted to assess the environmental load caused by
WBA concrete.

0.0
Blank
-100.0

Blank
0.24
0.07
<0.40

WBA

-200.0-300.0 From the results of the slump test and the aircontent test, it was proven that WBA concrete has
slump and air content without any problem inconstruction.

-400.0
0

7

14

21

28

35

42

49

56

Age（days）

342

SEE-Mie, Japan, Nov.10-12, 2022

Flowable Fill, Journal of Materials Science andChemical Engineering, Vol.4, No.7, July 2016,
pp. 101-114[3] Chowdhury S., Mishra M., and Suganya O., The
incorporation of wood waste ash as a partial
cement replacement material for making
structural grade concrete: An overview, Ain
Shams Engineering Journal, Volume 6, Issue 2,
June 2015, pp. 429-437[4] Raheem A. A., Adenuga O. A., Wood Ash from
Blead Bakery as Partial Replacement for Cementin Concrete, International Journal of Sustainable
Construction Engineering & Technology,
Volume 4, No 1, 2013, pp.75-81[5] Batt A. S. and Garg A., Partial Replacement ofWood Ash with Ordinary Portland Cement andFoundry Sand as Fine Aggregate, Journal of
Civil & Environmental Engineering, Volume 7,
Issue 2, January 2017[6] Obernberger I., Biedermann F., Widmann W.,
and Riedl R., Concentrations of inorganic
elements in biomass fuels and recovery in the
different ash fractions, Biomass and Bioenergy,
Volume 12, Issue 3, 1997, pp. 211-224[7] Gougar M. L. D., Scheetz B. E., and Roy D. M.,
Ettringite and C-S-H Portland cement phases for
waste ion immobilization: A review, Waste
Management, Volume 16, Issue 4, 1996, pp. 295303[8] Sklivaniti V., Tsakiridis P. E., Katsiotis N. S.,
Velissariou D., Pistofidis N., Papageorgiou D.,
and Beazi M.,Valorisation of woody biomassbottom ash in Portland cement: A
characterization and hydration study, Journal ofEnvironmental Chemical Engineering, Volume 5,
Issue 1, February 2017, pp. 205-213[9] Elinwa A. U., Mahmood Y. A., Ash from timber
waste as cement replacement material, Cement
and Concrete Composites, Volume 24, Issue 2,
April 2002, pp. 219-222[10] Abdullahi M., Characteristics of Wood
ASH/OPC Concrete, Leonardo Electronic
Journal of Practices and Technologies, Issue 8,
January-June 2006, pp. 9-16
[11] da Luz Garcia M., Sousa-Coutinho J., Strengthand durability of cement with forest waste
bottom ash, Construction and Building Materials,
Volume 41, April 2013, pp. 897-910[12] Eckbo C., Okkenhaug G., Hale S. E., The effects
of soil organic matter on leaching of hexavalentchromium from concrete waste: Batch andcolumn experiments, Journal of Environmental
Management, Volume 309, May 2022, 11470

 Although the compressive strength of WBA
concrete was slightly lower than that of Blank
concrete, it exceeded the standard design strength
in Japan.
 The drying shrinkage of concrete was suppressedby replacing cement used in concrete with woody
bottom ash.
 The leaching amount of heavy metals from WBA
concrete was equivalent to that from Blank
concrete. In the meantime, the concentrations ofheavy metals exceeding the soil environmental
quality standard values in Japan were leachedbecause the leaching test for the finely crushedconcrete was conducted.
These findings indicated that the physicalproperties of WBA concrete after hardening are notsignificantly different from those of Blank concrete.
On the other hand, there is a possibility that theconcentrations of heavy metals exceeding the soil
environmental quality standard values in Japan areleached from the demolished WBA concrete.
Therefore, it can be said that the woody ash can beused as a concrete material by treating the demolished
WBA concrete to reduce the leaching amount ofheavy metals. However, it is not clear how muchcement to be replaced with woody ash is rational andeconomical. For this reason, it is necessary to clarify
the relationship between the amount of woody ash
substitution for cement and the properties of WBA
concrete, such as the strength development anddrying shrinkage, in the future. Additionally, further
examination such as a long-term water curing of
concrete is needed to obtain more clear knowledge on
the strength development of WBA concrete.
ACKNOWLEDGMENTS
This work has been supported by JSPS
KAKENHI Grant Number JP20K04684. Also, incarrying out this study, Amron Corporation provided
woody ash. We express our gratitude here.
REFERENCES[1] Siddique R., Utilization of wood ash in concrete
manufacturing, Resources, Conservation andRecycling, Volume 67, October 2012, pp. 27-33[2] Yang Z., Huddleston J., and Brown H., Effects ofWood Ash on Properties of Concrete and343

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

TECHNOLOGY FOR IMPROVING OCTOPUS RESOURCEPRODUCTIVITY USING ARTIFICIAL REEFS AND AI

1Takafumi Yamamoto1, Yoshihiro Suenaga2, Tetsuya Tamaki2, Shinichiro Okazaki2, Hidenori Yoshida2
Graduate School of Engineering, Kagawa University, Japan; 2 Faculty of Engineering and Design, Kagawa
University, Japan
ABSTRACTIn recent years, the decrease in the catch of useful fish and shellfish has become serious in Japan. In particular,
in the Seto Inland Sea area including Kagawa Prefecture, we have focused on octopus as a useful fishery resource
since 1999, and have been trying to increase and cultivate it in the actual sea area. In addition, there is a growing
demand for fishery cooperatives and fishermen in the Setouchi region to increase octopus’s production and catch.
Therefore, in this study, we focused on the porous substrate attached to the artificial reef that was developed by
the authors and is effective in improving the productivity of fishery resources, and examined the conditions
necessary for octopus to inhabit the artificial reef. First, we conducted octopus breeding experiments and examinedthe ecology of octopus, such as preferring concrete substrates to unglazed jars commonly used in octopus fishing.
Next, we aimed to develop a technology for improving the resource productivity of octopus by proposing a
structure suitable for octopus and examining a method for discriminating octopus using AI. In this study, weinvestigated the aggregation of octopus by diving in the sea area where artificial reefs were installed, andquantitatively evaluated the amount of prey organisms and seaweeds attached to the structures. In addition, byusing AI, we will develop a method for discriminating octopus in the sea, quantitatively evaluate the distribution
area of octopus and the utilization rate of artificial reefs, and proposed efficiently promotion method for recruit
octopus’s resources.
Keywords: Fishery resource, Productivity of octopus, Artificial Reef, Porous substrate, AI

INTRODUCTION

OCTOPUS’ HABITAT

It is becoming even more serious that the fisheries
catch is decreasing every year in Japan. Special
attention is placed on to valuable fisheries resources
such as octopuses (Octopus: Octopus sinensis) androckfish (Black Rockfish: Sebastes inermis, Red
spotted grouper: Epinephelus akaara etc.) in Seto
Inland sea area (i.e. Kagawa prefecture). It is
understood that the demand for octopus’ catch isincreasing based on surveys and interviews forfisherman and their union.
In this study, an artificial reef was developed andenvironmental conditions necessary for octopuses
was explored. This artificial reef is made of porous
material which provides adherence of preferable preyorganisms for fish juveniles and has a current control
function. It would form the better habitat for themwith these two remarkable functions.
Also, based on the research by the substrate selection
breeding experiment of octopus, it was found thatthey prefer concrete substrates to other materials (e.g.
glass, ceramics, iron etc.) as one of the environmental
conditions.
The study also examined the method to increase
productivity. AI was used for quantitative assessmentof the usage rates of artificial reef and distribution ofoctopuses in the case study area (Shinoo Bay and
Kamano Bay, Aji town, Kagawa Prefecture, Japan).

The ecology of octopuses and habitat conditions
were extracted and organized, and as a result, theconditions necessary for octopus’ habitat were (1)preferred substrate, (2) shape, and (3) securing of
seaweeds and feed organisms. We have conducted thesubstrate selection breeding experiment of octopus(octopus: Octopus sinensis). It was found that octopus
has a strong tendency to prefer concrete substrate tooctopus trap made of unglazed pottery (see Fig. 1). In
addition, octopuses have a habit of digging octopus
traps and holes and inhabiting in hiding, and it isgenerally accepted that female parents do not feed
and protect eggs in the habitat even during spawning.
From this, it was confirmed that octopuses prefer toinhabit concrete substrates and hole shapes. From theresearch by Kadowaki et al. 2018 [1], there was asignificant difference in the growth of octopus
depending on the presence or absence of seaweed (sealettuce), and it was concluded that the growth ofseaweed is preferable for the growth of octopus. From
this, it was decided that seaweeds are necessary forthe octopus’ habitat. Adult octopuses are carnivorouswith a strong appetite and prey on prey organisms
such as shrimp, crabs and fish [2], [3]. In addition, it
is said to eat shellfish, and it is said that small bivalves
can be pried open by the force of their arms, but ifthey do not open, they make a small hole in the shell344

SEE-Mie, Japan, Nov.10-12, 2022

and inject anesthetic poison from there to prey on it.
When these prey biomasses are inadequate, octopuses
may cannibalize each other or eat their own arms,
which is one of the factors that reduce octopus’
fecundity.

TEST METHODS
Hydraulic experiment
We verified these functions by two methods. One
is hydraulic experiment and the second is fieldresearch. In hydraulic experiment we arranged 1/25
scale model and visualized the flow situation aroundthe model. In field research we settled experimental
structure and some components of the structure forthe purpose of measuring the change of amount ofrooted seaweed and adhered prey organisms. In
hydraulic experiment we confirmed that many small
retention areas formed on the surface of the upper partof the structure (see Fig. 3). This area would
contribute to accumulation of spores of seaweed.

Fig. 1 Substrate selection breeding experiment
ARTIFICIAL REEF
We investigated the collection of octopus species
in structures aimed at protecting and nurturing fry andimproving the environment associated with thecreation of stable seagrass beds (see Fig. 2). The
structure integrates a porous body and a concrete
block foundation, and is also equipped with a growth
substrate that has a detachable function for creating
seaweed beds. The existing structures in Shinoo andKamano, Aji-cho, Takamatsu City, Kagawa
Prefecture and the surrounding sea area were used as
the survey sea area in this study.
We developed one structure that increases theseaweed rootage by its current control function. This
structure is made of one special porous material
which provides excellent adherence of preferable
prey organisms for fish juveniles. This structure
would form the better habitat for them with these tworemarkable functions.

Fig. 3 Hydraulic experiment of artificial reef
Installation of the artificial reef
We selected the installation area for theexperimental structures using the multi-levelnumerical model. Before installation, we conducted
the carbonation of porous materials because
carbonation is very effective for promoting prey
abundances and seaweeds seeds to adhere the porous
materials [4], [5]. We developed full scale
experimental structures in the area indicated in Fig. 4
in December 19th, 2020. Installation depth was 4-5 m
and the bottom sediment were sand and gravel. The
predominant direction of the tidal current in the
installation site was north and south.

Aji

Plain view

Side view(mm)Fig. 4 Study area (Aji-Kamano, Takamatsu City,
Kagawa Pref., Japan)
We settled 20 porous material specimen plates and2 concrete plates, 2 steel plates and 5 clusters ofstones and porous material for the purpose ofcomparison around the experimental structures andmeasured the quantity of adhered preferable preyorganisms in the specimens collected 4 times after the

Fig. 2 Artificial reef for octopus

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SEE-Mie, Japan, Nov.10-12, 2022

settlement. We confirmed the quantity of attachedseaweeds by mowing the surface of the experimental
substrates 7 times during April 2020 to May 2022.
Furthermore, we examined the number of fishes
aggregated around this experimental structure byvisual observation 2 times during the same period.

Learning method
1) Image preparation
Apart from the images to be verified, we used an
online search to prepare images of approximately 110
adult octopuses and 20 octopuses guarding their eggs
for this analysis. Assuming that an underwater
camera will be used in the future, we prepared a totalof 2,069 images by performing processing such as
blurring, rotation, inversion, hue conversion,light/dark conversion, and lowering the resolution [6].

Identification of octopuses in the sea using AI
Currently, the method of confirming the collectionof octopus is visual confirmation. However, due totheir habits, octopuses may be difficult to visuallyconfirm because they assimilate with surrounding
substrates or hide themselves. Therefore, in thisresearch, we tried to detect an object using AI [6]. We
propose a method for confirming the habitat ofoctopus using an underwater robot or an underwater
camera through object detection. In this study, as amethod of confirming octopus, image/video
recognition using object detection by AI was
performed. YOLOv5 is the latest object detection
method released in 2020, featuring fast dataprocessing speed and high accuracy. YOLO canidentify what kind of object is reflected in the image
by integrating the results of the data obtained by the
analysis of annotations. Annotation is a term that
expresses the act of adding additional informationthat explains the data to data such as sentences,images, sounds, and videos, or the information itself.
There are many annotation specifications, and theyvary depending on the work content of the target data.
Image/video recognition also includes object
detection, area detection, and image classification. A
typical annotation in object detection is a boundingbox. A bounding box is a box-shaped figure used todetermine the approximate range of each object in animage. Each bounding box has an axis that represents
its position in the image, and the possibility that what
is contained in that box is an object is also calculated
numerically. With this numerical value, it is possible
to judge whether the image in each box is an object ora background, and to estimate the size of the entire
object. By integrating the class probability and thebounding box, it is possible to roughly infer what kindof object is in what range in the image (see Fig. 5:
Octopus in blue box).

2) Annotation:
This time, we used an annotation tool calledlabelImg for a total of 2,069 images prepared in 1).
After starting labelImg, the image file was opened
and the image was selected. The bounding box of theoctopus was specified in the selected image, and the
YOLO format text file was saved. The classprobability here is octopus.
3) Preparation of Python:
YOLOv5 runs on Python, so we prepared a virtualenvironment. A dedicated file was created in the
personal computer, and the annotated image and thelabel text describing the axis were put in the specified
location in the file.
4) Operation with Anaconda Prompt:
YOLOv5 was started at the command prompt
called Anaconda Prompt. We entered the learning
code and spent 5 to 8 hours learning. After thelearning was completed, the image to be verified (theimage not used for learning) was put in the specified
place different from the file in 3). With Anaconda
Prompt again, I entered the verification code andverified it over 10 to 15 minutes.
RESULTS AND DISCUSSION
The abundance of prey organism settled on each
substrate
Quantity of the adhered preferable prey
abundances in the experimental porous material was
shown in Fig. 6. The adherence of prey abundance inand around the carbonation porous material (PMPS)
was 2-20 times larger against other substrates. Also,
the porous material with porosity 30% had the highest
quantity of adherent prey abundance [4], [5].
We conducted the fish catch around the artificial
reefs using fish net to confirm the fish bait those prey
abundances or not. The result of juvenile fish catches,it was verified the rockfish juvenile could feed theadherent prey abundance by dissecting their stomach.
We confirmed that the volume of them increased astime progressed. An example of a prey organisms isshown in Fig. 7.

Fig. 5 Detection of octopus by bounding box
346

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 8 Difference of attached Seaweed (shidamoku)
on the specimens on April 24th 2020. (PMP: Porous
material plate, PMPS: Porous material in the
structure)

Fig. 6 Temporal changes of adhered preferable preyorganisms wet weight biomass per unit volume after
36 months. (PMP: Porous material plate, PMPS: PMP
in the structure)

Fig. 7 The adhered preferable prey organisms
Attached seaweeds

Fig. 9 The adhered Seaweed on the Artificial Reefs

We observed that seaweed attached to the porous
material through the research on April 24th 2020 to
May 8th 2022. We confirmed the abundance of
attached seaweed (dry weight) on the porous material.
It was shidamoku (Sargassum filicinum Harvey), akind of brown algae. It decreased sharply from
October to November 2020. We call this algae
shidamoku hereinafter. Furthermore, we show thevolume of attached seaweed shidamoku on thesurface of porous material specimen and otherspecimens for comparison. The maximum value
39.0kg/m2-dw was indicated in the sample of theporous material in the experiment structure in April
24th and exceeded the remarkable value 14.1kg/m2dw in the porous material specimen plate (see Fig. 8).
Also, we confirmed the recovery of seaweed and it
was expected smooth growth of shidamoku in spring
season. From those results, the porous structure is theeffective base foundation for seaweed to root.
We observed extremely larger amount of seaweed
rooted on the upper part of the structure than someother materials. Furthermore, we measured large
amount of adhered preferable prey organisms on theseaweeds. An example of the adhered seaweeds on
the artificial reefs are shown in Fig. 9 and preyorganisms that have settled on seaweed leaves shownin Fig. 10.
It is considered that the porous structure of theartificial reef contributes to fixing the roots ofseaweed. Also, it was possible to verify that theseaweed itself serves as a feeding ground for fishjuveniles.

Fig. 10 Prey organisms that have settled on seaweed
leavesFish aggregation
We investigated the temporal change of theobserved number of fishes, such as Black Rockfish(Sebastes inermis), Red Seabream (Pagrus major)
and Thread-sail filrfish (Stephanolepis cirrhifer) andoctopus, aggregated around the artificial reefs. The
increase in black rockfish was especially remarkable.
Also, Redspotted grouper (Epinephelus akaara)
began to be observed during August 2020.
At the beginning of the survey, only about 5
juvenile rockfish were found per fish, but in 2020, 35
fish were also seen. In addition, the average bodylength is also on the rise, and although it was 8 cm onaverage at the start of the survey, it grew to an averageof 20 cm in 2020 (see Fig.11-12). It was found thatthe average body length gradually increased as theamount of collection increased, and there was apositive correlation. In the survey after October every
year, it became possible to confirm the inhabitation ofoctopus in the hole of the artificial reef. Also, octopus
would prey on shellfish that have settled on artificial
reefs. (see Fig.13). In particular, octopus was347

SEE-Mie, Japan, Nov.10-12, 2022

assimilated with the surrounding color and wasdifficult to confirm, but it was suggested that thisartificial reef is suitable for octopus’ habitat due to its
holes and porous structure.

convenient hiding place for foreign enemies evenwhen protecting octopuses’ eggs. Furthermore, thestructure in which artificial upwelling occurs makes
it easy to give fresh currents to eggs, so it can be said
that it is an environment in which both larvae andadults of octopus can easily inhabit. If the target
structure becomes established as a habitat for octopus,
it is possible to improve the fisheries resources
productivity. However, since these structures are
specialized for seaweed bed construction, we thoughtthat it was necessary to improve the structures moresuitable for octopus. This structure would provide
better habitat for fish juveniles both with many hiding
spaces realized by good rootage of seaweed andabundant prey organisms adhered to the porous
materials consisting the structure.

Fig. 11 Relationship between average body length(cm) of rockfish and aggregation amount (pieces)

Learning results by AI
First, some of the results of the first verification
are shown in Fig.14. The closer the number in thephoto is to 1, the better the accuracy. It can be said
that the accuracy is not good because both of figures
are 0.5 or less. In addition, it can be said that theaccuracy of left photo of Fig. 14 is low because there
are many areas that are identified as octopuses andsome of the reefs are misrecognized.

Fig. 12 Aggregation of rock fish in the artificial reefs

Fig. 14 Results of image verification (Accuracy
Left:0.49, Right:0.40)

Fig. 13 Aggregation of octopus in and around theartificial reefs

From the first learning result, we focused on the
spawning situation of octopus. Since the appearanceof octopus eggs does not change until hatching, thesecond learning added an image of the octopus
holding an egg mass as imparted information. The
appearance of protecting eggs was also classified into
the same classification as adults of octopus, and AI
was trained. Some of the results of the second
verification are shown in Fig.15 -17. Comparing Fig.
15 with the results of the first time as Fig. 14, it canbe seen that the accuracy is improved. Although it isa little, the range of object detection has narrowed,
and no misrecognition has occurred. The images ofthe octopus holding the egg mass were successfully
detected, and the accuracy was high at 0.73 (see Fig.
16), [7]. Since the octopus egg mass was used for thesecond time, the image verification in which theoctopus is assimilated with the surrounding
environment, failed to detect the object both times.
The accuracy was generally improved except for the

Results of collection in survey area
In the existing structures in the survey area,
seaweed epiphytes, prey organisms, and octopus’
collections were confirmed under the abovementioned conditions. In the biological collection
survey conducted in 2020-2022, it was confirmed thatrockfish and wrasse were as stable as before, and thatthe artificial reef function was maintained. As forseaweed, epiphytes of hondawara (Sargassum
fulvelus), etc. were confirmed. Especially inoctopuses, it was confirmed that they lived in twoholes of the 10 structures investigated, spawned, andpredated by shellfish. On the other hand, no collectionof octopus was found in the octopus trap used foroctopus fishing near the structure.
From the collection results, it was verified that thestructure functions as a "habitat" sufficiently, and thatthe characteristics of the target structure make it a348

SEE-Mie, Japan, Nov.10-12, 2022

effective for improving the production of octopus’
resources. Although the image recognition accuracyof octopus has improved by performing image
verification twice, it can be said that the number oflearning sheets is not sufficient because some images
cannot be detected with octopus. Since mollusks
behave unpredictably, it is also necessary to learn
various forms of octopus. In addition, we thought thatthe reason why the detection range of octopus waslarge in the verification image was due to theannotation method. The bounding box was used as theannotation method this time, but the long arm of theoctopus learns other information such as the
background as the octopus when the bounding box isselected. In order to detect octopus accurately, it isnecessary to try segmentation used for region
extraction and polygonal polygons.

images in which the octopus used for otherverifications did not cause anabolic action and theimages in which only a part of the body was hidden
and visible (see Fig. 17). It can be said that theaccuracy was improved by learning not only the adultoctopus but also the state of holding the egg.

Fig. 15 Results of image verification (Accuracy
Left:0.62, Right:0.46)

ACKNOWLEDGMENTS
This work has been supported by JSPS
KAKENHI Grant Number JP20K06209. Also, incarrying out this study, Nihon Kogyo Co., Ltd.
constructed artificial reefs and supported fieldreserach. We express our gratitude here.
REFERENCES[1] Kadowaki H., Fujiwara H., Kasedo T., Onoe T.,
Common octopus hanging basket farming andsuitable environment using horticultural pots,
Bulletin of Faculty of Fisheries, Kagoshima
University, Vol. 67, 2018, p.7-12.
[2] Yoshioka F., and Suenaga Y., Research on aquatic
resource breeding structures with environmental
control function, Technical Report, Departmentof Agricultural Eng., Faculty of Agriculture,
Kagawa University, pp.1-12, 2000, pp.9-12.
[3] Okutani T., ed., Japanese Octopus, Tokai
University Press, 2013, pp9-10.
[4] Kagawa University Setouchi Area ResearchCenter: Takamatsu City Aji-cho Shinoo area
Report of Artificial Reef, 2020-2021, pp.1-24.
[5] Kameyama T., Matsuyama T., Yasuoka K.,
Honjo T., Tada K. and Suenaga Y., Study on theCreation of Seaweed Beds by Artificial Reef
Includes the Porous Material, Recent Advancesin Marine Science and Technology - PACON
International, 2012, pp.29-36.
[6] Shahinfar, S., Meek, P., and Falzon, G. “Howmany images do I need?” Understanding how
sample size per class affects deep learning model
performance metrics for balanced designs inautonomous wildlife monitoring. Ecological
Informatics, 57: 101085, 2020.
[7] Uozu Aquarium: A word from the keeper, 2015.
http://uozu-aquarium.jp/hitorigoto/wpcontent/uploads/2015/06/kimura601.jpg

Fig. 16 Learning results of octopus holding an egg [7]Fig. 17 Image verification that octopus is assimilatedwith the surrounding environment
CONCLUSIONSIn this study, the octopus’ habitat and spawning
were confirmed on the developed artificial reef,indicating that it is an effective structure for octopus.
Since the octopus and the egg mass could berecognized by the image verification, it is consideredthat it becomes easier to find the octopus spawned in
the actual sea area at the time of spawning of theoctopus. After the discovery of octopus, theirproduction is carried out by artificially protecting andhatching octopus’ larvae, and artificially raising andreleasing octopus for about one month, which is said
to shift from floating life to submarine life. It is349

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

NUMERICAL AND ANALYTICAL STUDY FOR SOLVING HEATEQUATION OF THE REFRIGERATION OF APPLE
Dalal Adnan Maturi 1
1

Departement of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
ABSTRACTIn this paper, we study the mathematical Heat and Mass transfer model, Apple shipments from Australia to
England began to decline several decades ago. Due to a disorder known as "brown heart," which developed due toinsufficient cooling. When placed on deck, the apples are normally warm and must be refrigerated to keep them
fresh. Storing in the cold Breathing generates heat as well. This heat was thought to be the cause. The generation
successfully counteracted the apple's cooling, resulting in dark fruit. ''Brown Heart ".This was the issue that
resulted in the Awberry. To investigate how heat is distributed within a room. The location where heat is produced.
At first, Awberry assumed the apple was in the beginning.at a constant temperature In the suitable value, we canassume that this temperature is zero. Select a temperature scale from the drop-down menu. t = 0 is the current time.
It must be concluded that the generation of heat inside the apple is not ''Brown Heart "cause.
We now know that the brown core is caused by an excessive concentration of carbon dioxide and an insufficientamount of oxygen in the stockpile. It affects the metabolic activities that occur in apples and leads to a decrease intemperature separation. We have solved the heat equation for cooling apples using the method of separating
variables in addition to numerical methods and clarification of the results obtained, including comparing the exact
solution with the numerical solution. In terms of discovering analytical and numerical solutions, the approach isquite effective and useful.
Keywords: Heat Equation, Refrigeration of Apple, Numerical Method ,Matlab.

INTRODUCTION[10] used a control volume model to tackle theproblem. A similar correlation was utilized to explore
the same topic in reference [11], but this time withexperimental data rather than numerical simulations.
Young and Vafai [12] looked into the cooling ofheated blocks, focusing on the heat transfer process's
conjugate behavior. Fruit cooling is a conjugate heattransfer phenomenon, and a thorough understandingof the problem requires modeling and simulation, in
which the local air velocity fields, as well as themutual heat transfer between each fruit and thesurrounding cooling agent, are analyzed. Fuji apples
are often stored and chilled in rectangular crates withlateral holes to allow cool air to enter. The
temperature is normally controlled at or below
freezing.
Two consecutive apples will be separated byaround one diameter. As a result, the heat emitted by
the leading apple will almost surely delay the coolingof the following lining apples during the chilling
process. The influence of the leading apple on thefollowing apple as a function of the coolant air flow
can be used to investigate the overall cooling
performance of two apples.

To reduce post-harvest deterioration, agricultural
goods should be chilled from ambient temperatures totheir optimal storage temperatures [1]. After harvest,
there is a significant loss of fresh fruits due to rot andshriveling as a result of inappropriate storage andhandling conditions [2]. In practice, storage facility
managers frequently define and apply storage
conditions based on past experience, allowing for
certain product losses due to non-optimal storage
conditions. Local heat and mass transfer intensities
are usually overlooked while assuming global heatand mass transfer rates through product layers.
As a result, the complex interactions between
products in the same layer as well as between layers
are ignored. Computer modeling and computational
fluid dynamics have been used to investigate
challenges in the agriculture and food industries [1-5]. For decades, numerical and experimental methods
have been used to study conjugate heat transfer andfluid flow in a channel containing heated components[6-9]. Despite the fact that such issues were primarily
focused on the cooling of electronic components,
several post-harvest processing processes make useof the same problem configuration. The conjugate
heat transfer problem for laminar flow over a threeheated obstacle array.

HEAT EQUATION OF REFRIGERATION OF
APPLEThe nonhomogeneous heat equation becomes350

SEE-Mie, Japan, Nov.10-12, 2022

spherical because of the spherical geometry.
1 𝜕𝑢
1 𝜕
𝜕𝑢
𝐹
= 𝑟 2 𝜕𝑟 (𝑟 2 𝜕𝑡 ) + 𝜅 , 0 ≤ 𝑟 < 𝑏, 0 < 𝑡,
(1)
𝛼2 𝜕𝑡
2
where 𝛼 represents the thermal diffusivity, b
represents the apple's radius, 𝜅 is the thermal
conductivity, and 𝐹 is the heating rate (per unit time
per unit volume).When we try to employ variable𝐹
separation on Equation (1), we find that the 𝜅 It
prevents us from doing so. To get around this problem,
we ask the more straightforward issue of what occurs
after a very long time.
We expect a balance to be reached eventually, inwhich conduction takes the heat generated within theapple to the surface, where the environment absorbs
it. We hope for a steady-state solution 𝑤(𝑟) where
heat conduction removes the heat generated within
the apples. The differential equation in its most basic
form
1 𝑑
𝜕𝑤
𝐹
(𝑟 2 𝜕𝑡 ) = − 𝜅 ,(2)𝑟 2 𝑑𝑟𝑛 2 𝜋2𝑎2 𝑡

𝑛
∑∞
sin(
𝑛=1

𝐵

𝑛𝜋𝑟

𝑟

𝑏

2𝜃𝑏

𝐹

𝑏

𝜅

𝑛𝜋

) exp (− 𝑏2 )(10)
Finally, we use the initial condition u(r, 0) = 0 to
calculate the coefficients 𝐵𝑛 .Therefore,
−2 𝑏
𝐹
𝑛𝜋𝑟
𝐵𝑛 = 𝑏 ∫0 𝑟 [𝜃 + 6𝜅 (𝑏2 − 𝑟 2 )] sin( 𝑏 ) 𝑑𝑟 =𝑛𝜋3(−1)𝑛 + ( ) (−1)𝑛(11)The entire package is𝑢(𝑟, 𝑡)
∞
(−1)𝑛
2𝜃𝑏
𝑛𝜋𝑟
𝑛2 𝜋 2 𝑎2 𝑡
=𝜃+
∑
sin (
) exp (−
)
𝑟𝜋
𝑛
𝑏
𝑏2
𝑛=1

𝐹

+ 6𝜅 (𝑏2 − 𝑟 2 ) +
2𝐹𝑏3

∑∞
𝑛=1

(−1)𝑛

𝑛𝜋𝑟

𝑛 2𝜋2𝑎2𝑡sin( 𝑏 ) exp (− 𝑏2 )(12)
The temperature distribution due to the imposition of
the temperature on the apple's surface is given by the
first line of Equation 12. In contrast, the second line
raises the temperature due to interior heating.
𝑟𝑘𝜋3

𝑛3

Provides the steady-state value. In addition, just as we
added a transient solution to allow our solution tosatisfy the starting condition, we must have one here
as well, and the governing Equation
𝜕𝑤

𝑎2 𝜕

𝜕𝑣

= 𝑟 2 𝜕𝑟 (𝑟 2 𝜕𝑟 ).
First, solve Equation (3).
𝜕𝑡

𝐷

(3)

𝐹𝑟 2

𝑤(𝑟) = 𝐶 + 𝑟 − 6𝜅(4)
Because the answer must be finite at r = 0, theconstant D equals zero. Therefore, the steady-statesolution must satisfy the boundary condition w(b) =.
𝐹𝑏2

𝐶 = 𝜃 + 6𝜅(5)
We introduce a new dependent variable y(r, t) = RVin the transient issue (r, t). Equation 3 can be replacedwith Equation 3 thanks to the new dependent variable.
𝜕𝑦
𝜕𝑡

𝜕2𝑦

= 𝑎2 𝜕𝑟 2 ,The temperature 𝑢(𝑟, 𝑡)/𝑇0 within an
infinitely long cylinder at various points
𝑟/𝑏 and times 𝑎2 𝑡/𝑏2 that we heated to thebeginning temperature 𝑇0 temperature
uniformity After that, the surface was forced
to cool.
Returning to our original question of whether theinside heating is powerful enough to offset thecooling caused by refrigeration, we apply the secondline of Equation 12 to determine how much thetemperature deviates from what we predict. Becauseof this, the maximum temperature is found in thecenter of each apple, and it is the only one of its kind.
This problem has piqued your curiosity. Assumingthat the radius of the apple is b = 4 cm, a1 G/ =1.33105C/s, as well as a2.55 103 = 2.55 103 = 2.55 103 = 2.55 103 = 2.55 103=The temperature effect of heat generation isparticularly high at cm2/s.
When the temperatures within the apples reach
0.0232 C after around 2 hours, the temperature inside
the apples is small, only 0.0232 C.
Equilibrium. As a result, we must conclude that heatgeneration within the apples is not the cause of theFig. 1(6)

We can resolve The R(r) equation to become R(r)T(t)if we assume y(r, t) = R(r)T(t) and only have anegative separation constant.
𝑑2 𝑅+ 𝑘 2 𝑅 = 0,
which has the answer
𝑑𝑟 2

𝑅(𝑟) = 𝐴𝑐𝑜𝑠(𝑘𝑟) + 𝐵𝑠𝑖𝑛(𝑘𝑟)

(7)

(8)

Because the solution, Equation 8, must disappear at r
= 0 in order for v(0, t) to stay finite, the constant A
equals zero. However, because for every time = w(b)+ v(b, t) and v(b, t) = R(b)T(t)/b = 0, R(b) = 0. As aresult, 𝑘𝑛 = 𝑛/𝑏, and𝐵𝑛𝜋𝑟𝑛 2𝜋2𝑎2𝑡

𝑢𝑛 (𝑟, 𝑡) = 𝑟𝑛 sin( 𝑏 ) exp (− 𝑏2 )(9)
The entire solution is obtained via superposition,
which equals𝐹𝑢(𝑟, 𝑡) = 𝜃 + 6𝜅 (𝑏2 − 𝑟 2 ) +351

SEE-Mie, Japan, Nov.10-12, 2022

problem. brown heart's cause .Brown heart is now
known to be caused by an excess of carbon dioxide in
the storage hold and an insufficient amount of oxygen.
This environment, it's assumed, impacts the apple's
metabolic activities, leading to low-temperature
disintegration.
TRANSIENT CONDUCTION WITH A HEATSOURCE

Fig. 2

The following equation governs one-dimensionaltransient conduction (1).
By introducing the following nondimensional
quantities, we may reduce this equation to adimensionless form
𝑥
𝛼𝑡
𝜏= 2
𝐿
𝐿
𝑇 − 𝑇∞
𝜃=∑𝑇𝑖 − 𝑇∞−𝐹′′𝐿
𝜒=𝑘(𝑇𝑖 − 𝑇∞ )
𝜉=

𝐵𝑖 =
=

Source geometry for a one-dimensionaltransient heat transfer.

due to the equal spacing of the curves at The
temperature at which convection occurs isrepresented by the upper curve in Figure 3. The
temperature drops quickly at tiny levels of due toconvection and conduction. As the steady-state
temperature profile determined by the energy source
approaches, the temperature of the surface begins toclimb. The profile at the moment of lowest
temperature is displayed as a dotted line in Figure 4.
Running pdepe for a long time yielded the steadystate solution. The steady-state curve depicted in
Figure 4 was generated using bvp4c to corroboratethat finding.

ℎ𝐿
𝑘

𝐿2 𝐹
𝑘(𝑇𝑖 − 𝑇∞ )Where𝜃 = 𝜃 (𝜉, 𝜏) , 𝐿, is the domain length,𝑇𝑖 is
an arbitrary temperature that usually represents the
beginning temperature, 𝐹′′ is the heat flux, andfor𝑇∞ a convective boundary is the fluid temperature.
When a convective boundary condition is not
employed, is an arbitrary temperature that must
deviate from. The governing equation changes whenthese variables are included𝜕𝜃𝜕2𝜃= 𝜕𝜉 2 + ∑(13)𝜕𝜏Table 1 Input Values
Parameter

Value

BC

∑=𝟏

𝝃=𝟎

𝑩𝒊 = 𝟎. 𝟏

𝝃=𝟏𝜽(𝟏, 𝝉) = 𝜽𝒘
= 𝟎. 𝟓𝟓𝜃 = 𝜃𝑤IC

𝜽(𝟏, 𝝉)= 𝟏 − 𝟎. 𝟓𝟓𝝃

𝜕𝜃
= 𝜒𝑤
𝜕𝜉

𝟎<𝝃<𝟏

𝟒𝟏

𝟎<𝝉<𝟏

𝟏𝟎𝟏

Fixed TemperatureSpecified Flux

Convective𝜕𝜃= −𝐵𝑖𝑜𝜃𝑤𝜕𝜉The boundary at is represented by the negative
sign in the convective boundary condition, while thevalues at the wall are represented by the subscript.
Equation (13) is a parabolic partial differential
equation with one spatial dimension. Separation ofvariables is one approach of solution that is applicable
to a limited number of boundary conditions. This isan example of a solution of this typ
Fig. 3352

For the same data plotted against the spatial
coordinate with time as a parameter, onedimensional heat conduction using the data

SEE-Mie, Japan, Nov.10-12, 2022

in Table 1.

Fig. 4[4] Jun S., Sastry S., Modeling And Optimization Of
Ohmic Heating Of Foods Inside A flexible
Package, Journal Of Food Process Engineering,
Vol.28, 2005,pp. 417-436.
[5] Roy J.C., Vidal C., Fargues J., & Boulard T., CFD
Based Determination Of Temperature And
Humidity At Leaf Surface. Computers andElectronics in Agriculture, Vol.61, 2008,pp. 201212.
[6] Ortega A., Writh U.S. & Kim S.J, Conjugate
Forced Convection From Discrete Heat Source
On Aplane Conducting Surface: A benchmark
Experiment. Heat Transfer in Electronic Systems,
Vol.292, 1994 ,pp.25-36.
[7] Sablani S.S., Ramaswamy H.S. & Mujumdar A.S.,
Dimensionless Correlations For Convective Heat
Transfer To Liquid And Particles In Cans
Subjected To End-Over-End Rotation, Journal of
Food Engineering, Vol.34, 1997,pp. 453-472.
[8] Jensen B.B.B., Friis A., Prediction Of Flow In
Mixproof Valve By Use Of CFD - Validation By
LDA, Journal of Food Process Engineering,Vol.
27, 2004,pp. 65-85.
[9] De-bonis M.V., & Ruocco G. A., Generalized
Conjugate Model For Forced Convection Drying
Based On An Evaporative Kinetics, Journal of
Food Engineering, Vol.89, 2008,pp. 232–240.
[10] Davalath J., & Bayazitoglu Y. Forced
Convection Cooling Across Rectangular Blocks.
1987.
[11] Garron K., & Garimella S.V., Composite
Correlations For Fonvective Heat Transfer From
Arrays Of Three-Dimensional Obstacles,
International Journal of Heat and Mass Transfer,
Vol.40, 1997,pp. 493-498.
[12] Young T.J., & Vafai K., Convective Flow And
Heat Transfer In Channel Containing Multiple
Heated Obstacles, International Journal of Heatand Mass Transfer, Vol.41, 1998,pp.3279- 3298.
[13] Wazwaz A.M., The variational iteration method;a reliable tool for solving linear and nonlinear
wave equations, Comput. Math. Appl., 54 (2007)
926–932.
[14] Wazwaz A.M., A First Course in Integral
Equations, World Scientific, Singapore, (1997).
[15] Wazwaz A.M., Suheil A. Khuri, The variational
iteration method for solving the Volterra
integrodifferential forms of the lane-Emden andthe Emden-Fowler problems with initial andboundary value conditions, DE GRUYTEROpen Eng. (2015);5:31-41.
[16] Maturi A.D., Numerical Solution of System of
Two Nonlinear Volterra Integral Equations,International Journal of Computers &Technology, Vol12, No.10, 2014, pp.3967-3975.
[17] Maturi A.D., Bajamal. Z.A, AlGethami M.B.,
Numerical Solution of Volterra Integral Equationof Second Kind Using Implicit Trapezoidal,

Heat conduction in one dimension using datafrom Table 1. Figure 3 shows the same data
displayed versus time with location as aparameter.

CONCLUSIONS
The development and performance of acomputer algorithm that calculates latent and sensible
heat loads, as well as moisture loss and temperature
distribution in the environment, are presented in thiswork.
Apples should be refrigerated in quantity. Thisalgorithm was created as a helper for both the is a
refrigeration facility designer and operator who cansimulate a wide range of commodities. In addition,
the thermophysical properties of commodities andflow field parameters were discussed in thispaper.which regulates heat and mass transmission in
fresh apple.
ACKNOWLEDGMENTS
This paper was supported by the Deanship ofScientific Research (DSR), King Abdulaziz
University, Jeddah.
REFERENCES[1] Lopes D.C., Martins J.H., Lacerda Filho A.F.,
Melo E.C., Monteiro P.M.B., & Queiroz D.M.,
Aeration strategy for controlling grain storage
based on simulation and on real data acquisition.
Computers and Electronics in Agriculture, 63,
2008,pp.140-146..
[2] Mohsenin N.N. Thermal Properties Of Foods And
Agricultural Materials. CRC Press, New York,US. 1980.
[3] Sun D.S., Computational Fluid Dynamics (CFD)- A design And Analysis Tool For the Agri-Food
Industry. Computers and Electronics inAgriculture, Vol.34, 2002,pp.1-3.
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Journal of Advances In Mathematics, Vol8,
No.2,2014, pp.1540-1553.
[18] Maturi A.D., Adomian Decomposition Method
of Fredholm Integral Equation of the Second
Kind Using Maple, Journal of Advances In
Mathematics, Vol9, No.1,2014, pp.1868-1875.
[19] Maturi A.D., Application of Adomian
Decomposition Method for Solving of Fredholm
Integral Equation of the Second Kind, European
Journal of Science and Engineering, Vol9,
No.2,2014, pp.1-9.
[20] Sorkun H.H., Yalcinbas S., Approximate
solutions of linear Volterra integral equation
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[21] Maturi A.D., Malaikah M.H., Numerical
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[22] Maturi A.D., The Modified Decomposition
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Of The Second Kind Using Maple, International
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[23] Maturi A.D., Aljedani I.A., Alaidarous S.E.,
Finite Difference Method For Solving Heat
Conduction Equation Of The Granite,
International Journal of GEOMATE, Sept.,
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2186-2982 (P), 2186-2990 (O), Japan.
[24] Maturi A.D., Finite Difference Method For
Solving Heat Conduction Equation Of The Brick,
International Journal of GEOMATE, April,
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[25] Maturi A.D., Simbawa A.E., The Modified
Decomposition Method For Solving Volterra
Fredholm Integro-Differential Equation Using
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March Vol.18, Issue 67,2020, pp. 84-89.

354

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE INVESTIGATION OF BIOGAS PERFORMANCE AFTERPURIFICATION USING NATURAL ZEOLITE AND RICE-HUSK
BIOCHARAmbar Pertiwiningrum1, Margaretha Arnita Wuri2, Alva Edy Tontowi3, Andang Widi Harto4 and Misri
Gozan5
1

Faculty of Animal Science, Universitas Gadjah Mada, Indonesia; 2Center for Energy Studies, Universitas
Gadjah Mada, Indonesia; 3,4Faculty of Engineering, Universitas Gadjah Mada, Indonesia; 5Faculty ofEngineering, Universitas Indonesia, Indonesia
ABSTRACT

Renewable energy is expected to gain a larger share of Indonesia’s Mix Energy in 2030. To increase renewableenergy sharing in the energy mix, biogas technology is encouraged to improve its performance. The challenge isto purify biogas on the community biogas scale to overcome well-established technologies and the current heavily
fossil fuel-based energy. The study aims to investigate the effect of the substitution of natural zeolite with biochar
to decrease investment costs. For our analysis, the researchers used four different times in biogas purification: 10,
15, 20 and 25 minutes of adsorption time to find the best performance. The performance was measured frombiogas's CO2 and CH4 methane composition after biogas purification. In this study, biogas purification using
natural zeolite and rice-husk biochar decreased either CO2 or CH4 methane composition in biogas. It’s related tothe characteristics of adsorbents. The researchers concluded that the mesopore characteristic of the pore structureof biochar didn’t selectively adsorb CO2 molecules only by analysis using a surface area analyzer. The results
showed that natural zeolite and biochar have pore sizes of 4.74 and 3.26 nm respectively. Both of them were
dominated by meso-sized pore volume with a volume of 0.057-0.093 cc/g. The characteristic of adsorbent needs
to be improved to encourage the acceleration of biogas adoption in Indonesia.
Keywords: CO2 Adsorption, Rice-husk biochar, Biogas, Purification

INTRODUCTION

2019 [4]. To accelerate the implementation of thesepolicies, many plan actions to adopt renewableenergies have been conducted in Indonesia such as
biogas technology. Until today, the renewable energy
supply is still dominated by biofuels, biomass,hydropower, and geothermal. Meanwhile, the otherrenewable energies, wind energy, solar cell, andbiogas, have a very small share [5].
There are some challenges to biogas program
adoption in the energy mix policy in Indonesia [6].
Rachmawan [7] reported that there are still many
obstacles that can be classified as problems of (1)market, (2) economics and finance, (3) institutional,(4) technical, and (5) social and culture. From atechnical point of view, according to this study, thebiogas system was not capable to deliver gas, even ata distance of 10 m from the digester. Moreover, ingeneral, biogas did not meet the expected cooking andlighting needs of households [8]. It means the use of
biogas didn’t fully replace the use of fossil fuels.
Dintani [9] also reported that the implementation of
the communal biogas wasn’t able distributed to all
households due to biogas having low pressure.
The low pressure of biogas is caused by biogas
components that are not pure methane. Biogas
consists mainly of methane and carbon dioxide, butalso contains several impurities. To transfer biogasthat has high methane components, a major stepIndonesia has many plans to achieve greenhousegas (GHG) mitigation. Some policies and regulations
have been proclaimed to support the achievement of
this goal, including the National Action Plan on
Greenhouse Gas Emissions Reductions (RAN-GRK)
through Presidential Regulation No. 61/2011 [1] andInventory of Greenhouse Gases through Presidential
Regulation No. 71/2011 [2]. In the energy sector, thegovernment has determined the energy mix policy
which is also contained in Government Regulation
no. 79/2014. The main energy mix is organized asfollows: (1) new renewable energy is at least 23% in2025 and at least 31% in 2050, (2) the oil must be lessthan 25% in 2025 and less than 20% in 2050, (3) thecoal is at least 30% in 2025 and at least 25% in 2050,
and the last (4) the gas is at least 22% in 2025 and at
least 24% in 2050 [3].
Throughout 2019, Indonesia added 385 MW ofrenewable energy. The increase in the role ofrenewable energy substitutes for the declining shareof oil and natural gas. Renewable energy supply
keeps being pushed along with increasing concern
about the increase of fossil fuel prices and theenvironmental impact of fossil fuel. Unfortunately, interms of generation, renewable energy only
contributed to 12.2% of the installed capacity mix in
355

SEE-Mie, Japan, Nov.10-12, 2022

offered is a cleansing process to remove the tracecomponents or biogas purification. The presence ofthe other components in biogas causes a detrimental
effect on the structure of the downstream
implementation of biogas such as corrosion ofengines and lower calorific value and gas pressure. If
these components are removed, the purified biogas
would have high-quality methane and can be used fora wider variety of uses, either for cooking orelectricity or vehicle fuels. In this study, theresearchers focused on CO2 removal, as the biggest
impurities in biogas. As the CO2 component gas isremoved, the relative density decreases and thecalorific value increases [10]. The lower calorificvalue of biogas compared to natural gas is also thereason that biogas purification is important.
But, Sahota [11] also reviewed that biogas
purification in small-scale plants is too expensive due
to high investment costs for the pieces of equipment.
Thus, for now, a simple biogas purification needs tobe developed and can be developed by reduction of
the complexity of the control system and the use ofcheap material as adsorbent. Ryckebosch [10]reviewed the advantages and disadvantages oftechniques for the removal of CO2 and the adsorption
method is suitable for the small capacity of a biogas
plant.
The study aims to develop a simple biogas
purification system that uses an adsorbent-based
biowaste. As the researchers know, according to
Statistics Indonesia [12], rice husk, a major byproduct of rice milling industries, is abundant. To
capture CO2, rice husk is required to convert tobiochar. Biochar is a solid material obtained from thecarbonization of biomass. Biochar is non-expensive,
environmental-friendly, and can capture CO2 [13]. In
the previous study, the researchers investigated five
formulations with different ratios of zeolite and ricehusk based-biochar: A1 (100% of natural zeolite), A2(75%:25%), A3 (50%:50%), A4 (25%:75%), and A5(100% of biochar) to decrease carbon dioxide
composition. The substitution of 25% volume ofzeolite with rice husk-based biochar adsorbed CO2
optimally with a CO2 reduction of 43.13%. In thisstudy, the researchers investigated the effect of timeof adsorption on CO2 reduction in biogas purification
using the combination of 25% volume of biochar and
75% volume of zeolite.

Biochar preparation for biogas purification
The biochar and natural zeolite samples prepare
for biogas purification. In this study, the substitutionof a 25% volume of zeolite with rice husk-basedbiochar adsorbed CO2 was carried out. Biogas
purification was conducted in a packed second-level
bed column with a column length of 20 cm and adiameter of 3 cm. The placement of the adsorbent in
the column is sorted where the natural zeolite (75%volume) is at the bottom of the column then rice husk
biochar (25% volume) is on top for each column (Fig.
1).

Fig. 1The CO2 adsorption column in biogas
purification.

Four variations of adsorption time were carriedout (10, 15, 20, and 25 minutes). Biogas before andafter biogas purification were analyzed of CH4 andCO2 contents by gas chromatography. Sampling was
carried out in three repetitions for each variation
adsorption time. Sample names are following Table
1.
Table 1 Samples in the variation’s adsorption time
Adsorption time
Samples(minutes)
10
ZR1
15
ZR2
20
ZR3
25
ZR4
Surface Properties

METHODOLOGY
The specific surface area of adsorbents wasmeasured with a surface area analyzer using the N2
adsorption method to determine the macro andmicropore surface area.

Rice husk-based biochar production
The rice husk was collected from the paddy
farmers near Yogyakarta. The rice husk was sundried overnight and then pyrolyzed at the temperatureof 255oC for 3 hours in the furnace. After that, biochar
was characterized by a surface area analyzer.

RESULTS AND DISCUSSION
Carbon dioxide content in biogas

356

SEE-Mie, Japan, Nov.10-12, 2022

Carbon dioxide (CO2) is the biggest impurities inbiogas contents. In this study, the change in CO2
content in biogas between before and after biogas
purification represented that biogas purification run
well. It means the adsorbents, the combination ofnatural zeolite and rice husk biochar, were capable tocapture CO2. Our previous study reported that the
optimal adsorbents formula with a composition of
75% volume of natural zeolite and 25% volume ofbiochar for each column gave the highest CO2
reduction so in this study, for investigating thevariations of adsorption time, used the adsorption
composition.
Many references [13]-[14] reported that thevariation in adsorption time continually gavedifferent impacts on CO2 adsorption capacity. Figure
2 showed the correlation between adsorption time andCO2 reduction.

surface area by the substitution of 25% by volume ofnatural zeolite with biochar, which played an
important role in the capability of CO2 adsorption.
Therefore, surface area analysis was also conductedin this study.
Methane content in biogas
The consequence of the implementation of
biogas purification by CO2 adsorption is an increasein CH4 content in biogas [10]-[11],[15]. As the CO2
content in biogas is removed, the CH4 content
increases [10] and impacts the calorific value. Figure
3 showed the correlation between adsorption time andthe CH4 composition in biogas.

Fig. 3Fig. 2The different CO2 compositions of biogas
before and after biogas purification.

The different CH4 compositions of biogas
before and after biogas purification.

Unlike the previous studies, biogas purification
by CO2 adsorption has the effect of reducing CH4content at the same time. For all samples, biogas
purification by CH4 adsorption in the variations ofadsorption time (10, 15, 20, and 25 minutes) s
reduced CH4 content compared to CH4 content inbiogas before biogas purification. The highest CH4
reduction is shown by biogas purification with anadsorption time of 10 minutes, the trend is as same as
CO2 reduction. There is a decrease in CH4 content
from 426,727.56 to 266,451.89 ppm or with a CH4
reduction of 32.67% (Fig. 3). Above 10 minutes ofadsorption time, the adsorbents also captured CH4
molecules. Figure 2 shows that the CH4 also
happened after biogas purification for 15 minutes,
with a decrease in CH4 content from 420,435.56 to393,761.63 ppm or with a CH4 reduction of 7.26%.
For 20 and 25 minutes of adsorption time, there are a
CH4 reduction of 2.72 and 3.16% respectively. The
trend of the decrease in CH4 content is in line with thedecrease in CO2 content in biogas.
The facts showed that either natural zeolite or
rice husk-based biochar not only captures CO2
molecules but also CH4 in biogas. This phenomenon
can be explained further by investigating thecharacteristics of the adsorbents. This probably can

For all samples, biogas purification by CO2
adsorption in the variations of adsorption time (10,15, 20, and 25 minutes) succeeded reduce CO2
content compared to CO2 content in biogas before
biogas purification. The highest CO2 reduction isshown by biogas purification with an adsorption timeof 10 minutes. There is a decrease in CO2 content
from 246,370.98 to 140,107.09 ppm or with a CO2
reduction of 43.14% (Fig. 2). Above 10 minutes ofadsorption time, the adsorbents’ capability to capture
CO2 molecules is reduced. Figure 2 shows that theCO2 adsorption process occurred very fast in the first
10 minutes and became slow after 10 minutes. For 15
minutes of adsorption time, there is a decrease in CO2
content from 228,503.73 to 217,554.23 ppm or with a
CO2 reduction of 3.49%. For 20 and 25 minutes ofadsorption time, there are a CO2 reduction of 2.72 and3.16% respectively. There is a tendency for the CO2
adsorption ability to stagnate after biogas purification
is carried out for more than 10 minutes. It means the
combination of adsorbents undergoes CO2 adsorption
equilibrium at 15 to 25 minutes of adsorption. The
trend was consistent with the previous studies [13][14] of CO2 adsorption on biochar and natural zeolite.
The result predicts that there was an increase in357

SEE-Mie, Japan, Nov.10-12, 2022

be attributed to micro or mesopore surface area onadsorbents, which could promote the physisorption of
CO2 and CH4. To provide evidence of the mechanism
the physisorption of CO2 and CH4 has related toadsorbents characteristics so adsorbents’ surfaces aremeasured in this study.

Therefore, based on this study, biochar synthesis or
biochar pyrolysis becomes key factor to develop
micropore-sized adsorbent. Temperature of pyrolysis
must be investigated deeply for the further study. In
addition, surface modification and pore size control
are essential for CO2 capture selectively.

Surface area properties

CONCLUSIONS

Based on the experimental data showed that ricehusk-based biochar combined with natural zeolite
could be a promising framework for CO2 capture. But,
the use of rice husk-based biochar combined withnatural zeolite as adsorbents in the biogas purification
system still has to be developed further.
The BET surface area, total pore volume, andmicro and mesopores size were measured by a surface
area analyzer. The results are shown in Table 2. The
combination of adsorbents, natural zeolite and ricehusk-based biochar, adds the specific surface areasthat have a role in capturing CO2 when the biogas ispassed through the adsorption column at a gas
pressure of 5-7 bar. The CO2 reduction value by ZR1
is higher than the 100% volume of natural zeolite witha CO2 reduction of 25% [16].

Results from this study indicated that the
combination of natural zeolite and rice husk-based
biochar (with a volume ratio of 3:1) could be a
promising adsorbent for CO2 capture. The best CO2
adsorption was performed by adsorbents after 10
minutes of biogas purification and reached adsorption
equilibrium after 25 minutes of adsorption.
It’s also concluded that surface modification to
make micro-sized pores of the adsorbent is suggested
to be a concern for the next study. In this study, theadsorbents not only captured CO2 but also CH4
molecules at the same time and trend. The dominantmeso-sized pores on adsorbents caused adsorbents
were not selectively in adsorbing CO2 because CH4molecules belong to the meso-sized molecule with amolecule size of 0.38 nm.
ACKNOWLEDGEMENTS

Table 2 The adsorbents’ characteristics
Characteristics

NaturalzeoliteSpecific surface area
(m2/g)
Pore radius (nm)
Total pore volume (cc/g)
Micro-sized pore volume(cc/g)
Meso-sized pore volume(cc/g)

47.66

Rice
huskbasedbiochar
50.40

4.74
0.110
0.017

3.26
0.082
0.025

0.093

0.057

In this study, it is impossible to thank everyone
individually, so the researchers give our thanks to
many people and individuals who have assisted us
over the years, and to the colleagues, students andvolunteers who have similarly offered their support.
The researchers also wish to express our sincere
thanks to the Directorate General of Higher
Education, Ministry of Education and Culture for its
funding and support through the PTUPT research
grant.
REFERENCES[1] Government Regulation Number 79/2014.
National Energy Policy, 2014.
[2] Presidential Regulation Number 61/2011.
National Action Plan on Greenhouse Gas
Emissions Reduction (RAN-GRK), 2011.
[3] Presidential Regulation Number 71/2011.
National Inventory of Greenhouse Gases, 2011.
[4] Author H., A Book New York Publisher, Year,
pp.1-200.
[5] Institute for Essential Services Reform (IESR),IESR Publisher, 2019, pp.1-69.
[6] The Agency of the Assessment and Application
Technology, Center for the Study of Process
Industry and Energy (PPIPE), 2020, pp.1-70.
[7] Rachmawan B., Ridwan, Mohammad K.R.,
Andianto H., Yogana S.A., Suhono and Kutut S.,
Sustainability Challenge for Small Scale

However, the adsorbents have the potential
capability as the CO2 adsorption in biogas
purification, the adsorbents also can adsorb the CH4molecules. One possible reason is that due to bothnatural zeolite and biochar are still dominated by ameso-sized pore with a size pore diameter range of 250 nm (Table 2). For selective adsorbents that
capture CO2 molecules only, the adsorbents musthave a micro-sized pore dominantly. The dominantmeso-sized pores cause CH4 molecules to be captured
by adsorbents. Lee [17] observed the presence ofabundant narrow micro-sized pores has an importantrole in doing the best CO2 adsorption capacity.

358

SEE-Mie, Japan, Nov.10-12, 2022

Renewable Energy Use in Yogyakarta, Procedia.
Vol.17, 2013, pp.513-518.
[8] Florence L., Johnny M., Peter N.W., Jo S., andBedru B., Dis-adoption of Household Biogas
Technologies in Central Uganda., Energy for Sus.
Dev., Vol. 37, 2017, pp. 124-132.
[9] Dintani Y.N.N., Margaretha A.W., Ambar P.,
Rachmawan B., and Tiwi P.H., Technical andSocial Assessment of Biogas in Yogyakarta andGorontalo, Indonesia, in Proc. 2019 ICESE, Vol.
471, 2020, pp. 1-8.
[10] E. Ryckebosch, M. Drouillon, and H. Vervaeren,Techniques for Transformation of Biogas to
Biomethane, Biomass and Bioenergy, Vol. 35,
2011, pp. 1633-1645.
[11] Sahota S., Shah G., Ghosh P., Kapoor R.,
Sengupta S.m Singh P., Vijay V., Sahay A., Vijay
V.K., and Shekhar T., Reviews of Trends in
Biogas Upgradation Technologies and Future
Perspectives, Biores. Tech. Reports, Vol. 1, 2018,
pp. 79-88.
[12] Statistics Indonesia, Statistics Indonesia, 2018,
pp. 12[13] Cha, J.S., Park S.H., Jung S., Ryu C., Jeon J.,
Shin M., and Park Y., Production and Utilizationof Biochar: A Review, J. of Industrial and Eng.
Chem., Vol. 40, 2016, pp. 1-15.
[14] Xu X., Kan Y., Zhao L., and Xinde C., Chemical
Transformation of CO2 during Its Capture by
Waste Biomass Derived Biochars, Env. Pollution,
Vol. 213, 2016, pp. 522-540.
[15] Anne E.C., Bin G., and Ming Z., Carbon Dioxide
Capture Using Biochar Produced from Sugarcane
Bagasse and Hickory Wood, Chem. Eng. Journal,
Vol. 249, 2014, pp. 174-179.
[16] Margaretha A.W., Ambar P., Rachmawan B.,
Misri G., and Andang W.H., The Waste Recyclingof Sugarcane Bagasse-Based Biochar for Biogas
Purification. in Proc. JESSD, Vol. 940, 2021, pp.
1-6.
[17] Lee S. and Park S., A Review on Solid
Adsorbents for Carbon Dioxide Capture, Journalof Industrial and Eng. Chem., Vol. 23, 2015, pp.
1-11.

359

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

WATER AND SANITATION SERVICE: A PRIORITY TO IMPROVEQUALITY OF SLUM AREAS IN PONTIANAK CITYBASED ON STAKEHOLDERS’ PREFERENCES

1

Zulfa Amala1, Ahmad Soleh Setiyawan1, Prasanti Widyasih Sarli1, Prayatni Soewondo1, and Dion Awfa2
Faculty of Civil and Environmental Engineering, Bandung Institute of Technology, Indonesia; 2Faculty ofEnvironmental Engineering, Sumatera Institute of Technology, Indonesia

ABSTRACT
Water and sanitation facilities of an area are important aspects that affect the quality of life, health andenvironment. Pontianak City, Indonesia is known as the “Equator City.” There are 150.16 hectares of slum areasin this city. The existence of these slum areas is mostly due to the lack of basic facilities and infrastructure, andlack of public understanding about the importance of a healthy and quality environment. The government has madeefforts over the past 5 years to improve the quality of water and sanitation infrastructure in slum areas in order toachieve the 2030 SDGs and to ensure the universal accessibility of water and sanitation and their sustainable
management. This research was conducted to determine the priority of stakeholders in Pontianak City in improving
the provision of water and sanitation infrastructure in slum areas. The methods of Analytic Hierarchy Process(AHP) were used, with the approach referring to the Indonesian Minister of PUPR No. 14 of 2018 concerning
Prevention and Quality Improvement of Slum Housing and Settlements. The results (CR value < 0.1) showed that
the Pontianak City stakeholders prioritized 0.30 the provision of drinking water in slum areas, 0.25 solid waste
management, 0.23 wastewater management, and 0.22 environmental drainage. An in-depth priority study byvarious relevant stakeholders is needed to improve the quality of slum areas.
Keywords: Pontianak City, Slum area, Stakeholders, Water and sanitation

INTRODUCTION

weights of a number of criteria or options in relation
to a specific criterion in an approach that is bothstraightforward and easy to understand. Raters arestill able to determine whether one criterion is more
important than another, even if quantitative ratings
are not available. This method is simple, rational, andmost often used for weighting. In this paper, AHP isused in the consideration of priorities for improving
clean water and sanitation in the slum areas of thestudy site in Pontianak City. This makes it possible toidentify stakeholder priorities, and to compare themwith the current condition of clean water andsanitation management. As a result, valuable
information can be obtained regarding stakeholder
preferences and their impact on current existing
conditions and the appropriateness of water andsanitation management which may be conflicting.

Along with the development of Pontianak City,
the population of slum settlements has increased overthe last 5 years. It’s influenced by population growthand urbanization [1]. The resident built these areas
spontaneously and privately alongside the rivers andditches. It is well-known as "river culture" due to theadaptive characteristics of its residents in their
physical, social, and economic life [2]. There wereslum settlements of 70.51 hectares with various levelsof slum in 2015 (light, medium and heavy) and due tothe results of the latest regulation issued by the
Pontianak Mayor Decree Number 1063.1/DPRKP/2020, it becomes 150.16 hectares of slum
settlements with a light level. The existence of theseslum settlements in Pontianak is mostly due to thelack of basic facilities and infrastructure quality andalso lack of public understanding about theimportance of a healthy and quality environment [3].
Because of this failure, there will be serious
repercussions for both the health of humans and theenvironment. At a crucial stage in the process ofsanitation planning, the lack of involvement fromboth
governmental
andnongovernmental
stakeholders is one of the primary factors that
contributes to the problems [4].
The Analytic Hierarchy Process (AHP) technique
is one way to facilitate users' access to the relative

STUDY AREA
The study was conducted in three slum areas in
Pontianak City, namely the Panglima A. Rani Area
(RT 01, 02, and 03) in Tambelan Sampit Subdistrict,
RA Kartini (RT 01) in Tengah Subdistrict and Kayu
Manis in Sungai Jawi Luar Subdistrict (RT 04, 05,
and 08). The selection of this area refers to the Decreeof the Mayor of Pontianak Number 1063.1/DPRKP/Year 2020, which is the determination of slumareas in Pontianak City. The selection of the area is360

SEE-Mie, Japan, Nov.10-12, 2022

based on Deltares data where the area is in a water
sensitive area, besides that it also has thecharacteristics of a densely populated area, highpoverty rate, flood risk, and passes through drainage
channels or rivers.

consistency index. Logical consistency states ameasure of whether or not an assessment/weighting is
consistent in the pairwise comparison matrix. This
happens because of the inconsistency of respondents
in giving preferences [5]. One way to measureconsistency is through a consistency index (CI). n
represents the alternative being compared and λ max
represents the largest eigen value of the pairwise
comparison matrix.

RESEARCH METHODS
Data Collection Method
Descriptive research is used to describe theexisting conditions related to water and sanitation at
the study site. The survey method was used to collectprimary data, where closed-ended questions wereused as a tool. This is done to compare field
conditions with stakeholder priorities related toincreasing access to clean water and sanitation.
The existing condition data collection uses cluster
random sampling to ensure the probability of
respondents in the selected group. The Yamane
method was used to determine the number of samples
using the formula in Eq. 1. The total sample in thisstudy amounted to 127 households with a margin oferror of 10%. In Yamane's formula, refers to thesample size (n), population size (N), and margin oferror (e).
𝑛=𝑁
1 + 𝑁𝑒 2𝐶𝐼 =(𝜆 𝑚𝑎𝑥 − 𝑛)(𝑛 − 1)(2)

If the CI is 0 then the assessment decision is thesame as the number of criteria being compared. The
higher the CI value, the higher the level ofinconsistency of the comparison decisions that havebeen made. The consistency index of the randommatrix with a scale of 9 (1-9) and its inverse is called
the Random Index/RI. Based on Saaty and Vargas(2006) obtained the average value of the Random
Index as in Table 1 [6].
Table 1 Average value of random index
1
0

2
0

3
0,58

5
0,90

6
1,12

7
1,24

8
1,41

9
1,45

(1)
If the values of CI and RI have been obtained, then
the next step is to find the value of Consistency Ratio(CR) formulated by:Prioritization is needed to determine the level ofimportance and contribution of each exposure
indicator to its impact. Criteria and indicators forincreasing access and demand for drinking water,
environmental drainage conditions, facilities andinfrastructure for domestic wastewater management,
and solid waste management systems, refer to theIndonesia Minister of PUPR Regulation No. 14 of
2018
concerning
Prevention
andQuality
Improvement of Slum Housing and Settlements.
Stakeholders who responded include: Department ofEnvironment and Forestry (DLHK) of West
Kalimantan Province, Department of Environment(DLH) of Pontianak City, Department of Health(Dinkes) of Pontianak City, Department of Public
Housing and Settlement Areas (DPRKP) ofPontianak City, Department of Public Works andPublic Housing (DPUPR) Pontianak City, Head ofeach study location, Head of RW and nongovernmental groups.
A weighting method is required to determine thepriority of these indicators. Therefore, the method
used in this study is AHP because this method is
simple, rational and most often used for weighting
indicators. The type of questionnaire used for
determining priorities is a pairwise comparison
questionnaire. The principle that must be applied tothe pairwise comparison method is Logical
Consistency, the ratio of consistency by looking at the

𝐶𝑅 =

𝐶𝐼
𝑅𝐼

(3)

Next is to make a combined assessment, namely
by using the geometric mean [5]. X represents the
sample value and n represents the number of samples.
The geometric mean is formulated as follows:
𝐺 = 𝑛√𝑥1 × 𝑥2 × … × 𝑥𝑛

(4)

Data Analysis
The results of the closed questions and the AHP
were analyzed using descriptive statistics, andMicrosoft Excel was used for the processing andillustration of the results. The information that was
gathered, which was supported by documentation anddirect observation, will be used to describe the current
state of the slum area that is located in the area understudy [7].

361SEE-Mie, Japan, Nov.10-12, 2022

slum settlements in this study’s location did not meet
minimum water needs.
The management of domestic wastewater at the
study sites showed that the management was 100%
unsafe. As shown in Table 3, generally, households
that were located on the riverside were at the basic
level of sanitation, and households in the city were at
the level of shared sanitation. Moreover, the septic
tanks that the community owns did not meet technicalstandards. Meanwhile, in households that did nothave a septic tank, some directly discharged theirwaste into water bodies and drainage channels.
Therefore, the function of the drainage channel was
still mixed with domestic wastewater discharge. Thiswas made worse by the fact that there was still apractice of defecation in the river, the highest
occurrence being in the Kayu Manis Area. The
practice of defecating in public is one of the problems
that plague the developing world and is the root causeof the spread of diseases that cause diarrhea [10]. The
unsafe management of domestic wastewater can
produce high levels of nutrients in the waters andcause environmental degradation, such as
eutrophication [11].
The condition of solid waste in slum areas,
especially in the Kayu Manis and Panglima A. Rani
areas, which is located on the riverside, can be seenby the large mass of garbage scattered or piled in thearea. This is partly due to the habit of riverside
residents throwing garbage into the Kapuas River.
For household solid waste management, as shown in
Fig. 2, generally, the community collected theirwaste individually into containers that have been
provided at several locations. The wastetransportation system used was the HCS (Hauled
Container System) system. However, themanagement of solid waste transported to landfills
only reached around 53-87%. The community
managed the remaining household waste by burningand throwing their waste into the river.

RESULT AND DISCUSSION
Water and Sanitation in slum household
In this study, the classification of drinking waterrefers to the three-step ladder used by the
WHO/UNICEF Joint Monitoring Program (JMP),
piped water inside buildings, as well as otherimproved sources and unimproved sources [8]. Fig. 1
exhibit the source of drinking water in the study area
based on JMP classification. The use of community
drinking water is generally classified into the otherimproved sources category, where the source ofdrinking water is rainwater. The remainder is from
unimproved sources, where the source of drinking
water is refilled water and bottled water. However, in
the RA Kartini and Kayu Manis areas, some people
do not treat rainwater first. Rainwater is not always agood clean water source that is ready to be consumed;
physically, it does not have color, taste, and clarity,
however, rainwater is affected by the area where therain falls [9].

Area

RA. Kartini

Kayu Manis

Panglima A.
Rani
0%

20%

40%

Other Improved Source

60%

80%

100%

Unimproved Source

Fig. 1 Drinking water sources of households in slumareas based on the JMP three-ladderclassification (n=127).
Table 2 Clean water sources of households in slumareasHousehold
Water Source
River water
Portable water
Well water
Rainwater

Area
Panglima Kayu
A. Rani Manis
88
62
12
34
2
34
2
7

Table 3 Sanitation ladder of households in slum areas

No

RA.
Kartini
78
22
22

1
2
3
4

Table 2 shows that the majority of riversidehouseholds used river water directly without any
treatment. Households in the city used portable water,whereas wells and rainwater were also used forbathing and washing needs. According to the PUPR
standard Number 14/PRT/M/2018, a community's
minimum drinking water needs are < 60
liters/person/day. As much as 83% of households in

5

362

Sanitation
LadderSafety Managed
Basic
SharedUnimproved
Open
Defecation

Panglima
A. Rani
84%
2%
2%

Area
Kayu
Manis
66,2%
-

RA.
Kartini
30,4%
65,2%
-

12%

33,8%

4,3%

SEE-Mie, Japan, Nov.10-12, 2022

areas takes a long time.

Area

RA. Kartini

Table 4 Flood incidences of households in slum areas

Kayu Manis

Criteria

Panglima A. Rani

0%

20%

40%

60%

80%

Flood
incidences

100%

Flood
height
The flooddries upCollected and dumped to container
BurnedThrown into the river/time/sea/lakeFig. 2 Solid waste management of households inslum areas

Panglima
A. Rani
24%
Severaltimes a
year
Adult
knee
Half-day

Area
Kayu
Manis
47%
Once a
year
Adult
knee
Less than
1 hourRA.
Kartini
48%
Severaltimes a
year
Adult
knee
Less than
1 hourStakeholder’s Priority

Burning trash and throwing it in rivers due to alack of public awareness is a bad habit that can havelong-term implications. In most cases, children willmodel their behavior after their parents. If children
see their parents throwing trash into the river, there isa significant likelihood that the children will follow
in their parents' footsteps and do the same [12]. The
negative effects of littering can range from lessening
a city's appeal from an aesthetic standpoint topolluting waterways and ecosystems [13].
The drainage concept that is still widely applied isthe principle that rainwater needs to be dumped into
the river as soon as possible. This causes the river toreceive a load that exceeds its capacity, while notmuch water seeps into the ground [14]. Likewise, inthis study, not all households had drainage channels.
Especially in the Kayu Manis and Panglima A. Rani
areas, several community houses were located above
the river on stilts. In addition, the function of thedrainage channel was still combined with the disposalof domestic wastewater such as bathing and washing.
As much as 84.4% of households dispose of graywater in drainage channels.
Table 4 indicates the incidence of flooding in thestudied slum area. This research found that Panglima
A. Rani and RA. Kartini areas were more vulnerable
to flooding. Flood heights could reach the knee heightof adults, with the receding time being less than 1hour to half a day. At the study site, the factors that
influenced the amount of flooding/ puddle were thelack of drainage channels, drains for surface runoff,and high tides, especially in low-lying areas.
Flooding/puddle was also caused by the small
drainage potential of Pontianak City due to the area’s
flat topography. Therefore, the small drainage
potential and influence of rising tides causes the water
to flow slowly, so the process of determining flood

Standard and interest groups are the twocategories that can be used to classify the
stakeholders in the water and sanitation planning
process [4]. In this study, the opinions of interest
groups were obtained as stakeholders because they
are the most familiar with slum areas. Interest groups
include political parties, civic organizations, andresidents of the impact area. Each interest group has
its point of view for evaluating potential alternatives
and often has different relational systems ofpreference, thus creating competition and conflicts
based on different group values [15]. According to thepriority results by stakeholders shown in Table 5, theconsistency value obtained was 0.043. The CR value
was less than 0.1, so the results can be declaredconsistent. Therefore, the stakeholders’ priorities
according to priority weights are the provision ofdrinking water, followed by waste management,
domestic
wastewater
management,
andenvironmental drainage.
This information was used to create the decisionhierarchy structure shown in Fig. 3. From the existing
criteria, each indicator that supported stakeholders inpreventing and improving the quality of slum areas
was also identified.
Table 5 Priorities for increasing access to water andsanitation

363

No.

Criteria

1
2
3
4

Drinking water supply
Domestic wastewater
Solid waste
Environmental drainage

Priority
vector
0.30
0.23
0.25
0.22

Rank
1
3
2
4

SEE-Mie, Japan, Nov.10-12, 2022

Priority for increasing access towater and sanitation in SlumDrinking Water Supply(0.30)
Minimum drinking waterrequirement for eachindividual is fulfilled(0.18)

Safe access to drinking
water (0.12)

Solid Waste (0.25)

Domestic Wastewater(0.23)

Environmental
Drainage (0.22)

Technical requirements ofsolid waste management
system (0.19)

Technical requirements
for wastewater facilities
and infrastructure (0.13)

Environmental drainage
ability to drain waterrunoff (0.14)

Technical requirements
for solid waste facilities
and infrastructure (0.06)

Technical requirementsof wastewater
management system(0.10)

Availability ofenvironmental drainage(0.04)
Environmental drainage
construction quality(0.04)

Fig. 3 Hierarchy priority for increasing access to water and sanitation for households in slum areas
Fig. 3 shows the priority of stakeholders was asmuch as 0.30 in increased drinking water supply inslum areas. In supporting the increase in water supply,
stakeholders prioritize the minimum drinking waterrequirements for each individual being met, whichthen provides safe access to drinking water. The
existing condition of slum households, it shows that
there were still 83% of households whose minimum
water needs had not been met. Meanwhile, theprovision of secure access is still not fully fulfilled.
Households are still very dependent on rain water andrefill water to meet their drinking water needs. In fact,
the management of rainwater is still not well managed
by households.
In the second priority, 0.25 of stakeholders
prioritized solid waste management. Indicators
supporting the improvement of solid waste
management are the technical requirements of thesolid waste management system (domestic collection
and sorting, environmental collection, environmental
transportation, and environmental treatment) andtechnical requirements for solid waste facilities andinfrastructure (household-scale waste segregation,
TPS 3R, transportation facilities, transportation ofenvironmental scale waste, and TPST). From theexisting condition of slum households, 53-87% of
solid waste was transported to landfills. Somehouseholds still managed their solid waste bythrowing it into the river or burning it. Meanwhile,
only 10.6% of waste sorting activities were conducted,
with the selected waste being organic, plastic, or glass
waste.
In the third priority, 0.23 of stakeholders
prioritized domestic wastewater. The supporting
indicators include the technical requirements for
wastewater facilities and infrastructure (latrine/closet
connected to a septic tank and the availability of a
local or centralized sewage treatment system) andtechnical requirements for a wastewater management
system (basic, proper and safe services). Based on theexisting condition of slum households, households on
the riverside were still at the basic level of sanitation,and households in the city center were at the level ofshared sanitation. Meanwhile, households that did nothave a septic tank would directly discharge theirwaste into water bodies or drainage channels.
For the last priority, as much as 0.22 of
stakeholders prioritized environmental drainage. The
supporting indicators include the ability ofenvironmental drainage to drain water runoff, theavailability of environmental drainage, and thequality of environmental drainage construction.
Based on the existing conditions of slum households,
the availability of environmental drainage alreadyexisted, but it was still unable to accept high waterrunoff in cases of changes in the climate. In addition,
drainage channels were still mixed with domestic
wastewater which caused environmental pollution.
The majority of waterway managers and researchers
also concentrated their attention on the contaminants
that were already widely known to be present in urban
waterways. These contaminants include nutrients,
heavy metals, sediment, and various other types ofphysical and chemical contaminants. Freshwater
ecosystems are also affected by a variety of otherchemical properties of the water, such as the pH level,
electrical conductivity, and ionic composition [16].
Therefore, it is difficult from a management point ofview to identify urban pollutants and appropriately
control them [17]. Within urban areas, it has come toeveryone's attention that the imperviousness ofcatchment areas and the lack of drainage
infrastructure are significant factors that influence thewater quality, hydrology, and form of urban rivers[16].
However, despite the stakeholders’ expression on
the prioritization of clean water, there has not been an
increase in access to clean water and sanitation inslum households, as the domestic wastewater
management has a fairly severe condition, and thesanitation ladder is at the basic sanitation and sharedsanitation levels. Finally, domestic wastewater has
been indicated to contaminate the soil and/or the
Kapuas River.
364

SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSION[6] Saaty, Pengambilan Keputusan. Jakarta: Pustaka
Binaman Pressindo, 1968.
[7] W. M. Fatimah, P. W. Sarli, P. Soewondo, and N.
M. Zakiyya, Strategic thinking to improve
sanitation in Kampung Pelangi 200, Bandung
City: in comparison with Kampung JodipanKsatrian, Malang City, IOP Conf. Ser.: EarthEnviron. Sci., vol. 592, no. 1, p. 012018, Nov.
2020, doi: 10.1088/1755-1315/592/1/012018.
[8] A. Nastiti et al., Water And Sanitation In Urban
Slum: A Case From Bandung Municipality, West
Java, Indonesia, p. 15, 2013.
[9] K. Khayan, A. Heru Husodo, I. Astuti, S.
Sudarmadji, and T. Sugandawaty Djohan,
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The priorities for increasing access to clean waterand sanitation were determined based on stakeholder
perceptions. These priorities include drinking water
management (0.30), solid waste management (0.25),
domestic wastewater management (0.23), andenvironmental drainage management (0.22). The
existing conditions of water and sanitation in slumareas were still unsafe and unsustainable. Domestic
wastewater management and drainage had the highest
risk of affecting environmental quality. This indicatesthat the priority of stakeholders in slum areas has notbeen able to improve the quality of slum areas.
Therefore, stakeholders need to conduct deeper
studies on the priorities of clean water and sanitation
supply and management in slum areas. One of themis by considering improvements in the managementof the most at-risk priority to improve the quality ofclean water and sanitation in these areas.
ACKNOWLEDGMENTS
The authors would like to extend their gratitude
toward the Netherlands Organization for Scientific(NWO) and Indonesian Ministry of Education,
Culture,Research,andTechnology(KEMENDIKBUDRISTEK) for funding thisresearch. This research was part of the Resilient
Indonesia Slum Envisioned project (RISE). This
research was also supported by the Global Sanitation
Graduate School (GSGS) program.
REFERENCES[1] E. B. Santoso and L. V. Therik, Faktor Penentu
Bertempat Tinggal Pada Kawasan Kumuh Di
Kota Malang Berdasarkan Teori Doxiadis,
tataloka, vol. 18, no. 4, p. 261, Nov. 2016, doi:
10.14710/tataloka.18.4.261-273.
[2] M. V. Michiani and J. Asano, Physical upgradingplan for slum riverside settlement in traditional
area: A case study in Kuin Utara, Banjarmasin,Indonesia, Frontiers of Architectural Research,
vol. 8, no. 3, pp. 378–395, Sep. 2019, doi:
10.1016/j.foar.2019.03.005.
[3] A. Yamri, Studi Penanganan Terpadu Kawasan
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[5] R. Putra, Analisis Faktor Penentu Pengembangan
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Tangerang (Studi Kasus: Kecamatan Tangerang.
Bandung: Institut Teknologi Bandung, 2016.
365

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

IDENTIFICATION OF POTENTIAL URBAN SLUM SETTLEMENTS
TO IMPLEMENT WATER-SENSITIVE URBAN DESIGN
Nico Halomoan1, Ahmad Soleh Setiyawan1, Prayatni Soewondo1,
Prasanti Widyasih Sarli1, Dion Awfa2
1,
Faculty of Civil and Environmental Engineering, Institut Teknologi Bandung, Indonesia;
2
Department of Environmental Engineering, Institut Teknologi Sumatera, Indonesia

ABSTRACT
Slums are settlements that do not meet the quality standards of buildings, facilities, and infrastructures, andthis is affected by the increasing population and the strategic value of the city. Water sensitivity can be interpreted
as an effort to utilize the water cycle in sustainable water management. Manado city, Indonesia, has a strategic
location but still has slums and flood-prone areas. This study aims to identify urban slum areas in Manado City,
Indonesia, in the context of implementing water sensitive urban design (WSUD). The WSUD is an integration of
structural planning through an engineering approach. It combines several objectives of water cycle management
through engineering design approaches that are beneficial for water conservation, rainwater management, andimprovement of rainwater runoff quality, including flood control and environmental sanitation. Interviews andquestionnaires addressed to stakeholders and the community were carried out to identify urban slum area. Threeurban villages were reviewed as case studies by comparing settlements based on their topological characteristics,
namely hills, river banks, and coastal areas. The feasibility of implementing WSUD is carried out by looking at
the features of the availability of sanitation infrastructure, water management, potential disasters, and socioeconomic aspects. Based on the identification results, the environmental and water conditions of each site topology
indicate the need to provide adequate facilities with the application of WSUD.
Keywords: Identification, Manado City, Slum Settlement, WSUDINTRODUCTIONof the urban settlement planning concepts with theuse of a sustainable water cycle, one of which is
rainwater being used as a water source with thedevelopment of appropriate technology and design. In
the WSUD application, all aspects of the urban water
cycle are considered a valuable resource. WSUD also
takes an engineering approach through integration theurban water cycle, including rainwater, groundwater,
and wastewater management, as a resource that canbe stored on land, public spaces, or open spaces, forreuse or through filtration process [4].
This WSUD can be implemented as a stand-alone
system or combined with centralized rainwater andwaste distribution system[5]. The advantages of
WSUD are that floods can be utilized and mitigated,
protected forms of the environment, liveability can be
improved and it requires community commitment andunderstanding [6].
The research location identified was the city of
Manado, the capital of the province of North
Sulawesi, Indonesia. The city is located downstreamof the river and the coast which has 20 rivers, withfive of them large rivers flowing into Manado Bay,
where in 2014 there was a flash flood overflowing
Lake Tondano. This city has a slum location due tourbanization and population growth. The basis fordetermining the location to be studied is the Decree

Slum settlements arise due to minimal andinadequate facilities and infrastructure that not meetstandards in a developing municipality. The
inadequate public services including water, sanitation,and hygiene conditions that cause environmental
degradation and lack adequate water [1]. Physical andnon-physical characteristics, which do not meet therequirements, become the basis for formulating
criteria and indicators of slum symptoms. Physicalaspects include housing and settlement units andbuilding conditions. Non-physical aspects include
community behavior, legal, and business certainty.
This is the process of identifying the location of slum
settlements. Poor planning with poor infrastructure
and inadequate sanitation facilities for mosthouseholds has been one of the reasons[2].
Water sensitivity is an effort to prevent andmitigate runoff that is not handled/utilized in water
management, including water supply, sanitation, andflood protection, in realizing environmental
protection services that
ensurelong-term
sustainability, viability, and resilience. The watersensitive concept developed on a city scale is a watersensitive city applied in urban planning under Water
Sensitive Urban Design (WSUD) [3]. WSUD is one
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SEE-Mie, Japan, Nov.10-12, 2022

of
the
Mayor
of
ManadoNumber
163/KEP/LT.02/Bappeda/2015
concerningtheDetermination of the Location of Slum Settlement
Areas in Manado City based on the determination of
the location of slum areas in Manado City which
includes 25 sites in 9 sub-districts.
The implementation of WSUD in slum areas is
expected to result in the availability of alternative
water sources, this includes aquifer filling schemes,
captured surface and roof rainwater runoff, andrecycling. Through a fundamental approach toproactive, sustainable rainwater management
planning with environmental facilities management
design, it is possible to maintain environmental healthand improve community quality [3]. WSUD that has
been implemented currently is limited to common
residential areas. In contrast with the advantages of
WSUD and its applications, such as the use of green
roofs, and porous pavements, can actively operate in
mitigating flood risk and increasing city resilience[6],it is necessary to use it to slum settlements to improve
the quality of life, this has been done with visual
improvement in slum settlements to improve thequality of life [7]. WSUD which is applied to slumareas is expected to support improving the quality oflife and improving infrastructure. This study is
expected to see the initial potential of slum
settlements to implement WSUD applications.

representatives, this is done because one solution to
improving the quality of slum areas must be locationspecific [8]. Interviews attempt to ask a representative
group of respondents open-ended questions to obtain
qualitative responses [9]. In this study, structured
interviews were conducted with the head of the area,accompanied by a direct visit to the location.
Structured interviews to determine the location of thestudy were conducted with information fromsecondary data which was also taken into account byregional regulations and desk studies. The mainquestions asked were about the physical condition of
settlements, residents, disasters, and water andsanitation facilities in general in the area. The results
will be displayed descriptively and followed up withinterviews using a questionnaire at a later stage.
Identification of WSUD Implementation
Identification by questionnaire interview was
conducted on 93 household samples from a
population of 1345 households; the sample
calculation used the Yamane formula with a marginof error of 10%. The interview material focused onquestions related to the potential for implementing
WSUD in slum areas by reviewing the design
characteristics of the housing environment, thecondition of water management in the environment
and the socio-economic factors of the population. The
structure of the questionnaire questions will ask about
the design characteristics of the housing environment,socio-economic aspects, conditions for managing
sanitation facilities, as well as management
conditions and water availability.

METHODOLOGY
Slums Identification
Identification of slum settlement in location study
considers several factors, including physicalconditions, the potential for disasters, settlements,
population density, clean water and sanitation
facilities. The study desk data is deemed, this is basedon the Decree of the Mayor of Manado Number
163/KEP/LT.02/Bappeda/2015
concerningtheDetermination of the Location of Slum Settlement
Areas in Manado City, then several locations are
selected, which will be verified by visiting theselected area. , then search for information throughstructured interviews with regional management
stakeholders.
The method used to obtain information is a
structured interview method through field visits, thisis done in slum locations and coordination is carriedoutthroughmeetings
withcommunity

RESULT AND DISCUSSION
Three locations of slums settlements are
determined from several of locations contained in theregional regulations of Manado City, these locations
are located with different physical characteristics or
topologies, these locations are North Titiwungen
Village, Sario District on the sea side; Singkil Satu
Village, Singkil District which is a location with ahilly; Wawonasa Village, Singkil District with ariverbank. The basis for identifying the study sites canbe seen in Table 1. The characteristics of the threelocations have the potential water sensitivity incongested and slum areas with problems withsanitation infrastructure.

367

SEE-Mie, Japan, Nov.10-12, 2022

Table 1. General characteristics and conditions Study site
Criteria
LocationStudyofSettlement
Conditions
Topology

North TitiwungenLingkungan 02 dan half of
lingkungan 03 TitiwungenUtara Village
Residential density with adensity of 10,347 people/km2
Location flat land close to the
Sulawesi Sea and located in
the coastal area of the sea.
Frequent rob floods and no
flood protection.

Potential
Disaster

Location of Study
Singkil Satu
Lingkungan 2
Singkil Satu Village
Densely populated
settlements with a density ofaround 14,439 people/km2
Located on hilly land with asharp downward contour.
Potential landslide disaster

Drainage
Infrastructure
Condition

The drainage channels are
mixed with greywater fromhouseholds with some drains
containing garbage.

With inadequate drainage
channels, rainwater runoff isdifficult to drain and mixes
with greywater.

Wastewater
Infrastructure
Condition

Most of the houses alreadyhave family latrines withseptic tanks and a few use acentralized system from thenearest mall.
Most residents have been
served by the water drinking
water services company, but
it has not been continuous,
mainly using shallow anddeep well water.

Most of the houses havefamily latrines, there are no
public toilets.

Water
Infrastructure
Condition

Most residents use waterfrom pipe network services
provided by residents, someuse shallow and deep wells.

Wawonasa
Lingkungan 02 and 03,
Wawonasa Village
Densely populated settlementswith an average number of
15,872 people/km2
Situated on flat land very
close to the Tondano
watershed
Potential for flood disaster

The flow in the drainage
channel is disrupted by thepresence o garbage andgreywater mixed in thestream.
Most of the houses havefamily latrines with septic
tanks and there are public
toilets.
Most residents use water fromwells and rivers, and drinking
water company services are
inadequate, but houses still do
not have safe access.

Social and Economy Aspects
The condition of the house will also affect thereadiness to implement the WSUD, some applications
from the WSUD will modify the function of part of
the house such as changing the function of the roof,
yard or drainage channel, including harvesting
rainwater. Most of the houses in the study area werepermanent homes, but not all of them became
homeowners. The majority of Singkil Satu (68%) and
Wawonasa (50%) residents live in their own homes,
while in the North Titiwungen area, more than 48%
live with their families.
With the majority having permanent and private
homes, there is potential to be able to implement
WSUD in residents' homes (Fig. 2), because it isrecognized that there is a need for ownership andinvolvement in implementing WSUD thereby
increasing risk awareness and greatly influence thecommunity's decision to provide access to cleanwater and proper sanitation.

Social and economic aspects that support thisidentification analysis are income, employment, andhouse ownership. Economically, in the three areas
reviewed, households have a low average economic
capacity, with less than 33% of the population having
an income above 3 million per month (Fig. 1) . At thesame time, the most common occupations aretraders/entrepreneurs in each area. This will also
affect the availability and willingness to improve thequality of residential facilities owned.

Percentage

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

15%

73%

13%
North Titiwungen

32%

33%

46%

48%

22%

20%

Singkil Satu

Wawonasa

Area≤ Rp 750.000/month>Rp 3.000.001/month

Fig. 1

Rp 750.000 - Rp 3.000.000

Percentage of household economic income
capacity
368

SEE-Mie, Japan, Nov.10-12, 2022

Percentage

100%
80%

60%

95%

88%
68%

6%

23%

Centralized
system0%
Singkil Satu Wawonasa

Area

Fig. 2

Fig. 4

Rent

Private ownership

Permanent73%

Not know

North
Titiwungen

Family Ownership

1%

Septic tanks

48%

43%

26%

3%

Pit latrine

13%

8%

40%
20%

88%
40%

50%

Percentage of use of domestic wastewater
systemPercentage of household ownership in the
study area
Water Management

Sanitation Infrastuctures

The water supply aspect is considered in thisidentification. the majority of residents in North
Titiwugen use groundwater as a source of cleanwater, as well as most residents in Singkil Satu andWawonasa, only a few residents use tap water,
because it is not optimal in providing water (Fig.
2).On the other hand, as a source of drinking water,
the community prefers refilled water compared to
ground water or tap water. Based on these two
conditions, it is indicated the need for continuous
availability of water as a source of clean water; With
the implementation of WSUD, the potential use of
rainwater as a water source will support theavailability of water from pipelines and groundwater.

Some residents in the study area use inadequate
domestic wastewater management, although 97% ofresidents stated that they have private latrines (Fig. 3),
using septic tanks that are not waterproof which aregrouped as cubluk (Fig. 4), this has the potential tocause ground water pollution. The potential forcontamination can be reduced by carrying out further
treatment of effluent from sanitation facilities.
Several WSUD systems have been used to improve
the quality of rainwater by removing contaminants byeither infiltration or sedimentation methods[4]. The
combination of waste treatment in sanitation facilities
with WSUD facilities has the potential to improve thequality of the water produced.

60%
2%

50%

Percentage

1%

97%

40%

Fig. 3

Family or Neighbors Latrines

Public Toilet

48%

33%
27%

30%
20%
10%

Private Latrine

49%

20%
16%

16%

12%
6%

36%
29%

9%
2%

0%

0%

Singkil Satu

Wawonasa

North
Titiwungen0%

Ownership of private latrines at the study
area

Area
Water Purchased
Shallow Well Water
Rainwater

Drainage channel is one of the infrastructure for
WSUD implementation. However, the condition in
the study area shows that most of the drainage
channels are not functioning properly, because more
greywater is channeled into the canal. Anotherproblem is the inadequate width of the drainage
channel; blockage or clogging by garbage, oil andgrease from kitchen activities; Drainage channels thatare higher than the road cause inundation andflooding during the rainy season.

Fig. 5

Tap water
Deep Well Water

Percentage of water sources used byresidents

The aspect related to water management is thepotential for disasters caused by water. Wawonasa
area, which is very close to the Tondano watershed,
the potential for flood events often occurs during the369

SEE-Mie, Japan, Nov.10-12, 2022

rainy season; 60% of the community stated thatflooding occurred several times a year (Fig. 6), thisarea is prone to flooding. North Titiwungen is an areathat is very close to the Sulawesi Sea. Most of theflooding occurs when high tides occur, or the
potential for being affected by tidal flooding. On theother hand, in Singkil Satu, water only passes when it
rains, but no flooding occurs due to the area’s
contours. Regional topology also affects flood events,
the impact of flood events can be reduced if they canseep into the ground, and the application of WSUD inseveral flood-affected and inundated areas has thepotential to support the reduction of inundation due toflood events.
100%

0%

Percentage

CONCLUSIONS
The identification of the potential for
implementing WSUD in slum areas has been studied
in three slum areas in Manado City by conducting
surveys and interviews related to socio-economic
conditions,watermanagement,
sanitation
infrastructure and flood potential. Socio-economic
conditions are a challenge with the majority ofresidents earning below 3 million/month, but private
home ownership will support the potential
willingness to apply WSUD technology. The
condition of drainage and sanitation infrastructure has
not functioned properly, this needs to be supported bycommunity understanding and water availability.
People still rely on groundwater and do not use
rainwater, drinking water relies on refilled gallon
water, this technical condition has great potential in
the WSUD application, especially increasing theavailability of water for residents, but there needs tobe research on the potential of rainwater and soil
absorption. Seeing the challenges and opportunities
that exist, further research is needed by involving
technical studies and focusing on each location to findthe appropriate WSUD technology to be applied.

2%
0%

90%
80%

Another challenge is that the characteristics ofeach regional topology result in a more specificapplication, so further research is needed at thelocation to find the most suitable WSUD design to be
applied in each location.

23%
40%

70%
60%

3%

50%

98%

60%

40%
30%

58%

20%
10%

18%
0%

0%

North
Titiwungen

Singkil Satu

Wawonasa

Area
Once or several times a month
Several time a year
Once a year
Never

Fig. 6ACKNOWLEDGMENTS
This research was part of the Resilient Indonesia
Slum Envisioned (RISE) project 2021-2023. It was
funded by the Netherlands Organization for Scientific(NWO) and the Ministry of Education, Culture,
ResearchandTechnology(KEMENDIKBUDRISTEK).

Percentage of flood events at the study area

WSUD potential implementation
Based on the results presented, the potential for
implementing WSUD in slum areas in Manado City,
it is indicated that there are significant challenges but
there are still opportunities to be able to implement
WSUD. The first challenge is the high population
density with adjacent houses; this makes it difficult toprovide land for implementing WSUD; some design
options require land for infiltrated water and growing
vegetation. Another WSUD method is water
infiltration, where the limited drainage canal can beused as eco drainage for rainwater absorption, but
first prepared management for greywater andsediment barriers[10]. WSUD potential to be
implemented is rainwater harvesting used as potablewater, where the roof is used as a rainwater receiverand supports the supply of water as a backup for eachhousehold. Still, it is necessary to add a supporting
unit so that the water produced can be used directly
as a source of clean water.

REFERENCES[1] H. Taubenböck and N. J. Kraff, “The physicalface of slums: a structural comparison of slums in
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38, Mar. 2014, doi: 10.1007/s10901-013-9333-x.
[2] I. K. Tumwebaze, C. G. Orach, C. Niwagaba, C.
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4,
pp.
436–447,
Oct.
2020,
doi:
10.1016/j.oneear.2020.09.012.

370

SEE-Mie, Japan, Nov.10-12, 2022

Ksatrian, Malang City,” IOP Conf. Ser.: EarthEnviron. Sci., vol. 592, no. 1, p. 012018, Nov.
2020, doi: 10.1088/1755-1315/592/1/012018.
[8] P.
Jones,“Formalizing
theInformal:
Understanding the Position of Informal
Settlements and Slums in Sustainable
Urbanization Policies and Strategies in Bandung,Indonesia,” Sustainability, vol. 9, no. 8, p. 1436,
Aug. 2017, doi: 10.3390/su9081436.
[9] A. Davis, A. Javernick-Will, and S. M. Cook, “Acomparison of interviews, focus groups, andphotovoice to identify sanitation priorities andincrease success of community-based sanitation
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10.1039/C8EW00391B.
[10]
T. H. F. Wong and Engineers Australia,
Eds., Australian runoff quality: a guide to water
sensitive urban design. Crows Nest, N.S.W:
Engineers Media, 2006.

[4] A. K. Sharma, S. Rashetnia, T. Gardner, and D.
Begbie, “WSUD Design Guidelines and Data
Needs,” in Approaches to Water Sensitive Urban
Design, Elsevier, 2019, pp. 75–86. doi:
10.1016/B978-0-12-812843-5.00004-6.
[5] A. Sharma et al., “Water Sensitive Urban Design:
An Investigation of Current
Systems,
Implementation Drivers, Community Perceptions
and Potential to Supplement Urban Water
Services,” Water, vol. 8, no. 7, p. 272, Jun. 2016,
doi: 10.3390/w8070272.
[6] A. Dada, C. Urich, F. Berteni, M. Pezzagno, P.
Piro, and G. Grossi, “Water Sensitive Cities: An
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[7] W. M. Fatimah, P. W. Sarli, P. Soewondo, and N.
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City: in comparison with Kampung Jodipan-371

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE CHARACTERISTICS AND DISTRIBUTION OF DEEPGROUNDWATER IN DJIBOUTI
Yasuhiro Asakura1, Sawahiko Shimada1, Ko Hinokidani1 and Yasuhiro Nakanishi1
1
Tokyo University of Agriculture, Japan

ABSTRACT
Djibouti is one of the most arid areas in the world and rivers are not formed regularly in this region. So,
groundwater has been used as the main water resource for humans and livestock. Therefore, necessary tounderstand the state of groundwater in terms of utilizing of sustainable water resources in this country. In thisstudy, we measured ion contents (Li+, Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO2-, Br-, SO42-, NO3-, PO43-, HCO3- ) ingroundwater using ion chromatography, and analyzed characteristics groundwater quality using by multivariate
analysis based upon groundwater quality with stable isotope ratio of hydrogen and oxygen and tritium
concentrations, with reference to their locations and examined the distribution analysis using GIS data of watershed
maps. As a result of groundwater quality measurements, the most of groundwater samples in this study mixed withseawater or hot spring water and fossil seawater. And the concentration of NO3- in groundwater was over 50 mgL1 at 4 sites. In addition, as a result of the hierarchical cluster analysis, groundwater in this study showed different
chemical characteristics even in the same watershed. As results of this study, although some important data ofgroundwater quality in Djibouti has been obtained, it is considered necessary to study in groundwater dating andwater stable isotope ratios more wide area in order to understand its complex groundwater distribution and water
quality characteristics.
Keywords: Ion chromatography, Arid area, water resources, GIS, Stable isotope ratio
INTRODUCTION

conducted to find out groundwater quality, age andflow system, the data is still scarce for understanding
the spatial characteristics of groundwater in Djibouti[4] In press [5] [6]. Accumulating of the basic
database on the quality and the location of thegroundwater in Djibouti, which flows throughcomplex geological structures is necessary.
In this study, we analyzed characteristics ofgroundwater quality using multivariate analysis andhierarchical cluster analysis based upon ion structure(Li+, Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO2-, Br-,
SO42-, NO3-, PO43-, HCO3- ) with stable isotope ratioof hydrogen and oxygen (δ D and δ18O), and tritiumcontents with reference to their locations andexamined the distribution analysis using GIS data ofwatershed maps.

Djibouti is located at the northeastern end of theAfrican continent, called the "Horn of Africa", where
the climate is extremely arid belonging to the Hot
Desert or Semi-arid Climate of BWh in the Köppen
classification. The climate of this region shows two
seasons, a cold (winter) season from October to April
and a warm season (summer) from May to September.
Winters are relatively cool (20~30 °C) due to thenortheast trade winds blowing from the Gulf of Aden,
while in summer, the equatorial westerly winds blow
over the mountains from Ethiopia and Somalia, whichfurther enhances the hot and dry climate (35~45℃)
due to the foehn phenomenon [1]. As a result,
precipitation is extremely low (c.a. 150 mmyr-1), in
this region and occurs irregularly as a short time event.
Hence, rivers are not formed regularly in this region,and groundwater has been used as the main water
resource for humans and livestock.
In recent years, however, as the lifestyle ofnomads has shifted from pastoralism to a combined
agro-pastoralism [2][3], the demand for groundwater
resources, mainly for irrigation, has increased, andgroundwater pollution due to human impacts andstarvation of groundwater resources due to overpumping have become problems. Therefore, it isnecessary to understand groundwater conditions fromthe perspective of sustainable use of limited water
resources in this country with extremely low
precipitation. Although some studies have been

MATERIALS & METHODS
Sites description
We selected 16 deep wells from 4 areas inDjibouti: Djibouti city area, Arta, Ali-Sabieh, andDikihil. Djibouti city facing Tajoura Bay is the mosturbanized area in Djibouti. More than 60% of thenation is concentrated in this area. Arta area has oneof the largest wadis in the country called Ambli Wadi,
and most of the 250 wells are drilled along the wadi.
Ali-Sabieh area is close to Somalia and has over 300
wells drilled. Dikihil area is close to Ethiopia and has
372

SEE-Mie, Japan, Nov.10-12, 2022

potential (ORP), and dissolved oxygen (DO) ingroundwater samples were measured at study sites
using portable instruments.
The characteristics of ion structure in the
groundwater samples were classified by piper [7] andhexa-diagrams using equivalent concentrations of ioncomponents measured by ion chromatography.

Table 1 Details of study points for the groundwater
samples.
No.

LatitudeLongitude

1

N11°12'23.8"

E42°25'54.6"2

N11°05'10.6"

E42°24'25.9"

N11°16'09.1"

E42°13'45.5"

4

N11°06'04.68"

E42°10'49.43"5

N11°00'13.32"

E42°12'27.35"

N11°12'42.6"

E42°45'19.0"

N11°09'40.2"

E42°57'49.6"

8

N11°26'23.6''

E42°48'12.6''9

N11°29'16.4''

E42°50'19.0''

Watershed map with study points

10

N11°31'22.1''

E42°54'45.0''

N11°31'22.1''

E42°54'45.0''12

N11°26'15.79"

E42°47'1.11"13

N11°26'14.86"

E42°46'57.16"

Watershed map of Djibouti was sourced fromdatabase of Ministry of Agriculture, Water, Fisheryand Livestock in Charge of Marine Resources ofDjibouti. All study points were plotted on this map
using Arc GIS and indicated by classification using
hierarchical cluster analysis.

14

N11°25'24.24"

E42°45'37.59"

RESULTS

N11°33'9.95"

E42°57'47.24"

Ion structures of groundwater

N11°32'42.35"

E42°43'00.72"

3

6
7

11

District

DikhilAlihSabieh

Arta

15

Chemical characteristics of groundwater
The chemical characteristics of groundwater wereclassified by hierarchical cluster analysis (Ward's
method). These analyses were based upon equivalentconcentrations of 14 major ion components (Li+, Na+,
NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO2-, Br-, SO42-, NO3-,
PO43-, HCO3- ), EC, hydrogen and oxygen stable
isotope ratio ( δ D and δ 18O) and tritium
concentrations [8]. Principal component analysis(PCA) using the values of EC, DO, ORP, pH, watertemperature (WT), Na, Ca2, Cl, Mg2, SO42

Djibouti
16

The characteristics of the groundwater quality
composition were classified by piper and hexadiagrams based upon the value of ionic constituentsthe second largest population in Djibouti. Most of theabout 270 wells are concentrated in densely populatedareas, and some wells are in suburban areas.

I: Ca-SO4
II: Ca-HCO3
III: Na-HCO3
IV: Na-Cl

Collection of groundwater samples
We collected groundwater samples from 16 deep
wells (100-200m depth) in Feb. 2020 (Table 1). All
groundwater samples were filtered using a 0.22 μm
syringe filter and put into a 100 mL plastic bottle. All
the bottle samples were refrigerated until analysis inJapan.
Ion structures of groundwater quality
Ion concentrations of groundwater were measured
by ion chromatography (Shimadzu; HIC-SP) for 6
cations (Li+, Na+, NH4+, K+, Mg2+, Ca2+) and 7 anions(F-, Cl-, NO2-, Br-, SO42-, NO3-, PO43-, HCO3-). HCO3concentrations were measured at pH 4.8 and by thealkalinity titration method. Water temperature (WT),pH, electric conductivity (EC), oxidation-reduction

Fig. 1 A piper diagram of groundwater samples inDjibouti.
373

SEE-Mie, Japan, Nov.10-12, 2022

of HCO3- in groundwater were high at all study sites.
Chemical characteristics of groundwater
Hierarchical cluster analysis using values of 14
major dissolved ions and EC and DO, all groundwatercollected at study sites were classified into threeclusters at a height of 20. At Cluster 3, only Point 7
was classified (Fig. 5). As a result of PCA, thefactorial axis 2 represented 53.6 ％ of the variance

Fig. 2 Hexa-diagram of groundwater samples on
study sites map in Djibouti.
in the groundwater. According to the piper diagram(Fig.1), the groundwater in this study was classified
into two main types. All groundwater of Djibouti City
and Ali-Sabieh area were classified as Na-Cl type,while most of groundwater of Dikihil and 3 points ofArta were classified as Na-HCO3 type. However,
Point 1 in Dikihil and Point 9, 10, 12 and 11 in Arta
were classified as Na-Cl type. According to the hexadiagram (Fig. 2), the groundwater in this study wasclassified into two main types of water quality
composition. In Djibouti area, located on the coast,and in Ali-Sabieh area, Na-Cl type was predominant.
On the other hand, in Dikihil area, located furthestfrom the sea, and in Arta area, Na-HCO3 type waspredominant.
The equivalent concentration ratio of Cl- to Na+ ingroundwater was richer than in seawater (Cl- : Na+ =1 : 0.85) at most of the study sites (Fig. 3).
The equivalent concentration ratio of Cl- to Br+ in
all groundwater samples was plotted on seawater
between halite (Fig. 4).
Table 2 shows the values of EC, DO, ORP, pH, andwater temperature of groundwater collected at study
sites. The values of EC showed high at all sites (0.84
to 6.90 mScm-1), there was no significant correlation
with elevation or distance from the ocean. Water
temperature was over 30°C at all sites, with amaximum of 52°C. There was a significant negative
correlation between water temperature and elevation.
pH was around 7.5, maximum was 8.5 with nosignificant correlation with water temperature. DO
ranged from 2.61 to 6.90 mgL-1.
The concentration of NO3- in groundwater wasover 50 mgL-1 at 4 sites (Table 2). The concentrations

Fig. 3 and 4 Relationship between concentrations of
Cl- and Na+ in groundwater samples. Relationshipbetween concentrations of Cl- and Br+ in groundwater
samples.
and groundwater classified in Cluster 2 wascharacterized by positive factor in pH, DO and HCO3.
The factorial axis 1 represented 20.5 ％ of thevariance and groundwater classified in Cluster 1 and3 were characterized by positive factor in EC, Na,
Ca2,
374

SEE-Mie, Japan, Nov.10-12, 2022

of groundwater samples.
Table2 NO3-, DO, EC, ORP, water temperature, pH
No.

pH

NO3-

DO

EC

WT

mgL-1

mScm-1

℃

1

6.08

2.78

31

7.87

50.9

2

5.68

0.84

37

7.98

24.4

3

6.40

0.91

32

8.28

20.1

4

5.47

1.20

36

8.12

94.2

5

6.43

1.00

32

8.52

10.0

6

6.90

1.26

32

8.35

47.2

7

5.90

4.42

32

7.34

39.1

8

6.50

0.91

38

7.84

14.5

9

6.85

2.15

34

7.39

63.3

10

6.16

1.48

30

7.99

37.3

11

2.61

1.16

31

7.86

34.5

12

5.32

1.28

39

7.64

22.4

13

6.07

1.08

37

8.14

16.1

14

6.08

1.29

36

8.30

16.3

15

3.71

1.93

52

7.45

38.3

16

5.87

2.83

48

7.77

61.1

mgL-1
Cluster

Cluster
ClusterFig. 5 Hierarchical cluster analysis of groundwater
samples in Djibouti.

Cl, Mg2, SO42 and negative factor in ORP, watertemperature (Fig. 6).
Watershed map with study points
Fig. 7 showed study points on watershed map ofDjibouti. In the Dikihil area, study points were
distributed in 3 watersheds. Points 3 and 4 were in thesame watershed and were also classified in the samecluster, Points 2 and 5 were also in the samewatershed and in the same cluster. Point 1 wasclassified in a different cluster from other four points,
and its watershed was also different from the otherfour sites. Although all study points in Arta andDjibouti area were distributed in same watershed,these points classified two clusters. In Ali-Sabieh area,
study points were distributed two watersheds.

Fig. 6 Principal component analysis (PCA) using thevalues of EC, DO, ORP Water temperature (WT), pH,
Na, Ca2, Cl, Mg2, SO42.
Various factors such as mixing with seawater,
weathering of bedrocks, and leaching of inorganic
constituents from minerals may be influenced thedifferences in values of EC in groundwater (0.84 to
6.90 mScm-1).
In general, it has been reported that groundwater
quality classified as Na-Cl type is likely affected bymixing with fossil seawater confined in theunderground [9]. Therefore, the mixing of fossil
seawater and groundwater was considered at the

DISCUSSION
Ion structures of groundwater quality375

SEE-Mie, Japan, Nov.10-12, 2022

The results of the hierarchical cluster analysis
indicated that Point 7 in the Ali-Sabieh area has
different characteristics compared to the other study
points. The results of the principal component
analysis also indicated the characteristics werepositive factors in EC, Na, Ca2, Cl, Mg2, and SO42.
This suggest that inorganic constituents into thegroundwater primarily cause to weathering of thebasalts and seawater intrusion [13]. Groundwater at
Points 1, 9, 15, and 16 were classified in the same
Cluster 1 in the hierarchical cluster analysis, and theprincipal component analysis results alsocharacterized groundwater at these Points by similar
factors. But there was difference between
groundwater at Points 1, 9 and Points 15, 16 based onwater temperature and ORP. The water temperatureof groundwater at Points 15 and 16 wasapproximately 50°C, and they were plotted as TypeIV in piper diagram, suggesting that thesegroundwaters was influenced by the mixing of hot
spring water and seawater [14]. Groundwaterclassified as Cluster 2 was characterized primarily bypositive factors in pH and HCO3. The highconcentrations of HCO3- detected in groundwater arereported to be supplied from soil [15]. Therefore, highconcentrations of HCO3- means groundwater age isold. So, groundwater at these study points were likely
to have been in residence for a long time. However,point 11 was plotted in a different direction than the
groundwater in the same cluster 2. This was mainly
due to positive water temperature and ORP factors,
with a negative direction for the HCO3- factor. This
result suggests that the groundwater at this site isrelatively young in age and may have been mixed
with hot spring water [14].

Ethiopia

Fig. 7 Study site with watershed map of Djibouti.
The area divided by color gradients shows watershed(source: Ministry of Agriculture, Water, Fishery andLivestock in Charge of Marine Resources).
study sites classified as Na-Cl type groundwater. In
this study, piper diagram classified groundwater
quality into four types to estimate the origin of ions ingroundwater. Ca-SO4 type (I): This type is thecommonly found in shallow groundwater in Japan.
Ca-HCO3 (II): This type is commonly found in deep
groundwater with very old age. Na-HCO3 (III): This
type contains hydrothermal water and fossil seawater.
Na-Cl type (IV): This type is commonly found inseawater and hot spring water. Therefore, in thisstudy, groundwater classified as Na-HCO3 type may
be mixed with fossil seawater or geothermal water,and groundwater classified as Na-Cl type may bemixed with seawater or hot spring water [10]. The
relationship between the equivalent concentration
ratios of Na+ and Cl- suggests possibility thatgroundwater at most of study sites may be affected bysodium leaching from volcanic rocks and by mixing
seawater and fossil seawater [11].

Relationships between cluster of groundwater andwatersheds
Distribution of watersheds of Djibouti arecharacterized by the Great Rift Valley that crosses thecountry. At Arta and Djibouti City area included morethan half of the study points, they were plotted within
the same watershed. Cluster analysis also showed that
6 of the 9 sites were classified in the same cluster,suggesting that groundwater quality in eastern
Djibouti is characterized by inorganic component
runoff due to weathering of basaltic rocks. However,the characteristics of groundwater quality was notunitary even in the same watershed, since there are
groundwaters influenced by hot springs or
geothermal waters, such as at Points 11 and 12. On
the other hand, groundwater plotted in different
watershed in Dikihil area was in the same cluster,suggesting that groundwater characterized by the

Origin of NO3- in groundwater
As a result of ion chromatography, theconcentration of NO3- in groundwater was over 50
mgL-1 at 4 sites. Generally, NO3- in groundwater may
be derived from fertilizers, livestock manure,domestic wastewater, and soil organic matter. In
particular, it has been reported that highconcentrations of NO3- in groundwater in arid areas
are likely to originate from natural soil sources [12].
But most of the wells in study sites are also used by
local nomads as drinking water for their livestock too,
it is possible that NO3- in the groundwater was also
originated from livestock manure.
Chemical characteristics of groundwater376

SEE-Mie, Japan, Nov.10-12, 2022

environmental isotopes data: Dalha basalts
aquifer, southwest of Republic of Djibouti.
Environmental Earth Science, 2013, Vol. 70,
pp.3335-3349[5] Awaleh M., Paul B., Youssouf D. S., Tiziano B.,
Farhan B. H., Nima M. E., jalludin M., Omar A.
D., Janie M. D., Jean C., Recharge, groundwaterflow pattern and contamination processes in anarid volcanic area: Insights from isotopic andgeochemical tracers (Bara aquifer system,
Republic of Djibouti). Journal of Geochemical
Exploration, 2017, Vol. 175, pp.82-98.
[6] Ahmed A.H., Rayaleh W.E., Zghib A., Ouddane
B., Assessment of chemical quality ofgroundwater in coastal volcano- sedimentaryaquifer of Djibouti, Horn of Africa. Journal of
African Earth Science, 2017, Vol. 131, pp.284300.
[7] Piper A.M., A graphic procedure in thegeochemical interpretation of water-analyses.
EOS, American Geophysical Union Transaction,
1944, Vol. 25, Issue 6, pp.914–923.
[8] Asakura Y., Nakanishi Y., Ofleh B.H., Values ofδ D and δ 18O and concentrations of 3H and 14C ofdeep groundwater in Djibouti. Journal of Arid
Land Studies, Unpublished Work but Accepted.
[9] Frape S.K., Fritz P., McNutt R.H., Water-rockinteraction and chemistry of groundwaters fromthe
CanadianShield.
Geochemica
etComochimica Acta, Vol. 48, Issue 8, pp.16171627.
[10] Editorial Board of Handbook of Groundwater,
For Chapter 9 in Handbook of Groundwater, 1980,
Research Institute of Construction and Industry,
Tokyo, pp. 358-367.
[11] Join J.L., Coudray J., Longworth K., Using
principal components analysis and Na/Cl ratios
to trace groundwater circulation in a volcanicisland: the example of Reunion. Journal of
Hydrology, 1997, Vol. 190, Issue1-2, pp.1–18.
[12] Kendall, C., Elliott. E.M., Wankel. S.D., For
Chapter 12 in Stable Isotopes in Ecology andEnvironmental Science, second ed., 2007,
Blackwell Publishing, New York, pp. 375-449.
[13] Freeze R.A., Cherry J.A., For Chapter 3 in
Groundwater,
1979,
Prentice-Hall
Inc.,
Englewood Cliffs, Vol. 7632, pp.80-139.
[14] Awaleh M.O., Hoch F.B., Boschetti T.,
Soubaneh Y.D., Egueh N.M., Elmi S.A., jalludinM., Khaireh M.A., The geothermal resources of
the Republic of Djibouti - II: geo- chemical studyof the Lake Abhe geothermal field. Journal of
Geochemical Explorer. Vol. 159, pp.129-147.
[15] Nordstrom D.K., Ball J.B., Donahoe R.J.,
Whittemore D., Groundwater chemistry andwater-rock interactions at Stripa. Geochemica
et Cosmochimica Acta, 1989, Vol.53, pp. 17271740.

same sediments or basalt were widely distributed.
CONCLUSIONSAs results of this study, although some importantdata of groundwater quality in Djibouti has beenobtained, it is considered necessary to study ingroundwater dating and water stable isotope ratios
more wide area to understand its complex
groundwater distribution and water quality
characteristics. In addition, it is considered important
to conduct long-term monitoring studies at a large
number of study sites in order to consider
anthropogenic influences on groundwater. In Djibouti,
groundwater is the only freshwater resources ofdomestic water for local nomads. Although there
have been no reports of groundwater being affectedby nitrogen contamination due to human activities, it
was considered important to estimate the origin ofNO3- in groundwater using nitrogen stable isotope
ratio in this study and to understand groundwatercontamination in detail to propose appropriate
management for sustainable and stable groundwater
resources in Djibouti.
ACKNOWLEDGMENTS
This study was supported by Japan Science andTechnology Agency (JST) and Japan International
Cooperation Agency (JICA) under the project of
Science and Technology Research Partnership for
Sustainable Development (SATREPS GRANT
NUMBER: JPMJSA1802).
REFERENCES[1] Assowe, O.D., Awaleh, M.O., Kirk-Davidoff, D.,
Olauson, J., Söder, L., Awaleh, S.I., Wind
resource assessment and economic analysis forelectricity generation in three locations of the
Republic of Djibouti. Energy Vol 185, 2019,
pp.884–894.
[2] JICA, The Master Plan Study Project for
Sustainable Irrigation and Farming in South- ern
Djibouti. The Republic of Djibouti. Final Report,
2014, pp.52–172.
[3] Awaleh M.O., Boscheti T, Adaneh A.E., Chrdon
M.A., Ahmed M.M., Dabar O., Soubaneh Y.D.,
Egueh E.M., Kawalieh A.D., Kadieh I.H.,
Chaheire M., Origin of nitrate and sulfate sourcesin volcano-sedimentary aquifers of the East Africa
Rift System: An example of the Ali-Sabieh
groundwater (Republic of Djibouti). Science of
the Total Environment, Vol. 804, Issue 15, 2022,
pp.1-13.
[4] Aboubaker M., Jalludin M., Razack M.,
Hydrochemistry of a complex volcanosedimentary aquifer using major ions and377

SEE-Mie, Japan, Nov.10-12, 2022

378

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

HYDROCHEMICAL CHARACTERISTIC OF THE EASTERN SLOPESOF MOUNT KARANG, WEST JAVA, INDONESIA
1

Hadi Hidayat1, Deden Zaenudin1, Boy Yoseph CSS Syah Alam1
Faculty of Geology, Padjadjaran University, Bandung, West Java, Indonesia

ABSTRACT
Population and industrial growth in Java are the most significant compared to other regions inIndonesia, which triggers high groundwater use. The Eastern slopes of Mount Karang (a volcano in West Java,
Indonesia) has the potential to be a significant groundwater source. Analyzing the characteristics of groundwater
is significant for the rational management of groundwater resources. Samples were collected from springs, dug
wells and drill wells. We use information about aquifer systems, hydrogeological conditions and hydro-chemical
data to investigate groundwater sources and groundwater quality resulting from water-rock interactions. Chemical
data showed that samples belonged to the Ca-Mg-HCO3 type, Mg-HCO3 type, Na+K-HCO3 type and Na+K-Cl
type. Ca²⁺ indicates that this water may have flowed through a rock formation composed of andesitic rocks with
Ca-plagioclase minerals. The presence of Mg2+ shows that the water has flowed from shallow to the deeper aquifer.
HCO₃⁻ originates from either infiltration of rain water that has been equilibrated with CO₂ in the atmosphere, orfrom CO2 that has been generated by respiration of organic material. The different types of groundwater detected(Na+K-Cl type) indicate that groundwater on this slope has flowed in rocks of different geological products.
Groundwater chemical characteristic is mainly controlled by changes in volcanic deposits.
Keywords: Groundwater, hydro-chemical, water-rock interactions, Mount Karang
INTRODUCTION

caused by the diversity of landforms which are
influenced by different types of lithology.
Based on the results of geological mapping of theeastern slope of the Karang Mountain, it is divided
into 11 (eleven) volcanic lithofacies which areinterpreted as the result of 5 (five) eruptions of
Karang Mountain (Fig.1), the results of the 1st
eruption depositing the old rough lapilli rock facies(Fbl) autoclastic facies with lava (ALKa). Well sorted
lapilli tuff facies (PDct) and the grain supported
pyroclastic-breccia breccia facies (ALHb), then the
2nd eruption produces pyroclastic breccia-tuff grain
supported facies (ALHbr), the result of the 3rd
eruption is andesite lava facies (ALK), coarse tuff
facies – matrix supported graded bedding facies(JPbt) tuff breccia, poorly sorted matrix supported
tuff breccia facies (APbt), 4th eruption of Karang
Mountain produced andesite sheeting joint (ALsj)
lava facies, medium tuff facies – breccia tuff matrix
supported graded bedding (Jpt). As well as the 5th
eruption of Mount Karang which produces autoclastic with lava facies (ALKal).
The geological structures that developed in the
study area are the Cilenggor sinistral horizontal fault,
the Cikirup normal fault, the Cikarang normal dextral fault and the Cilalaki normal - sinistral fault(Fig.1).

Population and industrial growth in Java are themost significant compared to other regions inIndonesia, Thus, urbanization is one of the major
triggers’ high groundwater use, Jakarta was theexample of a decrease in groundwater reserves [1], as
well as several buffer areas of the capital city thatwere affected, such as the Banten area. So that
research on groundwater must be done a lot to meetthe needs of many people. The Eastern slopes ofMount Karang (a volcano in West Java, Indonesia)
has the potential to be a significant groundwater
source [2].
The aims of this study were to identify
groundwater sources, groundwater quality as a resultof the interaction between water and rocks, as well as
the influence of geological conditions (changes involcanic lithofacies), hydrogeological conditions onhydrochemistry and groundwater flow. Analyzing thecharacteristics of groundwater is significant for therational management of groundwater resources.
This research was carried out on the eastern slopeof Mount Karang, Pandeglang, Banten, Indonesia(Fig. 1), which is geographically located at 106 ͦ 3`28”
E 6 ͦ 13`18” S and 106 ͦ 8`39” E 6 ͦ 17`51” S.
GEOLOGICAL SETTING
The research area is located on the morphology ofthe slopes of the mountain at the foot of the mountainand solitary hills at the foot of the mountain, with aslope from sloping to steep. The difference in slope is379

SEE-Mie, Japan, Nov.10-12, 2022

AQUIFER SYSTEM
Three different aquifer systems in the study area
based on the survey, including the aquifer system in
autoclastic lithology, lava and andesite lava (fractured
system), aquifer system in pyroclastic breccia
lithology and tuff grain supported (combined between
contact and porus) aquifer system in tuff and lapilli
lithology (porus).

Figure 2. Map of Sampling Location
Analysis methods
pH, electrical conductivity (EC), total
dissolved solid (Tds) and temperature using HANNA
Instruments HI9811-5 were measured on site. The
cations (Li+, Na+, K+, NH4+Ca2+and Mg2+) and anions(Cl-, NO3-, SO42-) were determined by ion
chromatography (IC- metrohm type 930 Compact), inlaboratory. HCO3- was analyzed using the titration
method with a 0.1N HCl, methyl red and bromocresol
green were used as tritants.
A 5% difference in the electrical balance
between cations and anions is required and was
obtained for all samples.

Figure 1. Geological Map of Study Area
METHODOLOGY
Sampling Location
This study reports analytical data for 20
groundwater sources located at elevations ranging
from 167 to 928 m a.s.l. and springs, and wells(Figure 2). Springs are generally found on the contact
between volcanic lithofacies and at varying
morphology of the valley. Two dug wells are locatedat elevations of 297 m and 239 m asl with their depthof water level as 3.9 m and 0 m respectively.

RESULT AND DISCUSSION
Physical Properties
Groundwater parameter such as Electric
Conductivity (EC), Total dissolved solid (Tds), pH,
Temperature, together with analytical data for the
major ions are presented in Table 1. The measured
Electrical Conductivity (EC) values for springs, river
and wells were 50 -460 µS/cm which shows that the
groundwater in the study area is freshwater. Total
dissolved solid (Tds) were 20 – 220 mg/L, pH rangeof springs and wells from slightly acidic to neutral(5.5 -7.8) and then the temperature from 23-31 ͦ C.

Sampling methods
Field survey was carried out from January-March
2020.
Water sampling was performed using 500-mL
polyethylene bottles. Prior to sampling, the bottles,
ladle, filtration units and messzy inder were rinsed
three times with the filtered water. The water samples
were filtered in situ using 0.45 µm Syringe filter. As
much as 500 mL of sample was collected for cation
and anion analyses. The bottles containing the water
samples for thesealed.

Major Ions
Chemical contents especially major ionsshowed Ca+ 3.16- 41.17 ppm, Na+ from 3.47 to 30.37,
K+ from 2.76 to 13.52, Mg2+ from 0.84 to 19.37 ppm,
Cl- from 1.23 to 38,32 ppm, HCO3- from 13.85 to
249.74 ppm and SO42- from 1.12 to 18.71 ppm.

380

SEE-Mie, Japan, Nov.10-12, 2022

Table 1. Physical properties and chemical analysis of water saples
Sample ID
PDG 01
PDG 03
PDG 05
PDG 06
PDG 08
PDG 09PDG 12
PDG 13
PDG 14
PDG 17
PDG 22
PDG 23
PDG 25
PDG 26
PDG 31
PDG 32
PDG 34
PDG 37
SMR 01
SMR 02

Type

EC

TDS

T

SpringSpringSpringSpringSpringSpringSpringDug Well
SpringSpringDug WellspringspringspringspringspringspringspringDrill Well
Drill Well

µS/cm
80
60
290
50
150
130
140
460
230
180
160
190
320
150
140
210
130
140
120
130

mg/L
20
20
140
20
70
60
60
220
110
80
70
80
150
70
80
90
50
60
50
60

ͦC
23
23
24,9
23,6
25
24,8
25,9
25,9
23,3
27,4
26,6
25,2
26,5
26,3
30,4
31
25,4
25,5
27,8
29,3

pH
7,6
6,5
6,9
7,2
6,8
7
6,4
6,3
6,5
7,4
6,5
6,5
5,5
6,6
6,7
6,4
6,1
6,2
7,8
7,10

Li+
0,02
0,03
0,00
0,00
0,00
0,02
0,00
0,00
0,02
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00

Na+
6,17
6,11
12,61
3,47
9,90
8,73
9,07
13,29
11,21
8,44
9,73
11,45
30,37
9,75
13,66
15,46
10,16
10,08
11,09
9,76

NH4+
0,03
0,09
0,06
0,03
0,18
0,06
0,04
0,10
0,06
0,07
0,06
0,06
0,14
0,04
0,00
0,14
0,11
0,07
0,00
0,05

K+
2,85
2,76
4,04
2,87
3,31
4,62
4,89
13,52
5,03
8,15
4,88
4,94
7,86
4,73
4,49
5,52
4,30
4,57
5,42
4,90

Ca2+
3,16
3,98
26,21
4,91
9,86
9,97
11,30
41,17
20,51
18,08
14,26
16,83
15,39
11,58
24,52
27,69
15,95
12,72
10,42
13,89

Mg2+
0,88
0,84
9,29
1,26
6,53
5,24
5,01
19,37
12,55
4,20
6,67
10,72
5,52
6,17
9,02
12,15
5,20
5,07
4,81
6,97

Fppm
0,23
0,14
0,13
0,12
0,15
0,17
0,16
0,14
0,20
0,16
0,16
0,18
0,13
0,17
159,22
0,17
0,13
0,14
0,16

Cl-

NO2-

Br-

NO3-

SO42-

HCO3-

1,67
1,59
17,88
1,23
1,73
2,46
2,61
5,68
2,16
5,76
2,04
4,23
38,32
1,75
0,00
4,62
1,42
1,34
3,51
1,43

0,00
0,00
0,00
0,60
0,00
0,63
0,00
0,65
0,00
0,00
0,00
0,00
0,60
0,00
0,00
1,34
0,85
1,84
0,00
2,06

0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,00
0,53
0,00
0,00
3,71
1,25
1,12
0,00
1,60

3,10
3,95
54,63
2,49
1,50
2,58
4,26
17,54
3,09
2,04
3,09
6,27
12,87
2,20
0,00
1,34
0,85
1,84
0,00
2,06

3,14
2,97
3,81
1,79
1,34
2,79
2,72
18,71
1,45
6,56
1,92
2,63
15,38
2,16
6,29
3,71
1,25
1,12
4,90
1,60

30,10
15,00
57,19
13,85
77,69
67,71
93,05
249,74
170,05
57,15
89,01
81,76
57,38
65,65
154,15
187,12
96,61
92,03
101,9996,20

The results of chemical analysis for the waters wereplotted on a piper diagram and stiff diagram as shownin Figure 3 and Figure 4. From Fig. 3 waters are
divided into 5 (five) groups based on their chemical
characteristics: Ca-Mg-HCO3, Mg-Ca-HCO3, MgHCO3, Na+K-HCO3, and Na-+K-Cl.

Figure 3. Piper Diagram

Twelve waters Samples of Ca-Mg-HCO3 type,are located on elevations from 167 to 928 ma.s.l..
That groundwater facies is the type of groundwaterthat dominates in the study area. One sample belong
to Mg-Ca-HCO3 type is located on 437 m.a.s.l. two
samples belong to Mg-HCO3 type are located onelevation 199 and 251 m.a.s.l. Then two waters of
Na+K-HCO3 type are located in the elevation 459
m.a.s.l. and one water sample belong to Na+K-Cl is
located in the elevation 180 m.a.s.l.

Figure 4. Stiff diagram for major ion of water samples
From the stiff diagram in Fig.4, Ca2+ is adominant cation in Ca-Mg HCO3 type water in PDG
5 which is located at an elevation of 750 m.a.s.l. Thiswater has flowed in the volcanic facies of andesitic
rock that contains Ca-plagioclase.
The presence of Mg2+ shows that the water has
flowed from shallow to the deeper aquifer. As in PDG
14 and PDG 23 where these cations are elements thatare quite widely dissolved in groundwater samples
with concentrations of 12.55 ppm and 10.72 ppm,
respectively.
Variations in the presence of cations ingroundwater samples in the study area are indicatedby the dominance of Na+K cations in groundwater
samples from PDG 1 and PDG 25 points with
381

SEE-Mie, Japan, Nov.10-12, 2022

concentrations of 6.17 ppm and 30.37 ppm,
respectively. shows that the interaction ofgroundwater with rocks lasts quite a long time. PDG1
is associated with the ALHbr volcanic facies which iscomposed of breccia lithology, so that the dominanceof Na+K elements is the result of dissolution ofplagioclase minerals.
Meanwhile, HCO3 is derived from infiltration of
rainwater equilibrated with CO2 in atmosphere or is
CO2 generated by root respiration organic material.
These ype indicated for local flow system. In general,
surface water is controlled by the type ofgroundwaters.

CONCLUSION
Physical properties of groundwater identified asa result of the interaction of groundwater with rocks,
it shows that the water in the study area is included in
fresh water. Lithological variations and changes thatcompose various volcanic facies in the study area
control the chemical composition of groundwater as
indicated by variations in groundwater types
identified from various groundwater samples
including Ca-Mg-HCO3, Mg-Ca-HCO3, Mg-HCO3,
Na+K-HCO3 and Na+K-Cl. In addition, the various
types of groundwater show differences ingroundwater flow which are controlled by geologicalevents. The direction of shallow groundwater flowfrom west to east is also controlled by the morphologyof the study area.

The concentration of Cl- anions in PDG 25 showeda value of 38.32 pp, so it was an anomaly comparedto the anions contained in other water samples. The
PDG 5 sample point is associated with the oldest
volcanic facies in the study area, namely Fbl which iscomposed of lapilli lithology. In addition, theemergence of these springs is associated with asinistral horizontal fault, so it is interpreted thatgroundwater that appears at the PDG 5 point has
flowed into the deep groundwater aquifer

ACKNOWLEDGMENTS
The authors would like to thank deeply to Faculty ofGeology, Universitas Padjadjaran and the Unpad
team for their invaluable participation in this study.
We would also like to express our gratitude for thevaluable comments provided by reviewers and theeditor of GEOMATE.

Groundwater flow system
Based on the water table and water types in the
study area, groundwater flow in the volcanic aquifer
system can be determined. In the upstream part, theCa-Mg-HCO3 type indicated that it is close to thesource. The presence of the Mg-Ca-HCO3 type atelevation 437 and the Mg-HCO3 type indicates thegroundwater flow is quite far from the recharge area
and the groundwater has flowed into the aquifer
which is deep enough. The appearance of the Na+KCl type indicates that in the study area there isgroundwater flowing very deep and far from its
infiltration source and its appearance is influenced by
the geological structure (fault). The direction ofgroundwater flow is generally from West to East andshown in Figure 5.

REFERENCES[1] Anna Rusyidi, Mitsuyo Saito,Seiichiro Ioka, and Rizka
Maria., Estimation of Ammonium Sources in Alluvial
Groundwater Using Cl- and GIS A Case Study Of
Indramayu, Indonesia. Int. Conf. on Science,
Engineering & Environment (SEE), 12-14,
2018,pp.203-207[2] Boy Yoseph CSS Syah Alam, Yuichi Itoi, Sachihiro
taguc=hi and Rie Yamashiro, Spatial variation in
groundwater type of the volcanic aquifer system basedon hydro-chemical and stable isotopes (δD and δ18O)
at Mt. Karang, West Java, Indonesia. Modern Applied
Science; Vol 8 No.6 2014.
[3] Muhammed Haji,Dajun Qin,Yi Guo,Lu LiDongdong
Wang Shankar Karuppannan,Hassen Shube, Origin
and geochemical evolution of groundwater in the
Abaya Chamo basin of the Main Ethiopian Rift:
application of multi-tracer approaches. Hydrogeology
Journal (2021) 29:1219–1238.
[4] Appelo,
C.A.J.andPostma,
D.,Geochemistry,
Groundwater and Pollution. A.A. Balkema(2005).
[5] Domenico,P.A. and Schwartz, W.F., Physical andchemical hydrogeology.John Wiley and Sons, Inc.,
Canada, 824p (1990).
[6] Fetter, Jr.C.W., Applied hydrogeology.Bell andHowell Company, 488p (1980).
[7] Freeze R.A. and Cherry, J.A., Groundwater. PrenticeHall, 604p (1979).
[8] Fury W,.Hydrochemical characterization of complex
volcanic aquifers in a conteinental rifted zone: theMiddle Awash basin, Ethiopia. Hydrogeology Journal
20: 385-400(2011)

Figure 5. The stiff diagram map and shallow
groundwater flow.

382

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

RELATIONSHIP BETWEEN THE LIVINGENVIRONMENT AND THE SENSE OF TIME-SPACE

1

Kazuki Miyake1, Kazunari Tanaka2
Osaka institute of technology Graduate Course in Architecture, Civil Engineering and Urban Design,
2
Osaka Institute of Technology

ABSTRACT
People’s behavior in public spaces has been studied from different viewpoints and previous studies haveshown that actions are influenced by the layout of the device and the shape of the space. The cognitive distanceand means of transportation to and from school and workplace depends on where people live. Compared withurban areas, suburban areas have fewer stores. In other words, people living in urban areas and suburbs havedifferent means of transportation and surroundings. They have different space-time senses. Depending on theliving environment, such as the waiting time of public transportation and the distance of facilities used daily. The
distance and the speed of transportation are changed depending on the location. The purpose of this study is toquantify the differences in distance perception, depending on the living environment. Focusing on the residence
position of people with respect to the distance from the station, the residence data was displayed and visualized
by GIS. The structure of distance intervals in people's lives was extracted.
Keywords: (Living environment, Kernel density estimation, distance intervals, GIS),INTRODUCTION

lives. The experiment will be conducted in Asahi-ku,
Osaka City, Osaka Prefecture, and Sakurai City,
Nara Prefecture. As a preliminary study, we
conducted a survey on the location of people staying
in Sakurai City, Nara Prefecture. Here, we focusedon people's location in relation to the distance fromthe station and visualized the data by displaying it ina GIS. Next, a questionnaire survey was conducted
to extract people's sense of distance and time axis.
Since previous studies have shown that theperceived distance differs depending on the historyof residence, a questionnaire survey was conducted
targeting both visitors and residents of the city. In
order to have subjects perceive distance, we asked
them to describe their means of travel and travel
time to a certain point and compared them with theactual distance and travel time.

Background
There is a large body of literature that addresses
the influence of the surrounding environment, suchas season and the placement of retention devices, on
people's behavioral choices in retention spaces.
However, we believe that behavior also varies
depending on the experience that is the source ofaffordance. Currently, the population of Japan isaging rapidly, and the problem of depopulation insuburban areas has arisen due to population decline.
Depending on where people live, the distance they
travel to school and work and the means oftransportation differ. In addition, there are fewer
stores and residences in suburban areas than in urban
areas. In other words, people living in urban andsuburban areas have different means oftransportationanddifferent
surrounding
environments, and each has a different sense of time.

EXPERIMENT
Experiment１
The first study was conducted during the social
experiment in front of Sakurai Station in Sakurai
City, Nara Prefecture. The first study was acomparison of the different periods of time during
which the social experiment was held in front of
Sakurai Station in Sakurai City, Nara Prefecture,
Japan. Figure 1 shows the results of the residential
location of the passers-by for each period.

Purpose and Method
We believe that differences in perception such asnear/distant and early/slow form due to living
environment, such as waiting time for public
transportation and distance to facilities used andchange daily. Therefore, the purpose of this study isto quantify the differences in the perception of
distance due to living environment, and to extract
the structure of perceived distance in people's daily383

SEE-Mie, Japan, Nov.10-12, 2022

20
18
16
14
12
10
8
6
4
2
0

③
①
②

October 29th

October 30th

November 20th

Fig. 1

Fig. 2October 29th Inflow/Outflow

Fig. 3October 30th Inflow/Outflow

Fig. 4

November 20th Inflow/Outflow

Percentage of visitor residence

The survey was conducted by videotaping 90
minutes of data and counting the number ofincoming and outgoing flows. The results are shownin Table 1.
Table 1

Day Number of in/out flows
High school student

Others①

October 29 th
14

318

②

5

330

③

4

190

①

October 30th
68

2229

②

30

1027

③

24

1149
th

①

September 20
282

②

22

311

③

44

190

330

Figures 2, 3, and 4 show the results of Table 1 as thesize of the arrows on the map for each schedule.
High school student counts are indicated by blue
arrows and the general public by red arrows.

384

SEE-Mie, Japan, Nov.10-12, 2022

October 29 was an experimental day with arelatively large number of residents, October 30 was
an event held at a nearby location, and November 20
was an experimental day with a large number of
non-local visitors during the fall foliage season. The
traffic volume in the vicinity of the station was
higher on the experimental days when there weremore visitors, while on the experimental days when
there were more residents, the traffic volume in frontof the commercial facilities was higher. In the next
section, we will visualize and verify the difference indwell position by residential area.

①
④
②
③

⑤

Experiment 2
Fig. 6The second survey was conducted to determine
the location of the visitors in the vicinity of thestation plaza. The results of the questionnaire survey,
shown in figure 5, revealed that there was adifference in the number of times the respondents
visited the area and the location of their stay. We
believe that the range of behavior may change
depending on the residential area or the level ofrecognition of the area, and we compared the dwell
time positions of residents and visitors to extract
differences in behavior in the residential area.

Table 2 shows the results of the location of stay byplace of residence for a total of 5 days.
Table 1

Area 1
Area2
Area3
Area4
Araa5

80%
70%
60%
50%
40%
30%
20%
10%
0%

Day Number of in/out flows
Resident
24
23
22
7
12

Visitor
15
24
15
11
0

Figures 4 and 5 show heat maps created by kernel
density estimation using GIS with the results shownin Table 2.

Area 1

Fig. 5

Area Location

Area2

Area3

OthersDwell position by number of visits
Fig. 7

The purpose of the survey was to extract data on
the place of stay by place of residence through aquestionnaire survey and to compare the range ofactivities of the two groups. Plotting the staylocations of visitors and residents obtained from thequestionnaire survey on a map was performed. The
subject site is shown in Figure 5. Area 1 is in frontof the commercial center as the target area. Area 2 islocated in front of the east exit of Sakurai Station.
Area 3 is the tourist information center. Area 4 is thebus stop Area 5 is Hommachi Street.

385

Resident action range

SEE-Mie, Japan, Nov.10-12, 2022

that people have a different sense of distance fromeach other depending on their residential
environment. In an aging society with a declining
birthrate, the sense of distance is an important
perspective in promoting the mobility of residents insuburbanareasthroughcompacturban
development and is considered to be fundamental
information regarding the layout of facilities andtarget areas. We were able to obtain results that canbe used as an indicator for the development of future
residential environments.
Fig. 8

Visitor Action Area
REFERENCES[1] Murata S., Morihara K., and Koda T., Analysesof Effect of Personality on Personal Space inReal World and Metaverse. The Japanese journalof Psychology, Vol. 52(2), 1981, pp. 124-127.
[2] Konishi H., Nozawa K., Study on Seating
Behavior in the Train; the Influence of Prediction
about Crowd on Seating Behavior. The annual
bulletin of Musashino University Institute of
Human sciences, Vol. 7, 2018, pp. 37-39.
[3] soshihiro O., Ayaka M., Distance Measure Basedon Spatiotemporal Coexistence of Residents. J.
Archit Plan., AIJ, Vol.80 No.715 2001-2010
Sep.,2015

It was found that most of the visitors stayed at
the bottom of the east staircase, while the residents
stayed in relatively calm areas with little traffic,
moving to various locations during events. These
results indicate that the location of residence and therange of activities vary depending on the level ofrecognition of the town, and that each individual has
a different sense of distance from the others.
3 CONCLUSION
Survey 1 revealed that the flow in and out ofeach area differs depending on the residential area,and Survey 2 revealed that the location of residence
and the range of activities differ depending on thelevel of recognition of the town. The results indicate

386

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

A REVIEW OF THE CURRENT LEGISLATION ON WASTE
MANAGEMENT IN DEVELOPING AND DEVELOPED COUNTRIES
Kylie Douglas1, Daniela Ionescu2, Joe Petrolito 3 and Bandita Mainali4
1
Council of Greater Bendigo, Bendigo, Australia
2,3School of Engineering and Mathematical Sciences, La Trobe University, Australia
4
School of Engineering, Macquarie University, Australia

ABSTRACTThe management of municipal solid waste is a major problem worldwide. However, the approaches on SMW
widely vary between countries due to in-place legislation. Developed countries are moving towards a Circular
Economy and are developing policies and legislation to support this move. However, the policies and legislation
makers are not always up to date with studies on the best practices on MSW, which results in few tangible outcomes.
In developing countries, landfills are still an accepted means of disposal. The legislation mandates source
segregation of recyclates. However, in some countries there is little desire to enforce this, resulting in tones ofrecyclates being discarded to landfill.
The aim of this paper is to review the strengths and weaknesses of the legislation governing solid waste
management (SWM) in both developed and developing countries. It looks specifically at comparing the legislationand policies directly pertaining to SWM and how they are enacted at ground level using Regional Victoria,
Australia, and Kathmandu Metropolitan City (KMC), Nepal as case studies. In addition, it examines the potential
for the transfer of knowledge and learnings between Regional Victoria and KMC.
The results from the study strongly support the transfer of learnings between Regional Victoria and KMC, toactively enforce sustainable SWM practices. Moreover, the learnings from Regional Victoria’s move towards
becoming a truly Circular Economy can be directly applied to KMC. Conversely, learnings from KMC and their
methods of production of high-quality recyclates can also be directly applied to Regional Victoria, aiding in thetransition towards a Circular Economy.
Keywords: Solid waste management, Circular economy, Technology transfer, Waste reduction

INTRODUCTION

become apparent.
It is reported that the amount of waste generated
strongly reﬂects the economic status of the people [3]and also depends on socio-cultural patterns andclimatic factors [4]. There is no agreement on thecorrelation between Gross Domestic Product (GDP)and waste generation. Othman et al. [5] reported thatthe average solid waste generation in developing
countries is 0.7-0.8 kg/person/day, while it is 0.4-0.6
kg/person/day in developed countries. In contrast, [4]showed that the median generation rates in highincome countries is about six-fold greater than in lowincome countries, as presented in Fig. 1.
The aim of this paper is to review the strengths
and weaknesses of the legislation governing SWM inboth developed and developing countries. It looks
specifically at comparing the legislation and policies
directly pertaining to SWM, and how they are enacted
at ground level using Regional Victoria, Australia,
and Kathmandu Metropolitan City (KMC), Nepal ascase studies. In addition, it examines the potential forthe transfer of knowledge and learnings between
Regional Victoria and KMC.

The spread of urbanization and intensified
industrialization are phenomena that are observed indeveloped as well as developing economies, and they
are associated with rapid population growth.
Developments, growth and consumption of goods
and services are on the increase. This causes anincreased rate of municipal solid waste generation,
which in 2016 was reported to be 0.75 kg/person/day
and is expected to increase by 70% in 2050 [1]. The
sustainable collection and management of this wasteis critical to economic development, the environment,
and society [2].
The challenges of solid waste management(SWM) are recognized at a global level, and they are
not limited by boundaries or by the development
status of countries. Common challenges include
limited ‘waste’ disposal infrastructure, resource
recovery and the availability of markets for therecovered materials, and the quality and ‘cleanliness’of the recovered products. However, with thechallenges come opportunities, and it is in realizingthese opportunities that the differences between
developed countries and developing countries387

SEE-Mie, Japan, Nov.10-12, 2022

Figure 1. Waste generation versus income level by country [4]EXISTING SOLID WASTE MANAGEMENT
FACILITES

originates overseas (UK, India, etc.), with 68% of the
population being Australian-born citizens [13]. The
varied range of migrants practice diverse religions,although Christianity is the largest. Similarly,
multiple languages are spoken, with English being
predominant.

Geographic and Demographic Background
Kathmandu occupies an area of 49.45 km2 inCentral Nepal, at an average altitude of 1400 m. 74%
of its surface is built-up area [6]-[8]. It has atemperate climate for most of the year, with four
distinct seasons [9]. It currently has 1.521 million
inhabitants, resulting in a population density of over
30,750 people/km2 [10]. The terrain surrounding
Kathmandu is primarily used for agriculture to
support the growing population [11].
Kathmandu is a multicultural metropolitan area
comprising of four major ethnic groups, namely
Newar 30%, Matwali 25%, Khas Brahmins 20% andChettris 18.5% [8]. The two major religions are
Hinduism and Buddhism, and there are three main
languages that are spoken, namely Nepali, Nepal
Bhasa and English [8]. The city’s infrastructure dates
to the 10th Century.
Regional Victoria is located in South-Eastern
Australia and has a topography that ranges fromplains to mountainous, with elevations varying from
10 m to 2000 m [12]. The total land space of 226,267
km2 supports a population of 6,681 million people,
with a density varying from 1 people/km2 to 37
people/km2 [13]. Regional Victoria also has atemperate climate for most of the year, with four
distinct seasons [11].
Australia was built on migration after the initial
settlement by the British. Settlements in Regional
Victoria date back to the mid-1800s [11]. Regional
Victoria has a rich multicultural history. Although the
Aboriginals are recognized as the first inhabitants of
the land, a quarter of the Regional Victoria population

Kathmandu Metropolitan City
SWM was formalized in KMC in the 1980s withthe construction of the Teku composting facility, theTeku transfer station and the Gokarna landfill. During
the 1990s, waste was disposed of without any
segregation taking place [14]. The closure of the Teku
composting facility in 1992 and then of the Gokarna
landfill in 2005 resulted in a return to poor SWM anduncontrolled dumping in KMC [14].
The opening of the Sisdol landfill and the 2011
SWM Act in Nepal facilitate improved collection anddisposal practices in KMC, as segregation of waste at
the source and separation of organics from waste was
implemented and promoted [15]. In 2012, KMC
allocated 24% of its budget to SWM, of which
between 60-70% was used in street sweeping to clean
up the street-side dumping of waste, and 20-30% wasused for waste transportation [6]. The adoption of the
new constitution in 2015, and the merger of thecentral governmental offices with the local
government, resulted in a lower proportion of thebudget (6.3%) being allocated to SWM, although theoverall funding was higher [16].
The waste collection occurs through a
combination of KMC vehicles and staff, and private
sector organizations (PSOs) [17]. Inconsistent fees
for service are being charged throughout KMC,
resulting in inconsistent collection services [16].
Currently, KMC and the surrounding region are388

SEE-Mie, Japan, Nov.10-12, 2022

serviced by a single landfill located at Sisdol. A new
landfill is being constructed at Banchare Danda [18].

impose fines in the event of dumping of waste inundesignated areas. The fines can be up to Rs. 15,000(approximately AUD $192), and if required can
include additional clean-up costs. Although the Act
covers dumping of waste in undesignated areas,street-side dumping is still an accepted practice in
KMC.

Regional Victoria
During the gold rush era, until the late 1800s andinto the 1900s, there was uncontrolled disposal ofwaste [19]. With the formation of Local Government
Authorities (LGAs), waste management became
more formalized, with the establishment of local ‘tipsites’ for the disposal of waste [19].
The Local Government reform of the 1990s
resulted in the amalgamation of 210 shires into just
78 [20]. Many smaller disposal sites were closed,
waste collection was mandated, and the remaining
disposal sites were formalized and controlled.
Collection services took place under a mandatory ‘feefor service’ model [20].
Hence, in contrast to the KMC practice, each of
the municipalities of Regional Victoria has access tocontrolled waste disposal facilities. Resource andrecovery facilities are common at the transfer stations
and landfills. A kerbside waste collection occurs
weekly, and most municipalities support a fortnightly
collection of recyclable materials. A green waste
collection service is offered by some municipalities,
and private operators also provide, for a fee, a green
waste collection service in other areas. The kerbside
collection of waste is the responsibility of themunicipality, although residents can access disposal
and recycling facilities to deposit excess waste fromproperties.
LEGISLATION
PRACTICESTOSUPPORT

Interim Constitution of Nepal - 2008
According to [21], this policy includes someprovisions that broadly relate to SWM, and it states
the right of each person to live in a clean environment,
and that it is the state responsibility to maintain andprovide the environment. However, the policy does
not indicate how this is to be achieved, nor does it
detail what it covers.
Solid Waste Management Act - 2011
This Act focused solely on SWM and allocatesthe responsibility of the construction and operation ofany disposal facilities, including transfer stations,
treatment plants and landfills, solely with the Local
Government [7]. Although the Act makes provisions
for the management of hazardous, medical, chemical,
or industrial waste to be managed by the generator,
these provisions lack detail and do not dictate howthese hazardous waste streams must be disposed of ortreated. Furthermore, the Act does not provide
directions on the disposal of SW, except that it must
be to a sanitary landfill, with no differentiation
between waste types and classifications. However,the Act specifies that organics must be segregated at
the source from SW and encourages the Local Body
to promote, whenever possible, waste reduction,
waster reuse and recycling [7].
The Act empowers the Local Body to charge a fee
for the SWM services provided, to monitor the SWM,
contract PSOs to carry out this work, assess, evaluate,
and report on the effectiveness of SWM, andimplement report recommendations. While the Act
maintains that regular monitoring must be undertaken,
it does not dictate how often it should be carried out
and how it will be regulated.
The Act leaves the responsibility of SWM
squarely with KMC to implement, manage andregulate. The Act also delegates power to the Local
Body (KMC) to suspend services, such as power andtelephone, and to prevent the sale of house and land
by offenders for breaches of the Act [7].

CURRENT

An overview of the legislation and policies
currently in place for both KMC and Regional
Victoria is provided in this section. How they are
implemented and enforced, and the weaknesses andstrengths of the legislation is also presented.
Kathmandu Municipal City - Legislation
The focus of regulations in KMC is on the timely
collection and disposal of the waste material. The
regulations include provisions for the recovery ofrecyclable materials, such as organics from the waste
stream. The enforcement of the regulations is left to
KMC Council, although, there is little evidence ofactive enforcement by KMC. This is evident in thelack of segregation of recyclable materials, as wellallowing many PSOs to operate without the required
license [15].

Local Government Operation Act, 2074 FY - 2018
SWM activities are largely governed by this Act,with the roles, responsibilities and functions being
spelt out in it [10]. The Act focuses on:• Raising awareness on sanitation and waste
management,

Local Self Governance Act - 1999
This Act allows municipalities to impose service
charges for SWM, as well as for the authority to389

SEE-Mie, Japan, Nov.10-12, 2022

• Collection, re-use, re-cycle and disposal of waste,
and tariffs and their regulation, and• Coordination, collaboration and partnership withprivate sector and non-government agencies for
waste management.

Environment Protection Authority (EPA) has thepower to enforce, prosecute and impose penalties forany breaches of the Act [23].
It is noted that this Act has been superseded by the
EP Act 2017, which places a greater focus on theprevention and risk management than the previous
Act. The EPA is also the regulating authority for thisAct and the subsequent regulations, and it has greater
powers to investigate and prosecute where breachesof the Act have been identified.

Environmental Protection Act 2076 FY - 2019
This is a recent Act that is the result of amending
and consolidating older laws pertaining toenvironment protection into a single Act [10]. The
Central Bureau of Statistics [10] lists the focus of thisAct as follows:• To protect the fundamental right of each citizen tolive in a clean and healthy environment,• To provide the victim with compensation by thepolluter for any damage resulting fromenvironmental pollution or degradation,• To maintain a proper balance between theenvironment and development,• To mitigate adverse environmental impacts on theenvironment and biodiversity, and• To face the challenges posed by climate change.

Local Government Act - 2020
In Victoria, the Act pertaining to the provision of
SWM services, such as household collections, leaves
the responsibilities predominantly with LGAs, likethe Solid Waste Management Act 2011 in Nepal.
However, the regulation of the Act is different.
Instead of self-regulation by LGAs, independent
regulating bodies were set up by the State
Government under the provisions of the Act, toensure that the requirements under the Act were being
met by each LGA. These governing bodies include
Sustainability Victoria (SV) and Department ofEnvironment, Land, Water and Planning (DELWP),
with each body being responsible for different aspects
and being able to feed into legislation for additional
requirements. It should be noted that the regulating
body, EPA, also reports to DELWP. The Act covers
the requirement for LGAs to provide for specificservices to residents, such as access to recovery andwaste drop off facilities, the provision for collectionsof MSW and recycling where practicable and costeffective.
In addition to regulating bodies, Waste andResource Recovery Groups (WRRGs) were alsoestablished, and these are responsible for fixed zones
that cover multiple LGA areas. The role of the
WRRGs is to work directly with LGAs and industry
to establish long-term SWM plans for the regions,
including the mapping, evaluation, and theestablishment of facilities for SW disposal andresource recovery.
LGAs have the authority to recover the costs forthe provision of the required services and can
independently set these costs. However, the charge toresidents must be for cost recovery only, as opposed
to making a profit. This is where the KMC private
operators differ from the LGAs in the provision ofwaste collection and disposal services, since they are
free to charge what they deem is appropriate, and they
operate to make a profit.

Regional Victoria – Legislation
The regulations regarding SWM are actively
enforced, and they include collection and theappropriate disposal and segregation of recyclates.
Audits of LGAs are carried out regularly inaccordance with several different pieces of legislation
by different State Government bodies to ensurecompliance. In addition, industries that specialize in
waste treatment and disposal are also audited
regularly to ensure compliance. Non-compliancepenalties apply and are very high.
Environment Protection Act - 1970
In Victoria, the Environment Protection Act 1970
(EP Act) was established to protect the environment
from harm through the generation, transportation, anddisposal of waste from both industry and LGAs alike[22]. It sets the standards and requirements for
acceptable operating requirements for industries, howwaste is to be handled once generated, how it is to betransported, and the final disposal requirements.
Hazardous wastes have very specific transportation,
storage, and disposal requirements, to ensure not only
the safety of those handling it, but also to protect theenvironment from harm. This is a distinct difference
to KMC, whose regulations do not include suchprovisions. Hence, PSOs in KMC that undertake
resource recovery are at a higher risk of exposure tohazardous wastes, due to a lack of separation of thewaste at the disposal site.
To ensure the provisions of the Act are met, an
independent regulating body oversees the
management of waste within the State. The

ENFORCEMENT AND ENACTMENT
Kathmandu Municipal City
The City is divided into 35 wards, and thecollection of waste from these areas is via a390

SEE-Mie, Japan, Nov.10-12, 2022

combination of private and government resources[17]. In 2015, twelve wards were serviced by KMC,
one ward was serviced solely by a PSO, and theremaining twenty-two wards were serviced by a
combination of KMC and PSOs [15], although it wasreported that only 8 wards are serviced solely by
KMC [16].
The older and more central wards (35% of thearea) are serviced by the staff of KMC at no charge,
due to the difficulty of collecting a service fee in theseareas. The waste in these areas is thrown on the sideof the road and collected from there. The rest of thearea is serviced by private operators who charge asmall monthly service fee for the collection of waste.
This fee is about AUD $4.26 per household, withhigher fees being charged for hospitals and businesses[16]. The vehicles used in the collection of the wastevary extensively from hand carts through to collection
trucks [15].
It is reported that waste generation in KMC is0.464 kg/person/day [6], [15], producing over 669
tonnes/day, of which only 250 tonnes is disposed
daily. Hence, the efficiency of collection appears to
be only 37%, as opposed to the 86.9% that [6] andKMC [15] have quoted. The major barriers to SWM
efficiency are the poor implementation of SWM by
KMC Council itself and the lack of enforcement of
the governing legislation. This has resulted in theaccepted practice of street side dumping. Whilesegregation is included in the legislation, the lack ofsupport and enforcement from the KMC council
results in minimal source segregation. Whileminimum segregation occurs, where it is performed
by PSOs and the informal sector, the products are ofhigh quality and cleanliness, resulting in goodmarkets for the products.

China to Australian recyclates and the subsequentclosure of other international markets, due to thecontamination in the recyclates being recovered,recyclates were stockpiled in the hope that newmarkets would open. The unforeseen impact of thiswas the breakout of fires at several major recycling
facilities [24]. Multiple studies and plans have beendeveloped at a State level in an attempt to address thelack of local markets and processing infrastructure.
However, these studies and plans have beendeveloped largely in isolation of each other.
The disposal of waste at landfill incurs a levy set
and collected by the State Government, with theintent of these funds going back into investment in
SWM infrastructure. Large amounts of State
Government support go to divert organics fromlandfill. However, the capacity of receiving facilities
has not been analyzed or considered. Street-side
dumping of waste is prohibited by law, and highmonetary penalties apply for noncompliant actions.
The current legislation is actively enforced in
Regional Victoria, resulting in household segregationof recyclates and clean streets. However, the focus of
the government is on policies, as opposed to actively
initiating change, and the same practices have beenused for more than 20 years with minimal change.
Change occurs at a very slow rate, with any new
direction taking years to initiate.
The State Government is also heavily reliant on
consultants to conduct studies to inform policy
making. However, there is a lack of expertise to map
out clear aims and objectives for the studies, and toanalyze and link the separate studies that have been
completed. In addition, large commercial operators
also influence policy making by portraying
themselves to be ‘experts’ in SWM, leaving smaller
operators without a voice.

Regional Victoria
DISCUSSION
The implementation of the EP Act 1970 initiatedthe segregation of paper, cardboard, glass, cans, andhard plastics from the waste at the source. Recycledmaterials were then collected and transported to theMaterial Recovery Facilities (MRF) for further
segregation and consolidation, followed by the sale ofthe material to processors, to be converted into new
products. The collection and transportation costs werepassed on to serviced residents.
The LG reform of the 1990s resulted in smaller
disposal sites being closed, waste collections
implemented, and waste disposal sites formalized andcontrolled. The collection services took place under amandatory ‘fee for service’ model [20].
In the late 1990s and early 2000s, the comingledservice was established. All recyclates were placed
into a single bin, instead of being separated by the
product stream. Victoria became reliant on overseas
markets and the income they generated, resulting in
the closure of local markets. After the closure of

The examination of the legislation and thepractices implemented on the ground in Kathmandu
Metropolitan City identified large gaps in both. Whilethe backbone of the legislation is there, it does not go
far enough and fails to address problems such as street
side dumping, leaving the problem solely with themunicipality. The practices on the ground are also aclear indication of the lack of enforcement of theexisting legislation. However, the waste segregation
performed by PSOs results in products of high quality
and cleanliness, ensuring good markets for them.
This contrasts with Regional Victoria. The
legislation is actively enforced, resulting in clean
streets, effective waste, and recycling collections.
However, the legislation is too slow to change with
updates in technology and trends in waste
management. As Victoria is moving towards
becoming a Circular Economy, the legislation is
becoming outdated quickly, with Government bodies
391

SEE-Mie, Japan, Nov.10-12, 2022

struggling to make the necessary changes to ensurethat it is still valid.

2021, Kathmandu, Nepal.
[11] Douglas, K., Ionescu, D., Mainali, B. andPetrolito, J., Integrated Waste Management –Technology Transfer Between Australia and
Nepal – Proc. International Conference on
Environmental
ScienceandSustainable
Development (ICESSD2015), October 2015, pp.
25-26.
[12] State of Victoria, Department of Environment,
Land,
Water
and
Planning,2015,
http://maps.land.vic.gov.au/lassi/SmesUI.jsp.
[13] Australian Bureau of Statistics, National, Stateand Territory Population - Statistics About the
Population and Components of Change (Births,
Deaths, Migration) for Australia and Its States andTerritories, 17 March 2022, Australia.
[14] Rakesh, T.L., Internationalization of Waste
Management Company in Kathmandu, thesis,
Turku University of Applied Sciences,
Kathmandu, Nepal, 2010.
[15] Urban Development Ministry, Solid Waste
Management of Kathmandu Municipal City,
2015, Kathmandu, Nepal.
[16] Pathak, D.R., Director Engineering Study andResearch Centre, Kathmandu, Nepal, personalcommunication, 10 July 2019.
[17] Maze Solution, Kathmandu Valley Temples,
http://kathmandu-valleytemples.com/ktmvalley_php/main.php?site=rundgang&object=079, August 2017.
[18] Pathak, D.R., Integrated Resource Recovery
Approach for Sustainable Solid Waste
Management in Developing Countries, 7 August
2021, Kathmandu, Nepal.
[19] Visit Victoria, Gold Rush History,
https://www.visitmelbourne.com/Regions/Goldfi
elds/Things-to-do/History-and-heritage/Goldrush-history[20] Connoley, R., Victorian Local Government
Reform 1992-1999, Journal of Economic andSocial Policy, Vol. 11, Issue 2, 2007, p.3-21.
[21] Kumar, A., Smith, S.R., Fowler, G., Velis, C.,
Kumar, S.J., Rena, S.A., Kumar, R. andCheeseman, C., Challenges and Opportunities
Associated with Waste Management in India,
Royal Society Open Science, Vol. 4, Published:22
March 2017.
[22] Victorian State Government, Environment
Protection Act 1970, 1 July 2010, Melbourne,State Government of Victoria.
[23] EPA Victoria, Compliance and Enforcement.
https://www.epa.vic.gov.au/about-epa/what-wedo/compliance-and-enforcement.
[24] Hope, Z., Major Fire at Factory Belonging toNotorious Melbourne Recycler, The Age, 9 July
2019, Melbourne, Victoria, Australia.

CONCLUSION
The existing SWM practices and the current
legislation regulating these activities in Kathmandu
Municipal City and Regional Victoria were reviewed
and compared.
Learnings regarding the enforcement of existinglegislation can be transferred to KMC from Regional
Victoria. Conversely, learnings from KMC regarding
the input and value of smaller operators can be takenback to Regional Victoria and would aid in thetransition to a truly Circular Economy.
REFERENCES[1] The World Bank, Solid Waste Management, 2022
https://www.worldbank.org/en/topic/urbandevelo
pment/brief/solid-waste-management.
[2] Heidari, R., Yazdanparast, R., and Jabbarzadeh,A., Sustainable Design of a Municipal Solid
Waste Management System Considering Waste
Separators:
A
Real-World
Application,
Sustainable Cities and Society, Vol. 47, May
2019, 101457, p. 14.
[3] Shekdar, A.V., Sustainable Solid Waste
Management: An Integrated Approach for AsianCountries, Waste Management, Vol. 29, April
2009, pp. 1438-1448.
[4] Modak, P., Wilson, D.C. and Velis, C., Waste
Management: Global Status, Global Waste
Management
Outlook,
UnitedNations
Environment Programme, 2015, pp. 51-124.
[5] Othman, S.N., Noor, Z.Z., Abba, A.H., Yusuf,
R.O. and Hassan, M.A.A., Review on Life Cycle
Assessment of Integrated Solid Waste
Management in Some Asian Countries, Journal of
Cleaner Production, Vol. 41, February 2013, pp.
251-262.
[6] Asian Development Bank, Solid Waste
Management in Nepal: Current Status and Policy
Recommendations, 2013, Mandaluyong City,
Philippines.
[7] Government of Nepal Central Bureau of
Statistics, National Population and Housing
Census 2011, November 2012, Kathmandu,
Nepal.
[8] World Population Review (2015) Kathmandu
Population, http://worldpopulationreview.com/
world-cities/kathmandu-population.
[9] Shreshta, V.P., A Concise Geography of Nepal:
Climate, 2007, Mandal Publications, Kathmandu.
[10] Central Bureau of Statistics, Current Kathmandu
Macroeconomic and Financial Situation, April392

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE IMPACT OF THE COVID-19 PANDEMIC ON RESORT AREAS
AND ITS RELEVANT TO AGRICULTURAL MARKETS-A CASE STUDY OF KARUIZAWA, NAGANO PREFECTURE, JAPANReiko MACHIDA1, Yuya MIKAMI2, Waya KOBAYASHI1, Nobuhiko TANAKA3, Teruaki IRIE1,
Hijiri SJIMOJIMA1, Tomohiro KIMATA4 and Shigeyuki MIYABAYASHI1
1
Department of Regional Regeneration Science TOKYO UNIVERSITY OF AGRICULTURE, Japan,
2
Tohoku Nippon Ham Co., Japan; 3TOKAI University, School of Tourism, Japan, 4SATOYUME Co.Japan
ABSTRACTIn Japan, the development of resort towns in rural areas began during the Meiji period (1868-1912). Karuizawa
Town in Nagano prefecture with a history of over 100 years has been the most prominent of these resort towns. In
the 1850s, Japanese farm villages began facing challenges such as the weakening of local communities, anddifficulties of continuing agricultural work because of shrinking and aging populations. On the other hand, due tothe COVID-19 pandemic, agricultural towns have experienced increased popularity as people started relocating to
the countryside or living in multiple locations. In this study, we conducted a literature review and an interview
survey in Karuizawa, Nagano Prefecture, to shed light on the development of tourism in the postwar period, andto examine the impact of COVID-19 on resort areas and their relationship to the local economy, particularly
agriculture. As a result, we have been able to confirm an increase in the town’s population due to new residents
moving in or increased long term stays in conjunction with working holidays and educational organizations. It also
became clear that the population increase has led to a positive impact on the local economy for agricultural produce
and a higher name recognition for local products..
Keywords: Tourism, Vila,Agricultural markets, COVID-19,Karuizawa
INTRODUCTION

According to a review of studies on sustainable
tourism from an environmental, social, and economic
perspective, Miyagawa (2020) points out that in orderto manage cultural landscapes, it may be necessary tobalance the needs of communities and tourism[4].
Putu Hermawati (2019) analyzed the characteristics
of individual and group tours to the island of Bali inorder to model the chains and modes of tourism. His
research helped the government create effective
marketing strategies, draft regulations, innovate newtechnologies and provide infrastructure to better
manage traffic[5]. Lily Soraya (2017) highlights theimportance of the role and involvement of thegovernment and private sector in marine ecotourism
related to biodiversity conservation in the Celib
Islands[6]. Gunawan Prayitno (2019) reports that thebetter the social capital in the community, the betterthe management of environmental tourism[7].
However, there are still only a few research
reports discussing the state of sustainable tourism
after COVID-19. Following the outbreak of the
COVID-19 pandemic in Japan, rural villages havegained increased attention. Karuizawa Town in
Nagano Prefecture is one of the leading vacationhome areas in Japan with a history of more than ahundred years as a holiday resort. The number of newresidents who moved here following the outbreak of
the pandemic has been increasing. In addition, local
industries based on agriculture have also become
more active, and the town is now gaining attention asa model for a sustainable tourist destination.
Therefore, this study conducted a literature

The tourism industry has suffered a major
economic blow from COVID-19 due to thegovernment restrictions imposed on the movement
and gathering of people. According to the UNWTO(World Tourism Organization), in 2020 the COVID19 pandemic will result in a more than 70% year-onyear decline in international tourist arrivals whichtranslates to 800 million to 1 billion fewer tourists
worldwide and is also expected to result in a loss of
100 million jobs. In addition, in 2021, international
tourism is expected to grow by a meagre 4%,
significantly below pre-pandemic levels, and therecovery of the tourism industry is still expected to besluggish[1].
On the other hand, the COVID-19 pandemic has
led to an increased interest in relocating to rural areasand people living in two separate locations in Japan(Tanaka, 2020) [2]. The UNWTO report also revealed
the criteria that were important to tourists following
the outbreak of COVID-19. They were the following:"safety and security", "price", and "location andbrand"[3].
Considering the changes in tourists' preferences
following COVID-19, discussions toward sustainable
tourism have become more active, specificallytowards "tourism that is responsive to the needs ofvisitors, the industry, the environment, and thecommunities that host them, while taking full accountof current and future economic, social, andenvironmental impacts."
393

SEE-Mie, Japan, Nov.10-12, 2022

review and interview surveys to clarify thedevelopment
processof postwar tourism
development in Karuizawa, Nagano Prefecture, andto examine the impact of COVID-19 on tourism in
Karuizawa and its relationship to the local economy,
particularly agriculture. Specifically, we identified
the new demands of tourism in Karuizawa after
COVID-19, the relationship with holiday homeresidents, and the impact of the agricultural market on
the local economy.

120 days per year due to the influence of air currents
approaching from the Kanto region. Annual
precipitation is 1,000 to 1,500 mm, and the lowest
temperature in the winter is nearly 15 degrees below
zero, although snowfalls of 30 cm or more has rarely
been recorded.
Karuizawa town lies on an important, historicalland transportation route between the Sekisoku region
and Nagano Prefecture, but over time it has
transformed into a separate, summer resort area. The
city is still in the process of being redeveloped.
The number of farm households, the size of the
farmer population, and arable land in Karuizawa havedecreased in all categories except for tree-planting.
Comparing the total number of farm households(units) between 1990 and 2015, the number has
decreased by about half. The number of full-time
farming households first increased from 69 in 1990 to
72 in 2005, and then decreased to 57 in 2015. The
number of farmers per farming operation has also
decreased from 4 to 1, indicating a lack of successors.
In terms of the farmer population, the number offarmers has decreased from 1,608 in 1995 to merely
331 in 2015. Clearly, the aging of farmers and lack ofsuccessors has been a central issue.
On the other hand, the Karuizawa Hotchi
Farmers Market has become a tourist attraction
drawing 262,315 visitors annually (as of March 2020).
It was opened in 2016 as a retail sales center offeringa variety of popular, fresh local vegetables, including
brand-name vegetables marketed under the name"Karuizawa Kirishita Vegetables" (Fig.1)..
Karuizawa Town's development into a resortarea began in 1888 when Canadian missionary A.C.
Shaw built a villa on Mt. Otsuka in the older area of
Karuizawa (Kyu Karuizawa). The first Japanesevacation home was built there by Yujiro Hatta in 1893.
Later, in the early Taisho period (1912-1926), with
the inflow of private-sector real estate capital,
development and subdivision of the area began. In the
beginning, Kyu Karuizawa was the center of the villaarea, but development gradually moved southward
and westward, expanding the area in size which has
continued to this day.

METHOD
This study analyzes the characteristics of tourism
development and holiday home development in
Karuizawa during the period between 1950, whenholiday homes and transportation networks weredeveloped and 2020, the beginning of the COVID-19
pandemic. This study also examines the process andsustainability of these developments in the town of
Karuizawa.
A literature survey was conducted concerning thechanges in holiday home development and tourism
development during the 1950 to 2020 period broken
down into decades. In this literature survey, we
researched the history of holiday home development
and tourism development and the current state of theresort areas. We examined the changes in the numberof households, infrastructure, and transportation[8][9].
An interview survey was conducted on September
9, 2020, with the Karuizawa Tourist Association andthe Tourism and Economy Division of the Karuizawa
Town Hall regarding the current state of Karuizawa
and the resort areas in the wake of the COVID-19
pandemic. Then, on November 1, 2021, anotherinterview survey was conducted with the officials of
the Karuizawa Town Agricultural Market regarding
the state of post-COVID-19 use of the agricultural
market.
RESEARCH AREA
Karuizawa Town, located on the eastern edge ofNagano Prefecture right next to Gunma Prefecture, isa highland town spread out on the southern slopes ofMount Asama (2,568 m above sea level) at anelevation of 900 to 1,000 m above sea level. Mount
Asama, the symbol of Karuizawa Town, is a triple
stratovolcano representative of Japanese volcanoes,
that has repeatedly erupted every year until the 1960s.
The area’s climate is cool, befitting a summer
resort area, with an average annual temperature ofaround 8 degrees Celsius. Even in the summer, theaverage temperature remains around 20 degrees
Celsius, and the maximum temperature rarely
exceeds 30 degrees Celsius. Karuizawa is also known
for its foggy summers. Fogs occur on an average of

Fig.1 The Karuizawa Hotchi Farmers Market
THE CHARACTERISTICS OF TOURISM
DEVELOPMENT AND HOLIDAY HOME
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SEE-Mie, Japan, Nov.10-12, 2022

DEVELOPMENT IN KARUIZAWA

Negative growth period (2001-2019)
This period is defined as a negative economic
growth period because real disposable income wasnegative. This era can be characterized by the lack ofmajor development and the town's active promotionof community development policies. In addition,
vacation home development increased slightly during
this period. Although the total number of holiday
homes has continued to increase, the number ofpermanent homes has declined once again due to thesluggish growth in national income.

Japan's period of rapid economic growth after
WWII (1950-1973)
During this period, along with the development oflarge-scale golf courses and ski resorts, Karuizawa
experienced a rapid boost in popularity as a locationfor vacation homes for high-income earners and as asummer resort, with an increase in the number ofsummer homes and entertainment facilities built inthe surrounding areas. During this development ofvacation homes, private companies also developed
areas to the north and south of the main town. In thoseareas, the Karuizawa Cultural Association and the
Karuizawa Oiwakekai residential communities were
established. In terms of tourism policies, theKaruizawa Town Nature Preservation Measures
Outline was issued, establishing strict standards forthe land area, floor-area ratios, and building-to-landratios.

Trends of villas in Karuizawa Town in the
COVID-19 Pandemic
According to our interview survey, there werevarious challenges and prospects faced by the
Karuizawa area during the COVID-19 pandemic. The
first is the growing need for vacation home sites.
There was a tendency for residents who owned
properties at two or more locations to movepermanently to their vacation homes in Karuizawa
Town beginning March 2021. The push towards
teleworking has led to more spaces in the region
allowing for telework and to an increase in thenumber of hotels and cottages that offer telework
opportunities as a business. As a result of these trends,
we can see a marked increase in land prices forvacation homes.

Period of stable growth (1974-1986)
Reflecting the “100 million people leisure boom”,
cultural facilities such as art museums and libraries
were opened one after another, and the establishmentof facilities where people could experience nature has
also greatly increased. The development of holiday
homes however resulted in conflicts between
vacation home owners, permanent residents, and the
local government. Frustration among local residents
also grew due to rising land prices caused by thepurchases of land for investment purposes.

INTERVIEW SURVEY OF THE KARUIZAWATOWN REGARDING THE STATE OF POSTCOVID-19

Bubble economy period (1986-1991)
During this period, there was a holiday homeboom, but unlike with other tourist destinations, there
was no largescale development in tourism. It was
mostly limited to the establishment of sports facilities
and outdoor experience facilities. In terms of vacationhome development, there was no development
financed by private capital, but rather small-scale
weekend home development and a gradual increase in
the number of permanent residents.

The business concept of the Hotchi Farmers
MarketEven though the Karuizawa area has long been a
tourist destination, the Karuizawa Minami area hasremained a primarily agricultural one. In 2002,
residents requested from the town of Karuizawa to set
up a tourist-type farmers' market facility. In 2014, theKaruizawa Town Office began plans to build the
Hotchi Farmers Market.
The main objective of Hotchi Farmers Market was
to promote Karuizawa's food culture. The idea was tomake Hotchi Farmers Market not only a direct sales
outlet, but also a place to promote Karuizawa's foodculture. The concept of Hotchi Farmers Market is tofunction not just as a direct sales venue for the
purpose of purchasing groceries like in a supermarket,
but to serve as a physical space where people cangather. It offers facilities such as a sub-conference
room, and provides space to various tenants such as
several restaurants of Karuizawa, aiming to run adirect sales venue where people can not only shop,
but enjoy their stay.
Number of customers at the Hotchi Farmers
MarketLow-growth period (1992-2000)
This period is characterized by a stable andgrowing number of tourists due to the development of
a new high-speed transportation network and theestablishment of an enormous outlet mall, which hassuddenly brought the area closer to the metropolitan
area. In addition, although there have been no
significant large-scale holiday home developments,
the area has transformed into a shopping-oriented
tourist destination in addition to an experienceoriented and nature-oriented tourist destination.
There were few vacation home developments during
this period, and what we can see here is
predominantly long-term use of the villas.

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SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Number of visitors in Hocchi Farmaers
Markket [9]The number of customers in April 2016, when thepark opened was about 7,000, but in May it reached
20,000, showing a significant increase duringconsecutive holidays and other events. The highest
number of visitors in each year was in August, most
likely due to the summer vacation season and otherlong-term vacations. For the six-month period from
May to November, the number of visitors recorded
was over 20,000 per month, while the number ofvisitors in winter trended down. The number of users
was on an increasing trend from 2016, the year of
opening to 2018, but the number of users decreased
due to the COVID-19 pandemic. Nevertheless, thenumber of users is expected to recover in 2021.
The Hotchi Farmers Market conducts regularvehicle license plate number checks. Accordingly,
90% of the vehicles had license plates from outside
the prefecture, 20% of which were villa residents. In
addition, the results of a customer surveys, whichwere conducted about once every four months,
revealed that many tourists from Yokohama and otherareas use the Ken-O Expressway, the Higashi-Kanto
Expressway, and the Kan-Etsu Expressway.

2019 fiscal year 2020 fiscal year 2021 fiscal year
January

5,594

2,751

5,747

February

7,555

7,081

5,919

March

10,501

10,740

8,975

April

16,470

7,522

14,967

May

27,166

June

22,71019,90019,988July

30,74825,491

30,241

August49,81941,64339,668September

36,43431,75330,578October

23,54029,10331,284

November

21,791

22,66623,962

December

9,987

9,155

11,163

Total aomount

262,315

207,805

243,983―

21,491

Characteristics of farmers who have stalls in the
Hotchi Farmers Market
The Hotchi Farmers Market has a Karuizawa
direct sales management committee, and farmers are
members of this organization. There are two
membership organizations: farm product producing
members and souvenir/processed goods producing
members. The designated manager selects thebusinesses for the fairs and the processed goods to be
sold, which are managed in cooperation with thedirect sales center.
About 60% of the 226 members of the Karuizawa
direct sales center were local farmers of Karuizawa.
There are some cases where the family members lived
separately, such as when the wife and children wereJA (Japan Agricultural Cooperation Agency)
members and the husband is a member of the Hotchi
Farmers Market. The average Karuizawa direct sales
shop management committee member is in their late70s. These previously retired farmers grow theirproduce as a hobby or to earn additional income.
The designated manager focuses on side dishes
and processed foods when selecting farmers. Some of
the members are farmers who have acquired
qualifications for producing processed food items,
such as jams, side dishes, and other processed
products. Some members deliver both farm produce
and processed food items.

Number of customers at the Hotchi Farmers
Market
The number of customers in April 2016, when thepark opened was about 7,000, but in May it reached
20,000, showing a significant increase duringconsecutive holidays and other events. The highest
number of visitors in each year was in August, most
likely due to the summer vacation season and otherlong-term vacations. For the six-month period from
May to November, the number of visitors recorded
was over 20,000 per month, while the number ofvisitors in winter trended down. The number of users
was on an increasing trend from 2016, the year of
opening to 2018, but the number of users decreased
due to the COVID-19 pandemic. Nevertheless, thenumber of users is expected to recover in 2021.
The Hotchi Farmers Market conducts regularvehicle license plate number checks. Accordingly,
90% of the vehicles had license plates from outside
the prefecture, 20% of which were villa residents. In
addition, the results of a customer surveys, whichwere conducted about once every four months,
revealed that many tourists from other areas use theHigashi-KantoExpressway,the Kan-Etsu Expressway.

396

SEE-Mie, Japan, Nov.10-12, 2022

Agricultural products and local brands sold at the
Hotchi Farmers Market
The vegetables produced in Karuizawa and solddirectly by the Hotchi Farmers Market are marketed
as "Karuizawa Kirishita Vegetables". During thesummer, when the temperature rises, Karuizawa's
highland plateau produces fog in the morning, andthanks to the humidity, the highland vegetables growwithout their surface drying out, which leads to thevegetables’ softness and sweetness. This is the reason
behind the name "Karuizawa Fog Vegetables".
"Karuizawa Kirishita Vegetables" is the brand namepersonally registered by one of the current
representatives of Hatsuchi Farmers Market.
Therefore, only products sold at Hotchi Farmers
Market can use the brand name Karuizawa Kirishita
Vegetable. This brand name has helped raiseawareness for the Hotchi Farmers Market and made it
popular, especially among holiday home residents.
Typical vegetables sold at the Hotchi Farmers
Market are cabbage, lettuce, Chinese cabbage, corn,and spinach. The number of cabbages grown under
the fog shipped each morning is two to three hundredwith more cabbages added during the peak season.
The unsold produce for sale was 1 percent of the total
shipment, which means it was almost completely soldout. According to interviews with the Hotchi Farmers
Market, one of the reasons for the sell-out is that there
are many repeat customers who are holiday homeresidents.
In addition, Hotchi Farmers Market tries to sellvegetables of high quality and freshness. For
example, the direct sales staff checks the freshness ofvegetables that have short shelf lives like eggplants
and cucumbers when placing them on the store
shelves. Farmers use a so called "Post System," inwhich they ship before opening and sales data for themorning is sent to their cell phones so that they can
reship around noon. Highly motivated farmers may
even visit the store to monitor the situation on thesales floor to determine their course of action for theafternoon.

purchase all ingredients necessary for cooking one
stop at the Hotchi Farmers Market. By responding to
the requests of villa residents in such a way, the store
was able to see an increased number of customers.
Since the Hotchi Farmers Market facility is a close
contact environment, it was treated equally to generalsupermarkets by the government in May 2020 when
the state of emergency was declared, so the decision
was made to temporarily close the store. Afterwards
however, the company decided not to close the store,even when the state of emergency was declared again,
based on the view that the store should remain open
while ensuring safety since it is a facility closely
connected to people's lives and the environment of
Karuizawa.
As of March 2022, the number of visitors was
12,000, up 111% from the previous year. In addition,
the average price per item purchased has also
increased and total sales were up 131% from theprevious year.
In the snacks and refreshments section, the upper
section displays snacks and refreshments that are
packaged in small bags and easy to eat by hand in thecar, rather than the large boxes of local souvenirs
typically displayed at direct sales venues ofagricultural products. The local delicacies of
Karuizawa, such as okowa also became popularamong villa residents, and by 2021, after the Corona
pandemic, sales at the side dish corner have reached
6 million to 10 million yen per month.
THE
IMPACT
OF
THE
COVID-19
PANDEMICON RESORT AREAS AND ITSRELEVANT TO AGRICULTURAL MARKETS
According to our interview survey, there werevarious challenges and prospects faced by the
Karuizawa area during the COVID-19 pandemic. The
first is the growing need for vacation home sites.
There was a tendency for residents who owned
properties at two or more locations to movepermanently to their vacation homes in Karuizawa
Town beginning March 2021. The push towards
teleworking has led to more spaces in the region
allowing for telework and to an increase in thenumber of hotels and cottages that offer telework
opportunities as a business. As a result of these trends,
we can see a marked increase in land prices forvacation homes.
The second trend is the newly transformed
relationship between the local community and thevacation home residents as a result of the increase in
the number of new residents moving to and settling
down in the area. Following the outbreak of the
COVID-19 pandemic and the push towards
teleworking, the number of people moving out of theTokyo Metropolitan area has increased. However,unlike in the case of the popular vacation home areasin the Hakone, Nasu, and Tateshina regions, theHoliday home residents and THE IMPACT OF
THE COVID-19 PANDEMIC
The users of Hotchi Farmers Market include few
permanent residents, many of them are the vacationhome residents. Therefore, the employees of Hotchi
Farmers Market have made efforts to becomeacquainted with the holiday home users, and often ask
these users directly about their requests. For example,
holiday home residents often find the road to the
Tsuruya Karuizawa supermarket heavily congested
during the summer. For this reason, they requested
that the Hotchi Farmers Market store carry regulardaily food items such as olive oil. Therefore, as a new
idea at the store additional supplementary cooking
ingredients, such as dressings and pasta have beenplaced near the vegetables, allowing customers to397

SEE-Mie, Japan, Nov.10-12, 2022

residents of Karuizawa had formed uniquecommunities in the vacation home areas, including
the Karuizawa Association (1916), Karuizawa
Minamihara Cultural Association (1932), Karuizawa
Cultural Association (1953), and Karuizawa Cultural
Association (1954), Karuizawa Oiwake-kai (1963),
and Karuizawa Shirakaba-kai (2013). Unlike urban
communities, these unique communities are places
where people can enjoy entertainment, talk aboutbusiness, share their values, and stimulate each other,which is one of Karuizawa's strengths.
Third, there is a growing demand for education,
agriculture, and forestry as basic means of livelihood.
The demand for education in Karuizawa is increasing
due to the COVID-19 pandemic and the risingnumber of families moving to and settling down in
the area. In particular, more and more businesspeople
from the IT industry, mostly in their 30s and 40s are
moving into the area bringing their families andchildren, further increasing the demand for schools.
As an example, many parents in Karuizawa areenrolling their children into the Kazakoshi Gakuen, aprivate, integrated kindergarten, elementary, andmiddle school, and into United World College ISAK
Japan, an international school.Table numbers andlabels should be placed on top of the table, hanging
by 12.5 mm, and left- and right-justified. Number thetables consecutively and locate them after and close
to where they are first referenced. Leave at least one
line space between the table, label and the text. Tables
should be auto-fit to a single column or the wholewidth over two columns and no vertical lines orborders are needed.
Regarding agriculture, an increasing number offarmers are producing a wider variety of leafy
vegetables in smaller quantities, growing for example
not only regular lettuce, but also green curl lettuce
and sunny lettuce. Furthermore, farmers are also
beginning to grow rhubarb and other rare vegetables.
While local residents tend to go to local, inexpensive
supermarkets, the holiday home residents prefer topurchase fresh vegetables and fruits sold at the
Karuizawa Hotchi Farmers Market which serves as a
new source of motivation for the farmers to continue
to work in agriculture. Karuizawa's agriculture andvegetables are gaining increased attention, and a
project is underway to promote agriculture on the 19hectare idle farmland in Karuizawa's southern district.
There is also demand for agricultural employment
from outside the prefecture, and it is expected thatinterest in and desire to work in agriculture among
Karuizawa's vacation home residents and outsiders
will increase even further.
In the forestry industry, Karuizawa Town has alumberyard that aims to make effective use of
harvested trees and recycled resources. Pruned
branches are processed into chips, which are offeredto people free of charge. Since holiday home residents
spend about 400,000-500,000 yen per year on

firewood, we believe that the demand for firewood
will continue to increase in the future as well.
ACKNOWLEDGMENTS
This study was supported by the Town of
Karuizawa and the Karuizawa Tourism Association.
We are grateful to Dr. Yuichido Hirano, Forestry andForest Products Research Institute, for helpful
discussions. In addition, this research was partially
carried out at Kakenhi 20H04442.
REFERENCES[1] UNWTO., WORLD TOURISM
BAROMETER, https://www.e-unwto.org/,2021[2] Nobuhiko TANAKA.,A STUDY ON THE
INFLUENCE WHICH COVID-19 BROUGTTO TOURISM AND ON THE WAY OF THE
NEW TOURSIM IN JAPAN., Journal of theJapanese Institute of LandscapeArchitecture,2021,pp.246-249.
[3] UNWTO., TOURISM UNITED, RESILIENT
AND DETERMINED,
https://www.unwto.org/2021-a-year-inreview,2021[4] Tomoko M, Sakura Y, Sayuri Y,Shinpei Y and
Masahiro T.,CHARACTERISTICS OF
CULTURAL LANDSCAPE IN THE
GATEWAYTOWN OF KUDOYAMA,International Journal of GEOMATE Vol. 19,
Issue76,2020, pp.1467-147[5] Putu H, Sakti A. A, Muhammad I. R andSumarni H.,CHOICES MODELS OF TRIPCHAIN AND TRANSPORTATION MODE
FOR INTERNATIONAL TOURISTS IN
TOURISM DESTINATION ISLAND,International Journal of GEOMATE, Vol. 66,
Issue 55, 2019, pp. 195-203.
[6] Lily S, Eka P and Kuristiyanto., ROLE OF
GOVERNMENT AND PRIVATE SECTOR IN
MARINE ECOTOURISM RELATED TOCONSERVATION OF BIODIVERSITY IN
SERIBU ISLANDS, International Journal of
GEOMATE, Vol. 14, Issue 43, 2018, pp.140147.
[7] Gunawan P, Nindya S, Ike K, Putri K,. SOCIALCAPITAL IN POVERTY ALLEVIATION
THROUGH PRO-POOR TOURISM CONCEPTIN SLUM AREA (CASE STUDY:
KELURAHAN JODIPAN, MALANG CITY) .
International Journal of GEOMATE, Vol. 16,
Issue 55, 2019, pp.131-137.
[8] KARUIZAWA TOWN,. Karuizawa Town
Directory, commemorating the 95th anniversaryof the town's establishment. 2018，p.65[9] KARUIZAWA TOWN,. The number of visitorsof Hocchi Farmers Market,
https://www.town.karuizawa.lg.jp/www/content
s/1528425604611/simple/7.nougyou.pdf，
2021.1.13.
398

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

SOCIAL COSTS BY OCCURRING ROADKILL OF
AMAMI RABBIT IN KAGOSHIMA, JAPAN
1,3

Hideyuki Ito1, Yosuke Imahashi2 and Takahiro Fujii3
Nihon University, Japan; 2 East Japan Railway Company, Japan

ABSTRACTThe Amami Oshima and Tokunoshima Islands in Kagoshima Prefecture, Japan are the main habitats of theendemic Amami rabbit (Pentalagus furnessi). As a result, it was listed as an endangered species on the Red Listof the Ministry of the Environment, Japan. However, the Ministry of the Environment, Japan has implemented amongoose control project on Amami Oshima, and both the population and habitat of the Amami rabbit have been
increasing since around 2015. However, the number of traffic accidents involving Amami rabbit and vehicles has
been increasing every year, and also recorded the worst ever record of 56 accidents in 2021. In addition, the United
Nations Educational, Scientific and Cultural Organization (UNESCO) has pointed out the need to strengthen
roadkill measures for the Amami Oshima Island in 2021, when the island is registered as a World Natural Heritagesite. In this study, we estimated the economic value of Amami rabbit using the Contingent Valuation Method, andalso estimated the social cost of roadkill. As the results, it was indicated that significant social economic losses
have occurred due to roadkill outbreaks of the Amami rabbit.
Keywords: Roadkill, Contingent valuation method, Amami rabbit (Pentalagus furnessi), Social cost

INTRODUCTION

Organization (UNESCO) has pointed out the need tostrengthen measures against roadkill by Amami
rabbit and other animals in conjunction with theregistration of Amami and Okinawa as World
Heritage sites.
The purpose of this study is to estimate theeconomic value of the Amami rabbit in Amami
Oshima using the Contingent Valuation Method(CVM) and to estimate the social costs of roadkill,
and to show the importance of conservation of thisanimal.

Amami Oshima Island in Japan is located in theocean between the Kagoshima mainland and the
Okinawa mainland and is rich in nature andbiodiversity, and is home to manJPYdemic and rare
species such as the Amami rabbit (Pentalagus
furnessi) and the Lidth's jay (Garrulus lidthi), etc. It
is recognized as a unique ecosystem, and on July 26,
2021, Amami Oshima and Tokunoshima wereregistered as a World Natural Heritage site together
with the northern Okinawa Main Island and Iriomote
Island were registered as "World Natural Heritage"
together with the northern Okinawa Island andIriomote Island.
The Amami Oshima and Tokunoshima Islands in
Kagoshima Prefecture are the main habitats of theendemic Amami rabbit, but the introduction ofmongooses in 1979 for the purpose of exterminationof habu and other animals resulted in predation and a
decline in both population numbers and habitat area.
As a result, Amami Oshima was listed as Endangeredon the Red List of the Ministry of the Environment.
However, the Ministry of the Environment has
implemented a mongoose control project on Amami
Oshima, and both the population and habitat of theAmami rabbit have been increasing since around2015.
However, the number of roadkills of Amami
rabbit by vehicles running over them has been
increasing every year, with Amami Oshima Island
recording 50 road kills in 2020 and a record 56 roadkills/year in 2021 [1]. Against this background, theUnited Nations Educational, Scientific and Cultural

LITERATURE REVIEWThe Ministry of the Environment, Japan [2]estimated the economic value of the Tsushima
leopard cat (Prionailurus bengalensis euptilurus)
conservation and propagation project to be about 52.7
billion JPY per year by estimating the Willingness To
Pay (WTP) for the Tsushima leopard cat using CVM,
assuming an increase in population due to the project.
Based on the occurrence of roadkill of Amami
rabbit within Amami Oshima Island, Heijo et al. [3]found that road width may affect both the length oftime animals stay on the road and the speed ofvehicles, which in turn may induce roadkill.
Ito et al. [4] estimated the social external costs ofaccidents between Ezo sika deer (Cervus nippon
yesoensis) and vehicles in Hokkaido using CVM, andfound that 62.9% of the external costs were caused by
Ezo sika deer running over and killing animals, which
accounted for a high proportion of the total costs.
The Research Institute for Global Environmental
399

SEE-Mie, Japan, Nov.10-12, 2022

Strategies et al. [5] estimated the value of wildlife
conservation in the Yanbaru region of Okinawa
Prefecture using CVM, and found that the WTP perhousehold was 772 JPY. They also conducted aselection experiment and found that the marginal
willingness-to-pay for increasing the protected areaof forest by one square kilometer is 2.9 JPY perhousehold per year, the marginal willingness-to-pay
for increasing the number of Yanbaru rail birds(Hypotaenidia okinawae) by one bird is 1.0 JPY, andit was estimated to be 2,423 JPY for special
protection to avoid extinction of the Yanbaru longarmed scarab beetle.
Mitsui and Kubo [6] found that the highest BWS(Best-Worst Scaling) rating of the respondents'
preference for the use rules in Kanehakubara, a virginforest in the Amami Islands National Park, was"Mandatory guided tours," followed by "Shuttle buses,""Limit the number of people," and "Raise money forcooperation. The second highest BWS was "shuttle
buses," followed by "limiting the number of visitors,"and "asking for cooperation money. The results revealed
that "free use" was the least desirable option.
Sasaki et al. [7] used CVM to estimate social
losses caused by raccoons in Hokkaido, including
ecosystem destruction, damage to the living
environment, and infectious disease damage. The
results indicated that the WTP was 153.3 JPY perhousehold per month, which represents an annual lossof approximately 5.04 billion JPY in whole Hokkaido.
Qiu and Hashimoto [8] conducted an economic
evaluation analysis of the tourism value of Amami
Oshima Island using the travel cost method, andfound that the portion of tourism services generated
annually that corresponds to public recreation
services is equivalent to about 10 billion JPY whenevaluated in terms of consumer surplus. The resultshows that the portion of the public recreation
services generated every year is equivalent to about
10 billion JPY.
Kurt and Peter [9] examined the method of
calculating the value of deer in deer-vehicle collisions.
From the viewpoint of economics, they stated thatmost of the values of deer estimated in previous
researches were basically expenditure indicators, noteconomic values, and suggested using consumer
surplus or net WTP as a measure of deer value.
Previous studies have been conducted on various
endangered species using CVM to calculate
economic values and to estimate the social costs ofroadkill. However, there is a few studies, and nostudies have been conducted on the Amami rabbit.

Kagoshima Prefecture, Japan. It is designated as a
special natural monument of Japan, a domestic rarewild animal and plant species, and an endangered
species on the Ministry of the Environment's Red Listof Threatened Species IB. In the past, the Amami
Oshima Amami rabbit could be seen in almost all areasof the island. However, in 1979, mongooses and habu
were released into Naze, Amami City, for the purposeof exterminating bear rats, and the number ofmongooses continued to increase and their habitat
expanded. In 2005, mongooses were designated as"Specified Invasive Alien Species" under the Invasive
Alien Species Act, and extermination began in earnest,
and the number of Amami rabbit inhabitants and theirhabitat area have been increasing since around 2015.
On the other hand, the number of roadkill
incidents by Amami rabbit has been increasing every
year, with Amami Oshima Island recording the worst
ever record of 56 incidents/year in 2021. Amami
rabbit is nocturnal, acting from nightfall to morning,and has a habit of defecating in open areas to avoid
predators2) . In addition, their black body color andsmall body size make them less visible to drivers. For
these reasons, roadkill is likely to occur. Also.
Roadkill occurs throughout the year, but tends tooccur more frequently in fall and winter, whichcoincide with the breeding season of the Amami
rabbit as shown in Fig.2.

Fig. 1

Amami rabbit

Fig. 2

Number of road kills on Amami Oshima

SUMMARY OF AMAMI RABBITThe Amami rabbit (Fig.1) is endemic only to
Amami Oshima and Tokunoshima Island in400

SEE-Mie, Japan, Nov.10-12, 2022

ESTIMATION OF SOCIAL COST BYROADKILL OF AMAMI RABBIT USING CVM

asked why they were against the payment.
Finally, to conduct an analysis of factors
influencing WTP for Amami rabbit conservation, we
asked about personal attributes. We asked
respondents about their "awareness of protecting thenatural environment and living creatures," "frequencyof participation in activities to protect the naturalenvironment and living creatures," "awareness of theterm 'Amami rabbit," "awareness of the term'roadkill,'" "awareness of the term 'over tourism,'""car driving license possession status," "awareness ofmaking trips to Have you ever visited Amami OshimaIsland?", "Have you ever seen an Amami rabbit in the
wild?," "occupation," "annual household income,""gender," and "age," respectively.

Outline of Questionnaire Survey
To estimate the social costs of roadkill by the
Amami rabbit, a web-based survey using Rakuten
Insight company was conducted on December 22-24,
2021, targeting Rakuten Insight members aged 20-79
living in whole Japan (47 prefectures). The survey
was conducted from December 22 to 24, 2021, and1,500 samples (500 samples x 3 patterns) wereobtained.
At the beginning of the questionnaire, we usedcharts and photographs to explain the survey and thecurrent status of the Amami rabbit in order to give
respondents an accurate understanding of the survey
and the current status of the Amami rabbit. In the
middle part of the questionnaire, we explained theutilization of the Amami rabbit and the status ofroadkill occurrence. At the end of the questionnaire,questions were asked to confirm the level ofunderstanding of the questionnaire content. The
reason for this was to ensure that only those samples
who correctly understood the content of thequestionnaire were extracted for analysis. Questions
asking about WTP for Amami rabbit conservationand questions asking about personal attributes werethen asked. As a result, out of the 1,500 samples
collected, 1,041 samples were used in the analysis.
In the question asking about the WTP for Amami
Oshima roadkill conservation, it was assumed that inorder to reduce the number of roadkills to zero onroad segments where roadkills occur frequently on
Amami Oshima, measures would be implemented toprevent roadkills by installing Amami Oshima
roadkill prevention fences and warning signs and by
installing speed humps in the road. We explained ascenario in which a nature conservation organization
would solicit donations from the Japanese public only
once to implement these measures, and asked the
WTP in a two-step, dichotomous-choice approach as
shown in Table 1.
We explained a scenario in which a conservationgroup would solicit donations from the Japanesepublic only once to implement these measures, andasked the WTP in double-bounded Dichotomous
Choice. The initial amounts to be offered were set at
20 JPY, 40 JPY, and 60 JPY, and a scope response
test was conducted by offering amounts for one, five,and ten Amami rabbits. Then, in order to eliminate
resistant responses, "respondents who answered thatthey were unwilling to pay in all questions" wereTable. 1 Amount offered for each pattern
1 Amami rabbit
Initialoffer

5 Amami rabbits
Initialoffer

Second offer
YES

Patter 1
40 JPY

80 JPYNo

Patter 3

20 JPY

60 JPY

50 JPYNo

300 JPY

600 JPY
No

200 JPY

500 JPYNo

YES

150 JPY
YES
300 JPY

400 JPY
No

10 JPY

100 JPY

YES
120 JPY

YES
250 JPY

No
30 JPY

Second offer

YES

20 JPYYES
Patter 2

Second offer

10 Amami rabbits
Initialoffer

100 JPY

No
50 JPY

100 JPY
YES
600 JPY

1,200 JPY
No
300 JPY

400 JPY

YES
800 JPY
No
200 JPY

Results of the Survey
The results of the questionnaire survey, in which
1,041 samples were collected, showed that 816
samples (78%) were in favor of respondents paying
donations for roadkill control, with the most common
reason given as "because I want to protect theendangered Amami rabbit," at 60.5%. This wasfollowed by "because I think it is good to pay forsomething useful in the world" and "because I think
it is important for society to protect the life of theAmami Owl Rabbit," at 21.6% and 11.9%,
respectively. In all questions, 225 samples (22%)
disagreed with the respondent's decision to pay the
donation. Of the samples that were opposed, the mostcommon response was "because I can't make adecision based on this information," at 44.4%. Thiswas followed by 32.9% who were against the systemof collecting money through donations.
Regarding the respondents' awareness of theimportance of protecting the natural environment andliving creatures, "agree" was the most common
response, at 46.7% of the sample. This was followed401

SEE-Mie, Japan, Nov.10-12, 2022

WTP Results for Conservation of Amami Rabbit

by "very much so" at 41.0% and "neither" at 10.3%.
Regarding the frequency of respondents'
participation in activities to protect the naturalenvironment and living creatures, the largest numberof respondents (75.8%) answered that they "havenever participated at all. This was followed by 14.3%
who answered, "I do not participate now, but I haveparticipated in the past," and 6.8% who answered, "I
participate occasionally (a few times a year). The
percentage of respondents who had visited Amami
Oshima was 6.0%, and 43.9% of the respondents"knew" the name of the Amami rabbit, 22.6% had"heard only the word," and 33.5% "did not know.

The WTP to Amami rabbit conservation was
estimated based on 809 samples after eliminating
resistance responses from the 1,500 samples obtained.
The estimation was performed using "CVM in Excel
Version 4.0" provided by Kuriyama [10]. The
Weibull survival distribution was applied to estimate
a non-discrimination curve, and the median and meanvalues were calculated to estimate the WTP of theAmami rabbit. The WTP estimated for one, five, andten Amami rabbit are shown in Fig. 3, Fig. 4, and Fig.
5, respectively.

Elimination of Resistance Responses
In some cases, respondents do not respond to thewillingness-to-pay question because they compare
the utility of implementing roadkill measures with theutility of not implementing roadkill measures. There
are also resistant responses, in which the respondent
does not respond "no payment" because of resistanceto the scenario presented in the survey form or to theway the willingness-to-pay amount is collected.
There are also cases in which respondents respond to
the amount of willingness to pay because they value
something other than the effects realized by theroadkill measure, or they agree to pay even though
they do not value the implementation of the roadkill
measure. In such cases, there is a risk that thewillingness to pay may be overstated, and that an
appropriate willingness to pay may not be obtained.
Therefore, it is necessary to eliminate from theanalysis the data of respondents who do not fully
understand the questionnaire in an appropriatemanner. In this survey, a total of 39 samples (29samples that answered "Because I think it isinevitable if others also pay" as the reason foragreeing with the 809 samples that agreed withpaying the donation and 10 samples from "other freestatements" were excluded as resistant responses.
In the reasons for opposition to the 225 samples
that opposed paying donations, a total of 193 samples(74 samples responded "I am opposed to the system ofcollecting money through donations," 100 samples
responded "I cannot make a decision based on thisinformation," and 19 samples from "other freestatements") were excluded as resistant responses toestimate the WTP. The most common reasons given as
opposition were "Taxpayers should pay for theconservation of the Amami Rabbit, not donations," and"The population of the Amami Rabbit is increasing.
402

Fig. 3

Estimated WTP for 1 Amami rabbit

Fig. 4

Estimated WTP for 5 Amami rabbits

Fig. 5

Estimated WTP for 10 Amami rabbits

SEE-Mie, Japan, Nov.10-12, 2022

Table. 3 Social costs by roadkill of Amami rabbit

The estimated results of the WTP for theconservation of Amami rabbit for each number ofanimals are shown in Table.2. Therefore, in this study,
the WTP for Amami rabbit conservation was
estimated at 54.9 JPY/household, which was
calculated by converting the median value per 10
animals, which showed the lowest value, into per
animal (Table.2).

Evaluation period

Number of roadkills

Social cost

2021

56

176.04 billion JPY

Total since 2000

341

1.07 trillion JPY

2021

17

53.6 billion JPY

Total since 2000

95

299.3 billion JPY

2021

73

230.0 billion JPY

Total since 2000

436

1.40 trillion JPY

Amami Oshima

Tokunoshima

Table. 2 Amount offered for each pattern
Total

WTP

1 Amami rabbit

5 Amami rabbit

10 Amami rabbit

411 JPY/household(82.2 JPY per rabbit/household)

549 JPY/household(54.9 JPY per rabbit/household)

375 JPY/household
Average 102 JPY/household(75.0 JPY per rabbit/household)

616 JPY/household(61.6 JPY per rabbit/household)Median 336 JPY/household

Analysis of Factors Affecting WTP
Factors influencing WTP for Amami rabbit
conservation were analyzed based on the personal
attributes obtained from the questionnaire. The
following items were analyzed in the full log-linear
logit model: "frequency of participation in activities
to protect the natural environment and living
creatures," "awareness of the term 'Amami rabbit',""awareness of the term 'roadkill'," "awareness ofovertourism," "car driving license ownership,""awareness of traveling," "have you visited Amami
Oshima Island? ". Table 4 shows the results of theanalysis of factors affecting WTP.
The results of the analysis showed that the threevariables that met the 10% level of significance were"awareness of protecting the natural environment andliving creatures," "awareness of the term 'Amami
rabbit,'" and "awareness of the term 'roadkill'". Thus,
the results indicated that WTP may be higher in thecase of respondents who had these factors.
1) Those with high "awareness of the protection of
the natural environment and living creatures" had ahigh awareness of the protection of living creaturesand felt that the protection of the Amami rabbit wasalso important, which is thought to have resulted in ahigher WTP.
2) Those with high "awareness of the term 'Amami
rabbit'" had prior knowledge of the situation of theAmami rabbit and felt the need to conserve it, andthus their WTP was higher.
3) Those with high "awareness of the wordroadkill" had some knowledge of traffic accidents
between wild animals and vehicles, and the
proportion of those who wanted to save wild animals
from roadkill was also higher than that of the groupwith low awareness. Therefore, the proportion ofpeople who wanted to save the Amami rabbit fromroadkill would also be higher, which would haveresulted in a higher WTP.

Results of Social Cost by Roadkill of Amami
Rabbit
The estimated WTP value was multiplied by the
number of households in Japan (57,378,423
households) [11] and the number of roadkill cases ofAmami Oshima by Amami rabbit in 2021 (56 cases),resulting in an estimated social cost of 176.04 billion
JPY due to roadkill cases of Amami Oshima in 2021.
The social cost of roadkill by Amami rabbit in 2021
was estimated at 176.04 billion JPY. The social cost
due to roadkill by Amami Oshima hare (341 cases)
during the 22 years from 2000 to 2021, when data
were recorded, was estimated to be 1.07 trillion JPY.
In this study, Amami Oshima, the main habitat of
the Amami rabbit, was targeted. But, using the WTP(54.9 JPY/household) for Amami rabbit conservation
estimated in this study, the social loss for
Tokunoshima and the Amami rabbit as a whole wasalso estimated using the same method. In
Tokunoshima, 17 cases of roadkill of Amami rabbit
were estimated to have occurred in 2021, resulting ina social loss of 53.6 billion JPY. The social cost of
roadkill by Amami rabbit (95 cases) in Tokunoshima
during the 22 years from 2000 to 2021, when records
are available, was estimated to be 299.3 billion JPY.
The total number of roadkill by Amami Oshima
and Tokunoshima in 2021 was 73, and the social
cost was estimated to be 230.0 billion JPY. The
social cost of roadkill by Amami rabbit (436 cases)
during the 22-year period from 2000 to 2021, whenrecords are available, was estimated to be 1.40
trillion JPY. Table.3 shows the social cost of
roadkill by Amami rabbit.
403

SEE-Mie, Japan, Nov.10-12, 2022

Table. 4 Results of analysis of factors affecting
WTP

Variables

Coefficientt-valuep-valueConstant

4.352

7.147

0.000

***

In(Bid)-1.629-20.508

0.000

***

Awareness of the natural environment and biological conservation(1: Not at all disagree - 5: Agree very much)

0.956

8.703

0.000

***

Frequency of participation in activities to protect the naturalenvironment and living organisms(1: Not participating at all - 5: Participating frequently)

0.231

2.528

0.012

**

Awareness of the term "Amami rabbit"(1: Don't know - 3: Know)

0.246

3.002

0.003

***

Awareness of the term "Roadkill"(1: Don't know - 3: Know)

0.261

2.596

0.010

***

Age

0.106

2.388

0.017

**

n

809

log-likelihood

leopard cat conservation and propagation projectby CVM,https://www.biodic.go.jp/biodiversity/activity/policy/valuation/pdf/t1_03-2_140311.pdf(last access: July 2, 2022)[3] T. Hiragi, Y. Kimoto and C. Iwamoto, Road-killsof the Amami rabbit Pentalagus furnessi on
Amami-Ohshima Island from April 2007 to
March 2017, Mammalian science, Vol.57, No.2,
2017, pp.249-255.
[4] H. Ito, M. Wada and T. Fujii, EXTERNALCOSTS CAUSED BY HOKKAIDO SIKA
DEER-VEHICLECOLLISIONSINHOKKAIDO, JAPAN, Proceedings of 7thInternational
Conferenceon
Structure,Engineering & Environment, 2021, pp.328-334.
[5] Institute for Global Environmental Strategies,
Kyoto Univ., Nagasaki Univ. and Nagoya Univ.,
2011 Policy Research on Environmental
Economy Research on policy options forsustainable use of ecosystem services throughinternalization of economic values Final
Research Report,
http://www.env.go.jp/policy/keizai_portal/F_res
earch/f-09-03.pdf (last access: July 2, 2022)[6] S. Mitsui and T. Kubo, Visitors’ Evaluation ofManagement Rules in Amami Oshima“Kinsakubaru Native Forest”: Application ofBest-Worst Scaling, Journal of Forest Economics,
Vol.64, No.3, 2018, pp.1-7.
[7] T. Sasaki, H. Nakamura and S. Suzuki, Estimationof Social Losses caused by Raccoon based on
CVM, Annual Report of the Hokkaido Branch of
the Civil Engineering Society, Paper No. 72. 2015.
http://library.jsce.or.jp/jsce/open/00057/2016/72D-0003.pdf (last access: July 2, 2022)[8] C. Qiu and Y. Hashimoto, A Travel Cost
Analysisof the Recreation Value of Amami
Oshima, Journal of Japan Institute of Tourism
Research, The Tourism Studies Quarterly ，Vol.16, No．1, 2003, pp.1-8.
[9] Kurt A. Schwabe and Peter W. Schuhmann, DeerVehicle Collisions and Deer Value: An Analysis
of Competing Literatures, Wildlife Society
Bulletin, Vo.30, No.2, 2002, pp.609-615.
[10] K. Kuriyama, CVM in Excel, Version 4.0,
http://kkuri.eco.coocan.jp/research/introtxt/index.
html (last access: July 2, 2022)[11] Ministry of Internal Affairs and Communications
HP: Population, Demographics and Number ofHouseholds based on the Basic Resident Ledger
as of January 1, 2021
https://www.soumu.go.jp/main_sosiki/jichi_gyou
sei/daityo/jinkou_jinkoudoutai-setaisuu.html (lastaccess: July 2, 2022)-996.768

CONCLUSION
In this study, we estimated the WTP for Amami
rabbit conservation using CVM and estimated thesocial costs of Amami rabbit roadkill occurrence. The
results indicated that the occurrence of roadkill by
Amami rabbit has caused significant social losses.
Therefore, it can be said that measures to prevent
roadkill of the Amami rabbit should be implemented
as soon as possible. However, the CVM used in thisstudy requires further study to determine theappropriate number of exposed populations, since thesocial costs vary depending on the number of exposed
population.
In addition, as a future issue, roadkill ofendangered amphibian species, such as the Amami
ishikawa frog (Odorrana splendida) and the Otton's
frog (Babina subaspera), which are endemic to
Amami Oshima and are listed as endangered in red
data book of the Ministry of the Environment, Japan,
is also occurring frequently. It is considerednecessary to estimate the social costs of roadkill ofthese species.
REFERENCES[1] Ministry of the Environment, Elucidation of thecause of death of rare mammals in Amami
Oshima and Tokunoshima in 2021
https://kyushu.env.go.jp/okinawa/pre_2022/2021.html (last access: July 2, 2022)[2] Ministry of the Environment, Results of theeconomic value evaluation of the Tsushima404

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

IMPUTATION OF OUTLIERS AND MISSING VALUES FOR
ACTIVATED SLUDGE DISSOLVED OXYGEN DATABASE USINGMULTIVARIATE IMPUTATION BY CHAINED EQUATIONS (MICE)
1,2

Hatem Nijim1and Rabee Rustum2
Department of Civil Engineering, Heriot-Watt University, United Arab Emirates

ABSTRACT
Activated sludge process (ASP) is the most widely used process in wastewater treatment plants. The concentrationof dissolved oxygen (DO) is a crucial controlling parameter in this process as the DO affects the efficiency of thetreatment, operational cost, and system sustainability. While Field electrodes measure DO, maintaining regularand accurate records remains a challenge, even in the absence of aggressive climate conditions. Most of the DOprobes are sensitive and require careful maintenance and calibration that may lead to non-accurate data recording.
This paper discussed the validity of statistical models to impute missing DO values. Multivariate Imputation by
Chained Equations (MICE) is used in R programming language to predict missing values and replace outliers in
the DO measurements. The performance of this technique was very good as the correlation ranges between 0.999
and 0.821 when the missing values range from 1 to 15 % (424 to 6,360 of total data of 42,420). The method ishighly effective and ready to be used for many other applications. Kohonen Self Organising Map (KSOM) is
applied as an alternative model to verify the accuracy of the MICE.
Keywords: Activated sludge process; Dissolved Oxygen (DO); Multiple Imputations; Chained Equations
INTRODUCTION
Outlier Detection
The concentration of dissolved oxygen (DO) is a
key variable in water resource recovery facilities [1].
DO is monitored to ensure oxygen is sufficient foraquatic species to survive [2]. In wastewater
treatment, dissolved oxygen monitoring in aeration
tanks in the activated sludge process is essential as it
significantly impacts the efficiency of the treatment
process.
There are two methods to measure the DOconcentrations: Winkler titration method [3]. Or
oxygen electrode sensors [1]. DO sensors are the mostaccurate method; however, instrumental errors areinevitable, and a certain procedure should be
followed to obtain reliable data [4].
When the DO concentration levels are reduced, thenumber of filamentous microorganisms increases,
which subsequently impacts the ability of theactivated sludge to settle. If DO levels continue todecrease, effluent turbidity increases, and treatment
will be reduced rapidly [5].
This study was based on Seafield wastewater
treatment plant data in Edinburgh, UK. The Seafield
wastewater treatment plant (WWTP) is the largest
WWTP in Scotland and treats more than 300 million
litres of wastewater per day. The main areas of
Seafield WWTP Comprise of Eight sedimentation
tanks with a volume of 9260 m3, Eight final
settlements tanks with a volume of 3974 m3, and fiverectangular aeration lanes. Data of DO values in these
five lanes are used in this paper.

Data values with magnitudes that differ
significantly from the majority of other data values
are known as outliers. There are many possible
reasons for outliers. Commonly, human errors such as
errors in transferring the data or a fault in handling themeasuring sensors can lead to unintentional outliers[6].
Identifying the outliers from the data sets andreplacing them so the model will create more uniform
sets of data, and accordingly, the results for the model
performance will be more accurate. A Z-score test
was used to identify the outliers. A Z-score test in Eq.
1 and 2 are used to obtain a Z-score [6].
̅)( 𝒙𝒊 − 𝒙𝒔(1)∑𝒏 (𝒙𝒊 − 𝒙̅ )𝟐
𝒔 = √ 𝒊=𝟏
𝒏−𝟏

(2)

𝒛𝒊 =

Where
𝒙𝒊 Observed DO value,𝐱̅ Mean for all observed DO,
S Standard deviation,
N sample size (total number of the data).
As per the Z-score equation, the z-score is 3.5 < Z < 3.5. The values beyond this range should be marked
as an outlier and considered as missing values to be
imputed by the models later.

METHODOLGY
405

SEE-Mie, Japan, Nov.10-12, 2022

Missing Data

to recognise a specific group from a complex data set[6]. The KSOM has been used in various research
fields, as discussed in [6] [14]. KSOM converts the
input signal pattern of complex data into a twodimensional map. The tuned input pattern are shownas clusters where similar patterns are shown in thesame output neurons or with its adjacent one; theseclusters reduce the amount of huge data, andaccordingly, the relationship between higherdimensional data will be in lower dimension [6]. The
KOSM consists of two layers, the input layer, andoutput layer, the layers are composed of neurons, andboth layers are connected with a weight vector. The
input layer consists of multi-dimensional layers, andthe output layer consists of two-dimensional layers
made of neurons. A specific dimensional weightvector represents each neuron in the two-dimensional
map. Similar neurons are located together, andneurons which are not similar will be further apart.
Map size varies depending on the number of neurons;
the number of neurons affects the accuracy of KOSM.
More details on the theory and application of the
KSOM can be found in [6][15][16].

Missing data are two types, ignorable and nonignorable [7].
1- Ignorable Missing Data are two types:a. Missing Data Completely at
Random (MCAR): they occur
randomly, meaning the value of themissing and observed data is
independent.
b. Missing at Random (MAR): The
value of the missing data andobserved data might be dependent.
2Non-Ignorable Missing Data: If the missing
data are not at random (MNAR), then they are
considered non-ignorable. The MNAR are when thevalue of the unobserved variable itself predicts
missingness [8].
Multiple Imputations
The concept of Multiple Imputation (MI) uses the
distribution of the observed data to estimate andpredict a set of the possible values for the missing data.
With MI, the missing values are replaced by manydifferent values, and accordingly, many different full
data sets are performed. Complete data sets will becreated by multiple imputations, and these sets shouldslightly differ. The final step of the MI is to pool out
from these imputed steps one complete data set as a
final result [9].

RESULTS AND DISCUSSION
Results for the predicted values of the dissolved
oxygen by MICE and KOSM are compared with theobserved one. The accuracy of the predicted values
was evaluated by three statistical parameters namely
the Correlation Coefficient R, the mean square error(MSE), and the Average Absolute Error AAE [6].
Figure 1 illustrates the component planes for the
Kohonen self-organising map (KSOM) for all lanes
when missing values are 15%; these planes visuallyshow the relationship between DO values for eachlane. As shown, lanes 1,2 and 3 are slightly correlated,
and lanes 4 and 5 are less correlated. The morecorrelated vectors between each other lanes indicate
better results.
Table 1 shows the results for MICE, and KOSM when
1 % up to 75 % of data are missing. The tablesummarises the results as an average for the fivelanes. The values for R, MSE, and AAE almost havethe same values for MICE and KOSM. The
performance of the models is very good when 15%of
DO data are missing, . The R values for MICE andKOSM are 0.884 and 0.919, the MSE is 0.308 and0.211, the AAE is 0.158 and 0.124.

Multivariate Imputation By Chained Equations(MICE)
Multivariate imputation by chained equations(MICE), also known as Sequential Regression
Imputation [10]. It is a practical approach for
imputing missing datasets based on a set of
imputation models. MICE is a chain of equations
used to impute missing values and is fully conditional.
The missing values are imputed one by one. For
example, in a data set Y1 ,Y2 ,Y3,…….,Y10 , if Y1 is a
missing value, MICE will use the information fromall other variables Y2 ,Y3,…….,Y10, and the sameprocedure will be repeated for all missing values. The
imputed values are modified by adding a residual
error which can be added directly to the imputed
values or to the parameters estimates of the MICE
model. The residual error will improve the sampling
variability to the imputations [11]. MICE assumes
that missing data are missing at random[12]. MICE
procedure is provided in many software, such as
SPSS, STATS and S-Plus [13]. However, the mostcommon software is R [11].

CONCLUSION
The performance of MICE is excellent when the
missing data are 10% or less, very good performance
when the missing data is between 10% and 15%, good
performance when the missing data is between 15%
and 20%, and poor performance when the missing
data more than 20%. KSOM was used as analternative model to validate the MICE results.
KSOM is applied in previous case studies, andKohonen Self-Organizing Map (KSOM)KOSM is a nonlinear classification technique able

406

SEE-Mie, Japan, Nov.10-12, 2022

therefore, KSOM results which are similar to MICE
results, emphasise MICE application to predict themissing values.

accuracy of the predicted values after replacing theoutliers will not be improved.
MICE can be applied regardless of the type of missing
data. However, better performance for MICE whenthe missing data is MAR. The number of imputations
affects the accuracy of the predicted values; 5 to 10
imputations are the default number of imputations;however, for the data with a big variance, more
imputations should be applied. Increasing the numberof imputations may have an impact on the software
speed; delay is expected when the number of
imputations is more than10.

LIMITATIONS AND RECOMMENDATIONSFOR MICE
Data quality is the major factor which will affectthe accuracy of the predicted values. Replacing theoutlier will improve the accuracy however if theoutliers are more than 10% of the overall data, the1
Figure 1 The component planes of the KSOM for all lanes when missing values are 15%
Table 1 Summary of Statistical values for MICE and KOSM performance

Percentage Of Missing Date

Results when 1% of Dates are Missing

Results when 5 % of Dates are Missing

Results when 10% of Dates are Missing

Results when 15% of Dates are Missing
Results when 20% of Dates are Missing

Results when Dates are Missing
Mice
KOSM
Statistical Parameters Value Statistical Parameters
R
0.994
R
MSE
0.015
MSE
AAE
0.009
AAE
R
0.96
R
MSE
0.107
MSE
AAE
0.054
AAE
R
0.929
R
MSE
0.21
MSE
AAE
0.108
AAE
R
0.884
R
MSE
0.308
MSE
AAE
0.158
AAE
R
0.837
R
MSE
0.435
MSE
407

Value
0.997
0.009
0.007
0.975
0.066
0.039
0.948
0.136
0.081
0.919
0.211
0.124
0.884
0.302

SEE-Mie, Japan, Nov.10-12, 2022

Results when 30% of Dates are Missing

Results when 40% of Dates are Missing

Results when 50% of Dates are Missing

Results when 60% of Dates are Missing

Results when 75% of Dates are Missing

AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE

0.221
0.837
0.435
0.221
0.633
0.945
0.469
0.63
1.16
0.599
0.519
1.538
0.752
0.235
1.687
0.864

AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE
R
MSE
AAE

0.173
0.794
0.506
0.305
0.686
0.729
0.422
0.791
0.512
0.389
0.689
0.739
0.506
0.291
1.339
0.782

[8] Bouhlila, D.S. and Sellaouti, F., 2013. Multiple
imputation using chained equations for missing
data in TIMSS: a case study. Large-scale
Assessments in Education, 1(1), pp.1-33.

REFERENCES[1] Samuelsson, O., 2021. Sensor Fault Detection
and Process Monitoring in Water Resource
Recovery Facilities (Doctoral dissertation, Acta
Universitatis Upsaliensis).
[2] Holenda, B., Domokos, E., Redey, A. andFazakas, J., 2008. Dissolved oxygen control of
the activated sludge wastewater treatment
process using model predictive control.
Computers & Chemical.
[3] Winkler, L.W., 1888. The determination ofdissolved oxygen in water. Berlin DeutChem
Gas, 21, pp.2843-2855.
[4] Wei, Y., Jiao, Y., An, D., Li, D., Li, W. and Wei,
Q., 2019. Review of dissolved oxygen detection
technology: From laboratory analysis to online
intelligent detection. Sensors, 19(18), p.3995.
[5] Rustum, R., 2009. Modelling activated sludge
wastewater treatment plants using artificial
intelligence techniques (fuzzy logic and neuralnetworks) (Doctoral dissertation, Heriot-Watt
University).
[6] Rustum, R., Adeloye, A. and Simala, A., 2007.
Kohonen self-organising map (KSOM) extracted
features for enhancing MLP-ANN prediction
models of BOD5. In International Symposium:
Quantification and Reduction of Predictive
Uncertainty for Sustainable Water Resources
Management-24th General Assembly of theInternational Union of Geodesy and Geophysics(IUGG) (pp. 181-187).
[7] Rubin, D.B., 1987. Statistical analysis withmissing data.

[9] Harel, O. and Zhou, X.H., 2007. Multiple imputation:
review of theory, implementation and software.
Statistics in medicine, 26(16), pp.3057-3077.
[10] Van Buuren, S. and Groothuis-Oudshoorn, K., 2011.
mice: Multivariate imputation by chained equations in
R. Journal of statistical software, 45, pp.1-67.
[11] Zhang, Z., 2016. Multiple imputation withmultivariate imputation by chained equation (MICE)
package. Annals of translational medicine, 4(2).
[12] Ratolojanahary, R., Ngouna, R.H., Medjaher, K.,
Junca-Bourié, J., Dauriac, F. and Sebilo, M., 2019.
Model selection to improve multiple imputation forhandling high rate missingness in a water quality
dataset. Expert Systems with Applications, 131,
pp.299-307.
[13] Azur, M.J., Stuart, E.A., Frangakis, C. and Leaf, P.J.,
2011. Multiple imputation by chained equations: what
is it and how does it work?. International journal of
methods in psychiatric research, 20(1), pp.40-49.
[14] Rustum, R. and Adeloye, A.J., 2007. Replacing
outliers and missing values from activated sludge datausing Kohonen self-organising map. Journal ofEnvironmental Engineering, 133(9), pp.909-916.
[15] Kumar, N., Rustum, R., Shankar, V. and Adeloye,
A.J., 2021. Self-organising map estimator for the cropwater stress index. Computers and Electronics inAgriculture, 187, p.106232.
[16] Kumar, N., Shankar, V., Rustum, R. and Adeloye,
A.J., 2021. Evaluating the performance of selforganizing maps to estimate well-watered canopy
temperature for calculating crop water stress index in
Indian mustard (Brassica Juncea). Journal of Irrigation
and Drainage Eng, 147(2), p.0402004

408

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

THE EFFECT OF FLEXIBLE WORKING ARRANGEMENT AND WORK LIFE
BALANCE ON EMPLOYEE PRODUCTIVITY IN GOVERNMENT OFFICES IN
BEKASI CITY, WEST JAVA
Beti Nurbaiti1, Waluyo2 and Dwi Setyowati3
1

Universitas Bhayangkara, Indonesia; 2Aidhub Services; 3Universitas Bhayangkara, Indonesia

ABSTRACTThe purpose of this study is to analyze the effect of Flexible Working Arrangement (FWA) and Work Life
Balanced (WLB) on Employee Productivity in the City Government (Pemkot) of Bekasi, West Java. The approach
used is a quantitative method using a survey questionnaire from primary data of 151 employees, at the BekasiCity Government, West Java during April 1 – May 30, 2022. The research equation is in the form of structuralresearch (SEM) which is processed using Lisrel software. The results show that there is a significant positive
relationship between FWA and WLB, as well as a negative relationship significant difference between WLB and
PROD. This finding shows that the implementation of FWA during the COVID-19 pandemic in the Bekasi City
Government of West Java has a positive impact on WLB, but does not necessarily increase employee productivity
in the Bekasi City Government. The presence of employees is still required at the Bekasi City Government office
as a place for community services and activities, even though they take turns because of the prokes during the
pandemic. So it can be concluded that the application of flexible work from home is not effective if fully enforcedin the office on employee productivity.
Keywords: Flexible Working Arrangement; Work Life Balance; Productivity; SEM

I.

COVID-19 pandemic has changed the behavior
pattern of a person with a flexible work system thatis not limited by time and place with the use oftechnology (Ko & Kim, 2018). Work flexibility
offers employees a balance between theirprofessional and personal lives, which leads to job
satisfaction and high performance and overall
improvement of the organization (Sethi & Saini,2020). Work flexibility is very important, and withdigitaladvancements
andtechnologicaladvancements, employees can continue their work
anywhere they want, as long as they have an internet
connection (Davidescu et al, 2020). Flexible
working hours and home-based remote work areadded values, (Dilmaghani, 2021).

INTRODUCTION

The COVID-19 pandemic over the past 2 years
has had a significant impact on people's lives in allparts of the world on economic conditions, as well
as social, cultural, and daily activities. Social life hasturned into face-to-face remotely by utilizing
technology (zoom, google meet, whatsapp, and othersocial media platforms). On the one hand, thepandemic of giving is considered a disaster, but on
the other hand, it creates a virtual communication
technology that is more flexible without time andplace limits. The ferocity of this flu mutation has
forced many people to stay at home using digitaltechnology with various policies/regulations. The
Bekasi City Government has also implemented apolicy of Enforcement of Community Activity
Restrictions (PPKM) for both its employees and the
local community, where the regulation continues theprevious policy, namely Large-Scale Social
Restrictions (PSBB) to break the chain of spread of
the COVID-19 virus. However, it is necessary to
study further whether the concept of flexible work
or Flexible Working Arrangement (FWA) is in linewith the concept of work life balance (WLB) andhas an impact on employee productivity. To analyze
these three variables, the authors conducted a study
by taking saturated samples of all employees withthe status of the government employee the Bina
Marga dan Sumber Daya Air (BMSDA) Bekasi City.

II.

There are three reasons why work-life measuresthat focus on flexibility can prevent employees fromleaving the company: First, employees feel that theleader or company cares about the need forreconciliation and work-life balance. Second,
flexibility measures imply greater autonomy withrespect to employees' working time and workplace.
Third, flexible work patterns are applied dependingon the size of the company, generally the larger thesize of the company, the more attractive flexible
work systems are because of clear remunerationaccording to output (Marx et al, 2021).
There are several advantages obtained from
FWA as expressed by FGD respondents, namely: a)Flexible time; b) work and family life balance; c)freedom to choose a comfortable workplace; d)safety and security; e) company budget savings forfacilities and utilities; f) develop trust among
employees; and g) and developing a digital work
environment (Hasan & Butt, 2021). The application

LITERATURE REVIEW

2.1. Flexible Working Arrangement409

SEE-Mie, Japan, Nov.10-12, 2022

of flexible options to employees has potential
benefits and this type of arrangement ensuring worklife balance for employees (Anya et al, 2021). It is
hoped that employees of organizations that provide
flexible working hours have a much higher turnover
intention low, influenced by collective culture andnorms in the workplace (Gašić & Berber, 2021).

positive work atmosphere that encourages andenables workers to maintain a balance between theirprofessional and personal lives, thereby increasing
productivity and employee loyalty (Anya et al,2021).
This type of flexible work will increase
productivity if employees can reduce stress, rest
more and are happier, and more prosperousOfcourse, this condition has an impact on higherorganizational outcomes in production and income(Martínez-León et al, 2019). Monitoring andmanagement of employee work stress is emphasized
because it is a factor that affects productivity.
(Rachmawati et al, 2021). Adequate funding forflexible work is important so that it is right on target
and produces high work productivity (Hoggart et al,2021).

2.2 Working Life Balance (WLB)
WLB is defined as a balance of individual life
activities between work/professional and non-work
activities, in order to enable individuals to havesufficient autonomy to meet the demands of theirprofessional and personal duties. (Johnson &College, 2021).
WLB practices can be categorized as follows:(1) Time reduction practices, allowing employees tovoluntarily reduce the number of hours they work byworking part time or sharing jobs, temporarily
reducing their workload and salaries;

III.

(2) The practice of flexible work arrangements,
including all employer policies that allow employees
to control flexibly without reducing their salary(Martines-Leon et al, 2019).

The research method used quantitative by taking
a of the entire population of Bina Marga and Sumber
Daya Air Kota Bekasi yang berjumlah 158 people,
with data returned and ready to be processed from151 people. The research equation using a
structured model (Structural Equation Modeling/SEM) was processed with Lisrel software (Asra i etal, 2015). Statistical tests used in this study include:(1) model fit test, measuring the suitability of thedata with the model; (2) validity test, measuring
what the researcher wants to measure; and (3)reliability test, test instrument reliability, and (4)structural model test/hypothesis test (Wijanto,2008).

WLB emphasizes eliminating difficulties related
to gender and employee welfare, especially for
women. Employees need a meaningful balance
between work and life in order to be productive andfocus on both areas (Uddin & Khan, 2022) and(Martinez-Leon et al, 2019). WLB is necessary forpeople to find a match between their personal andprofessional lives. An employee can be better atmanaging personal and work commitments if thecompany has a good functional information system
to reduce employee problems (Paje et al, 2020).
2.3

METHODS, HYPOTHESES, AND
RESEARCH RESULTS

According to Wijanto (2008) the GOFI indicator
is sufficiently represented by 9 (nine) indicators,
which are: RMSEA < 0.080, NFI > 0.90, NNFI >0.90, CFI > 0.90, RFI > 0.90, IFI > 0.90,
Standardized RMR < 0.050, GFI > 0.90, dan AGFI
> 0.90. GOFI dengan Degrees of Freedom = 0; ChiSquare = 0.0;P = 1.00): The Model is Saturated, theFit is Perfect in other words the fit is very good.
Good validity to the construct or latent variable if
the Standardized Loading Factor (SLF) value >0.50. Measurement of reliability seen from the valueof Construct Reliability (CR) > 0.70 and Variance
Extracted Mesure (VE) > 0.50.

Productivity (PROD)

Productivity is the relationship between outputs(goods or services) and inputs (labor, materials,
money). Productivity is a measure of productive
efficiency. A comparison between the output andinput. For work, workers prefer FWA so that they
can benefit from increased productivity andefficiency (Ko & Kim, 2018). Productivity and skill
development of employees can be increased by
improving the working life of employees in theworkplace through flexible work (Kumar & Verma,2022).

There are 2 (two) research hypotheses, namely:

Flexible Work Arrangements (Flextime,
Flexplace and Compressed Workweek) have apositive impact on employee engagement and thus
lead toincreased productivity, financial
performance, customer satisfaction, quality
improvement (Gašić & Berber, 2021). The idea ofwork-life balance is focused on developing a

Hypothesis 1 (H1): There is a significant
relationshipbetweenFlexible
Working
Arrangement (FWA) and WA, also Work Life
Balance (WLB)
Hypothesis 2 (H2): There is a significant
relationship between Work Life Balance (WLB) and
Productivity (PROD).
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SEE-Mie, Japan, Nov.10-12, 2022

Table 3.1 Goodness of Fit, Validity, Reliability of Flexible Working Arrangement (FWA) Result
Questionnaire
Number
FWA2

Questionnaire Statement

SLF Value

Error

Validity Test
Results
Good Validity

Reliability Test
Results

I work more effectively with flexible
0.82
0.29
working hours.
FWA7
Flexible working hours are assessed
0.79
0.38
Good Validity
CR Value =according to work safety and security
0.86
standards.
FWA3
I feel more comfortable with flexible
0.73
0.47
Good Validity
working hours.
VE Value =FWA5Flexible working hours allow me to do two
0.69
0.53
Good Validity
0.52
or more jobs more than normal working
hours.
FWA6
Flexible working hours are able to create a
0.61
0.62
Good Validity
Good Reliability
balance between working and family time.
FWA4
The company’s policy of implementing
0.60
0.64
Good Validity
flexible working hours has a positive
impact on my work motivation.
FWA1
My income has increased with flexible
0.59
0.65
Good Validity
working hours.
FWA9
Flexible working hours contributes in
0.56
0.69
Good Validity
reducing conflicts between me and mycolleagues.
RMSEA = 0.00; NFI = 0.99; NNFI = 1.00; CFI = 1.00; IFI = 1.00, RFI = 0.97; Standardized RMR = 0.039; GFI = 0.98 and AGFI = 0.90
Conclusion: all variables observed in the latent variable FWA have good validity and reliability.
Source: processed by researchers (2022)

The results of the survey data processing in thetable 3.1 shows that FWA is considered by
employees to be more effective, safer because it
avoids the spread of the covid-19 virus according to
the results of research Kumar & Verma (2022) and
Reard et al (2021, Martínez-León (2018).

Respondents' perceptions indicate that employees
minimize conflicts between colleagues and FWA, as
well as increased income due to savings fromtransportation costs due to working more from homein line with findings from Nwagbara (2020) andRachmawati (2021).

Table 3.2 Goodness of Fit, Validity, Reliability of Work Life Balance (WLB) Result
Questionnaire
NumberWLB1

Questionnaire Statement

SLF
Value
0.9 3

Error

Validity Test
Results
Good Validity

Reliability Test
Results

I am able to find a balance between work activities and
0.14
family activities with the implementation of FWA.
WLB 9
I am able to harmonize work time with family or
0.87
0.24
Good Validity
CR Value =personally as a result of implementing FWA.
0.91
WLB 6
I find it easier to meet work targets with the FWA
0.77
0.40
Good Validity
concept.
WLB 7
I am more motivated to work with the FWA concept.
0.77
0.41
Good Validity
VE Value =WLB 5With the FWA concept, I feel more comfortable working
0.76
0.42
Good Validity
0.60
because I have more time with my family.
WLB 4
With the FWA concept, I feel more comfortable working
0.69
0.52
Good Validity
because I have more time for my personal life.
Good Reliability
WLB 8
I can complete my work anywhere because of the
0.59
0.65
Good Validity
application of the FWA concept.
RMSEA = 0.00; NFI = 1.00; NNFI = 1.00; CFI = 1.00; IFI = 1.00, RFI = 0.99; Standardized RMR = 0.020; GFI = 0.99 and AGFI = 0.93
Conclusion: all variables observed in the latent variable WLB have good validity and reliability.
Source: processed by researchers (2022)

Referring to the results of the WLB variable dataprocessing in the table 3.2 it can be seen that
employees think that the FWA work concept canharmonize work and home or family affairs. Thiscondition is in line with research from Bartsch et al(2021) where in order for this balance to occur, aleader/supervisor needs to take conducive actions

by: (1) involving employees in virtual team work;(2) give their employees the necessary autonomy
and support and (3) adequate internet supporting
facilities related to digital technology to maintain ahigh level of performance among employees. Thebalance of work and personal according to research
conducted by Marx et al (2021).

411

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Table 3.3 Goodness of Fit, Validity, Reliability of Productivity (PROD) Result
Questionnaire
Number
PROD 6

Questionnaire Statement

SLF
Value
0.80

Error

Validity Test
Results
Good Validity

Reliability Test
Results

The punctuality of completion of work by employees is
0.35
better with the application of the FWA concept.
PROD 4
The quality of employee work results is better with the
0.73
0.47
Good Validity
CR Value =implementation of FWA.
0.89
PROD 10
The application of the FWA concept demands the
0.72
0.48
Good Validity
achievement of higher targets.
PROD 2
I have more autonomy in my work with FWA concept.
0.71
0.50
Good Validity
VE Value =PROD 5
Achievement of work targets by employees is better with
0.68
0.54
Good Validity
0.50
the application of the FWA concept.
PROD8
The level of employee independence is higher with the
0.68
0.54
Good Validity
application of the FWA concept.
Good Reliability
PROD 9The responsibility of superiors in supervising
0.67
0.55
Good Validity
subordinates/staff is lighter with the application of the
FWA concept.
PROD 3
Employees are more responsible for completing work
0.65
0.58
Good Validity
with the FWA concept.
PROD 7Companies benefit from saving organizational resources
0.65
0.58
Good Validity
as a result of applying the FWA concept to theiremployees.
RMSEA = 0.00; NFI = 1.00; NNFI = 1.00; CFI = 1.00; IFI = 1.00, RFI = 0.99; Standardized RMR = 0.018; GFI = 0.99 and AGFI = 0.96
Conclusion: all variables observed in the latent variable PROD have good validity and reliability.
Source: processed by researchers (2022)

The majority of government employees in the
Bekasi City Government think that the completionof work is the most important thing compared to theimplementation of FWA work itself. This finding is
in line with previous research from Dilmaghani(2021). Employee independence increases with theimplementation of FWA in the office, supported bysupervision and the necessary technological devices
such as research results from Paje et al (2020).
Employees have more responsibility with theapplication of FWA, and this phenomenon is in linewith the findings of Nwagbara (2020).

Table 3.4 Research Hypothesis Test

No
1

2

Questionnaire statement

T-Value

CoefficientStandard
0.50

H1: There is a significant relationship5.38
between the Flexible Working Arrangement(FWA) variable and the Work Life Balance(WLB).
H2: There is a significant relationship- 6.42- 0.58
between the Work Life Balance (WLB)
variable on Productivity (PROD).
Source: processed by the author (2022)

Based on the hypothesis test, it can be seenthat both research hypotheses are accepted, where
Hypothesis 1 answers that there is a positive
relationship/correlation between the latent variable

Conclusion
Hypothesis 1 is accepted. There is a significant positive
relationship between FWA and WLB.

Hypothesis 2 is accepted. There is a significant negative
relationship between WLB and PROD.

Flexible Working Arrangement (FWA) and Work
Life Balance (WLB), or in other words, the higher
the application of FWA, the better the WLB
condition. Furthermore, hypothesis 2 answers that412

SEE-Mie, Japan, Nov.10-12, 2022

there is a negative relationship/correlation between
the latent variable Work Life Balance (WLB) and
Productivity (PROD), or it can be concluded that ahigh WLB will reduce employees' PROD.
IV.

certainly a dilemma for organizations in
implementing the FWA concept. Organizations
offering FWAs should periodically assess whether
employees find FWAs attractive and facilitate
different circumstances of flexibility.

DISCUSSION

One's work-life balance must be measured andseen in the hope of providing a better future. The
implementation of FWA must be balanced with thesystem so that employees are not trapped in a blurred
time limit between work and personal or household.
Most of the work done in developing countries
related to the implementation of FWA creates family
conflicts, especially for societies with a strong
patriarchal culture. The main determinant ofeffective WLB implementation is HR policy thatemphasizes a work-life balance culture. A flexible
work system must be supported by good leadership.
Leadership behaviors, particularly relationshiporiented leadership, can promote a supportive work
environment and make it easier to cope withexcessive work demands and establish appropriate
boundaries between work and personal life. But on
the other hand, if there is a state of excessivecommitment to work (individual behavior) and highjob demands, it will have a negative impact on theemployee's life balance because of disturbed
psychosocial factors.

The COVID-19 outbreak has an impact on worklife balance and employee job satisfaction.
Employees who enjoy a favorable work-life balance
tend to be more satisfied with their jobs. The positive
impact that emerges from telecommuting reduces
work-family conflict and improves well-being for
employees, thus leading to positive outcomes suchas increased performance and productivity. The
supporting aspects of work-life balance signal to
Bekasi City Government employees that they arevalued by the organization, and employees feelincluded when the organization provides resourcesthat meet employees' work-life balance needs.
Work-life balance satisfaction is stronger among
men and women without dependent children. The
demands of work even if expressed in the realm of
flexible work can interfere with domains of life, notjust child-rearing responsibilities, such as health,friendships, and civic engagement. To overcome thisin order to avoid work-family conflict requires more
specific actions. Flexible work needs to be supported
by bonuses and remuneration that are adjusted to thedemands of the Bekasi City Government.

The level of job flexibility does not necessarily
have high flexibility. This is influenced by otherfactors such as functional flexibility, working time,
and work space flexibility in increasing the level ofsatisfaction and work productivity of employees.
WLB has an impact on organizational performance,
productivity and sustainability. WLB is aligned withparticipatory human resource (HR) management,
making it possible for mutual benefit (or win-win
situation) for both employers and employees. This
flexible working method will have a positive impact
if the organization helps employees achieve morebalance by offering various policies and initiatives
that balance work and family pressures. One of the
drawbacks of FWA is that the company may not beable to control every employee, and will not be able
to see whether everyone is working or not, or
whether they are productive. For this reason, work
management is needed so that work stress does notoccur, where this can trigger low productivity,
illness and ineffectiveness of government
employees in the Bekasi City Government.

For the effective operation of the FWA, it isimportant not only to launch the flexible work
program itself, but also to ensure that users areproperly understood and evaluated fairly. Work-life
programs such as flexible work arrangements,
employee assistance programs, family anddependent care services, and health and wellness
aim to provide a means for the workforce. This work
system aims to meet performance expectations while
managing their personal life needs andcommitments, but the level of participation or
response from the community can be negative.
However, not all types of flexible work
arrangements are manageable or beneficial for all
sizes and types of organizations. There are several
things employers should consider what type of
flexible scheduling will best suit their needs. On theother hand, previous research found a negative sidethat concerns all organizations, namely the lack of
direct supervision of workers from theirorganizations during FWA can result in a decrease
in intrinsic motivation and unethical behavior ofthese employees. In addition, flexible work can lead
to work-family conflict as spouses need to multitask
to take care of family responsibilities and work
responsibilities at the same time. This is because
flexible work arrangements can result in blurred
boundaries between work and home roles leading toan increase in work and family conflicts. This isV.

CONCLUSIONThe COVID-19 outbreak has affected the lives
of individuals around the world, without any age
limit and the type of work they are currently engaged
in, including employees, so it can be concluded :1) Flexible work began to be carried out as an
adaptation to conditions during the
pandemic due to restrictions on individual413

SEE-Mie, Japan, Nov.10-12, 2022

movement out of the house to break the
chain of the spread of the COVID-19 virus.
2) Employees will enjoy work-life balance if
telecommuting
reduces
work-family
conflict and increases welfare for
employees,
therebyincreasing
performance and productivity.
3) Flexible work needs to be supported by aflexible work environment, bonuses, andremuneration adapted to the demands of the
Bekasi City Government work to avoid
decreasing intrinsic motivation andemployee unethical behavior.
4) The control function when implementing
FWA needs to be arranged so that theperformance of the Bekasi City
Government can be maintained.

Miller, H., Ngonadi, C. V., Pilaar Birch, S. E.,
Pritchard, C., Vacca, K., Watkins, T. B., Zavodny,
E., & Ventresca Miller, A. R. (2021). Impacts of thecovid-19 pandemic on women and early careerarchaeologists. Heritage, 4(3), 1681–1702.
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flexible work arrangements: The case of workers in
Korea and gender differences in motivation. Journalof Organizational Change Management, 31(7),1438–1460.
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(QWL) OF BANK MANAGERS IN PUBLIC ANDPRIVATE SECTOR BANKS IN BIHAR, INDIA : A.
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[10] Martínez-León, I. M., Olmedo-Cifuentes, I., &Sanchez-Vidal, M. E. (2019). Relationship between
availability of WLB practices and financial results.
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ACKNOWLEDGEMENTS
This research was supported by the Bekasi City
Government, Bina Marga dan Sumber Daya Air(BMSDA) division’s.
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ACOUSTIC EMISSION OF INTERNAL DRAINAGE IN MULTISTOREY BUILDINGS
Anaebo Chike Emmanuel1, Rabee Rustum2,*, Lynne B Jack3 and Adebayo J. Adeloye4
1

Heriot-Watt University, Dubai Campus; UAE
Heriot-Watt University, Dubai Campus; UAE
3
Heriot-Watt University, Edinburgh Campus, UK
4Heriot-Watt University, Edinburgh Campus, UK
2

ABSTRACTThe number of multi-story buildings continues to increase around the world, and as a result, the quality of life
for those people living in these buildings requires ongoing evaluation. Many residents of multi-story buildings
complain about noise disturbances from internal drainage systems, mostly from toilets flushing in the upper levels.
This paper seeks to establish whether or not the noise from internal drainage systems in multi-story buildings
affects daily human activity and sleep patterns. A survey was undertaken on a 6-storey building and used a soundlevel meter to measure noise levels on different floors in the building. The results showed that the building height
does not influence the noise, nor does the noise affect human activity and sleep patterns, principally because thenoise does not last longer than a few seconds, with a typical duration of 15 seconds or less.
Keywords: Multi-storey building; Acoustics Emissions; Drainage; Flow.
INTRODUCTION

Although these different materials can be tested andthe material properties compared [6], there is noevidence that noise emissions have been completely
eliminated in most buildings.
The research reported herein has reported theacoustic emissions generated from internal drainage
systems in multi-floor occupancy buildings. In
addition, a questionnaire has been circulated tounderstand the effects, if any, of noise from drainage
on sleep behaviour and premature awakening and togather subjective responses from residents. This study
is an experimental one, looking at a 5-story building
and focusing on the effect of sound transmission on
occupants. Acoustic measurements were made to gain
an understanding of the extent of transmission thatmight affect occupants' well-being. Thus, the work
has been done so as to help propose a systematic
approach to reducing sound emissions during thedesign and installation stages. Hence the goal is toascertain the level of sound emissions from multistorey building sanitary facilities and how best to
properly mitigate any adverse effects by identifying
suitable sound-insulation material. Information on
methods and materials are presented along with detailon data collection techniques, followed by the main
results and recommendations for future research.

Multi-story buildings have seen a significant risein number in recent years. Starting from around the
middle of the 20th Century, the growth rate in their
numbers has been considerable, particularly in cities
in Asia and Europe. In developed cities across theglobe, multi-story buildings are often the main featureof urbanisation[1]. Multi-story buildings also bringeconomic implications as they often increase the costof buying land. In addition, they can also add
aesthetic value and can influence the lifestyle ofpeople living in and around these developments)[2].
However, modern structures must offer theirresidents comfort, of which curbing sound emissions
is one significant aspect [3]. Unfortunately, soundemissions can be found in buildings where proper
provisions have not been made to tackle suchproblems. Sound emissions in multi-storey buildings
can come from, for example, floor impact noise,neighbours, and electronic and elevator equipment. In
addition, it is not uncommon that emissions in newbuildings arise from the plumbing systems. And
while noise from sanitary facilities is not peculiar tomulti-storey buildings, it is essential to tackle thisproblem as multi-story buildings are home to a large
number of residents. Over time, occupants living withplumbing noise problems realise that such noises canbe irritating during the day and can interfere withsleep at night[4].
In the construction industry, there is a range ofmaterials that possess high sound insulation
properties; in particular, studies show that multiple
walled pipes can significantly reduce soundemissions[5]. Another method of reducing noise inpipes involves using sound insulation materials.

REVIEW OF THE LITERATURE
From the beginning of civilisation, tall structures
have fascinated humankind. This dates back to 2600
BC, when the Egyptian pyramids were constructed
and are still regarded as one of the seven wonders of
the ancient world [7]. Currently, the tallest buildingin the world is the Burj Khalifa, located in Dubai in
the United Arab Emirates, standing at 828m tall [8].
415SEE-Mie, Japan, Nov.10-12, 2022

However, multi-storey buildings require modern
technology to aid their function, part of which is theprovision of sanitary facilities for the removal ofwastewater.

[17]. Flow impact on bends and tees designed canalso lead to noise, horizontal movement of sewage
leads to flow noise as vertical movement leads tofalling noise[18].

Sound emission from drainage

Transmission of noise in the building

Sound is generated in pipes due to solid, gaseous,and liquid waste transport. Sound waves can travel
through elastic mediums and liquid and various solidmaterials [9,10]. The majority of audible frequencies
range between 20 and 20,000 Hz. Humans hear soundbest between 1,000 and 5,000 Hz [11].
Audible ranges are divided into 10-octave bands,
representing specific frequency spectrums. These
range from 16,000 Hz to 31.5 Hz and sometimes are
separated into third-octave bands for accuracy. If 500
Hz is taken as a medium frequency, its low and highfrequencies will range between 300 Hz and 750 Hz,
respectively. Hence, the knowledge of the thirdoctave bands aids the overall calculation of soundlevel[12].
Burk et al. (2011)[13] stated that an A-weighting
is applied to sound measurements that consider the
relative sound perceived by the human ear,recognising the ear's sensitivity to low audio
frequencies, particularly below 1,000 Hz, with B-, Cand Z-weightings used to measure very low, medium
and very high frequencies. Ray (2010) [14] also notedthat a minor change in the decibel reading leads to asignificant change in the sound produced, which has
an impact on what the person hears. The NIH (2014)[15] pointed out that the duration of exposure tocertain sounds is a significant factor in the amount ofpleasure or discomfort experienced by the listener.
Thus, humans should limit their exposure time tocertain sounds beyond 85 dB, and for every 3 dB
beyond 85 dB, the exposure time should be cut by half
to avoid permanent hearing damage.
The average sound level in dwellings is typicallyaround 25 dB, with 60 dB being the norm for offices,
depending on the activity and overall quality. This
results in noise rating (NR) curves for backgroundnoise evaluation as reported by Ref. [16].

Sound is transmitted through a building by air andsolid-borne pathways. Structure-borne transmission
involves sound emissions through solid materials andis regarded as the main noise path. Noise can also
convert from one form to another, e.g. from structureborne to airborne and vice versa. According to BS
8233: 2014[19], two stages of plumbing noise should
be considered during the design and construction
stages. Porous materials tend to absorb the sound of
middle to high frequencies based on their thickness.
Typical materials are:
• Hard finish: Plaster on a solid backing,• Porous absorber: 50 mm mineral fibre 50 kg/m3,• Panel absorber: 9 mm ply, 50 mm cavity containing
25 mm mineral fibre,• Perforated panel: 14% perforations, 25 mm cavity
containing mineral fibre,• Perforated gypsum tiles/board, 16% perforations,suspended with 200 mm plenum.
METHODOLOGY
The two major pieces of equipment required forthis analysis are the Nor140 sound analyser and thecalibrator. The Nor140 sound analyser is a precision
handheld device used to record sound and monitor
building acoustics in real-time. The calibrator isinserted within the microphone cartridge of the soundlevel meter.
Acoustic emission measurements
Measurements were collected from a 6-storey
student residence with modern engineering design
and technology. Each floor has the same layout from
top to bottom, with each room having a toilet with abathtub, WC and a washbasin. Care was taken to
ensure that the faucets in the bathtub and washbasins
were turned off, and there was no ongoing plumbing
activity in the building before the test was carried out.
The Nor140 sound analysing device was placedon the ground floor, and the water closet was flushed
on the 5th, 4th, 3rd, 2nd and 1st floors in turn and theresults were recorded on the ground floor. This was
repeated for each floor. The sound pressure levelmeasurements were made using 1/3 octave bands
because this produces more precise results. These
were then converted to octave bands so as to makecomparisons with required standards. Equation 1 aids
in calculating the sound pressure level for different

Causes of noise in the drainage system
Causes of noise in drainage systems include water
hammers, impact noises on bends and tees, flow
noises, and falling solid matter noise. When the watercloset, WC, is flushed, noise emissions are typicallytransmitted via connected structures. While a degreeof noise within the room housing the sanitary facility
is usually deemed acceptable, consequent sound insurrounding apartments is undesirable, and measures
should be taken to prevent this[11]. In addition, water
hammers can lead to the unwanted movement of
improperly attached pipes, causing vibrations, noise
and, in some cases, the loosening of joints and fittings
416

SEE-Mie, Japan, Nov.10-12, 2022

octave [20].
L𝒑 = 10 log ( 𝟏𝟎RESULTS AND DISCUSSION
𝑳𝟏
𝟏𝟎

+ 𝟏𝟎

𝑳𝟐
𝟏𝟎

+ 𝟏𝟎

𝑳𝟑
𝟏𝟎

+ …… + 𝟏𝟎
(1)

𝑳𝒏
𝟏𝟎

)

Acoustic results

Questionnaire

Using Equation 1, all the measurements were
calculated in octave bands and plotted as shown in
Figure 1. The frequencies analysed were for audible
frequencies only, ranging from 16 Hz to 8 kHz, andcompared with the NR curve. NR curves fordwellings are 25 and 30. The NR curve is used toascertain where the SPL level exceeds standards bycomparing the sound pressure level lines measured
with the NR curve, representing typical soundpressure level values with respect to octave bands.

A series of questions were drafted for the purposeof understanding the effect of noise emissions fromthe drainage system on the sleep pattern and daily
activities of the residents of the multi-storey building.
The questionnaire was developed and delivered
online and deployed a scaling system to assist
respondents (aged 15-35 years). The questionnaire
was designed in accordance with ISO (2003)[21]
recommendations and uses a direct question method.
The procedure used to choose the words for thequestionnaire scale was done in a way that is
consistent with its position on a numerical scale of 1
to 5 for most of the questions. The questionnaire wasused to answer the following questions:
1. Have you lived or currently live in a multi-story
building?
2. Are you satisfied or dissatisfied with the noisefrom your water closet as a result of flushing?
3. Are you satisfied or dissatisfied with the noisefrom your building drainage system?
4. Does the noise from your water closet as a resultof flushing affect your daily activities?
5. How heavy or high do you sleep?
6. Does the noise from the flushing of the watercloset from the upper floors affect your sleep?
7. Does the noise from the flushing of the watercloset from your adjacent neighbour affect yoursleep?

Fig. 1: Integrated average sound pressure level dBA.
Table 1 illustrates the results obtained from aseries of noise tests run with the aid of a sound level
meter on different levels of the multi-story building.
The results show that the sound level from the fivefloors tested is similar, which means that when the
toilet is flushed, irrespective of the level it is flushedfrom, the sound is transmitted through the pipes
equally down the building. This means that the heightof the building does not influence sound transmission
through the internal drainage system of a multi-storey
building. The results in Table 1 show the averagevalue of the results presented graphically in Figure 3.

Table 1. The sound level from flushing at different levels in a building.

Location of measurement
Background noise
Ground floor measurement from flush at 1st floor
Ground floor measurement from flush at 2nd floor
Ground floor measurement from flush at 3rd floor
Ground floor measurement from flush at 4th floor
Ground floor measurement from flush at 5th floor

Figure 2 shows the same measurements as in
Table 2, but with octave bands, the result of the tests
represented graphically for integrated average soundpressure levels. The results illustrated in Figure 2
show the corresponding values for the tests carriedout. The green curve depicts the NR curve of 30.
From the Figure, the sound measurements at
frequencies just above 250 Hz to 4.0 KHz clearly fallabove the acceptable values for dwellings. As a result,LAeq, dBA
26.0
42.0
39.0
41.6
40.9
42.2

there is a need to further analyse the noise levels toascertain the noise level that needs to be reduced in
A-weighting frequency.
From the graph above, it can be seen that the noisefrom each floor is similar throughout; from themoment the toilet is flushed from any level, it follows
the same pattern, with little difference, which may becaused by the speed of the sound takes from thesource to arrive at the point of collection with the417

SEE-Mie, Japan, Nov.10-12, 2022

sound level meter. The noise peaked at a frequency of
500 Hz and 39.2 dBA, which is well within the limitof 45 dBA for toilet flushing noise within a residentialbuilding.

Fig. 2. Drainage measurement results.
Table 2 shows that only noise of frequencies ranging
from 500 Hz to 4 kHz needs reduction with all soundpressure levels not exceeding 10 dB; this indicatesthat the acoustic emissions are not so high but can
result in discomfort for residents. As such, it ispertinent that more insulation should be added toreduce the noise emissions in the drainage system.

Table 2: Loudest SPL octave band measurement analysis.
Frequency
Drainage measurement SPL, dB
NR 30 curve
Reduction
values, neededdB
A-weighting correction factor
Reduction needed in A-weighting

31.5
57.7
Hz
75.8
-18.1
-39.4
-

63
45.8
Hz
59.2
-13.4
-26.2
-

125
43.7
Hz
48.1
-4.4
-16.1
-

Questionnaire results

250
37.7
Hz
39.9
-2.2
-8.6
-

500
42.4
Hz
34
8.4
-3.2
5.2

1.0
37
kHz
30
7
0
7

2.0
kHz
32.6
26.9
5.7
1.2
6.9

4.0
kHz
28.8
24.7
4.1
1
5.1

8.0
kHz
21.5
22.9
-1.4
-1.1
-

activities such as reading, working, or watching amovie. 51.1% disagreed that noise from theflushing of the water closet affected their daily
activity, 21.1% neither agreed nor disagreed,
14.4% agreed, 8.8% strongly disagreed, and 4.4%strongly agreed. This shows that most respondents
are not affected by noise from toilet flushing, andothers are indifferent, leaving just the small
number who believe it bothers them. Those may
be individuals who are more intolerant to the noiseof any kind.
d) Impact of water closet flushing noise from upper
floors on sleep: Ninety respondents gave theirverdict on the impact of flushing water closets
from upper floors on their sleep pattern. 46.6% ofrespondents noted that noise from the flushing ofwater closets from upper floors does not affecttheir sleep pattern, 21.1% agree, 17.7% neither
agree nor disagree, 13.3% strongly disagree, andjust 1.1% strongly agree. This shows that the
majority of respondents are of the opinion thatwater closet flushing from upper floors has no
impact on their sleep patterns. Those who felt
their sleep was disturbed may be light sleepers
whose sleep patterns can easily be interrupted by
the mildest of sounds.
e) Impact of water closet flushing noise from a nextdoor neighbour on sleep: This survey showed thatnoise generated from the flushing of the waterclosets from the adjacent neighbours on the same
floor has no impact on sleep patterns. Of the 90
respondents, 44.4% disagreed, 22.2% strongly
disagreed, 16.6% agreed, 14.4% neither disagreed
nor agreed, and only 2.2% strongly agreed. Thisis an indication that sleep is not affected by noise

Results are presented in percentages illustrating
the survey responses from 90 participants tounderstand their perception of noise from the flushingof WCs in the multi-storey building underconsideration. Key findings are presented below, andgraphical results are available in Appendix 1.
a) The tolerance level of respondents to noise fromthe flushing of the water closet: This aspectreflects how satisfied or dissatisfied respondents
are about the noise emission from their watercloset when flushed. The range spa was 'very
dissatisfied' to 'very satisfied'. 33.3% of
respondents were neither satisfied nor dissatisfied,followed by 31.1% who said they were satisfied,
26.6% who were dissatisfied, 5.5% very
dissatisfied, and 3.3% very satisfied. This showsthat most respondents are either indifferent about
the noise from the flushing of the water closet or
satisfied with it.
b) Respondents' satisfaction with noise insulation:
This question aims to understand the overallsatisfaction level of respondents with noise
insulation in their building of residence. Out of the
90 respondents that participated in the survey,
35.5% were satisfied with the insulation level of
their building, 27.7% were dissatisfied, 26.6%
were neither satisfied nor dissatisfied, 6.6% werevery satisfied, and just 3.3% were very
dissatisfied. This shows that most of the
respondents were either satisfied or indifferent.
c) Impact of water closet flushing noise on daily
human activity: This question was drafted tounderstand if toilet flushing affects daily human418

SEE-Mie, Japan, Nov.10-12, 2022

casa.com/conferences/zagreb/papers/Akram1HighRise.pdf[2] Hayati, H. and Sayadi, M.H., 2012. Impact of tallbuildings in environmental pollution, , inEnvironmental skeptics and critics. IAEES, pp. 9, 10.
http://taccire.suanet.ac.tz/handle/123456789/153[3] Science for Environment Policy (2017) Noiseabatement approaches. Future Brief 17. Produced for
the European Commission DG Environment by the
Science Communication Unit, UWE, Bristol. Available
at:https://ec.europa.eu/environment/integration/research/newsalert/pdf/noise_abatement_approaches_FB17_en.
pdf .
[4] Hye-kyung shin, Kyoung-woo kim, Jun-oh yeon, K.
yang (2016) 'Suggest toilet noise standardfor multidwelling residential building', in Proceedings of the
22nd international congress on acoustics. Buenos Aires,p.
2.
http://www.ica2016.org.ar/ica2016proceedings/ica201
6/ICA2016-0301.pdf[5] Marley-dBlue (2011) Acoustic soil and waste.
https://www.marleyplumbinganddrainage.com/media/
11322/marley-dblue.pdf.
[6] van der Schee W.G. (2012) 'Measurement of the noiseproduction in drainage pipes', CIB W062 Symposium
2012.
https://www.irbnet.de/daten/iconda/CIB_DC25341.pdf[7] Institute for steel development growth, (2014) Multistorey
building.
https://www.yumpu.com/en/document/read/36193244/
multi-storey-buildings-ii-institute-for-steeldevelopment-growth[8] Khalifa, B. (2010) Fact sheet Burj Khalifa. Dubai.
https://www.burjkhalifa.ae/img/FACT-SHEET.pdf[9] Schmidt-Jones, (2005) 'Sound, physics and music',
https://cnx.org/contents/GOQaowEz@1.52:ZSG7escu@10/Talking-about-Sound-and-Music[10] Fahy, F. and Thompson, D. (2015) Fundamentals ofsound and vibrations. Second Edi. Edited by F. Fahy
and D. Thompson. Boca Raton: CRC Press. Taylor andFrances group. https://doi.org/10.1201/b18348[11] Nataliya, D. (2016) Plumbing noises in water supply
and sewage systems. Mikkeli University of Applied
Sciences.
https://www.theseus.fi/bitstream/handle/10024/109246/Danchenko_Nataliya.pdf?sequence=1&isAllowed=y[12] Abel, E., Nilsson, P.E., Ekberg, L., Fahlén, P.,
Jagemar, L., Clark, R., Fanger, O., Fitzner, K.,
Gunnarsen, L., Nielsen, P.V. and Stoops, J.,
2003. Achieving the desired indoor climate-energy
efficiency aspects of system design. Studentlitteratur.
[13] Burk, P., Polansky, L., Repetto, D., Roberts, M. andRockmore, D., 2011. Music and computers: atheoretical and historical approach. Preface to theArchival Version (Spring, 2011).
[14] Ray, E.F., 2010. Industrial Noise Series, Part IV,
Modeling Sound Propagation. June, 16, p.2010.
[15] NIH Pub. No. 99-4233, 2014, Noise induced hearing
loss.
https://www.nidcd.nih.gov/sites/default/files/Documen
ts/health/hearing/noise-induced-hearing-loss-english8-2021.pdf[16] Cirrus research Plc. (2013) Calculation of NR & NC
Curves in the optimus sound level meters andNoiseTools software. North Yorkshire. pp. 4 – 14.

from the flushing of the toilet from a neighbour's
residence on the same floor.
From the analysis carried out, it is observed thatwhile most respondents claim that the noise fromflushing water closets does not disrupt their daily
activity and sleep pattern, others believe it does. Thisfinding is confirmed from the acoustic emissions
levels presented herein. The analyses also show that
there is a need for further insulation. Hence, the pipes
should be insulated further to reduce noise emissions.
CONCLUSION
The tests carried out as reported herein lead to theconclusion that noise from the internal drainage
system from flushing WCs at different levels in a
multi-story building does not change with height. The
test was run on a 6-storey residential building, and theaverage noise levels obtained were 42, 39, 41.6, 40.9
and 42.2 dBs, respectively. The variability in thisrange is negligible, showing that the noise differenceis unchanged throughout the different levels. The
questionnaire also provides results that show thatnoise from the water closet's flushing, although loudenough to be heard by its residents, whose ages range
from 15 to 35 years, does not pose a major problem
because it does not occur beyond 10 seconds. The
noise does not disturb sleep patterns but can beproblematic if it becomes continuous. Since the noise
to be reduced is between the mid to high-level
frequency, pipes should be covered thoroughly by
insulation and placed behind a perforated gypsum
board, 16% perforations, suspended with 200 mm
plenum as recommended in BS 8233:2014. These
results can be used to improve human health, comfort
and general wellbeing. Furthermore, this article will
aid better sound insulation in buildings, knowledge ofthe best materials for sound insulations and a proper
understanding of what humans perceive as tolerable
and intolerable noise levels.
RECOMMENDATION
To further reduce the noise level within a multistory building, it is pertinent to run further tests toconfirm the best materials to protect residents fromunwanted noise. In addition, it is pertinent to analyse
the acoustic emissions generated from the hydraulicjumps that occur at junctions between vertical andhorizontal stacks and determine optimum places tocreate bends and velocity breaks, hence decreasing
the acoustic emissions.
REFERENCES[1] Farouk, A., 2011. High rise buildings and how theyaffect countries progression. E iataorC Leader.
https://g-419SEE-Mie, Japan, Nov.10-12, 2022

Availableat:https://www.cirrusresearch.co.uk/library/documents/te
chnical_papers/TN31_Calculcation_of_NR_and_NC_
Curves_in_the_optimus_sound_level_meter_and_Nois
eTools_software.pdf[17] Choon, T. W. et al. (2012) 'Investigation of Water
HammerEffectThrough Pipeline System',International Journal on Advanced Science,
Engineering and Information Technology, pp. 48, 49.
doi: 10.18517/ijaseit.2.3.196.
[18] Catron, F. and Fagerlund, A. (2009) 'Noise generationand propagation effects on piping system components',
in Noise Control Engineering Journal. doi:
10.3397/1.3155382.

[19][20] BS 8233, (2014) Guidance on sound insulation andnoise reduction for buildings. BSI standards limited
2014.
20- Nor 140 (2021), Nor Instruction Manual,https://www.akustik.lth.se/fileadmin/tekniskakustik/ed
ucation/LjudBS_17/Nor140_Instruction_Manual_v3R0.pdf[22] ISO (2003) ISO-TS-15666: Acoustic-assessment ofnoise annoyance by means of social and socio-acoustic
surveys. Geneva:ISO, International Organization forStandardization.
https://www.iso.org/standard/28630.html

APPENDIX 1
Results of the survey

420

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

INFRASTRUCTURE IMPACTS CALCULATOR:AN INFRASTRUCTURE ASSESSMENT TOOLUSING CO-BENEFIT APPROACH
Nicanor R. Roxas, Jr.1, Krister Ian Daniel Z. Roquel2, Krista Danielle S. Yu3, Alerik Ezekiel C. Ruiz2, andAlexis M. Fillone2
1
Department of Manufacturing Engineering and Management, De La Salle University, Philippines;
2
Department of Civil Engineering, De La Salle University, Philippines;
3
School of Economics, De La Salle University, Philippines

ABSTRACTThe 1992 United Nations Conference on Environment and Development recognized the concept of sustainable
development which balances the economic, social, and environmental factors to meet our needs and the future.
Succeeding climate actions such as the Clean Development Mechanism, Nationally Appropriate Mitigation
Actions, Green Climate Fund, Intended Nationally Determined Contributions, and the Paris Agreement reinforce
the support for co-benefits. The co-benefits approach considers both the development and climate benefits in asingle policy. The Sustainable Technology Assisted Route Planning for Region VI, funded by the Department of
Science and Technology – Philippine Council for Industry, Energy, and Emerging Technology Research andDevelopment, considers this approach. It aims to support the development of a sustainable Local Public Transport
Route Plan (LPTRP) that integrates the road and maritime transport network of Region VI through the use ofdeveloped technologies for the transport sector while considering its social, economic, and environmental impacts.
The LPTRP is crucial in the implementation of the Public Utility Vehicle Modernization Program launched in2017. In this regard, an Excel-based assessment tool compatible with a transport simulation tool is developed andpresented. The tool facilitates a swift processing of information from the simulation results of different scenarios
to the comparative assessment of transport infrastructure proposals and policies. It enhances the capabilities of
local staff and researchers in assessing the effects of transport projects and programs using co-benefit analysis.
This endeavor hopes to foster better local decision-making related to transportation planning and management
affecting not only the economy but also the environment.

Keywords: Co-benefit analysis, Transportation planning, Impact assessment tool, Sustainability

INTRODUCTION

growth.
Thestrongrelationshipbetweentransportation and health necessitates a more
inclusive approach - one that would cover theinterests of both the stakeholders and the society. In
light of the broad evidence that climate change isoccurring with potentially expensive and far-reachinghealth consequences, urgent and substantial actions
are needed. Several researchers have employed theco-benefits (CB) framework to assess transport
projects and policies beyond just transportation
metrics [1]–[3]. Its use has become a predominantconcept in scientific writing that focuses onreconciling environmental and developmental goals.
This appears to be very promising for developed
economies and emerging economies, as it offers away of not compromising economic growth whilestill allowing environmental aspects to be taken into
account. The literature is abundant with transportationand traffic studies offering various solutions for the many
problems that face the transport sector. Experiences ofother countries and best practices all over the world are
now readily available. With these information, local

The 1992 United Nations Conference on
Environment and Development recognized the conceptof sustainable development which balances the
economic, social, and environmental factors to meet ourneeds and the future. Succeeding climate actions such as
the Clean Development Mechanism, Nationally
Appropriate Mitigation Actions (NAMAs), Green
Climate Fund (GCF), Intended Nationally Determined
Contributions (INDCs), and the Paris Agreement
reinforce the support for co-benefits. The co-benefits
approach aims to consider both the development andclimate benefits simultaneously in a single policy.
The transportation sector links the different sectors of
our economies. Investments in the transportation sector
affect the country’s development. The movement ofpeople, goods, and services almost always require the useof transportation. In this regard, being able to improveand optimize the transportation sector is critical to sustain
economic growth. However, public health should
never be overshadowed by the pursuit of economic
421

SEE-Mie, Japan, Nov.10-12, 2022

planners are given the opportunity to learn from previous
mistakes and follow or even improve on the success ofothers for local projects implementations.
Back in 2018, local transportation planningspecialists were commissioned to conduct a twoweek hands-on training to municipal, city, andprovincial representatives of Local Government
Units (LGUs) to develop the Local Public Transport
Route Plan (LPTRP). The expected output of thecapacity building activity is the submission of
LPTRPs. However, only a few LGUs were able toachieve. The LPTRP is an important document for the
LGUs in order for the Public Utility Vehicle
Modernization
Program(PUVMP)
tobe
implemented. The training has shown that theparticipants had limited exposure to both QGIS for
spatial land-use planning and JICA STRADA v.3.5
for public transport planning. JICA STRADA
software is highly complex and thus, participants
were not able to utilize this tool in developing theirrespective route plans.
A more user-friendly
transportation planning tool is therefore proposed.
Transportation plans and policies crafted from soundand holistic approaches are needed in identifying asustainable transportation development roadmap thatwould cater to the needs of all stakeholders. This
research is part of an ongoing research program entitledSustainable Technology-Assisted Route Planning for
Region VI (STARPLANVI) which is funded by the
Department of Science and Technology – Philippine
Council for Industry, Energy, and Emerging
Technology Research and Development (DOSTPCIEERD). The STARPLAN program aims to
support the development of a sustainable Local Public
Transport Route Plan (LPTRP) that integrates theroad and maritime transport network of Region VI
through the use of developed technologies for thetransport sector. The LPTRP is crucial in theimplementation of the Public Utility Vehicle
Modernization Program of the Philippine government
which was launched in 2017. STARPLAN will
specifically train and provide both the software andhardware public transport planning tools to the local
government staff and university faculty and staff for
their use to sustain the public transport planning andmanagement of Region VI.
Through the
STARPLAN VI, several computers installed with thenecessary public transport planning tools andtrainings are provided to the local government staff
and partner educational institutions for their use tosustain the public transport research, planning, andmanagement of Region VI. The program objective isvery timely and appropriate as various projects arebeing constructed and many are still in the planning
process. In this light, the trainings provided to thestaff are quite apt. The level of understanding of thevarious concepts of the transportation planning
process and the skills are further enhanced. In thevarious trainings, different participants have different

level of understanding of the transportation planning
concepts. In order to further streamline this process,the Traffic Infrastructure Impacts Calculator wasconceived. This will facilitate LGU personnel andresearchers to easily estimate the effects of certain
policies and proposals from their simulations. The
tool facilitates a swift processing of information fromthe simulation results of different scenarios to thecomparative assessment of the proposals and policies
for the region using Co-benefit Analysis. Thisendeavor hopes to foster better local decision-making
related to transportation planning and management.
To adopt a more systems-oriented approach andconsidering the archipelagic nature of the country, it
is essential to plan towards an interconnectedmaritime and road transport network. Noting the caseof Region VI wherein maritime transport services areavailable to provide linkages between Negros
Occidental and Guimaras with Panay Island.
The targeted audience of the TIIC are LGUs,
specifically those who are in charge of making local
policies, transport projects and infrastructure.
STARPLAN also provides training in varioustransportation tools and software to Region VI LGUs
and providing the TIIC tool can provide huge benefit
to them. This is because the TIIC can provide LGUs
a way to quickly test and assess policies,
infrastructures, and projects on their own.
REVIEW OF RELATED LITERATURE
Urban areas are generally centers of economic
growth. Rapid development and expansion of theseareas require a massive amount of investment ininfrastructure and transportation for sustainability.
The transportation sector is next to the industrial
sector in terms of energy consumption accounting forabout 30% of the world’s total delivered energy. The
transportation sector guzzles around 60% of the
global oil demand and is responsible forapproximately 22% of the CO2 emission in 2008
globally. Moreover, road vehicles account for around
81% of the total transportation energy demand [4]. In
a research in Delhi, India, cobenefits was used inorder to determine the effects of mode shifting to a
non-polluting mass transit system. The study was
motivated by the increasing population in the city
resulting in an escalation of transportation demand
and thus the problems of congestion and emissions
from road vehicles [5]. In another study in Manila,
Philippines, cobenefit analysis was also applied indetermining the effect of mode choices of commuters
along EDSA when hypothetical improvements are
made with respect to the access and egress modes to
MRT3. The difference of these scenarios in terms ofenvironmental effects from baseline and hypotheticalscenarios were examined [6]. The same researchteam also did a cobenefit analysis for the proposed
Panay-Guimaras-Negros Bridge in Western Visayas
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SEE-Mie, Japan, Nov.10-12, 2022

Region [7]. A study made in Beijing also looked into
cobenefits. The study specifically looked into theeffect of promoting NEVs (new energy vehicle) on
energy consumption [8]. There are quite a lot of
studies concerning the use of cobenefits to assess theeffects of various proposed transportation projects
and policies. Mayrhofer and Gupta [9] accredits the
co-benefits approach as a positive and constructive“win-win” way to operationalize how economic,
environmental, and social aspects can be integrated
within the concept of sustainable development,
instead of framing them in terms of trade-offs. In thisstudy, by incorporating the benefits of travel time andvehicle operating cost (VOC) reduction with theprimary CB of savings in accident losses andemission costs, an all-inclusive and long-term
assessment will be performed, aiming to determine
the optimum development roadmap that caters to theinterests of both the industry and the community.
In this light, useful tools are required in order tofurther facilitate and improve transportation planningtowards sustainability. A growing consensus amongplanners regarding the interaction between the
integrated land-use and the transport policies results
in better outcomes [10]. The researchers mentionedthat accessibility planning is a key strategy inmaximizing environmental sustainability and qualityof life in urban areas brought about by more efficienttransport systems. In this particular study, they
developed a tool which assesses the location choicesof new activities in Rome based on accessibilitychanges. This tool aids planners in assessing theeffects of new location choices on mobility and theenvironment in monetary terms. Another study byMateichyk et al [11] also developed a tool in thefacilitation of the processes and analysis for EIAs in
Ukraine. Their web-based tool was proven to work
starting from encoding to reports generation tosupervisory state agency. These tools aid in theplanning and could therefore aid in achieving thevarious sustainability goals through the proper
assessment of various projects and policies.
In the Philippines, one of the flagship projects ofthe current administration is the PUVMP. To shed
more light on the importance of this program, basedon an LTO report, there are more than 12 million
motor vehicle units registered as of 2019 wherearound 18% are PUJs [12]. Buses and PUJs servearound 67% of the demand in Metro Manila. The
PUVMP is not just about modernizing the PUJs as it
also aims to consolidate the operators into
cooperatives, reduce emission, encourage mode shift
through improved services, and enhance the living
standards of the PUJ industry/sector [12]. The newbody make which costs at least 1.6 million pesos,
minimum of EURO IV emission standards, global
navigation satellite system (GNSS), automatic farecollection, free WIFI, CCTVs, speed limiters,
dashboard cameras, and easy accessibility for PWDs

are some of those which have been required by
LTFRB. Under the modernization, the units willachieve being comfortable, accessible, reliable,
environment-friendly, and sustainable (CARES) withdue consideration to PWDS and the elderly. It is
worth noting that 90% of the total PUJs nationwide
are at least 15 years old [12]. The timeworn units
contribute largely to air pollution and are getting
obsolete. In order to aid the drivers and operators inthis program, the Land Bank of the Philippines andthe Development bank of the Philippines areproviding special loan packages where the 5% equity
or down payment of 80,000PHP can be shouldered by
the government [12].
However, one of therequirements for the loan is to secure the Local Public
Transportation Route Plan (LTPRP) from the LGUs
which is also a problem due to non-submission of
LGUs [13]. In the current fragmented set-up which
is characterized by disorganized dispatching and onstreet competition, drivers tend to be more aggressive
in order to increase their profit. Jeepney units also
stop anywhere causing congestion [14].
METHODOLOGYThe TIIC uses both Excel’s and Visual Basic forApplications (VBA) Userform functions. The tool
uses input based around EMME’s output which are
the Average speed of the network, Total VDT, and
VHT in order to do the Co-benefits analysis. The
output of the analysis would be in billions ofPhilippine Pesos per year for Time Savings, Vehicle
Operating Cost, and Environmental Cost Savings.
This enables a simple comparison among alternatives.
The Institute for Global Environmental Strategies(IGES) has promoted the use of the co-benefits
approach to incorporate both the climate anddevelopment issues in project evaluations. The cobenefit analysis is a tool which provides invaluable
information to policy makers. It incorporates savingsin travel time, vehicle operating costs, traffic safety,
and environmental emissions [15].
The travel time savings is quantified by taking thedifference between the total travel cost of travellers
with and without the project. The total travel time
costs for the scenarios are computed as follows:
𝑩𝑻𝒊 = ∑𝒋 ∑𝒍(𝑸𝒊𝒋𝒍 × 𝑻𝒊𝒋𝒍 × 𝜶𝒋 ) × 𝟑𝟔𝟓

(1)

where
𝑩𝑻𝒊 − total travel time cost with/without the
project
𝑸𝒊𝒋𝒍 −traffic volume for j vehicle type on link l,
with/without the project (vehicle/day)𝑻𝒊𝒋𝒍 − average travel time for j vehicle type on linkl, with/without the project (min)𝜶𝒋 − value of time for j vehicle type𝒊 ∶ 𝒊 = 𝒘 𝐰𝐢𝐭𝐡 𝐩𝐫𝐨𝐣𝐞𝐜𝐭; 𝒊 = 𝟎 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭423

SEE-Mie, Japan, Nov.10-12, 2022

The vehicle operating cost reduction is quantified
by taking the difference between the vehicle
operating costs between the two scenarios. The
computation for the savings is shown as follows:

volume of vehicles on links for the baseline scenario.

𝑩𝑹𝒊 = ∑𝒋 ∑𝒍(𝑸𝒊𝒋𝒍 × 𝑳𝒍 × 𝜷𝒋 ) × 𝟑𝟔𝟓
(2)
where
𝑩𝑹𝒊 − total vehicle operating cost with/without
the project
𝑸𝒊𝒋𝒍 −traffic volume for j vehicle type on link l,
with/without the project (vehicle/day)
𝑳𝒍 − link length of link, l (km)𝜷𝒋 − value of vehicle operating cost for j vehicle
type𝒊 ∶ 𝒊 = 𝒘 𝐰𝐢𝐭𝐡 𝐩𝐫𝐨𝐣𝐞𝐜𝐭; 𝒊 = 𝟎 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭

Fig. 2The environmental emissions are quantified using
the top-down approach where the amount of fuel used
for the scenarios are first quantified. This provides
the basis for taking the difference in the emissions
generated between the baseline and the with-project
scenarios. The emissions included are the SOx, CO2,
NOx, and the PM which are also monetized using thevarious marginal costs per air pollutant. Monetizing
all the benefits enable the comparison of scenarios
using a single unit. The overall savings provide
policy makers an overview of the costs and benefits
associated with the scenarios involving policychanges or project proposals being evaluated.

Roxas City baseline Emme network

Two hypothetical scenarios were formulated as
seen in Fig.3. The first one is related to theintroduction of a circumferential road whereas theother scenario involves adding the same
circumferential road with other new local roads.

RESULTS AND DISCUSSION
In this particular research, Roxas City has beenchosen as the pilot city to implement the TIIC. Roxas
City, as seen in Fig.1, is in the island of Panay whichis part of the Western Visayas Region where the
STARPLAN VI project is deployed.
Fig. 3

Two formulated hypothetical scenarios

The traffic is forecasted for the 5, 10, and 20 year
projections shown below. The comparison of thebaseline scenario against the other two hypotheticalscenarios are based on the projections shown in Fig.4.
70000
60000
50000

Fig. 1

Roxas City Location

40000
30000

The city has been chosen because they wereamong the first to gather data for their LPTRP. In thisregard, the data, which includes traffic counts, origin
and destination information, public transport routes,
and other relevant information, gathered was used inorder to develop the EMME model for the baseline
scenario. The various traffic counts were used tocalibrate the baseline model. Shown in Fig.2 is the

20000
10000

Public0Baseline
trips

Fig. 4424

5-year trips

Private10-yeartrips

Baseline and forecasted traffic

20-yeartrips

SEE-Mie, Japan, Nov.10-12, 2022

The different scenarios were simulated and werecompared with the baseline scenario. Shown in Table
1 is the summary of the scenarios simulated in EMME.
It can be seen that overall, the proposed scenarios will
improve the current situation due to the enhancementin average zone to zone travel time and speed. The
volume-capacity ratio (VCR) also shows a significant
improvement brought about by the proposed roads.
Table 1
Scenarios
baselinewithcircumferential
roads
with
circumferential
and additionalroad links

These information were directly fed into the TIIC as
shown in Fig.6.
The information can either be
encoded manually or imported from the worksheet
output of EMME. Once all the information is fed to
the TIIC, the calculation may be started and several
charts and a table can be seen in the output tab of thetool. Figure 7 contains four different charts for thedifferent savings calculated. For travel time savings,
the hypothetical scenarios are each compared with thebaseline scenario and the savings are calculated basedon the reduction in travel time for the entire network.
The minimum wage rate is used to convert the travel
time savings to monetary units. The next cobenefit
included in the TIIC is the vehicle operating costsavings. This is computed based on the link speeds
and estimated using equations developed by JICA
[16]. Due to improved speed in the network, thevehicle operating cost for the scenarios indicate
savings. More savings can be derived from thecircumferential plus other local roads scenario due tobetter average speed in the network. The reduction in
NOx, CO, CO2, SOx, and PM were considered forthe environmental savings. The reduction also
derived from the changes in speed and quantified
through the values obtained from Clean Air Asia
Initiatives. Figure 7 shows a similar result wherescenario B involving the provision of thecircumferential road along with other local roads
yield the larger amount of savings.

EMME Scenario modeling summary
Averagezone tozone travel
time (min)
23.55

VCR

Ave.
speed
(kph)

VDT
(veh-km)VHT(veh-hr)

0.16

26.75

63010.38

2306.13

20.86

0.11

28.10

60090.06

1779.55

20.54

0.11

28.15

59512.49

1750.47

Fig. 5Baseline and with-circumferential road
scenarios comparison (left) and baseline and withcircumferential road plus other local roads scenarios
comparison (right)
Figure 5 on the left shows the scenario
comparison output of the baseline vs withcircumferential road and on the right, the comparison
between baseline and with-circumferential plus otherlocal roads. The green-colored links show reduction
in traffic volume while those in red show increase involume. The scenario comparison clearly shows theimpact of the provision of the proposed roads.
Though this tool, planners can visualize the extent of
the effect of the projects, the TIIC can aid in
accurately comparing the effects of these scenarios interms of the cobenefits.

Fig. 6

Fig. 7

TIIC comparison of various scenarios

CONCLUSIONSThis study is part of the government-funded research
program STARPLAN VI which aims to support thedevelopment of the LPTRPs of various LGUs that
integrates the road and maritime transport network ofRegion VI through the use of developed technologies
for the transport sector. In order to aid government
staff in assessing proposed transport infrastructure
projects, the TIIC was conceived. The TIIC tool isable to perform co-benefit analysis in line with theoutputs of EMME which is the transportation
planning software used in the project. The toolstreamlines the process of being able to compare
various scenarios that are introduced in EMME
through co-benefit analysis that is integrated in the

TIIC GUI with EMME baseline results

After incorporating the two scenarios in EMME,
separate simulations were prepared for each of them.
After each run, results were exported and compiled.
425

SEE-Mie, Japan, Nov.10-12, 2022

TIIC tool. This tool can either accept imported
EMME CSV data or through manual encoding. Cobenefit analysis has been utilized as it not only looks
into vehicle operating costs and value of travel timesavings as well as environmental emission savings.
This promotes the concept of sustainability which isessential especially during these times were climatechange is a pressing issue.
In this paper, Roxas City, Philippines was chosen
to be the pilot implementation of the TIIC. Two
EMME scenarios were formulated and wereseparately compared with the baseline scenario. Not
only can this tool accept various scenarios but it canalso accept various projections from each scenario. It
was determined that the second case will provide themore co-benefits to the city. Through this tool, thisresearch aims to achieve its goal of assisting the
LGUs in their task of crafting sustainable transport
infrastructure projects and programs in Region VI.

[6] Roxas, N. R., Fillone, A. M., & Roquel, K. I. D.
(2018). Estimating the environmental effects ofcar shifting behavior along EDSA. International
Journal of GEOMATE, 14(44), 8–14.
[7] Roxas, N. R., & Fillone, A. M. (2017). Co-benefit
analysis of the proposed Panay-Guimaras-Negros
Bridge Project, Western Visayas, Philippines.
Transportation Research Procedia, 25, 3568–
3581.
[8] Yang, X., Lin, W., Gong, R., Zhu, M., & Springer,
C. (2021). Transport decarbonization in big cities:
An integrated environmental co-benefit analysis
of vehicles purchases quota-limit and new energy
vehicles promotion policy in Beijing. Sustainable
Cities and Society, 71(August 2020), 102976.
[9] Mayrhofer, J. & Gupta, J. (2015). The science andpolitics of co-benefits in climate policy.
Environmental Science and Policy, 57, 22-30.
[10] Coppola, P., & Papa, E. (2013). Accessibility
Planning Tools for Sustainable and Integrated
Land Use/Transport (LUT) Development: An
Application to Rome. Procedia - Social and
Behavioral Sciences, 87, 133–146.
[11] Mateichyk, V., Khrutba, V., Kharchenko, A.,
Khrutba, Y., Protsyk, O., & Silantieva, I. (2021).
Developing a Tool for Environmental Impact
Assessment of Planned Activities and Transport
Infrastructure Facilities. Transportation Research
Procedia, 55(2019), 1194–1201.
[12] Estipular, J. L. (2020). CPBRD Policy Brief
Looking into the impLementation of pubLic
utiLity
VehicLemodernization
programCongressional Policy and Budget Research
Department House of Representatives.
[13] ARTA. (2021). ARTA to create TWG to address
issues raised by transport coops in PUV
Modernization Program - Anti-Red Tape
Authority. https://arta.gov.ph/press-releases/artato-create-twg-to-address-issues-raised-bytransport-coops-in-puv-modernization-program/[14] Pontawe, J., & Napalang, S. (2018). Examining
the Potential Significanceof Industry
Consolidation and Fleet Management in
Implementing the DOTr ’ s PUV Modernization
Program : A Case Study of 1TEAM. Philippine
Transportation Journal, 1(2), 47–58.
[15] (IGES), I. for G. E. S. (2011). Mainstreaming
Transport Co ‐ benefits Approach. A Guide to
Evaluating Transport Projects. In Institute for
Global Environmental Strategies (IGES).
[16] JICA. (2014). Technical Report No. 2: Transport
DemandAnalysis.
March.
http://www.neda.gov.ph/wpcontent/uploads/2015/03/FR-TR2-TECHNICALANALYSIS.-12149639.pdf

ACKNOWLEDGMENTS
This project is funded by the Department of
Science and Technology (DOST) through thePhilippine Council for Industry, Energy andEmerging Technology Research and Development(PCIEERD). The authors would like to acknowledge
DOST-PCIEERD, De La Salle University, and the
University Research Coordinating Office for theirsupport on this research. The authors would also liketo extend their gratitude to the staff of the various
LGUs from Region VI for their assistance.
REFERENCES[1] Kwan, S., Tainio, M., Woodcock, J., Sutan, R., &Hashim, J. (2017). The carbon savings and healthco-benefits from the introduction of mass rapidtransit system in Greater Kuala Lumpur,
Malaysia. Journal of Transport&Health, 6, 187200.
[2] Shaw, C., Hales, S., Edwards, R., HowdenChapman, P., & Stanley, J. (2017). What can fuelprice increases tell us about the air pollution healthco-benefits of a carbon price. Journal of Transport& Health. Advanced online publication.
[3] Alam, M., Hyde, B., Duffy, P., & McNabola, A.
(2018). Analysing the co-benefits of transport
fleet and fuel policies in PM2.5 and CO2
emissions. Journal of Cleaner Production, 172,623-634.
[4] Atabani, A. E., Badruddin, I. A., Mekhilef, S., &Silitonga, A. S. (2011). A review on global fueleconomy standards, labels and technologies in thetransportation sector. Renewable and Sustainable
Energy Reviews, 15(9), 4586–4610.
[5] Panwar, M., Singh, D. K., & Devadas, V. (2018).
Analysis of environmental co-benefits oftransportation sub-system of Delhi. Alexandria
Engineering Journal, 57(4), 2649–2658.
426

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

GROWTH CHARACTERISTICS OF PINUS DENSIFLORA INSIMULATED HEAVY METAL CONTAMINATED SOIL

1

Takuma Kubohara1, Hiroyuki Ii2, Ryoichi Araki3 and Masakazu Saito4
Kinokawa City Office, Japan; 2Faculty of Systems Engineering, Wakayama University, Japan; 3Faculty of
Education, Wakayama University, Japan; 4Wakayama Prefectural Forestry Experiment Station, Japan

ABSTRACTThe effects of heavy metals on the growth and their accumulation patterns in Pinus densiflora in heavy metal
contaminated soil were studied because the influences of heavy metals on the growth of Pinus densiflora have notbeen well revealed. The tree heights of Pinus densiflora grew 11 ~ 14 cm to 15 ~ 17 cm in 4 weeks with or without
Zn, W, Cu, and Ni loading. Zn and W concentrations (37 to 140 for Zn and 10 to 52 mg/kg-dry for W) in Pinus
densiflora in each metal load condition were higher than those in other load conditions (20 to 53 for Zn and 7 to
40 mg/kg-dry for W). Zn and W concentrations in roots of Pinus densiflora in each metal load condition (70 to
140 for Zn and 30 to 52 mg/kg-dry for W) were higher than those concentrations in leaves and stems of Pinus
densiflora in each load condition (37 to 66 for Zn and 10 to 30 mg/kg-dry for W). Zn concentrations in leaves (37to 50 mg/kg-dry), stems (49 to 66 mg/kg-dry), and roots (70 to 140 mg/kg-dry) of Pinus densiflora in Zn loadcondition were higher than those in other load conditions (20 to 40 for leaves, 30 to 45 for stems, and 30 to 53
mg/kg-dry for roots). Therefore, it was concluded that Pinus densiflora was not affected by growth abnormalities
caused by heavy metal-contaminated soil and grew while accumulating Zn in the leaves, stems, and roots and W
in the roots.
Keywords: Pinus densiflora, Heavy metal tolerance, Roots, Zn, W

INTRODUCTION

each pot, and the load of heavy metals was started
approximately 2 months after transplanting. The
experimental period was early May to early June
2022. Pinus densiflora seedlings were placed outside
in a sunny place during the experiment. Table 1
shows the experimental conditions. The pot
experiment was carried out under five conditions ofcopper, nickel, zinc, tungsten, and no load. Cu, Ni, Zn,

It is known that some plants accumulate large
amounts of heavy metals. Scopelophila cataractae, atype of bryophyte, and Athyrium yokoscense (Franch.
et Savat.) Christ, a type of fern are famous[1]-[2].
Those species are often found in heavy metal
contaminated areas such as mining sites. On the other
hand, Pinus densiflora is also often found in mining
sites and is known to accumulate heavy metals [3]-[5].
However, the influences of heavy metals on thegrowth of Pinus densiflora have not been wellstudied. Therefore, in this study, we reveal the effectsof heavy metals on growth and their accumulation
patterns in Pinus densiflora under different heavy
metal-contaminated soil conditions.
STUDY METHOD
Outdoor Experiment
Figure 1 shows the location of the outdoor
experiment. The outdoor experiment was carried out
in Kinokawa City, Wakayama Prefecture. In thisexperiment, Pinus densiflora seedlings provided by
Wakayama Prefectural Forestry Experiment Station
were used. Figure 2 shows the outline of pot
experiment. Pinus densiflora seedlings that had beensown in the open field for about 10 months were usedin the experiment. One seedling was transplanted into

Fig.1 Location of the outdoor experiment.
427

SEE-Mie, Japan, Nov.10-12, 2022

50

Tree height growth (mm)Pinus densiflorad = 140mm

dia. =
55mm

pot
soil

dia. = 40mm

-

20
10
0
0

1

Zn
Cu
CTRL

W
Ni

0

1

2
3
Elapsd weeks

4

Tree height (mm)160

Table1 The experimental conditions.

Nothing30

180

Fig.2 The outline of pot experiment.

CTRL

40

W
Ni

200

*At the experiment start.

Heavy metal
SampleLoaded heavy metal concentration
name
（ppm）
Zn
Zn
860
(ZnSO4 solution)
W
W
33(K2WO4 solution)
Cu
Cu
2.5
(CuSO4 solution)
Ni
Ni
2.6
(NiSO4 solution)

Zn
Cu
CTRL

140

Loadings

120

start and 1 week
after theexperiment start:
10mL/pot
2 and 3 weeks
after theexperiment start:
20mL/pot100
2
3
Elapsd weeks

4

Fig.3 Changes of tree height growths and treeheights.
Pinus densiflora were measured by ICP-OES(AMETEK, Inc., SPECTRO ARCOS). The actual
detection limit of ICP-OES is 0.01ppm for Cu, Ni, Zn,
and W.

-and W concentrations in solutions were 2.5, 2.6, 860
and 33ppm. Heavy metals were loaded at theexperiment start, 1 week, 2 weeks, and 3 weeks after
the experiment start. The amount of loaded heavy
metal solutions was 10 mL/pot at the experiment startand 1 week after the experiment start, and was 20
mL/pot at 2 weeks and 3 weeks after the experimentstart. The tree height of Pinus densiflora seedlings
was measured in an outdoor experiment. 4 weeks
after the experiment start, Pinus densiflora seedlings
were pulled out from their pots to determine the heavy
metals concentrations in the seedlings. Afterremoving the soil from the roots of Pinus densiflora
seedlings, the whole body was rinsed with pure water.
Then, Pinus densiflora seedlings were divided into
leaves, stems, and roots.

RESULTS AND DISCUSSION
Tree Height Growths of Pinus densiflora inContaminated and Non-contaminated Soils
Figure 3 shows tree height growths and treeheights of Zn, W, Cu, Ni, and CTRL. At 4 weeks laterfrom the experiment start, tree height growths of Zn,
Cu, and Ni were almost the same as that of CTRL.
However, tree height growth of W was lower thanthat of CTRL. At 4 weeks later from the experimentstart, tree heights of Zn, W, Cu, and Ni were almost
the same as that of CTRL. Moreover, at theexperiment start, tree height of W was the third tallest
of all and was already tall. Therefore, it was thoughtthat tree height growth of W was small. And then, no
appearance growth abnormalities such as wilting
were observed in all seedlings during the experiment.
From the above results, it was found that Pinus
densiflora can grow in Zn, W, Cu, and Ni
contaminated soils.

Laboratory analysis
Laboratory analysis was performed at Wakayama
University. Three samples for analysis were prepared
for leaves, stems, and roots. Leaves, stems, and rootsof Pinus densiflora were desiccated by a dryer at
60 °C. After drying, they were dissolved withconcentrated nitric acid and filtered with a membranefilter in 0.45 micrometer of pore size. After filtering,
the Cu, Ni, Zn, and W concentrations in each part of428

SEE-Mie, Japan, Nov.10-12, 2022

15
Cu (mg/kg-dry)Zn (mg/kg-dry)

150

100

50

0

Zn

W

Cu

Ni

10

5

0

CTRL

Zn

W

Cu
Ni
Sample name

CTRL

Zn

W

Cu
Ni
Sample name

CTRL

Sample name60

10
Ni (mg/kg-dry)

W (mg/kg-dry)

50
40
30
20

5

10

0

Zn

W
Cu
Ni
Sample name

0

CTRL

Fig.4 Zn, W, Cu, and Ni concentrations in Pinus densiflora in contaminated and non-contaminated soils.
Heavy Metal Concentrations in Pinus densiflora inContaminated and Non- contaminated Soils

densiflora absorbs a large amount of heavy metal insoils containing a large amount of heavy metal.
Moreover, it was found that Pinus densiflora
accumulate Zn and W.

Figure 4 shows Zn, W, Cu, and Ni concentrationsin Pinus densiflora in contaminated and noncontaminated soils.
Zn concentrations in Zn, W, Cu, Ni, and CTRL
were 37 to 140, 30 to 45, 29 to 45, 30 to 53, and 20 to
43 mg/kg-dry, respectively. W concentrations in Zn,
W, Cu, Ni, and CTRL were 9 to 40, 10 to 52, 10 to30, 9 to 20, and 7 to 20 mg/kg-dry, respectively.
Therefore, Zn concentrations in Zn and W
concentrations in W were higher than thoseconcentrations in other conditions. Cu concentrations
in Zn, W, Cu, Ni, and CTRL were 4 to 10, 4 to 7, 3 to10, 4 to 10, and 3 to 10 mg/kg-dry, respectively. Ni
concentrations in Zn, W, Cu, Ni, and CTRL were 4 to7, 4 to 7, 3 to 7, 3 to 7, and 3 to 7 mg/kg-dry,
respectively. Therefore, Cu and Ni concentrations
were almost the same as those concentrations in allconditions. Cu, Ni, Zn, and W concentrations in theloaded solutions were 2.5, 2.6, 860, and 33ppm. Zn
and W concentrations in the solutions were higher
than Cu and Ni concentrations in the solutions.
Therefore, it was thought that the heavy metals
concentrations in Pinus densiflora were influenced by
the difference of heavy metals concentrations in theloaded solutions.
From the above results, it was deemed that Pinus

Heavy Metals Concentrations in Leaves, Stems,
and Roots of Pinus densiflora
Figure 5 shows Zn, W, Cu, and Ni concentrationsin leaves, stems, and roots of Pinus densiflora.
Zn concentrations in leaves, stems, and roots ofZn were 37 to 50, 49 to 66, and 70 to 140 mg/kg-dry,
respectively. Zn concentrations in leaves, stems, androots of W were 30 to 40, 37 to 45, and 30 to 40
mg/kg-dry, respectively. Zn concentrations in leaves,stems, and roots of Cu were 29 to 34, 30 to 32, and 32
to 45 mg/kg-dry, respectively. Zn concentrations inleaves, stems, and roots of Ni were 30, 30, and 34 to
53 mg/kg-dry, respectively. Zn concentrations inleaves, stems, and roots of CTRL were 20 to 34, 33 to
38, and 40 to 43 mg/kg-dry, respectively. Therefore,roots Zn concentrations were higher than Znconcentrations in leaves and stems for Zn. Roots Zn
concentrations were almost the same as Zn
concentrations in leaves and stems for W, Cu, Ni, and
CTRL. It is known that fern accumulates large
amounts of Zn in its roots [2], [6-7]. Moreover, it isreported that Zn concentration in root of Pinus

429

SEE-Mie, Japan, Nov.10-12, 2022

Zn
Cu
CTRL

15

W
Ni

Zn

Cu (mg/kg-dry)Zn (mg/kg-dry)

150

100

50

60

W (mg/kg-dry)

50

leaves

Zn
Cu
CTRL

stems

Cu

Ni

CTRL

10

5

0

roots

leaves

stems

Zn

Cu

roots

10

W
Ni

Ni (mg/kg-dry)

0

W

40
30
20

W

Ni

CTRL

5

10
0

0

leaves

stems

roots

leaves

stems

roots

Fig.5 Zn, W, Cu, and Ni concentrations in leaves, stems, and roots of Pinus densiflora.
densiflora grown in heavy metal contaminated soil
was higher than those in leave and stem [4]. Therefore,
it was thought that Pinus densiflora can accumulate
large amounts of Zn in its roots. And then, Zn
concentrations in leaves, stems, and roots of Zn werehigher than those concentrations of W, Cu, Ni, and
CTRL. It is reported that Athyrium yokoscense(Franch. et Savat.) Christ and Clethra barbinervis
Sieb. et Zucc. which live in the contaminated area,
contain large amounts of Zn not only in their roots but
also in their leaves and stems [2], [8-9]. Therefore, it
was thought that Pinus densiflora also canaccumulate large amounts of Zn in its leaves andstems.
W concentrations in leaves, stems, and roots of Zn
were 9 to 20, 20 to 40, and 20 to 40 mg/kg-dry,
respectively. W concentrations in leaves, stems, androots of W were 10 to 30, 20 to 30, and 30 to 52
mg/kg-dry, respectively. W concentrations in leaves,stems, and roots of Cu were 10 to 20, 20 to 30, and 10
to 20 mg/kg-dry, respectively. W concentrations inleaves, stems, and roots of Ni were 10 to 20, 10 to 20,
and 9 to 10 mg/kg-dry, respectively. W
concentrations in leaves, stems, and roots of CTRL
were 9 to 20, 20, and 7 to 10 mg/kg-dry, respectively.
Therefore, roots W concentrations were higher thanthose in leaves and stems for W. Roots W
concentrations were almost the same as W
concentrations in leaves and stems for Zn, Cu, and Ni.
Roots W concentrations of CTRL were lower than W

concentrations in leaves and stems of CTRL.
Moreover, roots W concentrations of W were higher
than those of Zn, Cu,
Ni, and CTRL, but W
concentrations in leaves and stems of W were almost
the same as those of Zn, Cu, Ni, and CTRL. It isreported that W concentrations in roots of Italianryegrass grown in the nutrient solution containing
tungsten were higher than those in leaves and stems[10]. Therefore, it was thought that Pinus densifloraalso can accumulate large amounts of W in its roots.
In contrast, Cu concentrations in leaves, stems,
and roots of Zn were 4 to 6, 6 to 9, and 10 mg/kg-dry,
respectively. Cu concentrations in leaves, stems, androots of W were 4, 4 to 7, and 4 to 7 mg/kg-dry,
respectively. Cu concentrations in leaves, stems, androots of Cu were 3, 3 to 6, and 7 to 10 mg/kg-dry,
respectively. Cu concentrations in leaves, stems, androots of Ni were under the detection limit, 4, and 9 to
10 mg/kg-dry, respectively. Cu concentrations inleaves, stems, and roots of CTRL were 3, 3 to 6, and10 mg/kg-dry, respectively. Therefore, roots Cu
concentrations were almost the same as Cu
concentrations in stems and leaves for all conditions.
Ni concentrations in leaves, stems, and roots of Zn
were 6 to 7, 4 to 7, and 5 to 6 mg/kg-dry, respectively.
Ni concentrations in leaves, stems, and roots of W
were 4 to 7, 4 to 5, and 4 to 7 mg/kg-dry, respectively.
Ni concentrations in leaves, stems, and roots of Cu
were 3 to 6, 3 to 4, and 6 to 7 mg/kg-dry, respectively.
Ni concentrations in leaves, stems, and roots of Ni
430

SEE-Mie, Japan, Nov.10-12, 2022

were 3 to 4, 4, and 6 to 7 mg/kg-dry, respectively. Ni
concentrations in leaves, stems, and roots of CTRL
were 3 to 5, 3 to 4, and 4 to 7 mg/kg-dry, respectively.
Therefore, roots Ni concentrations were almost thesame as Ni concentrations in stems and leaves for all
conditions.
From the above results, it was found that Pinus
densiflora accumulated Zn and W in the roots and Zn
in the stems and leaves.

Proceedings of the Bryological Society of Japan,
Vol.5, No.4, 1990, pp.49-53.
[2] Honjo T., Heavy Metals and Indicator Plants Recovery of Natural Environment, Bulletin of
the Japan Sea Research Institute Kanazawa
University, No.30, 1999, pp.171-193.
[3] Hori K., Sakakibara M., and Sera K., Heavy Metal
Accumulation in Trees on an Abandoned Mine
Tailing in Southwestern Japan, NMCC Annual
Report, 19, 2012, pp.198-205.
[4] Kyung W.S., Yowhan S., Charles C.R., Nam J.N.,
Jin W.K., and Jeong-Gyu K., Seedling Growthand Heavy Metal Accumulation of Candidate
Woody Species for Revegetating Korean Mine
Spoils, Restoration Ecology, Vol.16, No.4, 2008,
pp.702-712.
[5] Honjo T., Studies on the Deposit of Heavy Metals
in Pinus densiflora Leaves from the Kanazawa
Castle Area, Kanazawa City, Ishikawa Prefecture,
The Journal of Phytogeography and Taxonomy,
Vol.XXVIII, No.2, 1980, pp.72–75.
[6] Nishioka H., Kodera H., Heavy metal content infern plants, Journal of Environmental
Conservation Engineering, Vol.34, No.4, 2005,
pp.301-305.
[7] Kubohara T. and Ii H., Zn and Fe Contamination
Index for River using River Insects and Water
Plants in The Kinokawa River Catchment,International Journal of GEOMATE, Vol.19,
Issue 75, 2020, pp.76-83.
[8] Morishita T. and Boratynski K. J., Accumulationof cadmium and other metals in organs of plants
growing around metal smelters in Japan, Soil
Science and Plant Nutrition, Vol.38, Issue 4,
1992, pp.781-785.
[9] Honjo T., http://kanazawa-sakurada.cocolognifty.com/blog/2009/06/2009626-9bd2.html[10] Yamada. H., Nishimura K., Hattori T, andTakahashi E., Uptakes of Molybdenum andTungsten by Italian Ryegrass, Japanese Journalof Soil Science and Plant Nutrition, Vol.60, Issue
5, 1989, pp.463-465.

CONCLUSIONS
Zn, W, Cu, and Ni concentrations in Pinus
densiflora and growth conditions (tree heights andappearances) were investigated to reveal the effectsof heavy metals on the growth and their accumulation
patterns in Pinus densiflora under different heavy
metal-contaminated soil conditions. At 4 weeks laterfrom the experiment start, the tree heights of Pinus
densiflora in Zn, W, Cu, Ni, and CTRL were almost
the same, and no appearance growth abnormalities
were observed. it was found that Pinus densiflora cangrow in Zn, W, Cu, and Ni contaminated soils. Zn
concentrations in the Zn load condition and W
concentrations in the W load condition were higher
than those concentrations in other experimental
conditions. Therefore, it was found that Pinus
densiflora accumulate Zn and W. Roots Zn
concentrations were higher than Zn concentrations inleaves and stems for the Zn load condition. W
concentrations in roots were higher than those inleaves and stems for the W load condition. Therefore,
it was found that Pinus densiflora can accumulate
large amounts of Zn and W in its roots. Moreover, Znconcentrations in leaves, stems, and roots of Zn loadcondition were higher than those of otherexperimental conditions. Therefore, it was found that
Pinus densiflora can also accumulate large amountsof Zn in its leaves and stems.
REFERENCES[1] S, “A “b” Scopelophila
cataractae and copper (1) - Distribution of
Scopelophila cataractae”,431

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ANALYSIS OF FLOOD FLOW RATE CALCULATE FROMPRECIPITATION AT TYPHOON NO.19 IN 2019 IN THE ABUKUMA
RIVER BASIN
Masanobu Taniguchi
Wakayama University
ABSTRACTP Recent year, Japan has big typhoons, So the cities occurred flood, the Cities in Abukuma River Basin isdamaged by the typhoon. The characteristic of flood runoff is not cleared. The Abukuma River is flooded by thetyphoon, a part of the region of the Nasugawa City, the Hongu City, the Marumori Town, the Date City and the
Hukushima City flooded. The Rain runoff calculation system is developed. The system can calculate the river
runoff converted by precipitation, the system has river structure database and the small basin distribution. The rain
runoff is calculated by Thiessen method at each rain observing station.
Keywords:Abukuma River, Typhoon, Flood, runoff, Flow rate

INTRODUCTIONOVERVIEW OF RESEARCH AREA

The Abukuma River Basin was called“Abaregawa” its mean often flooded by the Typhoonin past. The Abukuma River has flood in 2019 at
Typhoon No.19, some city were damaged by flood
condition. The National major road No.349 whichconnects Miyagi and Fukushima prefectures, wasbroken by the flood, and the tunnel was filled withriver and forest sediment. The Ministry of Land,
Infrastructure, Transport and Tourism has
rehabilitated the river to prevent flooding. The river
was researched by some researcher, Sabo &Landslide Technical Center has surveyed thedamaged from the typhoon. The Abukuma River
Basin is 6th length in Japan. Therefore, it is difficult
to clarify the flood phenomenon. The typhoon has
moved slowly, thus the flood is occurred in 2019. It
is necessary to analyze rain runoff quickly. The rain
runoff calculation system is developed. The research
objective is clear the relation between the
precipitation and the river flowrate, and to calculate
the river flows from the precipitation. The novelty ofthis study is to calculate the amount of runoff that
arrives from the flow velocity and the distance of theriver, and to predict the time when the rainfall water
will arrive.

N
Observing Station
Paddy
Orchard
ForestWaste Land
Building
Traffic
Other
River or Lake
Beach
Sea
Golf course
0

10

20

30

40km

Fig.1 Overview of Abukuma River Basin
Fig.1 shows overview of Abukuma River Basin.
The area in Abukuma River basin is 5,400 km². The
flow path extension of the Abukuma River is
239km.[5] The length is 2nd long in Tohoku Area inJapan. The population is about 1.78 million people in
the Basin. The Abukuma River has 17 cities inFukushima Prefecture, has five cities in Miyagi
Prefecture. The Abukuma River is originated at
Asahidake in South - East of Fukushima. The land useof 56% in whole basin is forest, 16% is paddy, 14%
is orchard, and 6% is building. The water of theInawashiro lake inflows in the upper stream of
Abukuma River Basin shown in arrow in figure. The
sending water is mainly used for paddy.

432

SEE-Mie, Japan, Nov.10-12, 2022

THE METHODRUNOFFOF

CALCULETE

curved not straight, and location information isrequired to know the distance accurately. The rain
runoff analyze system can calculate by location dataof longitude and latitude. The runoff rate can becalculated by amount of rainfall per second calculated
by precipitation and area, as the flow rate is per
second. The calculation is performed from the
upstream first, and the calculation is performed to thedownstream. The amount of water reached is
calculated by multiplying the amount of runoff by thecoefficient obtained by the approximate formula.
First type of method has one storage, next one has has
two storages to reflect the value at the next time. And
the third type of method is to calculate the runoff at
higher speeds more accurately.

RAIN

Calculation method in Small Basin (method No.1)
Precipitation

3

Precipitation

Small Basin

Storage(S)Flow out to Parent upper tank(next 1hour late )River runoff

1

Tank

Runoff(R)2

distance (D)(km)

Runoff rate
( <=1)(km/h)

Calculation method in Small Basin (method No.2)
Precipitation
2
Small Basin
Flow out to Parent upper tank(next 1hour late )Lower Tank

Runoff(R)StorageFig 4. The overview of water flow.
Figure 4 shows overview of water flow.

Storage(S)1Upper Tank

3

distance (D)(km)

Runoff rate
( <=1)(km/h)

Calculation method in Small Basin (method No.3)
Precipitation
2
Small Basin
Flow out to Parent upper tank(next 1hour late )Runoff(R)
4down

3down

Storage

Storage(S)Lower Tank

1

Upper Tank

3

2down
1down

distance (D)(km)

Runoff rate
( <=1)(km/h)

Fig.2 Method of calculation of rain runoff

Figure 2 shows the method of 3 types ofcalculation of rain runoff. The system has the river
structure database, the river basin location data, river
channel data, so the distance from upstream can becalculated. The distance is very important data tocalculate the time of flood condition. The flow path isFig. 5. The method of amount of rain runoff
calculate by precipitation

Figure 5 shows the method of amount of rain runoff
calculate by precipitation. There are 49 precipitation
433

SEE-Mie, Japan, Nov.10-12, 2022

amount of rain runoff as “S” (m3/sec). The “a” and“b” are coefficients. The rain water runoff velocity is
calculated by multiplying the power of “S” to “b” by“a”. Next the runoff ratio is calculated by dividing the
distance by the runoff velocity shown as formula (2).
The runoff ratio is calculated by the distance andvelocity of the river. Moreover the amount of runoff
is calculated by multiplying the runoff ratio by theamount of runoff shown as formula (3).

stations in the Abukuma River basin. As, the data of
precipitation is point data, the data need to calculated
for each with small river basins. The point data is
distributed by the Thiessen method. The amount ofrain runoff is divided by the small basins, andcollected by the rivers. The calculation of runoff
needs to know relation between the basins.

River structure database

Level 0 1 2 3 4 5 6 7 8 9 10 11 12…

𝑣 = 𝑎𝑆 𝑏

Abukuma River Basin
Max level 69(1)

𝐷

downstream

𝑓 = 𝑣 (𝑓 <=1)

(2)

𝑅 = 𝑓𝑆(3)Using this formula, the flow rate can be predictedfrom the amount of precipitation.

upstream

Fig.6. the small river basin structure database
RESULT OF RAIN RUNOFF DISTRIBUTION
Figure 6 shows the small river basin structure
database. The rain runoff is collected by the river, theflow rate is calculated by each one hour time. The
Abukuma River Basin has 543 places of the small
basins. The max level of small basin is 69, thecalculation of rain runoff is started from upper stream.
The small basin has certainly one of river flow pass.
COMPARISONOFOBSERVEDCALCULATED VALUES

AND

8

4

7

3.5

6

3

5

2.5

4

2

3

1.5

2

1

1

0.5

0

0
0

5000

10000

15000

20000

Y=0.05x^0.35
Y=0.1x^0.3
Y=0.01x^0.6

40000
Rain runoff
Motomiya
YahataShirakawa
Ejiri
Tateyama
Akutsu

10/16

10/15

10/14

10/13

0

10/12

10000

Y=0.05x^0.45
Y=0.1x^0.4
Y=0.01x^0.5

0

1000

2000

Y=0.05x^0.35
Y=0.1x^0.3
Y=0.01x^0.6

3000

4000

5000

Y=0.05x^0.45
Y=0.1x^0.4
Y=0.01x^0.5

Fig 8. Approximate line between amount of rain
runoff (m3/sec) and velocity (km/hour)
10/18

20000

10/17

30000

2019/10/11

runoff (m3/sec)

50000

Figure 8 shows the approximate line between
amount of rain runoff and velocity. It is important toconsider velocity in order to estimate the amount ofwater that will reach the downstream basin after one
hour. Generally, when the amount of rain is heavy,
the flow velocity tends to be high. However thevelocity is unknown in flood condition, the velocity
is estimated by some the approximate lines.

Fig 7. Time series of flow rate in the Abukuma
river Basin at typhoon No.19 in 2019
Figure 7 shows the time series of flow rate in the
Abukuma river Basin at typhoon No.19 in 2019. The
max value of rain runoff is 43050m3/sec, sum ofamount of rain runoff from October 11 to 18 is1,494,241,200m3. The sum of water volume at Ejiri
the lowest observing station is 1,044,104,400m3.

RAIN RUNOFF CALCULATION
The distance of river pass is calculated by theLongitude latitude. The runoff velocity is showed byfollow formula (1). The velocity is calculated by434

SEE-Mie, Japan, Nov.10-12, 2022

10/12 21：00

10/13 13：00

10/14 21：00

5000m3/sec
20000

Flood occurred

10/18

10/17

10/16

10/15

10/14

10/13

10/12

10000

0

Peak of raining

Motomiya
YahataEjiri
Tateyama
288
128
110
86

2019/10/11

runoff (m3/sec)

0m3/sec

Fig 12. The time series of water runoff (No.2)

a 0.1 b 0.2(method No.1)

Fig 9. The result of rain runoff distribution(No.1)

Figure 12 shows the time series of water runoff
calculated by the method No.2. The peak of rainwaterrunoff is not sharp. The water flow is determined by
the small basin, and it was estimated that Small basinsneed to be skipped.

Figure 9 shows the result of rain runoff distribution
calculated by the method No.1. In the formula,
Coefficient “a” was used 0.1, and “b” was 0.2.
The max of rain runoff is showed over 5000m3/sec
by red color. The peak of typhoon raining is October
12 21:00 in whole area. At October 13 13:00, theflooding in some area is occurred. As the flood is
occurred, the result of lower stream of rain runoff wasdifferent value from observed flow rate. The No.1
method is the small basin has one tank, same time ofwater storage is include the upper stream of waterrunoff value, as the value is calculated from upperstream. The problem of the method is seemed to
calculate higher value.

10/12 21：00

10/13 13：00

Peak of raining

10/14 21：00

Flood occured

a 0.01 b 0.55(method No.3)

Fig 13. The result of rain runoff distribution(No.3)
10/12 21：00

10/13 13：00

10/14 21：00

Figure 13 shows the time series of water runoff
calculated by the method No.3. The flow velocity fits
well with the following coefficients. In the formula,
Coefficient “a” was used 0.01, and “b” was 0.55. If
the small basin is skipped, the water does not flow inthe small basin. As the river flow is wave, it was
assumed the rain runoff was triangle wave. However
the calculation occurred noise.
Flood occured

a 0.05 b 0.35(method No.2)

Fig 11. The result of rain runoff distribution(No.2)
runoff (m3/sec)

20000

Figure 11 shows the result of rain runoff
distribution calculated by the method No.2. In theformula, Coefficient “a” was used 0.05, and “b” was
0.35. The No.2 method has two tanks, so upper streamof amount of water runoff is calculated one hour after.
It is estimated to calculate water runoff was
accurately, however the channel distance of the small
basin is shorter than the calculated velocity. As aresult, the calculated rain runoff was slower than theactual flow rate. Since the tanks are separated, themaximum value is also determined, and water isflowing in order.

10000
86
Ejiri

0

2019/10/1
10/2
10/3
10/4
10/5
10/6
10/7
10/8
10/9
10/10
10/11
10/12
10/13
10/14
10/15
10/16
10/17
10/18
10/19
10/20
10/21
10/22
10/23
10/24
10/25
10/26
10/27
10/28
10/29
10/30
10/31
2019/11/1

Peak of raining

Fig 14. The time series of water runoff (No.3)
Figure 12 shows the time series of water runoff
calculated by the method No.3. The peak time isseemed same time, and the shape of the peak is very
similar.

435

SEE-Mie, Japan, Nov.10-12, 2022

Water quality and nutrient loads in the abukuma
watershed under normal flow condition, Water
Engineering paper, vol. 51, February 2007(inJapanese)[3] Ralia,https://www.wakayamau.ac.jp/~masa/profile/soft/index.html, 2018.
[4] Ministry of Land, Infrastructure and Transport,
Japan, Water information system, http://www1.
river.go.jp/[5] Digitalnational
land
information,
http://nlftp.mlit.go.jp/ksj/
Japan Meteorological Agency, http://www.jma.
go.jp/jma/index.html[6] Kazuyuki Mizumura, Hydrosphere hydrology,
1998.
[7] Isamu Kayane, Hydrology, Daimeido 1980.

CONCLUSIONS
The rain runoff analysis system is developed. The
Abukuma Basin was flooding in 2019. The rain
runoff was calculated, some method of calculation
was tried. The peak time of the calculated amount ofrain runoff is seemed same time to observed flow rate,
and the shape of the peak is very similar in the method
No.3. However the calculated rain runoff has noise,and the system is need to improve.
REFERENCES[1] Tokuo KISHII, On the Flood Disaster in the
Abukuma River Basin at the End of August 1998,
Natural Disaster Research Report of the National
Research Institute for Earth Science and Disaster
Resilience 37 , pp. 91-105, 2001.
[2] Tsuyoshi KINOUCHI and Katumi MUSIAKE,436

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ANALYSIS OF SEASONAL AND SECULAR VARIATIONS IN
DISSOLVED OXYGEN CONCENTRATION AT THE BOTTOM OF
LAKE BIWA, JAPANJinichi Koue1,21

Graduate school of Maritime Sciences, Kobe University, Japan; 2Graduate School of Engineering, Osaka
University, Japan

ABSTRACT
Lake Biwa in Japan is a water resource utilized by approximately 14 million people in Kansai region, and its
water pollution has a significant impact not only on people but also on the ecosystem, particularly in the bottom
layer, where hypoxia can cause an environmental problem. Until the 1980s, eutrophication was the main cause ofhypoxia of the lake bottom, and after the measures for eutrophication, it is not clear what the main cause
quantitatively is such as the climate change and a regime shift in the ecosystem. In the present study, seasonal andsecular variations of water quality in Lake Biwa over the past 30 years were analyzed by using vertical profile dataof water temperature and dissolved oxygen concentration observed by Lake Biwa Environmental ResearchInstitute in Shiga Prefecture at the deepest point of fixed-point observation and weather data at Hikone Local
Meteorological Observatory. The results of the analysis showed that intensity of stratification increased in thesurface layer of Lake Biwa, but conversely stratification weakened in the deeper layers. These changes in thephysical environment of the lake have affected the decline of dissolved oxygen in the lake bottom of Lake Biwa.
The seasonal changes in dissolved oxygen over 30 years could be classified into approximately three patterns, withthe dominant factors being the strengthening of stratification due to the change in air temperature and wind speed,
the shortening of the period of the overturning and the vertical mixing by wind during stratified season and cooling
period.
Keywords: Dissolved Oxygen, Climate change, Overturning, Lake Biwa
INTRODUCTION

is divided into northern part and southern part of thelake based on its shape, with an average depth of 43
m in northern part and 4 m in southern part. The total
volume of Lake Biwa is approximately 27.5 billion
m3. The annual water inflow is about 5 billion m3, andthe average residence time is 5.5 years in North Lakeand approximately 15 days in South Lake.
Hypoxia in the bottom layer of the northern partof Lake Biwa became pronounced around the 1960s,
and it has been pointed out that the cause of thehypoxia in Lake Biwa is an increase in organic matterin the surface water layer due to eutrophication andsedimentation into the deep layer. There is concernthat anoxia of the bottom layer may affect the habitatof the ecosystem living in the bottom layer, leading towater pollution in Lake Biwa. The concentration ofdissolved oxygen of 2 mg/l or less in the bottom layer(90 m) in Imazu-Oki has been observed in some years
since 1979. The concentration of 2 mg/l has
significance as a value at which the basic metabolismof organisms declines. For example, in Lake Ikeda,
the overturning (whole-layer circulation) did notoccur every year, but partial circulation prevailed, anddissolved oxygen in the deep layer continued todecrease, becoming nearly anoxic in recent years [1].
In the case of Lake Biwa, it is necessary to pay

Water contains a variety of substances, includingorganic matter, minerals, and microorganisms, andphysical, biological, and chemical reactions
constantly occur. In rivers, there is a time span
between the time the water originates at the source
and the time it flows out to the sea, but that time spanis only a few days. Therefore, as the water quality inthe river changes, these physical, biological, andchemical reactions in rivers brought about lesssignificant problem than in lakes and marshes.
However, in lakes, once the water flows into the lake,water stays in the closed water body for a long periodof time. During the residence process, physical,
biological, and chemical reactions such as heatexchange with the atmosphere and elution of nutrientsfrom the bottom sediment proceed, and hypoxia,
eutrophication, and other visible changes in water
quality eventually occur.
Lake Biwa is the largest freshwater lake in Japan.
The lake has an area of approximately 674 km2 (616
km2 in the north and 58 km2 in the south), a maximum
depth of 103.6 m, a length of approximately 63.5 km
from north to south, a maximum width of 22.8 km anda minimum width of 1.35 km (Figure 1). Lake Biwa
437

SEE-Mie, Japan, Nov.10-12, 2022

attention to future trends. However, even after the
1980s, when organic substances and nutrient loads
from the land area were regulated, the dissolved
oxygen concentration in the bottom layer of Lake
Biwa remained below 2 mg/L. This is attributed toclimate change around Lake Biwa in recent years([2],[3]). Woolway stated that changes instratification due to climate change have a significant
impact on the hypoxia of the bottom layer in lakes
worldwide. In particular, they reported that theincrease in air temperature and decrease in windspeed may weaken vertical mixing of lake water andcause a decrease in dissolved oxygen concentration.
The effect of wind speed, precipitation, andinflows on stratification in relation to warm and cold
weather was significant especially when observed
climate patterns were expected to have effects onthermal characteristics [4]. For example, the global
warming has reduced snowfall mainly in the northernbasin of Lake Biwa, and that the amount of snowmelt
water, which is colder and richer in oxygen than lakewater during the snowmelt season, may be flowing
into the bottom layer along the lake bottom. However,no such phenomenon of snowmelt water flowing
along the lake bottom was observed, and studies of
the relationship between the size of snowmelt runoff
and the minimum annual dissolved oxygen level
showed no effect. Vertical mixing by wind causes
various phenomena such as blowdown flow anddestruction of stratification by vertical mixing whenwind blows. In addition, wind causes internal waves,and the breaking of these waves results in active
mixing of the lake water. Wind-driven wind, verticalmixing, and internal waves have been observed bycontinuously monitoring the vertical distribution ofwater temperature using a mooring system [5].
Among these, wind influences on the deep-waterlayer are vertical mixing and internal waves causedby strong winds. They showed that vertical mixing is
caused by the passage of such waves (internal surge)
in Lake Biwa during summer. However, the seasonaland secular changes in dissolved oxygen at all depths
due to strong winds and internal waves have not yet
been fully investigated. In this study, environmental
changes in Lake Biwa were investigated from thephysical aspect using data from a fixed point in thenorthern part of Lake Biwa.

Shiga Prefecture at the monitoring point of Imazu-oki(Fig. 1) (water depth: approximately 90 m). This
periodic survey has been conducted since 1979. This
monitoring point is the deepest point among the fixed
points of the periodic surveys conducted on amultidecadal scale. The depths are 0.5 m, 5 m, 10 m,
15 m, 20 m, 30 m, 40 m, 60 m, 80 m, and 1 m justabove the lake bottom (approximately 90 m). (Water
temperature, dissolved oxygen concentration, anddepth were measured in the field using a
HYDOROLAB water quality sensor (Quanta). Air
temperature, wind speed, wind direction, andprecipitation were observed at Hikone District
Meteorological Observatory (every 3 hours (onlyprecipitation is a daily average)). The height from theground of the thermometer, which observed airtemperature, is 1.5 m. The height from the ground of
the anemometer, which observed wind speed anddirection, is 17 m. The minimum unit of water and airtemperature, wind speed and precipitation are 0.1°C,
0.1 m/s and 0.1 mm respectively. The wind direction
was observed in 16 directions. The stratification
strength is estimated by the difference in watertemperature between the surface layer (5 m) and thebottom layer (90 m). The surface layer is not at a
depth of 0.5 m, where water temperature is likely tochange due to wind mixing, but at a depth of 5 m
below the surface layer, while the bottom layer is at a
depth of 90 m. SSI (Schmidt stability index (kgm/m2)
was estimated in order to calculate the strength ofstratification as follows.
1

𝑧

0

0

𝑆𝑆𝐼 = 𝐴 ∫𝑧 𝑚 𝐴𝑧 (𝑧 − 𝑧𝑔 )(𝜌𝑧 − 𝜌𝑔 )𝑑𝑧𝑧𝑚
𝑧𝑔 = 𝑧𝑚∫ 𝐴𝑧 𝜌𝑧 𝑧𝑑𝑧∫𝑧 𝐴𝑧 𝜌𝑧 𝑑𝑧 𝑧0
1

0

0

𝑊𝑆𝐼

𝑉𝑀𝐼 =
𝑆𝑆𝐼
𝑊𝑆𝐼 = 𝜅 × |𝜏|𝜏 = ρ𝑎 C𝐷 ⌊𝑈𝑎 ⌋𝑈𝑎

(1)
(2)
(3)
(4)
(5)

where A0 is surface area of lake (m2), z is depth (m),zm is maximum depth (m), z0 is water surface depth(m), Az is area at depth z (m2), z is density at depth z(kg/m3), g is density at depth zg (kg/m3), V is lakevolume (m3), and zg is depth to the center of gravity
of stratified lake (m). In this study, the density wascalculated as a function of only water temperature.
Vertical mixing index (VMI) indicates the parameterof expressing the proportion of the wind stress on thestratification. 𝜅 is the constant of 1.0. Wind stressindex was calculated in order to evaluate theinfluence of the strong wind on the stratification. 𝜏 is
the wind stress, ρ𝑎 is the air density above the lake
surface (1.2255 kg/m3), 𝑈𝑎 indicates the atmosphericwind speed at a height of 17 m above the lake surface,
Cd represents the drag coefficient of lake surface,which performs the momentum transfer efficiency
between atmosphere and lake, and is dependent on
wind speed, currents, waves, lake surface roughness,

DATA ANALYSISThe analysis used data on water temperature anddissolved oxygen concentration obtained fromperiodic surveys (once or twice a month) conductedby Lake Biwa Environmental Research Institute in
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SEE-Mie, Japan, Nov.10-12, 2022

and stability amongst other factors.
Frequency analysis was used to determine
whether a particular period of wind prevailed.

in the 1990s, while C-pattern was observed after 1990
in all but one case.
Fig. 2 shows the averaged seasonal changes in DO
for each pattern. Fig. 3, 4, 5 shows the secular change
of SSI, VMI, period of overturning from 1980 to 2009.
SSI of average of A-pattern was 197.93 and 7 higher
than that of B and C-pattern. The strength ofstratification in A-pattern was higher than that of B
and C-pattern. The decreasing rate of DO was
influenced by the strength of stratification. From Fig.
4, VMI of A-pattern was 6.98×10-5 and 4.42×10-6
lower than B-pattern, and 5.67×10-6 lower than Cpattern. Considering the effect of the wind stress, thecorrelation coefficient between VMI and decreasingrate of DO was 0.54, therefore the contribution of thewind stress to the vertical mixing plays an importantrole in the change of DO. As for A-pattern, thevertical mixing due to the wind stress less occurredcompared with B, C-pattern. DO tended to decreaseduring the period of stratification due to theconsumption of DO by bacteria under the thermocline.
From the perspective of the amount of precipitation,
the correlation between precipitation and decreasingrate of DO was rather low (Fig. 5). Fig.6 shows thesecular change of period of overturning from 1980 to
2009. The correlation coefficient of the period of
overturning and decreasing rate of DO was 0.54,
hence as the period of overturning decreased, thedecreasing rate of DO increased. The vertical mixing
in winter occurred efficiently, DO in lake was enoughin all layers, and hypoxia in the bottom of the layer
less likely happened as in the case of B-pattern.

Imazu-oki

HikoneFig.1 Monitoring point for each data in Lake Biwa
RESULTS AND DISCUSSIONS
Factors of the seasonal change of dissolved oxygen
over 30 years

DO(mg/l)DO (mg/l)

Seasonal changes in dissolved oxygen (DO) in thebottom layer (90 m depth) in the monitoring point of
Imazu-oki over the past 30 years could be 14
approximately classified into three patterns (Fig. 2). . 12
14Firstly, in A-pattern, DO began to decrease with the 10
12
onset of stratification, reached a minimum around 8
average A-pattern
10
average B-pattern
October, and then recovered somewhat before the 6
average C-pattern
84
overturning occurred. In this case, the minimum DO
A-average
6
B-average
was often around 2 mg/l. On the other hand, in B- 2
C-average
pattern, DO gradually decreased and maintained a 0 1/1 2/1 3/4 4/44 5/5 6/5 7/6 8/6 9/6 10/711/712/8 1/8 2/8 3/11
Date
2
value higher than the minimum DO in A-pattern0
before the overturning. In C-pattern, the decrease in
1/1 2/1 3/4 4/4 5/5 6/5 7/6 8/6 9/6 10/7 11/7 12/8 1/8 2/8 3/11
DO continued until around December, but thedateminimum DO was 2-4 mg/l at most. The rate ofdecrease in DO was greatest in A-pattern, andFig.2 Average of seasonal change of DO over 30 years
decreased in the order of C-pattern and B-pattern.
Table 1 Three types of classification based on the shape of seasonal changes
in DO concentration over 30 years (A-pattern 11 times, B-pattern 11 times)
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 20091980-1989

A-pattern

1990-1999

B-pattern

2000-2009

C-pattern

Seasonal changes in DO over the past 30 years canbe divided into these three patterns: A-pattern 11
times, B-pattern 11 times, and C-pattern 8 times(Table 1). A-pattern was most frequently observed in
the late 1980s and 2000s, with only two cases in the
1990s (1996 and 1999). B-pattern was more common
439

SEE-Mie, Japan, Nov.10-12, 2022

Recovery of DO in the case of A-pattern
0.6699 kgm/m2year

A-pattern
B-pattern
C-pattern

200
150
100
1980

1985

1990

1995
Year

2000

2005

2010

0.000120.00010.00008
0.00006
0.00004
0.000020
1980

A-pattern
B-pattern
C-pattern

3E-08 (1/s2year)

1985

1990

1995
Year

2000

2005

2010

7
6
5
4
3
2
1
0
1980

A-pattern
B-pattern
C-pattern-0.0269 mm/day year

1985

1990

1995
Year

2000

2005

2010

80
70
60
50
40
30
20
10
0
1980

0.2943 day/year0

A-pattern

0.00005

0.0001
VMI (1/s2)

0.000150.0002

Fig. 7 The relationship between recovery of DO andVMI in A-pattern

B-pattern
C-pattern

1985

1990

1995
Year

2000

2005

2010

The trend of secular change of DO
Fig. 8 shows the secular change of difference of
DO between 90m and each depth from 1980 to 2009.
Difference in DO between 90m and each depth was
determined by annual moving average. Difference in
DO between the bottom layer and each layer (fromthe surface layer (0.5 m) to the deep layer (20-60 m))
became larger as time passed.

Fig. 6 Secular change of period of overturning from1980 to 200911
0.5-90m 0.028℃/year

9
5-90m 0.028℃/year8

10-90m 0.027℃/year

76

15-90m 0.0084℃/year

54

20-90m -0.016℃/year

3

2009

2008

2007

2006

2005

2004

2003

2002

1998

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1985

60-90m -0.012℃/year
80-90m -0.0057℃/year

1984

0

1983

1

1982

30-90m -0.026℃/year
40-90m -0.017℃/year

1981

2

1980

Difference of water temperature (℃)

10

1997

Period of overturnig(day)

Fig. 5 Secular change of precipitation from thestarting day of overturning to the day of minimum DO
for 30 years

4
3.5
3
2.5
2
1.5
1
0.5
0

2001

Precipitation (mm/day)Fig. 4 Secular change of VMI from the starting day ofoverturning to the day of minimum DO for 30 years

2000

VMI (1/s2)

Fig. 3 Secular change of average SSI from the starting
day of overturning to the day of minimum DO for 30
years

As for the case of A and C-pattern, DO decreased
more than B-pattern. Only in the case of A-pattern,
DO recovered slightly right before the overturning
period. Fig. 7 shows the relationship between
recovery of DO and VMI in A-pattern. The
correlation coefficient of VMI and the amount of
average recovery value of DO in A-pattern was 0.41.
The amount of recovery value of DO was calculatedby the averaging the values from the day of theminimum DO to the day right before the overturning.
During the period of recovery in DO, as thestratification weakened and the strong wind blew, thevertical mixing between 80 m layer and 90 m layer
more likely occurred. Minimum DO remained greaterfor B-pattern and C-pattern than for A-pattern.
Therefore, the strong wind lead to the vertical mixing
in the bottom layer, which supplied with the DO fromthe just above the bottom layer.
Recovery of DO (mg/l)

250

1999

SSI (kgm/m2)

300

Year

Fig. 8 Secular change of difference of DO between 90 m and each depth from 1980 to 2009
440

0.5m-90m
5m-90m
10m-90m
15m-90m
20m-90m
30m-90m
40m-90m
60m-90m
80m-90m

SEE-Mie, Japan, Nov.10-12, 2022

0.5-90 m 0.012mg/l・year

Difference of DO (mg/L)

20-90 m 0.017mg/l・year

5-9 0m 0.0090mg/l・year
30-90m 0.015mg/l・year

4.4
4.2
4
3.8
3.6
3.4
3.2
3
2.8
2.6
2.4
2.2
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

10-90m 0.014mg/l・year
40-90m 0.018mg/l・year

15-90m 0.018mg/l・year
60-90m 0.013mg/l・year

0.5m-90m
5m-90m
10m-90m
15m-90m
20m-90m
30m-90m

40m-90m
60m-90m
80m-90m

80-90m -0.015mg/l・yr

YearPower spectrum (m2/s)

Fig. 9 Secular change of difference of water temperature between 90 m and each depth from 1980 to 2009
Fig.10 demonstrates the secular change of power
Difference in DO between 90 m and 80 m layer
spectrumof wind speed from April to December overbecame less from 1980 to 2009, which means that the30years.
The power spectrum shows a relatively
bottom layer from 80 m to 90 m became theweak trend in the 1980s and 2000s and a strong trend
homogeneous layer, taking into account that thein the 1990s. This trend was consistent with the fact
difference of water temperature between 90 m and 80
that B and C-patterns were more frequent in the 1990s
m was not so large (From Fig.9). The increase ofand A-pattern were more frequent in the 1980s andwater temperature in the surface layer was closely
2000s. Seasonal change of DO in 1990, 1992, 1994,
related to the increase in air temperature during theand 1998 were classified as B-patterns, in those years,
stratification period. The air temperature at Hikone
24-hour period power spectra of wind speed wereincreased by about 1.3°C as a linear trend over thelarge. Seasonal change of DO in 1987 and 2008 were
past 30 years. On the other hand, it was reported thatclassified as A-pattern, and 1980, 1991, 1993, 2000,
water temperature at the lake bottom was highlyand 2005 as C-pattern, and their power spectra werecorrelated with the air temperature in winter when therelatively small. The periodic strong wind speed
overturning (whole-layer circulation) occurred.
influenced seasonal change of DO over 30 years.
The difference in the trend of the increase inwater temperature by depth showed an interesting
0.5
A-patternfeature in the temporal variation of the difference
B-pattern
0.45
between the water temperature in each layer and that
C-pattern
0.4
at the bottom of the lake. The difference between the
0.35
water temperature at the surface and that at the bottomof the lake increased with depth from the surface to
0.3
1980
1985
1990
1995
2000
2005
2010
15 m, while the difference decreased at depths deeperYearthan 20 m. This means that the stratification was
Fig.10 demonstrates the secular change of power
enhanced in the entire lake, while the stratification
spectrum of wind speed from April to December over
was weakened at depths deeper than the thermocline
30 yearsin summer (this is irrelevant in winter, when the watertemperature was uniform).
The trend of water temperature uniformity in the
CONCLUSIONS
stratified layer is considered to be related to theincrease in wind intensity. The annual mean wind
Seasonal and secular changes of water quality inspeed at Hikone showed an increasing trend withLake
Biwa over the past 30 years were examined
time, increasing by 0.29 m/s over 30 years (10%) as a
using
data
of water temperature and dissolved oxygen
linear trend. It is possible that the mixing of the deep
concentration
observed by Lake Biwa Environmental
water layer associated with enhanced winds caused
Research
Instituteand data of air temperature, wind
the uniformity of water temperature. Anotherspeed,
andprecipitationfrom Hikone Local Weather
possibility is that the vertical mixing at the beginning
Station.
of stratification has been enhanced in recent years. In
DO increased with time, except at depths of 80
other words, it is reasonable to assume that theand90m for 30 years. The increase in DO wasconditions below the thermocline were not due toinversely
correlated with the increase in water
stratification period but were due to non-(weakly)
temperature.
The reason for the increase in DO in
stratified conditions (overturning period).
contrast to the increase in water temperature from 0.5
441

SEE-Mie, Japan, Nov.10-12, 2022

m to 15 m was unknown, but the increase inphytoplankton near the surface could have an effect.
The decreasing rate in DO at 80 m depth was larger
than that at 90 m depth. Therefore, in the bottom layer
the DO concentration tended to decrease over 30
years.
Seasonal changes in DO at the lake bottom
varied from year to year, but could be roughlyclassified into three patterns. A-pattern showed anearlier decrease in DO during the period ofstratification than B and C-patterns, and a further
decrease than the minimum of the B and C-patterns.
In B-pattern, the decrease in DO during thestratification period was slower and the minimum
value remained higher than in A-pattern, and thenrecovered during the overturning period. In C-pattern,
DO decreased more slowly than in A-pattern andrecovered earlier than in B-pattern. The minimum DO
was higher than in A-pattern and DO rarely recovered
before the overturning.
VMI (the average of the period from the start ofthe overturning to the lowest DO date) showed acorresponding relationship with the three patterns.
The strength of stratification in A-pattern wasstronger than the average of B-pattern except in 1982,
1996, and 2009, that of B-pattern was weaker than the
average of A-pattern except in 1994 and 1998, andthat of C-pattern was weaker than the average of Apattern except in 1980, 1993, and 1995. The strengthof stratification of the C-pattern was higher than thatof the B-pattern except in 1980, 1993, and 1995. The
strength of stratification mainly depends on the windstress and air temperature.
The period of overturning was also related to thethree patterns. In most cases, the short period of
overturning corresponded to A-pattern, while the long
period of overturning corresponded to B and Cpattern. For example, the A-pattern had a longer
stratification period than the B-pattern. The
overturning of A-pattern (except for 1984 and 1996)
were shorter than those of B and C-pattern, while
those of B-pattern (except for 1983, 1992, and 1997)
tended to be longer.
Another factor controlling the pattern ofseasonal changes in DO was the strong wind in the
period of strong and weak stratification, and thesecular variation of wind velocity over a 24-hourcycle. As for the recovery of DO in A-pattern inautumn, the strong wind such as typhoon played an
important role in the vertical mixing in the bottom
layer (80 m and 90 m) according to the calculation of
VMI. On the other hand, the most prominent windsystem in Lake Biwa during the period ofstratification is the lake breeze, which is the mostdominant wind system during this period. The secularvariation of the power spectrum of wind speed
showed a relatively weak trend in the 1980s and2000s and a strong trend in the 1990s. This trend wasconsistent with the fact that B and C-pattern weremore frequent in the 1990s, and A-pattern were more
frequent in the 1980s and 2000s. In other words, thevertical mixing was relatively strong in the 1990s,
when winds of this period were strong, and B-patterns
were more likely to appear, while mixing was weakerin the 1980s and 2000s, when A and C-patterns weremore likely to appear. the secular change of the 24hour cycle of the lake breeze appeared to beconsistent with DO pattern.
In this study, environmental changes in Lake Biwa
were investigated from the physical aspect using datafrom a fixed point in the northern part of Lake Biwa.
In order to examine changes of water quality in Lake
Biwa as a whole in more detail, it will be necessary to
study them in combination with model experiments
as we developed [3]. In addition, changes in DO could
be examined from a biochemical point of view, and acomplex study that includes the physical environmentis a major issue for the future.
REFERENCES[1] Ito Y., Momii K., Impacts of regional warming
on long-term hypolimnetic anoxia and dissolved
oxygen concentration in a deep lake,
HYDROLOGICAL PROCESSES 29(9) 22322242[2] Kumagai, M., Vincent, W.F., Ishikawa, K., andAota, Y, Lessons from Lake Biwa and other
Asian lakes: Global and local perspectives, inFreshwater Management (eds. M. Kumagai, W.F.
Vincent), Springer, Tokyo, 2003, pp.1-23.
[3] Koue J., Shimadera H., Matsuo T., Kondo A.,
Numerical Analysis of Sensitivity of Structure of
the Stratification in Lake Biwa, Japan bychanging Meteorological elements, Water, Vol.
10, 2018,1492.
[4] R. Iestyn Woolway., Sapna Sharma., Gesa A.
Weyhenmeyer., Andrey Debolskiy., Malgorzata
Golub, and Eleanor Jennings, Phenological shifts
in lake stratification under climate change. Nature
Communications volume 12, 2021, 2318.
[5] Stetler, J. T., S. Girdner, J. Mack, L. A. Winslow,
T. H. Leach, and K. C. Rose. 2021. Atmosphericstilling and warming air temperatures drive longterm changes in lake stratification in a large
oligotrophic lake. Limnol. Oceanogr. 66: 954–
964.
[6] Saggio A. and Imberger J., ”Internal wave
weather in a stratified lake.”, Limnology andOceanography, Vol.43, 1998, pp.1780-1795.

442

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

GREEN PROCESS FOR CRUDE PALM OIL BIODIESELPRODUCTION USING COMMERCIAL LIPASE ENZYMEMallika Tapanwong1, Rayakorn Nokkaew2, Pinsuda Viravathana3 and Vittaya Punsuvon4*Faculty of Science, Kasetsart University, Thailand; 2,3,4Center of Excellence-Oil Palm Kasetsart University,
Thailand

1,3,4

ABSTRACT
Antioxidants such as carotene about 500-700 ppm and vitamin E (tocopherol and tocotrienol) about 600-1,000
ppm are abundant in crude palm oil (CPO). Those antioxidants have many beneficial effects to human healthincluding enhancement of immune and reduction of the risk degenerative diseases such as cancer andcardiovascular diseases. Thus, the extraction of antioxidants from oil is interesting. Because oil, carotene andtocols are non-polar substances, they are good solubility with each other. One separation method is transforming
CPO to biodiesel and then separating biodiesel out of the antioxidants, called as palm phytonutrients, by biodiesel
distillation. The keys of this method are producing highly biodiesel yield while keeping the minimum
destructiveness on palm phytonutrients. In this research, the enzymatic transesterification with commercial lipase
was carried out. The 2-levels factorial design was performed to evaluate four parameters including enzyme amount,methanol molar ratio, water amount, and operation time, on fatty acid methyl ester (FAME), free fatty acid (FFA),
carotene content, tocopherol and tocotrienol content. The ANOVA reported that enzyme amount was significant
to all responses except FAME while the effect of methanol molar ratio was significant on FFA and tocotrienol
content. The interactive effect between methanol to oil molar ratio and water amount had affected FAME andcarotene content. In summary, the production of biodiesel synthesized by commercial lipase was a green process
which non-waste water, gave highly biodiesel yield without using chemical catalysts, and especially preserved
palm phytonutrients.
Keywords: Crude palm oil biodiesel, Enzymatic transesterification, Commercial lipase, Free fatty acid, Carotene
content

Mainly, CPO can be used as a raw material for the
production of two different groups. The first group isfor human consumption such as palm olein oil, redpalm oil and margarine. The second group is forenergy consumption such as biodiesel. Biodiesel canbe synthesized from CPO and alcohol especiallymethanol using several catalysts. In esterification
reaction, the acid catalyst is used to reduce highcontent of free fatty acid in CPO to lower than 2%.
After that, the transesterification reaction is
performed to synthesize biodiesel from oil containing
free fatty acid under 2% that obtained fromesterification reaction. The catalyst in this step can beseparated to two types. Firstly, the homogeneous
catalysts are sodium hydroxide and potassiumhydroxide which can synthesize highly biodiesel
yield but it give waste water from purification process[6]. The second catalyst is heterogeneous catalyst
such as calcium oxide and calcium hydroxide which
are more benefit in terms of no waste water [7].
Normally, biodiesel synthesized from CPO
presents the red color. It indicates that the carotene in
CPO still contains within biodiesel. If this biodiesel isfurther distillated under reduced pressure, it will
generate two products, pure biodiesel and a palm
phytonutrients [8]-[10]. The palm phytonutrients are

INTRODUCTION
Palm is one of several economical plant inThailand. It can produce a lot of oil comparing withother oil-based plants. In crude palm oil (CPO), themajor component is saponified matter including freefatty acid and triglyceride. The minor part is acollection of phytonutrients such as carotenoids (500700 ppm), tocopherol and tocotrienol (600-1,000ppm), sterols (326-527 ppm) and squalene (200-500ppm) [1]. The main carotenoids in CPO are βcarotene (70%) and α-carotene (30%) which areconsidered as a pro-vitamin A. The carotenoids havea function as a biological antioxidants and it has a lotof beneficial effect on human health that enhanced theimmune response and reduced the risk ofdegenerative diseases such as cancer, cardiovasculardiseases, cataract, and muscular degeneration [2]-[3].
Moreover, tocopherol and tocotrienol are also
accepted as a potential antioxidant. They exhibit thebiological activities on human health such asneuroprotective, anti-cancer, anti-inflammatory andcholesterol lowering properties [4]. In CPO, there isabundant of tocotrienol which shows a superior
antioxidant activities and anti-inflammatory
properties more than tocopherol [5].
443SEE-Mie, Japan, Nov.10-12, 2022

a combination of carotene, tocopherol, tocotrienol
and other antioxidants. From those process, CPO is
not only originated a purified biodiesel but it also
produces a value-added product as well. In this case,the process of biodiesel production is important. The
reaction should perform under mild condition
because the carotene, tocopherol and tocotrienol aresensitive by heat and chemical substance such as acidcatalyst in esterification process and basic catalyst intransesterification process. Thus, the enzymatictransesterification using lipase enzyme is very
interested because of low temperature operation, nonchemical catalyst and also easy for purification [11][17].
The objective of this research is to study theparameters that affected on biodiesel properties via
enzymatic transesterification using commercial lipase
enzyme. The four variables are enzyme amount,methanol to oil molar ratio, water amount andreaction time. The biodiesel properties such as fatty
acid methyl ester content (FAME), free fatty acid
(FFA), carotene content, tocopherol content andtocotrienol content are also evaluated.

reaction at 45 oC and 250 rpm of the shaking speed.
After that, the mixture was separated bycentrifugation at 10,000 rpm for 15 minutes. The
biodiesel locating in the upper layer was transferred
into a beaker for removing the excess methanol byheating at 70 oC. Finally, the biodiesel in terms of afatty acid methyl ester (FAME), free fatty acid (FFA),
carotene content, tocopherol and tocotrienol content
were analyzed. The statistical analysis was performed
by SPSS software version 12.

MATERIAL AND METHODS

Fatty acid methyl ester content (FAME)

Materials

A 30 mg of oil was dissolved with 1 ml of methyl
heptadecanoate as an internal standard. The FAME
content was measured by gas chromatograph with
FID. Helium was used as a carrier gas. The solution
was analyzed by DB-WAX column (30m x 0.25mm
x 0.25µm). The injection mode was split as a split
ratio of 30:1. The injector and detector temperature
were set at 250 oC. The temperature program wasinitially set at 80 oC for 2 minutes. Then, it wasincreased to 250 oC with ramping of 10 oC/min andheld at the final temperature for 5 minutes. The C8C24 of methyl ester was used as a standard. Equation(1) presented the calculation of FAME content.

Table 1 Actual value of studied parameters
Factorunit

Enzyme amount
Methanol to oil molar
ratio
Water amount
Time

value

%wt.
mole

-1
13
3

1
23
5

%wt.
h.

3
2

7
4

Analysis of Biodiesel Properties

Oil palm bunches were obtained from Faculty ofagriculture, Kasetsart University. All reagents wereanalytical grade from Merck (Germany). The
commercial lipase enzyme was purchased from
Sichuan Habio Bioengineering (China). All standard
chemical are purchased from Sigma-Aldrich (USA).
Preparation of CPO
Oil palm bunches were chopped into oil palm
spikelet. About 1.5 kg of palm spikelet was dried byhousehold microwave (Samsung Co.,Ltd., Thailand)
at 850 watt for 10 minutes. Then, the palm fruits was
detached from its spikelet and separated a mesocarp
out of its nut. After that, the CPO was extracted using
hexane solvent after that the solvent was evaporated
by rotary evaporator. The obtained CPO wasanalyzed the fatty acid composition using the AOAC
Official Method 969.3. In addition, the CPO was also
checked its free fatty acid (FFA), carotene content,
tocopherol and tocotrienol content.

𝐅𝐀𝐌𝐄 (%𝐰𝐭. ) =(𝐀 𝐭𝐨𝐭 −𝐀 𝐈𝐒 )𝐀 𝐈𝐒×(𝐂𝐈𝐒 ×𝐕𝐈𝐒 )
𝐖

× 𝟏𝟎𝟎

(1)

Where, Atot and AIS are the total area and the areaof internal standard, respectively. CIS is theconcentration of internal standard (mg/ml). VIS is thevolume of internal standard (ml). W is the sample
weight (mg)Free fatty acid content (FFA)

Enzymatic Transesterification

The FFA content was performed according to
AOCS official method ca5a-40. For a brief
explanation, the sample was dissolved with ethanol
and titrated with 0.1 N sodium hydroxide using
phenolphthalein as an indicator. The FFA content wascalculated following Eq. (2).

The enzymatic transesterification was carried out
using 24 factorial design which was totally 16
experimental runs. The two level of each factor was
shown in Table 1. CPO was weighed in an erlenmeyer
flask. Then, methanol and water were added into CPO
and covered the flask with aluminum foil. The flask
was placed in the shaking incubator to operate the

𝐅𝐅𝐀 (%𝐰𝐭. ) =444(𝐒−𝐁)×𝐂×𝟐𝟓.𝟔
𝐖(2)

SEE-Mie, Japan, Nov.10-12, 2022

Where, S and B are the volume of sodiumhydroxide titrated with sample and blank,
respectively. C is concentration of sodium hydroxide(normality; N). W is the sample weight (g)The FFA of CPO using microwave for drying
decreased from 35.44% to 1.25%. This result
indicated that CPO can directly produce biodiesel bytransesterification reaction due to its low FFA content(less than 2%). While the carotene content increased
from 382.23 ppm to 490.68 ppm. It indicates that the
microwave drying is beneficial technique for CPO’s
quality improvement. In addition, the analysis of fatty
acid composition in Table 3 revealed that the main
component was palmitic acid (45.65%), oleic acid(39%) and linoleic acid (9.73%).

Carotene content
Carotene content was analyzed by highperformance liquid chromatograph equipped with
UV detector at 450 nm (Yonglin Co., Ltd, Korea).
The analytical column was YMC carotenoid (30cm x
8mm ID). A 100 mg of oil was dissolved with nhexane in 10 ml of volumetric flask. The solution was
injected to a column with the flow rate of 1 ml/min.
The mobile phase was the mixture of solvent A anddichloromethane (70:30, respectively). Solvent A
was a mixture of methanol, acetonitrile and ultrapure
water (84:14:2, respectively). The carotene content
was quantify comparing with the standard of αcarotene and β-carotene.

Table 3 Fatty acid composition of CPO
Fatty acid
Myristic acid (C14)
Palmitic acid (C16)
Palmitoleic acid (C16:1)
Stearic acid (C18)
Oleic acid (C18:1)
Linoleic acid (C18:2)
Linolenic acid (C18:3)
Arachidic acid (C20)
Behenic acid (C22)
Lignoceric acid (C24)

Tocopherol (TP) and tocotrienol (TT) content
100 mg of oil was dissolved with n-hexane in 10
ml of volumetric flask. A 20 µl of solution was
analyzed tocopherol and tocotrienol content by highperformance liquid chromatograph equipped with
UV detector. The solution was directly injected to a
UK-silica column (15cm x 4.6 mm ID) at a flow rateof 1 ml/min. The mobile phase was 99.5% n-hexane
and 0.5% isopropanol and the measured wavelengthwas 292 nm. The tocopherols and tocotrienols content
were quantify using external standard technique. The
tocopherol and tocotrienol standard consisted of αtocopherol, γ- tocopherol, δ-tocopherol, αtocotrienol, γ- tocotrienol and δ- tocotrienol

Biodiesel Production
Statistical analysis
The four parameters such as enzyme amount,methanol to oil molar ratio, water amount andreaction time were used to evaluate the biodiesel
properties in terms of FAME, FFA, carotene content,
tocopherol and tocotrienols content that was shown in
Table 4. All experimental data were tested theanalysis of variance (ANOVA) at 95% confident
interval. It revealed that enzyme amount, methanol to
oil molar ratio and interactive effect between
methanol molar ratio and water amount had affectedbiodiesel properties. The P-value of four responses
including FFA content, carotene content, tocopherol
and tocotroenol content on the effect of enzyme
amount were 0.013, 0.008, 0.021 and 0.022,
respectively. It indicated that the enzyme amount had
affected those responses. The methanol to oil molar
ratio had affected FFA content (P-value=0.011) andtocotrienols content (P-value=0.010). In addition, theinteractive effect between methanol to oil molar ratio
and water amount had also affected FAME content(P-value=0.033).

RESULTS AND DISCUSSION
Characterization of CPO
Table 2 presented the properties of CPO thatobtained from dried oil palm spikelet with microwave(MW).
Table 2 CPO Properties
Properties ofCPO
FFA (%wt.)
Carotene
content (ppm)
Tocopherol
content (ppm)
Tocotrienol
content (ppm)

AmountNot using MW
Using MW
35.44
1.25
382.23490.68-345.49-811.80

Amount (%Area)
1.22
45.65
0.22
3.23
39.00
9.73
0.41
0.39
0.06
0.10

Optimum condition
The FAME content increased when enzyme
loading increased (compared between run 1 to 7 andrun 14 to 16). Therefore, selected enzyme loading in
445

SEE-Mie, Japan, Nov.10-12, 2022

Table 4 Full factorial design of biodiesel properties based on FAME, FFA, carotene content, tocopherols content
and tocotrienols content
Run

Enzyme Methanol to
Water
Time
amountoil molar
amount(h)(%wt.)
ratio (mole)(%wt.)
1
13
3
3
2
2
13
3
3
4
3
13
3
7
2
4
13
3
7
4
5
13
5
3
2
6
13
5
3
4
7
13
5
7
2
8
13
5
7
4
9
23
3
3
2
10
23
3
3
4
11
23
3
7
2
12
23
3
7
4
13
23
5
3
2
14
23
5
3
4
15
23
5
7
2
16
23
5
7
4
Note: 1TP is tocopherol and 2TT is tocotrienol.

FAME
content(%wt.)
60.52
64.42
56.40
61.96
54.85
56.77
68.90
83.35
66.41
71.52
58.36
69.02
57.50
86.07
84.98
84.88

FFA
content(%wt.)
8.66
9.35
8.39
10.25
4.75
4.68
8.13
9.60
12.92
11.85
10.83
12.34
6.19
10.70
9.35
9.96

Carotene
content(ppm)
734.17734.71685.97617.76613.55548.76621.40651.12745.12795.84718.87740.65563.89701.02
839.59865.58TP
content1(ppm)
477.03515.81375.98513.69414.99444.24454.74487.60593.46511.81547.77490.49464.04504.01
540.12582.55TTcontent2(ppm)
858.48905.66648.49915.81779.55808.87756.79770.881,110.78
946.25
1,017.96
983.55786.86756.06885.09812.57this transesterification was 23%wt. When the reaction
time was compared (run 15 with run 16), the result
showed that the FAME content as well as FFA,
carotene content, TP and TT were slightly changed. It
can be said that the reaction time has not affected
FFA, carotene content, TP and TT. For water amount(run 14 with run 16), it was found that 3% of wateramount produced high FFA content, lower amount ofcarotene, TP and TT when compared with highamount of water (7%). For methanol to oil molar ratio(run 11 with run 15), it showed that high methanol to
oil molar ratio gave high FAME, lower FFA content
and higher carotene, TP and TT when compared with
5 mole. Therefore, run 15 is selected in thisexperiment to produce biodiesel by enzyme catalyst
due to high FAME, carotene content, TP and TT of
biodiesel production with lower FFA content.

increasing of FFA content as shown in run 1 and run
9 (Table 4). In run 1, the biodiesel produced by 13%
of lipase presented the FFA content of 8.66% while
the one produced by 23% of lipase (run 9) presented
12.92% of FFA content. In addition, the FFA content
showed a direct proportion on the effect of waterloading and reaction time while the methanol molar
ratio had affected FFA content in terms of an inverse
proportion. For example, the reaction using 3 mole ofmethanol (run 1) produced 8.66% FFA content of
biodiesel comparing with 5 mole of methanol (run 5)
generated 4.75% FFA content.

Properties of Biodiesel

O

O
2HC

O

C
O

R

HC

O

C
O

R

H2C

O

C

R

ase
H, lip
CH 3O
)
(a
HO
2 , li
pase
(b)

R

R

2HC

OH

HC

OH

Biodiesel

H2C

OH

O

2HC

OH

HC

OH

H2C

OH

C

C

OCH3 +

OH

TriglycerideFree fatty acid content (FFA)

Free fatty acid+

Fig. 1 Competitive
reaction
catalyzed
bycommercial
lipaseenzyme:(a)Transesterification reaction; (b) Hydrolysis
reaction

The FFA content of biodiesel presented in Table
4 was higher than FFA content of CPO. It was causedby the two competitive reactions. The main reaction
was transesterification catalyzed by lipase enzyme forbiodiesel production. However, the commercial
lipase enzyme using in this work was a liquid lipase
resulting to hydrolysis reaction was performed and it
promoted the FFA molecule as shown in Fig. 1. Thus,a higher level of enzyme amount resulted in the

Carotene content
All experiments showed that the carotene content
in biodiesel was higher than CPO because of two
reasons. Firstly, the enzymatic transesterification was446

SEE-Mie, Japan, Nov.10-12, 2022

carotene and β-carotene was the same in both CPO
and biodiesel. It contained about 24% of α-carotene
and 76% of β-carotene. At the same FAME content(about 85% in run 15), biodiesel catalyzed by enzyme
gave carotene content about 840 ppm while biodiesel
catalyzed by potassium hydroxide gave 465 ppm ofcarotene content. This high carotene content indicatedthat the enzymatic reaction can prevent the carotene
destruction.

1000

100

800

80

600

60

400

40

FAME content

200

20

Carotene content
0

FAME content (%wt.)

Carotene content (ppm)

performed at low temperature (45 oC), so it prevented
carotene from destruction by heat. Secondly, carotene
content was measured in terms of ppm (defined as
carotene weight (mg) per oil weight (kg)) and thetransesterification reaction of CPO eliminated theglycerol molecule out of the oil. Therefore, theproportion of carotene in oil was increased resulting
to a high carotene content in biodiesel.

Tocopherol and tocotrienol content
In Table 4, the TP and TT content in biodiesel
were in range of 375.98-593.44 ppm and 648.491,110.78 ppm, respectively, which is higher than in
CPO (345.49 ppm of TP and 811.80 ppm of TT). The
biodiesel given by suitable condition (run 15)
consisted of 474.48 ppm α-TP, 65.64 ppm γ-TP,
299.83 ppm α-TT, 484.58 ppm γ-TT and 100.68 ppmof δ-TT while CPO had 301.17 ppm α-TP, 44.32 ppm
γ-TP, 281.84 ppm α-TT, 431.15 ppm γ-TT and 98.81
ppm of δ-TT as presented in Table 5. It showed that
TP and TT in biodiesel were higher than the ones in
CPO. When compared between catalysts, the result
showed that biodiesel synthesized by basic catalyst(potassium hydroxide) was γ-TT and δ-TT reduction
while enzyme catalyst could save both γ-TT and δ-TTfrom destruction.

0

0

2

4

6

8 10 12 14 16
Run

Fig. 2 Carotene content and FAME content
containing in biodiesel of all experiment
The variation of carotene content containing in
biodiesel presented mostly similar trend as the FAME
content in Fig. 2. However, the proportional of α-

Table 5 Composition of tocopherol and tocotrienol containing in biodiesel and CPO
Run

Composition of TT and TP (ppm)
γ-TP
α-TT
γ-TT
57.25
298.81460.4464.61
315.99485.1345.95
231.90345.1061.40
315.52494.9756.76
286.18411.1256.70
303.31411.5954.98
261.11411.7757.76
262.54413.82
69.16
385.64606.3164.01
332.55502.8568.53
353.39544.3344.44
338.11541.8960.34
295.61397.6455.62
255.07410.6765.64
299.83484.5860.55
314.55401.7544.32
281.84431.15111.20510.27360.11α-TP419.771451.202
330.033452.284358.235
387.54
6
399.777429.848524.299447.7910479.2411446.0512403.7013448.3914474.4815522.0016301.17
CPO
810.70
Biodiesel catalyzed by basic catalyst
Note: TP is tocopherol and TT is tocotrienol.

447

δ-TT
99.23
104.5471.50
105.32
82.25
93.97
83.91
94.52
118.82110.85120.23103.5693.60
90.32
100.68
96.28
98.81
89.87

SEE-Mie, Japan, Nov.10-12, 2022

[7] Surbhi S., Ajay K.A., Rajendra P.B. and Deepak
K. T., Biodiesel Production Using Heterogeneous
Catalysts. Bioresource Technology, Vol. 102,
2011, pp. 2151-2161.
[8] Batistella C.B., Moraes E.B., Filho R.M. andMaciel M.R.W., Molecular Distillation Process
for Recovering Biodiesel and Carotenoids from
Palm
Oil.
AppliedBiochemistry
andBiotechnology, Vol. 98, 2002, pp. 1149-1159.
[9] C M., Ida I.M. and Eko S., Potential Source andExtraction of Vitamin E from Palm-Based Oils: a
Review. Journal Teknologi, Vol. 69, Issue 4, pp.
43-50.
[10] Ramesh K.S. and Young S.K., Carotenoid
Extraction Methods: a Review of Recent
Developments. Food Chemistry, Vol. 240, 2018,
pp. 90-103.
[11] Prakash S.B., Bhagwan S.S., Gulab S.T., Rakesh
K.B. and Prasad G.B.K.S., Biodiesel Production
with Special Emphasis on Lipase-Catalyzed
Transesterification. Biotechnol Lett, Vol. 32,
2010, pp. 1019-1030.
[12] Adriana G., Marius R., Monica T.¸ Csaba P. andFlorin D.I., Biodiesel Production Using
Enzymatic Transesterification – Current State andPerspectives. Renewable Energy, Vol. 39, 2012,
pp. 10-16.
[13] Aarthy M., Saravananb P., Gowthamana M.K.,
Rose C. and Kamini N.R., EnzymaticTransesterification for Production of Biodiesel
Using Yeast Lipases: an Overview. Chemical
Engineering Research and Design, Vol. 92, 2014,
pp. 1591-1601.
[14] Yang L., Wei D. and Dehua L., Free LipaseCatalyzed
Biodiesel
Production
fromPhospholipids-Containing Oils. Biomass andBioenergy, Vol. 71, 2014, pp. 162-169.
[15] Abhishek G., Bhaskar S., Taurai M., Kugen P.
and Faizal B., Advances in Synthesis of Biodiesel
via Enzyme Catalysis: Novel and Sustainable
Approaches. Renewable and Sustainable Energy
Reviews, Vol. 41, 2015, pp. 1447-1464.
[16] Xuebing Z., Feng Q., Chongli Y., Wei D. andDehua L., Lipase-Catalyzed Process for Biodiesel
Production: Enzyme Immobilization, Process
Simulation and Optimization. Renewable andSustainable Energy Reviews, Vol. 44, 2015,
pp.182-197.
[17] Kareem S.O., Falokun E.I., Balogun S.A.,
Akinloye O.A. and Omeike S.O., Enzymatic
Biodiesel Production from Palm Oil and Palm
Kernel Oil Using Free Lipase. Egyptian Journal of
Petroleum, Vol. 26, 2017, pp. 635-642.
[18] Cheng S.F., Mohd Nor L. and Chuah C.H.,
Microwave Pretreatment: a Clean and Dry
Method for Palm Oil Production. Industrial Crops
and Products, Vol. 34, 2011, pp. 967-971.

CONCLUSIONSThe commercial lipase enzyme was successfully
catalyzed transesterification for biodiesel synthesis.
The suitable condition was performed at 23% enzyme
loading, 5 mole of methanol, 5% water loading, 2hours of reaction time and 45 oC of reaction
temperature that gave 84.98% of FAME content. In
this condition, the biodiesel contained 839.59 ppm ofcarotene content, 540.12 ppm of tocopherols content
and 885.09 ppm of tocotrienols content. The
advantages of using commercial lipase as a catalyst
for biodiesel production are high biodiesel yield, lowenergy consumption, easy purification, less chemical
usage and saving palm phytonutrients (carotene andvitamin E). The synthesized biodiesel consisted of ahigh carotene and vitamin E content. When it was
further distillated under reduced pressure, it improved
the purification of biodiesel and amount ofphytonutrients. However, using commercial lipase
production had some drawback of a high FFA
content.
ACKNOWLEDGMENTS
This research was supported by The Researchand Researchers for Industries (RRI; PHDI0022),
Center of Excellence-Oil Palm and Sang Arun Palm
Oil Ltd., Co. and Thailand Institute of Nuclear
Technology (TINT) under Thailand Science
Research and Innovation (TSRI).
REFERENCES[1] Choo Y.M., Palm Oil Carotenoids. Food andNutrition Bulletin, Vol. 15, Issue 2, 1994, pp. 1-8.
[2] Namitha K.K. and Negi P.S., Chemistry andBiotechnology of Carotenoids. Critical Reviewsin Food Science and Nutrition, Vol. 50, Issue 2,
2010, pp. 728-760.
[3] Sumita S.K. and Munish G., Pharmacological
Effects of Carotenoids: a Review. International
Journal of Pharmaceutical Sciences and Research,
Vol. 3, Issue 1, 2012, pp. 42-48.
[4] Haseeb A., Amjid A., Jahangir I. and Waseem A
S., Pharmacological Potential of Tocotrienols: A
Review. Nutrition & Metabolism, Vol. 11, Issue
52, 2014, pp.1-22.
[5] Hong Y.P., Tan W.S.D., Wupeng L. and Wong
W.S.F., Vitamin E Therapy beyond Cancer:
Tocopherol versus Tocotrienol. Pharmacology &Therapeutics, Vol. 162, 2016, pp. 152-169.
[6] Man K.L., Keat T.L. and Abdul R.M.,
Homogeneous, Heterogeneous and Enzymatic
Catalysis for Transesterification of High Free
Fatty Acid Oil (Waste Cooking Oil) to Biodiesel:
A Review. Biotechnology Advances, Vol. 28,
2010, pp. 500-518.

448

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

QUANTIFICATION OF HYDRATION PRODUCTS IN RICE HUSK ASH(RHA)-BLENDED CEMENT CONCRETE WITH CRUMB WASTE
RUBBER TIRES (CWRT) & ITS CORRELATION WITH
MECHANICAL PERFORMANCE

1

John Mark L. David1, Richard M. De Jesus1 and Rodolfo P. Mendoza1
Department of Civil Engineering, Gokongwei College of Engineering, De La Salle University, Philippines

ABSTRACTPrevious studies on the use of rice husk ash (RHA) as a replacement of cement focused on attributing thestrength enhancements in mechanical strength in hardened concrete to its pozzolanic reactivity. Investigation of
the pozzolanic reaction RHA in terms of cement hydration has yet to be examined. This study intended to assess
the pozzolanic activity of RHA by quantification of calcium hydroxide (CH) and calcium silicate hydrate (C-S-H)
gel in RHA-blended cement pastes using simultaneous thermogravimetric and differential-thermal analysis (TGDTA). Moreover, the application of crumb waste rubber tire (CWRT) in concrete as fine aggregate replacement is
known to reduce mechanical strength. Thus, the pozzolanic reaction of RHA compensating the strength loss by
CWRT was also investigated. Two types of RHA, from open-air burning (RHA-O) and thermal power plant (RHAT), were used in casting cement pastes and mortars with 0%, 7.5%, 12.5%, and 17.5% replacement of cement (byweight). Finally, concrete with fixed optimal RHA and 5%, 10%, and 15% CWRT (by volume) were tested forcompression and splitting tensile strength. Results from TG-DTA revealed reductions in quantified CH contents
and increase in C-S-H gel contents in cement pastes with RHA indicating pozzolanic reaction. Decreasing CH
content corresponded to increasing compressive strength highlighting the strength enhancement by pozzolanic
activity, optimal at 17.5% using RHA-O. For concrete, results showed that incorporating 17.5% RHA-O and 5%
CWRT provided comparable compressive strength and higher splitting tensile strength than normal concrete,signifying the compensation of strength loss of CWRT by RHA.
Keywords: Rice husk ash, Pozzolanic effect, Thermogravimetric analysis, Hydration product, Crumb rubber
INTRODUCTION

Considering the abundant research on the effect of
RHA on the mechanical strength, the mechanism of
pozzolanic reaction by RHA in blended mortar andconcrete has yet to be studied. Therefore, one of themain objectives of the study is to evaluate thepozzolanic activity of RHA through thequantification of hydration products. Simultaneous
thermogravimetric and differential-thermal analysis(TG-DTA) has been considered as the easiest andmost widely used methodology for the analysis ofhydration reactions in cementitious pastes [7]. In thismethod, thermogravimetric analysis (TGA) monitors
the weight of the sample upon heating to a constantrate while differential-thermal analysis (DTA) detects
the temperature at which the reactions in the sample
occur manifested by peaks in the curve.
The
hydration
products
haveuniquedecomposition temperatures. This allows thedetermination of their quantities based on the masslosses associated with the decomposition
temperatures. For C-S-H gel, the temperature ofdecomposition ranges from 110°C to 400°C [7]whereas for CH, the decomposition ranges from
400°C to 600°C [8]. Using this method, reduction in
the quantity of CH can be indicative of reaction with
SiO2 from RHA while increase in C-S--H can beConcrete remains the single most widely usedmaterial in the world. Production of cement
contributes to about five percent of the global carbon
dioxide (CO2) production due to human activities [1].
One of the waste materials that have been
investigated to be an effective supplementary
cementitious material is rice husk ash (RHA).
Combustion of rice husk to run milling processes willproduce a huge amount of RHA, usually dumped on
bodies of water that cause pollution andcontamination [2]. RHA is described to have highsilica (SiO2) content ranging from 85% to 90% [3]making it very reactive and pozzolanic. Amorphoussilica is highly reactive whereas crystalline silica has
no pozzolanic activity [4].
Notable increase in mechanical strength has been
observed in mortars and concrete with replacementsof cement with RHA [3], [5]. The pozzolanic effectof RHA happens when the excess calcium hydroxide(CH) from the hydration of cement reacts with silica(SiO2) of RHA to form additional calcium silicate
hydrate (C-S-H) gel. The C-S-H gel is considered as
the main carrier of strength in a hardened concrete
hence increasing its overall mechanical strength [6].
449SEE-Mie, Japan, Nov.10-12, 2022

associated with the production of secondary C-S-H
gel.
Another potential material replacement in theconcrete mix is the crumb waste rubber tire (CWRT)
as fine aggregates. Although the addition of CWRT
reduces strength [9], the increase in strength provided
by the pozzolanic reaction of RHA can compensate
for this lack.
In this paper, two types of RHA will be examined:
RHA from open-air burning (RHA-O) and RHA froma thermal plant (RHA-T). Using TG-DTA, C-S-H andCH contents from the hydration of RHA-blended
cement pastes will be quantified and correlated to thecompressive strength of mortar with and without
RHA to evaluate strength improvement in relation to
pozzolanic effect. The final output of this study is a
blended concrete with optimal amount of RHA andCWRT.

METHODOLOGY
Preparation of RHA
The burning of rice husks was performed in an
open area using a cylindrical hollow steel plate. The
fire was maintained for one hour without controllingthe combustion temperature and cooled for 24 hours.
Two types of RHA were utilized in this study: (a)RHA from open-air burning (RHA-O) and (b) RHA
from a thermal plant (RHA-T). Both RHA were
further ground using Los Angeles Abrasion machine
to attain the required fineness of ASTM C618.
Characterization of OPC and RHA
Characterization of OPC and RHA wereconducted as follows: a) Blaine Air-Permeability Test
(ASTM C204) and No. 325 mesh fineness test
(ASTM C430) for fineness, b) Scanning Electron
Microscope (SEM) Imaging using JEOL JSM-5310
for microstructure, c) X-ray fluorescence
spectrometry (XRF) for chemical compositions andd) X-ray Diffraction (XRD) analysis for crystallinity.
The degree of crystallinity (DOC) of silica in each
RHA was estimated using Eq. (3) based on areas of
crystalline peaks and residual area in the diffraction
curve attributed to the area of amorphous peaks [13]:THEORETICAL BACKGROUND
Hydration of Portland Cement with RHA
The hydration of C3S and C2S in Portland cement
produces CH and C-S-H gel in the form C1.7SH4
where: C = CaO, S = SiO2 and H = H2O [10]. The
reaction of amorphous silica (SiO2) in RHA with theexcess CH from the hydration of Portland cement
forms another type of C-S-H given by the formula[11]: 2S + 3CH + H → 2C1.5 SH2 .

DOC(%) =The weight fraction of amorphous silica is given by:

Quantification of Hydration Products by TG-DTA

Wamorphous (%) = 100× (1-DOC)

Various authors have observed the following
decomposition reactions that occur in cement pastes
upon heating during TG-DTA: a) 30 °C to 105 °C:
dehydration of evaporable water [12], b) 110 °C to
400 °C: dehydration or loss of chemically boundwater from C-S-H molecules [7], c) 400 °C to 600 °C:
dehydroxylation of CH [8] following the reaction:
Ca(OH)2 → CaO + H2 O, and d) 600 °C to 1100 °C:
decarbonation (loss of carbon dioxide) in CaCO3 [10]based from the reaction: CaCO3 → CaO + CO2 .
The amount of CH can be estimated using [10]:MW (CH)

CH (%) = CHloss · MW (H)MW (C-S-H)(4)

Thermogravimetric and Differential-Thermal
Analysis (TG-DTA) of RHA Cement Pastes
Two sets of cement pastes were prepared with
RHA-O and RHA-T, at levels of replacement of purecement equal to 0%, 7.5%, 12.5% and 17.5% (Table
1). All pastes were mixed following ASTM C305,
casted into plastic jars (Ø30mm) with 10 mm heightand stored in a water bath 24 hours after casting.
All hardened cement pastes cured for 120 days
were dried in an oven at 105 °C for at least 24 hours,
pulverized using mortar and pestle, and then sieved
using
No.
200
sieve.
Simultaneous
thermogravimetric and differential-thermal analysis(TG-DTA) was performed using Perkin Elmer
Simultaneous Thermal Analyzer (STA) 6000
available in Advanced Device and Materials Testing
Laboratory (DOST-ADMATEL). Approximately 20
mg of each powdered sample was weighed and filled
in a platinum crucible. The heating program was set
in the following manner: (a) heat from 30 to 995 °C
at 10 °C per min and (b) hold for 5 min at 995 °C. All
samples were heated in Nitrogen gas atmosphere.
Quantification of CH and C-S-H contents in pureand blended cement paste samples were based on the
proposed methods from previous works [7], [8]calculated using Eq. (1) and (2), respectively.

(1)

where CH (%) is the percentage amount of CH,
CHloss is the mass loss in percentage due todehydroxylation of CH, and MW (CH) and MW (H)are the molecular weights of CH and water,
respectively. Calcium silicate hydrate (C-S-H) gel
content can be computed using the equation [7]:C-S-H (%) = C-S-Hloss · Moles of water · MW (H)

Crystalline area
× 100 (3)Crystalline area + Amorphous area(2)

where C-S-H (%) is the percentage amount of C-S-H,
C-S-Hloss is the mass loss in percentage due todehydration of C-S-H gel between 110°C - 400°C and
MW (C-S-H) and MW (H) are the molecular weights
of C-S-H gel and water, respectively.
450

SEE-Mie, Japan, Nov.10-12, 2022

Mortar Mix Proportioning and Testing

Crystallinity of silica in RHA
The silica phase of RHA-T is partly crystalline andpartly amorphous due to narrow peaks at around 21.8°
at the top of a broad peak between 10° and 28° andanother at 29.4° as shown in Fig. 1. These sharp peaks
are indicative of crystalline silica while the broad
peak is attributed to amorphous silica. The broadsmooth hump between 10° and 30° of RHA-O
indicated amorphous silica content. From the DOC
method, RHA-O and RHA-T contained 90.91% and76.18% amorphous silica, respectively. Hence, it canbe concluded that RHA-O will be more reactive than
RHA-T since it has more amorphous silica content.

Mortar cubes having 50 mm edge with 7.5%,
12.5% and 17.5% cement replacement (by weight) byeach RHA type (RHA-O and RHA-T) were madeusing ASTM C109 and mixing per ASTM C305 asshown in Table 2. Mortar fragments were subjected
to SEM imaging after testing.
Table 1 Mix proportion of pure Portland cement andRHA-cement pastes
Mix
DesignCP
7.5PO
12.5PO
17.5PO
7.5PT
12.5PT
17.5PT

Material
RHA, gCementRHARHA,g
O
T
100
0
0
92.5
7.5
87.5
12.5
82.5
17.5
92.5
7.5
87.5
12.5
82.5
17.5

Water,mL

Table 4 Chemical composition of RHA-O, RHA-T
and OPC

48.5
48.5
48.5
48.5
48.5
48.5
48.5

Chemical analysis (%)
RHA-O
Silicon Dioxide (SiO2)
93.38
Aluminum Oxide (Al2O3)
Ferric oxide (Fe2O3)
1.35
Calcium oxide (CaO)
1.65
Moisture content (%)
0.36

Table 2 Mixture proportion of 6-cube batch RHA
mortars
Mix
DesignCM
7.5MO
12.5MO
17.5MO
7.5MT
12.5MT
17.5MT

Cement
,g
500
462.5
437.5
412.5
462.5
437.5
412.5

Material
RHA, gRHA RHA-O
T
0
37.5
62.5
87.5
37.5
62.5
87.5

Sand
,g

Water
, mL

1375
1375
1375
1375
1375
1375
1375

242
242
242
242
242
242
242

RHA-T
82.73
1.1
11.22
0.29

OPC
16
3.69
2.93
67.6
-

Concrete Mix Proportioning and Testing
From the compression test on RHA mortars, themost optimal RHA type is RHA-O at 17.5% cement
replacement. Concrete cylinders were prepared atfixed 17.5% RHA-O with CWRT at replacementlevels 5%, 10% and 15% by volume. Mix
proportioning per 1m3 of each batch in Table 3 wasformulated according to ACI 211.1 at w/c equal to0.5. Three replicates of Ø100mm×200mm cylinders
were tested for compression and splitting tensile
strength after 28 days as per ASTM C39 and ASTM
C496, respectively.

Fig. 1XRD pattern of RHA-O and RHA-T

Thermogravimetric Analysis of Cement Pastes
Figures 2a show the profiles of thermogravimetric(TG) curves of 120-day cement pastes with RHA-O
typical to cement pastes with RHA-T where gradualweight loss with increasing heating temperature canbe observed. Differential Thermal (DTA) curves arealso presented in the figure showing the temperaturesat which reactions in the samples occur.
Thermogravimetric curves
From the DTG curves in Fig. 2b, four zones were
defined where the sharp peaks occurred for all
samples. Zone 1 is the first mass loss stepcorresponding to dehydration or loss of evaporable
water [12]. Zone 2 characterizes the dehydration orloss of chemically bound water from C-S-H
molecules [7]. Zone 3 indicates the dehydroxylationof calcium hydroxide (CH) [7]. Lastly, Zone 4 isassociated with the decarbonation of calcium
carbonate or calcite (CaCO3) [8]. The temperature ofpeaks and decompositions for all cement pastes did

RESULTS AND DISCUSSIONS
Properties of RHA and OPC
Chemical composition
Both RHA-O and RHA-T manifested high silica(SiO2) contents equal to 93.38% and 82.73%,
respectively, as shown in Table 4. Jamil et al. [11]demonstrated that amorphous silica from RHA reacts
with CH from cement hydration process to form
secondary C-S-H gel.
451

SEE-Mie, Japan, Nov.10-12, 2022

Table 3 Mixture proportion of concrete cylinders with RHA and CWRT in kg for 1 m3 concrete production.
Mix
RHA (%)CWRT (%)
R0C0
0
0
R0C10
0
10
R17.5C017.5
0R17.5C517.5
5
R17.5C1017.5
10R17.5C15
17.5
15
Note: a fine aggregate, b coarse aggregate

Cement
418
418
345
345
345
345

FAa
779
701
779
740
701
662

RHA
0
0
73
73
73
73

(a)

CWRT
0
38
0
19
38
57

CAb
1151
1151
1151
1151
1151
1151

(b)

Water
241
241
241
241
241
241

DTG
C-S-H

TG

CH

CaCO3

DTA
Zone 1

Fig. 2

Zone 2

Zone 3

Zone 4TG-DTA results for RHA-O cement pastes: (a) TG-DTA curve and (b) DTG curve

not vary significantly thus no major change in phasechemistry of the products.

7.5PO, 12.5PO and 17.5PO, respectively. The same
trend was observed for cement pastes with RHA-T
where CH content diminished to 10.43%, 8.30% and7.89% for 7.5PT, 12.5PT and 17.5PT, respectively.
Further, CH in blended cement decreases withincreasing RHA content. Between RHA-O and RHAT at same level of replacement, CH content does notvary significantly.

Calcium silicate hydrate (C-S-H) content
The formation of C-S-H gel with chemicalcomposition 1.7CaO·SiO2 ·4H2O for cement pastes
with pure Portland cement [10] and 2Ca1.5SiO3.5·2H2O for RHA-blended cement pastes [11] wereconsidered for its quantification by TG-DTA. Figure
3 presents the computed C-S-H gel from 120 days ofhydration with mass loss from 110 °C to 400 °C. The
formation of C-S-H gel increased from 22.37% in CP(control) to 33.09%, 32.06% and 29.54% with 7.5PO,
12.5PO, and 17.5PO, respectively. Similarly, the CS-H content in 7.5PT, 12.5PT, and 17.5PT increasedby 31.82%, 29.89% and 30.14%, respectively.
However, C-S-H gel does not vary significantly withthe replacement level of RHA.
It can be inferred that the addition of both RHA
types as cement replacement can cause a significant
increase in the C-S-H content. The mechanism of CS-H increase can be explained by the pozzolanic
activity of RHA where secondary C-S-H is produced
from the consumption of CH from Portland cement
hydration [11]. For cement pastes with RHA-O, theamount of C-S-H is higher than pastes with RHA-T
except at 17.5% replacement. This is due to higher
amorphous silica content and higher fineness of
RHA-O as compared to RHA-T.

Fig. 3

Hydration product contents of cement pastes
after 120 days

The reduction in the CH content confirmed the
pozzolanic activity of RHA-O and RHA-T. This isconsistent with the results of the quantification of CS-H gel where cement pastes with RHA exhibited
more C-S-H gel content than with plain Portland
cement. Boualleg et al. [14] reported that as theCalcium hydroxide (CH) content
The quantity of CH in cement pastes wascalculated from the mass loss from 400°C to 500°C
as shown in Fig. 3. The amount of CH decreased from
16.22% in CP to 10.32%, 8.73%, and 7.35% for452

SEE-Mie, Japan, Nov.10-12, 2022

(a) CM

prismatic CH(b) 12.5MO(c) 12.5MT
flocculent C-S-H

CH
CH

dense C-S-H

porous C-S-H

dense C-S-H
X7,500Fig. 41μm

1μm

X7,500

X7,5001μm

Microstructure of (a) control mortar (CM), (b) mortar with 12.5% RHA-O (12.5MO) and (c) mortar with
12.5% RHA-T (12.5MT) after 120 days of curing

hydration of pure cement progresses, portlandite ions
(Ca++ and OH-) are released and captured by the
pozzolan to form a new type of C-S-H gel. Based on
the results, the reduction of CH is greatest in cement
paste with 17.5% RHA-O (17.5PO) indicating thegreatest pozzolanic reaction.

microstructure of mortar with 12.5% RHA-T in Fig.
4c manifested porous and flocculent C-S-H gel withthe presence of more voids and CH crystals.
Effect of RHA and CWRT on ConcreteCompressive strength
It can be observed in Fig. 5, R17.5C0 recorded thehighest compressive strength improvement equal to12.4% when compared to the control (R0C0).
Comparing the results of sample concrete withCWRT only (R0C10) and samples with both RHA-O
and CWRT (R17.5C5, R17.5C10, R17.5C15), it canbe inferred that the incorporation of RHA-O canincrease the compressive strength up to 10% CWRT.
The compressive strength of R17.5C5 is comparable
to the control with a slight decrease of 3.4%. The
enhancement in strength by RHA-O is attributed to its
pozzolanic effect. It is also observed that replacing
fine aggregates with rubber decreases thecompressive strength.

Effect of RHA in Mortar
Compressive strength
After 3 days, the compressive strengths of allmortars with RHA are lower than the control mortar(CM) except to the mortar with 7.5% RHA-O(7.5MO). For 28-day samples, 12.5MO and 17.5MO
exhibited comparable strength increase equal to29.1% and 27.3% of the control, respectively.
Mortars with 12.5% RHA-T (12.5MT) and 17.5%
RHA-T (17.5MT) also increased in strength by 15.5%
and 3.6% of the control, respectively. After 120
curing days, similar trend to 28 days is observed
where 12.5MO, 17.5MO, 12.5MT, and 17.5MT
showed strength increase equal to 23.0%, 14.0%,
17.9%, and 1.6% of the control, respectively. It is also
evident that mortars with 12.5% RHA-O and RHA-T
performed slightly better than mortars with 17.5%.
Habeeb and Mahmud [15] reported that CH from thehydration of Portland cement may be insufficient toreact with the available silica in RHA, thus leading to
the incomplete pozzolanic reaction.
Researchers have reported that the compressive
strength increase of mortars with RHA may bepartially due to its high fineness and pozzolanic
reaction [11], particularly the presence of highly
amorphous silica in RHA enhancing its reactivity [4].
Microstructure
Prismatic CH and dense C-S-H gel were visible on
the surface of control mortar (CM) at 120 curing days
as seen in Fig. 4a. The prismatic CH is abundant andembedded on the C-S-H matrix since it is one of themain products from the hydration of Portland cement.
In Fig. 4b, mortar containing 12.5% RHA-O showeda denser C-S-H than CM. The presence of CH also
diminished. Production of secondary C-S-H from thepozzolanic reaction of RHA-O contributed to a denser
C-S-H matrix and less CH when compared to thecontrol. Pore refinement of the microstructure of themortar with 12.5% RHA-O resulted to the highest
compressive strength. On the other hand, theFig. 5Compressive and splitting tensile strength of
concrete with RHA-O and CWRT after 28
days

Splitting tensile strength
In terms of splitting tensile strength, R17.5C0
gained the highest strength at 3.06 MPa with anincrease of 31.2% of the control as shown in Fig. 5. It
is also noted that additions of both RHA-O andCWRT showed remarkable tensile strength increases
ranging from 7.2% up to 15.1% of the control unlike
in compressive strength where strength enhancement
is only due to RHA-O. When both RHA-O andCWRT are incorporated, the concrete is seen to453

SEE-Mie, Japan, Nov.10-12, 2022

perform better than concrete with CWRT only
(R0C10) but still lower strength than concrete with
RHA-O only (R17.5C0).

properties. Case Studies in Construction
Materials, 2017, pp. 73–81.
[4] Xu, W., Lo, T. Y., & Memon, S. A.,
Microstructure and reactivity of rich husk ash.
Construction and Building Materials, 29, 2012,
pp. 541–547.
[5] Isberto, C. D., Labra, K. L., Landicho, J. M. B., &De Jesus, R., Optimized preparation of rice huskash (RHA) as a supplementary cementitious
material. International Journal of GEOMATE,
16(57), 2019, pp. 56–61.
[6] Alex, J., Dhanalakshmi, J., & Ambedkar, B.,
Experimental investigation on rice husk ash as
cement replacement on concrete production.
Construction and Building Materials, 127, 2016,
pp. 353–362.
[7] Singh, L. P., Goel, A., Bhattacharyya, S. K., &Mishra, G., Quantification of hydration products
in cementitious materials incorporating silica
nanoparticles. Frontiers of Structural and Civil
Engineering, 10(2), 2016, pp. 162–167.
[8] Collier, N. C., Transition and decomposition
temperatures of cement phases - a collection ofthermal analysis data. Ceramics - Silikaty, 60(4),2016, pp. 338–343.
[9] Bisht, K., & Ramana, P. V., Evaluation of
mechanical and durability properties of crumbrubber concrete. Construction and Building
Materials, 155, 2017, pp. 811–817.
[10] Mounanga, P., Khelidj, A., Loukili, A.,
Baroghel-Bouny, V., Predicting Ca (OH)2
content and chemical shrinkage of hydrating
cement pastes using analytical approach. Cement
and Concrete Research, Elsevier, 34 (2), 2017, pp.
255-265.
[11] Jamil, M., Kaish, A. B. M. A., Raman, S. N., &Zain, M. F. M., Pozzolanic contribution of ricehusk ash in cementitious system. Construction
and Building Materials, 47, 2013, pp. 588–593.
[12] Fagerlund, G., Chemically bound water asmeasure of degree of hydration: method andpotential errors. In Division of Building
Materials, 315, 2009.
[13] Madsen, I. C., Scarlett, N. V. Y., & Kern, A.,
Description and survey of methodologies for thedetermination of amorphous content via X-ray
powderdiffraction.
Zeitschrift
Fur
Kristallographie, 226(12), 2011, pp. 944–955.
[14] Boualleg, S., Bencheikh, M., Belagraa, L.,
Daoudi, A., & Chikouche, M. A., The combined
effect of the initial cure and the type of cement on
the natural carbonation, the portlandite content,
and nonevaporable water in blended cement.
Advances in Materials Science and Engineering,
2017.
[15] Habeeb, G., & Mahmud, H., Study on propertiesof rice husk ash and its use as cement replacement
material. Materials Research, 13(2), 2010, pp.
185–190.

CONCLUSIONS
Based on the analysis of results presented in the
study, the following conclusions can be derived:
1. RHA- RHA-O and RHA-T exhibited high silica(Si02) contents equal to 93.38% and 82.73%,
respectively. X-ray diffraction (XRD) analysis
revealed that silica in RHA-O is mainly amorphous inform, whereas silica in RHA-T is partly amorphousand partly crystalline.
2. Simultaneous thermogravimetric and differentialthermal analysis (TG-DTA) can be used to quantify
C-S-H and CH and examine the extent of pozzolanic
reaction in blended cement pastes.
3. The amount of C-S-H gel is higher in RHA cement
pastes than plain cement pastes after 120 days. C-SH gel does not vary significantly with the RHA
replacement level. Reductions in CH are observed on
RHA-blended cement pastes at 120 days of curing.
Increasing RHA content resulted in decreasing CH
content confirming the pozzolanic activity of RHA.
4. Mortars prepared with 12.5% and 17.5% RHA-O
showed excellent compressive strength gain after 28
and 120 days. To maximize RHA content, 17.5%
RHA-O is used in concrete since their strengths arecomparable.
5. Concrete with 17.5% RHA-O only yielded thehighest compressive and splitting tensile strength
after 28 days among all mix types. Increasing CWRT
content decreases compressive strength. Additions ofboth RHA-O and CWRT resulted in higher splitting
tensile strength than the control. Adding 17.5% RHAO and 5% CWRT provided comparable compressive
strength and higher splitting tensile strength thannormal concrete which signifies the compensation ofstrength loss of CWRT by RHA.
ACKNOWLEDGEMENT
The authors acknowledge the Department of
Science and Technology (DOST-ERDT) of thePhilippines for providing the grant for this research.
REFERENCES[1] Boden, T. A., Andres, R. J., & Marland, G.,
Global, regional, and national fossil-fuel CO2
emissions, carbon dioxide information analysis
center, Oak Ridge National Laboratory, U.S.
Department of Energy, Oak Ridge, Tenn., USA,2017.
[2] Rodríguez De Sensale, G., Strength developmentof concrete with rice-husk ash. Cement andConcrete Composites, 28(2), 2006, pp. 158–160.
[3] Zareei, S. A., Ameri, F., Dorostkar, F., & Ahmadi,
M., Rice husk ash as a partial replacement of
cement in high strength concrete containing micro
silica: Evaluating durability and mechanical454

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FEASIBILITY STUDY FOR ENVIRONMENTALLY FRIENDLY
PROCESS IN PREMIUM CRUDE PALM OIL PRODUCTION
Sureerat Namwong1, Vittaya Punsuwan2, Pinsuda Viravathana3 and Rayakorn Nokkaew4
1,2,3
Faculty of Science, Kasetsart University, Bangkok, Thailand;
2,3,4
Center of Excellence-Oil Palm Kasetsart University, Bangkok, Thailand

ABSTRACT
Thailand has more than 149 factories of small palm oil mills. Mostly, they produce with low quality of crude
palm oil (CPO) with high free fatty acid (6-15% of FFA) and low Deterioration of Bleachability Index (2.0 ofDOBI). This research investigated the application of microwave technology for the production of premium CPO.
In this experiment, the CPO quality from two heating processes were compared. The first process is two times
palm spikelet heating by microwave and the second one is heating by microwave and hot air drying. The results
showed that two processes can produce the premium CPO with less than 1% of FFA, more than 4 of DOBI, about
500 ppm of carotenoids content, and less than 10 meq.kg-1 of peroxide value. The operating time of the first andthe second process were 0.28 and 2.23 hr., respectively with the convention process was 10 -15 hr. Summarized,
the microwave technology can reduce operating time and palm spikelet heating has the high potential process forpremium CPO production.
Keywords: Premium crude palm oil, Microwave technology, Small palm oil mill, Low free fatty acid.

INTRODUCTION

mill use dry pretreatment of fresh palm fruits (Hot air
pretreatment) that the mill is not occur POME
problem. However, disadvantage of dry process isgetting lower quality of CPO [4].
Microwave heat treatment for improving of CPO
has been widely accepted and continually developed[7]. Many research was studied on sterilization ofpalm fruit bunch using microwave. The result foundthat the microwave consumed shot time whencompared with the sterilized process of the large mill.

Palm oil is currently the world’s largest vegetableoil consumed for food, follow by soyabean andrapeseed oil [1], [2]. Thailand is the third palm oil
producer inferior to Indonesia and Malaysia. There
are 149 mills in Thailand estimates, they have thecapacity to produce 2.8 million tonnes of CPO per
year. About 0.24 million households across thecountry are involved in this sector, the majority (79%)
of which are smallholders [3]. Half of mills are small
palm oil mill. These were limited knowledge andtechnology making, it unable to produce premium
CPO, can only produce low quality oil [4]. They are
the main problem of small palm oil mills in Thailand.
This research therefore focuses on study thefeasibility of premium CPO production using
microwave technology for small palm oil mill.
In the conventional palm oil milling process inThailand provides 2 scales. There are a large scale
and a small scale. The large scale mill; fresh fruitbunches are pretreated under sterilization process. It
uses steaming as wet heat treatment. This process isto deactivate the oil splitting enzyme, soften the palm
fruitlets and encourage detachment of fruitlets frombunches [5]. Fruits are stripped to separate thesterilized fruits from the sterilized bunch stalks. After
that, loose fruits are preparative to screw pressing
process for good CPO quality. However, thesterilization process was produced large amount ofpalm oil mill effluent (POME) [6]. Most small-scale

However, microwave heating worked only the outerlayer of the fresh fruit bunch due to limitation of
microwave to penetrate inner layer of the bunch [8],[9], [10]. The spikelet without core of fresh fruitbunch microwave sterilization would be much more
efficient and effective process.
Two times heat treatments were used sterilization
process by microwave and hot air. These processes
consumed less time and low temperature which
reduced the destruction of antioxidants to effect onhigh quality of CPO [8]. Therefore, microwave
heating and two times heat treatment processes werea good alternative for environmentally friendly
process.
The aim of this research is feasibility study forpremium CPO production using microwave heating
and comparison between two times heating form
palm spikelets by microwave and the second one isheating by microwave and hot air drying. The
optimum conditions were collected on quality ofpremium CPO.
455

SEE-Mie, Japan, Nov.10-12, 2022

MATERIALS AND METHODS
Materials
Palm fresh bunch were obtained from the Facultyof Agriculture, Kasetsart University, Thailand.
Solvents and chemicals were obtained as follow: nhexane (99%), acetic acid, sodium thiosulfate, starchand hydrochloric acid were purchased from QReC,
Newzaland. n-hexane (95%) for extraction waspurchased from Burdick&Jeckson, South Korea.
Sodium hydroxide and methanol (95%) werepurchased from Merck Geramany. Ethanal (95%) was
purchased from Liquor distillery organization.
Potassium hydrogen phthalate, phenolphthalein,potassium iodine and sodium bicarbonate werepurchased from Ajex Finechem, Newzeland.
Chloroform was purchased from RCI Labscan limited,Thailand. Folin-Ciocalteu reagen was purchased from
Sisco Research Laboratories, India. Gallic acid waspurchased from Sigma-aldrich, USA.

Fresh fruit
bunch

Spikelets

Pre-heatedspikeletsby microwave
oven

Optimum
condition

fruitlets

Methods

1st processby microwave
oven

Two times heating process were carried out:1) collected of palm spikelet from bunch chopped for
microwave treatment optimization study and 2) palm
fruitlets from spikelet via microwave treatment at
optimization for the second heating by microwave
and hot air drying.

2nd processby hot airoven

The pre-heating process for treatment premium CPO
production
Palm spikelets were heated by a domestic
microwave oven (Sumsung, Model MS28H5125BK,
28 liters, 2.4 GH) at medium power intensity (850
W). Duration of heating varied from 2-26 min. After
that, palm fruitlets were analyzed heated by
microwave (the fist process) and by hot air oven (thesecond process).

Mesocarp oil extraction by solvent extraction

The first and second heating processes for treatment
premium CPO production

Fig. 1 The experimental diagram for premium CPO
production.

The fruitlets from the pre-heating process were
raw material for the first and the second processes
The first process; the fruitlets were heated by
microwave at 850 W for 1-5 min of heating time. The
second process; the fruitlets were heated by hot air
oven at 90°C for 1-3 hr. of heating time. Then
mesocarp was oil extraction by solvent. After that, theCPO was analyzed the physical and chemical
properties.
Each condition of two heating processes,
measured the temperature on palm fruit after heating,then peeled mesocarp and extracted the oil bysolution extraction. The oil was collected for chemical
analysis. The overall of experiment shown in Fig.1.

Analysis of Palm Oil Properties

Analysisof CPO
qualitiesof CPO

Determination of free fatty acid content (FFA)
FFA content of the oil sample was measured bydissolving oil in 95% ethanol and titrated with 0.1 N
sodium hydroxide solution using a phenolphthalein
indicator. The FFA content is calculated by following
Eq. (1).
FFA (%) =456(S−B)× N ×25.6
W(1)

SEE-Mie, Japan, Nov.10-12, 2022

Where, S is the volume of sodium hydroxide
solution for oil titration, B is the volume of sodiumhydroxide solution for blank titration, N is theconcentration of sodium hydroxide, W is the weightof oil.

Where, X is the volume of sodium thiosulphateused to titrate with oil sample, Y is the volume ofsodium thiosulphate used to titrate with blank, C isthe concentration of sodium thiosulphate, g is theweight of oil.

Determination of Deterioration of Bleachability
Index (DOBI)

Determination of total phenolic content (TPC)
Total phenolic content was determined the FolinCiocalteau colorimetric method by [11]. Gallic acid(GA) was standard for used to plot the standard curvethat was constructed by a range of concentrations
dissolved with the solvent. The equation was obtained,
total phenolic content of the CPO as GA equivalent
per gram of oil extract (mg GAE/ 100 g oil).

DOBI was determined followed MPOB test
method (2004). DOBI is defined as the ratio of thespectrometric absorbance at 446 nm 269 nm 0.1 g ofoil sample was weighed into 25 mL of volumetricflask and dissolved with hexane. The sample solution
was measured absorbance at 269 and 446 nm using
UV-VIS spectrophotometer. The value of DOBI iscalculated followed Eq. (2).
DOBI =

𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑎𝑡 446 𝑛𝑚
𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 𝑎𝑡 269 𝑛𝑚

Determination of 1,1-diphenyl-2-picrylhydrazyl(DPPH) radical scavenging activity
DPPH analysis is the methods for evaluating
antioxidant activity in oil. DPPH scavenging activity
was determined using a modified method of
yingngam and Chooklin [12], [13]. Different
concentrations of sample dilution (0.3 mL) weremixed with 1.5 mL of 0.1 mM ethanolic DPPH
solution. The resulting mixture was kept in the darkfor 30 min and measured absorbance by UV-Vis
spectrophotometer at 517 nm. The percentage of free
radical inhibition of the palm oil was calculated
according to the following Eq. (5).

(2)

Determination of carotene content (CC)
Carotene content was carried using MPOB test
method (2004). Briefly explained, 0.1 g of oil sample
was dissolved with n-hexane in a 25 mL volumetricflask. The absorbance reading of the solution at
446 nm was taken using UV-VIS spectrophotometer.
The carotene content is calculated as Eq. (3).
Carotene content (mg.kg-1) =383 (A)(V)
100(W)(3)
Inhibition (%) =Where, A is the absorbance at 446 nm, V is thevolume of oil solution and W is the weight of oilsample.

5 g of oil sample was dissolved in 30 mL mixture
solution of (acetic acid and chloroform). Then added
0.5 mL of saturated potassium iodine solution andshaked the solution and shaked the solution. After that,
added 30 mL of water and shaken vigorously toliberate iodine from the organic to aqueous layer.
Iodine was titrated with a 0.1 N sodium thiosulphate
solution using a starch indicator. A blankdetermination was made using the same procedure
without the oil sample. PV was calculated using theEq. (4).
(X−Y)×C ×1000
g

× 100

(5)

Where, A0 is the absorbance of ethanol and DPPH
mixed, A1 is the absorbance of standard and DPPH
mixed and A2 is the absorbance of standard andethanol mixed. Inhibition (%) was used to plot thestandard curve. The equation was obtained DPPH
antioxidant activity on μg Trolox/g CPO.

Determination of peroxide value (PV)PV =𝐴0 −( 𝐴1−𝐴2 )𝐴0

RESULTS AND DISCUSSIONS
Spikelets pre-heating by microwave heating
Table 1 show the physical properties of palm
spikelet after microwave heating the criteria for
optimum condition of pre-heating was completely
loosing of palm fruit and premium CPO quality(FFA<3%, DOBI>3). The results found that at 14 minof duration heating consumed less time for 100% of
fruitless. The characteristic of palm fruit was good
physical. Mesocarp was slightly soft and kernel was
white which whole palm fruit could produce crude
palm oil and crude palm kernel oil. The temperature
on palm fruit at 4 min was 89.14°C to optimum
temperature was more than 90°C to affect on

(4)

457

SEE-Mie, Japan, Nov.10-12, 2022

carotenoids degradation [14]. So, the optimum
condition for spikelet preheating was 14 min ofheating duration. The cause of loose fruitlets by the
microwave heating was compensate steam heating
and dielectric properties of the materials (water inmaterial) that is major absorber of microwave energy.
The microwave generated is distributed and absorbedby the component leading to rise in temperature.
Consequently, palm spikelets received fast heating inkernel and mesocarp [8]. Although at 26 min ofheating duration gave 6.68% of MC and completely
fruitlet which the MC was optimum condition for oil
production by screw press. The temperature was108.34°C to effect on antioxidants degradable which
this condition gave lower TPC (table 2). The moisture
content (MC) of mesocarp was decreased rapidly withhigher heating duration because the water was rapidly
evaporated from inside to outside of palm fruits.
Moreover, over heat of microwave has effect on
destruction of the physical structure, specially oil cell
rupture, has effect on oil content (OC) [14]-[15].

peroxide value and total phenolic contents were slightly
reduced due to deterioration of palm oil from highheating [8].
The advantage of spikelet pre-treat by microwave
was reducing of FFA 1% of FFA with out chemical
when compared with conventional process. The main
problem of community palm oil mill is high FFA
content. In the CPO which FFA reducing has toalkaline chemical for neutralization process while
microwave heating can be stopped the activity oflipase enzyme and reversed reaction of hydrolysis to
produce oil content [14].
Table 2 The qualities of palm spikelet oil after
microwave pre-heating
Heating
DOBI
PV
FFA
TPC
duration (min)(mg.kg-1) (%) (mg.GAE/100 g)
2
2.97
1.97
10.97
20.21
8
3.72
2.63
1.44
18.45
14
3.89
3.28
0.60
16.45
20
3.58
3.60
0.51
16.19
26
3.88
4.35
0.43
14.91

Table 1 Physical properties of palm after microwave
pre-heating

The Two Times Heating Processes

Heating T
MC OC fruitlets
Condition
duration (°C) (%) (%)(%)
Mesocarp Kernel(min)2
51.74 38.20 72.47 0.02 no changes white884.06 27.80 75.37 58.41 no changes white14
89.14 17.32 76.17 100.00 slightly soft white
20 100.76 13.04 76.76 100.00 slightly soft white
26 108.34 6.68 78.55 100.00 oily and soft white
Note: T – Temperature (°C)

The condition of palm fruitlets after heating by
microwave (first process) and hot air (second process)
Table 3 shown the conditions of palm fruitlets
after two times heating by microwave (the firstprocess) and hot air (the second process) for treatment
premium CPO production. The result showed that thetemperature increasing was proportional to theheating duration of microwave and hot air. The
optimum heating duration of palm fruitlets wasdetermined to be 3 min of microwave heating and2.00 hr. of hot air heating. The physical characteristicof fruitlet was slightly soft of mesocarp and white ofkernel, and not burning, which get the oil yield andundamaged antioxidant substrate [6]. In first process,sharply increased temperature made to low MC andhigh OC on short time heating. It also has a positiveeffect on the quality of oil.

Heat penetration is key factor in palm sterilization
via microwave heating. Notably, qualities of palm
spikelet oil after microwave heating shown in Table 2.
At the optimum pre-heating, DOBI, Peroxide value and
FFA were 3.89, 3.28 mg.kg-1 and 0.60% respectively.
The result showed that the CPO met premium palm oilstandard. FFA reducing by microwave heating due to thelipase enzyme induced the hydrolysis reaction of
triglyceride to generate the FFA with inactivated by
microwave [4], [6]. The result of carotene content,

Table 3 The condition of palm fruitlets after double heating by microwave and hot air for treatment premium
CPO production
First Process of Microwave Heating Treatment
Heating TMCduration (°C) (%)(min)
69.82 16.74
12
98.76 11.94
3 105.58 7.43
4 109.04 4.53
5 120.50 1.43

Second Process of Hot Air Heating Treatment

OC Condition of the heated fruitlets Heating
TMC(%)
duration (°C)
(%)
(hr.)
Mesocarp
Kernelwhite
1.00
57.08 13.77
76.46 slightly soft
77.20 slightly soft
white
1.50
66.34 9.88
78.29 slightly soft
white
2.00
70.52 7.69
78.19 partially dry slightly brown
2.50
72.84 7.29
78.83 dry and stiff completely brown
3.00
78.14 5.53

458

OC
(%)
75.60
76.38
76.66
77.76
78.74

Condition of
the heated fruitlets
Mesocarp
Kernelslightly softwhite
slightly softwhite
slightly softwhite
slightly softwhite
slightly softwhite

SEE-Mie, Japan, Nov.10-12, 2022

Table 4 The qualities of crude palm oil after two times heating by microwave (first process) and hot air (second
process) at various of heating duration
First Process of Microwave Heating Treatment
Second Process of Hot Air Heating Treatment
Heating
DOBI
CC
PV
FFA
Heating
DOBI
CC
PV
FFA
duration (min)(mg.kg-1) (meq.kg-1)(%)
duration (hr.)(mg.kg-1) (meq.kg-1)
(%)
1
4.15
444.90
15.21
0.47
1.00
3.66
487.04
5.58
0.48
2
4.14
458.58
15.11
0.36
1.50
3.71
457.36
5.80
0.48
3
4.80
544.22
9.24
0.29
2.00
4.42
521.17
5.86
0.51
4
3.96
521.36
8.37
0.27
2.50
5.09
509.06
7.35
0.60
5
3.73
531.89
6.50
0.26
3.00
4.49
521.35
7.05
0.87
Limit
>4.00
500-700<10.00
<1.00
Limit
>4.00
500-700<10.00<1.00
Note: Limit – the trending specifications limit of premium crude palm oil (CPO)

The qualities of CPO after microwave and hot air
processes shown in Table 4. The results from the firstprocess presented the premium CPO at 3 min ofheating duration. This condition gave 4.80 of DOBI,
544.22 mg.kg-1 of CC, 9.24 meq.kg-1 of PV, and
0.29% of FFA which the results were supported highpotential of microwave technology for premium CPO
production. Atter 3 min of heating duration thetemperature on palm fruit was more than 100°C toindicate that destruction of the physical structure, oilcell rupture, of the mesocarp [14], [15]. In
antioxidants of CPO had reported that the hexane
extraction mechanism gave the high concentrations ofvitamin E and carotene from mesocarp fiber [6] thatis antioxidant to encourage protecting the oil fromoxidation reaction [8]. Corresponding, total phenoliccontents indicated that the oil has antioxidants. Fromexperiment found that the value of TPC and DPPH
has similar trending.
The result of TPC and antioxidative activity by
DPPH method for first and second processes shown in
Table 5. The both processes had slightly decreased TPC
and DPPH when heating duration was increased.
Oxidation reduction in the oil was cause of reducing of
TPC and DPPH. The excess of high temperature andlong heating duration could reflect the deterioration in
the CPO. Decreased level of antioxidant indicated thatthe oil was less protected against oxidation which the
CPO was deteriorated [8]. Although, the bothprocesses provided similar antioxidative values but hot
air heating consumed long time for premium CPO
production. Thus, the first process by was the optimum
process more than the second process.

Table 5 Total phenolic content and anti-oxidative
activity by DPPH method of the CPO
First Process of Microwave Heating Treatment
Heating
TPC
DPPH
duration (min) (mg.GAE/100 g) (μg Trolox/g CPO)
1
15.17
22.3
2
12.55
21.6
3
12.23
20.0
4
12.40
19.5
5
12.92
18.8
Second Process of Hot Air Heating Treatment
Heating
TPC
DPPH
duration (hr.)(mg.GAE/100 g)(μg Trolox/g CPO)
1.00
14.93
22.5
1.50
13.26
21.6
2.00
13.05
20.8
2.50
12.91
17.4
3.00
11.11
16.9

technology was enveronmental friendly process andcan improve the oil quilities.
ACKNOWLEDGMENTS
This research was supported by National
Research Council of Thailand (NRCT), undercontract no. N41A640264, Thailand Institute of
Nuclear Technology (TINT), under Thailand Science
Research and Innovation (TSRI), Sang Arun Palm Oil
Limited Partnership, Center of Excellence-Oil Palm,
Kasetsart University, Department of Chemistry,
Faculty of Science, and Faculty of Agriculture,
Kasetsart University.

CONCLUSIONSREFERENCES

Microwave had high potential for premium CPO
production. The optimum conditions were 14 min for
spikelet pretreatment followed to 2 min for drying ofpalm fruit by microwave. The important point of oilpalm pretreatment by microwave was shot operated
time for protection of oil deterioration. From all resultof experiment were subported as the microwave

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Kushairi A., Loh S. K., Azman I., Meilina O. A.,
Zainal Bidin M. N. I., Razmah G., Shamala S., andParveez G. K. A., Oil palm economic performancein Malaysia and R&D progress in 2017. J. Oil
Palm Res., Vol. 30, 2018, pp. 163-195.

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[2] Statista. Vegetable oils: Global consumption by
oil type. http://www.statista.com/statistics/
263937/vegetable-oil-global-consumption/,
accessed on 1 Nov., 2019.
[3] Krungsri, Industry Outlook 2020-2022: Palm Oil
Industry, https://www.krungsri.com/en/research/
industry/industry-outlook/agriculture/sugar(1)/IO/io-oil-palm-20-th on 30 May., 2022.
[4] Tapanwong M., Rayakorn N. and Vittaya P.,
Effect of combination microwave and ovendrying on the chemical properties of different
ripeness crude palm oil. International Journal of
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[5] Olie, J.J. and Tjeng, T.D., The Extraction ofPalm Oil. The Incorporated Society of Planters,
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[6] Cheng S.F., Mohd N. L. and Chuah C.H.,
Microwave pretreatment: A clean and dry
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Crops and Products, Vol. 34, 2011, pp. 967-971.
[7] Umudee
I.,
Chongcheawchamnan
M.,
Kaitweerasakul M., and Tongurai C.,
Sterilization of Oil Palm Fresh Fruit Using
Microwave Technique. International Journal ofChemical Engineering and Applications, Vol. 4,
Issue 3, 2013, pp.111-113.
[8] Hadi N.A., Han N.M., Majid R.A. and Met C.R.
C., The effect of microwave treatment anddelayed harvesting on oil palm fruitlets oil
quality,
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2021;
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[9] Chow M.C. and Ma A.N., Processing of fresh palm
fruits using microwaves, J. Microw. Power EE, Vol.
40, Issue 3, 2007, pp. 165–173.

[10] Kandiah S., Basiron Y., Suki A., Taha R. M.,
Hwa T. Y. and Sulong M. Continuous
sterilization: The new paradigm for modernisingpalm oil milling. J. Oil Palm Res., Special Issue,
2006, pp. 144-152.
[11] Wolfe K., Wu X., and Liu R.H., Antioxidant
Activity of Apple Peels. J ARG Food chem andFood Chemistry, Vol. 51, 2003, pp.609-614.
[12] Yingngam B., Supaka N. and Rungseevijitprapa
W. Optimization of process conditions forphenolics extraction from Cratoxylum formosumssp. formosum leaves using response surface
methodology. J Food Sci Technol 2013;10.1007/s13197-013-1030-y.
[13] Chooklin S., Rehbenmood K., Bunmak J. andChingsong W.
Characterization of AntiOxidative Cassava Starch Based Film
Supplemented with Anacardium occidentale L.
Leaf Extract. Walailak J Sci & Tech, Vol. 14,
Issue 12, 2017, pp. 981-995.
[14] Nokkeaw R., development of community crude
palm oil mill without steam utilization andmethod development for percentage oil analysis
in fresh fruit bunch for rapid analysis. Thesis of
Graduate School, Kasetsart University, 2017.
[15] Chang J.S.L., Law M.C., Chan Y.S., and Leo
C.P., Effects of microwave heating on oil palm
mesocarp, Chemical Engineering Transactions,Vol. 45, 2015, pp. 1633-1.

460

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

TUNGSTEN, COPPER, MANGANESE, ZINC, IRON AND ARSENICCONCENTRATIONS OF PLANTS IN KIWADA MINE

1Daiki Yamamoto1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan ;2
Faculty of Systems Engineering, Wakayama University, Japan

ABSTRACT
Athyrium yokoscense (a special kind of fern) and Arabis gemmifera (a kind of Brassicaceae) are known as
hyperaccumulators that contain specific heavy metals. However, only a few studies have confirmed thehyperaccumulator status of other plants. The hyperaccumulator of tungsten (W) was the focus of this study. W has
similar chemical properties to molybdenum (Mo). Mo is necessary for plant protein synthesis and nitrogenmetabolism, and Mo is recognized as an essential trace element. On the other hand, it remains to be elucidated
whether W has such a function. Here quantitative analysis was undertaken to determine the concentration of heavy
metals in plants growing in three areas of Kiwada mine that is considered with heavy metals. The deposit at the
Kiwada mine is a skarn deposit which contained W formed by alternating limestone in an olistostrome. The main
W-bearing mineral is scheelite (CaWO4) and chalcopyrite (CuFeS2), pyrrhotite (Fe1-xS) and arsenopyrite (FeAsS)
are also present. One of the study areas was near the mine entrance adit, and the other was a place where the
excavated ore deposits were stockpiled. Pine, cyrtomium and pteris cretica (another kind of fern), etc. were found.
As a result, it was found that multiple plants contained W over 100 ppm, most of which were concentrated in theroots. These plants are not common but are found in various parts of Japan. Together, these results provide new
insight into our understanding into tolerance for heavy metal in plants.
Keywords: Hyperaccumulator, Heavy metals, Tungsten, Fern

INTRODUCTION

absorption of Mo and W using Italian grass showedthat the plants absorbed significantly higher
concentrations of Mo and W than normal plants
growing in soil, and that the higher the concentrationin the culture medium, the greater the amountabsorbed. Based on these results, it can be predictedthat W will be absorbed by plants in the same way as
Mo if the supply of W is sufficient [2]. If this is thecase, it is possible that wild plants also absorb W in
soils with high W concentrations.
The Kiwada Mine, located in Futashika, Iwakuni
City, Yamaguchi Prefecture, has long been known asa mineral deposit area, where small mines were
established to extract tin (Sn) and copper (Cu) during
the Edo period. Since the Meiji period (1868-1912),
the area has been known as a tungsten production area
due to the discovery of a large amount of ash heavyore. The Fujigatani Mine is located southwest of theKiwada Mine, and the Kuga Mine is locatednorthwest of the Kiwada Mine, and ash feldspar was
the main ore for both mines [3]. All the mines are now
closed, but some of the waste rock containing ash
heavy ore has been left in some areas, and it ispossible that a large amount of W is contained in thesoil.
The purpose of this study is to investigate plants
growing naturally in the Kiwada Mine and to measure
the concentration of heavy metals, including W, in thecollected plants. In addition, we examine whether

By the 1860s, De Saussure, von Sacks, and Knop
had shown that C, H, O, N, P, S, K, Ca, Mg, and Fe
were essential for plant growth. C, H, O, N, P, S, K,
Ca, Mg, and Fe are essential for plant growth.
Subsequently, 17 essential elements for plant growth
were listed by 1987 [1]. Since heavy metals and othersoil contaminants are absorbed together during theabsorption process, plants in general cannot grow inareas with high concentrations of soil contaminants.
However, some plants prefer to grow in areas withhigh concentrations of contaminants, especiallyheavy metals, and absorb and accumulate heavy
metals at high levels. These plants are called mine
plants or metal-loving plants in Japanese.
Tungsten (W) is a rare metal that exists in theenvironment in the form of WO42- (tungstate ion), an
element with very similar chemical properties tomolybdenum (Mo). However, while Mo is a traceessential element for plants involved in nitrate
reduction, W has not been recognized as essential,
and therefore, there are few examples of analysis of
W in plants and soil. The reason for the low
concentration of W in plants growing in soil isassumed to be that the solubility of W-containing
components in soil is low and the supply of W isinsufficient compared to that of Mo. On the other
hand, hydroponic experiments comparing the461

SEE-Mie, Japan, Nov.10-12, 2022

there are plants that absorb and accumulate highconcentrations of W, and discuss the differences inheavy metal concentrations among plant sites andsampling locations.

sometimes accompanied by quarts and white mica [4].

METHODS
About The Kiwada Mine
The geology of the Nishiki River basin consists of
the Triassic Kuga County Formation and the Late
Cretaceous granitoids that intrude the Kuga County
Formation. The Kuga County Formation consists ofmudstone, chert and sandstone, and has narrowlenticular limestone. The deposits are composed of
massive skarn deposits and quartz veins, which arealternated with limestone, and both of them areoperated by ash heavy rocks. The number of ore
bodies is large, and based on past open-pit mining
sites, more than 30 ore bodies are estimated to haveexisted. The main ore bodies are represented by the
Hontei, Suehiro, Mabo, and the 10th ore bodies of the
5th, 8th, and Choei Ants, etc [3].
The term skarn is derived from a mining term usedfor vein stones composed of coarse-grained calciumrich silicate minerals from iron mines in the Persberg
area of Sweden. Skarn occurs in association withmetamorphic and igneous rocks, but it is sometimes
enriched in useful elements to the extent that it can beused as a mineral resource, and is called a skarn
deposit.
The type of skarn deposit is related to various
geological factors, the most significant of which is theoxidation degree of the igneous rocks involved.
Based on the amount of magnetite or magnetic
susceptibility contained in the granitoids, they areclassified into two types: oxidizing magnetite-series
and reducing ilmenite-series. On the other hand,based on differences in the source rock, they are
divided into I-type and S-type granitoids. Whensedimentary rocks containing coal are involved, therocks become reductive granitoids. When magnetite
or I-type granitoids are involved lead, zine, copper,
iron, molybdenum, and silver are present, whereas tin
and fluorine are present when ilmenite or S-typegranitoids are involved. Tungsten is associated withboth types of granitoids. Tungsten occurs as ash
heavy rocks and is divided into oxidized and reduced
forms depending on the type of mineralaccompanying it, the letter being associated with
ilmenitic granitoids.
Among the W skarns, the oxidized type iscomposed of glauconite skarn with a low
monoclinopyroxene to porphyroxene, with a highmonoclinopyroxene to porphyroxene ratio, and tin
and fluorine. The Kiwada Mine corresponds to the
reduced type, in which the deposit develops in layers
or lenses between limestone and sandy-muddy rocks,
and is poor in sulfide minerals, with ash heavy rocks

Fig .1

Distribution of skarn deposits in Japan [4]Outline Of The Study Site
The locations of plant collections in this study are
shown in the figure below. Point (1) is Choei Adit andpoint (2) is the work hut. Point (3) is the ore storage.

Fig .2

Location of Kiwada mine

Fig .3

Location of sampling points in Kiwada mine

Figure 4 is a photograph of the entrance to the
Choei Adit at point (1). The Choei Adit is one of themine entrances dug during mining. The ore storage atpoint (3) refers to a pile of mined ore that has been
accumulated in a specific location and discarded aswaste. In these rock piles, ash heavy rocks consistingof CaWO4 were found in abundance.
462

SEE-Mie, Japan, Nov.10-12, 2022

metals in the plants are extracted and a yellow
solution is obtained. Fine impurities remain in thescrew tube, so these are removed using a filter andsyringe.
The analysis was performed using an ICP opticalemission spectrometer to measure the concentrationof heavy metals in the prepared samples. The heavy
metals measured were tungsten (W), copper (Cu),manganese (Mn), zinc (Zn), iron (Fe) and arsenic(As).
From the above steps, the concentration of heavy
metals is measured. Since the concentration measured
is the concentration in the sample solution, it must be
converted to the concentration of heavy metals in thedried plant sample using the following equation

Fig .4 Photograph of the entrance to the Choei Aditat point (1)𝑎 (𝑚𝑔/𝑘𝑔) =𝑏 (𝑚𝑔/𝑘𝑔)× 𝑐(𝑔)

(1)

𝑑 (𝑔)

a Heavy metal concentrations in plant samples
b Concentration of solutionc Weight of solutiond Dry weight of sample
RESULTS

Fig .5In this study, the concentration of six elements
were measured: tungsten (W), copper (Cu),manganese (Mn), zinc (Zn), iron (Fe) and arsenic(As). The concentrations of each heavy metal
detected are shown in the graphs for each sampling
point and site.

Photograph of the ore storage at point (3)Analysis Method

Table 1After pretreatment, the collected plants aremeasured for heavy metal concentrations in the plants
using an ICP optical emission spectrometer.
Pretreatment consists of cleaning the plants andpreparing samples. First, the collected plants are
separated into root, leaf, and stem parts as much as
possible. The soil is washed because it contains alarge amount of heavy metals, which can cause large
errors in the measurement results. After washing withtap water, an ultrasonic cleaner was used. To use themachine, the sample to be cleaned is placed in acontainer, soaked in water, and then placed in themachine. Most of the stains are removed in about 20
minutes, but heavily soiled specimens, such as roots,need to be washed again. After the dirt is removed,
the specimens are placed in the dryer for one or twodays to dry.
A solution sample of heavy metals extracted fromplants is prepared for ICP emission spectrometry.
First, dried plants are placed in a screw tube andconcentrated nitric acid is added. Nitric acid has theeffect of oxidatively decomposing organic matter inthe sample and extracting heavy metals. Afterapproximately two weeks of standing, the heavy

Collected plants and sampling point

Numbers
A
B
C
D
E
F
G

Collected
plantsPteris cretica

Sampling
point①

CyrtomiumfortuneRubus
buergeriRubusbuergeri
CyrtomiumfortuneArachniodes
standishii
Pinus
densiflora

①
①
③
③
②
②

Measurement Results Of W
Figure 6 and Fig 7 show the concentration of W
in the dried samples of each plant. The average
concentrations in A per site were 6.089 mg/kg forleaves, 2.083 mg/kg for stems and 57.192 mg/kg for463

SEE-Mie, Japan, Nov.10-12, 2022

for roots. The average concentrations in E per sitewere 37.746 mg/kg for leaves, 14.787 mg/kg forstems and 2349.335 mg/kg for roots. The average
concentrations in F per site were 9.41 mg/kg forleaves, 4.842 mg/kg for stems and 74.521 mg/kg forroots. The average concentrations in G per site were3.176 mg/kg for leaves and 6.767 mg/kg for stems.
Cu concentrations in the roots were high,especially in the roots of E. Leaves and stems
contained little Cu.

roots. The average concentrations in B per site were7.531 mg/kg for leaves, 2.442 mg/kg for stems and136.979 mg/kg for roots. The average concentrations
in C per site were 40.119 mg/kg for leaves, 7.818
mg/kg for stems and 49.692 mg/kg for roots. The
average concentrations in D per site were 35.27
mg/kg for leaves, 4.102 mg/kg for stems and 237.552
mg/kg for roots. The average concentrations in E persite were 231.29 mg/kg for leaves, 61.317 mg/kg forstems and 1114.655 mg/kg for roots. The average
concentrations in F per site were 9.815 mg/kg forleaves, 3.91 mg/kg for stems and 21.595 mg/kg forroots. The average concentrations in G per site were
2.554 mg/kg for leaves and 3.779 mg/kg for stems.
Roots in the plants contain a large amount of W,
and among them, E showed W concentrations of morethan 800 mg/kg. On the other hand, some plants, such
as F, showed almost no W detected even in the roots.

Fig .8

Measurement results for Cu

Measurement Result Of Mn

Fig .6

Figure 9 shows the concentration of Mn in driedsamples from each plant. The average concentrations
in A per site were 32.755 mg/kg for leaves,
6.358mg/kg for stems and 135.9 mg/kg for roots. The
average concentrations in B per site were 59.008
mg/kg for leaves, 18.639 mg/kg for stems and198.932 mg/kg for roots. The average concentrations
in C per site were 154.829 mg/kg for leaves, 51.985
mg/kg for stems and 84.501 mg/kg for roots. The
average concentrations in D per site were 497.188
mg/kg for leaves, 35.664 mg/kg for stems and 80.385
mg/kg for roots. The average concentrations in E persite were 52.031 mg/kg for leaves, 22.631 mg/kg forstems and 190.311 mg/kg for roots. The average
concentrations in F per site were 53.884 mg/kg forleaves, 17.046 mg/kg for stems and 260.649 mg/kg
for roots. The average concentrations in G per sitewere 114.689 mg/kg for leaves and 40.354 mg/kg forstems.

Measurement results for W

Fig .7

Measurement results for W

Measurement Results Of Cu
Figure 8 shows the concentration of Cu in driedsamples from each plant. The average concentrations
in A per site were 6.282 mg/kg for leaves, 5.103
mg/kg for stems and 221.925 mg/kg for roots. The
average concentrations in B per site were 7.359
mg/kg for leaves, 5.321 mg/kg for stems and 109.236
mg/kg for roots. The average concentrations in C persite were 15.384 mg/kg for leaves, 13.006 mg/kg forstems and 84.858 mg/kg for roots. The average
concentrations in D per site were 13.367 mg/kg forleaves, 12.623 mg/kg for stems and 172.653 mg/kg

Fig .9464

Measurement results of Mn

SEE-Mie, Japan, Nov.10-12, 2022

Measurement Result Of Zn
Figure 10 shows the concentration of Zn in driedsamples from each plant. The average concentrations
in A per site were 39.326 mg/kg for leaves, 11.965
mg/kg for stems and 74.883 mg/kg for roots. The
average concentrations in B per site were 31.816
mg/kg for leaves, 22.317 mg/kg for stems and 66.405
mg/kg for roots. The average concentrations in C persite were 26.167 mg/kg for leaves, 46.706 mg/kg forstems and 132.19 mg/kg for roots. The average
concentrations in D per site were 22.929 mg/kg forleaves, 27.452 mg/kg for stems and 153.176 mg/kg
for roots. The average concentrations in E per sitewere 77.237 mg/kg for leaves, 24.035 mg/kg forstems and 282.881 mg/kg for roots. The average
concentrations in F per site were 91.786 mg/kg forleaves, 77.17 mg/kg for stems and 90.622 mg/kg forroots. The average concentrations in G per site were
32.871 mg/kg for leaves and 30.847 mg/kg for stems.

Fig .11

Measurement results of Fe

Measurement Results Of As
Figure 12 shows the concentration of As in driedsamples from each plant. The average concentrations
in A per site were 67.533 mg/kg for leaves, 130.625
mg/kg for stems and 47.512 mg/kg for roots. The
average concentrations in B per site were 6.605
mg/kg for leaves, 1.323 mg/kg for stems and 33.131
mg/kg for roots. The average concentrations in C persite were 1.086 mg/kg for leaves, 0 mg/kg for stems
and 11.668 mg/kg for roots. The average
concentrations in D per site were 0 mg/kg for leaves,
0 mg/kg for stems and 13.174 mg/kg for roots. The
average concentrations in E per site were 3.488 mg/kg
for leaves, 0.304 mg/kg for stems and 140.611 mg/kg
for roots. The average concentrations in F per sitewere 0 mg/kg for leaves, 0 mg/kg for stems and 0.724
mg/kg for roots. The average concentrations in G persite were 0 mg/kg for leaves and 0 mg/kg for stems.
Leaves and stems of A contained 40~225 mg/kg
As, while them of other plants contained almost noAs.

Fig. 10 Measurement results of Zn
Measurement Results Of Fe
Figure 11 shows the concentration of Fe in driedsamples from each plant. The average concentrations
in A per site were 178.702 mg/kg for leaves, 48.97
mg/kg for stems and 1856.047 mg/kg for roots. The
average concentrations in B per site were 133.107
mg/kg for leaves, 20.378 mg/kg for stems and3691.684 mg/kg for roots. The average
concentrations in C per site were 377.678 mg/kg forleaves, 74.636 mg/kg for stems and 572.191 mg/kg
for roots. The average concentrations in D per sitewere 151.567 mg/kg for leaves, 32.182 mg/kg forstems and 1114.103 mg/kg for roots. The average
concentrations in E per site were 580.856 mg/kg forleaves, 102.535 mg/kg for stems and 6879.96 mg/kg
for roots. The average concentrations in F per sitewere 199.745 mg/kg for leaves, 28.985 mg/kg forstems and 1150.652 mg/kg for roots. The average
concentrations in G per site were 33.735 mg/kg forleaves and 56.949 mg/kg for stems.

Fig. 12 Measurement results of As
DISCUSSION
Differences In Heavy Metal Concentrations In
Different Parts Of The Body
Comparing the heavy metal elements in thecollected plants by site, the concentrations of tungsten(W), copper (Cu), iron (Fe) and manganese (Mn)were higher in the roots of all plants. The higher
concentrations of Cu, Fe and Mn in roots are thought
465

SEE-Mie, Japan, Nov.10-12, 2022

To clarify this fact, it is necessary to investigate
whether W adheres to the root surface or permeates
the inside of the roots. To this end, it is necessary to
expand the study area at the Kiwada mine and also toinvestigate plants native to the surrounding tungsten
mines and W-skarn mines.
As was only found in the leaves and stems of
petris cretica of Choei Adit. Sakae S. et al.’s study [6]showed that this plant has an accumulation potential
for As with the results of the present analysis.

to be due to the fact that only the necessary amounts
are transported to the leaves during the absorption
process, and excess heavy metals are accumulated in
the roots. W and As, which are not consideredessential elements, were found almost exclusively inthe roots. It is thought that the accumulation andadsorption of these elements in the roots during
growth may prevent them rom being taken into thebody. In addition, Comparing the graphs of heavy
metal concentrations in each plant, it can be seen thatthe heavy metal concentrations of W and Cu have asimilar concentration distribution.

ACKNOWLEDGMENTS
I would like to express my sincere gratitude to
Associate Professor Masanobu Taniguchi of graduate
school of Systems Engineering, Wakayama
University, who took time out of his busy schedule togive me great advice and guidance in the course ofthis research.
A would like to express my sincere gratitude to
the members of the laboratory for their constantguidance and cooperation in laboratory analysis anddata processing.
We would like to express our gratitude to all of
you for your cooperation.

Differences In Heavy Metal Concentrations
Between Sampling Sites
A comparison of heavy metal concentrations in plantsfrom the Choei Adit and the ore storage shows that W
and Cu tend to be more abundant in plants from theore storage than from the Choei Adit. The ores minedin the Choei Adit were mainly dumped in the ore
storage area, with ash feldspar contains calcium (Ca)and tungsten (W), and bress ores contain copper (Cu)and iron (Fe). Therefore, heavy metals are thought tohave been leached from these rocks by rainfall andother factors, causing the concentrations of W and Cu
to increase at Point (3).

REFERENCES[1] Mori T., Mae T., Yoneyama T., Bunseido
Publisher, 2001.
[2] Yamada H., Nishimura K., Hattori K., TakahashiE., Absorption of molybdenum and tungsten by
Italian grass, Japanese Journal of Soil Scienceand Fertilizer, Vol.60, No.5, 1989, pp.463-465.
[3] Nagahara S., Geological Deposit and Explorationof Kiwada Mine, Yamaguchi Prefecture, Mining
Geology, Vol.28, No.152, 1978, pp.373-384.
[4] Etuo U., Takanori N., Approach to skarn Deposit,
Geochemistry, Vol.52, No.4, 2018, pp.149-169.
[5] Shigeyuki M., Hoikusya, Shida no Zukan(illustrated Book of fern), 1986.
[6] Sakae S., Yusuke Y., Kana D., Shigeyoshi W.,
Accumulation of arsenic in soils by Pteris cretica,
Abstracts of the Annual Meeting of theGeological Society of Japan, 2007, pp.615-615.

CONCLUSIONSIn this study, heavy metal concentrations inplants collected from the Choei Adit and ore storage
areas of Kiwada mine were alalyzed. As a result, it
was found that cyrtomium fortune contained a large
amount of tungsten (W), most of which accumulated
in the roots. Interesting results were also obtained,with high concentrations of arsenic (As) detected in
Pteris cretica. The reason for the significantly higher
W concentration in roots then in stems and leaves
may be that W is easily precipitated throughhydrolysis and polymerization, and W precipitated on
the root surface and W absorbed in the root interior
are mixed. However, it is possible that W absorbed
from the roots of cyrtomium foutune may be
accumulated in the leaves and stems.

466

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

DIFFERENCES IN PLANTS HEAVY METAL CONCENTRATIONSBY REGION
Takuya Ueda1 and Hiroyuki Ii2Faculty of System Engineering, Wakayama University, Japan

ABSTRACTThis study describes the accumulation of heavy metals in plants. Research is underway on plants that are foundto be specific for growing in contaminated soil and accumulating heavy metals at high levels. In this study, theconcentrations of heavy metals in plants sampled at Tada Silver Mine in Hyogo prefecture, central Japan were
measured in order to clarify the relation between heavy metals concentration and parts of plants. Tada Silver
Mine is closed and produced Ag, Zn, Pb, and Cu. There were 5 sites surveyed at the Tada Silver Mine, and theplants growing were Arabis gemmifera, Fallopia japonica, and Blechnum niponicum. The collected plants werepretreated, and the concentration of heavy metal genus plants were measured using ICP emission spectroscopy
analysis. As a result, the concentrations of leaves for Zn were 6000 to 13000mg/kg for Arabis gemmifera, 100 to
200mg/kg for Fallopia japonica, and 100 to 200mg/kg for Blechnum niponicum. The concentrations of roots for
Pb were 300 to 1100mg/kg for Blechnum niponicum, 0to 10mg/kg for Fallopia japonica, and 0 to 10mg/kg for
Arabis gemmifera.
Keyword: Arabis gemmifera, Blechnum niponicum, heavy metal, soil

INTRODUCTION

chalcopyrite have been found at this survey site, it isthought that zinc, lead, and copper is contaminated[7]. Mino Falls is near where the mine where copper
was mined, and it is thought that coppe r
contamination is occurring [8].

Plants absorb various inorganic substances present
in the soil from their roots and live as nutrients inthem. In the process, contaminants in the soil,
including heavy metals, are absorbed together, so
ordinary plants cannot grow in places with high soil
pollutant concentrations [1]. However, some plants
prefer to grow in places where there are manypollutants, especially metals, and absorb andaccumulate pollutants at high levels [2]. An example
is the fern plant Pteris vittata, which has been foundto accumulate arsenic concentrations 10,000 times
higher than other plants [3]. Such plants are called
heavy metal accumulation plants and have been
focused on from the viewpoint of phytoremediation
which uses plants to improve soil contamination, andresearch and experiments are still being conductedToday [4],[5].
Since the growth conditions of plants differ
depending on the environment such as soil andtemperature, it was thought that changes in thenumber of heavy metals in plants occur depending on
regional differences. Therefore, I investigated two
locations, the Tada Silver Mine in Inagawa Town,
Hyogo Prefecture, and the Mino Waterfall in Mino
City, Osaka Prefecture, and aimed to verify whether
th er e w a s a d if f er en c e i n th e h e av y m e t alconcentration of plants due to changes in the area.
Tada Silver Mine is famous as a copper and silvermine with a long history that has been mined since
the Nara period and lasted until 1973 [6]. Since ores
su ch as zin c sph aler ite, b lue lead o r e, an d

APPROACH
Sites② ~ ⑤ of the Tada Mine are contaminatedwith a lot of heavy metals left in the soil, so plants
may be accumulating heavy metals. In addition, inorder to clarify the specificity of numerical values,
plants at point① of the non-contaminated zone werealso collected at the same time and compared. The
survey date for Tada Mine is May 22, 2022. There
were a total of five types of plants, including Fallopia
japonica , Arabis gemmifera , and Blechnum
niponicum in the contaminated area, andDicranopteris dichotoma growing naturally in the
non-polluted zone. Since we were able to collectBlechnum niponicum at three locations, we will pay
attention to the change in the concentration of heavy
metals due to the difference between each point.
Since the ores discovered this time are two types ofore, linarite, and chalcopyrite, and since ores such as
bornite, galena, and sphalerite also exist in the Tada
Silver Mine, it is presu med that the soil iscontaminated with Cu (copper), Pb (lead), and Zn(zinc) [2],[6].
The survey date for Mino Falls is May 25, 2022.
At Mino Falls, two kinds of plants were collected:
Arabis gemmifera and Athrium yokoscense. Since
Arabis gemmifera grew naturally in both the Tada
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SEE-Mie, Japan, Nov.10-12, 2022

Mine and Mino Falls, we will conduct a comparative
study by region based on the results of the analysis ofboth.

In this analysis, since the heavy metal concentrationof the solution of the sample is measured, Equation(1) was used to obtain the heavy metal concentrationof the plant.

Table 1 Survey points and details
𝑿=𝑺∗
Site

DetailTada
Mine① Non-filthy

Dyeing place

Dicranopteris
dichotoma

Tada
Mine

② Smelting andrefining traces

Fallopia japonica

Tada
Mine

③ Veins

Tada
Mine④ Aoki

Mabu

Blechnumniponicum

Tada
Mine

⑤ Ore

dumpingsite

Blechnumniponicum

Mino
Waterfall

⑥

(𝑷+𝑵)
𝑷

Plant Name

(1)

X: Heavy metal concentration in plants(mg/kg)
S: concentration in solution (mg/kg)
P: dry weight of plant (g)N: weight of nitric acid (g)Arabis gemmifera,

RESULTS AND DISCUSSIONS
along

Mino Waterfall

Blechnumniponicum

Specific values were shown from among theheavy metal concentrations detected by ICP emission
spectroscopic analysis and graphed for each plant.
The X-axis lists the names of the plants and thenumber of points collected, and the Y-axis indicatesthe concentration of each heavy metal.
Figure. 1 shows the heavy metal content of Zn inplants. Because Zn is a trace essential element ofplants, it was also included in a small amount of
Dicranopteris dichotoma in non-contaminated zones.
The specific value was shown in Arabis gemmifera,
which contained about 6,000 ~ 13,000 mg/kg in theleaf and showed the highest concentration. Also,
when looking at the amount of Zn contained in the
Tada Mine and the Arabis gemmifera of Mino Falls,
the leaves showed the same value, but the stems androots contained an overwhelming amount of Arabis
gemmifera of Mino Falls.

Arabis gemmifera,
Athriumyokoscense

The collected plants were divided into roots,
stems, and leaves and washed to remove the soil
adhering to the sample. The cleaning method was a
combination of the use of an ultrasonic cleaner and amethod of washing directly by hand. After washing,put in the dryer for a week. The dried sample wasweighed with an electronic balance, put in a screw
tube, concentrated sulfuric acid was added, and theweight was measured. Nitric acid is suitable for the
extraction of heavy metals because it oxidizes anddecomposes organic matter in the specimen.
Thereafter, it was allowed for a week to confirm thatthe sample had turned light yellow, and then thesolids in the solution were removed using a syringe
and filter.
In the analysis, it was measured using ICP-AES.
ICP emission spectroscopy measures are based on thefollowing principles. First, when plasma energy isapplied to the sample, the atoms of the elements
contained in the sample absorb the energy and are
excited. The excited atom then emits light (spectral
lines) when returning to a lower energy level. Since
light at this time is specific to the element, it can beanalyzed by measuring the wavelength and amountof light. The elements measured in this study are Zn(zinc), Ni (nickel), Cu (copper), Co (cobalt), As(arsenic), Mn (manganese), Cr (chromium), Ca(calcium), Mg (magnesium), Pb (lead), Ag (silver),Cd (cadmium), Al (aluminum), Ba (barium), Bi(bismuth), Li (lithium), Mo (molybdenum), Sb(antimony) , Se (selenium), Sn (tin), Sr (strontium),Th (tho rium ) , U (u r an ium ) , V ( v an ad iu m ).

Fig. 1 Zn concentration in plants
Figure. 2 shows the number of heavy metals in
Cd in plants. Because CDs are toxic heavy metals thatcan be h armfu l ev en in sm all quan tities ofaccumulation, they were not included in the noncontaminated areas of Dicranopteris dichotoma andBlechnum niponicum. However, Arabis gemmifera,
which grows naturally in the Tada Mine, accumulated
a high concentration of 1000 ~ 2000 mg/kg.
Furthermore, it is noteworthy that the same species of468

SEE-Mie, Japan, Nov.10-12, 2022

Arabis gemmifera also showed different results at the
Tada Mine and Mino Falls. Despite accumulating a
lot of CDs at the Tada Mine, the Arabis gemmifera at
Mino Falls contained almost no Cd.

almost no lead accumulation, but high concentrations
were accumulated in the squirrel native to points ③,④, and ⑤. Further, when compared at points ③, ④,
and ⑤, it was found that a large amount of lead was
accumulated in the Aoki Mabu at point ④.

Fig. 2 Cd concentration in plants
Fig. 4 Pb concentration in plants

Figure. 3 shows the number of heavy metals in
Cu in plants. Since Cu is a trace essential element ofplants, it was also slightly contained in the
Dicranopteris dichotoma of the non-contaminatedzone. However, plants other than Dicranopteris
dichotoma showed a large accumulation of heavy
metals at the roots of 200 mg/kg~1000 mg/kg. As
with the Cd concentration of Fig.2, there was a large
difference in the amount of accumulation of Tada
Mine and Arabis gemmifera at Mino Falls in Cu. In
addition, when comparing the Tada mine points③,
points④, and points⑤, the Blechnum niponicum atpoint⑤ showed a high concentration, and even
within the same mine, large differences in the numberof heavy metals were observed depending on thelocation.

Figure. 5 indicates the number of heavy metals in
the plant Fe. The plant that showed the highest value
was Athyrium yokoscense native to Mino Falls,
accumulating 3,000 to 4,500 mg/kg at the roots. Also,
when viewed as a whole, they tended to accumulate
large amounts of Fe in the roots, and the leaves andstems contained almost no Fe.

Fig. 5 Fe concentration in plants
If we focus on each part of the leaf, stem, and root,
we can see that the place where it accumulates differs
depending on the heavy metal. Specifically, Arabis
gemmifera tends to have a large amount ofaccumulation in the leaves of Zn and Cd, but Cu andFe have a large amount of accumulation in the roots.
From this, it can be seen that Arabis gemmifera isresistant to heavy metals of Zn and Cd and canperform photosynthetic activities even when heavy
metals are accumulated in large amounts in leaves. In

Fig. 3 Cu concentration in plants
Figure. 4 shows the number of heavy metals in Pb
in plants. Since Pb is hardly contained in the nonpolluted zone, the Dicranopteris dichotoma had
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SEE-Mie, Japan, Nov.10-12, 2022

addition, when focusing on Pb, a large amount ofaccumulation is seen in the sea beetle, and highconcentrations are shown in all leaves, stems, androots. So, it was found that the sea lily has Pb
tolerance and can grow while accumulating Pb on theleaves, stems, and roots.
In this section, we will focus on the differences in
the heavy metal concentrations of plants by region
and location. First, when we focused on the Arabis
gemmifera, which grows naturally in the Tada Mineand Mino Falls, there was not much difference in theconcentration of Zn and Pb, and there was no majordifference. However, heavy metals from Cd, Cu, andFe were accumulated at high levels at the Tada Minebut were rarely contained at Mino Falls. If I were to
guess why there was a big difference in the numberof heavy metals due to regional differences, I think it
was because there was a difference in the soil
contamination situation. As mentioned in the survey
summary, the Tada Mine has strong soil
contamination due to the discovery of Pb, Zn, and Cu
ores, and as a result, it is thought that it has had asignificant impact on plants. Since many Cd arederived from Zn ore, it is thought that a large amountof accumulation was seen in Arabis gemmifera forthe same reason as before. Copper mining was carriedout nearby at Mino Falls, but in this study, there is ahigh possibility that the survey was conducted in aplace with weak contamination of Cu, and it isthought that Arabis gemmifera of Mino Waterfall did
not accumulate much Cd due to t his factor.
Next, when we focused on the Blechnum
niponicum, it was found that it accumulated a large
amount of Pb. Looking at the difference in thenumber of heavy metals at each point, the heavy
metal concentration was about 600 g / kg higher thanthat along the vein at point③ in the Aoki walk at point④. It was presumed that Aoki Mabu was the sitewhere Pb ore was mined, so high numbers wereindicated, and it was found that the heavy metal
concentration of plants also changes depending on thesoil contamination situation.

environment such as soil. In this survey, since the soil
conditions of the Tada Mine and Mino Falls are very
different, it is thought that the heavy metal
concentration of plants depends on the soil
contamination situation.
As a future task, since there are individual
differences in plants and the results of this analysis
are not necessarily correct, it is necessary to test the
average value to investigate the difference in theaccumulation of heavy metal content depending on
the individual difference, and to investigate theinfluence on plants by investigating the soil
contamination situation.
ACKNOWLEDGMENTS
In advancing this research, I would like to express
my sincere gratitude to my supervisor, Professor
Hiroyuki Ii of the Graduate School of System
Engineering, Wakayama University, who gave me
tremendous advice and guidance during his busy
schedule. I would also like to express my heartfelt
gratitude to Associate Professor Masanobu Taniguchi
for his guidance and encouragement during his busy
schedule.
I would like to express my sincere gratitude to
everyone in the laboratory for their constant guidanceand cooperation in in-room analysis, data processing,
etc. I would like to express my gratitude to everyone
who has cooperated with me.
REFERENCES[1] Poisonous Plants - Why Do Plants Store Heavy
Metals? - (2007 Vol. 26, No. 6) | National Institutefor Environmental Studies News, Vol. 26|
National Institute for Environmental Studies(nies.go.jp)
https://www.nies.go.jp/kanko/news/26/26-6/266-03.html[2] Takayasu Kitagawa：Analysis of heavy metals
in Athyrium yokoscense at Tada Silver Mine,
Hyogo Prefecture, Journal of Plant Geography
and Taxonomy (2005) p161-165[3] Obata, Kan, Miyauti, Endo: Basic research on theabsorption and removal of soil arsenic by Pteris
vittate, Technical Research Presentation of the
Tohoku Branch of the Japan Society of Civil
Engineers（2012）VII-29[4] What is phytoremediation| World Social Good
Ideas Magazine | IDEAS FOR GOOD
https://ideasforgood.jp/glossary/phytoremediation/[5] Yoshida, Akiyoshi, Fujihara： The Current
Situation and Challenges of Phytoremediation,
Taisei Construction Center Bulletin No. 38（2005）p.06‐1～06‐4

CONCLUSIONSIn this study, we investigated the number of heavy
metals in plants native to the Tada Mine and Mino
Falls and investigated what kind of plants dominantly
contain heavy metals, and whether there are changes
in the amount of heavy metal accumulation due toregional differences.
Arabis gemmifera, which grows naturally in the Tada
Mine, had a large accumulation of heavy metals of
Zn, Cu, Cd, and Fe, while Arabis gemmifera, which
grows naturally in Mino Falls, had a large amount ofZn accumulation, and not much heavy metals of Cu,
Cd, and Fe. From this, it was found that even if it is
the same plant, the amo unt of heavy metal
accumulated changes due to differences in the470

SEE-Mie, Japan, Nov.10-12, 2022

[6] Tada Silver and Copper Mine - Inagawa Town
Sightseeing Guide to Everything (jimdofree.com)
https://inagawa-kankou.jimdofree.com[7] Ore deposits by origin (hydrothermal deposits:vein deposits): Academic Materials Exhibition
Hall, Faculty of Engineering, Yamaguchi
University(Yamaguchi-u.ac.jp)
http://www.msoc.eng.yamaguchiu.ac.jp/collection/origin_23.php[8] Hirao Mine - Ruins Search Map (haikyo.info)
https://haikyo.info/s/1333.html

471

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

A STUDY ON APPLICATION POSSIBILITY OF WOODEN BIOMASSCOMBUSTION ASH MODIFIED BY FLOTATION METHOD AS
CONCRETE ADMIXTURE
Shilun Liu1, Koji Takasu1, Hidehiro Koyamada1, and Hiroki Suyama1
Dept. of Architecture, Faculty of Environmental Engineering, The University of Kitakyushu, 1-1 Hibikino
Wakamatsu, Kitakyushu, Fukuoka 8080135, Japan
ABSTRACTIn response to global warming, there has been a growing call for alternative energy sources, and in recent
years there has been growing interest in Wooden Biomass power generation. With the popularity of Wooden
Biomass power generation, the Wood Biomass Combustion Ash generated by power generation is also on the rise,
but there is no good method for the treatment of Wood Biomass Combustion Ash, and it still needs to be treatedby landfill. In order to verify whether wood biomass combustion ash can be used as an additive for concrete inbuildings, six kinds of ash from different power plants, BC-a, BC-b, BC-c, BCC-a, BCC-b and BCC-c, aremodified by the flotation method, and the feasibility of using modified wood biomass combustion ash as anadditive for concrete is discussed by studying its physical properties, SEM, particle size distribution, chemicalcomposition, mineral composition and other properties. The results show that wooden biomass combustion ash
removes unburned carbon and improves the particle shape through the flotation method. As an additive of concrete,
it obtains the fluidity meeting the requirements of JIS, and the activity index is also equivalent to the value specified
by JIS I. From the above results, modified wood biomass combustion ash is highly likely to be used as concrete
additive.
Keywords: Flotation method, woody biomass combustion ash, flow ratio, chemical composition, XRD/Rietveld
method
1.INTRODUCTION

Solid woody biomass fuels include wood chips,
pellets, bark, and construction waste, and havevarious properties such as moisture content, ash
content, and calorific value. Furthermore, some of theashes from burning them have a very high loss on
ignition, which is believed to adversely affect theflow properties of concrete when it is assumed to be
used as an admixture to concrete. Therefore, it isnecessary to modify WBCA using the flotation
method developed by Takasu et al. 9 ） Flotation
method is a conventional technology mainly used forcoal preparation, ore beneficiation, and deinking ofwastepaper. is a method of collecting from the bottom
10）Compared with other modification methods suchas heating modification 11） and electrostatic belt type
12 ）, the advantage of this method is that the heavy
metals contained in FA can be removed by the stirring
work of pretreatment and the microbubbles offlotation method. 13 ） Therefore, it is better to use
flotation method to modify WBCA containing a large
amount of heavy metals. However, it is not clear
whether WBCA modified by flotation method can beused as an admixture of concrete. And little is known
about the properties of woody biomass fuels as
concrete burnt ash mixtures. Therefore, in this study,
the flotation method was used to modify the special
burnt ash, the properties of the raw ash and themodified ash were clarified, and the possibility ofusing them as admixtures was investigated.

Currently, Japan's draft pledge to reducegreenhouse gas emissions under the Paris Agreement
aims to reduce energy-derived carbon dioxide (CO2)emissions by 26 percent by 2030 compared to 2013
levels. The policy aims to reduce the amount ofelectricity generated from fossil fuels such as coal in
the energy mix to meet targets, with plans to close
coal-fired power plants.1) Renewable energy has
been on the rise in recent years due to the closure ofthermal power plants. Examples of renewable energy
include solar, hydro, wind, geothermal and biomass
power generation. In particular, annual power
generation from biomass is expected to double by2030. 2 ）3）At the same time, the burning of woody
biomass fuels produces approximately 0.5% to 12%
of woody biomass combustion ash (hereafter referred
to as WBCA) from the facility. 4 ） If WBCA is not
used effectively, it is classified as industrial waste
under the provisions of the Waste Disposal and Public
Cleaning Act. 5）However, in 2013, a notice from the
Ministry of the Environment stated that "incinerator
ash that is actually used effectively and is judged to
be unnecessary is not classified as industrial waste. 6）
In recent years, research has been conducted on theeffective utilization of various substances such as
fertilizer raw materials and building materials. 7）8）472

SEE-Mie, Japan, Nov.10-12, 2022

In order to verify whether wood biomass
combustion ash can be used as an additive forconcrete in buildings, six kinds of ash from different
power plants, BC-a, BC-b, BC-c, BCC-a, BCC-b andBCC-c, are modified by the flotation method, and thefeasibility of using modified wood biomass
combustion ash as an additive for concrete is
discussed by studying its physical properties, SEM,
particle size distribution, chemical composition,mineral composition and other properties.

Concrete Engineering. Carbon content is defined as
the value obtained by adjusting the supply of oxygenand nitrogen and subtracting the results in thenitrogen environment from the results in the air
environment.The BET specific surface area wasmeasured by the BET method using a specific surface
area and pore distribution measuring apparatus(Microtrac Co., Ltd.: BELSORP MINI II). Methylene
blue adsorption is based on JCAS I-61 "Test Method
for Methylene Blue Adsorption in Fly Ash." Theparticle size distribution was measured using a laser
diffraction/scattering type particle size distribution
measuring apparatus. The chemical constituents wereidentified using a fluorescence X-ray analyzer(RIGAKU: ZSX101e). SEM images were observedwith a field emission scanning electron microscope(FE-SEM). The mineral composition was measured
by the XRD/Rietveld method using a fully automatichorizontal type multifunctional X-ray diffractometer(manufactured by RIGAKU), and analyzed using
analysis software PDXL2 (manufactured by Rigaku).

2.EXPERIMENTAL OUTLINE
2.1The Materials
Three types of woody biomass fuels BC-a, BCb and BC-c, which are woody biomass fly ash, wereused. The ash obtained by reforming it by flotation
are called MBC-b and MBC-c, respectively. BC-ahardens immediately after immersion in water andcannot be modified by flotation method. For
comparison, JIS II certified fly ash (hereinafterreferred to as FA) is called FA-R and used. In addition,
the results of burning ash of woody biomass fuel andcoal and its modified ash BCC-a, MBCC-a, BCC-b
and MBCC-b used in our previous study are shown in
the following figure.

3.RESULT AND DISCUSSION
3.1 Physical properties of each Fly ash
Table 2 shows the physical properties of each fly
ash. Focusing on the loss on ignition, the raw ash of
woody biomass fly ash other than BC-b does not meet
the JIS standard. BC-c does not meet the JIS standard
even after modification, but the carbon content issignificantly reduced. From this, it is considered that
MBC-c has other substances with loss on ignition.
The specific surface area of all fly ashes is ofcomparable quality to JIS II.

2.2Experimental items and methods
As a pretreatment for flotation, wood biomass fly
ash, water and kerosene were added and stirred witha high-speed stirring mixer. Table 1 shows theconditions of the pretreatment. After that, pine oil wasadded, and the flotation method was carried out for
30 minutes.
The experimental items are density, moisture,
specific surface area, loss on ignition, carbon content
measured by differential thermogravimetric analysis,
flow value ratio, activity index, BET specific surface
area, methylene blue adsorption, SEM image, particle
size distribution, chemical composition, mineralcomposition.
Density, moisture, specific surface area, loss on
ignition, flow rate ratio, activity index was carried out
in accordance with JIS A 6201 "Fly ash for concrete".
The carbon content by differential thermogravimetricanalysis was measured according to the "Concrete
Test Analysis Handbook" of the Japan Society of

3.2 SEM image
Photo 1 shows the SEM images of each ash. For
the 500x image, it was confirmed that the FA-R
particles were nearly spherical, while the woody
biomass burning ash particles had a distorted shapeand that the shape and size varied by ash species.
Furthermore, when the raw Fly ash and the modified
Fly ash are compared, it can be confirmed that themodified ash has a significantly smaller particle size.
It is believed that this is because flotation and its prestirring have such an effect. Furthermore, for the
5000x image, the modified fly ash particles have acleaner surface than the original fly ash particles.
However, even with the reforming of woody biomass
combustion ash, the original particle shape isdistorted, Therefore, it is difficult to make it into astate with many spherical particles like FA-R, and it
is unlikely to obtain the same fluidity as FA-R whenused as an admixture for concrete. A large amount of
unburned carbon was confirmed in BC-a with thehighest adsorption of methylene blue (red part inTable 1 Pre-mixing conditions
Symbol

MBCC-a
MBCC-b
MBC-b
MBC-c

Raw
Fly
ash
[kg]

2.0

Stirring
time
[min]

3.0

5.0

Water
additionamount[%]30.0

Kerosene
additionamount[%]Pine oiladditionamount
[%]

5.0

0.5

1.0

0.1

5.0

0.5

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Table 2 Physical properties of fly ash

Photo 1 SEM image (top: 500x, bottom: 5000x)
Photo 1.

biomass combustion ash was higher than that ofFA, but since K was not present at all in BC-a andBC-b, the chemical composition of fly ash wasdifferent when the types of woody biomass fuels weredifferent.

3.3 Particle size distribution
Figure 1 shows the particle size distribution ofeach ash. In contrast to FA-R, which has no 100-1000
micron particles, woody biomass combustion ash
contains all of it. With the modified BC-b and BC-c,the proportion of coarse particles decreased and the
proportion of fine particles increased. It is believedthat this is because the flotation process removes
unburned carbon causing coarse particles and cleans
the particle surface.In addition, the proportion ofparticles of MBC-b smaller than 10 μm is higher thanthat of FA-R, and previous studies reported that FAwith a higher amount of fine particles tends to have ahigher activity index, so the activity index of WBC-b
is higher than that of FA-R .

3.5 Mineral composition
Figure 3 shows the mineral composition of eachash by the Rietveld method. The main minerals of FA
are quartz, mullite and magnetite. It was confirmedthat the proportion of these minerals in the total
woody biomass combustion ash was greater than thatof FA-R. In addition, woody biomass combustion ash
other than BC-b and MBC-b has a higher crystalline
phase ratio than FA-R. Since the crystalline phase isa substance that is easily crystallized when water isadded, it can be said that the crystallization ratio inwoody biomass combustion ash increases when water
is added. Judging from the results of loss on ignition
in previous studies, it is believed that this is the reason
for the increase in the amount of weight loss material
after adding water to woody biomass combustion ash.
Furthermore, BC-a has no glass (amorphous phase)and is all crystalline, showing significantly different
results from the other ashes. It is believed that this is
the reason why BC-a solidifies immediately after
being immersed in water at the time of flotation.
Therefore, if the raw ash has a large amount ofcrystalline phases, it cannot be upgraded by flotation.
It is known that the reaction rate of FA increases with

3.4 chemical composition
Figure 2 shows the chemical composition ofeach ash. The Si content in the special fired ash does
not meet the JIS standard whether it has been
modified or not. The Ca content of BC-a and BC-b ishigher than that of Si and Al, which is significantly
different from that of FA-R. In general, SiO2 andAl2O3 in FA are known to be involved in pozzolanic
reactions, so BC-a, BC-b, and MBC-b are expected tohave lower pozzolanic reactivity than FA-R. Previous
studies reported that the proportion of K in woody
474

SEE-Mie, Japan, Nov.10-12, 2022

100

100

100～1000μm

Si
Al

80

50～100μm

Quantitative value [%]Content rate [%]80

10～50μm

60

5～10μm

40

1～5μm

20

Ca
Fe

60
K
Ti

40
Zr
Mg

20

Others

FA

MBC-c

BC-c

MBC-b

BC-b

BC-a

MBCC-bBCC-a

Fig.1 Particle size distribution

BCC-b

Ig.loss

0

MBCC-a

FA-R

BC-c

MBC-c

MBC-b

BC-a

BC-b

BCC-b

MBCC-b

BCC-a

MBCC-a0.1～1μm
0

Fig.2 chemical components

100
Glass

Quartz80

Quantitative value [%]0.96, which is a very high value, indicating that theflow-value ratio of woody biomass combustion ash
can be evaluated by LOI. Figure 6 shows the activity
index of each ash. The woody biomass fly ash values
were very high at 7 days of age. Since woody biomass
fly ash contains a large amount of Ca, it is possible togenerate a large amount of aluminate. Therefore, theactivity index is very high initially. Since all woody
biomass fly ash showed values equivalent to JIS class
I at 28 days, it is likely that significant amounts ofchlorophyll were also produced.
Figure 7 shows the correlation of the 28-day-old
activity index with each item. Originally relevant is
the loss on ignition, but its coefficient ofdetermination is as low as 0.6. Although not shown
due to space limitations, we also investigated therelevance of other items. However, no particular
correlation has been demonstrated. The reason forthis is thought to be that the chemical and mineralcomposition of woody biomass combustion ash
varies by type, But in the future we will analyze thereaction rate and CH amount of the cement slurry
mixed with woody biomass combustion ash, and plan
to study the water and reaction changes in detail.

Mullite60
Magnetite

40
Calcium Hydroxide

20

FA-R

MBC-c

BC-c

MBC-b

BC-a

BC-b

MBCC-b

BCC-b

BCC-a

Ig.loss

MBCC-a0

OthersFig.3 Mineral composition
the amount of glass. Since the amount of glass in BCb and MBC-b is larger than that in FA-R, the reaction
rate is high and the activity index may be higher thanthat in FA-R.
3.6 Flow ratio and activity index
Figure 4 shows the flow value ratio for each ash
type. Although the fluidity change of BC-b is difficult
to confirm by modification, BC-c can be improved toa level comparable to JIS type III by modification.
Since the particle size distribution of BC-c did notchange due to the modification and the carbon content
changed significantly, it is considered that the change
in particle shape and the reduction in carbon content
have a great influence on the fluidity. Figure 5 shows
the relationship between the flow value ratio and each
item. Since the unburned carbon of FA is said toadversely affect the fluidity of concrete, a correlation
between the flow value ratio and the amount ofmethylene blue adsorption was predicted, but asufficient correlation was not obtained in this study.
However, its coefficient of determination with LOI is

4.CONCLUSION
In this study, woody biomass fly ash was
modified by flotation method to clarify the propertiesof raw ash and modified ash, and to explore thepossibility of using it as a concrete admixture.
Flotation is not suitable for woody biomass fly
ash containing a large amount of crystalline phasebecause it hardens due to increased crystallization
when water is added. The wood biomass fly ash was
upgraded by flotation method to remove unburned
carbon and improve particle morphology. When themodified fly ash was used as an admixture, thefluidity equivalent to the JIS standard was obtained,
indicating that the fluidity could be evaluated by the475

SEE-Mie, Japan, Nov.10-12, 2022

Raw fly ash

110

110

Modified fly ash

120

2

activity index [%]R =0.96

Flow ratio[%]

100
80
60

100

100

90

90

80

80

70

70

R2=0.76

40
60

0

10

60
20 2000

15

BCC-a

BCC-b

BC-b

BC-c

FA-R

Fig.4 Flow ratio
BCC-a
MBCC-a120

BCC-b
MBCC-b

BC-b
MBC-b

BC-c
MBC-c

FA-R

110

100

90

Activity index for 27 days of curing [%]

0

3000

4000

5000

6000

7000

specific surface area [m2/g]

loss on ignition [%]20

activity index[%]5

Fig.5 The relationship between the flow ratio andeach item
110

105

105

100

100

95

95

90
90

85

85

R2=0.60

80

80

75

R2=0.34

75

70
0

5

10

15

loss on ignition [%]

20

70
5

10

15

20

25

30

35

40

Constant value of Ca[%]

80

70

60

Fig.6 The relationship between the 28 days activity
index and each item
0

20

40

60

80

100

age [Days]

REFERENCES

Fig.5 activity index[1] https://www.meti.go.jp/shingikai/enecho/denryo
ku_gas/denryoku_gas/pdf/026_03_00.pdf%E3%
80%80%EF%BC%88%E9%96%B2%E8%A6%
A7%E6%97%A5%EF%BC%9A2021.
[2] https://www.isep.or.jp/archives/library/13188[3] http://www.env.go.jp/earth/ondanka/ghg/mat01_i
ndc.pdf[4] https://www.enecho.meti.go.jp/statistics/total_energy/results.html#headline7%EF%BC%88%E9%96%B2%E8%A6%A7%E6%97%A5%EF%B
C%9A2021[5] https://www.jwba.or.jp/explanation/heat/%EF%
BC%88%E9%96%B2%E8%A6%A7%E6%97%
A52021%E5%B9%B410[6] https://elaws.egov.go.jp/document/lawid=345AC
0000000137[7] http://www.env.go.jp/recycle/waste/reg_ref/no_1306282.pdf%EF%BC%88%E9%96%B2%E8%A6%A7%E6%97%A5%EF%BC%9A2021[8] Yuki Nojima: Outline of Revision of the
Fertilizer Control Law and Fertilizer Use of
Woody Biomass Combustion Ash, Journal of theEnergy Society of Japan, Enerumikusu, Vol. 100,
No. 1, pp.74-80, 2021u[9] Akihiro Maekawa et al. 4 people: Basic researchon various properties of hardened mortar for

loss on ignition of woody biomass combustion ash. In
addition, the activity kinetic index of the modified fly
ash showed a value equivalent to JIS type I.
Therefore, it can be said that there is a high possibility
that the modified woody biomass fly ash can be used
as an admixture
ACKNOWLEDGMENTS
The authors acknowledge the assistance in thiswork provided by Eiji Mikura and Yuxin Wang. This
work was supported by Environment Research andTechnology Development Fund, Environmental
Restoration and Conservation Agency of Japan(ERCA) (JPMEER F20213G03).

476

45

SEE-Mie, Japan, Nov.10-12, 2022

mixed woody biomass incinerators, Journal of
the Society for Recycling of Waste Resources,
Vol. 29, pp.209-210, 2018[10] Koji Takanashi et al. 2: Characteristics of
unburned carbon in concrete by flotation andusing fly ash slurry, Architectural Society ofJapan Papers on Structures, Vol. 73, No. 1,
pp331-pp334, 2014[11] Lee Sohwa et al. 3: Retrofit of coal ash by wind
power
generation processing pulverizing systemequipped with firing process, Annual Journal ofConcrete Engineering, Vol. 29, No. 1, pp. 183188, 2007Tadashi Misawa: New Supplemental
Classification/Classification, C[12]Etsuro Sakai et al 3: Properties of Fly Ash
Removal of Unburned Carbon with Electrostatic
Belt Classifier, Cement/Concrete Paper, Vol. 73,
Issue 1, Pages 65-70, 2019[13] Yusuke Sakai and 3 others: Adjustment of fly ash
particle size and removal of heavy metal components
by a continuous processing system, Steel, Vol. 103,
No. 3, pp. 166-173, 2017477

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EXAMINING WATER ENVIRONMENT DATA FOR AN ARTIFICIALINTELLIGENCE EVALUATION MODEL
Shengping Zhang1 and Jie Qi2Faculty of Urban Science, Meijo University, Japan.
2
School of International Studies, Utsunomiya University, Japan.
1

ABSTRACTThe objective of this study is to discover the most effective water environment improvement measures for the
109 most important watersheds of Japan, which are well-known Class-A watersheds under the jurisdiction of theJapanese government. An artificial intelligence (AI) model has been created by applying Deep Learningtechnologies, and watershed information from 109 watersheds has been collected as teacher data to train the AI
model. This study aims to find the best way to present the water environment data to an artificial intelligencemodel. In order to provide the most reliable water quality estimations, three different ways of water environment
data presentation have been examined. It has been identified that presenting the raw environment data to the AI
model as teacher data is the best way for building an AI model. This study concludes by pointing out that
preprocessing data will cause information loss of teacher data and will also add biased information into teacher
data. Therefore, using raw data without preprocessing as teacher data will help build a more reliable AI model. It
is hoped that this study will contribute to establishing a more reliable river environment planning and management
methodology.
Keywords: Water Environment Evaluation, Artificial Intelligence (AI) Model, Teacher Data, Data Preprocessing

INTRODUCTION

environment data with or without preprocessing
mentioned above.
The ultimate goal of this study is to find the best
way to present water environment data to an AI modelin order to create a more reliable water environment
evaluation AI model.

Artificial intelligence (AI) model has been widely
applied to water environment evaluation and planning[1], [2]. The reason why an AI model has been chosen
is its powerful capability of processing various types
of water environment data such as numerical data,
categorical data, image data. It does not require any
specific categorizations while presetting data to AI
model [3], [4].
This powerful capability of AI models, however,has raised a critical question: as the teacher datarequired for AI model training, what is the best way
to present water environment data to an AI model? A
typical water quality index BOD (Biochemical
Oxygen Demand) usually can be recorded andrepresented at least in three different ways: 1) BOD ismostly mentioned in the raw numerical data form thathas the unit mg/l; 2) BOD is also quite frequently
represented by its class according to the water
Environment Quality Standards (EQSs) such as Class
AA, Class A, etc.; 3) BOD is the categorical yes/noanswer to the question whether the administrational
water environment management goal has beenachieved. The numerical raw data form is the mostbasic form of BOD data, and the other two forms are
the preprocessed results. The most common
preprocessing includes filtering and converting, andboth EQSs and administrational water environment
management goals are served here as a filter. An AI
model is capable of dealing with each form of water

ARTIFICIAL INTELLIGENCE MODEL
An artificial intelligence model, specifically aneural network model has been adopted to compose awater environment evaluation method for evaluationor prediction problems due to the suitability of neuralnetwork models [4], [5].
Structure of Neural Network [5]A neural network is a network system constructed
artificially by idealizing the neurons (nerve cells), andconsists of a number of nodes and lines that are called
units and connections (or links) respectively. Basedon the differences in network structures, neuralnetworks generally are classified into two types:
layered networks and interconnected networks. It has
been shown that a layered network is suitable for
evaluation/prediction problems due to its abilities inlearning (self-organization) and parallel processing of
information.
A typical layered neural network, which has alayer of input units at the top, a layer of output units
at the bottom, and a number of hidden layers between
478

SEE-Mie, Japan, Nov.10-12, 2022

the input layer and the output layer. Connections exist
only between the units in the adjacent layers andconnections within a layer or from higher to lower
layers are forbidden.

through proper learning processes [6]. The potentialof this model has been verified with similar problem
to this study [3,], [4].
Learning Process of Neural Network Model

Modelling a Neural Network
For a neural network model, the process of setting
the connection weights unit thresholds is called
learning. The term learning here means the selforganization process through which the neuralnetwork model automatically adjusts all theparameters (i.e. all the connections and thresholds) tothe appropriate values, when a series of samples of
input-output data (called teacher data or teacher
signals) are shown to the model. If we consider the
information processing in a neural network model asa transformation of input data to output data, thenmodel learning can be considered to be a process
through which the neural network model gradually
becomes capable of imitating the transforming
patterns represented by the teacher data.
A lot of learning algorithms have been proposed,
and among them the Error Back Propagation
Algorithm is the most widely used and mostsuccessful algorithm. The following is the summaryof the Error Back Propagation Algorithm [7].
Suppose T sets of teacher data are given.

For the sake of simplicity, a neural network can
be considered as a unit consisting of three layers: let
the unit numbers of the input layer, hidden layer andoutput layer be N, M and 1, respectively. When an
input {𝐼𝑖 , 𝑖 = 1,2, ⋯ , 𝑁 } is given to the units of the
input layer, the inputs and outputs of the hidden layer
units as well as the output layer units are represented
as follows.
𝑌𝑗 = 𝑓(𝑋𝑗 ), 𝑗 = 1,2, ⋯ , 𝑀(1)𝑁

𝑋𝑗 = ∑ 𝑤𝑖𝑗 𝐼𝑖 + 𝜃𝑖 , 𝑗 = 1,2, ⋯ , 𝑀

(2)

𝑖=1

𝑂 = 𝑓 (𝑍 )(3)𝑀

𝑍 = ∑ 𝑤𝑗 𝑌𝑗 + 𝜃

(4)

𝑗=1

(𝑡)

1
1 + 𝑒 −𝑥(6)

Notice that the teacher data consists of two parts: the(𝑡) (𝑡)(𝑡)input part {𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁 ; 𝑡 = 1, 2, ⋯ , 𝑇} andthe output part{𝑂(𝑡) ; 𝑡 = 1,2, ⋯ , 𝑇} .
Now consider an initial value
[𝑘]

[𝑘]

[𝑘]

𝑤𝑖𝑗 , 𝑤𝑗 , 𝜃𝑗 , 𝜃 [𝑘] , 𝑘 = 0(7)

for each of the connection weights and thresholdvalues, respectively. Notice that the superscript [k]indicates the number of learning iterations and [k=0]means the initial values for all the parameters directly
preceding the start of the learning process. Then the
outputs corresponding to the inputs of the teacher data(𝑡) (𝑡){𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁(𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇} can be obtained
from Eq. (1) ~ Eq. (5). Let these outputs be{𝑈 [𝑘](𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} .
Clearly,{𝑈 [𝑘](𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} are different
from the outputs of the teacher data {𝑂(𝑡) ; 𝑡 =1,2, ⋯ , 𝑇}, and an error function can be defined withthe two different kinds of outputs as follows.

For the unit output function 𝑓 (∙) , some
expressions have been proposed. The following
Sigmoid function has been applied frequently.
However, it is not necessarily the best one in terms oflearning efficiency. A testing process for different
output functions is strongly suggested. In this studied
this Sigmoid function has been finally adopted after
careful tests.
𝑓 (𝑥 ) =(𝑡){𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁(𝑡) , 𝑂(𝑡) ; 𝑡 = 1,2, ⋯ , 𝑇}

Where 𝑌𝑗 : output from the unit 𝑗 of the hidden layer.
𝑋𝑗 : input the unit 𝑗 of the hidden layer.
(𝑓 ∙) : unit output function.
w𝑖𝑗 : connection weight between the input
layer unit 𝑖 and hidden layer unit 𝑗.
𝜃𝑗 : threshold value of the hidden layer unit 𝑗
O : output from the output layer unit.
Z : input to the output layer unit.
w𝑗 : connection weight between the hidden
layer unit 𝑗 and the output layer unit.
Θ : threshold value of the hidden layer unit 𝑗(5)

Theoretically, the neural network model
expressed by Eqs. (1) through (5) is able toapproximate any non-linear relationship between
inputs and outputs with any degree of accuracy byusing enough hidden layer units and setting
connection weights and thresholds to be appropriate

𝑇

𝑅

[𝑘]

2

= ∑(𝑂(𝑡) − 𝑈 [𝑘](𝑡) ) , 𝑘 = 0

(8)

𝑡=1

Obviously, 𝑅 [𝑘] is a function of connection479

SEE-Mie, Japan, Nov.10-12, 2022

weights and threshold values because {𝑈 [𝑘](𝑡) ; 𝑡 =[𝑘]1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} are calculated after all 𝑤𝑖𝑗 ,[𝑘]through a deep learning process by using waterenvironment-related data.
In this study, the data obtained from the water
quality survey conducted for the 109 Class-A riversof Japan are used for the deep learning process [8].
The data are stored in an open source database that ismaintained by Ministry of Land, Infrastructure,
Transport and Tourism of Japan.
After a careful data verification process, only 104
rivers out of 109 Class-A rivers are chosen to be
included in the teacher data set for deep learning
because there are quite a few of data missing for theother 5 rivers. For each river the data includes 58
water environment items as shown in Table 1. The
data records used in this study are from 1998 to 2018with a duration of 21 years long.
The 58 environment items are divided into twoparts to form a teacher data set, evaluation goal
variables and explanation variables. The evaluation
goal variables include the five environment items thatare used to define The Water Environment Standards
for Rivers as shown in Table 2 [9], which are pH,
BOD, SS, DO and Total coliform. All theenvironment items are used to explain how theachievement of water environment standards are
impacted.

[𝑘]𝑤𝑗 , 𝜃𝑗 𝑎𝑛𝑑 𝜃 [𝑘] are given.
The Error Back Propagation Algorithm makes useof the connection weights and threshold values thatminimize the above error function 𝑅[𝑘] . Usually anon-linear programming method is required to solve
the optimization problem along with an iteration
process in order to obtain the optimal (but possibly
suboptimal) connection weights and threshold values.
The final iteration procedures derived from a nonlinear programming method known as the Method of
Gradient Descent are as follows.
𝑇
[𝑘+1]

𝑤𝑗

[𝑘]

= 𝑤𝑗

[𝑘](𝑡)− 𝜂 ⋅ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑌𝑗

(9)

)

𝑡=1
𝑇

𝜃 [𝑘+1] = 𝜃 [𝑘] − 𝜂 ⋅ ∑ 𝛿 [𝑘](𝑡)

(10)

𝑡=1
𝑇
[𝑘+1]

𝑤𝑖𝑗

[𝑘]

[𝑘+1]

= 𝑤𝑖𝑗 − 𝜂 ⋅ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑤𝑗[𝑘](𝑡)⋅ 𝛾𝑗(𝑡)⋅ 𝐼𝑖 )

(11)

𝑡=1
𝑇
[𝑘+1]

𝜃𝑗

[𝑘]

[𝑘+1]

= 𝜃𝑗 − 𝜂 ∙ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑤𝑗[𝑘](𝑡)

⋅ 𝛾𝑗

)

(12)

𝑡=1

Presenting the Teacher Data

where the superscript [k] indicates the number oflearning iterations as mentioned earlier, and η is asmall positive number that indicates the step size of
the Method of Gradient Descent for optimization
iteration process. The other variables which occurredin the final learning procedures are defined as follows.
𝛿 [𝑘](𝑡) = (𝑂(𝑡) − 𝑈 [𝑘](𝑡) ) ∙ 𝑂(𝑡) ∙ (1 − 𝑂(𝑡) )[𝑘](𝑡)

𝛾𝑗[𝑘](𝑡)= 𝑌𝑗[𝑘](𝑡)∙ (1 − 𝑌𝑗)

In this study, the evaluation goal variables of theteacher data have been presented to the environment
evaluation AI model in the following three different
ways in order to identify the best way of teacher data
presentation by comparison.
The most basic way is to present the raw data ofwater quality directly to AI model. All the fiveenvironment items, pH, BOD, SS, DO and Total
Coliform are presented as continuous numerical raw
data to AI model as teacher data.
The second way is to present the achievement
degree of water Environment Quality Standards to the
AI model instead of the raw water quality data. The
achievement of EQDs has been scored with an effort
to make the final scores for different standard classes
that are corresponding to different water use purposesa uniform distribution, which is expected to maximize
the score distance between different standard classes.
The results are shown in Table 3.
The third way is to present AI model with thecategorical yes/no data whether administrational
water environment management goal has beenachieved for each water quality item.
Needless to say, the explanation variables of theteacher data are presented as raw data without any
pre-processing in spite of the very basic andreasonable question whether this is the best way topresent the explanation variables to AL models isremained to be answered, which is beyond theresearch purpose of this study though.

(13)
(14)

In order to avoid the overfitting (or over-learning)problem, a criterion is usually required to make a
judgement when the iterative learning process shouldbe terminated. In this study the learning process will
be stopped when the Mean Relative Error (MRE) of
the outputs is less than a specified relative error
expectation for prediction/evaluation results, which is
a common treatment for a learning process of teacher
data with random errors (i.e. white noise). Needlessto say, this error expectation should be set according
to the required accuracy of the problem which is
being dealt with.
ENVIRONMENT DATA PRESENTATIONSTeacher Data
In order to apply the neural network model
proposed above to a water environment evaluation
problem, the model has to be trained appropriately
480

SEE-Mie, Japan, Nov.10-12, 2022

Table 1 Water environment items of teacher data
Category (Number of Items)

Water Environment Item
Month
Hour

Year
Day

Time of Sampling (4)River/Flow Conditions (17)Watershed Conditions (7)Water Quality Indexes For The
Living Environment (10)Water Quality Indexes About
Human Health (9)Water Quality Index For Inflow Of
Domestic Wastewater (1)Place of Sampling
Water Level
Total Water Depth
Temperature
Vertical Visibility
Water Smell
Time of Low Tide of Sampling Day
Time of High Tide of Sampling Day
Visual Appearance:
Water Color
Turbidity (Muddiness)

WeatherQuantity of Flow
Water Depth of Sampling
Water Temperature
Horizontal Visibility

Length of Main Stream
Catchment Population
Annual Average Stream Flow
Number of Hydraulic Power Plants

Catchment Area
Number of Tributaries
Number of Dams

Flow Strength
Floating Waste/Garbage

pH
BOD
COD
SS
DO
Saturation Degree of DO
Total Coliform
The Amount of N-Hexane Extract (Oil)Total Nitrogen
Total Phosphorus
Cadmium
Lead
Arsenic
Alkyl Mercury
Dichloromethane

CyanogenHexavalent Chromium
Total Mercury
PCB

Ammonium Nitrogen
Chromaticity
Turbidity
Evaporation Residues
Total Hardness
Potassium Permanganate Consumption
SodiumIron
Manganese
Aluminum
Residual Chlorine

Others (10)

(7 categories in total)(58 items in total)

Table 2 Water environment quality standards for rivers [9]Standard Value
Item
Class

AA
A
B
C
D
E

Water Use
Water supply class 1, conservation ofnatural environment and uses listed in
A-E
Water supply class 2, fishery class 1,
bathing and uses listed in B-E
Water supply class 3, fishery class 2,
and uses listed in C-E
Fishery class 3, industrial water class
1, and uses listed in D-E
Industrial water class 2, agriculture
water, and uses listed in E
Industrial water class 3
conservation of environment

andHydrogen-ion
Concentration(pH)

Biochemical
OxygenDemand(BOD)

Suspended
Solids(SS)

Dissolved
Oxygen(DO)

Total Coliform

6.5≤pH≤8.5≤1 ㎎/L≤25 ㎎/L≥7.5 ㎎/L≤50MPN/100mL

6.5≤pH≤8.5≤2 ㎎/L≤25 ㎎/L≥7.5 ㎎/L

6.5≤pH≤8.5≤3 ㎎/L≤25 ㎎/L≥5.0 ㎎/L

6.5≤pH≤8.5≤5 ㎎/L≤50 ㎎/L≥5.0 ㎎/L≤1000MPN/100m
L≤5000MPN/100m
L-

6.0≤pH≤8.5≤8 ㎎/L≤100 ㎎/L≥2.0 ㎎/L-≤10 ㎎/L

Floating mattersuch as garbage
should not been
observed≥2.0 ㎎/L-

6.0≤pH≤8.5

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SEE-Mie, Japan, Nov.10-12, 2022

Table 3 Scoring of achievement degree of EQSs
𝐻𝑖𝑡𝑠(𝑈)

Threat Score(U) = 𝐻𝑖𝑡𝑠(𝑈)+𝐹𝑎𝑙𝑠𝑒(𝐴)+𝐹𝑎𝑙𝑠𝑒(𝑈)Water quality class ranked with EQSs forconservation of the living environment

Score

AA
A with indexes ranked in AAA
B with indexes ranked in A or higher
B
C
D
E
Below E

0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1

Table 4 Comparison of administrational
management goal achievement results
Estimation resultsby AI Model
Achieved
Unachieved

As we explained previously, the neural networkmodel has been trained (put under a learning process)with the collected teacher data. The training process
is based on the learning procedures but it is still aprocess of trial and error because there are still many
details that remain undecided, such as a suitable step
size of optimization, a suitable output function, an
efficient order to present the teacher data to the neuralnetwork model, and a proper initial network size(layers and units in each layers). The learning process
was stopped after the trained neural network model isable to reproduce the entire teacher data with anacceptable error, which was set in this study to be
below 2% in mean relative error.

Comparison Result Discussions
As shown in Table 5, the three different data
presentation ways have been compared based on thethree indexes defined above for year 2019, which isright after the teacher data duration.
Table 5 Estimation results of administrational
management goal achievement during 2019

COMPARISON OF DATA PRESENTATIONS

Way of data
presentation

In order to identify which of the three presentation
ways of the teacher data helps construct a better AI
model, this study have compared the estimation
results of administrational environment management
goal achievement by the Al models with theobservation results for the year of 2019 (including
four season results), which is right after the teacher
data duration 1998-2018. The administrational
environment management goal achievement has beenchosen as the comparison item because it is acommon output that three trained AI models cangenerate.

Raw data ofwater quality
Water EQSs
Class score
Management goal
achievement

The following three well-established statisticalevaluation indexes for comparing the presentation
ways of teacher data have been defined based on thecomparison results of the AI model estimation andobservation as shown in Table 4 [10].

𝐻𝑖𝑡𝑠(𝐴)

Threat Score(A) = 𝐻𝑖𝑡𝑠(𝐴)+𝐹𝑎𝑙𝑠𝑒(𝐴)+𝐹𝑎𝑙𝑠𝑒(𝑈)Accuracy

ThreatScore(A)

ThreatScore(U)

96.88%

96.22%

84.71%

92.55%

90.96%

70.19%

97.12%

96.57%

84.62%

From Table 5 demonstrates that scoring theteacher data according to the water EQSs classgenerated the worst estimation results of the threedifferent ways of teacher data presentation. A
reasonable explanation about this result is that both
the water EQSs and the scoring process are either
subjective or arbitrary, which means they havebasically been decided for human conveniences or
calculational purposes without any considerations of
the water quality evolution processes. These possiblybiased human pre-processing added to the teacher
data have clearly damaged the reliability of theoriginal raw teacher data.
The above hypothesis is also consistent with thefact that the AI model with the raw data as teacher
data generated the best water quality estimation interms of threat score (U). this is because the raw data
without any pre-processing, just as expected, include

Indexes for Comparison

𝐻𝑖𝑡𝑠(𝐴)+𝐻𝑖𝑡𝑠(𝑈)Observation results
Achieved UnachievedHits(A)
False(A)
False(U)
Hits(U)

Accuracy is the most common index to compare
different models. The threat Score is used to measure
how well each model is able to hit the target (achievedor unachieved). Threat score(A) usually is used when
the achievement rate is emphasized, and Thread
Score(U) is used when the un-achievement rate isemphasized. All the three indexes are defined
between 0 to 1, and 1 means an ideal estimation.

Training of Neural Network Model

Accuracy = 𝐻𝑖𝑡𝑠(𝐴)+𝐹𝑎𝑙𝑠𝑒(𝐴)+𝐹𝑎𝑙𝑠𝑒(𝑈)+𝐻𝑖𝑡𝑠(𝑈)

(17)

(15)
(16)

482

SEE-Mie, Japan, Nov.10-12, 2022

all the original information about the hidden water
quality natural evolution processes.
As a matter of fact, the categorical teacher data of
the administrational management goal achievements
help AI model generate even better water quality
estimation results in terms of both accuracy and threatscore(A) than the AI model trained with raw data does.
The reasonable explanation is that the outputs of the
AI model trained with the administrational
management goal achievements, are exactly the
results that are used in comparison indexes.
Considering the fact that the differences in thecomparison indexes between the two models are
small enough to be ignored although the AI modeltrained with the raw data even has not been given any
information on the administrational management goal
achievements, it is reasonable and fair enough tojustify the hypothesis that the AI model trained withthe raw data is more reliable than the other models
trained with different teacher data in terms of
producing accurate water quality estimations. Simply,
raw data without any preprocessing are the bestteacher data.

information loss of the teacher data or add biased
information into the teacher data, while raw data
without preprocessing will serve as the best teacher
data, and help build a more reliable AI model.
Needless to say, this hypothesis remains to be further
examined.
Moreover, this hypothesis does not deny any
necessary teacher data preprocessing if the
preprocessing serves the research purpose very well.
For example, if the only purpose of building an AI
model is to answer the question whether
administrational water environment management
goal will be achieved, preprocessing water quality
data into a categorical yes/no data still can provide aquite satisfied answer.
Further research will focus on applications of thewell-trained AI model, such as identifying the mostinfluential water environment factors/items as well as
the most effective water environment improvement
measures for each river of the 104 Class-A rivers that
contribute to the teacher data. These researches all
together are expected to contribute to establish a morereliable river environment planning and management
methodology.

CONCLUSIONSREFERENCES
With the purpose to built a reliable artificial
intelligence model for water environment evaluationand planning, this study examined different ways inwhich teacher data are presented to an AI model for
its training process or learning.
Artificial
intelligencemodelsaresocomprehensive and powerful that they are capable todeal with various kinds of teacher data such as
numerical data, categorical data and image data. Data
pre-processing techniques allows model-builders
convert data types so that the well-trained AI model
can server the model-builder’s purpose better.
This study has examined three different water
environment data types (or three different ways ofteacher data presentation) as teacher data for AI
model training, and water quality estimation results.
In order to identify what kind of teacher data help
build a better AI model in terms of accuracy of water
quality estimation, the well-trained models have been
compared with observation results.
The results have shown that the raw water quality
data without any pre-processing generated a better AI
model than the other two teacher data types with preprocessing. Furthermore, the teacher data
preprocessed slightly with a simple criterion about
whethertheadministrational
environment
management goals have been achieved, generated aneven better final model than the heavily-preprocessed
teacher data based on the complicated water EQSs forrivers.
Based on the above results, a hypothesis can beformed: preprocessing raw data will possibly cause[1] Hagihara Y. and Hagihara K. ed., Planning of
Urban Water and Green Space, Kyoto University
Press, 2010.
[2] Urban Science Study Group, ed., Introduction of
Urban Science, Soseisya Publisher, 2020, pp.3550.
[3] Zhang S. P. and Kido Y., A Study on theEnvironment Evaluation method for Aise Riverand the Effectiveness of River Environment
Improvement Measures, Urban Science Studies,No. 21, 2016, pp. 45-56.
[4] Zhang S.P. and Qi Jie, Evaluating Habitability ofWater Environments for Fireflies with an
Artificial Intelligence Model, International
Journal of GEOMATE, April, 2020, Vol.18, Issue
68, pp. 87 – 93.
[5] IPA, WHITE PAPER Artificial Intelligence 2019,
Kadokawa Publisher, 2018.
[6] Asou H., The Information Processing by Neural
Network Models, Sangyo Publisher, 1988. pp. 125-132.
[7] Rumelhart D. E., Hinton G. E., and Williams R. J.,
Learning Representations by Back-propagating Errors,
Nature, Vol. 323, No. 9, 1986, pp. 533-536.
[8] Ministry of Land, Infrastructure, Transport andTourism of Japan, Water Information System,
http://www1.river.go.jp/ (an Online Open Source
Database).
[9] Ministry of Environment of Japan, Environmental
White Paper, 2020.
[10] Scharfer J. T., The Critical Success Index as an
Indicator of Warning Skill, Weather Forecasting, No.5,
1990, pp.570-575.

483

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

FEASIBILITY OF USING BAUXITE RESIDUE STABILIZED WITH
CEMENT KILN DUST FOR GEOETCHNICAL APPLICATIONSMohamed Farid Abbas 1,2 and Sultan Abdulaziz Almuaythir 1
College of Engineering, Prince Sattam Bin Abdulaziz University, Saudi Arabia; 2 Soil Mechanics andGeotechnical Engineering Research Institute, Housing and Building National Research Center (HBRC),
Egypt
1

ABSTRACT
Bauxite residue (BR) is an industrial waste generated during the processing of bauxite into alumina using theBayer process. For every ton of alumina produced, approximately 1 to 1.5 tons of red mud are also produced. Dueto this high level of production and the material's high alkalinity, it can pose a significant environmental hazard.
Given the high cost of storage and its high level of toxicity inflicted on this material, it is of a paramount importance
to examine the probable approaches for recycling this residue and use it as construction material. This study
examines the feasibility of using Cement Bypass Dust (CKD) for BR stabilization. Geotechnical properties were
examined, including compaction parameters, volume change, and unconfined compressive strength for a different
mixture containing different doses of CKD. Oedometer testing indicated optimum content of the CKD for swellpotential as 2.5 %. Unconfined compressive strength testing indicated that UCS increased with adding CKD andcuring period and addition of 7.5% of CKD increased the undrained stability by almost three times, indicating its
effectiveness.
Keywords: Bauxite residue, Cement Bypass Dust, Stabilization, Volume Change, Unconfined Compressive
Strength
INTRODUCTION

properties of CKD. The dust from each plant can varysignificantly in chemical, mineralogical, and physicalcomposition since plant operations differ
considerably in raw feed, type of operation, dust
collection facility, and type of fuel used [14]. The
physical characteristic of CKD materials is highly
alkaline with pH between 12 to 14 and the gradation
ranging from 0.03 to 0.30 mm. The specific gravity
and the surface area for the materials are 2.6 to 2.8
g/cm3 and 4600 to 14000 cm2/g, respectively [15][17].
Some studies investigated the use of CKD instabilization of soils [18]-[23] and recommended its
use for enhancing the geotechnical properties and asalternative for other costly stabilizer such as cement
and lime.
Stabilizing BR with the CKD has received little
attention in the literature. For example, no specificstudies are available in the literature regarding thesuitability of red mud stabilized with cement kiln dust
to be used in civil engineering applications
The present research work is related to studying
the suitability of stabilizing BR with CKD for
geotechnical engineering applications. Several CKD
doses is examined and their impact on main
geotechnicalengineeringcharacteristics
isdetermined.

Bauxite residue (BR), or termed as red mud, is awaste material generated by the alumina industry via
the Bayer process. Bauxite residue (BR) is generally
considered hazardous waste due to the high level ofalkalinity and contains heavy metals. It can cause
environmental pollution due to its highly alkaline
nature by dry or liquid red mud [1]. It contains majoroxide elements such as Fe2O3, Al2O3, SiO2, TiO2,
K2O, and CaO with some trace elements. The best
way to avoid the hazard of BR is to reuse it forengineering applications such as building materials
and road constructions.
There are several attractive applications for BR
such as; use in iron [2], [3] and titanium recovery [4],[5], component in cement and concrete manufacture[6]–[8], construction material [9], soil stabilization
and road construction [10],[11]. Over the years,
extensive research has been carried out to improve
deficient soils. The two most used stabilizers for BR
are cement and lime. Researchers [12], [13] reported
that stabilizing this residue with cement or lime
admixture is effective but very costly.
The cement kiln dust (CKD) material is a
substance produced from cement manufacture known
as a bypass that comes in the form of dust. The dust
is a particulate mixture of partially calcined andunreacted raw feed, clinker dust, and ash, enrichedwith alkali sulfates, halides, and other volatiles.
Several factors influence the chemical and physical

MATERIALS
In this section, brief description for studied BR
and CKD and their chemical compositions are listed.
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SEE-Mie, Japan, Nov.10-12, 2022

Bauxite residue (BR)As it is well known that the characterization of
any geotechnical material is based on its deformationand stability properties, the current experimental
program involves oedometer (OED) and unconfinedcompressive (UCS) tests. Both testing groups weredivided into subgroups based on the CKD% added.
Oedometer and UCS tests were also executed for
different curing periods (1, 7, 14, and 28 days). The
actual curing period may slightly differ according to
the availability of utilized devices and working days.
Each tested sample has been labeled to infer the
CKD% added and actual curing period.

The bauxite residue (BR) used in the current study
was collected from a big storage area located in Ras
Al Khair Industrial City, Dammam, Saudi Arabia,
related to Ma'aden Aluminium Company. The
collected samples were obtained as a dry powder anddistinguished by their red color. The chemicalcomposition of collected BR samples is provided inTable 1 as percent by dry mass weight. The results
indicate high percentages of aluminum, iron, andsilica oxides (Al2O3, Fe2O3, and SiO2,
respectively).

1.35

Mineral

Al2O3

Fe2O3

SiO2

TiO2

%

25.5

18.8

18.8

6.6

Mineral

CaO

P2O5

ZrO2

Loss onIgnition

%

6.0

0.4

0.3

10.3

Dry density, gd (kN/m3 )Table 1 Chemical composition of bauxite residue
percent by weight of dry mass

0.0
2.5
5.0
7.5

1.30
1.25

1.20
1.15
1.10

1.05
1.00
20

Cement bypass dust (CKD)
In the current study, the cement bypass dust wasused to stabilize the BR to be used as a construction
material. Current CKD is a by-product of Yamama
cement plant in Riyadh, Saudi Arabia. Table 2
summarizes the average chemical composition of
CKD, showing a massive percentage of calciumoxide as well as high percentages of silica andaluminum oxides.

Fig. 1
CKD %

CaO

SiO2

Al2O3

K2O

%

67.47

14.37

4.21

2.54

Mineral

Fe2O3

SO3

Cr

Loss onIgnition

%

2.50

2.13

0.42

3.79

50

Standard compaction tests for examined

In order to prepare OED specimens, dry BR was
mixed with respective CKD% and optimum moisture
content and thoroughly mixed. After that, the mixture
was compacted in an oedometer ring to the desired
dry density (i.e., maximum dry density at selected
CKD%), wrapped in thin plastic wrap, and cured to
the respected curing period in a wet-desiccator. The
same is adopted for UCS specimens, except thecompacted specimen is dismantled after compaction
instead of left in the compaction ring.
OED testing was adopted with respect to ASTM
D4546-03 (2003), method B. Once the cured
specimen was installed in the oedometer device,seating stress was applied (7 kPa comparable to thestress applied to subgrades) and left for five minutes.
After that, the specimen was inundated, anddeformation due to wetting was recorded for 24 hours.
The final wetting strain was labeled as wetting
potential (ew). Then, the tested specimen was loaded
in increments with a load increment ratio (LIR=1) up
to maximum stress of 1600 kPa, subsequently
unloaded in increments to 25 kPa.
Regarding UCS testing, the strain rate is selected
as 0.25%/min. to ensure the undrained condition andavoid moisture evaporation from cured specimens.

Table 2 Chemical composition of cement bypass dust
percent by weight of dry mass
Mineral30
40
Moisture content, wc (%)

METHODS
To study the feasibility of using CKD as astabilizer of BR, three percentages of CKD by weight(2.5, 5.0, and 7.0 %) were used. In accordance withASTM D698 (2000), standard compaction tests were
executed to determine the compaction characteristicsof the selected mixtures. Fig. 1 shows the standard
compaction test results for untreated and treated BR.
As CKD% increases, the maximum dry density
decreases, and optimum moisture content increases,
which is comparable with previous research either for
the use of CKD or other stabilizers.

RESULTS AND ANALYSIS
In this section, the results and analysis of theexperimental program is depicted.
485

SEE-Mie, Japan, Nov.10-12, 2022

Oedometer testing, OED

that related to CKD%=2.5% for all cured periods, see
Table 3. Fig. 4 shows that Cc is not affected by thecuring period for CKD%=2.5%, while it is varied forother CKD%. Moreover, Cc is increased with anincrease in the added CKD%. On the other hand, Fig.
5 shows that swell index (Cs) is not affected by either
CKD% or the curing period and can be considered aconstant material.

Table 3 shows that untreated BR specimens
showed a small swell (ew=1.24%) under token stressapplied (7 kPa), which is considered low expansivity
soil. However, for some construction projects, suchas roads on the subgrade, it is desired to remove any
swell potential that might occur during wetting
periods. Fig. 2 shows that wetting strain (ew) reduces
with an increase of CKD%. As well, the effectivenessof the curing period is more in the case of
CKD%=2.5%. Fig. 3 depicts the impact of CKD% on
swell reduction. CKD%=2.5% is almost sufficient toremove the swell potential related to wetting.

1d

ID

Wetting
strain,w (%)

Compr.
Index,
Cc

Swell
index
, Cs

Swell
reduct.
(%)

CKD_0

1.24

0.08

0.03

0.00

CKD_2.5_1d
CKD_2.5_8d

0.18
0.11

0.09
0.08

0.02
0.02

85
91

CKD_2.5_14d

0.07

0.08

0.02

94

CKD_2.5_28d

0.06

0.09

0.02

95

CKD_5.0_1d
CKD_5.0_10d
CKD_5.0_17d
CKD_5.0_31d

0.05
0.02
-0.01
0.02

0.19
0.21
0.26
0.22

0.02
0.02
0.02
0.02

96
98
101
98

0.30
0.30

0.02
0.03

97
100

CKD_7.5_16d

-0.01

0.28

0.02

101

Wetting strain, w (%)

1.50
1.10
0.90

28d

90
80
70

2.5
5.0
7.5
Cement kiln dust, CKD (%)

Fig. 3Swell reduction versus CKD %It can be concluded that CKD%=2.5% is the
optimum value for deformation characteristics oftreated BR, where it succeeded in removing the swellpotential and maintaining the small Cc value for
untreated BR.
0.40

Untreated
2.5
5
7.5

1.30

14d

60

Compression index, Cc

0.04
0.00

Swell reduction (%)

Table 3 Summary of oedometer testing results

CKD_7.5_1d
CKD_7.5_9d

7d

100

Untreated
2.5
5.0
7.5

0.35
0.30
0.25
0.20

0.15
0.10
0.05
0.00
0

0.70

10
20
30
Curing period, t (days)

40

0.50
0.30

Fig. 4
Variation of compression index withcuring time for examined CKD %0.10-0.10 0

10

20

30

40

Unconfined compressive strength, UCS

Curing period, t (days)

The unconfined compressive strength is a key
variable for estimating the undrained shear strengthof fine-grained soils. The obtained results (see Table
4 and Figure 6) reveal that CKD addition effectively
improves BR stability.
As well, UCS of treated specimens increased withcuring time. Fig. 7 shows the improvement
percentage due to the addition of CKD and shows that

Fig. 2
Variation of wetting strain with curing
time for examined CKD %The key variables in estimating consolidation
settlement are compression and swell indices (Cc andCs, respectively). The compression index (Cc) for theuntreated specimen is equal to 0.08, almost equal to486

SEE-Mie, Japan, Nov.10-12, 2022

Improvement percentage (%)

adding 7.5% of CKD increases the undrained stability
by almost three times, indicating its effectiveness.

Swell index, Cs

0.030
0.025
0.020
0.015

Untreated
2.5
5.0
7.5

0.010
0.005

300

1d

7d

14d

28d

250
200
150
100
50
0
2.5
5
7.5
Cement kiln dust, CKD (%)

0.000
0

10
20
30
Curing period, t (days)

40

Fig. 7
Unconfined compressive improvement
versus CKD %Fig. 5
Variation of the swell index with curing
time for examined CKD %CONCLUSIONS
During the processing of bauxite into alumina,
bauxite residue (BR) is generated as industrial waste.
Bauxite residue (BR) can pose a significant
environmental hazard due to its high level ofproduction and its high alkalinity. The current study
examined the feasibility of recycling this residue andusing it as construction material using cement kiln
dust (CKD) which is an industrial waste material
during cement production. In this regard, this research
is of paramount importance for recycling two
environmental hazard waste materials used inconstruction. The compaction parameters, volume
change, and unconfined compressive strength were
examined for a different mixture containing different
doses of CKD.
Oedometer testing revealed that adding 2.5% of
CKD is sufficient to remove any swell potential of BR
besides maintaining a small compression index Cc, so
it is selected as the optimum dose for volume change
remediation.
Unconfined compressive strength testing showedthat UCS increased with adding CKD and curing
period. The addition of 7.5% of CKD increased theundrained stability by almost three times, indicating
its effectiveness.

Table 4 Summary of unconfined compressive testing
results
Uncon. Compr.
Strength
ID
Strength, UCS
Increase(%)(kN/m2)
CKD_0
194.2
0.0
CKD_2.5_1d
347.9
79.1
CKD_2.5_8d
452.1
132.8
CKD_2.5_14d
451.8
132.6
CKD_2.5_28d
454.9
134.2
CKD_5.0_1d
CKD_5.0_10d
CKD_5.0_17d

334.0
395.4
403.8

72.0
103.6
107.9

CKD_5.0_31d

457.8

135.8

CKD_7.5_1d
CKD_7.5_9d
CKD_7.5_16d
CKD_7.5_28d

489.8
592.2
721.9
752.7

152.2
204.9
271.7
287.6

800

UCS (kN/m2 )700

ACKNOWLEDGMENTS

600
500

The authors extend their appreciation to the
Deputyship for Research & Innovation, Ministry of
Education in Saudi Arabia for funding this research
work through the project number (IF-PSAU2021/01/19009).

400
300

Untreated
2.5
5.0
7.5

200

100
0

REFERENCES
0

Fig. 6

10
20
Curing period, t (days)

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Variation of unconfined compressive withcuring time for examined CKD %487

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Waste Management, Vol. 16, 1996, pp. 665-670.
[9] Klauber, C., Gräfe, M., and Power, G.P., Bauxite
residue issues: II. options for residue utilization.
Hydrometallurgy, Vol. 108, Issue 1, 2011, pp.
11-32.
[10] Biswas, W.K., and Cooling, D., Sustainability
Assessment of Red Sand as a Substitute for
Virgin Sand and Crushed Limestone. Journal ofIndustrial Ecology, Vol. 17, Issue 5, 2013, pp.
756–762.
[11] Mukiza, E., Zhang, L., Liu, X., & Zhang, N.,
Utilization of red mud in road base and subgrade
materials: A review. Resources, Conservation
and Recycling. Vol. 141, 2019, pp. 187–199.
[12] Osinubi, K.J. Lime modification of black cotton
soils. Spectr J, Vol. 2, Issue 1, 1995, pp.112–122.
[13] Balogun, L.A. Effect of sand and salt additives
on some geotechnical properties of lime
stabilized black cotton soil. Niger Eng. Vol. 26,
Issue 2, 1991, pp. 15–24.
[14] Wayne S. Adaska, Donald H. Taubert.,
Beneficial Uses of Cement Kiln Dust, IEEE/PCA

488

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

MODELING ADSORPTION OF HEXAVALENT CHROMIUM USINGA LOW-COST JORDANIAN OLIVE STONE WASTE ADSORBENT
Aymen Awad
Middle East University (MEU) – Civil Engineering Department - Amman - 11831 - Jordan,
aawad@meu.edu.jo
ABSTRACT
Heavy metals are very toxic metals found in water and wastewater. Heavy metals are nonbiodegradable
metals, accumulated in human bodies damaging human health. Many researchers tried to treat and purified
water, wastewater and industrial wastewater having these contaminates by using adsorption techniques. They
focused on low cost natural materials produced from agricultural waste. Olive stone waste (OSW) one of thesematerials which is generated in Mediterranean countries such as Jordan. Jordan produced thousands of tons of
this natural waste. Olive stone waste (OSW) was used as natural adsorbent to remove the Cr (IV) ions fromindustrial liquid solutions. The optimal conditions for removal processes were determined previously by setsof experiments. The contact time was 360 minutes, pH was 2.7, the adsorbent dosage was 4 g /L and thetemperature was 25oC. Results of adsorption mechanism data analysis for different Cr(IV) initialconcentrations of 0.3, 2.7, 4.5, 9, 18 and 60 mg/l removed by (OSW) adsorbent fitted the Freundlich adsorption
isotherm R2 = 1, and near very closed to pseudo second-order adsorption kinetics also R2 = 0.998. The
adsorption of Cr (VI) was found to be concentration dependent. Olive stone waste indicates highly removal
efficiency toward removing hexavalent chromium from liquid industrial wastewater.
Keywords: Hexavalent Chromium, Adsorption, Olive Stone Waste, pseudo second-order adsorption kinetics
Model.
INTRODUCTION

chromium [9]. These compounds are existed indifferent water and wastewaters sources especiallyindustrial. Consequently, Cr(IV) effluents aredischarged to the water bodies and environmental
systems from different industries such as
electroplating processes and materials dyeing
industries…etc., [10,4]. Many attempts were done
to treat water and wastewater which havehexavalent chromium contaminants using different
techniques. The common used methods andprocesses for treatment Cr (VI) from liquid
solutions are summarized in the following
techniques; chemical reduction, coagulations andfiltrations, precipitations, ion exchange, reverse
osmosis (RO) and adsorption by using active carbon[11,6]. For a different reasons and disadvantages,
these methods and techniques are described as
expensive, having toxicities, generate harmful
byproducts and produce high quantities of residuals
during and after treatment time [12]. As a result,scientists and researchers focused on findings new
low cost materials used as biosorbents for removalof heavy metals contaminants in the form of ions inaqueous solutions [13].

Water pollution is a major and essential problem
encountered everywhere [1]. Jordan is considered
as one of the poorest countries in water. Water
scarcity in Jordan is reflected by the water shortage
problems and elaborates the main challenges thatface the country throughout the recent and futureyears [2]. Water is very important and essential forhuman being and societies live. Water andenvironment are affected by contaminates fromdifferent sources especially industrial wastewater
which harm the natural sources [3]. Many sourcesof industrial pollutions affect the water andenvironment such as of batteries manufacturing,
electroplating processes, machining processes,
textile dyeing industry and as a biocide addition incooling waters [4]. Heavy metals are very toxic forenvironment and pollute water and wastewater withsmall quantities and low concentrations [5,6].
However, these heavy metals are nonbiodegradable and therefore accumulated in thecreatures’ bodies and in environment systems [7].
One of the most heavy metals contaminates and has
significant environmental concern is chromium
metals (Cr) [8]. Cr exists in nature in different
oxidation number varying from -2 to +6 such as(CrO4-2) called chromate or (Cr2O7-2) called
dichromate [5]. The most toxic chromium
compounds toward the environmental system are
the the hexavalent chromium and the trivalent

In the Mediterranean countries, the olive tree isa fundamental crop, there are more than 12 million
hectares of this crop (95% of the world’s cultivatedolive area) [14]. One of the new solid waste
byproduct and recently generated as agricultural
waste is olive stone waste [15]. The most point489

SEE-Mie, Japan, Nov.10-12, 2022

source of this industrial biowaste is the olive oil
industry. This industry also is dominated in the
Mediterranean Sea countries such as Jordan, Syria,
Lebanon and Palestine. Therefore, industries inthese countries produce huge quantities ofwastewater polluted with olive stone materials andconsequently need to be treated for discharging orreuse. Olive waste is considered a low-costadsorbent, natural materials, such as agriculturaland industrial biowaste and have been studied bymany researchers [16,17]. Park and others in 2007
investigated the organic materials used as
biosorbents which are made of natural biomaterials.
Olive stone waste was processed to produce
activated carbon chemically by using phosphoricacid (H3PO4) to use as biosorbent [6]. The
activated carbon of olive stone waste is consideredeffective adsorbent because of its high adsorption
surface area, its deep microspores andheterogeneous surface functional groups [15].

made from olive stone wastes could be used toeradicate industrial pollutants such as phenols [28,29]. Different investigations also approved thatolive stone waste is effective adsorbent could be
used to remove heavy metals contaminants like
Cd(II), Pb(II), Ni(II) and done by the following
researchers [30,31,32, 33].
Many researchers approved that the adsorption
technology is favorable and good for removal ofindustrial contaminants such as heavy metals
because of its high efficiency, low cost of treatment
and low residual production. Again solid residual ofolive mill products (SROOMP) was employedpotentially by many researches as adsorbent to treat
wastewater containing several heavy metals in trace
concentration, namely Cr(III), Ni(II), Pb(II), Cd (II)and Zn(II) and the results indicated that significant
removal was undertaken [34].
RESEARCH SIGNIFICANCE.

Adsorption is the most and common method to
remove contaminants from aqueous solutions[18,17]. The most effective and widely spreadadsorbent is activated carbon, but with a high cost,which convinced researchers and scientists tosearch for low-cost effective natural adsorbents,
recent studies and investigations were focused onnatural lignocellulosic waste materials and otheragricultural residuals [20,21].

This study was investigated the adsorption ofhexavalent chromium metal ions by olive stone
waste used as adsorbent. Batch system experiments
were used for Cr(IV) adsorption investigations withrespect to different initial metal concentrations
versus contact time. Equilibrium isotherms studies
were studied by using Langmuir model, Freundlichmodel,
Tempkinmodel,
andDubininRadushkevich model isotherms and kinetics for
Cr(VI) removal [35].

Cr(VI) removal using biosorbents was done andapproved that it taken place through the
combination of adsorption and reduction
mechanisms [27]. Today, regulations are more
restricted in applying the effluent standards ofpollutant’s discharging to environment [23, 24].
Olive stone wastes (biosorbent) can be utilized tomake activated carbon; such material is found to beeffective for the removal of toxic metals such asaluminum or arsenic from wastewater [25].

MATERIALS.
Preparation of adsorbent.
Olive stone waste was collected from different
sites in Jordan (Olive extraction oil plants andfactories). Firstly; OSW was mixed together, dried,
washed with distilled water, and then socked indiluted phosphoric acid H3PO4 for two hours.
Secondly; the washed stone was dried and crushed
to particle size and sieved between 300 – 800
microns. Thirdly; the homogenous OSW was
treated thermally at 104 o C for 3 hours to eliminate
the excess acid and evaporate the VOC in theadsorbent [37].

Adsorption isotherms represents the properties
and equilibrium data which reveal the mechanisms
how the pollutants removed by adsorbent materials[10,26]. Langmuir model, Freundlich model,
Temkin, and Dubinin-Radushkevich isotherms are
the usual used models and equations to test the olive
stone waste – hexavalent chromium metals
contaminants system [10, 27].

Preparation of Cr (VI) solution.

Even though there are many ecological benefits
could be achieved when using the natural waste assource of energy or a raw source for manufacturingof active carbon. Therefore it is good forenvironment to use such biowaste as adsorbent forremoval of industrial waste such as heavy metals[23]. Consequently, different studies and many
investigations have indicated that the biosorbent

A standard hexavalent chromium solution of3000 mg/l concentration was prepared using thedesired amount of solid chromium trioxide Cr 2O7-2(K2Cr2O7) dissolved in 250 ml of distilled water.
Cr(IV) solutions with the adsorbent amount of 4 g/lwere taken in conical flasks and shaken on anelectrical bench shaker for time of 360 minutes at
25oC and pH of 2.7.
490

SEE-Mie, Japan, Nov.10-12, 2022

METHODOLOGY.

forms of mathematical models describing theadsorption isotherms, based on physical bases or
empirical hypothesizes to represent data achieved
experimentally. In this research four models wereused to fit the experimental equilibrium data to findout which one is suitable for description theremoval process. Langmuir, Freundlich, Temkinand Dubinin–Radushkevich adsorption isotherm
models were used to fit the data [38].

Different experiments were done firstly to fix
the parameters of pH, adsorbent dosage, mixing or
contact time affecting adsorption rate. For the
purposes of adsorption isotherms and removal
kinetics investigations a tests group upon initialconcentrations testing were done. Therefore testingprocedures were constructed by taking different
initial metal concentrations of Cr(IV) solutions asfollows: 0.3, 2.7, 4.5, 9, 18 and 60 mg/l. Stocksolution was used to prepare the required initialconcentrations by a prober dilution factor for eachconcentration needed. Testing continued upon eachsample with initial concentration (Ci) until theconcentration of the residual metal after adsorption
was approximately fixed at a point which represents
the equilibrium concentration (Ce) of sorbent[Cr(IV)]. During testing the drop in concentration
with time was recorded. At the end of eachexperiment the equilibrium concentration of Cr (VI)was estimated calorimetrically by diphenyl
carbazide test method and directly measured with
spectrophotometer type of DR 5000 HACH-USA
manufacturer.). To estimate the percentage removalof chromium from aqueous solution the following
equation was used [20]: Removal of chromium =( C initial – C final )C initial

Removal percentage versus initial concentrationof Cr (VI).
The results of adsorption experiments of Cr (VI)at different initial concentrations ranging from 0.360 ppm received at the best value of acidity value of
2.7, the adsorbent dosage was (4g/L), while thestirring time was elapsed to (360 min) and themixing speed was 150 rpm. Table (1) represents theresults of Cr(VI) initial concentrations effects on
adsorption of the metals in batch reactor. (Fig.1)
shows the removal efficiency of Cr(VI) metal ionsremoved by the adsorbent (OSW) at 0.3, 2.7, 4.5, 9,18, and 60 mg/l of Cr(IV) initial concentrations
versus time. It is obvious that the percentage
removal is increased when the adsorbate
concentration is decreased and ranged from 80
percent up to 96 percent. This may be probably due
to site limitations on the surface of the adsorbent
which can cause a low removal percentage at highconcentrations.
Table 1 Effects of initial concentrations of metal
ions in a batch reactor using olive stone waste
adsorbent @ pH of 2.7 for Cr(VI) solutions.
[Processes’ temperature is 25 ± 1oC, adsorbent doseof 4 g/L, mixing speed is 150 rpm, and solutions
volumes of 0.25 liter]

x 100

EQUIPMENT.
The experiments of this part of the study weredone in 250 ml conical flasks and then mixed at aconstant speed of 150 rpm at pH of 2.7 and the fivedifferent initial concentrations of the salt’s solutions
and adsorbent dosage of 4 g/L at ambient
temperature (approximately 25°C).

Time
(Min)
0
2
4
8
90
180
270
360

Collected samples during testing were analyzed
for the determination of the concentrations of theremaining Cr(VI) by using a spectrophotometer
DR5000 Hach, USA. The adsorbent was weighted
each time by digital balance (Mettler AE200, USAmade), 200 grams capacity ± 0.1 mg accuracy.
RESULTS.
Experiments were carried out at temperature(298 K). Equilibrium adsorption isotherms
generated at equilibrium states. Adsorption
isotherms are calculated from the results of batch
experiments
studiesatdifferent
initialconcentrations as shown in (Tables 1 and 2) and(Fig.1) [35,26,27]. These isotherms represent theadsorption capacity of the adsorbent in terms ofmetal uptake (milligrams of adsorbate per grams ofadsorbent) and could be fitted to suitable correlation(Adsorption Model) [27,37]. There are different
491

Concentration of Hexavalent chromium(mg/l).
0.30
2.70 4.50 9.0
18.0 60
0.04
0.46 1.00 3.5
4.4
18
0.03
0.32 0.90 2.1
2.4
16
0.03
0.25 0.46 1.0
2.3
14
0.02
0.23 0.43 0.9
2.2
13
0.01
0.21 0.41 0.8
2.1
12
0.01
0.15 0.32 0.8
2.1
12
0.01
0.15 0.32 0.8
2.1
12SEE-Mie, Japan, Nov.10-12, 2022

Fig. 1 Removal efficiency of Cr(VI) metal ionsremoved by olive stone waste at different initialconcentrations versus time at an initial pH’s of 2.7

surface of adsorbent and no other adsorption types[40]. Fig. 2 illustrates the layers of adsorbate
attached to the adsorbent [41].

DISCUSSION OF RESULTS.
Adsorption Isotherms Models.
The results of the adsorption experiments at
equilibrium states were tabulated in in (Table 2).
Table 2 shows the calculated parameters for plottingof the liner forms of the adsorption models.
Table 2 Adsorption Isotherm parameters forLangmuir, Freundlich, Temkin and Dubinin–
Radushkevich models [38].
Co
mg/l
0.3
2.7
4.5
9.0
18.0
60.0

x/ms
mg/g)
0.003
0.038
0.080
0.200
0.525
3.000

log
(X/M)
-2.602-1.426-1.097-0.699-0.2800.477

log (Ce)-2.000-0.824-0.495-0.097
0.322
1.079

ln Ce
-4.605-1.897-1.139-0.223
0.742
2.485

Co
mg/l
0.3
2.7
4.5
9.0
18.0
60.0

Ce
(mg/l)
0.01
0.15
0.32
0.80
2.10
12.00

Qe
mg/g
0.073
0.638
1.045
2.050
3.975
12.000

Ce/qe
l/g
0.138
0.235
0.306
0.390
0.528
1.000

X
mg
0.003
0.038
0.080
0.200
0.525
3.000

Co
mg/l
0.3
2.7
4.5
9.0
18.0
60.0

ln qe
-2.624-0.450
0.044
0.718
1.380
2.485

𝜺
11200
4930
3430
1960
944
194

𝜺2
1.3E+08
2.4E+07
1.2E+07
3.9E+06
8.9E+05
3.8E+04

RL
0.935
0.616
0.490
0.325
0.194
0.067

Fig. 2 Adsorption layers of liquids on solid
adsorbents [41].
According to the assumptions mentioned, theLangmuir isotherm model is defined by following
equation:𝒒𝒆 =𝑸𝒎𝒂𝒙 𝑲𝑳 𝑪𝒆
𝟏+𝑲𝑳 𝑪𝒆………… (1)The linear form of the Langmuir isotherm model
is:
𝑪𝒆
𝒒𝒆

𝑪

𝟏

𝒎𝒂𝒙

𝒎𝒂𝒙 𝑲𝑳= 𝒒 𝒆 + 𝒒.........… (2)where the amount of adsorbent removed byadsorbent is qe (mg/grams) and Ce is theconcentration of adsorbate at equilibrium in mg/L,
qmax represents the maximum adsorbent capacity as
one layer on the adsorbent surface in (mg/g) and theadsorption isotherm constant is KL in (L/mg).
𝑪

The plotting of ( 𝒒𝒆 ) and (𝑪𝒆 ) of “Eq. (2)” will give𝒆a linear relationship from which 𝒒𝒎𝒂𝒙 and 𝑲𝑳 canbe determined from the slope and intercept of theplotting, respectively, as seen in Fig. 3. “Eq (3)”gives the value of separation factor RL which
describes the Langmuir isotherm process [42]:-𝑹𝑳 =Langmuir Isotherm.

𝟏
𝟏+ 𝑲𝑳 𝑪𝒐……………… (3)where 𝑪𝑶 is the initial concentration of theadsorbate [Cr(IV)] and RL is the separation factorof the adsorption process, which is unfavorable forvalue of > 1, linear for value of 1 and strong andirreversible for value = 0. The results are tabulated
in Table 1. RL values indicated that the process ofremoval are closed to pure adsorption.

Usually to describe the removal mechanism ofliquid molecules by solid material the Langmuir
Isotherm is used to test for applicability, Irving
Langmuir in 1916 set the model to test theadsorption of gas by adsorbents under certain
pressure [39]. The adsorption behavior by using
Irving Langmuir model was found to describe themonolayer removal mechanism between liquid
phase and solid in case of homogenous sites on
adsorbent surface. The model describes theadsorption process quantitatively, monolayer withthe same energy value of adsorption onto the outer492

SEE-Mie, Japan, Nov.10-12, 2022

Langmuir Plot for adsorption of Cr(IV) Metal
onto Olive Stone Waste at 25 ºC

Fig. 4 Freundlich Adsorption Isotherm Model

1.2

Ce/qe ( g/L)

1.0

Pseudo Second- Order Adsorption Isotherm.

0.8
Langmuir Plotfor Adsorptionof Cr(IV) onto
Olive Stone
Waste at 25 oC

0.6
0.4
0.2

y = 0.0628x + 0.2719
R² = 0.9131

This adsorption kinetic model can be expressedin liner form as follows [47, 35]:(0.0
0 1 2 3 4 5 6 7 8 9 10 11 12 13
Ce ( mg/L)

The plot of the term (t/qt) versus time as shownin “Eq. (5)”, should give a linear relation. The
constants and parameters of the model qe and k2 canbe determined from the line slope and intercept of
the fitted line, respectively.

Fig.3 Langmuir Adsorption Isotherm Model
Freundlich Adsorption Isotherm.
The heterogeneous adsorbent surface in the caseof multilayer adsorption process is assumed
wherever the Freundlich isotherm model is used to
fit the experimental data [43,44]. Freundlich
explained the behavior of adsorbed molecules on
the adsorbent surface and the data are fitted with thefollowing empirical linear form equation:-If the initial adsorption rate, h (mg/g·min) is:

h = k 2 qe

Where qe represents the metals uptake (mg/g),
Kf is the Freundlich constant, Ce is the equilibrium
concentration of adsorbate in (mg/l) and n is thelinearity constant describing the adsorption processwith respect to adsorbate concentration [44].
Plotting results for n values say that if n = 1 then theprocess of adsorption is linear adsorption process ,if n is less than 1 the process is with chemical
reaction but if n is higher than 1 a physicalmechanism is included in the adsorption process is
attained. As a conclusion if 0 < 1/n < 1 then thesituation is favorable and it is cooperative when 1/n> 1 [45,46]. Fitting of the data is illustrated in Fig.
4, with a correlation coefficient R2 of 1 and thevalue of the adsorption relation constant n equals 1
which mean that the adsorption is liner process.

600

(t/q)

200

y = x - 0.6021
R² = 1

Log X/M-1.000-1.500-2.000-2.500-3.000
Log Cey = 1.5684x + 1.8503
R² = 0.9999

100

0.000
0.000

(t/q)
versus (t)

300

0.500

-0.500

The Pesudo Second Order Equation[ Cr(IV)- OSW System ]

400

1.000

-1.0001.000…………… (6)500

Freundlich Isotherm for Adsorption ofCr(IV) on OSW at 25 ºC-2.0002

The constant k2 is refers to the rate constant of
the model (pseudo second-order adsorption model)(g/mg·min). At boundary conditions of t = 0 to t = t
and qt = 0 to qt = qt the data fitted as shown in Fig.
5. The generated straight line of the fitted data of[t/qt] versus [t] shows a good agreement of
measured data with the kinetic model form for all
initial chromium concentrations. The results also
indicated that the sorption of Cr(IV) removal
behaves as pseudo second-order adsorption kinetics.
It developed good correlation coefficient discussed
the fittingness of as pseudo second-order adsorption
model. (Table 3) lists the calculated constants andparameters obtained from the isotherm models. The
correlation coefficient for pseudo second-orderkinetic model obtained is 0.999.

log (𝑞𝑒 ) = log 𝐾𝑓 + 1⁄𝑛 𝑙𝑜𝑔𝐶𝑒 ….. (4)-3.000

t
1
1
) =
+
(t )
qt
h
qe
……………. (5)

0

2.000

0.00

Freundlich
Isotherm
forAdsorptionof cr(IV)on Olive
Stone
Waste at
25 oC

200.00Time (hours)

400.00Fig. 5 Pseudo second-order adsorption Model.
Trend revealed that sorption capacity of olive
stone waste increase by decreasing the initial493

SEE-Mie, Japan, Nov.10-12, 2022

concentration of metal ion. This is due to the factthat in case of low concentration of metal ion
solution there are more adsorbent sites available formetal ions to adsorb on it.

Constants

Langmuir

0.063

=1/qm

qm

15.92

Freundlich

1.000

= 1/n

n

1.00

Pseudosecond-order
Tempkin

1.568

= 1/h

h

0.64

1.532

=BT

BT

1.53

Dubinin–Radushkevich-3.0E+08

=-KDR

KDR

3E+08

MODEL

Intercept
0.272= KL*qm

kL =

0.231

Freundlich

0.602
1.850

= ln(Kf)

Kf =

0.548

= 1/qe

qe=

0.541

4.481

=
BTLn(Af)= Ln(Q0)

Af =18.642

Qo=

3.140

1.144

Dubinin–Radushkevich

MODEL

R2

Langmuir

0.913

Freundlich

1.000

Pseudo second - order

0.999

Tempkin

0.685

Dubinin–Radushkevich

0.790

14.0

Tempkin
Isotherm
Plot for
Adsorptionof Cr(IV)onto Olive
Stone Waste
at 25 oC

12.0

10.0
8.0

y = 1.5316x + 4.4806 6.0
R² = 0.6851
4.0

Constants

Langmuir

Pseudosecond order
TempkinTempkin Isotherm Plot for adsorption ofCr(IV) Metal onto Olive Stone Waste at 25 ºC

qe ( mg/g)

Slope

𝑇

AT is the isotherm equilibrium binding constant(L/g); while bT is the Tempkin isotherm constant; R,
the universal gas constant and equals 8.314
J/mol/K; T, is the temperature of the process usuallyat a temperature of 298 K; B, is a constant related tothe heat of sorption in (J/mol). The constants were
determined from the slope and intercept of themodel fitting by plotting the metal uptake qe against
ln Ce as shown in Fig. 6.

Table 3 Adsorption isotherms parameters ofLangmuir, Freundlich, Pseudo second-order,
Tempkin and Dubinin–Radushkevich isotherm ofhexavalent chromium Cr(IV) adsorption onto olive
stone waste (OSW).
MODEL

𝑅𝑇

𝐵𝑇 = 𝑏

Where

2.0
0.0
-6 -5 -4 -3 -2 -2.0
-1 0
-4.0

1

2

3

4

5

6

ln(Ce)

Fig.6 Tempkin adsorption isotherm Model
The plot slope and intercept are taken to
calculated the constant and binding energy and they
are found to be equal to the, AT = 18.642 L/μmol,
BT = 1.532 J/mol, where BT refers to amount of heatfor sorption which is indicating a physicaladsorption process and the R2 = 0.6851. Therefore,
results of fitting said that this process of removal is
not comply with this model with its hypothesis
which means that just small amount of energy isneeded to achieve the removal of contaminantsfrom solution and this will support the removal byanother adsorption model.

Tempkin Adsorption Isotherm

The Dubinin-Radushkevich (D-R) Isotherm

The process of adsorption of adsorbate byadsorbent in this isotherm is presented by a factor
called equilibrium binding constant Af (L/g). Thisfactor is related to the amount of energy that
required for the adsorbent to adsorb the pollutant
molecules measured in J/mol [48]. The model is set
by the following Equation of the nonlinear form[49]: -

This isotherm model depends on temperature
and a factor called adsorption potential constant (ε)
which considers the energy required for adsorption
according to the adsorbent micropore size on thesurface of adsorbent and the liner form of the modelis represented by the following equation [50]: -𝐿𝑛(𝑞𝑒 ) = 𝐿𝑛(𝑄0 ) − 𝐾𝐷𝑅 𝜀 2 …… (9)𝑅𝑇

𝑞𝑒 = 𝑏 𝐿𝑛(𝐴 𝑇 𝐶𝑒 )…….………. (7)𝑇Dubinin-Radushkevich (D-R) model presents
the required mean free energy for desorption of eachmolecule from its space site on the adsorbent
surface and can be calculated by the following
formula [51]:The linear form is given in the following
formula:𝑞𝑒 = 𝐵𝑇 𝐿𝑛 (𝐴 𝑇 ) + 𝐵𝑇 𝐿𝑛( 𝐶𝑒 )…(8)494SEE-Mie, Japan, Nov.10-12, 2022

E=

1
√2KDR

solutions at low initial concentration of 0.3 mg/L
and it decreases up to 80 % when the initialconcentration of adsorbate increases to 60 mg/L.
Olive stone waste has potential to be a good natural
resource material for effective removal ofchromium (VI) of low concentration fromwastewater and may be used for other contaminants
to remove. Freundlich adsorption isotherm model
agrees very well with experimental data and themechanism of removal for the adsorption of Cr(IV)onto OSW for different initial Cr(IV)concentrations.

…………… (10)The parameter 𝜀 can be calculated from thefollowing formula [52]:1

𝜀 = 𝑅𝑇 𝐿𝑛 (1 + 𝐶 ) ……….(11)𝑒where qe refers to metal uptake at equilibrium
conditions in (mg/g); Qo related to the theoretical
isotherm saturation capacity in (mg/g); KDR is theconstant called Dubinin–Radushkevich isotherm
constant in (mol2 J-2); ε is the adsorption potential
constant; R is the gas constant (8.314 J/mol/K), T is
the absolute temperature (K) and Ce adsorbate
equilibrium concentration (mg/L). Experimental
data were fitted according to DubininRadushkevich (D-R) model where 𝐿𝑛(𝑞𝑒 ) versus
𝜀 2 as shown in Fig. 7.

ACKNOWLEDGMENTS
The author would like to express his gratitude to
the support extended to him throughout and for the
all types of supports and grants to cover the worksof this research by Middle East University –Amman (MEU).

Dubinin and Radushkevich
Isotherm Plot for adsorption of Cr(IV)Metal onto Olive Stone Waste at 25 ºC
Dubinin
3.0
y = -3E-08x + 1.1441
and
R² = 0.7904
2.0
Radushkevich ( D-R)
1.0
Isotherm
0.02Plot for𝜀50
Thousands 150050 Adsorption-1.0
of Cr(IV)-2.0
onto Olive
Stone
-3.0
Waste at
-4.0
25 oC

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Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EFFECT OF LANDCOVER CHANGE ON LAND SURFACETEMPERATURE IN THE URBANIZED AREA

1

Agus Suharyanto
Faculty of Engineering, Universitas Brawijaya, Indonesia; 2,3 Company, Country

ABSTRACT
Changes in land cover affect various things, one of them being land surface temperature. This is because eachtype of land cover has its characteristics of absorption and reflectance of solar radiation. Solar radiation that isabsorbed by objects on the earth's surface will be re-emitted into the air and will warm the earth's surface together
with the radiation reflected by these objects. If the type of land cover on the earth's surface changes, the temperatureof the earth's surface will also change. This phenomenon is the theme of this research. Changes in land cover andchanges in land surface temperature were analyzed from remote sensing satellite imagery. The satellite image
processing method has been applied in the analysis. Land cover analysis using an unsupervised classification
method with iso cluster analysis is applied in this study. Land surface temperature analysis used the LST method.
The research locations are Malang and Surabaya Cities. The results showed that the land covered with vegetation
had the lowest land surface temperature. Meanwhile, land covered by soil, asphalt, concrete, zinc roof, andgalvanized roof tile has a higher land surface temperature, respectively. In other words, land that reflects a lot ofsolar radiation will increase the surface temperature of the land, and land cover that absorbs a lot of solar radiation
will reduce the surface temperature of the land. The results of the research indicate that changes in land cover willaffect changes in land surface temperature.
Keywords: Land cover, Land surface temperature, Solar radiation, Image analysis, Unsupervised classification

INTRODUCTION

low LST. For example, the high reflection andemission objects are concrete, zinc roof, andgalvanized roof tile. For low reflection and emission
objects are vegetation, water, and wetted soil.
Consequently, if the LULC is changed the LST will
be changed too.
The research areas are Malang and Surabaya
Cities, Indonesia, which are the first and second
largest cities of East Java Province. The satellite
imageries generated from Landsat scanned withsensor OLI and collected in 2015 and 2020 were usedin this research. The LULC in both cities changed
very fast, especially in the 2000 year. The LULC
changes will analyze using the NDVI method and airtemperature will analyze using the LST method [9],[10]. To confirm the NDVI values, the classificationof LULC will analyze using unsupervisedclassification method images using isoclass [11].
Based on the analysis result it can be estimatedthat the LST will change according to LULC changes.
The second estimation is the level of NDVI values
will follow the types of LULC in the certain area.

The landcover or landuse (LULC) changes arevery fast and dynamic in the urbanized area. Thisphenomenon will be affected by many environmental
characteristics such as surface runoff discharge,
traffic volume, and land surface temperature (LST)[1]. To minimize the effect, it is necessary to monitor
the LULC changes. One of the effective and efficientmethods to monitor it is by using satellite remotesensing data [2], [3]. The remote sensing data can bescanned with a wide area at the same time, in digitalformat, and available in data series from many years
before.
The LULC can be analyzed using satellite remotesensing data. One of the LULC characteristics can be
represented by Normalized Vegetation DifferenceIndex (NDVI) [4], [5]. The value of NDVI is from 0
to 1, and 0 is indicated that the land is not covered byvegetation, and 1 is indicated that the land covered byvegetation is 100% [6], [7]. Each type of land coverhas its characteristic of solar radiation reflection andemission. The reflected and emitted solar energy willaffect the air temperature surrounding each landcovertype and is named LST [8]. Based on thischaracteristic it can be predicted that the land coveredby the object which has high reflection and emission
characteristics will produce high LST. In opposite,
the land covered by the object which has low
reflection and emission characteristics will produce

RESEARCH AREA
The research areas are Malang and Surabaya
Cities, Indonesia. These cities are located in East Java
Province. Malang City located in a hilly area with anelevation is about 500 m from MSL (Mean Sea Level).
The population is 843.810 souls [12]. Surabaya City
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SEE-Mie, Japan, Nov.10-12, 2022

is located in the north area of East Java Province inthe flat area. The elevation is about 0 to 10 m from
MSL and in the coastal area. The population is 2.87
million souls (BPS Surabaya City, 2021). Two cities
were chosen as research areas because those cities arelocated under different topographic conditions andboth cities have the same fast urban development. The
city of Malang represents the mountainous area andthe city of Surabaya represents the coastal area. The
location of the research areas can be shown in Fig. 1.

shrub and brush, open land, an agricultural area, andbuilt-up area. This method was proposed, because
easy to do and the accuracy is good [13], [14]. The
final check of the landcover classification result will
be done by comparing the image and the groundsurvey data. If the comparison result agrees, then thelandcover classification process is finished. But if thecomparison does not agree, then the image will
reclassify from the beginning step.
NDVI Analysis
NDVI is the image representing the level
condition of land which are covered by vegetation.
The value of NDVI is from 0 to 1. Zero means theland is not covered by vegetation and one means theland is almost 100% covered by vegetation. NDVI
value is equal to a band near-infrared minus band red
divided by band infrared plus band red as shown in
Eq. (1) [15]. For Landsat 8 OLI, the infrared band
representing by band 5, and the red band isrepresented by band 4.
NIR − Rd
NIR + Rd

NDVI

Fig.1 Research area.

where NIR is the near-infrared band and Rd is the red
band.

MATERIALS AND METHODSLST Analysis

The main material used in this research is satellite
imagery. The digital image of the Landsat satellitewith sensor OLI was used in this research. The
imageries covered of research areas in 2015 and 2020
were collected. The satellite imagery in path/row
118/65 covered Surabaya City and path/row 118/66
covered Malang City. The imageries with a cloud
cover of less than 20% were selected. In summary,the selected imageries used in this research are shownin Table 1.

The temperature of the land surface is derived
from the thermal band of Landsat imagery. For
Landsat 8 OLI the thermal band are bands 10 and 11.
The LST is analyzed by using Eq. (2) until Eq. (6)[16].

TOA = L = M L . Ccal + AL
TC =Table 1 Satellite imageries used in this research
Path/Row
118/65
118/66

Date
5
6
8

City
Surabaya
Surabaya
MalangMalang(1)

Seasons
Dry
Dry
Dry
Dry

K2
K

ln 1 + 1
L
 


(2)

− 273.15

 NDVI − NDVI min PV =  NDVI max − NDVI min (3)2

E = 0.004. PV + 0.986

Landcover Analysis
The landcover of the research area is analyzed
using the iso cluster unsupervised classification
method. First, the imagery will be classified into 15
landcover categories. By comparing the classified
landcover image and high-resolution images such asa quick bird or Google images in the same area, thelandcover categories will reclassify from 15 to 5
categories. The five landcover categories are forest,

LST =

TC
   . TC 
 Ln E  
1 + 







(4)

(5)
(6)

Here ML is the radiance multiplicative scaling factor(Radiance_Mult_Band_10 or 11) obtained from the
MTL file on the Landsat data, and AL is the radiance499

SEE-Mie, Japan, Nov.10-12, 2022

additive scaling factor (Radiance_Add_Band_10 or
11) obtained from the MTL file on the Landsat data,
and Ccal is the digital value of Band 10 or 11. K1 andK2 are the band-specific thermal conversion constants
taken from the metadata of the imagery file. The
number 273.15 is the conversion factor for thetemperature unit from Kelvin to Celsius. The λ is thedigital number of Band 10 (λ is the wavelength ofemitted radiance = 10.8 µm for Landsat TIRS Band10), ρ = 14,380 (ρ = h × c/σ (1.438 × 10−2 mK)), TC
is the brightness temperature, σ is the Boltzmann
constant (1.38 × 10−23 J/K), h is the Planck constant(6.626 × 10−34 Js), c is the velocity of light (2.998 ×
108 m/s), and E is the land surface emissivity or error
correction.
UHI Analysis
Analysis of the relationship between LST, NDVI,
and LULC should ideally be carried out at each pixel
in all research locations. Based on the statistical
approach, the analysis will be done by the sampling
method. The sample must depict pixels that arelocated in the suburbs to the city center. These pixels
will be obtained from a line that runs from the suburb
area through the city center and ends in the suburb
area again. This line namely the urban heat island line
(UHI). The relationship between LST, NDVI, and
LULC will be analyzed by comparing the pixel values
on the UHI line and the landcover at the same positioncollected by the ground survey. From the result of thecomparison, it will be possible to obtain a relationshipbetween the types of landcover with the NDVI andLST values.
In the same way, as described above, the Landsat
imageries scanned on 2015 and 2020 will beanalyzed. By comparing the analysis results from2015 and 2020 imageries, landcover, NDVI, and LSTchanges can be known well. Thus the effect of LULC
change on LST will be analyzed and become the main
theme of this research. In principle, the researchmethod for carrying out this research can be seen in
the flow diagram chart shown in Fig. 2.

Fig.2 Flow diagram of research methods

Fig. 3 LULC of Malang City in 2020

RESULTS AND DISCUSSIONSThe collected satellite imageries were analyzed
using image processing software to generate the
LULC, NDVI, and LST imageries. For example, the2020 LULC, NDVI, and LST imageries of Malang
City were shown in Fig. 3, 4, and 5, respectively. Six
landcover categories can be classified i.e. forest,
shrub and brush, agricultural land, open land, built
area, and swamp area. From Fig. 4 it can be seen thatthe lowest NDVI is indicated as wet open land and thehighest NDVI is indicated as forest landcover. This
relationship was verified by high-resolution satellite
imagery as shown in Fig. 6. The same case is shownin Fig. 5. The highest temperature is reflected andFig. 4 NDVI of Malang City in 2020
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Surabaya City scanned in 2015 and 2020.
After the relationship between LULC, NDVI, andLST was verified, the LULC changes from 2015 to2020 were analyzed. The LULC change in Malang
and Surabaya Cities from 2015 to 2020 is shown in
Table 2. Both cities showed that built area isincreased and the others landcover were decreased.
The landcover imageries of Surabaya city scanned in2015 and 2020 are shown in Fig. 8. From this figure
it can be seen that the built area represented in red in2020 looks larger than the 2015 image. To analyze theeffect of landcover change on land surface
temperature, the landcover will be represented by
NDVI. The landcover will not be categorized as
landcover types but will categorize as NDVI values.
Table 2 LULC Changes Malang and Surabaya Cities
City

Fig. 5 LST of Malang City in 2020

MalangSurabayaLandcover
categories
ForestShrub and brush
Agricultural land
Open land
Built area
Shrub and brush
Agricultural land
Open land
Built area
Water

Area (Ha.)
2015
2020
1,554.9
1,621.4
1,808.7
1,933.7
1,570.2
988.1
420,3
741.1
5,636.9
5,706.4
6,637.7
3,466.2
6,095.202,048.7
1,649.5
15,760.2 21,551.4
2,306.7
6,180.3

Fig. 6 Verification of NDVI and LULC

Fig. 7 Verification of LST and LULC
emitted by the roof of the factory and the lowest
temperature is on open land. This relationship wasverified by high-resolution satellite imagery as shownin Fig. 7. This verification process was done also forimageries covered Malang City scanned in 2015 andFig. 8 LULC of Surabaya City in 2015 and 2020.
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The values of NDVI are from -1 to +1. The values -1
to 0 indicated that land is not covered by vegetation.
The value +1 indicated that land is covered 100% byvegetation. The NDVI value between 0 – 1 indicatedthe percentage of vegetation covered in the land. For
example, if NDVI is equal to 0.25 it means that theland is covered by about 25% of the vegetation.

32

LST

30

26

The NDVI changes in Malang and Surabaya
Cities from 2015 to 2020 are shown in Table 3. This
table indicated that the lowest, average, and highest
NDVI decreased from 2015 to 2020. For LST, thetemperature changes of Malang and Surabaya Cities
from 2015 to 2020 are shown in Table 4. From thistable, it can be concluded that the lowest, average,
and highest LSTs increased from 2015 to 2020. Basedon Table 3 and Table 4 it is seen that when NDVI goes
down, LST goes up. This phenomenon indicates thatthe land surface that is covered with a lot ofvegetation will reduce LST. This is because the land
surface that is covered by a lot of vegetation will
absorb a lot and slightly reflect solar radiation.

24
0.0

MalangSurabaya

Year
2015
2020
2015
2020

Min
-0.01
-0.21
-0.15
-0.15

NDVI
Ave
0.23
0.24
0.14
0.15

0.1

0.2

0.3

0.4

0.5

NDVI

Fig. 9 NDVI vs LST of Malang City 2015

32

LST

30

28

26

Table 3 NDVI of Malang and Surabaya Cities
City

28

24
0.0

Max
0.59
0.59
0.52
0.55

0.1

0.2

0.3

0.4

0.5

NDVI

Fig. 10 NDVI vs LST of Surabaya City 2020

To analyze the relationship between NDVI and
LST, it is necessary to draw a graph showing therelationship pixel by pixel from NDVI and LST data.
Due to a large number of pixels in one research area,
the NDVI and LST data are generated from the UHI
line. The relationship between NDVI and LST of
Malang and Surabaya Cities is shown in Fig. 9 andFig. 10. From these figures it can be concluded thatNDVI is inversely proportional to LST. When thevalue NDVI decreases, the LST value increases.

condition of land surface covered by vegetation. Witha value between 0-1, the higher NDVI indicated thatthe land surface has a higher land surface covered byvegetation. The minus NDVI indicated that land has
not been covered by vegetation such as open land,
water, sand, wetted open land, and bare land.
The land cover type and NDVI condition is closed
related to the land surface temperature. The analysis
result shows that the land cover which has a highreflectance material to solar radiation will have a high
LST. Finally, from this research, it can be concluded
that NDVI is inversely proportional to LST. An
increase in NDVI will have the effect of decreasing
LST and conversely, a decrease in NDVI will
increase NDVI. This phenomenon is shown by thechange in LST of Malang and Surabaya Cities from2015 to 2020 caused by changes in NDVI. Therefore,changing land cover from vegetation to nonvegetation will increase LST. This phenomenon
almost occurred in urban areas due to dynamic
development such as Malang and Surabaya Cities
Indonesia.

CONCLUSIONSACKNOWLEDGMENTS

The landcover, NDVI, and LST of Malang and
Surabaya Cities were analyzed using Landsat OLI
data scanned in 2015 and 2020. The imageries data
were scanned during the dry season. The analyzed
result shows that the NDVI is well represented in theThis research is partially funded by the Associate
Professor Doctoral Research Grant (Hibah Penelitian
Doktor Lektor Kepala), Faculty of Engineering
Universitas Brawijaya in the 2022 fiscal year. The

Table 4 LST of Malang and Surabaya Cities
City
MalangSurabaya

Year
2015
2020
2015
2020

Min
16.00
18.50
18.21
21.00

LST
Ave
26.05
26.41
26.96
28.16

Max
32.12
31.10
33.33
34.07

502

SEE-Mie, Japan, Nov.10-12, 2022

Response to Local Climate Change Using
Multispectral Remote Sensing Data. Land, Vol.
11, 2022, pp. 595.
https://doi.org/10.3390/land11050595.
[9] Mwangi P. W., Karanja F. N., Kamau P. K.,
Analysis of the Relationship between Land
Surface Temperature and Vegetation and BuiltUp Indices in Upper-Hill, Nairobi. Journal of
Geoscience and Environment Protection, Vol. 6,
2018, 6, pp. 1-16.
http://www.scirp.org/journal/gep[10] Guha S. and Govil H., Land Surface Temperature
and Normalized Difference Vegetation Index
Relationship: a Seasonal Study on a Tropical City.
SN Applied Science, Vol. 2, 2020, pp. 1661.
https://doi.org/10.1007/s42452-020-03458-8[11] Solórzano J. V., Mas, J. F., Gao, Y., andGallardo-Cruz, J.A. Land Use Land Covver
Classification with U-Net: Advantages ofCombining Sentinel-1 and Sentinel-2 Imagery.
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https://doi.org/10.3390/rs13183600[12] BPS Malang Municipality, Malang Municipality
inFigures,2021.
https://malangkota.bps.go.id/publication/2021/02/26/4ccb213f9a2a7ba007bff7c4/kota-malangdalam-angka-2021.html[13] Rwanga S. S., and Ndambuki J. M. Accuracy
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pp. 611 - 622. http://www.scirp.org/journal/ijg[14] Pande C. B., Moharir K. N., and Khadri S. F. R.
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in Pangari Watershed Area (MS), India, Based on
the Remote Sensing and GIS Techniques. Applied
Water Science, Vol. 11, Issue 96, 2021.
https://doi.org/10.1007/s13201-021-01425-1[15] Wright C. K., De-Beurs K. M, Henebry G.
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177 – 187. https://doi.org/10.1007/s11707-0120327-x.
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authors also thank Dinas Pengairan Provinsi Jawa
Timur for providing the temperature data. Finally, theauthors are indebted to the USGS server(https://earthexplorer.usgs.gov/).
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Middle Atlas of Morocco. Environment, 5, 131,2018. doi:10.3390/environments5120131[4] Wibowo A., Yusoff M. M., Adura T. A., andShidiq I. P. A. Urban Heat Hazard Threat on
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

POLICIES AND PLANS FOR OPEN SPACE MANAGEMENT IN
PARTNERSHIP IN POST-INDUSTRIAL LANDSCAPES

1

Tomoko Miyagawa1, Clare Olver2, Noriko Otsuka3, and Hirokazu Abe4
Faculty of Systems Engineering, Wakayama University, Japan; 2 The Mersey Forest, the UK;3
ILS Research gGmbH, Germany; 4 Cyber Media Centre, Osaka University, Japan

ABSTRACT
Post-industrial landscapes have transformed through environmental regeneration, creating open spaces withpublic access. To maintain quality in the long term, working in a partnership with voluntary, community, public
and private organisations may be necessary. This paper examines policies and plans for open space management
through community forestry activities in the post-industrial landscapes of St. Helens in the UK, where the Council
has been updating masterplans for green infrastructure. The study methods used here are literature reviews andinterviews. This study undertook the two case studies of action plans and one of the strategic sites from the plan
which are included within the masterplans for green infrastructure planning within St. Helens. Findings suggestthat policies and updated plans can be tools for maintaining sufficient standards of open spaces in restored postindustrial landscapes and to be well used by the community. However, this needs to be in tandem with partnerships
working towards long-term management by securing resources for open spaces.
Keywords: Community Forestry Activities; Environmental Regeneration; Green Infrastructure; long-term
management

INTRODUCTION

engaging communities in green infrastructure
planning, that is, having the potential to reduce publicmoney to be spent, while participation can bring a
sense of ownership and inclusion of the local
community [6]. Although Green Infrastrucutureplanning initially aims to respond the needs ofneighbouring communities by increasing the amountof green space for local benefits, such planning focus
tends to be shifted in practice. This is because somestakeholders put more priorities on economic benefits(e.g. increasing property values and place re-branding
to attract new residents, business growth andinvestment, [7]) than solving social andenvironmental issues in local neighbourhoods [8].
Moreover, it has become evident that there are gaps
in place-making and place-keeping, various
understandings of concepts among users,
practitioners, and policy makers due to ‘its
complexity and the wide implications’, and a wellestablished system for evaluating quality open spacein the long term [9]. Thus, long-term management isparticularly important given that post-industrial
landscapes contribute through their green
infrastructure in terms of restoring ecology andimproving the health and quality of life ofneighbouring communities [10]- [11].
To secure costs and time for sustainable
management, long-term management matters for its‘functionality and community appeal’ [12]. The UK
government’s policy document ‘The 25 Year Plan for
the Environment’ recognises the pivotal role of public,
private, and philanthropic funding to protect andEnvironmental regeneration, through community
forestry activities by public, private, and community
sector organisations, has been led by the Mersey
Forest Partnership in the northwest of the UK sincethe 1990s. The Mersey Forest is one of England’s
Community Forests which have been transforming
the landscapes and communities in and around ourlargest towns and cities [1]. Through its partnershipapproachenvironmental
regeneration
andlandscaping in post-industrial landscapes havecreated new open spaces, that are publicly accessible
and require long-term management and continual
enhancement. Environmental regeneration becomes
particularly important for managing and improving
the quality of post-industrial landscapes, as it has
been suggested that ‘even more importantly somespecific pollutant problems remain and will intensify’[2]. Therefore, it is important to consider ‘thecumulative impacts of change’ of newly created large
areas of publicly accessible open spaces by
incremental planting and by gaining public access tosmall parcels of former derelict and other lands’ [3].
Accessibility matters particularly for the public,
because ‘access to nearby nature that allows practicalengagement’ can lead to improve ‘in the challenging
settings of socially deprived urban areas’ [4].
Simultaneously, examining the policies that supportand ensure long-term management can also benecessary [5].
Long-term management can be a key issue in504

SEE-Mie, Japan, Nov.10-12, 2022

enhance the environment, including its role indeveloping and managing the Northern Forest, a newlandscape-scale tree planting project [13]. In the caseof the Mersey Forest, ‘community forestry
approaches have been achieved through a partnership,of over twenty years, with landowners and local
partners led by the Mersey Forest team, which has
secured resources for long-term management.
Working in partnership enables a diverse network ofpeople and groups to share expertise and diversify
activities [14]. In case of the Northwest of England,since 2004, the Mersey Forest team has led andhelped moderate policy making with the new agenda
of green infrastructure [1], [15]. In terms of benefits
in building community cohesion, it may also be
important to work in partnership to regenerate
damaged landscapes arising from contamination ordereliction, to empower the local community withenthusiasm [3].
The ultimate aim of this paper is to discuss key
factors which have contributed to a better partnershipworking in environmental regeneration by reviewing
local planning policies and presenting concrete
examples from two case studies in which the Mersey
forest has been involved over the last 20 years.

Joint Merseyside and Halton Waste Local Plan
(adopted July 2013) and the Bold Forest Park Area
Action Plan (adopted July 2017). This study
examined the two case studies of Bold Forest Parkand Colliers Moss Common using relevant maps andrevising planning documents including statutory andnon-statutory plans regarding open space
management policies in St. Helens focusing on postindustrial landscapes in St. Helens. Firstly, Bold
Forest Park is a priority area identified in local
statutory plans to promote better quality of open
spaces for community assets. The second case study
is Colliers Moss Common which demonstrates theimportance of securing resources for continuous
management, and was introduced as a best practice increating community open space and nature
conservation in England [19]. This research also
incorporated interviews with representatives from the
Mersey Forest team, and a local authority officer fromthe planning department of St. Helens Council to findout the main issues for long-term management. Theinterviews were held in August, 2018, and wereapproximately one hour each.
OPEN SPACE MANAGEMENT POLICIES IN
ST. HELENS

Study Methods
The St. Helens Council has undertaken open
space management through overall policies for theprotection of such spaces and promotion of green
infrastructure for ‘health, recreation, tourism, andbiodiversity’, as well as to support economic viability
and to act against climate change [18]. Over the past
25 years, the Council has been working closely with
the Mersey Forest team to create a network ofcommunity woodlands. In terms of protecting open
space, the designation of statutory registered sites andthe Green Belt have been implemented to secure landfor creating and maintaining green space for a longtime. According to the local plans adopted in St.
Helens, the overall policies are relevant to open space
management. To promote an area-wide strategy forgreen infrastructure at the regional level, the Council
has been working with the Mersey Forest Team toenhance existing and newly created networks ofcommunity woodlands.

This paper examines policies and plans
supporting the roles that the Mersey Forest
Partnership can play in the management of open
space in post-industrial landscapes, focusing on St.
Helens, located within the Liverpool City Region.
With an area of approximately 13,900 hectares [16]and a population of 180,585 in 2019 [17], St. Helens
developed rapidly during the Industrial Revolution
through coal mining and glass making which left alegacy of damaged landscapes in post-industrial sites[16], [18]. The St. Helens Council has experience inplanning and revitalising post-industrial landscapessince the 1980s [5], [19]. Post-industrial landscapesin St. Helens have been transformed into a variety ofopen spaces, with further opportunities as many
operational landfill sites have planning permission foropen space post closure. Further, the restoration
requires a certain time frame, some for around ten
years or more. To maintain the quality of open spaces
at sufficient standards, while simultaneously being
well-used by the community, it may be necessary toconsider planning policies that support and ensure
long-term management [5].
Thus, relevant literature was identified using
search engine platforms such as Google Scholar, withkeywords including ‘environmental regeneration’,‘local planning policies’, ‘St Helens’, ‘long-term
management’, and ‘open space’. The St. Helens
Council has adopted planning documents as follows:
Core Strategy Local Plan (adopted October 2012),
Saved Policies of the 1998 Unitary Development Plan,

Protection of Open Space and Promoting GreenInfrastructure
Open spaces within urban areas are underpressure from housing developers; thus, a sufficiently
robust policy framework is necessary. The St. Helens
Council has a policy of not permitting developmentthat would lead to the loss of existing open space ofspecific value, or where the development adversely
affects the amenity of open space or a Green Belt [16].
Protection of open spaces is promoted in terms of
multi-functionality, for example, recreation, amenity505

SEE-Mie, Japan, Nov.10-12, 2022

to provide quality public open spaces, conservation ofnature, and creation of culture and education [16].
Open spaces can be connected by strategic networksof greenways [18] including privately-owned landwith ‘major linear features’, such as ‘river valleys,
canal systems and disused railway lines’ (Fig.1). In
fact, the St. Helens Council sought to promote more
public access and to develop its network of linear
greenways [16]. The St. Helens Council has been
active in promoting the value of green infrastructure
to local communities, to increase additional open
spaces and to seek ‘positive uses’ by protecting,managing, and enhancing with detailed policies [18].

Mersey Forest Plan is a long term and strategic guideto the work of the Forest and its partners. It is
recognised in the National Planning Policy
Framework as a material consideration in preparing
development plans and deciding planningapplications. The Council has played an importantrole in transforming vacant and derelict land into
woodlands, such as the Wasteland to Woodland
programme which recognised the potential andcharacter of the southern and eastern areas of theborough [16]. The Mersey Forest Partnership has
promoted the benefits of regenerating post-industrial
landscapes in terms of ‘health, recreation, tourism andbiodiversity’ as well as reducing negative impacts ofclimate change, through policies and activities, suchas indicative woodland cover targets, and partnershipworking to support community forestry activities [1],[18]. A partnership between public and private
landowners, local authority officers, governmentorganisations, and the community was coordinated by
the Mersey Forest which played a key role intransforming the post-industrial sites into green open
spaces.
Wasteland to Woodland
The Wasteland to Woodland programme ran from1989 to 1998 [20]. It created at least 300 hectares of
new habitat and woodlands in St. Helens [18] throughlarge-scale tree planting on parcels of derelict land,
including previous colliery sites. Much of the land
was privately owned with no public access; therefore,
the project aimed to address the importance of largescale environmental regeneration for economic
benefits, and attracting investment. It also aimed atmeeting the needs of the community throughaccessible woodlands close to the urban population
where possible [20].
The strong partnership programme was led by asteering group comprising representatives frompublic and private landowners, local authority
officers, and government organisations, and wascoordinated by environmental charity, theGroundwork Trust. The individual projects became
known by the names of the former collieries andtransformed into publicly accessible woodlands, suchas Sutton Manor, Clock Face, Colliers Moss Common(formerly called Bold Moss Common), and Lyme &Wood Pits (Fig.2) [18]. These sites consisted of spoil
heaps, making up around 75 percent of the project
area of 330 ha in total [20], and have been included in
the plan for Town in the Forest and Bold Forest Park.
These have contributed to transforming the southernpart of St. Helens into the area addressing both
economic and environmental regeneration (Fig.3-4)[21]-[22].

Fig. 1 Map of case study areas with someamendments [18]St. Helens Council also recognises derelict landas an ‘existing or potential value of open space’.
According to a survey of open space in 1990,
approximately 505 hectares of land were classified as
vacant or derelict, and they have the potential toprovide functions as open spaces [16]. St. Helens
Council has been ensuring the transformation ofderelict land into open spaces such as woodlands or
grasslands with increased biodiversity; therefore, theimprovement of access by local communities andmanagement for conservation of biodiversity are thefuture tasks and priorities [18]. One approach fortransforming vacant or derelict land into open spaces
in St. Helens was the near-decade-long Wasteland to
Woodland programme.
The Mersey Forest
St. Helens Council was a founding local authority
partner in the Mersey Forest Partnership in 1994.
Since then, over 3,750 hectares of new habitat andwoodland has been created, with the aim of increasing
up to 8,000 hectares in the long term [18]. The St.
Helens Council supports the delivery of the Mersey
Forest Plan through policies within its adopted local
plans and through the promotion of additional areas
for further development of the community forest. The
506

SEE-Mie, Japan, Nov.10-12, 2022

Fig. 2

While newly planted mature woodlands can havea positive impact in regenerating and enhancing an
area [1], [21]; they can be opportunistic. Over onethird of all the woodlands in St. Helens is recently
regenerated and these newly planted trees require
substantial time to grow to maturity [21]. To support
and guide this landscape transformation, a woodland
strategy was published by St. Helens Council in 2006:“Town in the Forest” to guide the creation of a
network and enhancement of woodlands. The plan
identified sites for developing woodlands which
would contribute to and enhance the landscapecharacter of the area, with diversity anddistinctiveness [21]. The plan aimed to promote
greening and developing linear forests in urban areas,
particularly in the urban fringe through renewal
processes and connecting green infrastructure tocommunity woodlands, so that the regenerated area
could also potentially contribute to the rural economy[18]. This not only could create direct employment
but also to provide a healthy working environment inleafy settings to attract inward investment, andcontribute to increasing property values [21].
Therefore, improving the image of the area for
economic benefits was suggested throughenvironmental regeneration [21].
The plan of St. Helens Town in the Forest
Strategic Vision Document analysed the area in termsof transport network, nature conservation, education,
recreation, and regeneration opportunities. It
identified the sites, including Sutton Manor, Clock
Face, Colliers Moss Common (formerly Bold Moss
Common), and Lyme and Wood Pits as recent
woodlands created within the past 20 years, and also
identified areas of potential tree and woodland
planting (Fig.3) [21]. The plan suggested that a
network between these open spaces be developed tocreate a woodland framework around the mentioned
sites (St. Helens Council, 2006). The Mersey Forest
Plan for St. Helens also suggests 20-30% increase inwoodland planting on urban fringes, which includes
these key sites [1], [21].

Map of former collieries sites [20]Fig. 3 Map of the area for tree planting with someamendments [21]Nature Conservation and Site Protection
The St. Helens Council published a Policy for
Nature in 1986, defining the importance of wildlife
conservation, providing informal space for recreationand education, and improving the image of theborough [16]. Thus, the multi-purpose value of trees,
woodlands, and hedgerows will be protected andenhanced by the Council [18]. Statutory site
protection, such as local nature reserves, ancient
woodlands, local wildlife, and geological sites wereadopted to secure the continuity of open spaces andenhance protection of the natural environment. For
example, the Northern part of Colliers Moss Common
was designated as a local nature reserve, a statutory
designation [23]. Sutton Manor, Clock Face, ColliersFig. 4 Map of the Bold Forest Park with someamendments [22]Town in the Forest

507

SEE-Mie, Japan, Nov.10-12, 2022

Moss Common, and Lyme & Wood Pits were
designated as local wildlife sites. This is a nonstatutory designation, locally registered within northMerseyside to represent ecological diversity [24]. St.
Helens Council addressed the importance of
biological, educational, and community interests andvalue on these sites [16], and therefore developed amasterplan for green infrastructure which is now
recognised as one of the main statutory planningpolicies along with the Core Strategy and the Local
Plan.

attracting more local communities [18]. The plan
aims to support the local economy by increasing
opportunities for recreation [22] by promoting Bold
Forest Park as a gateway to the town and as a modelcase for managing large-scale open spaces of former
collieries. The Mersey Forest plan also recognises thearea represents potential sites for leisure activities by‘improving tourist infrastructure and creating new
visitor attractions’ [1].
Most of the area is designated within the Green
Belt with five recreation hubs, including Sutton
Manor, Clock Face, and Collier Moss Common
connected by key walking routes, road links, andproposed bridle ways to enhance its network andimprove access. There are two railway stations
between Liverpool and Manchester close to
Brickfields and Colliers Moss Common, whichmakes Bold Forest Park easily accessible by train.
The M62 motorway transects Forest Park, adjacent to
the Griffin Wood and Sutton Manor. The Mersey
Forest team is seeking a partnership to find resources
to deliver the aspirations of the Area Action Plan thatare being developed.

Green Belt
The Green Belt in St. Helens was designated in1983 to control urban sprawl, to conserve thecountryside, to support urban regeneration, and ‘thepermanence and protection of Green Belt boundaries’,
as well as promote the inclusion of land in the Green
Belt [16], [25]. The release of the Green Belt for land
supply is a sub-regional issue in the Liverpool City
Region to be considered in terms of sustainability tominimise the impact on the remaining Green Belt [18].
The Green Belt in St. Helens is located around theurban fringe and extends into the urban area. Around
50% of the borough is categorised as ‘rural’ (Fig.1)[16]. Most of the land within the Green Belt in St.
Helens in the north of the borough is a high-quality
agricultural land; however, it also includes seven golfcourses; in the south, the Green Belt includes newly
created community woodlands on former collierysites and agricultural lands [18]. Thus, the Green Belt
can promote the creation of a network of open spaces
with an area-wide environmental policy forconservation.
The next section presents the masterplan forincreasing woodlands and two case studies, in St.
Helens, which are considered a good practice increating community open spaces in post-industrial
landscapes. First the concept of an action plan of Bold
Forest Park will be examines and followed by, an
example of a strategic site, Colliers Moss Common
from the plan.

Colliers Moss Common - A Case Study
Collier Moss Common, formerly called Bold
Moss Common, is a former mossland complex which
was subject to tipping from the former Bold Colliery
and Bold Power Station. Owned by the National Coal
Board, the site ownership was transferred to the
Groundwork Trust St Helens, Sefton, and Knowsley
in 1990, who subsequently undertook an ecologicallyled restoration to create a valuable community asset
from derelict land. Restoration was completed in
1994. In 2005, the site was designated by the St
Helens Council as a local nature reserve inrecognition of the site’s ecological and social
importance.
The Groundwork Trust for St Helens went into
receivership in 2006 and the land was declared bonavacantia, coming under the remit of the Duchy of
Lancaster, as owner of last resort with nomanagement of the open space. This led to vandalism,
and the site attracted anti-social behaviour. Having
unsuccessfully attempted to access government
assistance to address the problem, St Helens Council
requested that the charity Community Forest Land
Trust (CFLT) acquires ownership of the land in order
to seek a partnership-led approach to a solution.
CFLT took ownership in 2014. It is run by a board of
five voluntary trustees and, with no regular funding,must generate income to carry out its activities.
Owing to the ownership of the site, CFLT has
facilitated a range of bids for external funding. In total,£213,000 external funds were generated for the
improvement of the site from a variety of funding
sources. Concurrently, a number of funding bids havebeen unsuccessful, and clearly demonstrates that open

CASE STUDY OF STRATEGIC AREAS IN THE
SOUTH OF ST. HELENSBold Forest Park- A Case Study
Bold Forest Park was recognised as a priority area
to increase green infrastructure within the core
strategy and local plan in St. Helens [18]. The Bold
Forest Park Area Action Plan was adopted in 2017 toregenerate 320 hectares of land with a legacy of raised
spoil heaps of the former collieries industry [22]. The
vision of the Action Plan was to ‘create new
economicopportunities
through sustainable
development’ by promoting leisure and tourism andcreating networks of open spaces as assets for508

SEE-Mie, Japan, Nov.10-12, 2022

spaces require continuous management by securing
funding, due to the absence of sustainable
management plans that can cause anti-social
behaviour. It is part of the Collier Moss Common
Recreational Hub in the Bold Forest Park Area ActionPlan.

economic impacts, such as leisure and tourism,
through the development of Forest Park as a subregional tourist offering located between Liverpool
and Manchester. The case of Colliers Moss Common
has suggested that continuous management andfundamental condition of the quality of theenvironment on sites are required for further
improvement and enhancement as it became clear
from the open space assessment in the previous
section. The case studies found an essential role ofpartnership working as one of the priority issues insustainable Green Infrastructure planning, and thispoint has been echoed by a number of previous
research [6], [14], [28]- [29]. The case studies also
foundpartnershipworkingwithvariousorganaisations can contribute to long-term
management by enhancing assets and functions ofGreen Infrastructure for social, economic, andecological benefit [28]- [29].
According to an interview given by a former
planning officer of St. Helens Council, long-term
open space management is an important issue, and it
can be challenging to secure resources [9], [30]-[34].
Collaboration of experts with specific skill sets isimportant, and the same planning officer interviewed
maintains that the quality of open space matters, if
open space is not well-managed, ‘it can cause
problems and bring no benefits to the community’. In
terms of collaboration, it may be necessary to lookafter landscaping former landfills, which requires theinvolvement of experts in waste and mineralmanagement, ground maintenance, as well as theplanning department. The quality of open space canonly be ensured when such partnerships are in place,based on a long-term strategic maintenance plan.
In St. Helens, The Mersey Forest has been leading
the partnership in applying for funding andundertaking projects, while the St. Helens Council
has updated relevant plans for green infrastructure
planning. Therefore, partnership plays a key role incollaborating with a wide range of people to deliver
the plan and undertake long-term management. It
requires securing regular funding to maintain open
spaces, which has been an issue. The UK government
policy, the 25 Year Plan for the Environment,
recognises the significance of securing a mixture of
public and private funding and financing with various
partners for long-term management [13]. This point
has been evident in the two case studies, and constantefforts made by the Mersey Forest and St. Helens
Council in securing resources for maintenance andimprovement are the key ingredients for providing
neighbouring communities with high-quality open
spaces in post-industrial landscapes.

DISCUSSIONS
The industrial landscape of St. Helens has beendeveloped for over 250 years [20]. In comparison,policies for open space management and several
action plans for transforming post-industrial sites
have been undertaken for environmental regenerationin St. Helens over the last 30 years since the 1990’s.
Environmental regeneration requires extensive time
for trees to grow into mature woodlands, due to thecomplexity of ‘greening’ process and ‘the results areoften only partially successful’ [26]. Open space
management policies in St. Helens are continuously
identifying strategic sites, e.g., Sutton Manor, Clock
Face, Colliers Moss Common, and Lyme & Wood
Pits to promote environmental regeneration withlong-term management (Fig.2-4). For example, St.
Helens Town in the Forest Strategic Vision
Document in 2006 promoted additional planting byidentifying existing and new woodland planting toincrease the connectivity between woodlands createdat different times; therefore, the network of green
spaces was a key issue. Sutton Manor, Clock Face,and Colliers Moss Common can be categorised into
‘natural and semi-natural sites, including woodlands,
grasslands, and former collieries and quarries [27],which play an important role in linking nature andformer industrial sites. It can demonstrate activities
on sites from former industrial to environmental
regeneration to be opened to the communities, byutilising hill-shaped landforms which can become alandmark to the area. Lyme & Wood Pits was aformer colliery and a waste disposal site, and is being
reclaimed in the process of waste disposal operations,following the restoration and the creation of newaccess to surrounding neighbourhoods, it has opened
as a country park [18]. In terms of the open spaceassessment based on the Green Flag Award scheme,
which sets a management standard for parks and open
spaces in England and Wales, the results have shownthat Sutton Manor, Clock Face, and Lyme & Wood
Pits are undertaking quality of management, while
Collier Moss Common needs further improvementsin the quality of green open spaces, access, security,
facilities, maintenance, and use by different groups ofpeople [27].
This study undertook the two case studies ofaction plans and one of the strategic sites from theplan which are included within the masterplans forgreen infrastructure planning within St. Helens. The
Bold Forest Park Area Action Plan in 2017 was a
statutory planning document with a focus on

CONCLUSIONSIn St. Helens, through environmental
regeneration, networks of publicly accessible open509

SEE-Mie, Japan, Nov.10-12, 2022

spaces have been developed supported by policies fortheir long-term management. Over the past decade,green infrastructure masterplans have been revised
and published by St. Helens Council alongside thearea-wide Mersey Forest Plan. In terms of thedelivery of these plans, the Mersey Forest Partnershiphas and continues to secure resources from public andprivate landowners, local authorities, charities,
government organisations, and the community.
It
is also highlighted in the adopted local plans, as wellas The Mersey Forest Plan which identifies priority
areas for planting more trees, as a recommendation toenhance community forestry activities. In response
to local planning policies and to address local issues,action plans have been created and updated to meetthe needs of the area and the community inaccordance with the progress of environmental
regeneration for further enhancement.
Key
restoration and community woodland projects onformer collieries represent a variety of open spaces,and demonstrate that post-industrial landscapes canbe a driver for recreation development andcommunity engagement. In conclusion, to promotelong term open space management, policies andupdated plans can be a basis for introducing planning
tools to maintain sufficient standards in restored postindustrial landscapes and to be well used by thecommunity. However, these policies and action plansneed to work alongside delivery by partnerships, tofacilitate securing resources for long term
management of open spaces to improve and maintainenvironmental regeneration.

pp.295-312.
[5] Miyagawa, T., Olver, C., Otsuka, N. & Abe, H.,
Environmental regeneration and management in
partnership in the Northwest of England.
International Journal of GEOMATE, Vol.16,
Issue 54, 2019, pp.9-15.
[6] Wilker J., Rusche, K., & Rymsa-Fitschen, C.,
Improving Participation in Green Infrastructure
Planning. Planning Practice and Research, Vol.31,
No.3, 2016, pp.229-249.
[7] Forest Research, Benefits of green infrastructure.
2010.
[8] Horwood, K., The Development of GreenInfrastructure Policy in the North West Region of
the UK 2005–2010. Planning Practice andResearch, Vol.35, No.1, 2020, pp.1-17.
[9] Dempsey, N. & Burton, M., Defining placekeeping: The long-term management of public
spaces. Urban Forestry & Urban Greening, Vol.11,
No.1, 2011, pp.11-20.
[10] Williamson, K.S., Growing with GreenInfrastructure. Heritage Conservancy, 2003, pp.120.
[11] Handley, J., Pauleit, S. & Gill, S., Landscape,sustainability and the city. In: Landscape andSustainability, J. F. Benson & M. Roe, Ed.
Routledge, 2007, pp.167-195.
[12] Davies, C., Old culture and damaged landscapes:
The new cultural landscapes of post-industrialsites in Britain. In: New cultural landscapes, M.
Roe & K. Taylor, Ed. Routledge, 2014, pp.41-58.
[13] HM Government., A Green Future: Our 25 Year
Plan to improve the Environment. 2018.
https://www.gov.uk/government/publications/25year-environment-plan[14] Miyagawa T., Olver C., Otsuka N., Kurose T. &Abe H., Lessons and achievements from the
Mersey Forest by networking partnership fortwenty years. International Journal of GEOMATE,
Vol.15, Issue 48, 2018, pp.48-54.
[15] Mell, I., What Future for Green Infrastructure
Planning? Evaluating the Changing Environmentfor Green Infrastructure Planning Following the
Revocation of Regional Planning Policy inEngland. Planning Practice and Research, Vol.35,
No.1, 2020, pp.229-249.
[16] St. Helens Council., St. Helens Unitary
Development Plan (Originally Adopted by St.
Helens Metropolitan Borough Council on 2ndJuly1998),
1998.
https://www.sthelens.gov.uk/planning-buildingcontrol/planning-policy/unitary-developmentplan/[17] St. Helens Council, info4St.Helens website.
2019. https://info4.sthelens.gov.uk/[18] St.Helens Council., St. Helens Core Strategy.
2012.https://www.sthelens.gov.uk/media/3385/sthelens-local-plan-core-strategy-october-2012.pdf[19] Ling, C., Handley, J. & Rodwell, J.,

ACKNOWLEDGMENTS
The authors would like to express their gratitude
for the financial support provided by the Japan
Society for the Promotion of Science (17K06705,
18K18602). The authors would also like to thank theDevelopment Plans Section, St. Helens Council, andNorthwest of England Groundwork Trust forproviding information.
REFERENCES[1] The Mersey Forest, More from trees, The Mersey
ForestPlan.
2014.
https://www.merseyforest.org.uk/about/plan/[2] Freer-Smith, P., Environmental Change and theSustainability of European Forests. Journal of
Sustainable Forestry, Vol. 24, No.2-3, 2007, pp.
165-187.
[3] Roe, M., Exploring future cultural landscapes. In:
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Routledge, 2014, pp.241-269.
[4] Brook, I., The Importance of Nature, GreenSpaces, and Gardens in Human Well-Being.
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[20] Groundwork St Helens, Knowsley & Sefton.,
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2006.
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Forest Park Area Action Plan. 2017.
https://www.sthelens.gov.uk/planning-buildingcontrol/planning-policy/area-action-plans/[23] Natural England, Designated Sites View.
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Search.aspx[24] St. Helens Council, Local Wildlife Sites.
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https://www.sthelens.gov.uk/media/9432/greenbelt-review-2018.pdf[26] Moffat, A.J., Chapter 21: Green infrastructure
and regeneration of brownfield land. In:
Handbook on Green Infrastructure, D. Sinnett, N.
Smith & S. Burgess, Ed. 2015, pp.395–413.
[27] St. Helens Council, St. Helens Council OpenSpace Assessment Report. Knight, Kavanagh &Page, 2016.
[28] Mell, I., Can green infrastructure promote urban
sustainability? Proceedings of the Institution of
Civil Engineers -Engineering Sustainability, Vol.
162, No.1, 2009, pp.23-34.
[29] Lennon, M. & Scott, M., Delivering ecosystems
services via spatial planning: reviewing thepossibilities and implications of a green
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[30] Thompson, C.W., Urban open space in the 21st
century. Landscape and Urban Planning, Vol.60,
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[31] Konijnendijk, C.C., A decade of urban forestry
in Europe. Forest Policy and Economics, Vol.5,
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[32] Reeves, N., The Condition of Public Urban Parks
and Greenspace in Britain. Water andEnvironment Journal, Vol.14, 2007, pp.157-163.
[33] Dempsy, N. & Smith, H. Understanding placekeeping of open space. In: N. Dempsy, H. Smith,& M. Burton, Ed. Place-Keeping Open SpaceManagement in Practice, Routledge, 2014.
[34] Pediaditi, K., Doick, K.J., and Moffat, A.J.,
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regeneration to greenspace initiatives: A metaevaluation of assessment and monitoring tools.
Landscape and Urban Planning, Vol.97, No.1,
2010, pp.22-36.

511

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

SURVEY ON RESIDENTS' AWARENESS TO BUILD THE SYSTEM OFRESIDENTS’-PATTICIPATION MONITORING FOR SLOPEDISASTER PREVENTION USING THE TILT SENSORS
Zhijun Tang1, Yoshikazu Miyamoto 2, Shusuke Oji 3 and Hisashi Fujitani 4
Zhijun Tang１ in Yamanashi University and Chuo Kaihatsu Corporation，Japan
Yoshikazu Miyamoto 2 in Chuo Kaihatsu Corporation，Japan
Shusuke Oji 3 in Chuo Kaihatsu Corporation，Japan
Hisashi Fujitani 4 in Chuo Kaihatsu Corporation，Japan
ABSTRACTIn recent years, due to the effects of climate change, slope disasters have been occurring frequently and causing
severe damage in many places across the globe. In order to reduce the damage of slope disasters, it is important
for residents to understand hazards of the slope disaster correctly and protect themselves.
In this paper, we attempt to evaluate risks of slope disasters in local residential area and analyze resident’s
opinions which gathered trough a workshop with residents about resident‘s participation slope disaster monitoring
using tilt sensor for prevention of slope disaster.
As a result, an overview of the evaluation items for high-risk slopes and their contents was clarified, which had
been tacit knowledge, and the structure of local residents' concerns about slopes and their expectations formonitoring by utilizing tilt sensors to take evacuation action.

Keywords: Evacuation, Residents’ awareness survey, Slope disaster, Tilt sensor, Monitoring
INTRODUCTION

themselves monitor the slopes.
A field survey was conducted in the sedimentrelated disaster warning area from a geologicalexpert’s viewpoints, and high-risk slopes wereselected.
A workshop was held for local stakeholders to
select houses that should be evacuated to install IOT
tilt sensors [4] on selected slopes at high risk of slope
failure. In that workshop, the characteristics of the tilt
sensors, control thresholds, and lead time for
evacuation were explained to the residents to foster
their awareness. And then, discussion was held withresidents with regard to resident’s concern to theslopes and their expectations for monitoring by
utilizing tilt sensors to take evacuation action.
In this paper, we attempt to evaluate risks of slope
disasters in local residential area and analyze
resident’s opinions which gathered trough aworkshop with residents about resident’s
participation slope disaster monitoring using tilt
sensor for prevention of slope disaster.

In recent years, due to the effects of climatechange, slope disasters have been occurring
frequently and causing severe damage in many placesacross the globe. In order to reduce the damage ofslope disasters, it is important for residents tounderstand hazards of the slope disaster correctly andprotect themselves.
In Japan, there are about 2.7 million dwelling
units in contact with the sediment-related disasterwarning area, and even if the warning information istransmitted, the damage caused by the delay in escapeis constant [1].
There are various factors such as the tendency not
to receive warning information as one's own matter,
the tendency to avoid evacuation, and the problem of
the normalcy bias [2]-[3].
As an aid to solving such problems, by installingan IOT tilt sensor [4], we will directly notify therelevant residents of the warning alarm of sedimentrelated disasters and encourage the residents to takeevacuation actions to protect themselves. The purpose
is to verify whether it is possible to build a connection
mechanism.
Therefore, after consulting with local residents inFukuchiyama City, Kyoto prefecture, Japan, where
had suffered landslides in the past, to make themaware of the actual slope hazards, we proposed a"slope monitoring system by resident participation
using IOT tilt sensors" in which the residents

ARAKI DISTRICT, FUKUCHIYAMA CITY,
KYOTO PREFECTURE
The Araki district of Fukuchiyama City, Kyoto
Prefecture, is located in the middle reaches of theHaze River on the east side of the city of
Fukuchiyama. The number of households in the
district is 67, the population is 157, and the populationof elderly people aged 70 and over is 42, as in [5].
512SEE-Mie, Japan, Nov.10-12, 2022

As shown in Fig. 1, almost the entire area of themain part of the area is designated as a sedimentrelated disaster warning area, and part of it isdesignated as a sediment-related disaster special
warning area. There are three evacuation centers in
the Araki area: Araki Public Hall at the foot of themountain, Momijigaoka Hospital, and Toei JuniorHigh School.
In the heavy rains in August 2016, moist air
flowed into the stagnant fronts in the Kinki region,and local heavy rains hit the Kinki region andHokuriku.In Fukuchiyama City, the 24-hour rainfall
on the 16th to 17th exceeded 300 mm. In addition, theYura River temporarily exceeded the flood risk level,
and many inland floods and landslides occurred.
Evacuation advisories were issued to about 80,000
people throughout Fukuchiyama City, and theGround Self-Defense Force was dispatched to help.
Furthermore, due to this heavy rain, the JR
Fukuchiyama Line and the San-In Line were cut off,
and the social impact became extremely large. In the
Araki district, sediment-related disasters occurred inseven places, such as the collapse of the mountainbehind a private house. After that disaster, thevoluntary disaster prevention organization by the
Araki Neighborhood Association, with thecooperation of the Fukuchiyama City government
and Kyoto University, set up its own "evacuation
switch" that defines the criteria for residents to startevacuating using landslide potential information andsoil rainfall index. [6].

on the inside of the person who received "external
information / situation". Disaster information such as
disaster prevention weather information andevacuation information are "advanced" and"complex", but residents want to know more about
whether they are still okay or really dangerous thandetailed evacuation information. This is informationthat leads to the next action as in [8].
When setting the "evacuation switch" forinformation that turns on / off the switch inside theperson that leads to the next action, not only thedisaster prevention weather information provided by
the specialized agency, but also the local residents
themselves. It is important to utilize a wide range of
information such as phenomena that local residents
can observe and cases of historical disasters.
Yamori et al. also argues that diversification anddouble tracking of information that contributes to"switches" is more important than the sophisticationof disaster prevention weather information itself
when looking at disaster prevention and mitigation in
the coming decades.
Based on the above discussion, this paper considers
evacuation switches in slope hazards that can be
added to the currently applied landslide potential
information and soil rainfall indices. Groundwaterlevel and soil moisture content cannot be confirmed
without the installation of measuring equipment, andthese data in cloud uncertainty because they areindirect methods of observing slope failure potential.
In addition, it is dangerous to confirm flooding,inflow water from slopes, and falling pebbles on site.
For these reasons, this paper study whether alertsfrom IOT tilt sensor which measure slope degree
directly can be used as evacuation switches.

Issues surrounding evacuation information andevacuation behavior
There is multiple awareness of the problem that
evacuation information is not directly linked to theevacuation behavior of residents in previous studies
on evacuation.
In a study by Takenouchi et al., taking the case ofheavy rainfall in northern Kyushu in 2017, they arepaying attention to the fact that there are criteria forjudgment the area is unique, such as the situation of
streams flowing through the district, the inundation
situation of houses beside it, and the inundation
situation of small bridges in the neighborhood, etc.
[7].
From this study, it can be seen that in addition toevacuation information, "external information /situations" such as loud voices, voices of people close
to us, behaviors of people around us, and inundating
conditions have an effect on evacuation.
On the other hand, Yamori et al.'S research focuses

Map data©2022 Google
Fig. 1

513

Araki district, Fukuchiyama City, Kyoto
Prefecture (Site 2 and 3 where tilt sensors are
installed)

SEE-Mie, Japan, Nov.10-12, 2022

METHOD OF SELECTING SITES FOR TRIALMONITORING

the other hand, if the entire slope has collapsed in thepast and no surface soil is present, the risk of morecollapse may be low.

The selection of sites for trial monitoring was
conducted at candidate sites in the Araki area. Sevensites proposed by local residents were inspected
together with t them to evaluate the degree of risk ofdisaster on the slopes. Although there are no
established methods for evaluating slope hazard, so,
the following six items were identified based on the
results of the inspection. Slopes with relatively highlevels of each of these six items were evaluated on athree-point scale, and slopes with relatively highlevels of each of these items were evaluated as having
high risk. As a result, the slopes at Sites 2 and 3 wereselected for trial monitoring. (As shown in Table 1
and Fig.1).
Table 1

(C) Relatively tight slope
Natural slopes are more easily to collapse if theslope is relatively tight (greater than about 30°).
However, even if the slope is relatively tight, theslope is not easily to collapse if there is no collapsible
surface soil.
(D) Possibility of collapsed sediment reachinghouses, etc.
The risk is high if there is a possibility that
sediment from a slope that is expected to collapse willreach houses and other structures that are to bepreserved. Even if collapsible surface soil is
distributed, it will be not a disaster if it is expectedthat it will not reach houses and other structures.

Evaluation sites for trial monitoring
Site

Evaluation Items

1

2

3

4

5

6

7

(a)Slopes with no
exposed base rockand collapsible
surface soil

△

◎

◎

-

◎

△

△

(b) Evidence of pastcollapse or cracks-(c)Relatively tight
slope

◎

◎

◎

◎

〇

◎

〇

(d)Possibility ofcollapsed sedimentreaching houses, etc

〇

◎

◎

△

◎

△

-

(e)Facing a publicbuilding

◎

-

-

-

◎

-

-

(f)The degree ofdamage is assumed
to be above a certain
scale

○

◎

◎

△

◎

△

○

(E) Facing a public building

Note: ◎：much applicable△：a few applicable

◎

〇

-

-

◎

◎

If the conservation target to be damaged in theevent of slope failure is a public building such as ashelter, community center, government office, or
facility requiring nursing care, the damage may belarger and the risk of disaster is considered higher.
(F) The degree of damage is assumed to be above
a certain scale
If the slope collapses, the risk of disaster isconsidered significant if the damage is expected to be
above a certain scale, such as when sediment reaches
multiple houses, roads, or other public facilities, orwhen there is a possibility of causing further damage.
These evaluation items and scales are based on thetacit knowledge of experts and have not yet been
established. So, we will attempt this evaluation
method to many slopes for establishing from now on.
After selecting the location, we will hold on-site
discussions with the house owner (also the landownerof the slope), listen to the situation of past slope
disasters, and install a tilt sensor in consideration of
the microtopography of the slope, and we examined
the position where it to be.
Then, at the position where there is a possibilityof collapse, two tilt sensors are installed at site 2 andthree at site 3, and started trial monitoring.

〇 ：applicable- ：not applicable(A) Slopes with no exposed base rock andcollapsible surface soil
Talus deposit are present on the slope, or surface
soils formed by weathering of base rock or otherprocesses [9]. If the surface soil is not sufficiently
covered with forest vegetation, it is considered to beparticularly led to collapse [10]. If there are an
exposed of hard basement rock on the slope, it isunlikely to collapse except by landslides.
(B) Evidence of past collapse or cracks

WORKSHOP

If there are traces of collapse or cracks in or neara part of the slope, it is likely to collapse easily. On

A workshop on slope disaster evacuation using tilt
sensors was held at Araki Public Hall with local
514

SEE-Mie, Japan, Nov.10-12, 2022

residents, Fukuchiyama City government, andProfessor Yamori of Kyoto University.
In the workshop, local residents were made awareof the characteristics and dangers of slopes, thehandling of tilt sensors, control thresholds, andevacuation lead times were explained to them.
Afterwards, discussions were held on concerns aboutslopes and expectations for tilt sensors. (As shown in
Fig.2).

characteristics because it is far away (large) [11]-[12].
Analysis results
As a result of morphological analysis of the 9’s
answers obtained in the workshop, 220 total words
and 88 different words were extracted. Figure 3 is adiagram showing the co-occurrence network with aminimum number of occurrences of 2 for the remarksof local residents in the workshop.
The content of the remarks obtained in theworkshop is divided into groups by automaticallydetecting words that are relatively strongly connectedto each other, and the results are shown by color
coding.
A total of five words were extracted as theanswers characteristic of the golden system: "slope,""collapse," "heavy rain," "road," and "scary."

Local residents' anxiety and concern about heavy
rain / sediment disaster
Anxieties and concerns about heavy rains / slope
disaster are deep-rooted, especially among local
residents.
From the workshop, the opinions on the anxieties
and concerns of the local residents regarding heavy
rain / sediment disaster were analyzed using the cooccurrence network of text mining analysis.

Collapse

Slope

MountainFeel uneasy

DisasterHouse
Heavy rain
Araki district

Uncanny

Fig. 2Road

Workshop in Araki district.

Disaster prevention
information

Analysis method
By performing co-occurrence network analysis, it
is possible to visualize word-to-word connections(co-occurrence relationships). The circles in the
figure represent the extracted words. The size of thecircle indicates the frequency of appearance of words,
the higher frequency of appearance, the larger circle.
In this paper, we used subgraph detection, which
automatically detects and groups words that are
relatively strongly connected. The lines in the figure
represent the strength of the co-occurrence
relationship. The darkness of the line indicates thestrength of the co-occurrence relationship, thestronger connection, the darker color of line.
In addition, the Euclidean distance coefficient(“similarity” for words similar to distance) is used on
the line representing the co-occurrence relationship.
The Euclidean distance coefficient shows therelationship between similarity and distance,
Similar = High similarity = Close distance (small)
Dissimilarity = low similarity = strong

Fig. 3Results of co-occurrence network analysis.

As the answers characteristic of the light blue
system, a total of 6 words were extracted: "Araki
district," "disaster," "mountain," "feeling uneasy,""house," and "disaster prevention information."
This is a visualization of the co-occurrence
relationship between the yellow system and the light
blue system, and the difference in viewpoint
depending on the degree of similarity and distance.
In this study, the following four points wereclarified as a result of the co-occurrence network
analysis of text mining about the anxieties andconcerns of the local residents regarding heavy rain /sediment disasters at the workshop conducted for the
local residents in the Araki area. (As shown in Fig.3).
(a) Regarding Workshop, the content of theremarks automatically detects words that are
relatively yellow connected to each other and divides
515

SEE-Mie, Japan, Nov.10-12, 2022

them into golden and light blue groups, and therepresentatives of the words are "heavy rain," "slope,""collapse," and "feel uneasy".
(b) Regarding Workshop, it was recognized thatthe network of words characteristic of the light blue
system has a coefficient of 1.0 for "mountain" and"disaster", and darker line, indicating a strong
connection between "mountain" and "disaster.
It was recognized that the network of words
characteristic of the yellow system has a coefficientof 0.60 for "slope" and "collapse", and thicker line,
the stronger the degree of co-occurrence. It indicatesa heavy correlation between "slope" and "collapse".
(c) The connection between "slope," "collapse,""road," and " uncanny" was also observed around"heavy rainfall." It is thought that heavy rain, specificobjects such as slope collapse and roads, and the fearof these objects are perceived as a strong relationship.
(d)Focusing on the relationship between the light
blue colors, a network of "Araki District" and"disaster," "mountain," "anxiety," "house," and"disaster prevention information" can be seen. This isthought to represent the relationship between the
Araki district's elements for disaster anxiety anddisaster prevention.

connecting of their statements with arrow lines
considering their context. As a result, the statements
can be categorized into "factors of expectations" and"expected utilities.
In this diagram, the expected elements of the tilt
sensor are: (a) the information can be received by acellular phone, (b) the risk can be visualized, (c) the
information on specific site can be checked, and (d)the information is about a nearby slope. In theseelements, (a) and (b) are factors of expectations forthe characteristics of the system provided by the tilt
sensor. In addition, (c) and (d) are considered to be
the reason for the expectation of being able to obtain
information on the behavior of the slope itself where
the tilt sensor is installed, compared to disaster
information issued for a wide area, such as disaster
potential information and landslide warning
information.
These factors lead to the expectation of utility: (a)→ (e) evacuation can be planned, (b) and (c) → (f) toserve as the basis for evacuation decisions, and (d) →(g) early evacuation can be taken into consideration.
In other words, slope monitoring with tilt sensors is
expected to increase the utilities for evacuation
planning, early evacuation, and evacuation decisions
by local residents. On the other hand, there is also an
opinion that "(i) It will be a reference for deciding
when to return home". It is expected to be valuable
information for making a decision to return homefrom the evacuation center.
These factors of expectations and expectedutilities by residents should be fully considered indeveloping a system for participatory slope
monitoring.

Factors of expectations and expected utilities by
local residents
From the workshop conducted in the Araki district,the opinions of local residents regarding their
expectations of tilt sensors are shown in a structured
diagram (as shown in Fig. 4). This structural diagramvisualizes the local residents' statements by breaking
them down into their constituent elements andFig.4 The Structure on factors of expectations and expected utilities by local residents
516

SEE-Mie, Japan, Nov.10-12, 2022

CONCLUSIONS[2] Sugiman, T., and Misumi, J., of a new evacuation
method for emergencies , Control of collective
beha.Development vior by emergent small
groups. Journal of Applied Psychology, No.73,
1988, pp. 3-10.
[3] Satoru KIKUCHI , How to recognize cognitive
biases in risk perception in case of disasters.
Journal of the Japan Landslide Society. Vol.55,
No.6, pp.286.201[4] Uchimura, T., Towhata. I., Wang, L., Nishie S.,
Yamaguchi, H., Seko, I. and Qiao, J.P. ,Precaution and early warning of surface failureof slopes by using tilt sensors, Soils andFoundations, Vol.55, No.5 , 2015 , pp. 1086-1099.
[5] National
SurveyofJapan:
https://www.stat.go.jp/.2020.
[6] Japan Meteorological Agency "Weather Cases
that Caused Disasters Heavy Rains from Fronts
August 15, 2014-August 20, 2014 (Preliminary
Report)", August 21, 2014.
[7] Katsuya Yamori,and Kensuke Takenouchi,
Setting My Switch For Early evacuation ,2017
Northern Kyushu Heavy Rain Disaster Survey
Report,Kyoto University Disaster Prevention
Research Institute,2018,pp.99-102.
[8] Katsuya
Yamori,Swing,
FACP
Model.Evacuation
SwitchRethinking,
Evacuation from Heavy Rain Disasters, Scienceof Fire and Disaster Prevention, No.134, 2018,
pp.7-11.
[9] Kazuya Akiyama , Road earthwork-cutting
earthwork / slope stabilization work guideline ,Maruzen Publishing Co., Ltd, 2009, pp.14.
[10] Tomoyuki Iida, Knowledge of shallow landslideand deep-seated landslide for technicians ,Kashima Publishing Association, 2012, pp. 35.
[11] Koichi Higuchi, Quantitative Analysis of Texttype Data-Differentiation and Integration of Two
Approaches, Theory and Method ,No.19(1), 2004,
pp101-115.
[12] Lin, C.W. ROUGE., a package for automatic
evaluation of summaries. Proceedings of the
ACL-04 Workshop Text Summarization
Branches Out, Naoki Masuda and Norio Konno,
Complex Network Addendum (PDF version),
Modern Science, 2004, pp74-81.

In this paper, the overview of the evaluation items
for high-risk slopes and their contents was clarified,
which had been tacit knowledge, and the structure of
local residents' concerns about heavy rain, disaster,slopes and others. In addition, it obtained that thestructure of resident’s expectations for monitoring by
utilizing tilt sensors to take evacuation action.
There are many slope / sediment disaster risk
areas due to heavy rain, and it can be said that the riskof slope disaster is high topographically. In fact, it isinevitable that slope disasters caused by heavy rain
will occur almost every year. The roles of self-help,
mutual assistance, and public assistance are also very
important in order to reduce the damage caused byslope disasters. Among them, the basic one is selfhelp, and by acquiring knowledge about slope
disasters, understanding disasters correctly, thinking
about what to prepare for, it is important to protect
yourself by preparing for a disaster. In order toencourage such self-help efforts, we would like todevelop the monitoring system using the IOT tilt
sensors with the participation of local residents andprovide them with assistance so that they can takeappropriate evacuation actions.
ACKNOWLEDGMENTS
We would like to thank the residents of the
Fukuchiyama Araki area, Professor Yamori of Kyoto
University, and the Fukuchiyama City Crisis
Management Office for their great cooperation in thisstudy. We would like to express our deepest gratitude
here.
REFERENCES[1] Yamori.K, Disaster risk sense in Japan andgaming approach to risk communication.
International Journal of Mass Emergencies andDisasters, Vol.25 ,2007, pp. 101-131.

517

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

CONCRETE BEHAVIOR USING RECYCLED WASTEWATER
Khaled Mohamed Nabil I. Elsayed 1, Gerald Benjamin Felipe Guico 2 and Rabee Rustum3
1,2
Department of Civil Engineering, Heriot-Watt University, United Arab Emirates
ABSTRACT
Concrete is one of the world's most essential and most widely used civil engineering applications, making it
the reason to continue the need for development by implementing a more sustainable and less environmentally
damaging approach. Water is one of the fundamental pillars in its manufacture and its acquisition of the required
mechanical and physical properties through the applicable mixing ratios. So far, tap water is mainly used in thisprocess, whether in the preparation of components, mixing or even after hardening during the curing treatment
process. However, this may become a burden in the future due to the continuing increasing scarcity of fresh water,which is only less than 3% of the total water on earth, where regions are suffering due to population growth,
climatic changes and poor management of water systems. This paper deals with the use of treated wastewater(recycled water) as an alternative in the concrete industry during the mixing and curing treatment phase by testing
the extent of this effect on the mechanical properties of concrete, such as compressive, flexural, and tensile strengthfrom a general perspective. The results show a significant improvement in the compressive strength observed
according to the cubes crushing test, reaching 33% after seven days, 70% after 14 days, 56% after 21 days, andthe endurance tensile strength test improved by 4% after 28 days.
Keywords: Tertiary Treated Wastewater, Concrete, Tap Water, Mechanical properties.
INTRODUCTION

needed. The aims were to minimise the freshwater
use in the concrete industry, eliminate the continued
expanding need for it, and be reserved for drinking
purposes only [13]. The freshwater was targeted tobe replaced by another alternative that can utilise its
functionality in concrete manufacturing. Many typesof disposed water were suggested to be investigatedby the researchers, for example, treated anduntreated wastewater (WW), fertiliser factory WW,
textile factory WW, sugar factory WW, service
station WW (preliminary, secondary, and tertiary
treated) WW, salty water, oily water, stone slurry
WW, sludge WW, car wash station WW, and manyother types [11].

The construction sector is blamed for being thelargest natural resources consumer [7]. Concrete is
the most widely used in this industry which is a
product of gathered materials mixed as cement, sand,gravel, and with the presence of fresh water.
Unfortunately, it is considered one of the largest
fresh water-consuming during its different process
stages. Practically, one m3 of concrete requires about
150 litres of fresh water, increasing to 500 litres if
counting
thewashing
materials,
curing,transportation losses and equipment preparation[11]. It is nearly one trillion m3 annually reserved for
concrete production [12]. It accounts for around 9%of the extraction of fresh water for industrial use,accounting for up to 1.7% of the total extraction of
freshwater [1].

From the above short list of different water types,
the treated wastewater types are the mostconvenient, sustainably achievable, and globally canbe afforded both technically and financially.
Moreover, many researchers had achieved
progression in studying the differences inmechanically and physically on the concrete whenusing fresh, tap or potable water compared with
wastewater, and it was found to be almost similar or
having near properties which promote the idea of
replacement in the near future [17].

Undoubtedly, the stress of global population
growth, urbanisation, industrialisation, climatechange, poor management of water systems, surface
and groundwater contamination, and global
warming are the most effective challenging
environmental freshwater scarcity [1, 12, 5]. The
concrete industry, in general, is not environmentally
acting friendly; it is responsible for the emission of
more than 1.4 billion tons of CO2 through the cement
process production only, which is equal to 7% of theCO2 from worldwide production. In addition to thehigh energy requirement and the excessive use of
freshwater in its production processes are not attuned
with the sustainability development [13].

In this study, an investigation was attempted tofocus on the use of the tertiary recycled wastewater
as a replacement for the tap water in the concrete
mixing and curing stages by studying its impact onmechanical properties as compressive, tensile, andflexural strength and one of the physical properties
as workability.

Sustainable solutions shall take place in theconcrete manufacturing field, as it is strongly
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MATERIAL AND METHODOLOGY

Table 2 Concrete mixing design ratios and quantity
Tap Water /Recycled
WW

Aggregates

Concrete Component

Material

CementCoarseFineConcrete consists of 3 main components: cementwith a sharing rate of 12%, the water of 8%, andaggregate, whether coarse or fine, with a sharing rateof 80% from the mixer [3].

20 mm

10 mm

Ratio

1

1.5

2

1

0.5

Quantity(kg/m3)

436.4

654.6

872.7

436.4

218.2

CementConcrete Testing Preparations.
An ordinary Portland cement of CEMI type and42.5N class was used under the BS-EN-197-1:2011
speciation. [20]Physical properties
Workability (slump test): Metallic mold with acone shape filled with concrete in layers and rod
taped 25 times each, then mold pulled up, leaving theconcrete to deformity under the influence of its
gravity flow.

Water
Tap water: Normal tap water that is distributedby the DEWA authority (Dubai Electric and Water
Authority) [19].
Tertiary Treated Wastewater: Obtained from
Jebel Ali sewage treatment plant located south ofDubai emirate [18].

Mechanical properties
Testing machines:

Table 1 water quality test comparison between tap
water and recycled wastewater

1. Compressive strength test (concrete cubes
crushing test).
2. Tensile strength test.
3. Flexural strength test (beam test).

Water type
Unit

Tap
Water

Recycled
WW

Total suspended solids

TSS

mg/l

4

50

Total dissolved solids

TDS

mg/l

PH

PH

---

Turbidity

-

NTU

<5.0

75

BOD

mg/l

0

50

---

0

100

null

1000

null

1000

Biochemical Oxygen
demandChemical Oxygen
demandFecal Coliform
bacteria
Total Coliform

COD-

cells/
100ml
MPN/
100ml

100 to450
7.9 to8.5

Concrete Specimens' Preparation
The testing replaced fresh or tap water withtreated or recycled wastewater. Both types of water
were used interchangeably in the two stages, and so
the first testing option was to use only tap water inthe mixing and the curing stages. It was denoted by(control specimen or MC), while the second testing
option was to keep the tap water in the mixing,
whereas the curing with recycled wastewater was
denoted by (MC1) specimen. The third testing
option comes by replacing the tap water withrecycled wastewater; as for the curing stage, tapwater is used (MC2), and then the fourth and last
testing option is using recycled wastewater in bothstages of mixing and curing (MC3) Figure 1.

1500
6 to 9Aggregates
Fine: Black sand graded of medium size from
(0.4mm to 2mm)
Coarse: two sizes, 10 mm and 20 mm

Concrete

Symbol

stage
Water
Type

CuringParameter

Tap

Concrete Mixing Design
The Concrete mix design used in experiments is
proportional between its components (1 cement: 1.5
fine aggregates: 3 coarse aggregates) mixed by awater-cement ratio of 0.5 to produce a concrete
characteristic compressive strength of 40 N/mm2,
which is known as concrete grade M40.

Fig. 1

519

Recycled
WW

MixingRecycled
Tap
WW
MC
Control
MC2
Specimen
MC1

MC3

Shows the arrangement of using the two
types of water interchangeably in the
mixing and curing stages.

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

The recycled water used was the output of thetertiary wastewater treatment. The concrete mixtures
were arranged to produce a total of 16 concrete
specimens classified into 12 concrete cubes of
150 mm length, two concrete cylinders of 150 mm
diameter and 300 mm height, in addition to 2
concrete beams with dimensions of 100 mm forwidth and height and 500 mm for length.

Tests were maintained over time intervals up to
21days; each seven days, four different cubes wererequired to obtain their compressive strength value.
At seven days interval
The results were compared with the control
specimen and were found to be higher when tap
water mixing and recycled wastewater in curing(MC1) were used, as it got 24.62 MPa. In
comparison, the control specimen got 18.5 MPa,
which is 33.1% higher than the control specimen.
The other two specimens got lower values as the
specimen using recycled wastewater in mixing and
tap water in curing (MC2) got 16.66 MPa with low
as 8.9 % from the control specimen value. Also, thespecimen using recycled wastewater in both stagesof mixing and curing (MC3) got 10.99 MPa, as low
as 40.4% from the control specimen value.

The 12 concrete cubes were conducted to test theconcrete compressive strength behaviour. Tests were
performed at the ages of 7, 14, and 21 days, with fourcubes every time after drying from the curing stage,
four cubes that comply with four different water
combination options covering the two mixing stages
and curing. At the same time, the two concrete
cylinders were conducted for the concrete tensile
strength that was tested at the age of 28 days using
two different water options, which were either fully
mixed and cured by tap water or by recycled
wastewater. And finally, the two concrete beams
were conducted to test the concrete flexural tensile
strength behaviour and were tested at 28 days withthe same two different water options in the previous
test.

That was contrary to [2, 3, 7, 8] findings, inwhich the concrete with treated wastewater
exhibited a greater compressive strength than theconcrete with tap water. The reason that may arisefor lowering the strength of the concrete early age
when using recycled treated wastewater in concrete
mixing is that it may contain an organic matter thatlower the PH, which deteriorates the concrete [11].

RESULTS AND DISCUSSION
Workability (Slump Test)

At 14 days interval
It was observed that the concrete control
specimen produced by mixing the components withtap water had a higher value than that of recycled
tertiary treated wastewater. The control specimen
slump was 65 mm in height while the recycled
wastewater was 46 mm, reflecting a 29% decrease
from that in the control specimen values.

It was observed that all the results weresignificantly higher than the control specimen,
where it was found that the specimen made by using
recycled wastewater in mixing and tap water incuring (MC2) had 37.3 MPa. In comparison, thecontrol specimen got 22 MPa only, which reflects a
69.5% higher than the control specimen got. Also,
the other two specimens got higher values as the
specimen made using recycled wastewater in bothstages of mixing and curing (MC3) got 35.31 MPa
with a higher of 60.5 % from the control specimen
value. In contrast, the specimen made using tap
water in mixing and recycled wastewater in curing(MC1) got 27.46 MPa, a 24.8% increase from thecontrol specimen value.

In fact, the recycled tertiary treated wastewatercontains dissolved solid particles that have a highabsorption property that decrease the water content
quality. That leads to a lowering of the slump value
as agreed with [7,9,10,14], in other words, theexistence of high content of fine particles in therecycled wastewater reduces the effective W/C ratio
in the mix, and therefore the workability goes down.
However, it is still in the acceptance range.

That was also agreed by [2 and 3] findings thatthe increase of compressive strength in the concrete
mixed with treated wastewater is most significant
during the early concrete ages of 7, 14 and 28 days.

According to the findings of [9], the slump was
decreased by 25% when using tertiary treatedwastewater, giving a difference of only 4% awayfrom our values, while a decrease of 50% in the caseof using secondary treated wastewater.

At 21 days interval

Compressive Strength Test (Concrete Cubes
Crushing Test)

It was also observed that all the results weresignificantly higher compared with the control
specimen, where it was found that the specimen
made by using recycled wastewater in mixing and
tap water in curing (MC2) had got 40.5 MPa. In
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
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it was obvious that the mixing using the non-potablewater (MC2 and MC3) values would be higher thanthe potable water (MC and MC1) values, if not atleast equal to them, figure 3.
Compressive strength (MPa)comparison, the control specimen got 25.9 MPa
only, which reflects a 56.4% higher than the control
specimen. Also, the other two specimens got higher
values as the specimen made using recycled
wastewater in both stages of mixing and curing(MC3) got 38.13 MPa reflecting 47.2% higher fromthe control specimen value. In contrast, the specimen
made using tap water in mixing, and recycled
wastewater in curing (MC1) got 29.24 MPa with
12.9% increase than the control specimen value.
The [3] found that when the concrete is both
mixed and cured using treated wastewater, an
increase of 17% in compressive strength is obtained,
according to this experiment, an increase of 47.2%
was found when the concrete was both mixed andcured with the treated wastewater (MC3).
Results commentary
When comparing the result curves between the
different mixing and curing combinations, the curves
expressing the combinations using the tap water in
mixing as MC and MC1 have very similar patterns
as both grew linearly and almost turned into parallellines. Also, throughout the time intervals, theincrease in concrete strength was almost graduallyand small. In comparison, the other two curvespresent the use of recycled wastewater mixing
combination as MC2 and MC3 were having
nonlinear behaviour. They began lower than thosemixed with tap water in strength values as in theseven days test, then significantly increased at the 14
days test and became higher than the tap water
mixing curves, then continuing to slightly increase at
a rate nearly matching with that in the tap water
mixing curves values. Also, MC2 gains morestrength as values rather than MC3, but practically,
the MC3 gains more strength, since the start wassignificantly low compared to MC2, as it gained
23.84 MPa more during the period of testing fromthe 7 to 21 days. MC3 gains a higher value of 27.14
MPa for the same period, which confirms theadvantage of using recycled wastewater in curing,
figure 2.

45
40
35
30
25
20
15
10
5
0

7 DAYS

14 DAYS

21 DAYS

MC

18.5

22

25.9

MC1

24.62

27.46

29.24

MC2

16.66

37.3

40.5

MC3

10.99

35.31

38.13

Time (days)
Fig. 2Chart shows the compressive strength
values for all concrete mixing combinations(MC, MC1, MC2, and MC3) for 7, 14, and21 days periods.

An explanation that might approach the reason for
gaining more compressive strength in specimens
mixed with recycled wastewater has been illustrated
by [4], which mentions that the pore-filling provided
by the deposition of dissolved and suspended solids
existing in the recycled water was responsible for thestrength increasing and may have a relative meaning
when curing using the recycled wastewater as theefficiency of cement hydration increased under thepore filling effect. In other words, it is the poreclogging that exists by settling of dissolved solid
particles reducing the porosity, and then it enhancesthestrength [16]. Even though the concrete mix
water was tap water, it may be the reason why thecompressive strength differences were foundbetween the results for specimen mixing by tap
water and that cured by tap water MC and byrecycled water MC1. The differences between
control specimen MC and MC1 reached 33% extra
in strength at day 7, then reduced to 24.8% at day 14,
and finally reached 12.9% extra at day 21,
Eventually, the 2 curves of MC and MC1 are likely
to meet at day 28, figure 2.

Building codes like ACI [21] permit the use of
non-potable water in concrete mixing to provide atleast 90% of the strength gained by potable water
specimen values on both seven and 28-days time
testing [3]. By applying the ACI code to the result, it
was found that the two used mixing combinations
that use non-potable water (MC2) and (MC3) were
90.05% and 59.40%, respectively, for the 7-day test,
which means one of them passes (MC2), and theother is failed (MC3). However, the experimental
values went higher than those made using potablewater (MC and MC1) at 14 and 21 days. Although
there is no testing was conducted during the 28 days,

On the contrary, the findings of [6] concerning a
study of sharing different proportions between the
tap water to treated domestic wastewater of ratios(0,50,75 and 100%) using cylinder concrete521

Comperssive
strength (MPa)

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

50
40
30
20
10
0

25.9

24.62 27.46 29.24

37.3
16.66

40.5

35.31 38.13
10.99

MC

MC1

MC2

MC3

18.5

24.62

16.66

10.99

14 DAYS

22

27.46

37.3

35.31

21 DAYS

25.9

29.24

40.5

38.13

7 DAYS

Fig. 318.5

22Shows the compressive strength values for all concrete mixing combinations (MC, MC1, MC2, andMC3) for 7, 14, and 21 days period

specimens tested at the age of 28 days. Results
revealed that the specimens with a sharing ratio of
50% and 75% of treated wastewater have nosignificant differences from that of tap water. In
comparison, the 100% of treated wastewater sharegains a 17.7% increment in compressive strength.

water in curing (MC2). A decrease in the results wasobserved compared with the control specimen, as it
got strength of 3.8 MPa to 4.2 MPa for the control
specimen, representing an 8 % relative decrement.
According to [9], using secondary and tertiary
treated wastewater in concrete mix reduced theflexural strength of the concrete at its early age, thenslowly increased its strength at the later stage, as it
was found to be 7.71% at 28 days and further
decreased at its later ages of 90 days by 25.73%. In
comparison with this experiment, the figures were so
close in values in which MC2 reveals a decrease in
the strength of 8% at 21 days.

Tensile Strength Test (Splitting Cylinder Test)
Tensile strength test was done at the 28 days ofconcrete age for two cylinders, one of them was thecontrol specimen, and the other was selected basedon the superior results obtained from thecompressive strength test at day 21 and using thesame corresponding concrete combination for waterin mixing and curing, as it was the use of the recycled
wastewater in mixing and tap water in curing (MC2).
As a result, a slight increase in the results wereobserved compared with the control specimen, as it
got a tensile strength of 2.93 MPa to 2.83 MPa forthe control specimen, representing a 4.2% relative
increment.

Despite the compressive and tensile strength testing
results for the MC2 specimen, which were relatively
high in comparison with the control specimen MC
results, the flexural strength result was less, which
proves that there is no relationship between thecompressive strength and flexural strength,
nevertheless it was noticed that the use of therecycled treated wastewater in concrete mixing
effects the concrete bonding strength between the
cement pastry and aggregate [11], similarly, whatrevealed by [9] that the main contributor for flexuralstrength reduction was the tertiary treatedwastewater that has a high alkalinity content formeda layer in the interfacial transition zone between the
cement paste and aggregates.

Similarly, [5] found that the tensile strengths ofthe concrete specimens with 50% wastewater
sharing gained a higher value than the control mix.
Some researchers pointed out that the reduction or
increase in the tensile strength was related to thelevel of organic matter content in the water,
particularly the existence of the BOD and COD
values [11].

CONCLUSION
Flexural Strength Test (Beam Test)
It was noticed that to get the excellent benefit ofusing the recycled wastewater in mixing and curingconcrete is to choose the water-cement ratio thatenhances the workability, which is reduced by thelarge content of suspended and dissolved solid
particles that absorbs the water in the mixer.
Nevertheless, these dissolved solids play asignificant enrollment in filing the pores initiatedand reducing the porosity in the produced concreteduring the mixing stage, which increases its strength

A flexural strength test was done at day 28 ofconcrete age for two beams. One of them was thecontrol specimen, and the other was selected basedon the superior results obtained from thecompressive strength test at the 21 days of age andusing the same corresponding concrete combination
for water in mixing and curing as it was selected
previously in the tensile strength test, it was madeusing the recycled wastewater in mixing and tap
522

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

in the early developing ages. Besides, it has the same
effect when using the recycled wastewater in the
curing stage, where the more suspended anddissolved solid particles and larger curing time helps
the concrete to block the remaining pores due topercolation into and filing it, which eventually
increases the concrete strength.

[9] Meena K, Luhar S. Author' s AcceptedManuscript Effect of wastewater on propertiesof concrete. J Build Eng [Internet]. 2018;
Availablefrom:https://doi.org/10.1016/j.jobe.2018.10.003[10] Haezah A, Muhammad B, Ismail M, Abdulmajid Z. Characteristics of treated ef fl uentsand their potential applications for producing
concrete. 2012;110:27–32.
[11] Ali B, Kurda R, Brito J De. applied sciences A
Review on the Performance of ConcreteContaining Non-Potable Water. 2021;[12] Sheikh M, Asadollahfardi G, Fazlolah S, Jafari
S. The difference in chloride ion diffusion
coefficient of concrete made with drinking
water and wastewater. Vol. 231. Elsevier Ltd;
2020.
[13] June J, Politecnica U, Silva M, Naik TR.
Sustainable Use of Resources – Recycling of
Sewage Treatment Plant Water in Concrete.
2010;[14] Al-joulani N. Effect of Waste Water Type on
Concrete Properties. International Journal ofApplied Engineering Research. 2015;10(09734562):39865-70.
[15] Miller SA, Horvath A, Monteiro PJM. resources
worldwide. 2018;1(January):69–76.
[16] Sorkor K, Miretu TM. Curing of concrete with
wastewater and curing compounds : Effect onstrength and water absorption. 2014;(October).
[17] Arooj MF, Haseeb F, Butt AI, Irfan-ul- M. A
sustainable approach to reuse of treateddomestic
wastewaterinconstruction
incorporating admixtures. 2020;[18] Trakhees.ae.
1[cited 2022 Jun 13]. Available
from:.
https://www.trakhees.ae/en/ehs/env/Documents/Guidelines/Guideline%20ID-ENG02,%20Water%20Environment,%20Rev.%2000,%20Jan18.pdf, p.4-5[19] Gov.ae. [cited 2022 Jun 13]. Available from:https://www.dewa.gov.ae/~/media/Files/Custo
mer/Sustainability%20Reports/DEWA%20Sus
tainability%20Report%202020.ashx , p. 65[20] EN 197-1 TS. Cement- Part 1: Composition,
specifications and conformity criteria forcommoncements.
TurkishStand.
2002;(November 2011).
[21] ACI Committee 318, American Concrete
Institute. Building code requirements forstructural concrete (ACI 318-19) : Farmington
Hills, Mi: American Concrete Institute; 2019.

The main achievement pursued by theexperiment are as follows:
1- The possibility of replacing the tap waterwith recycled tertiary treated wastewater inconcrete manufacturing.
2- Concrete performed using recycled tertiary
wastewater has such a close performancemechanically and physically characteristic
properties relative to that performed using
tap water.
3- Using the recycled tertiary wastewater inthe concrete curing stage has an advanced
gaining strength similar to tap water use.
4- Using recycled tertiary wastewater inconcrete is a great achievement towardsustainability in generally preserving
freshwater and concrete manufacturing.
REFERENCES[1] Farid H, Mansoor MS, Adnan S, Shah R, Khan
NM, Muhammad R, et al. Impact Analysis of
Water Quality on the Development ofConstruction Materials. 2019;1–13.
[2] Al-ghusain I, Terro MJ. Use of treatedwastewater for concrete mixing in Kuwait.
2003;30(1).
[3] Engineering E. Use of biologically treateddomestic wastewater in concrete. 2012;39:97–
111.
[4] Swami D, Sarkar K, Bhattacharjee B. Use oftreated domestic effluent as mixing water forconcrete : Effect on strength and water
penetration at 28 days. 2015;(November).
[5] Concrete S. Procedia Engineering Effect ofusing wastewater on the Properties of HighStrength Concrete. 2011;14:370–6.
[6] Paper P. Practical Paper Water reuse in the
productionof
non-reinforced
concreteelements : An alternative for decentralised
wastewater management Natalia Cangussu
Duarte , Ana Elitha dos Santos Amaral , Bianca
Graziella Lento Araujo Gomes , Gustavo
Henrique Siqu. 2019;596–600.
[7] Testing B, Implementation F. Domestic
Wastewater Reuse in Concrete Using. 2016;i.
[8] Askariyeh AH. International Journal of Waste
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523

8th Int. Conf. on Structure, Engineering & Environment (SEE),
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LOW-COST TECHNOLOGY FOR HERITAGE BUILDINGSDOCUMENTATION
Yohannes Firzal 1, Reni Suryanita 2, M. Arief Al Husaini 3, Nangkula Utaberta 4
1, 3 Architecture of Universitas Riau, Pekanbaru, Indonesia
2 Civil Engineering of Universitas Riau, Pekanbaru, Indonesia
4 Universiti Tun Hussein Onn, Johor, Malaysia

ABSTRACT
Architectural heritage documentation becomes a serious concern in the learning method which mostly relies
on two-dimensional drawing, sketch, observation and recording, and photos of objects. Not only consume time incollecting data and processing, but this conventional method also has other issues related to data accuracy andfinal results. To overcome these matters, digital documentation methods such as Close-Range Photogrammetry
with Ultra-Light UAV are assumed to break-through methods for the problems of time efficiencies and accuracyof results. This digital documentation method is more reliable with the flexibility of multi-platform outputs thatallow the final result of the process to adapt to variations in demand.

Keywords: Close-Range Photogrammetry, Ultra-Light UAV, Accuracy, Digital Documentation

INTRODUCTION

requires a long and tiring process. Moreover, it willtake a much longer time for the iteration process has
to occur. From another perspective, students are also
required not only to understand and be able to quickly
and accurately document the process but also to beable to apply the latest techniques and equipment. In
this context, architectural documentation is thestarting point in heritage building studies, which isthen further defined and specified by technology.
Thus, this paper investigates how digitalizing
methods through low-cost technology can overcome
the issues related to the time-consuming processingof heritage building documentation, mainly whenapplied to architectural studies.

Learning architectural documentation demands alevel of precaution and proper technical methods.
Education in universities is mostly still teachingarchitectural documentation methods starting with
two-dimensional (2D) manual drawing techniquessuch as sketches, direct observations, direct notes,
and taking photos of objects as complements (Fig. 1).
However,
thisconventionalarchitectural
documentation method has several limitations related
to the processing time of data collection andprocessing with a good level of accuracy.
By relying on conventional methods, the processof documenting field data is a time consume andrequires more operators. This takes longer as moretypes of documentation methods are applied to
produce a good level of data accuracy. In terms of thelevel of data accuracy, conventional field data
documentation methods are strongly influenced byvarious other technical matters such as the location of
the height of the object being observed, the size of theobject that is too large, and or the position of theobject that is difficult to reach. Moreover, theconventional method of documentation has its own
complexity when processing field data. Field dataobtained manually in 2D form is then converted into
digital data with the help of graphic design software.
In this digitization conversion process, vector tracing
and interpretation techniques are modified into theplane and three-dimensional (3D) shapes.
The conventional methods become a significant
problem in learning architectural heritage
documentation for college students because it

Fig. 1

ArchitecturalDocumentation
Conventional Technique with Students

by

DIGITIZING IN ARCHITECTURAL
DOCUMENTATION STUDIES
Architectural heritage documentation has
developed along with the development of digitaltechnology which is proven to be able to bridge theissue of data retrieval time with a good level of data524

SEE-Mie, Japan, Nov.10-12, 2022

accuracy and can speed up data [1]. One of the latest
technological leaps in the documentation is known as
the Close-Range Photogrammetry (CRP) method.
Broadly speaking, the CRP method is part ofphotogrammetry which is defined as a digital image
processing method in orthoimages and mosaics whichwere initially used more in the field of archaeology[2]. Over the time, photogrammetry began to berecognized as an alternative solution for low-cost but
effective documentation in image processing [3]compared to other modern methods [4].
Photogrammetry has also been applied in various
disciplines [5] such as geoscience [6], structuralinvestigation [7], cultural heritage documentation [8][9], building inspections [10], architectural heritage[11], and architectural representations [12].
The CRP method in architectural heritage
documentation is mostly a modified form of aerial
photogrammetry to a simpler and more flexible form
to use [13]. In this context, the CRP method can beeffective and efficient in the digital image processingof field data. In its application, the CRP method
requires general equipment such as a metric camera,
personal computers, photogrammetry software, andscale bars [14]. Furthermore, the CRP method is also
recognized as a non-intrusive documentation
technique to produce digital 3D models, so it is moresuitable for students to use in learning architectural
heritage documentation.
Close-Range Photogrammetry converts serial
digital images into point clouds with photogrammetry
software. As a digital form since the beginning of theprocess, photogrammetric virtual models have been
generated accurately and shortened the analysis
process time [15]. Therefore, the CRP method can be
more effective in processing and analyzing data at alow cost [16]. The CRP in this context is not to change
the role of an architectural researcher, but rather as ameans to help overcome architectural obstacles [17].

more on the skills of the operator operating the device
in the field [13]. The second step is compiling theimage by applying photogrammetry software to
produce cloud data and dense textures. The softwarethen consecutive interprets the semantic informationof the image [19]. This computational phase is
executed sequentially in the software workflow to get
the 3D image at the end of the process.
The research unit on architectural heritage
documentation is a study on two objects of traditional
wooden construction buildings; mosques andtraditional houses (Fig. 2). Both building objects still
have intact and complete construction elements, sothey are appropriate as objects of documentation forstudents.

Fig. 2

Wooden Construction Buildings as theresearch unit objects

FINDING AND DISCUSSION
Field data acquisition has been collected by thecamera of an Ultra-Light UAV. In its working
principle, the image capture procedure with thecamera is giving more flexible in its movement (Fig.
3). The UAV can easily arrange to move verticallyand horizontally. However, operating a UAV is also
demanding on the pilot's ability to pay attention to thecaptured image of the environment around therecorded object so as not to result in excessive loadingof image quality.
Image acquisition of objects by the camera is still
paying attention to the suitability of thecharacteristics of the software that has been used toprocess the images. In this context, the collected
images must be ensured that the overlap between theimages is at least 60%. Thus, data processing
software will quickly determine the order andlocation of each existing image. By using
photogrammetry software, the image preparation
workflow is following the process template.

INSTRUMENT AND DATA COLLECTIONTECHNIQUE
Instruments in collecting field data have used an
Ultra-Light Unmanned Aerial Vehicle (UAV). The
UAV used in this research is the DJI Phantom Mavic
Mini 2-12MP 3-axis motorized gimbal Ultra Clear
4K/30 fps drone which is equipped with a 35 mm
camera lens. Meanwhile, to process field data to
produce cloud images using the Agisoft Metashape
Professional 64-bit photogrammetry software.
Collecting field data has been conducted throughtwo technical steps. The first step is to capture still
images from various angles using the Ultra-Light
UAV cameras. This step is called the fieldwork phasewhich aims to collect quality and geometric
information from the image such as position, size,
contrast, filtering, and shape [18]. This first step reliesFig. 3 Image Acquisition Process by Ultra-Light
UAV with Students

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SEE-Mie, Japan, Nov.10-12, 2022

Image preparation with software is arranged
through a series of fixed work sequences according to
the workflow of the software (Fig. 4). At each stageof the workflow, the software will display a dialogue
box confirming how the parameters will be used.
Thus, researchers can still control every step of theprocess and take necessary action if an error occurs in
the process of compiling this image.

CRP method can also answer the need for fast andaccurate documentation methods in digital format.
When compared with conventional documentation
methods, the CRP method is found to be more reliablewith the flexibility of multi-platform output.
However, the CRP method requires mastery of otherbasic techniques that support such as the ability tooperate an UAV and to run the software.

ACKNOWLEDGMENT
The research team would like to thank the LPPM
Universitas Riau and ADB AKSI Project forproviding financial support through the International
Collaboration Research Scheme in 2021.

Fig. 4 The Arrangement t of the Images in
Photogrammetry Software

REFERENCES

The series of processes in photogrammetry
software can produce various outputs and depths. The
workflow runs sequentially starting from aligned
images, dense cloud, mesh, texture, tiled models,
DEM, and ortho-mosaic. The view of the process canalso set the height and material properties of theobject being analyzed (Fig. 5). The use ofphotogrammetry software also provides more
flexibility. This is because the analysis process candetermine the multi-platform output to be targeted.
Not only produce corrected images and exterior
shapes in 3D format, but the photogrammetry
software is also externally flexible to link withother/multi-platform software.
However, the use of photogrammetry software
also demands several things besides the ability. Timeconsuming is still a matter that is of concern toresearchers in the analysis process. The level andquality of the output produced will be directly
proportional to the time required for the rendering
process. The higher and more detailed, the more time
it will take.

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Fig. 5 Various Outputs and Depths of the Object
Properties

CONCLUSION
A study using the adapted Close-Range
Photogrammetry method has proven to be able toovercome gaps in problems related to architectural
heritage documentation, especially for documenting
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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

APPLICATION OF DESIGN FOR MANUFACTURING ANDASSEMBLY ON TEMPORARY SHELTERS IN THE PHILIPPINES
Cheryl Lyne C. Roxas1, Orlean G. Dela Cruz2, Rhem Leoric C. Dela Cruz3, John Paul Q. De Pedro3,
Jonathan R. Dungca1, Bernardo A. Lejano 1 and Jason Maximino C. Ongpeng1
1
Faculty, De La Salle University, Philippines; 2 Faculty, Polytechnic University of the Philippines,
Philippines; 3Research Assistant, De La Salle University, Philippines

ABSTRACTThe Philippines has experienced several tropical cyclones over the years. The most destructive disasterrecorded in Philippine history was Typhoon Yolanda (Haiyan) in 2013, affecting 14 million people and deaths ofat least 6,000. The number of internally displaced persons (IDP) has increased because of disasters from natural
hazards. One of the challenges that people face during these times is the lack of durable and easy to build housing.
As part of the disaster rehabilitation and recovery plan, a safe and durable house to protect people from theaggressive environment and ensure privacy to cope with emotional and mental health problems is essential in adisaster-prone country like the Philippines. Towards this end, the Design for Manufacturing and Assembly(DfMA) methodology was explored using sustainable materials like steel – cold-formed steel as main structuralcomponents and screw piles for the foundation, on a previously designed shelter for the IDPs of Typhoon Yolanda.
The application of the proposed scheme has shown slight effect on project completion time but significant benefit
in terms of cost efficiency.
Keywords: DfMA, Temporary Shelter, Disaster, Philippines
INTRODUCTION

However, the developed designs also came withpotential issues, which, in general, involve
construction methodologies, site execution, andcomplexities due to numerous specifications [5] thatwould consume construction time.
To alleviate the potential issues stipulated inprevious shelter designs, this paper explores theapplication of the Design for Manufacturing andAssembly (DfMA) to the temporary sheltersdeveloped in the Philippines. Previous studies havealso applied DfMA in construction such as theconstruction of a light wall in 4-story houses [8],modules of cable-stayed towers [9], and student
dormitory modules [10]. DfMA improves design byconsidering the downstream processes ofmanufacturing and assembly [11] that can reduce
assembly and manufacturing costs and improvement
in quality of work and production time throughsimplification of the system [12]. To further explore
the advantages of applying DfMA, this paper utilizes
cold-formed steel (CFS) for the shelter framing
system and screw piles serving as its foundation. The
selection of CFS as a structural material for the frame
is supported by its benefits: reduced cost of materials
and implementation, reduced structural elements, lessmaintenance, and suitability for prefabrication [13].
As for the screw piles, related studies established thatthey are easy to install with the use of minimal
equipment and manpower, and reusable to other sites[14]. The usage of these materials is similar withanother shelter scheme used in Vietnam from theAnnually, shelters in the Philippines are damagedby climate-related disasters, from tropical storms,
flooding, earthquakes, and volcanic eruptions. On the
average, 300 shelters are affected by thesecatastrophes each year [1]. In 2013, Super Typhoon
Yolanda (International Name: Haiyan) took the livesof about 6300 people and destroyed almost 1.14
million houses upon its landfall in Eastern Visayas[2]. In a more recent event, Typhoon Odette(International Name: Rai) has wreaked havoc on
December 16, 2021, in Southern Leyte and Caraga
Region, affecting 9,800 families (approximately
40,300 IDPs), which as of March 2, 2022, are still
displaced and currently staying in the evacuation
centers or residence of their relatives [3].
To address the housing concerns of displaced
families, temporary shelters must be constructed; and,as such, guidelines for constructing these shelters
have been developed. Considering the technicalfactors, it is suggested that the temporary shelters
should be easy to erect and dismantled [4], has nocomplexities in their design since design complexities
may cause delays in the timely construction of the
shelter [5], could withstand and protect the
inhabitants from subsequent calamities [6], and must
be built from economical materials that areenvironmentally friendly, easy to manufacture andconstruct, and recyclable [7]. Several shelters havealready been designed to match these guidelines.
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IFRC Eight Designs [15], but without DfMA
application.
METHODOLOGY
For this research, a case study was developed incollaboration with a local steel contractor which
specializes in the manufacturing and assembly of CFS
sections and the installation of screw piles asfoundation. The case study covers the application of
DfMA using CFS and screw piles on a selected
shelter previously designed and constructed in thePhilippines.
Fig. 2

Selection of Shelter for DfMA

IFRC Philippine shelter 2013 elevation [5]Initial Design of the Structural System

In this research, DfMA methodology using CFS
and screw piles was applied to address the concerns
in a previous temporary shelter design in thePhilippines. The researchers chose a Philippine 2011
shelter from the International Federation of Red Cross
and Red Crescent Societies’ Ten Designs for Post
Disaster Shelter [5]. In overview, the shelter isconstructed using reinforced concrete columns andfoundations, masonry and timber walls, and timberroof framing with a dimension of 4.0mx5.0m (Fig. 1).
Based on the front elevation (Fig. 2), it has a gable
roof with a braced column height of 2.40m. Thisshelter took 12 days to be built, and it has an
anticipated lifespan of 5 years. Its performance
analysis against hazards indicates the possibility of
failure in resisting wind loads even at the reduced
level, and non-compliance with the structural code
requirements for seismic loads indicating that it could
only withstand seismic events at a reduced load level[5]. The other IFRC documented shelter for thePhilippines was a timber shelter and it was alreadyfound to be structurally adequate; and, therefore, was
not selected for this study.

Design of CFS Frame
The selected shelter was prepared with an initial CFS
framing and screw pile as foundation complying withthe design load requirements set by the National
Structural Code of the Philippines (NSCP)
requirements. The initial CFS frame was designed
using the software STAAD in accordance with
American Iron and Steel Institute (AISI) standards
and imported to Vertex BD, a Building Information
Modelling (BIM) software that facilitated the DfMA
phase. For the design, the selected shelter was
assumed to be situated in a hypothetical location in
San Gerardo Subdivision, Tacloban City, Leyte. The
wind and seismic parameters shown in Tables 1 and
2, respectively, were used in the design of the framein STAAD.
Table 1 Wind Load Parameters
Parameter
Wind Speed
Exposure Category

Input Values
290 kPh
Exposure C

Table 2 Seismic Load Parameters
Parameter
Soil Profile Type
Near Source Factors
Seismic Zone Factor
Response Modification
Factor, R

Input ValuesSD
Na = 1.0, Nv = 1.0
0.40
4.50 (Intermediate
Moment Frame)

Design of Screw Piles
For the shallow screw piles in cohesionless soils,
the cylindrical shear method was used for the designusing the equations suggested by Nasr (2004) [16] forpiles under compression, and Mitsch and Clemence(1985) [17] for tension/uplift.
Fig. 1IFRC Philippine shelter 2013 plan [5]529SEE-Mie, Japan, Nov.10-12, 2022

Shown in Table 3 are the soil parameters used in
the design of the screw piles. The soil parameters aresite specific and were obtained from an available soil
investigation report that generally assumes theparameters of a very dense sand of the selected site.
Table 3

Soil parameters

Parameter
Internal Friction Angle, f
Effective Unit Weight, g’
Breakout Factor, Fq

Values35°
10.19 kN/m3
10

Fig. 3

Trusses STAAD modelFig. 4

CFS Frame STAAD model

Structural Design Results

Fig. 5Screw pile design specification

STAAD models shown in Fig. 3 for the trusses
and Fig. 4 for the frame show that the CFS sizes were
designed according to the code specifications of AISI
for CFS sections which assure the adequacy of its
resistance against the wind and seismic loads. Since
the structure is relatively lightweight, the governing
load is the wind; thus, the sections, in majority, were
designed against the wind. Furthermore, due to wind,
the governing support reaction used in the design ofthe screw pile is an uplift force of 14 kN. The
designed specification of the screw piles as shown in
Fig. 5 mitigates the issue of the IFRC foundation of a
possible uplift occurring during typhoons.

Application of DfMA

Design Assessment Using DfMA Criteria
The scope of the research is limited to theapplication of DfMA as a design process and its
consequent effect on the material cost andapproximated theoretical time of installation of the
prototype shelter with CFS and screw pile. In thedesign phase, DfMA criteria were utilized to optimize
the production of the prototype. The following
criteria are as follows: (a) minimization of the numberof parts, (b) ease of handling, (c) ease of insertion ofparts, (d) standardized parts, (e) design for current
process capabilities, and (f) maintain margin foralternative design and assembly processes [11].
Usage of Building Information Modelling (BIM)
Upon application of the DfMA criteria, design
output was imported to Vertex BD for creation of theshop drawings of the CFS framing and connections
which were the basis of the material cost estimate andtheoretical time of completion for assembly. After
which, the obtained values were compared to thevalues of the original IFRC temporary shelter
scheme. The original scheme was designated as IFRC
and the new scheme applying DfMA with CFS andscrew piles was designated as CFS.
DATA AND ANALYSIS

Following the results of the structural design, thecriteria for DfMA were applied through theimportation of the STAAD file to Vertex BD.
Minimization of the number of parts
The number of parts was already trimmed down
to the required number of members based on
structural requirements. Hence, the number of parts isalready optimized. No further reduction of members
is necessary as all parts are deemed essential.

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Design for ease in handling
The Vertex BD output was readily imported to
the roll forming machine that would automaticallymanufacture the CFS sections according to the cutting
list. Hence, this process eases the flat-pack packagingof the CFS. The sections were relatively light suchthat handling each section would require two persons
only. Assembly is guided by the designations marked
by the Vertex BD for each member of a panel. Shop
drawings from Vertex BD include the specification ofeach member designation shown in Table 4 and its
respective designation on the parts of the truss shownin Fig. 6.

Fig. 7

Standardized parts

Table 4 Vertex BD truss parts specifications
Mark

Qty

5

1

3

1

6

1

2

1

7

1

4

1

8

1

1

1

Size
DH140-501.40
DH140-501.40
DH140-501.40
DH140-501.40
DH140-501.40
U140-501.40
U140-501.40
U140-501.40

Single screw connections of CFS frame

Use

Length
(mm)

Jack

1193

Web

1117

Web

1117

CFS components will be fabricated only by asingle local manufacturer. Moreover, all of the partsof the frame were set to be constructed at the samelength, size, and configuration. All frame connections
were also standardized as single screw connection.
From Tables 5 and 6, the quantity take-off of thestandardized parts is shown, adding up to 129 parts.
Table 5 CFS frame parts

Web

643

Web

643

Bottom
Chord
Top
Chord
Top
Chord

4259
2949
2941

Size

Use

DH140-50-1.40
DH140-50-1.40
DH140-50-1.40
U140-50-1.40
U140-50-1.40
U140-50-1.40

Stud
Stud
Stud
HeaderHeaderSill
Diagonal
Brace
Top Track
BottomTrack
Top Track
BottomTrack
NogginNogginNogginNogginTop Track
BottomTrack
NogginHeaderTop Track
BottomTrack
NogginHeaderHeader

U140-50-1.40
U140-50-2.50
U140-50-2.50
U140-50-2.50
U140-50-2.50

Fig. 6

U140-50-1.40
U140-50-1.40
U140-50-1.40
U140-50-1.40
U77-32-0.80

Vertex BD truss part designation

Design for ease in insertion and connections

U77-32-0.80

Self-drilling screws are used for each connection.
Each intersection would only require a single screw,
as reflected in the shop drawings, and a dimple wasalready provided for each screw connection during
the manufacturing process to lessen the amount oftime spent in the fastening of members, as shown in
Fig. 7. The location of these screws is also indicatedin the shop drawings created in the Vertex BD. These
self-drilling screws possess relatively high strength,
and their installation would only require a screw gun
for fastening.

U77-32-0.80
U77-32-0.80
U77-32-0.80
U77-32-0.80
U77-32-0.80
U77-32-0.80
U77-32-0.80

531

Length(mm)2392.00
292.001092.00
1135.00
1345.00
1345.00

Quantity
(pcs)
41.00
8.00
5.00
1.00
2.00
2.00

1188.00

8.00

4000.00

2.00

4000.00

2.00

6212.00

2.00

6212.00

2.00

2905.00
1832.00
3995.00
476.003696.00

1.00
1.00
1.00
1.00
1.00

2696.00

1.00

2702.00
1031.00
1487.40

1.00
1.00
1.00

493.101.00

493.801023.00
1031.00

1.00
1.00
1.00

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Table 6 CFS truss parts

Work Description

Size

Use

DH140-50-1.40
DH140-50-1.40
DH140-50-1.40
DH140-50-1.40
DH140-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40
U100-50-1.40

Top Chord
Bottom Chord
Web
Web
Web
Top Chord
Bottom Chord
Web
Diagonal Brace
Top Chord
Bottom Chord
Web
Diagonal Brace

Length(mm)
2252.804258.60
1116.80643.301193.00
2224.40
2224.40
1175.00
1501.00
1463.101463.00
1172.00
1294.00

Qty
(pcs)
4.00
4.00
4.00
4.00
4.00
2.00
2.00
6.00
4.00
1.00
1.00
3.00
2.00

Design for current process capabilities
A local CFS manufacturer was consulted
regarding the application of the DfMA parameters forthe frames. As such their current practices been
embedded in the application of DfMA.

DAY
Duration(days) 1 2 3 4 5 6 7 8 9 10 11Foundation Works
Manufacturing of Screw Piles
Delivery of Screw Piles
Installation of Screw Piles
Framing System
Manufacturing of CFS sections
Delivery of CFS sections
Assembly and Installation of CFS
Roof Framing
Trusses assembly and installation
Purlins Installation
Roofing Sheet Installation
Partitions
Exterior Walls Installation
Interior Drywalls Installation
Hardwares
Hinges Installation
Doors Installation
Windows Installation
Utilities Installation

Fig. 8

2
1
1
2
1
2
2
1
1
3
2
1
1
1
1

CFS Gantt chart

Cost (USD)

5000

Margin for alternative design and assembly process
Exploration of modularization and 3D
volumetric packaging options are suggested for futureassemblies, as well as assessing the impact of
adopting these methodologies.

4000
3000

Material Cost

2000

Labor Cost

1000
0

IFRC

Fig. 9Project Completion Time
The original IFRC shelter was recorded to beconstructed in 12 days. Based on the Gantt Chart
shown in Fig. 8, the total number of days forconstruction was reduced to 11 days by applying the
new scheme involving CFS and screw piles, saving
only 1 day in the construction period. In the chart,manufacturing and delivery must be included in thescheduling since the CFS and screw piles
specifications are not commercially available and are
to be fabricated according to the design
specifications, which, in the process, consumed 2days of the overall schedule. Thus, if the CFS andscrew piles are readily available, the construction
period would only take 9 days to complete.

CFS

Estimated project cost of IFRC and CFS

Cost per year
(USD/year)

600.00400.00200.00
0.00
IFRC

CFS

Fig. 10 Cost per year of IFRC and CFS shelters
However, to appropriately assess the efficiency ofusing the CFS scheme, the anticipated lifespan ofeach scheme must be taken into consideration. The
IFRC frame only has an anticipated lifespan of 5
years, whereas the CFS frame may last up to 30 years
in lifespan [18]. On the other hand, Eurocode has set
temporary structures to have a design life of 10 years[19] which will be the anticipated lifespan that will betaken into consideration for the CFS since it willdefinitely be able to last the 10-year requirement due
to its adequacy in design and documented anticipatedservice life. Therefore, to properly assess the cost
efficiency of the two schemes, it would be appropriate
to distribute the estimated cost over the indicative

Project Cost
Using the quantities provided by the IFRC in theoriginal scheme and the present unit costs ofmaterials, the present estimated cost for the original
IFRC increases by 98.99% in overall project costwhen replaced with the CFS scheme as shown in Fig.
9. Material cost is the primary contributor to theincrease since the CFS scheme uses steel, a material
known for expensive cost that escalates every year.
532

SEE-Mie, Japan, Nov.10-12, 2022

service life of both schemes which are 5 and 10 years
for IFRC and CFS, respectively. As reflected in Fig.
10, the IFRC incurs a higher annual cost at 567.75
USD per year compared to the CFS which only costs
472.75 USD per year which shows more favorable
cost efficiency by saving about 20.10% yearly costs.

[5] IFRC/RCS 2013. Post-disaster shelter: Ten
designs. Geneva: International Federation of Red
Cross and Red Crescent Societies. 2013.
[6] Camp Coordination/Camp Management 2010.
Collective Center Guidelines. United Nations
High Commissioner for Refugees andInternational Organization for Migration. 2010.
[7] Sever, S. M. & Altun, M. C. Design of a postdisaster temporary shelter unit. ITU Journal of
Faculty of Architecture, Vol. 6, 2009, pp. 58-74.
[8] Gerth, R., Boqvist, A., Bjelkemyr, M., &Lindberg, B. Design for construction: Utilizing
production
experiencesindevelopment.
Construction Management and Economics, Vol.
31, Issue No. 2, 2013. pp. 135–150.
[9] Peterseim, J. H., White, S., & Hellwig, U. Novelsolar tower structure to lower plant cost andconstruction risk. AIP Conference Proceedings,
Volume 1734, Issue No. 1, 2016.
[10] Ramaji, I. J., Memari, A. M., & Messner, J. I.
Product-oriented
informationdeliveryframework for multistory modular building
projects. Journal of Computing in Civil
Engineering, Vol. 31, Issue No.4, 2017.
[11] Boothroyd, G. Assembly automation and productdesign. CRC Press, 2005.
[12] Lu, W., Tan T., Xu, J., Wang, J., Chen, K., Gao,S. and Xue, F..Design for manufacture andassembly (DfMA) in construction: the old andthe new, Architectural Engineering and Design
Management, Vol. 17, Nos. 1-2, 2021 pp. 77-91.
[13] Alemdar, F. and Al Gaadi, F.M.A. Experimental
Study of Earthquake Simulator for 3D ColdFormed Steel Frame Structure. Latin American
Journal of Solids and Structures, Vol. 19, 2022.
[14] Zhang, D.J.Y. “Predicting Capacity of HelicalScrew Piles in Alberta Soils”. MS Thesis,
Department of Civil and Environmental
Engineering, University of Alberta. 1999.
[15] IFRC/RCS 2011. Post-disaster shelter – Eightdesigns. Geneva: International Federation of Red
Cross and Red Crescent Societies. 2011.
[16] Nasr, M.H., 2004. Large capacity screw piles. In:
Proceedings of the International Conference:
Future Vision and Challenges for Urban
Development. Cairo, Egypt, 20–22 December,
pp. 1–15.
[17] Mitsch, M.P., Clemence, S.P., 1985. The uplift
capacity of helix anchors in sand. In: Uplift
Behaviour of Anchor Foundations in Soil.
American Society of Civil Engineers, New York,
pp. 26–47.
[18] Lu, W. Chapter 12: Sustainable applications ofcold-formed steel structures: connections andjoints. Recent Trends in Cold Formed Steel
Structure. Woodhead Publishing. 2016. p.245[19] European Committee for Standardization.
Eurocode BS EN 1990:2002 +A1:2005. 2010.

CONCLUSION
This paper shows the process and advantages ofapplying DfMA using CFS and screw piles in
temporary shelters that could be utilized in thePhilippines after a disaster. DfMA considers the
manufacturing and assembly of the designed CFS
sections in the design which in turn would facilitate
the ease in construction process, cost and completion.
While the effect of using the proposed scheme to thecompletion time of the shelter was insignificant due
to addition of the manufacturing and delivery periodof the parts, it was shown that the cost efficiency ofusing the proposed scheme is more favorable than theoriginal scheme followed in constructing the shelter.
ACKNOWLEDGMENTS
This project is funded by the Department of
Science and Technology (DOST) through the Science
for Change Program (S4CP) – Collaborative
Research and Development to Leverage Philippine
Economy (CRADLE) and monitored by DOST Philippine Council for Industry, Energy, andEmerging Technology Research and Development(PCIEERD) with Project No. 8739. The authors
would like to acknowledge DOST, PCIEERD, De La
Salle University and Accutech Steel and Services,
Inc. for their support on this paper.
REFERENCES[1] Department of Human Settlements and Urban
Development - Philippines and The World Bank.
Post-Disaster
Shelter
RecoveryPolicyFramework: Building a Responsive System toSupport Resilient and Equitable Recovery in thePhilippines. 2021.
[2] United Nations Office for the Coordination of
Humanitarian Affairs (OCHA) Philippines:
Destructive Tropical Cyclones from 2006 –2016. March Issue, 2017.
[3] United Nations High Commissioner for Refugees(UNCHR). Safeguarding the rights of the
Vulnerable: Ensuring solutions for the internallydisplaced population due to Super Typhoon Rai in
Caraga Region and Southern Leyte province.
Thematic Bulletin Issue No. 1. 2022.
[4] Bashawari, A., Garrity, S. and Moodley, K. An
Overview of Design Relief Shelters. 4thInternational Conference on Building Resilience,
Salford Quays, United Kingdom. 2014.
533

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

DETECTION OF GEOGRAPHIC FRACTURE-FAULT STRUCTURES
USING DEEP LEARNING MODEL WITH STEPWISE ELIMINATIONMETHOD FROM HIGH RESOLUTION SATELLITE IMAGERY IN
DJIBOUTI

1

Denis Pastory Rubanga1, Sergio Azael May Cuevas1, Yessy Arvelyna2 and Sawahiko Shimada1
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan; 2 Remote Sensing
Technology Center of Japan, Japan

ABSTRACTIn the arid lands of Eastern African Djibouti, underground water is essential for supporting the livelihood of
humans and livestock animals since no permanent surface water exists. Several attempts have been made toestimate the groundwater flow in the regions to delineate the accessibility of the water resources. However,accurate groundwater simulation is hindered sometimes by the existence of the geological fault and fractures,
which influence the groundwater cycling systems in terms of the flow direction change, linkage or damming
functions. This study uses deep learning techniques in fracture-fault detection in the target area within Ali Faren
sub-catchment of Ambouli Wadi, Djibouti. We used WorldView-3 (WV-3) , high-spatial resolution Earth imaging
multispectral satellite image of eight bands as input in training deep convolutional neural network (Deep-CNN)
model using wadi streamline derived from AW3D-DEM as labels. The fracture-fault structures were extracted by
stepwise elimination method using the geological characteristics. We further validated the results using fault
distribution from relief images derived from adaptive gradient filter applied on ortho-rectified PALSAR-1 RTI andPALSAR-2 Global Mosaic (herein PALSAR-1/2) image data. The result showed that fracture-fault lines weredetected using multi-input images in the deep CNN model. The proposed Deep-CNN model will be applied toother catchments in Djibouti to help in groundwater flow model simulations and eventually help locate the potential
area for groundwater resources in the entire country of Djibouti.
Keywords: Fracture-fault, High-resolution satellite, Deep-learning, Stepwise elimination method

INTRODUCTION

the southwest of Djibouti show a common
evolutionary pattern of groundwater, i.e. a recharge
from wadi-rivers flown into the alluvium layer, then,circulated downward into the basalt sub-surface layer
through major faults, and mixed with a moregeochemically evolved groundwater [2]. Djiboutiwith a semi-arid and arid type of weather, ischaracterized by low rainfall of about 130 mm/year,
whereby 83% evaporates to the air and 6% flows on
the ground surface, 5.5% penetrates sub-surface and
5% into sub-ground, forming the renewable groundwater resources estimated as 300 Mm3/year [3].
In the current work to estimate the groundwaterflow in the regions to delineate the accessibility of thewater resources, GETFLOWS (a General purpose
terrestrial fluid-flow simulator) is used based on
previous works of [3] and [4], to simulate both surface
and subsurface systems (forming the undergroundwater reserve). A component of GETFLOWS
subsurface water simulation includes stream
formation that are purely based on hydrodynamic
principles governed by recharge, topography,
hydraulic conductivity, and flow parameters. Since
evolutionary patterns of groundwater as recharge ofwadi streams are majorly circulated through fracture-

Djibouti covers a land area of 23,200 km2, locatedon the north side of the Horn of Africa. The country
is characterized with fracture-fault lines due to its
geology setting that consist of ancient sedimentarylands from Mesozoic age (secondary era). Fracturefault structure systems such as the Ali Sabieh horst(ca, 27 to 23 Ma) from Djibouti city south into thenorth of the Aysha horst in Ethiopia. The fracturefault systems within borders of this horst arecomposed by rhyolitic lavas on the East (ca, 25 to 19
Ma) and in the west side (14 Ma to 10 Ma) andcovered mainly by basaltic flows, such as the Dalha
series (ca, 9 to 4 Ma), Somalis basalt (ca, 7 to 3 Ma)in the east side. In the central region, Tadjourah
basalts (3 Ma to 1 Ma). In the Asal rift zone,
Tadjourah region (central of Djibouti), the lavas frommagmatic episode of Fieale volcano (ca, 300 to 65 ka)
in current elevation contour lines, form thetopography and geology of the rift zone. Fracturefaults volcanic aquifers have been analyzed as themain water resources in Djibouti, shown by thepumping test data which consist of major basaltic
series [1]. The geochemical and isotopic surveys in
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fault systems, poor fracture-fault delineation using
GETLFOWS greatly impacts underground water
simulation, therefore, it is necessary to clearlydelineate the fracture-fault distribution in any locality
to support locating an area with high possibility ofgroundwater resources. However, the success of suchwork require data which apparently is limited.
In this study, we propose a Deep-CNN [5]approach that relies on easily accessible satellite
derived datasets that could help calibrate and evaluate
GETFLOWS hydrologic models for an ungauged
catchment area. Deep-CNN approach is used for
fracture-fault detection based on WV-3 [6],PALSAR-2 [7], 5 m resolution DEM (ALOS World
3D level 1 DSM) [8] and slope derived from DEM intraining a multi-input Deep-CNN model using wadi
streamline derived from AW3D-DEM as fracturefault labels of target area as shown in Fig. 1.
The use of deep learning techniques ingeological feature settings has widely been used, suchas automatic extraction of seismic landslides in large
areas with complex environment in earthquake areas[9] [10]. [11] used object-oriented classification
technique to segment homogeneous images using
high-resolution multi-spectral data. Other works haveused U-NET models in image classification [12].
However, the application of deep learning on surface
geological structures such as fracture- fault is limited.

streamline were derived from AW3D-DEM of thetarget area. The coverage of the created composite
layer included the target Ali Faren catchment. (Fig. 1)
Labeling the Training Data
To train the Deep-CNN model on a generated
multi-band raster image, a group of labeled raster
cells of the 11-multi-band, which can indicate thecharacteristics of fracture-fault, must be used to train
the model. We obtained the fracture-fault label byusing ArcGIS Pro software, applying the buffer
method of 50 m resulting into a polygon shape asshown in Fig. 1. The derived polygon shape files wereused as Region of Interest (ROI) in ENVI Deep
Learning in creating training labels [15], [16].

STUDY AREA
Study Area Data
In this study, we used WorldView-3 (WV-3) thelatest in a constellation of commercial high-spatial
resolution Earth imaging satellites developed byDigitalGlobe Inc (Longmont, Colorado, USA). [8]High-spatial images collected between 12th May 2018
and 5th April 2021 with 0% cloud cover between N.W
Latitude 11.55372100 and Longitude 42.77572500,
8-band multispectral image (red, red edge, coastal,
blue, green, yellow, near-IR1, and near-IR2) 400 nm– 1040 nm of 1.2-m spatial resolution, and 5-m spatial
resolution AW3D DEM (ALOS World 3D level 1
DSM). The original DEM resolution of 5-m wasdownscaled to same resolution as the PALSAR-2
images. Using ESRI’s ArcGIS Pro v 2.7 (ESRI 2021),
we created the slope images derived from the DEM
and PALSAR-2, that were stacked together to create
a composite of 11-band raster image. The PALSAR2 Global Mosaic data is a seamless global SAR image
created by mosaicking the SAR image inbackscattering coefficients measured by PALSAR-2
with 25-m resolution. Since PALSAR-2 are filledwith speckle noise due to the interference during
signal transmission, the adaptive filter Enhanced Lee
Filter was applied to reduce speckle noise on theimage [13], [14]. Fracture-fault labels as wadi

Fig. 1 Stacked 11-band raster image showing Ali
Faren water catchment in blue polygon, wadi
streamline polygons of training (red) and validation(black) data for training Deep-CNN model
DEEP-CNN TRAINING AND RESULTS
ENVINet5 (built in ENVI version 5.6, and ENVI
Deep Learning version 1.2) is used to train the DeepCNN model on the multi-band raster image. The
ENVINet5 architecture shown in Fig. 3 is a maskbased encoder-decoder fully convolutional networkwith 5 levels and 23 convolutional layers. Itsarchitecture is based on U-Net [17] with somemodifications on layers of convolution and the size of535

SEE-Mie, Japan, Nov.10-12, 2022

creates a new training dataset with a randomly
assigned scale factor per training example.
In traditional Deep-CNN training, an epoch
represents the period in which all data sets are passed
into the training model. However, it is different in the
ENVI Deep Learning Module, which intelligently
extracts patches from the training raster, so highbrightness characteristic pixel areas are more often
encountered than low-brightness regions at the
beginning of training. At the end of the training, allareas look more uniform. Because there is bias
determination in patch extraction, an epoch in ENVI
deep learning refers to the number of patches trained
before bias decision adjustment.
To get a better model, multiple epochs areneeded to fully train the model. The number of epochs
and the number of patches per epoch depend on thediversity of feature sets to be learned, which has noexact value. In general, enough epochs are needed toadjust the weight to ensure smooth progress. We set
number of epochs to 50.
Model training were run on a Windows 10 Pro
Operating System Intel (R) Core 9TM i9-990K CPU
processor clocking 3.6GHz and with a NVIDIA
GeForce RTX 2080i GPU. The training time of themodel is 50 min. The curves of training accuracy,
training loss, training precision and training recall are
shown in Fig. 3.

Fig. 2 ENVINet5 architecture.
Source; Harris Geospatial Solution (2021) [16]input and output. The input of ENVINet5 is a patchwith fracture-fault polygon sampled from the 11-band
multi-input raster images. Training raster is used totrain the initialization model. Model training is to
expose training raster to the model. The model learns
to convert the spectral and spatial information in the
training raster into a class activation map, aprobability map, highlighting the target to be
extracted as shown in Fig. 5.
ENVINet5 refers to the binary cross-entropy loss
function with the weighted map used by U-Net

RESULTS AND DISCUSSION
Training and evaluation result
The training curve showing accuracy, loss,
precision, and recall is shown in Fig 3. Similarly,
results of validation of the raster images showing
validation accuracy, validation loss, validation
precision and validation recall curves are shown in
Fig. 4.
ENVI generates a model based on the lowest
point of the validation loss value, that is, the epochwith the best match between the classifier and thevalidation data. The lowest loss value of the trainedmodel is 0.0393, accuracy is 0.9604, precision is0.8438, recall is 0.9582 and F1 is 0.8997. Validationof data yielded a loss 0.03391556, accuracy of 0.9684,
precision of 0.9124, recall of 0.9701 and F1 of 0.8997(1)
where pl(x)(x) is the softmax loss function; l : Ω→ {1,···,K} is the label value of the pixel and ω:εR
is the weight of the pixel that gives a higher weight tothe pixel close to the boundary point in the raster
image[18].
The number of patches per epoch determines theamount of training. The settings are lower for small
datasets and higher for large datasets. The number ofpatches per epoch is set to 414 and number of patches
per image set to 32. The number of patches per batch
system is automatically set to 1. The rest of theparameters ENVI automatically determines theappropriate values. To prevent overfitting, data
augmentation is used. Data augmentation is atechnique commonly used with deep learning to
supplement the original training data. By having more
information to extract from the training data, thetrainer and classifier can more effectively learn theappearance of features of interest. During each epoch,
ENVI creates a new training dataset with a randomly
assigned angle per training example. Likewise, it

Image classification
To classify other raster images for fracture-faults
using the trained model, class activation map raster
represented in Fig. 5 was generated. The classactivation map shows each pixel in the grayscale
image roughly represented as probability of
belonging to the fracture-fault, and the thresholdranges from 0 to 1. The black area in the classactivated grayscale image represents the area withhigh probability, which means it is identified as a
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SEE-Mie, Japan, Nov.10-12, 2022

fracture-fault. The result identified by the trainedmodel is a fracture-fault probability map; the larger
the values in this probability map, the more confident
the identified fracture-fault.

Step-wise
elimination
classificationinfracture-fault

Fracture-fault classification from the classified
image based on activation map is not astraightforward approach. To identify the real
fracture-fault a stepwise elimination approach wasused to identify the fracture-fault from the wadi
streamlines class activation map since the result of theactivation map are a mixture of wadi streamline andfault fracture.
Using the stepwise elimination, we set
conditions based on geological characteristics offracture-fault. Fracture-fault will not winded as muchas wadi. Wadis will not go beyond their watershedregions and some parts of the fracture-faults might beused as wadi. Fracture-fault shapes as defined ingeological maps also tend to be straight.
The predefined assumption of the stepwise
elimination considered setting threshold to the classactivation maps. With the set threshold of class valueof given pixel values of greater than or equal to thethreshold value, the polygon will be designated as thefracture-fault feature class within the polygon.
Through trial and error, the appropriate
threshold used was between 0.0588 and 0.8409 for a
mixture of wadi and fracture-fault polygons. The best
threshold for fracture-fault activation were between
0.186343 to 0.499941. We further eliminated theclassified raster based on the prior defined activation
map, result of the final fracture-fault are shown in Fig.
6 and Fig. 7.

Fig. 3 Showing Training curve for accuracy, loss,
precision, recall of the experimentFig. 4 Validation curves for accuracy, loss, precision,
recall and F1

Fig. 6 Image class activation raster showing fracturefault (green) after stepwise elimination

Fig. 5 Image class activation raster of selectedvalidation area. In blue: Ali Faren watershed.

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Science and Technology Research Partnership for
Sustainable Development (SATREPS GRANT
NUMBER: JPMJSA1802) SATREPS (Science andTechnology Research Partnership for Sustainable
Development). This study acknowledge the copyright
Notice for ALOS PALSAR RTC:© NASA 20062007, Includes Material © JAXA, METI [2006-2007].
The PALSAR-2 Global Mosaic data have been
provided by the Japan Aerospace Exploration Agency.
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Fig. 7 Fracture-fault as seen on a wadi after step-wiseelimination

CONCLUSIONSIn this study, we used Deep-CNN technique in
detection on fracture-fault structures in Ali Faren
catchment in Djibouti. Our solution evaluated thepossibility of fracture-fault structure detection fromhigh resolution satellite data, DEM, Slope and
PALSAR-2 data. Further, determination of fracturefaults is not straightforward, so we applied a stepwise
technique to the Deep-CNN generated classactivation map containing both wadi and fracturefault features to attain only fracture-fault structures.
The result showed that using multi-layer 11data in deep-CNN model, fracture-fault lines weredetected as evaluated using explained evaluation
metrics such as accuracy, precision, and recall. The
proposed Deep-CNN model results could be applied
to other catchments in Djibouti to help in groundwaterflow model simulations and eventually help locate thepotential area for groundwater resources in the entire
Djibouti.
Future research of this work will focus on
evaluating the developed deep-CNN models and its
application in wider areas within Djibouti, and on theimplementation of approaches based on other deeplearning architecture, such as Feature engineering ofmost appropriate parameter, that includes several
multispectral bands as inputs. The intended goal
would be to use the most appropriate models andlimited multispectral bands in developing a deepCNN model to be used in other water catchments in
Djibouti and eventually integrating fracture-faults
detected results from deep learning models ingroundwater flow model simulation.
ACKNOWLEDGMENTS
This study was supported by Japan Science andTechnology Agency (JST) and Japan International
Cooperation Agency (JICA) under the project of538

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

SPATIAL ANALYSIS ON THE WIN OF CANDIDATE NUMBER 2 IN
THE 2020 DEPOK CITY ELECTION
1,2 ,Imam Budi Hartono 1 , Chotib 2
Development Studies Study Program Urban, School of Strategic and Global Studies, University ofIndonesia, Indonesia

ABSTRACT
Depok City is one of the the city that embraces system democracy, since 1999 expansion, system election headarea in Depok City has been carried out by democracy. Of all many elections that have been taking place in Depok
City, the Depok City Local Election for the 2021-2024 period was one of the sufficient interesting Local Election
processes, because there are two strong candidates from the previous power holder with different partner. This
research aims to spatially analyze the victory of pair number 2 in the 2020 Depok City election. Spatial analysisof the research use LISA Moran's and spatial regression using Geoda software. The results of the analysis showthat there is no spatial dependence of the factors that affect the winning of the pair number 2. The distribution of
votes for pair number 2 has 31 sound bases and 30 bases for pairs number 1 and 2 in neutral villages, namely
Grogol and Curug. Based on picture Moran's Scatterplot picture on value : 0.163. This show existence trend
formation cluster spatial between nearby village.
Keywords: Depok 2020 Pilkada, Geoda, Couple No. 2, Regression Spatial
INTRODUCTION

characterized by geographical attributes like location
coordinate and others that the Geographical
Information System (GIS) has role important instudies spatial. GeoDa software was introduced firsttime by Luc Anselin 2002 .
The spatial effect spatial is divided into two parts:
spatial dependency and spatial heterogeneity.
Dependency spatial occurred because of the existence
dependence on regional data, while heterogeneity
spatial occurred because of the existence difference
among one region to another. Panel data linear
regression model containing interaction between
spatial units will have variable dependent spatial lagor spatial process in common mistakes called thespatial lag model (SAR) and the spatial error model(SEM), (Elhorst , 2010). The Spatial lag (SAR) modelshows influence variable independent on space j withrespect to variable dependent room I (Hasna, 2013).
One of the statistical tests to find out existence
dependencies spatial is by doing selection early
regression using the Lagrange Multiplier (LM) test to
detect existence dependencies spatial by more
Specific that is between LM (lag), LM (error) ormodels both of them are usually called the Spatial
Autoregressive Moving Average (SARMA), in
testing this determine choice best model Among
spatial lag or spatial error.
This research used regression spatial andquantitative method by testing autocorrelation spatialwith Moran's scatterplot method, and LISA by using
secondary data in the form of amount population/
district, total valid votes per candidate couple,
mapping Depok City Administration. According to
Chotib (2019), Moran's I as in the equation:

Geography political is a branch of humans
geography, which learns connection Among behavior
politics and physical features. This means thatbehavior political residents are explained by their
attachment on the physique characteristics theenvironment in which the community man that live
(Hayati , 2007). From all many elections that havebeen taking place in Depok City, the Depok City
Pilkada for the 2021-2024 period is one of theinteresting Election process, because there are twocandidates from previous period who had strong
holder power with different partner. Based on
temporary survey results, Idris Imam was potential to
become the winner and it turns out the became thewinner. The Idris – Imam pair got 415,699 votes in
the 2020 election defeated Pradi – Aviva couple
which gained 333,304.
For this reason, it is necessary to do a regression
to show that the use of the absolute number of votes
as the dependent variable is better than using a basic
and non-basic. And the next, just use regression
analysis with data on the absolute number of votes 02.
The purpose of this research is to test classicalregression analysis (OLS) and spatial regression of
votes for pair 02 in the 2020 Depok Regional HeadElection. In addition, this research also simulates 02
votes based on the model. formed, either by classicalregression or spatial regression.
RESEARCH METHODS
According to Jaya (2016) in Lloyd (2010) Spatial
data is all everything related to earthiness room540

SEE-Mie, Japan, Nov.10-12, 2022𝑍=

𝐼−𝐸(𝐼)(1)√𝑉 (𝐼)

Based on the descriptive analyze test, from 63
villages the results are as following :1. Vote number 2 has a minimum value is 2,143
people and a maximum is 17,651 people with anaverage of 6,603.21 people and a median of 5,514
people, with a standard deviation of 3276,33.
2. The population density has a minimum value of
2,587 people/km2 and a maximum of 24,582
people/km2 with an average of 10,175.67
people/km2 and a median of 8,983.00 people/km2
with a standard deviation of 5,179.40 people/km2.
3. Non moslem voters have a minimum value of 2%
and a maximum of 18% with an average of 6.3%,
median of 5% and standard deviation of 3.3%;
4. Beginner voters have minimum value 14%,
maximum is at numbered 19% with an average of
15.9%, a median of 16% and a standard deviationof 1.03%;
5. Formal workers voters have 3% minimum value ,maximum numbered 27% with an average of
6.1%, a median of 5% and a standard deviation of
3.54%;
6. High school graduates and above have minimum
value 33%, maximum numbered 65% with anaverage of 48.13%, median 49 % and standard
deviation 6.98%.

According to opan (2019) spatial error or spatial
moving average is a model that considers interaction
correlation error between regions. Spatial errors canbe described instability. The spatial error equation is
as follows :𝑦 = 𝛼 + λ𝑊𝜀 + 𝑋𝑖𝛽 + 𝜀(2)Description :α : Constanty : Variabel dependent
𝑿𝒊 : Variabel independent i𝛽 : Vektor coefficient independent variable (k × 1)
which has free from error effect.
λ : The coefficient of moving average that
accommodates the effect of the error from theinteracting neighboring region by spatial
ε : Vector error term where 𝜀~ 𝑁(0, 𝜎 2 𝐼).
This research used two types of variable,
independent variable and tied variable. According toAsmarani (2018), free variable that influenced boundvariable, where free variable is a control from boundvariable bound, while bound variable is variables thatare influenced by free variables. Bound Variable usedin research is the amounts of votes couple number 2(Idris – Imam) on election head Depok City area in
2020. Meanwhile free variable used in research is anumber of influencing factors, there are voters in
Depok City in 2020 including density residents, nonmoslem residents, novice resident, formal residents,and High school education level and above residents.
The regression modeling used is classical regression(OLS) and spatial error regression.

Based on the results of 2020 general election, forcouples number 2 Idris - Imam, has election base in
31 urban villages, 30 non-basic areas and 2 urban
villages which has neutral character, 2 villages that
had neutral character are Grogol Village and Curug
Village, Cimanggis Sub District. As described in
distribution as follows :ANALYSIS RESULTS
a. Descriptive Analysis
Data processing is carried out to integrate using
SPSS and Geoda software.
Table 1 Summary of StatisticsN
MeanMedian
Std.
Dev
Min
Max
Sum

Y
63
6603,215514,00
3276,33X1
6310175,678983,00
5179,40

X2
63
0,06
0,05
0,03

X3
63
0,15
0,16
0,01

X4
63
0,06
0,05
0,03

X5
63
0,48
0,49
0,06

2143
17651
4160022587
24582
641067

0,02
0,18
4,00

0,14
0,19
10,05

0,03
0,27
3,84

0,33
0,65
30,32

Fig. 1 Distribution Region Spatial Votes
Source : Analysis Results, 2022

Source : Analysis Results , 2022
Description :Y : Voice Number 2 (people)
X1 : Population Density (people/km2)
X2 : Pro Non Muslim (%)
X3 : Beginner Pro (%)
X4 : Pro Formal Workers (%)
X5 : Pro high school and above (%)

By using percentage of votes number 2, the author
did the scatter area selector mapping, the Type of the
map to be chosen must present different
visualizations and each maps gives different
conclusion to either high or low location numbers.
Highest and most value are generally depicted withdarker colors.
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SEE-Mie, Japan, Nov.10-12, 2022

Fig. 2 Distribution Spatial Custom Break
Source : Analysis Results , 2022

Fig. 4 Lisa Cluster Map Voice Number 2
Source : Analysis Results processed Geoda , 2022

Based on custom break map above, the percentage
of couple number 2 is divided to 3 categories
including :1. Category 40% to 50% of the votes, in 10 urban
villages ,2. Category 50% to 60% of the votes , in 39 urban
villages .
3. Category 60% to 80% of the votes, in 14 urban
villages.

In the figure 4, the voters of couple number 2 arenot equal, each region has been colored to signify
spatial effect on each region by using (LISA) method,that tested autocorrelation locally. In the mapping
there are 3 colors showing existence indication spatial
based on density area/location.
Quadrant I High – High (HH) consists of over 6
villages with percentage 9.52%, Quadrant I High –High (HH) consists of over 6 villages with percentage
9.52%, Quadrant II Low – High (LH) consists of over
6 villages with percentage 6.34%, Quadrant III Low –Low (LL) consists of over 3 wards with percentage
4.76%, Quadrant IV High – Low (HL) consists ofover 0 wards with percentage 0%, No Significant
there are 50 villages with percentage of 79%. Basedon pictures and tables above, as example Pasir
Gunung Selatan Village is in quadrant II Low – Highmeans has very different significant value 0.001 witharea surroundings (marked with color very darkgreen), however from aspect voice including 0.60 –
0.80% of the vote. While nearby village has above
80%, that means votes in Pasir Gunung Selatan
Village correlates with votes of nearby village that is
Pondok Cina Village (with spatial effects) which is
low and insignificant, while Pasir Gunung Selatan
Village has high score.

Depok City was dominated by 02 votes, ranging
from 50% to above 80%. Only a few regions have a
02 vote percentage of less than 50%.
b. Analysis Autocorrelation Spatial Voter
Analysis autocorrelation spatial covers testing andvisualization statistics Moran's I global (test forclustering) and local (test for clusters). Global test
visualized with using a Moran scatter plot (Hawkins
et al., 1999). Autocorrelation can be seen from
Moran's Index and local autocorrelation could seenfrom Local Indicators of Spatial (LISA).

c. Regression Analysis
The research evaluated how far the specification
regression classic is, which is well-known incriminology literature, and strong for explicit spatial
effect consideration (Anselin et al., 2006). The results
showed the classical regression on the votes of pairnumber 2 as follows :Fig. 3 Moran's Scatterplot Voice Number 2
Source : Analysis Results Geoda , 2022

Table 2 Correlation Test Results Inter OLS
Regression Variable
Var
Const
X1
X2
X3
X4

Based on picture Moran's Scatterplot picture on
value : 0.163. This indicates trend formation
existence cluster spatial between nearby villages bymapping LISA Cluster Map.

542

Coef
829,24500-0,06370-0,30775
1,04154-0,25319

Sta. Error
247,45400
0,02498
0,11798
0,15581
0,14223t-Sta
3,35111-2,55015-2,60858
6,68467-1,78013

Prob
0,00143**
0,01348**
0,01159**0,00000**
0,08039

SEE-Mie, Japan, Nov.10-12, 2022

X5

0,16285

0,06000

2,71427

0,00877**

Source : Analysis Results Author , 2022

Coefficient estimated significance at * p≤0.1; **p≤0.05; *** p≤0.01
Source : Analysis Results Author , 2022

Result of the above table shows that the Moran
I test has significant results or LM value (lag) > = 0.05
with value 0.00403 . P value on test this more small
from level real 5%, it can be concluded that there isspatial lag influence on this model. Based on LM
error test results > = 0.05 or = 0.1. P-value in testing
this level value exceeds 5%, it can be concluded that
there is spatial error influence in the model. Because
the Lagrange Multiplier (Lag) is smaller than the
Lagrange Multiplier (Error)/SEM, and the robustness
value shows that the error model is more significant
than the lag model.

Based on results regression R-squared value of0.953536 or 95%. And the Adjusted R-squared is0.949460. From result above regression indicated that
there is four correlated variables tall with significant
numbers of 0.005 or <= 0.05 or = 0.1 as variable
Density (X1), Non Moslem Voters (X2), Beginners
Voters(X3) and Voters with high school education
graduates (X5), background and above < 0.05. Basedon the results of classic regression classic above, theequation obtained regression is as follows :Table 4 Spatial Output Lagrange Multiplier (Error)
Y = 829.245 - 0.0637029x 1 - 0.307754x 2 + 1.04154x
3 – 0.253191x 4 + 0.162846x 5

Var
Const
X1
X2
X3
X4
X5
LambdaThe model indicated that :1. Characteristics of number 2 voters was not athigh density (x1 ), because if it had 1% increasein high density it would decrease 0.06 votes.
2. Characteristics of number 2 voters was not nonMoslem ( x2 ), because if had 1% increase in non– Moslem voters, it would decrease 0.30 votes .
3. Characteristics of number 2 voters was beginnervoters (x3), because if it had 1% increase in
beginner voters, it would increase 1.04 votes.
4. Characteristics of number 2 voters was notformally educated (x4), because if it had 1%
increase in Formal educated voters it would
decrease 0.25 votes.
5. Characteristics of number 2 voters had highschool background and above (x5 ), because if it
had 1% increase, it would increase 0.16 vote.

Sta. Error
262.678
0.0234015
0.102054
0.146466
0.134929
0.053911
0.143378

Z-Value
3.14091-2.40496-3.70317
5.87289-2.39581
4.30173
3.01067Prob
0.00168**
0.01617**0.00021**0.00000**
0.01658**
0.00002**0.00261**

Coefficient estimated significance at * p≤0.1; **p≤0.05; *** p≤0.01
Source : Analysis Results Author , 2022
Based on the results of spatial error regression
abovef, the equation obtained regression is asfollows:
Y = 825.048 + 0.431663 - 0.0562797X1 - 0.377924X2+ 0.860177X3 - 0.332263X4 + 0.231911X5that model indicated that k increase 1 unit variable
besides variable independent used in models in
nearby something output will raise 0.431663 votes inthe village (meaning there is other variables thatcomes from the surrounding area ). Increasing of 1
inhabitant /km2 density population will decrease 0.06
votes for couple number 2. 1 inhabitant would
increase non moslem population will decrease 0.40
votes for couple number 2. 1 inhabitant would
increase beginner population will raise 0.86 votes forcouple number 2. Increase 1 inhabitant of formal
residents will decrease 0.32 votes for couple number
2. Increase 1 inhabitant with high school backgroundwill raise 0.23 votes couple number 2.
Processing results with regression model spatial
error and OLS between variable free to achievements
voice couple number 2 presented in table 5 :Classic regression election was chosen as earlystep, conducted by using the Large Multiplier (LM)test to find out spatial dependencies influence(autocorrelation) so that at the end spatial regression
model could be formed properly or more specific. The
level of significance of the model at = 0.05 or = 0.1.
Based on The results of the LM test on the OLS
regression model, spatial test dependency results asfollows :Table 3 Spatial Output Econometrics
DIAGNOSTICS FOR SPATIAL DEPENDENCE
FOR WEIGHT MATRIX :Batas_Kelurahan_Polygon_10022022(row-standardized weights)
test
mi/df
value
Moran's I (error)
0,19
2,87
Lagrange Multiplier (lag)10,04
Robust lm (lag)10,18Lagrange Multiplier (error)
1
5,24
Robust lm (error)
15,38
Lagrange Multiplier (sarma)
2
5,42

Coef
825.048-0.0562797-0.377924
0.860177-0.323263
0.231911
0.431663

Table 5 Estimation Coefficient Regression Spatial
Errors and OLS
VARIABELSPASIALOLS
EROR
Density-0.0562797-0,06370(0.0234015) ** (0,02498)**
Non-0.377924-0.307754
Moslem(0.102054) *** (0.11798) **prob
0,00403 **0,826100,66933
0,02199 **0,02036 **0,06623

Coefficient estimated significance at * p≤0.1; **p≤0.05; *** p≤0.01

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SEE-Mie, Japan, Nov.10-12, 2022

Beginner

0.860177
1,04154(0.146466)*** (0,15581)***formal-0.323263-0,25319(0.134929)**(0,14223)*
High School 0.231911
0,16285
and Upper(0.053911)*** (0,06000)**
Lambda0.431663(0.143378)**
constant
825.048829,24500(262.678)**(247,45400)**
Coefficient estimated significance at * p≤0.1; **p≤0.05; *** p≤0.01
Source : Analysis Results Author , 2022

Based on the modeling and mapping of voters forserial number 2 as follows:
1. The distribution of votes for pair number 2 has 31
sound bases and 30 bases for pair number 1 and 2
in neutral villages, namely Grogol and Curug.
And by using the percentage of votes for pairnumber 2 is in 3 categories including: the 40% to
50% category in 10 urban villages, the 50% to
60% category in 39 villages and the 60% to 80%
category in 14 villages.
2. If using spatial autocorrelation analysis, the valueof the Moran's Index and local autocorrelation canbe seen from the Local Indicator of Spatial(LISA). III Low – Low, 0 village is in Quadrant
IV High – Low, and there are 50 villages that are
not significant.
3. The results of the comparison between the spatial
regression model (error model) and OLS showthat the OLS regression model is more appropriate
to be used in analyzing the factors that affect thevotes of pair number 2. Islam, novice voters,
voters who have formal jobs, and voters with an
educational background of high school and above.
For estimation voice should use equality
regression classic (OLS) versus with use
regression spatial error , with Y OLS value of
416,002 and Y Real 416,002 while Y Error worth
415,333.

The results of the simulation analysis using theClassical OLS Regression Model and the Spatial
Error Regression Model produce a slightly different
estimate of the number of votes 02. The two
estimation simulations are presented in Figure 5
which shows a higher similarity in the Classical OLS
Regression Model than the Spatial Error Regression
Model. It seems that the Classical Regression Modelis more appropriate to use for estimating voteacquisition than the use of the Spatial Error Model,
although there is a spatial effect on the voteacquisition of 02. The result showed that connection
existence between regions that can affectachievements voice couple number 2 is already taken
into account in the spatial model.

REFERENCESCOMPARISON OF VOTE
ESTIMATION NUMBER 2[1] Alam, Moh Zainul. (2019). East Java economic
growth modeling with a spatial panel
econometric approach. Journal of trunojoyo:
Economics and Development studies.
[2] Andriaty, Purri. (2004). Influence Economic
Agglomeration and Factors Production to the
GRDP of the Regency /City on the Island Java :Comparison 2001 and 2002 ( Spatial Analysis
econometrics ). Depok : Postgraduate Thesis
Faculty of Economics s and Business Universityof Indonesia.
[3] Anselin, Luc. (2005). Exploring Spatial Datawith GeoDA : A Workbook. Center for Spatially
Integrated Social Science.
[4] Anselin, L., Lozano, L., & Koschinsky, J.
(2006). Rate transformations and smoothing.
Urbana-Champaign: patial Analysis Laboratory
Department of Geography University of Illinois.
[5] Application Spatial For Development. (2019).
Department Geography Faculty Mathematics
and Science Knowledge nature . University ofIndonesia. ISBN: 978-623-92282-1-7.
[6] Annur Muhammad Firman. (2019). Analysis of
Human Development Index Factors in Landak
District Using the Spatial Regression Model.
Riemann Research of Mathematics and20,00010,0001 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61
y KLASIKy ERORy realFigure 5. Comparison Estimate Voice
Source : Analysis Results Author , 2022
Based on picture on conclusion for estimation
voice should use equality regression classic (OLS)
versus with use regression spatial error, with Y OLS
value of 416,002 and Y Real 416,002 while Y Error
worth 415,333. From this calculation, it appears that
the Classical Regression Model is closer to reality
than the calculation results using the Spatial Error
Regression Model. To prove again that the classicalOLS model is closer to the real results, it can be tried
using the estimated value of each kelurahan.
CONCLUSION

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Mathematics Education. Volume 1, No. 1,
October 2019, p. 44-54.
[7] Baltagi H. Badi & Long Liu. (2012). Testing for
Spatial Lag and Spatial Error Dependence Using
Doble Length Artificial Regressions. Stat
Papers(2014)55: 477-486.
[8] Fauzi, Fatkhurokhman. (2016). The Best Spatial
Regression Model for the Central Java Province
Human Development Index.
[9] Hamdan, Opan Fauzan. (2019). Ratio of
Educators, Ratio of Health Workers, and Human
Development Achievements in Analysis
Spatial. Depok: Master of Economics andPopulation Thesis Faculty of Economics andBusiness, University of Indonesia.
[10] Jaya, et al. (2016). Optimization Geoda In
Modeling And Mapping Diseases in BandungCity.
[11] Lloyd, C. (2010). Spatial data analysis. New
York: OXFORD University Press.
[12] LeSage, James P. (1999). The Theory andPracticeof
SpatialEconometrics.
ResearchGate.

[13] Mills, Terence C & Patterson, Kerry. (2009).
Palgrove Handbook of Econometrics Science.
New York:Springer .
[14] Nugroho, Aditya Harin . (2014). Spatial
Economics and Policy Analysis : Crime
Property Polda Metro Jaya. Depok: Thesis
Department Economics , Faculty of Economics
and Business, University of Indonesia.
[15] Novriandi Purba, Ongki. (2016). Modeling
Growth economy North Sumatra Province withapproach econometrics spatial panel data.
Journal science and art ITS Vol.5 No.2.
[16] Prahutama, Alan. (2014). Analysis of the 2013
Central Java Governor Election (Pilgub)
Victory With Spatial Autocorrelation. Statistics,
Vol. 2, No. 1, May 2014.
[17] Tobler, W. (1979). Cellular geography. In
Philosophy in geography, eds. S. Gale and G.
Olsson, pp.379-86, Dodrech: Reidel.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

EVALUATION OF GEOGRAPHICAL CHARACTERISTICS OF
FARMLANDS LOCATION IN DJIBOUTI USING GIS

1Ayako Sekiyama1, Towa Goto2, Takumi Sato3 and Sawahiko Shimada1
Faculty of Regional Environment Science, 2System Quest Inc, Japan, 3CAC Corp, Japan.

ABSTRACT
Djibouti is in Northeast Africa and is a severely arid region with annual precipitation of less than 200 mm. The
government of Djibouti is promoting an agro-pastoralist system to improve self-sufficiency, and it is necessary toestablish new agricultural land. In order to make this goal, it is needed to understand the current location
characteristics of farmlands and the potential of water resources in Djibouti. In this study, the location and area of
farmlands in 2010 and 2020 were first investigated using Google Earth and satellite image called ALOS AVNIR2. Next, wadis were created from a digital elevation model "AW3-DEM" using GIS software. The amount ofaccumulated water inflow into the wadis was calculated, and the wadis were classified into three classes: large,
medium, and small. Using these data, the relationship between topographic characteristics, such as altitude andslope where farmland is located, and wadi as water resources, was analyzed. As results, it was found that most of
the farmlands were distributed in areas with an altitude of less than 200 m and a slope of less than five degrees.
Regarding the distance between farmlands and wadis, it was shown that in the last decade the distribution has
increased in areas further away from large wadis. Farmlands in Djibouti were established to be more concentrated
in areas that are flat and close to densely populated areas.
Keywords: ALOS World 3D, Digital elevation Model, Hydrology Modeling, Wadi

INTRODUCTION

in Djibouti are mainly based on irrigation systems
using shallow groundwater from the Wadi. Therefore,
geographic proximity to the Wadi is an essential
location for agriculture in Djibouti. An agricultural
example in Djibouti is the successful agropastoral andsustainable farming of vegetables, orchards, andlivestock using shallow groundwater. In addition tothese successful examples, analysis of therelationship between location, water resource
environment, and farming conditions in many
farmlands operating in Djibouti is necessary toachieve the Ministry of Agriculture's goal of"designing new agricultural lands". However, in therural areas of Djibouti, the use of land is allowed by
the customary system, and the procedures foracquiring farmlands to the public organization are notcarried out. Therefore, it is not possible to obtainstatistical information on the location, size, and status
of farming operations used as farmlands. In order tobuild new farmlands, fundamental information isrequired on the current situation of the area and thelocation of farmlands all over Djibouti. It has also
been reported that the distribution of precipitation
period varies with altitude in Djibouti. Furthermore,
altitude and slope factors are also important from the
aspects of farmland establishment design and farming
operations. The objective of this study is to extractfrom satellite imagery, to clarify the geographicalcharacteristics of their location environment using
GIS, and to evaluate their agricultural potential
throughout Djibouti.

Djibouti, located in the "Horn of Africa" in thenortheast of the African continent, is situated at thenorthern end of the Rift Valley land area under adesert climate (Fig.1). Annual precipitation of
Djibouti is less than 200 mm which is a severe arid
condition. Most of the country is a desert surface
covered with basalt. There are no flowing rivers, so
only shallow groundwater from the Wadi area isavailable for agriculture, livestock, and domestic use.
Population is 974,000 as at 2019 [1]. In Djibouti, lessthan 1% of the population is engaged in agriculture
and about 25% is involved in the pastoral husbandry,
including nomadic pastoralism. Nomad people is
25% of the population, half of nomad is in southern
region of Djibouti. Pastoralism is only traditional andnon-commercial. The share of agricultural productionis less than 5% of GDP, and the food self-sufficiency
rate is only 13% in terms of production value. The
food self-sufficiency rate is only about 13% in terms
of production value. However, drought caused byrecent climate change has resulted in a shortage of
pasture grasses. The nomadic life has become moredifficult, and many nomads are currently in need ofadditional income, such as Gulf labor. To improve
this situation, the Djibouti government has developed
the Primary Industries Development Plan 2010-2020(PDDSP), which is designed to help rural nomads
augment their alternative income sources throughagriculture. Farming operations conducted by farmers
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SEE-Mie, Japan, Nov.10-12, 2022

In this study, a high-resolution DEM called
AW3D (ALOS World 3D) with a spatial resolution of
5 m, produced using satellite imagery taken by ALOS
PRISM, was used (Fig.2). The altitude of the Lake incentral Djibouti is -176 m, and the altitude of themountainous area on the border between Ethiopia andEritrea at the northern edge is about 2,020 m. The
country has an undulating terrain. The slope
distribution was calculated from this DEM asgeographical data for evaluating the location
environment (Fig.3). Relatively low slope throughout
Djibouti but appears to be steep in many areas in
Tadjourah Province.

Fig. 1 Location of Djibouti (six province) in Africa.
METHODOLOGIES
Data Collection of farmland sites in Djibouti
Many farmlands in rural Djibouti are surroundedby stone walls to protect crops from grazing livestockand hot winds. Farmlands were extracted fromsatellite image data by visually identifying thesefences as boundaries. ALOS AVNIR-2 imagery wasused to produce plantation polygon data for Djibouti
in 2010. The spatial resolution of AVNIR-2 imagery
was pan-sharpened to 2.5 m using ALOS
panchromatic imagery, as AVNIR-2 has a spatial
resolution of 10 m, which is insufficient for visualinterpretation of farmlands. Satellite imagery taken
between 6th October 2006 and 5th January 2011 wasused, although most areas in Djibouti were taken in2010.
Google Earth Pro was used for the 2018 polygon
data of farmland. Most areas were taken between
2018 and 2020, but some areas include imagery taken
in 2016.
The number of farmlands across Djibouti that
could be visually determined from Google Earth Pro
was 670, with a total area of 1090 ha. Compared to2010, the number of farmlands and the area of
farmlands increased. Compared to the other provinces,more farmlands were distributed in the three southern
provinces, which accounted for about 80% of the total
area. The density of farmlands in the eastern part ofAlta and the south-western region of Dhikil showed
the same trend in 2010 and 2020, and this trend waseven stronger in 2020. This farmland polygon datapreparation has been described in detail in previous
studies [2],[3].

Fig. 2 DEM (AW3D) in all of Djibouti

Digital Elevation Model
Satellite remote sensing by earth observation
satellites is effective for understanding wadi andwatersheds distributed over a wide area. One of theadvantages of satellite remote sensing is that wide
areas can be observed periodically, which may be
useful in the study area. Many studies have reported
the use of satellite remote sensing to extract
watersheds and wadis in arid regions [4], [5].

Fig. 3 Slope distribution from DEM in Djibouti.
Hydrological Modeling
Wadi means river or valley in Arabic. Generally,wadis only receive running water during heavy
547

SEE-Mie, Japan, Nov.10-12, 2022

rainfall, and usually have only a dry sand and gravel
covered riverbed. In Djibouti, which depends on
rainfall and is not able to store water, people use theshallow groundwater in wadis for their livelihoods
and for agricultural purposes. A river model (wadichannel) was calculated from the slope direction andaccumulated flow data using hydrological analysis in
ArcGIS Pro. The accumulated flow data were thenused to classify the threshold values for the numberof accumulated pixels (one pixel = 5 m) into threeclasses: more than ten thousand pixels, more than one
million pixels and more than three million pixels. The
wadi channels for each class were calculated anddefined as small, medium and large wadi classes,
respectively. The distribution of Wadi streams in eachclass is shown in Figure 4. The small and medium
wadi classes are approximately equally distributed
throughout Djibouti (Fig.4a, Fig. 4b). The large wadi
class was less distributed in the southern part of
Tadjoura province, which is at a relatively highaltitude (Fig.4c).

c) Large wadi

Fig.4 Wadi channel distribution in each class.
Medium and large wadi class lines are indicated bybold lines. a) Small wadi (Accumulated flow pixels
less than ten thousand), b) Medium wadi (less than
one million), c) Large wadi (less than three million)a) Small wadi

RESULTS AND DISCUSSIONS
Change of farmland area in Djibouti
The area of farms in each province in 2010 and2020 is shown in Table 1. Data on the location ofwells was used from the surveys conducted by FAO
in 2017. Between 2010 and 2020, the number offarmlands throughout Djibouti has twice and theirarea has increased by about 1.6 times. In 2010, thenumber of farmlands in Dhikil Province increased
from 354.3 ha (147 sites) to 388.2 ha (211 sites),accounting for about half of the total area of
farmlands in Djibouti. In 2020, the proportion of thearea of farmlands in Djibouti and nearby Arta, which
includes the capital Djibouti City, and, additionally,in Ali Sabieh and Tajurah provinces, increased. These
provinces are relatively well resourced in terms ofwater quality and water resources, such as wells.
Figure 5 shows the distribution of farmlands in2010 and 2020. The number of farmlands in 2020
appears to have increased, mainly in areas where
farmlands existed in 2010 throughout Djibouti. The
expansion of farmlands, particularly in the densely
populated surroundings of Djibouti City, which faces
the Gulf of Aden, has been significant. There was notendency for new farms to be established in 2020 inareas where no farms existed in 2010. Therefore,
geographical factors may have prevented theestablishment of new farms from the initial potential.

b) Medium wadi

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Table 1 Farmland area and water resource
information of each Province in 2010 and 2020.
ProvincenameArea(ha) in2010Area(ha) in2020

Area
increasingrate (%)

Numberof wellDjibouti

41.1

47.1

115

208

Arta

130.1

294.5

226

412

Ali-sabieh

78.2

193.9

248

324

Dikhil

354.3

388.2

110

337

Tadjourah

68.2

145.8

214

523

Obock

15.4

20.6

134

285

Total

687.3

1090.1

159

2089

Geographical characteristics of farmland in
Djibouti
The area of farmland by altitude class wascalculated for 2010 and 2020. The results showed thatin 2010 the maximum was between 200 m and 400 m,
while in 2020 the maximum was below 200 m, as
shown in Figure 6. It is considered that during thisperiod, farmlands were expanded to lower altitude
areas below 200 m. Most of the farmlands are locatedin lowland areas at altitudes below 400 m, althoughsome farmlands have expanded in the area between
400 m and 800 m in 2020.

(FAO, 2017)a) 2010

Fig.6 Altitude distribution of farmland in 2010 and2020.
Next, the area by slope class was calculated forthe years 2010 and 2020 as well. The results show thatin both periods, as shown in Figure 7, farmlands werelocated in areas with slopes of five degrees or below.
It was therefore assumed that the establishment offarmlands was restricted to areas with slopes of fivedegrees or below.

b) 2020

Fig.7 Slope distribution of farmland in 2010 and 2020.
From the above, it is considered appropriate toestablish farmlands in low and flat areas, but there ispotential for establishing farmlands at relatively highaltitudes if the slope degree is gently.

Fig.5 Farmland distribution in 2010 and 2020.
Symbols in the figure show the location of the
farmland.
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SEE-Mie, Japan, Nov.10-12, 2022

Finally Geographical proximity was further
investigated by calculating the Euclidean distance
between the farmlands and each wadi. In 2010 and
2020, areas with geographical proximity of 100 mfrom small wadis were selected as farmlands (Fig. 8).
For medium and large wadis, the distance between
wadi and farmland was more significant in 2020 thanin 2010, and the difference is more pronounced forlarge wadis. Therefore, it can be considered that in thelast decade, farmlands have been established in areas
far distance from the large wadis.
The above results indicate that the location
characteristics of the farmlands are low altitude andrelatively flat areas. It was also found that in the last
decade, farmlands have been established at a further
distance from large wadis.

Regarding the distance between farmlands andwadis, it was shown that in the last decade the
distribution has increased in areas further awayfrom large wadis.
It was found that farmlands are increasingly
being established in areas that satisfy the above
conditions.

ACKNOWLEDGMENTS
This research was supported by Science andTechnology Research Partnership for Sustainable
Development (SATREPS), Japan Science andTechnology Agency (JST) / Japan International
Cooperation Agency (JICA).
REFERENCES[1] United Nations.
https://population.un.org/wpp/Download/Standard/Population/ (Last access,4th Jul. 2022)[2] T. Sato. Farm extraction using deep learning withsatellite imagery in Djibouti. Tokyo University ofAgriculture, 2020, Master thesis.
[3] T. Sato, A. Sekiyama, S. Saito and S. Shimada.
Applicability of Farmlands Detection in Djibouti
from Satellite Imagery using Deep Learning.
International Journal of Arid Land Studies. 2022,
In press.
[4] C. Kessar, Y. Benkesmia, B. Blissag, L. Wahib
Kébir. Delineation of groundwater potential
zones in Wadi Saida Watershed of NW-Algeria
using remote sensing, geographic information
system-based AHP techniques and geostatisticalanalysis. Journal of Groundwater Science andEngineering. Vol. 9, Issue 1, 2021.pp.45-64.
[5] M. Abdekareem, N. Al-Arifi, F. Abdalla, A.
Mansour and F. El-Baz. Fusion of Remote
Sensing Data Using GIS-Based AHP-Weighted
Overlay Techniques for Groundwater
Sustainability in Arid Regions. International
Journal of sustainability. Vol. 14, Issue 13,2022. 7871; https://doi.org/10.3390/su14137871

Fig.8 Average distance from farmland to wadi ineach wadi class.

CONCLUSIONSIn this study, the geographical characteristics offarmlands in 2010 and 2020 were analyzed. Altitude,
slope and distance of farmland from wadis were
investigated. Wadis were analysed and classified
into three classes - large, medium and small according to the accumulated inflow of water. The
results of the analysis were as follows.
 Farmlands were distributed in areas with analtitude of less than 200 m and a slope of lessthan five degrees.

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8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

ENVIRONMENTAL IMPACTS ASSESSMENT OF REAL ESTATEPROJECT AT PALLABI EASTERN HOUSING AREA IN DHAKA
CITY, BANGLADESH*Md. Mahabub Alam1, Md. Soybur Rahman2, Alex Otieno Owino3, Abd Elmageed Atef 3, Md. Yachin
Islam3 and Zakaria Hossain3
1

Department of Environmental Science, State University of Bangladesh, Bangladesh
Department of Environmental Science, Bangladesh Agricultural University, Bangladesh
3
Department of Environmental Science and Technology, Mie University, Japan

2

ABSTRACT
Dhaka is the capital city of Bangladesh. A lot of people migrate every day. For their survival, the housing
sector is flourishing day by day. The demand impacts the supplies. A number of people are doing housingbusiness to support the situation. Still, on the contrary, they are grabbing a lot of green fields or water bodies
from private properties evacuating the owners. One of the ill examples is considered as Pallabi Eastern Housing
2nd Phase Project. The study is to find the socio-economic status of the land owners and local inhabitants whoare evicted from their land for the project. According to the primary observation and information collectedfrom different sources, approximately 350 families are relocated. Of the 45 relocated people placed undersurvey from the questionnaire survey by snowball sampling, it was found that most people were displaced fromtheir original location through the involuntary procedure. The income level, housing condition, and utility
facilities are worse off than before the resettlement. They are unaware of taking action against the developer
for the deprivation in the land price. The study discovered different aspects that clarified how land developers
exploited the local people. The four different actors, namely land developers, local musclemen, local officials,
and local people, were identified who actively played various roles in this relocation procedure. A few scopes
are identified to rehabilitate the victims to recover from their present situation. Government should adequately
care about the reallocated people to compensate at the current rate considering the long period of suffering.
There is scope for more intensive study on the topic.
Keywords: Housing sector, Socio-economic, Developer, Land, Government

1.

INTRODUCTION

Bangladesh is a developing country. Dhaka is
its capital city and the center of all main activitiesof the country, providing civic utilities. The realestate and housing sector of Dhaka City illustrates
the scenario of the real estate and housing situationof Bangladesh. The establishment of the real estatemarket in Bangladesh is hundred years old, but now
it has matured significantly another form of profit
earning campaign initiated by the developers is thetransformation of residential plots as well as flats
into commercial and business utilization which inturn putting pressure on the infrastructure, services,road network and creating greater environmental
impacts of Real Estate Projects in Dhaka City[4].
Although the plots of (EHL) Residential Area wereprimarily allocated for residential buildings with amaximum height limitation of 6 stories, most of thesingle houses are turning into high-rise residential
cum commercial apartments. In most cases, they do
not follow the setback rules and in other instances,violate the height restriction rules too. As a result,the increasing numbers of high rise commercial
buildings are making the area a high class slum
which in turn is causing the problems such as
dampness, shadow, disruption of airflow,

Bangladesh is a densely populated country.
About 25 percent of the population (35 million
people) live in urban areas. The urbanization
process is linked with economic development andcontributes to the national economy. Urbanization
and rapid urban change may be a negative sign ofdevelopment, provided urban problems arise due toimproper management and unplanned growth[1].
The increasing number of high rise commercial
buildings is making the area a high class slum,
causing problems such as dampness, shadow,
disruption of airflow, turbulence of airflow, etc.[2].
Land developers are converting low-lying areas aswell as agricultural land.
Consequently, land development companies
have a dominant force in the land market andsignificantly impact land development andplanning. Thus it is crucial to have a clear
understanding of the relocation process in the urban
fringe of Dhaka city due to private landdevelopment projects. This research also tried to
explore the socio-economic impact of relocation on
the locally affected people[3].
551SEE-Mie, Japan, Nov.10-12, 2022

turbulence of airflow, etc. [5].
The main objective of this research is to study
the environmental impact of Eastern Housing
Limited in Dhaka city. This research intends tofocus on the local people's relocation process andassess the relocated people's present and previous
socio-economic status. No work has been yet doneon the relocation of local people because of private
land development projects.

2.3 Data Analysis
After getting data from the field survey, theexisting documents were analyzed using MS Excel.
To the best of his knowledge, the researcher
avoided plagiarism and maintained high ethicalstandards in preparing this research paper.
3 RESULTS AND DISCUSSION

2.

METHODOLOGY
Every day, many people migrate to Dhaka City for
their livelihood. As a result, real estate activities are
increasing day by day. This study was conducted to
identify the environmental problem due to realestate projects in Dhaka City. The results of thisstudy have been presented and discussed under thefollowing headings.

2.1 Location of The Study
The study area is the Real Estate Project of Eastern
Housing Pallabi 2nd phase, Mirpur, athana of Dhaka city, Bangladesh. It is bounded
by Pallabi Thana to the north, Mohammadpur
Thana to the south, Kafrul to the east, and Savar
Upazila to the west.

3.1 Problem of outside labor in Real estate
Project
Data indicates that due to outside labor in the Realestate Project relocated people suffering 30(67%)
respondents and not suffering 15(33%)
respondents. Problems with outside labor strongly
relate to the improvement of real estate activities.
Maximum relocating people suffering with outside
labour issues in real estate project in Dhaka city[6].

Map 1: Eastern Housing Pallabi 2nd phase, Mirpur
33

2.2 Data Collection

67

Data were collected from both primary andsecondary sources to fulfill the research objectives.
According to an 80% confidence level andconfidence interval of 5, at least 50 questionnaires
needed to be surveyed. This research used snowball
sampling for the questionnaire survey. Snowball
sampling is also called network or chain sampling.
Residents of adjacent land development projects
were the main introducing section for snowball
sampling, and data were randomly collected fromthe field level. Secondary data included relevant
literature related to this research topic, including
published and unpublished thesis papers, study
reports, journals, books, newspaper magazines,
research
publications,seminarpapers,ordinance/policy, etc. Information on housing
projects was collected from RAJUK, REHAB,
offices of land developers, and advertisements
published in media and websites. The Internet wasanother informative source of secondary data usedin this report.

YES

NO

Fig. 1: Cause of Environmental Problem for real
Estate project3.2 Impact of Real Estate project in Land Value
Survey indicates that due to real estate project land
value increased 30 (67%) respondent and deceased
14 (31%) and not changed 01 (2%) respondentconfirmed the status. It is clear that continuous
constructing building has significant effect on theprice of land. Land price become more than twice
within 20 years due to real estate activities [7].
552SEE-Mie, Japan, Nov.10-12, 2022

Table 1: Increased or decreased of Land Value forReal Estate project
Chain Land Frequency
Present (%)
Value
Increased
30
67
Decreased
14
31
Unchanged
1
2
Total
45
100

16

3.3 Cause of Environmental Problems for Real
Estate Projects

84

The survey indicates that environmental impact isthere due to real estate projects. Problem 33 (77%)
respondent and No Problem 12 (23%) respondent
Confirm. It can be said that the environmental
problem has increased due to real estate projects.
Developing activities increase violations of humanrights, natural or human-made disasters, and othersocial problems [8].

YES

Fig. 3: Socio-economic impacts for Real Estate
project
3.5 Compensated from Real Estate Company forrelocated people
Data indicate that Compensated from Real Estate
Company for relocated people is given totally7(16%) respondent, No Compensated 13 (24%) andsame Compensated given 25 (59%) respondentconfirm. Real Estate Companies partiallycompensate the majority of relocating people. Less
than one-fourth of people don't get compensationfrom Real Estate Companies. It is a major challenge
for the City Development Authority (RAJUK) to
manage the urban spatial growth and to meet thegrowing population's demand with its limited
resource and maximum real estate company trying
to provide compensation for relocating people[10].

90
80
70
60
50
40

77

30
20
10

NO

23

0

Compensated

YES

NO

NO CompensatedSome CompensatedFig. 2: Cause of Environmental Problems for real
Estate project16%

3.4 Socio-economic Impact on Real Estate
Project

60%

Data indicates that Socio economics impact for Real
Estate project is happened 38 (84%) respondent andNo impact to 07 (16%) respondent. The resultclearly shows that almost all people suffer sociallyand financially from real estate projects. Land is theprimary source of livelihood for many living in thefringe areas. The poorest are often forced into
temporary settlements in urban fringe land. The
urban fringe poor depend to a greater extent onaccess to natural resources than wealthier, urbanbased groups [9].

24%Fig.4: Compensated from Real Estate Company forrelocated people

4.

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CONCLUSIONSSEE-Mie, Japan, Nov.10-12, 2022

Local people relocation is a complex issue. This
study has unfolded the procedure of local people
relocation in Dhaka City. Land developers with thehelp of local musclemen and local officials, used
many techniques to buy land from local people.
Both voluntary and involuntary procedures wereused for relocation. About 500 households relocatedbecause of the Eastern Housing limited land project.
Though this research outcome clearly shows thatmaximum local people were displaced from their
original location through the involuntary procedure.
This research also identified the socio-economic
condition of relocated people. The study shows thatthe overall socio-economic conditions of local
people are inferior compared with previous
locations, which ultimately supported social
researchers' opinion about the negative effect of
relocation. This study briefly recommends somebroad steps to consider for relocation issues. Good
governance is a prime consideration for fringe area
development. National Policy on Resettlement andRehabilitation should be implemented as soon as
possible to protect the land right of local people.

REFERENCES[1] Haial, G., "Rapidly Growing African Cities
Need to Adopt Smart Growth Policies to Solve
Urban Development Concerns," Urban Forum,
2008.
[2] Seraj, A.N., Climate Change Adaptationassessment: A Case Study of the Eastern Fringeof Dhaka, Bangladesh, MSc Thesis, Department
of Urban Management and Development,
Netherland, 2004.
[3] Tawhid, S., "Health Implications of Involuntary
Resettlement
andRehabilitationin
Developmental Projects in India", Society for
Health Education and Learning Packages,
Vol.01, New Delhi, India, 2010[4] Mahmud, Md. Akter., “Corruption in Plan
Permission Process in RAJUK: A Study ofViolations and Proposals,” Transparency
International Bangladesh, Dhaka, 2007.
[5] Arku, G., “Rapidly Growing African Cities
Need to Adopt Smart Growth Policies to Solve
Urban Development Concerns,” Urban Forum,
2009.
[6] Arman, M. S. B., and Alam, P. D. R.,"Sustainability of Development Trends in the
Urban Fringe: A Case Study on North-Eastern
Dhaka City," Protibesh, Volume 12, Issue 2 pp.
55-67 Dhaka, Bangladesh, 2018.
[7] Kabir, I., “Wetlands of Dhaka Metro Area: A
study from social, Economic & Institutional
perspectives,” A HDevelopment Publishing
House, Dhaka, Bangladesh. 2019.
[8] Lobo, L., and Kumar, S., “Land Acquisition,
Displacement and Resettlement in Gujrat: 19472004,” SAGE publication, Delhi, India, 2009.
[9] Clark, D. A. L., “Environmental Challenges toUrban Planning: Fringe areas, Ecological
Footprints and Climate Change. Key Challenges
in the Process of Urbanization in Ho Chi Minh
City,” Governance, Socio-Economic, andEnvironmental Issues, Vietnam, 2009.
[10] Masum,“Urban Fringe Management and Role
Of Good Governance: Integrating Stakeholders
in Land Management Process,” in 7th FIG
Regional Conference, Hanoi, Vietnam, 19-22
October 2009.

ACKNOWLEDGMENTS
At first, all praises belong to Almighty Allah,
the cherisher and sustainer of the world, whoallowed me to conduct this study. I express mygratitude to Khan Ferdousour Rahaman, Associate
Professor & Head, Department of Environmental
Science, State University of Bangladesh, for hiskind consideration of designing the approaches andmethodologies and his time-to-time suggestions,advice, and untiring efforts for the efficient
preparation of this paper. My special thanks to myfriend Md. Aminul Islam, Ebrahim Khalil, and the
Shanto Mariam University of Creative Technology
students for providing me with their valuable timeand Energy for my data collection at the field level.

554

8th Int. Conf. on Structure, Engineering & Environment (SEE),
Mie, Japan, Nov.10-12, 2022, ISBN: 978-4-909106094 C3051

SEASONAL VARIATION OF RESIDENTIAL INDOOR AIR QUALITYIN MYMENSINGH CITY, BANGLADESH
Md. Soybur Rahman1, Md. Mahabub Alam2, Alex Otieno Owino3, Abd Elmageed Atef3, Md. Yachin Islam3and Zakaria Hossain3
1

Department of Environmental Science, Bangladesh Agricultural University, Bangladesh
2
Department of Environmental Science, State University of Bangladesh, Bangladesh
3
Department of Environmental Science and Technology, Mie University, Japan
ABSTRACT

Indoor concentrations of PM2.5, PM10, TVOC, and CO2 were measured in winter and summer in 90 naturally
ventilated houses in three locations in Mymensingh city. Average indoor concentrations of PM2.5, PM10, TVOC,
and CO2 for all households in winter were (121.68 ± 50.28) μg/m3, (137.91 ± 57.69) μg/m3, (0.820 ± 8.0894)
μg/m3, (660.31±130.12) ppm. Summer average indoor concentrations were PM2.5 (86.753 ± 35.44) μg/m3, PM10(103.55 ± 38.90) μg/m3, TVOC (0.387 ± 0.0762) μg/m3, CO2 (581, 73 ± 78.50) ppm, and the results showed PM10
and PM2.5 experienced large seasonal variations, with air quality declining especially in winter. Average indoor
PM2.5 concentrations in Akua, Maskanda, and Town Hall were 70.96 μg/m3, 70.475 μg/m3, 95.85 μg/m3 insummer, and 130 μg/m3, 70.51 μg/m3, and 129.625 μg/m3, respectively in winter. The average PM10
concentrations in summer in the surveyed houses were 86.3612 μg/m3 in Akua, 78.77 μg/m3 in Maskanda, 128.077
μg/m3 in Town Hall, and 159.41 μg/m3, and 71, 78 μg/m3,170.225 μg/m3 in winter respectively. The average indoor
CO2 concentrations of the studied dwellings were 569.86 ppm (Akua), 547.1ppm (Maskanda), and 574.891ppm(Town Hall), respectively, during summer and 649.602 ppm, 629.133ppm, and, 724.76 ppm during the winterseason. This investigation found that the indoor PM10 and PM2.5 concentrations were notably higher than the
WHO guidelines in all selected dwellings throughout the two sample periods. In contrast, TVOC and CO2 values
were not exceeding the WHO guideline. Indoor pollutant concentrations were strongly dependent on ambientconcentrations due to increased ventilation rates in summer, with indoor sources influencing indoor concentrations
in winter due to increased human activity and poor ventilation.
Keywords: Indoor air, PM2.5, PM10, CO2, TVOC, Summer, WinterINTRODUCTION

indoors. Particles generated inside buildings can bereleased directly from indoor sources, known aselemental PM, or from chemical reactions of gaseous
precursors. For example, particles with aerodynamic
diameters below 10 µm, known as PM10, can beseparated into coarse particles of 2.5-10 µm in
diameter (PM2.5-10). A small fraction of fineparticles with aerodynamic diameters greater than 2.5
micrometers (PM2.5) often contain toxic substancesthat can penetrate deep into the lungs[5]. Thus, fineparticles increase morbidity and mortality from
respiratory and cardiovascular diseases[6]. Sources ofambient particulate matter generation in urban
environments include vehicle emissions, industrial
processes, construction activities, road dust frombrake wear and tire washing, particulate reactivation,and road transport[7].
Carbon dioxide (CO2) is mainly produced by
combustion and human metabolism. As a result, CO2concentrations are higher in indoor residential
environments than in outdoor environments[8].
Recent trends in building design, including
improving air tightness and reducing building

Indoor air quality (IAQ) is a fundamental issue
that is receiving increasing attention in bothdeveloped and developing countries as people spend
almost 90% of their time indoors and a higher
proportion of household expenditure[1]. Sensitive
groups such as the elderly and children may be
indoors all day and be at greater risk due to their
exposure to many indoor air pollutants from various
indoor and outdoor sources[2]. Indoor air quality(IAQ) is strongly influenced by many factors,
including indoor emission sources, building
characteristics (including design and ventilation), andoutdoor air quality. Most indoor air pollutants cancause respiratory and cardiovascular problems. The
severity of their effects depends on their toxicity,
concentration, duration of exposure, and the health ofthe people exposed to them [3].
Particulate matter (PM) is an essential air
pollutant associated with indoor and outdoor healtheffects[4]. PM comprises particles that were
penetrated from outdoor sources and those generated
555

SEE-Mie, Japan, Nov.10-12, 2022

ventilation rates to save energy and mitigate climatechange, can reduce indoor air quality and increase
CO2 emissions[9]. Indoor CO2 concentrations indicate
whether the rate of outdoor air entering a room issufficient to dilute indoor air pollutants [10]. Recent
trends in building design, including improving air
tightness and reducing building ventilation rates tosave energy and mitigate climate change, can reduce
indoorair
qualityandincrease
CO2emissions[11][12]. Indoor CO2 concentrations
indicate whether the rate of outdoor air entering aroom is sufficient to dilute indoor air pollutants [13].
There are different classifications of Total Volatile
Organic Compounds (TVOC). The most common
definition is that of the World Health Organization(WHO), which characterizes the volatility (or boilingpoint) of organic compounds to identify volatileorganic compounds (VOCs) and semi-volatileorganic compounds (VOC). It is generally related tothe molecular length of the carbon skeleton. The sumof all VOCs is called total volatile organic
compounds (TVOCs). VOCs are ubiquitous both
outdoors and indoors. Depending on the design anduse, the room may simultaneously be contaminatedwith different organic compounds. The World HealthOrganization (WHO) presents guidelines onprotecting public health from the risks posed bycertain chemicals commonly found in indoor air[14].
IAQ data are generally scarce in Mymensingh city,and the problem is less understood. There is currently
a lack of research studies in Mymensingh toinvestigate IAQ in urban homes. Therefore, thecurrent work aims to estimate seasonal variations in
the quality of indoor air in a number of residential
dwellings of Mymensingh during the winter andsummer seasons.

METHODOLOGY
Location of the study area
The present study was conducted in several locations
in Mymensingh city, Bangladesh. Mymensingh is
located on the bank of the Brahmaputra River, about
120 km north of the national capital Dhaka; it is amajor financial center and educational hub of northcentral Bangladesh.
Sample collection
Indoor air samples of PM10, PM2.5, TVOC, and CO2
were taken from 90 houses located in a dense urban
and commercial residential area. Air sampling was
carried out in two measurement periods
1. Winter (January to February/2022) and2. Summer (June to July/2022).
Sampling sites were all private apartments situated at
different distances from high-traffic routes. A typicalarchitectural design of residential buildings in the city
providing living rooms with balconies is an essential
source of natural ventilation. Outdoor air samples
were taken just outside the living area. Indoor andoutdoor air measurements of PM10, PM2.5, TVOC,
and CO2 were taken, followed by calculating the
average values. This included the condition and ageof the building, the ventilation pattern, the size of theliving area, the number of occupants, the number ofsmokers, the frequency of cleaning and cooking, andany potential factors.
Indoor and outdoor temperature, RH, and CO2 levels
were monitored simultaneously using portable QTrak monitors (BENTECH GM8802). Indoor andoutdoor concentrations of PM10 and PM2.5 and Total
Organic
Carbon (TVOC)
weremeasuredsimultaneously in each home using Lighthouse
Handheld 3016 IAQ.
BENTECH GM8802

Handheld 3016 IAQ

Data analysis
All descriptive statistics and statistical analyzes ofthe data were performed using the Statistical Package
for the Social Sciences (SPSS) for Windows (version
20.0, SPSS, Inc., NY, USA).

Fig. 1 Location of the sudy556

SEE-Mie, Japan, Nov.10-12, 2022

RESULTS AND DISCUSSION

average outdoor PM10 concentrations of examinedhouses were 73.95μg/m3 for Akua, 82.8066 μg/m3 forMaskanda,
and127.27μg/m3
Town Hall,
respectively, in the summer season and 147.35μg/m3,
82.805 μg/m3, 138.092 μg/m3 in the winter season.

The mean indoor and outdoor levels of measured
air pollutants (PM10, PM2.5, CO2, and TVOC) for all
households in the three study areas in the two
sampling periods under investigation are shown.

b.

a.

PM2.5
Daily mean PM2.5 concentrations measured at all
residential sites in Mymensingh were relatively high,varying from 55 to 186 μg/ m3. Outdoor PM2.5
concentrations measured outside the studied
apartment reached as high as 60 to 172 μg/m3.PM2.5
concentrations in three study areas showedremarkable variation in summer and winter except for
the Maskanda area in indoor and outdoor air. Many
studies across different countries have surveyed,
identiﬁed, and quantiﬁed PM in residential areas in
the United States, reporting an average concentrationof 10.8 μg/m3.
Birmingham, UK, found a valueof 7.9 μg/m3. Concentrations of PM2.5 display wintermaxima concluded that indoor and outdoor PM2.5
levels increased from rural to urban to roadsideenvironments[15].

Fig.1 Box plots for indoor (a) and outdoor (b) PM10
concentrations in the selected areas of Mymensinghcity [Lines across each box indicate the median value,box edges represent the 25th and 75th percentiles, andvalues outside this percentile range are shown as
black dots].
Carbon dioxide (CO2)a.

b.
The average indoor CO2 concentration of examinedhouses was 569.86 ppm (Akua), 547.16 ppm(Maskanda), and 574.891 ppm (Town Hall),respectively, in the summer season and 649.602 ppm,
629.133 ppm, 724.76 ppm in the winter season. The
average outdoor CO2 concentrations of examinedhouses were 495.03 ppm (Akua), 494.954 ppm(Maskanda), and 636.4 ± 110.61 ppm ( Town Hall),respectively, in the summer season and 553.99 ppm,
568.51 ppm, 633.4 ppm in the winter season.

Fig.1: Box plots for indoor (a) and outdoor (b) PM2.5
concentrations in the selected areas of Mymensinghcity [Lines across each box indicate the median value,box edges represent the 25th and 75th percentiles, andvalues outside this percentile range are shown as
black dots].

a.

b.

PM10
Daily mean PM10 concentrations measured at all
residential sites in Mymensingh were relatively high,varying from 65 to 215 μg/ m3. Outdoor PM10
concentrations measured outside the studied
apartment reached as high as 70 to 165 μg/m3. The
average indoor PM10 concentrations of examinedhouses were 86.3612 μg/m3 for Akua, 78.77 μg/m3 forMaskanda, and 128.077 μg/m3 for Town Hall,
respectively in summer season and 159.41 μg/m3,
71.78 μg/m3, 170.225 μg/m3 in the winter season. The

Fig.3 Box plots for indoor (a) and outdoor (b) CO2
concentrations in the selected areas of Mymensinghcity [Lines across each box indicate the median value,box edges represent the 25th and 75th percentiles, andvalues outside this percentile range are shown as
black dots].

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SEE-Mie, Japan, Nov.10-12, 2022

Total Volatile Organic Compound (TVOC)

range of 0.79–1.58 and median: 1.1 for CO2, 1.05
with a range of 0.86–1.42 and median: 1.01 for PM10,
0.981 with a range of 0.71–1.48 and median: 0.98 forPM2.5 and 1.31 with a range of 0.86–1.49 andmedian: 0.98 for TVOC.

100% TVOC concentrations in all selected houses
were below 0.6 μg/m3. TVOC concentration of 0.3
mg/m3 is considered a low TVOC concentration
value; values between 0.3 μg/m3 and 0.5 μg/m3 areacceptable (Airmax IOT blog, 2020). TVOC
concentrations in the Akua region showed the mostsignificant variation between summer and winter due
to the different types of lifestyles, building structures,
people's behaviors, and mixed cultures in theresidential area of Akua. The study area of Muskanda
is a sparsely populated, rural city with less variability
in indoor TVOC, and indoor TVOC concentrations
were lower in winter than in summer (Figure 4.3.4.1).
After all, the Town hall Hall is where cultural events,
trade fairs, political meetings, events, andperformances occur, and it was higher than the twostudy locations. Formaldehyde and TVOC emissions
from dry and wet building materials. We found thattemperature and relative humidity significantly
affected emissions, with formaldehyde emissions
being much higher in summer than in winter [16].

a.

Fig.5 Box plots for indoor-outdoor ratios of air
quality in the study area [Lines across each box
indicate the median value, box edges represent the25th and 75th percentiles, and values outside thispercentile range are shown as black dots].

b.

Toxicity Potential (TP) for PM2.5 and PM10
Toxicity Potential (TP) =𝐂𝐩⁄𝐒𝐩

Where Cp is the observed concentration of thepollutants and Sp is the usual recommendation valueof 25 μg/m3 for PM2.5 and 50 μg/m3 for PM10
(WHO 2006).
Table 1 TP PM10 and TP PM2.5 values in the threeselected areas throughout the winter and summer
seasons.

Fig.4 Box plots for indoor (a) and outdoor (b) TVOC
concentrations in the selected areas of Mymensinghcity [Lines across each box indicate the median value,box edges represent the 25th and 75th percentiles, andvalues outside this percentile range are shown as
black dots].

Pollutants

TP

PM2.5

4.52

PM10

3.01

Indoor/outdoor ratios
A TP value of more than 1 suggests a possible healthrisk of the specified pollutant in a given location.
Table 1 exhibits TP PM10 and TP PM2.5 values
throughout the winter and summer seasons in thethree selected areas where TP values are more thanone, suggesting a possible health issue [17].

Indoor concentrations were compared with thoseoutdoors using I/O ratios. I/O ratios obtained for eachresidence in the 90 houses are presented in Fig. 5. The
average I/O ratios for all sample sites throughout thesummer season were 1.13 with a range of 0.74–1.39,
and median: 1.13 for CO2; 1.12 with a range of 0.79–
3.37 and median: 0.94) for PM10, 0.94 with range
0.57–1.59 and median: 0.96 for PM2.5, and 1.09 withrange 1.01–1.47 and median: 1.12 for TVOC during
the summer season. During the winter season, theaverage I/O ratios at all sample sites were 0.96 with a

CONCLUSIONS
Indoor and outdoor concentrations of PM10, PM2.5,
TVOC, and CO2 were measured simultaneously in 90
naturally ventilated urban homes (25 homes were
supplied with AC) at three selected study sites in
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SEE-Mie, Japan, Nov.10-12, 2022

Mymensingh city during the winter and summer
season. This study revealed that the indoor PM10 andPM2.5 concentrations were noticeably higher than the
WHO guidelines in all selected homes during the two
sampling periods. For indoor TVOC and CO2 levels,none of the values exceeded the WHO guideline andthe ANSI/ ASHRAE Standard 62.1, respectively,
even though both TVOC and CO2 were very suitablefor indoor air quality. The toxicity potential ofparticulate matter was 3 to 4 times higher, causing
concern that particulate matter exposure can lead tomultiple adverse health effects. The winter season
had a higher PM2.5 concentration within the houses
than in the summer. However, the average PM2.5
concentration inside different places (balcony,
kitchen, living room) of homes was remarkably
similar in each season. PM2.5 and PM10
concentrations in the three study areas showedremarkable variation in summer and winter except for
the Maskanda area in indoor and outdoor air. Finally,
the total volume of indoor air quality in the study area
was satisfying for the indoor environment. According
to the air quality index, particulate matter
concentrations were unhealthy, and TVOC and CO2
concentrations were fine.

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ACKNOWLEDGMENTS
The author feels glad to pay his heartiest respect, mostprofound gratitude, and cordial thanks to all course
teachers of the Department of Environmental Science,
Bangladesh Agricultural University, Mymensingh,and others who directly or indirectly helped complete
this paper by giving valuable advice, suggestions, andco-operation.
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