Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Proceedings of the Transportation Research Congress 2016 Transportation Research Congress 2016 Innovations in Transportation Research Infrastructure Beijing, China June 6–8, 2016 EDITED BY Linbing Wang, Ph.D.; Jianming Ling, Ph.D.; Pan Liu, Ph.D.; Hehua Zhu; Hongren Gong; and Baoshan Huang, Ph.D., P.E Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved TRANSPORTATION RESEARCH CONGRESS 2016 INNOVATIONS IN TRANSPORTATION RESEARCH INFRASTRUCTURE PROCEEDINGS OF THE TRANSPORTATION RESEARCH CONGRESS 2016 June 6–8, 2016 Beijing, China SPONSORED BY China Research Institute of Highway Tongji University Southeast University Harbin Institute of Technology Chang’An University University of Science and Technology Beijing Construction Institute of the American Society of Civil Engineers EDITED BY Linbing Wang, Ph.D Jianming Ling, Ph.D Pan Liu, Ph.D Hehua Zhu Hongren Gong Baoshan Huang, Ph.D., P.E Published by the American Society of Civil Engineers Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Published by American Society of Civil Engineers 1801 Alexander Bell Drive Reston, Virginia, 20191-4382 www.asce.org/publications | ascelibrary.org Any statements expressed in these materials are those of the individual authors and not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein No reference made in this publication to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by ASCE The materials are for general information only and not represent a standard of ASCE, nor are they intended as a reference in purchase specifications, contracts, regulations, statutes, or any other legal document ASCE makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor The information contained in these materials should not be used without first securing competent advice with respect to its suitability for any general or specific application Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents ASCE and American Society of Civil Engineers—Registered in U.S Patent and Trademark Office Photocopies and permissions Permission to photocopy or reproduce material from ASCE publications can be requested by sending an e-mail to permissions@asce.org or by locating a title in ASCE's Civil Engineering Database (http://cedb.asce.org) or ASCE Library (http://ascelibrary.org) and using the “Permissions” link Errata: Errata, if any, can be found at https://doi.org/10.1061/9780784481240 Copyright © 2018 by the American Society of Civil Engineers All Rights Reserved ISBN 978-0-7844-8124-0 (PDF) Manufactured in the United States of America Transportation Research Congress 2016 iii Preface Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation infrastructure plays a critical role in the economic development of a country and the daily life of everybody Transportation researchers and engineers have always been making efforts towards the ambition of sustainable, smart and resilient transportation The recent years have seen numerous innovations in transportation materials, design, testing and characterization, construction, operation, maintenance and rehabilitation This ASCE Special Technical Publication contains sixty-eight fully-reviewed papers, covering the topics of pavement materials, pavement structures, geotechnical engineering, and bridge engineering These papers were presented at the inaugural meeting of the Transportation Research Congress (TRC) held at the National Convention Center, Beijing, China, June 6-8, 2016 The TRC is jointly organized by universities, research institutes, industries, and China Highway and Transportation Society TRC is intended to serve as an international platform for researchers, educators, practicing engineers, investors, entrepreneurs, and government officials in transportation infrastructure from all over the world At TRC, experts will present the latest research findings, exchange research ideas, share experiences and lessons learned, showcase successful innovations and practice, identify research and educational needs and provide consultations to transportation community on a regular basis Section Materials Twenty-seven papers are included in this section, covering mix design, testing, characterization and modeling of asphalt, cementitious, and base pavement materials Various sustainable materials, novel testing and modeling methods, and different material properties and performance characteristics are involved Section Pavement Structure Seventeen papers cover the response and long-term performance of asphalt and concrete pavements under traffic and different climatic conditions Different preventive maintenance and rehabilitation strategies are also provided Section Geotechnical Engineering Twenty-three papers offer the latest research on the construction and behavior of tunnels, deep foundations, deep excavations, special foundations and geologies Section Bridge Engineering Two papers provides the advances in the technologies of energy harvest from bridges and health monitoring system of bridges © ASCE Transportation Research Congress 2016 iv Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved All papers published in this ASCE Special Technical Publication were evaluated by at least two reviewers as well as the editors All comments were adequately addressed by the authors of these accepted papers In addition, all published papers are eligible for discussion in the Journal of Materials in Civil Engineering or Journal of Transportation Engineering and can also be considered and recommended for ASCE paper awards The editors would like to thank all the authors who have submitted their papers to the inaugural meeting of TRC Thanks also go to many reviewers for their time and efforts The editors are appreciative to Laura Ciampa and Katerina Lachinova from the ASCE Construction Institute (CI), and Donna Dickert from the ASCE Publications for their great support in approving and scheduling the publication of this proceeding Editors Linbing Wang, Virginia Polytechnic University Jianming Ling, Tongji University Pan Liu, Southeast University Hehua Zhu, Tongji University Hongren Gong, University of Tennessee Baoshan Huang, University of Tennessee © ASCE Transportation Research Congress 2016 v Contents Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Materials Research on Moisture Susceptibility of Asphalt Mixture Based on Surface Energy Theory Yu Sun and Lihan Li Analysis on Moisture Susceptibility of Warm Mix Asphalt Affected by Moist Aggregate and Multiple Freeze-Thaw Cycles 12 Jie Ji, Peng Zhai, Zhi Suo, Ying Xu, and Shi-Fa Xu Properties and Performance Evaluation Index of Lateritic Gravel from Mali in West Africa .22 Gengzhan Ji, Jinsong Qian, and Guoxi Liang The Effect of Material Composition on Abrasive Resistance of Pavement Concrete 31 Ping Li, Ying Li, Lingyi Kong, Feili Pan, and Qiumin Wang Investigation on Inherent Anisotropy of Asphalt Concrete Due to Internal Aggregate Particles 39 J Chen, Y Kong, H Wang, Y Chen, and J Liu Evaluation of Rejuvenator on Softening, Toughness, and Diffusion Ability for Lab-Aged SBS Modified Asphalt 49 Zhen Wang, Zhen Li, Gen Li, Hao Liu, and Liying Yang Research of Marshall Test Evaluation Method Based on Anti-Cracking Material 61 Li Liu, Zhaohui Liu, Sheng Li, and Yu Xiang Preliminary Study of Using Spent Fluid Catalytic Cracking (FCC) Catalyst in Asphalt 69 Jianming Wei, Yanan Li, Meng Xu, Xingong Zhang, and Yuzhen Zhang Law and Corresponding Relationship between TFOT and PAV of Asphalt 82 Guizhao Li, Yelong Feng, Yuzhen Zhang, Cheng Liu, Fuqiang Dong, and Yuchao Lv Nanomaterials in Civil Engineering: A State-of-the-Art Review 88 Lei Gao, Ren Zhen, Xiangjuan Yu, and Keyi Ren The Influence of Foaming Water Content on the Aging Characteristic of Foamed Warm-Mix Asphalt .98 Fuqiang Dong, Xin Yu, Xingmin Liang, Shengjie Liu, Gongying Ding, and Bo Xu © ASCE Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Cement Asphalt Mastic Dynamic Mechanical Properties and Microstructure Research 106 Yunliang Li, Menglong He, Jiuye Zhao, Shanshan Wang, Lun Ji, Ouyang Jian, and Yiqiu Tan Laboratory Test of Expansive Soil Improved by Lime–Basalt Fiber Reinforcement 120 Yuehua Wang, Shu Sun, Wei Ye, Fulin Li, and Hanfei Ding Laboratory Research on Fatty Acid Based Biobinder as an Addition for Crumb Rubber Modified Asphalt 127 Jiayun Zhang, Gang Xu, Minghui Gong, and Jun Yang Dynamic Shear Modulus Prediction of Asphalt Mastic Based on Micromechanics 141 Naisheng Guo, Zhichen Wang, Zhanping You, and Yinghua Zhao Creep Instability Rules of Asphalt Mixture Based on Compression-Shear Fatigue Test 156 Junxiu Lv, Xingyu Gu, Xiaoyuan Zhang, and Yiqing Dai Concrete Strength Monitoring Based on Piezoelectric Smart Aggregates 165 S Yan, J Chen, and W Sun The Influence of Mixing Temperature on the Performance of Hot In-Plant Recycled Asphalt Mixture 173 Xuchang Ying and Songlin Ma Asphalt-Aggregate Interface Failure Mechanism and Its Characterization Methods .182 Xin Qiu, Shanglin Xiao, Qing Yang, and Xiaohua Luo Experimental Study on the Effect of Steel Slag Powder and Fine Steel Slag on the Performance of Asphalt Mixture 195 Bangwei Wu, Liping Liu, Guowei Liu, and Yanjin Feng Study on the Properties of Waterborne Polyurethane Modified Emulsified Asphalt 207 Dongwei Cao, Yanjun Zhang, Lei Xia, Yingfu Li, and Haiyan Zhang Influence of CWCPM on the Mechanical Property of Cement Stabilized Aggregate 216 Cuizhen Xue, Aiqin Shen, Tianqin He, and Zhenghua Lv Application of 3D Fractal Dimension in Describing Surface Morphology of Aggregates 225 Lingjian Meng, Yue Hou, Zhenyu Qian, Linbing Wang, and Meng Guo © ASCE vi Transportation Research Congress 2016 vii Experimental Research on Mix Design and Pavement Performance for Special Basalt Fiber Reinforced OGFC Asphalt Mixture 233 Xudong Zha, Jieyuan Deng, and Chengjian Zhang Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Design and Text Method of Indoor Noise for Micro-Surfacing Mixture .242 Zhen Li, Hao Liu, Yuming Dong, and Zhen Wang The State-of-the-Art of Multiscale Mechanical Modeling Methods for Hydrated Cement Concrete 251 Wenjuan Sun, Yue Hou, and Linbing Wang Effect of Aggregate Mineral Composition on Polish Resistance Performance 263 Zhenyu Qian, Jiangfeng Wu, Fengyan Sun, and Linbing Wang Pavement Structure Preventive Maintenance Decision Making of Asphalt Pavement Based on Fuzzy Comprehensive Evaluation Method 272 Xiaoshan Liu, Haichen Yu, and Haiyao Miao Public Transport Choice Behavior Model of Short Trip under the Subtropical Climate 280 Jianmin Xu, Xiaoran Qin, and Yingying Ma The Long Term Service Performance of Non-Slip and Noise Reduction Asphalt Pavement Followed Up and Observed in the Southern Climates 291 Xian-Ping Tang, Wen Yi, Xian-Feng He, and Bo Yao Research on Pavement Materials and Innovations in Intelligent Transportation Systems 299 Shanglin Song, Linbing Wang, Meng Guo, Yue Hou, Zhoujing Ye, and Qian Zhao A Brief Review for SMA Pavements in China 305 Meng Guo, Yiqiu Tan, Xuesong Du, Rui Wen, and Ming Zhang Environmental Impacts of Different Maintenance and Rehabilitation Strategies for Asphalt Pavement 312 Bingye Han, Jianming Ling, and Hongduo Zhao Numeric Analysis of Basalt Fiber Reinforced Concrete Pavement .323 Yiqing Dai, Zhenyi Wang, Junxiu Lv, and Xingyu Gu Mechanical Response Analysis of Asphalt Concrete Overlay Placed on Asphalt Pavement Considering Cross-Anisotropic Pavement Materials .333 Yingbin Hu, Kezhen Yan, and Lingyun You © ASCE Transportation Research Congress 2016 viii Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Incorporating Life Cycle Science into Asphalt Pavement Maintenance Decision Making 341 Haoran Zhu, Haiquan Cai, Jinhai Yan, Hao Li, and Hui Li Long-Term Performance Study of Long Life Pavement Pilot Section in Jiangsu, China 353 Aihua Liu, Hao Li, and Peng Zhang Research on Influencing Factors for Permanent Deformation of Soil Base of Low Embankment Highway 364 Wei-Zhi Dong and Fu Zhu Prototype Modeling of Pile-Type Piezoelectric Transducer for Harvesting Energy from Vehicle Load 374 Yanliang Niu, Hongduo Zhao, Xueqian Fang, and Yujie Tao Real-Time Monitoring System and Evaluation Method of Asphalt Pavement Paving Temperature Segregation 383 Lili Zhang, Yan Shi, Zhiqiang Zhao, and Peng Zhang Study on the Long-Term Performance of Subgrade Structure Considering Environmental and Climatic Factors .396 Yanbin Ruan, Bin He, and Wanping Wu Research on RLWT and APA Rutting Loading Mode Based on Digital Image Technology 400 Cheng Wan, Qiang Yi, Bin Yang, Ke Xu, Yongjun Meng, and Hongliu Rong Self-Powered Intelligent Monitoring System for Transportation Infrastructures 409 Linbing Wang, Zhoujing Ye, Yue Hou, Hailu Yang, and Xinlong Tong Highway Geometric Design for Mountainous Regions Considering the Vehicle-Road Coupling Factors 420 Lei Yue, Yuchuan Du, and Hongyun Yao Geotechnical Experiment Study on Tunnel Crown Collapse and the Bolt Anchoring Effect in Weak and Broken Rock Mass 430 Q W Xu, W T Wang, P P Cheng, H H Zhu, and W Q Ding Study on the Optimization of Underground Continuous Wall Embedded Depth of the Super Large Pit 438 Jiabing Yao, Jiangshan Fu, Xin Xu, and Shimin Wang Studies of the Effect of Seasonal Temperature Change on a Circle Beam Supporting Excavation 446 Chang Liu, Yan-Po Liu, Gang Zheng, and Ya-Long Zhang © ASCE Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Finite Element Analysis on the Influence of Unloading Effect and Rebound Effect on Load and Settlement of Single Pile 463 Chang Liu and Deqiang Guo Research of Prediction Method on Geology Faults of Karst Area in Southwest of Guangxi Province 472 Haibo Yao, Weidong Lv, Yansheng Geng, and Fan Wang Centrifuge Modeling of Geosynthetic-Encased Stone Columns in Soft Clay under Embankment 486 Liangyong Li, Jianfeng Chen, Cao Xu, and Shouzhong Feng The Preparation and Properties of New Subgrade Replacement Material in Discontinuous Permafrost Zone 496 Dongfeng Chen, Chunyu Zheng, Jinsong Qian, and Dongxue Li Influence on High-Speed Railway Bridge Caused by Shield Tunneling in Sandy Pebble Stratum and Its Controlling Technologies 507 Panpan Cheng, Qianwei Xu, Guyang Li, and Xiaoliang Li Effect of Subway Tunnel Excavation by Drill-Blasting Method on Pipeline .521 Yongyan Yu, Yongtao Gao, and Zijian Du Experimental Study on Dynamic Characteristics and Associated Influencing Factors of Saturated Sand 530 Xiangjuan Yu, Zhen Ren, and Lei Gao Research on Mechanical Properties of Existing Station Structure While Diaphragm Wall Is Demolished during Construction 537 Xingzhu Shen, Qiang Qi, Quanxia Yang, and Shimin Wang Research about Effect of Defects of Filled Layer in Inverted Arch on the Deep-Buried and Heavy-Haul Railway Tunnel Structures and Its Reinforcement Measures 545 Shimin Wang, Qingyang Yu, Xingzhu Shen, Xiangfan He, and Jiabing Yao Three-Dimensional Calculation on Vertical Soil Displacement of Shield Tunnel Induced by Ground Loss Considering Consolidation .553 Wenjun Zhang, Mingming Jin, Huayang Lei, Heng Kong, and Caixia Guo Research on Optimization of the Stratum Reinforcement Scheme When Shield Tunnel Crossing the Fault Fracture Zone 569 Xiangfan He, Hongzhao Feng, Feng Gao, and Shimin Wang Stratigraphic Classification Based on the Evaluated Difficulty of the Construction by Using Shield Tunneling Machine 577 Mengbo Liu, Shaoming Liao, Longge Xiao, and Chihao Cheng © ASCE ix 682 caused by the road irregularity is close to the natural frequency of the harvester The most energy can be harvested at present situation As the irregularity length increases to 1.31 m, the frequency caused by the road irregularity is close to the second frequency of the bridge The second mode of the bridge plays the main contribution in the energy harvesting The harvester at L / can harvest the most energy, and two peak values can occur due to the moving vehicle The energy harvested has little influence for the harvester location at L / When the irregularity length is around 5.23 m, the load frequency is close to the first frequency of the bridge, the energy harvested reach their peak values at the same time The harvester at the mid-span can harvest the most energy The necessary minimum energy of the wireless sensor network node in a working cycle is 12.85 mJ (Li et al., 2014) An appropriate designed piezoelectric energy harvester can be used as a power source for wireless sensor 1000 100 Energy [mJ] Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 10 x0  L / 0.1 x0  L / x0  L / 0.01 20 40 60 80 Velocity [m/s] 100 120 Figure Vehicle velocity influence on energy harvesting Figure Road irregularity length influence on energy harvesting CONCLUSIONS Piezoelectric energy harvesting from bridge vibration has been investigated in this work The bridge was modeled as a simply supported beam based on Euler–Bernoulli theory The electrical output of the piezoelectric energy harvester was derived Position of the harvester, resistance in © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 the circuit, vehicle velocity and road irregularity were analyzed to investigate influences on energy harvesting Numerical results indicated that vehicle velocity and road irregularity both have influences on the energy harvesting When the frequency caused by the road irregularity is equal to the n-th natural frequency of the bridge The n-th mode plays an important contribution to the energy harvesting Higher energy can be harvested for the harvester installed at one of these points where the mode shape reaches the maximum values In the energy harvest circuit, a particular resistance exists, which can lead the harvester harvest the most energy For a certain road irregularity, the vehicle velocity has a significant influence on the energy harvesting When the frequency caused by the road irregularity is close to the natural frequency of the harvester, the energy harvested reaches to peak value An appropriate designed piezoelectric energy harvester can be used in the certain bridge The natural frequency of the harvester can approach to the frequency of the vehicle moves across the bridge An energy management system needs to be designed, which include the energy storage and account for the health monitoring system to be powered ACKNOWLEDGMENTS This work is supported by the National Natural Science Foundation of China (51522803), the Fundamental Research Funds for the Central Universities (2015YJS123), the Program for New Century Excellent Talents in University (NCET-13-0658), and Beijing Higher Education Young Elite Teacher Project (YETP0565) REFERENCES Ali SF, Friswell M and Adhikari S (2011) "Analysis of energy harvesters for highway bridges." J Intell Mater Syst Struct 22: 1929-1938 Anton SR and Sodano HA (2007) "A review of power harvesting using piezoelectric materials (2003–2006)." Smart Mater Struct 16: R1-21 Cahill P, Nuallain NAN, Jackson N, Mathewson A, Karoumi R and Pakrashi V (2014) "Energy Harvesting from Train-Induced Response in Bridges." J Bridge Eng 19: 04014034 Cheng Y, Au F, Cheung Y and Zheng D (1999) "On the separation between moving vehicles and bridge." J Sound Vib 222: 781-801 Chopra AK (2012) Dynamics of Structures Upper Saddle River: Prentice Hall Elvin NG, Lajnef N and Elvin AA (2006) "Feasibility of structural monitoring with vibration powered sensors." Smart Mater Struct 15: 977-986 Kaur N and Bhalla S (2014) "Combined Energy Harvesting and Structural Health Monitoring Potential of Embedded Piezo-Concrete Vibration Sensors." J Energy Eng 141: D4014001 Kim HS, Kim JH and Kim J (2011a) "A review of piezoelectric energy harvesting based on vibration." Int J Precis Eng Manuf 12: 1129-1141 Kim SH, Ahn JH, Chung HM and Kang HW (2011b) "Analysis of piezoelectric effects on various loading conditions for energy harvesting in a bridge system." Sens Actuator A: Phys 167: 468-483 Leger P, Ide I and Paultre P (1990) "Multiple-support seismic analysis of large structures." Comput Struct 36: 1153-1158 Li P, Wen Y, Yin W and Wu H (2014) "An upconversion management circuit for low-frequency vibrating energy harvesting." IEEE Trans Ind Electron 61: 3349-3358 Li Y and Shi RH (2015) "An intelligent solar energy-harvesting system for wireless sensor networks." EURASIP J Wirel Commun Netw 2015: 1-12 © ASCE 683 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 Park JW, Sim SH and Jung HJ (2014) "Wireless displacement sensing system for bridges using multi-sensor fusion." Smart Mater Struct 23: 045022 Peigney M and Siegert D (2013) "Piezoelectric energy harvesting from traffic-induced bridge vibrations." Smart Mater Struct 22: 095019 Tan YK and Panda SK (2011) "Self-autonomous wireless sensor nodes with wind energy harvesting for remote sensing of wind-driven wildfire spread." IEEE Trans Instrum Meas 60: 1367-1377 Yin XF, Cai CS, Fang Z and Deng L (2010) "Bridge vibration under vehicular loads: Tire patch contact versus point contact." Int J Struct Stab Dyn 10: 529-554 Zhang Y (2011) "Eigen frequency computation of beam/plate carrying concentrated mass/spring." J Vib Acoust 133: 021006 Zhang Y, Cai SC and Deng L (2014) "Piezoelectric-based energy harvesting in bridge systems." J Intell Mater Syst Struct 25: 1414-1428 Zhu W, Deng Y, Gao M, Wang Y, Cui J and Gao H (2015) "Thin-film solar thermoelectric generator with enhanced power output: Integrated optimization design to obtain directional heat flow." Energy 89: 106-117 © ASCE 684 Transportation Research Congress 2016 The Health Monitoring System Design for Bridge Based on Internet of Things Xinlong Tong1; Zhoujing Ye2; Yinan Liu3; Hailu Yang4; Yue Hou5; and Linbing Wang6 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Graduate Research Assistant, National Center for Materials Service Safety, Univ of Science and Technology Beijing, Beijing 100083, China E-mail: maniga@163.com Graduate Research Assistant, National Center for Materials Service Safety, Univ of Science and Technology Beijing, Beijing 100083, China E-mail: 503497949@qq.com Graduate Research Assistant, National Center for Materials Service Safety, Univ of Science and Technology Beijing, Beijing 100083, China E-mail: 934125514@qq.com Graduate Research Assistant, National Center for Materials Service Safety, Univ of Science and Technology Beijing, Beijing 100083, China E-mail: 727930305@qq.com Associate Professor, National Center for Materials Service Safety, Univ of Science and Technology Beijing, Beijing, China E-mail: alladin@outlook.com Professor, National Center for Materials Service Safety, Joint USTB-Virginia Tech Lab on Multifunctional Materials, Univ of Science and Technology Beijing, Beijing, Virginia Tech, Blacksburg, VA 24061, U.S (corresponding author) E-mail: wangl@vt.edu ABSTRACT With the rapid development of bridges, the traditional sensing technology is difficult to meet the needs of diversified tests To overcome the limitations and further develop the health monitoring system of bridges, a new network concept, namely, Internet of things (IOT), which exchanges information and creates the interconnection and communication between bridge and the monitoring system, is presented in this paper The system is designed to achieve real-time monitoring of bridge cluster health status This system introduces the wireless acceleration transducer by wireless gateway and cloud platform to monitor the bridge health status, which can real-time monitor the bridge cluster health status, process the real-time data, and help bridge maintenance KEYWORDS: Network; Bridges; Wireless Sensors; Health Monitoring System INTRODUCTION Since 1960s, bridge structures have been widely used throughout the world due to the high safety and strong durability The research on the intelligent control and monitoring of bridge structure has thus become an attractive issue for civil engineers The bridge structure is inevitably subjected to external and internal structure damage, which may cause the failure of bridge structure To monitor the health status of bridges and keep regular maintenance, the health state of the infrastructure needs to be monitored with an implemented system (Chen, et al 2013, Hou et al 2014, 2015, Guo et al 2014, Tan & Guo 2014, Wang et al 2005) There have been various approaches to set up the bridge monitoring system Among those methods, the Internet of Things (IOT) is a new and innovative approach, which is a network concept for information exchange and extends the client via the Internet to any goods and between goods Its essence is to realize the interconnection and sharing of information by using Radio Frequency Identification (RFID) technology, ZigBee and 3G/4G, etc Also, based on the information bearer such as the Internet and the traditional telecommunication, IOT makes all ordinary physical independent objects achieve connectivity It has three important characteristics, the common object equipment, homemade terminals connected and universal intelligent service © ASCE 685 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 Information collection, information transmission and information processing are the three main factors of IOT, (He et al 2012, Bo et al 2011, Jin et al 2014) The basic connotation of bridge health monitoring is to trigger the early warning signal when bridges are under the condition of the special climate, transportation or serious abnormal running state, through monitoring and evaluation of the bridge structure state The health monitoring system can also provide the basis for bridge maintenance, repair and management (Zheng et al 2012, Wu et al 2011, Zhang et al 2011, Ling et al 2009) Traditional bridge health monitoring system needs to collect data artificially The system has a large amount of sensors to monitor the state of bridges, which requires replacement after the sensor failure to the maintenance and replacement of sensors cause enormous waste of manpower and material resources The aim of this paper is to introduce a new bridge health monitor system based on Internet of Things, which could significantly reduce the cost during maintenance The sensor network and Internet are both used in the bridge health monitoring, to collect the safety information of the key position of the bridge structures The signals are then transmitted and processed through the Internet By analyzing the data using the IOT system, the health state of the bridge can be realtime obtained efficiently and accurately, (Wu et al 2011, Zhang et al 2011) RESEARCH AND DEPLOYMENT OF WIRELESS SENSOR 2.1 Design of data acquisition and processing system Different from the traditional wired transmission methods, in IOT, the wireless sensors are normally used for data transmission and management Every wireless sensor is considered as a node when monitoring bridge, the nodes not only has the ability for wireless communication, but also can process and analyze signal and network data According to the type of application, every node has a specified address It generally includes sensing device, the data processing microcontroller, and a wireless module The data by sensor collected will be transfer to gateway or database center after initial processing In this paper, the structure of the wireless sensor system is composed by the ARM microprocessor, ADXL345 sensor device, built-in 12 bit AD acquisition module, built-in RTC real time clock, CC1101 wireless communication module, a plurality of analog-digital interface, LED lights and the power supply The system uses TI's CC1101 sub1G radio frequency chip communication with gateway The band of using is 433.5M, modulation mode is GFSK, and communication rate is 38.4KBPS The acquisition and transmission module using a low-power sleep mode, CC1101 waked by electromagnetic wave to communicate with gateway The master controller uses STMicroelectronics’ STM32L152 ultra-low power 32-bit ARMCortexM3 processor powered by LTC3331.Considering data collection and transmission power, ADXL345 Sensing collection device is used in system design, which has a ultra-low operating consumption between 23 to 140μA The power consumption of sleep time is as low as 0.1μA, and the measurement range of ± 2, ± 4, ± 8, ± 16g The system structure diagram is shown in Figure 1, and the circuit diagram design of data acquisition and transmission is shown in Figure 2.2 Layout of sensor Sensors for collection and transmission of data must have high-quality structural response, and thus the layout of sensors, should comprehensively consider the support of layout method for node data analysis, which is a prerequisite for structural damage identification The interfacial © ASCE 686 Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved behavior between different materials also influences the accuracy of collected data (Tan & Guo 2014, Guo et al 2016) Due to the economy and running state of the structure, the bridge alldirection sensor installation is not realistic, it is facing a sensor layout problem The purpose of the layout is that using a finite number of sensors in the bridge key node, to obtain the comprehensive information Figure Structure chart of data acquisition and processing system based on ARM Figure The circuit diagram design of data acquisition and transmission A cost-effective sensor layout program should include the following aspects: 1) the sensor can obtain comprehensive and accurate information in noise environments; 2) the measured modality should be able to establish a correspondence with the results of model analysis; and 3) Through adding sensors, the data of interest part can be collected 4) Measured time history record is sensitive to the change of model parameters, (Wang et al 2006) According to the structure and monitoring indicators of bridge, the sensors layout should be © ASCE 687 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 688 setup considering the following factors: 1) the main control points of the structure;2) maximum stress distribution and artifact positions such as bridges across and quartile position;3) positions of stress concentration such as pier top, arch foot in contact with the abutment, etc;4)control points of temperature monitoring of the overall structure, such as bridge middle position;5) control points of structure natural frequency of vibration test;6) Part of the sensor laid redundancy, (Sui et al 2014) By experimental and theoretical analysis, the most excited bridge modes and the corresponding natural frequency can be obtained, while the purpose of the acceleration sensor measuring point is the objective to obtain the excitation modes information of bridge under external loadings The specific layout programs are as follows (in the X direction along the bridge, mid-span is the origin) Table wireless acceleration sensor layout scheme position X the bottom of Outer tie beam mid-span the bottom of Outer tie beam about 1/4 span +/-21.3m number Figure Layout plan of Acceleration sensor measuring point Figure shows sensor layout for bridge vibration monitoring DESIGN OF BRIDGE HEALTH MONITORING SYSTEM BASED ON INTERNET OF THINGS 3.1 The framework of bridge health monitoring system Bridge health monitoring system is an integrated monitoring system that considers the bridge as a platform, applies modern sensor technology, communication network technology and computer technology, optimizes the combination structure monitoring, traffic monitoring, equipment monitoring, and processes data analysis © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 Figure The concept of the IOT In this paper, the wireless sensor technology is used to obtain the bridge health information, by means of IOT All the sensors information could wireless transmitted to the Web database to realize the real-time bridge remote, dynamic management and control It can detect various kinds of bad phenomena caused by external factors such as vibration fast and efficiently, so as to provide technical support for all kinds of bridge disasters Figure Overall framework of health monitoring system for bridge structure The sensors collect real-time data and transmit to the gateway The gateway collects all range sensor data, unifies them using the 433 frequencies and transmits to the background database server And the data will be processed and analyzed using the special data processing equipment and processing method After processing and analysis, the data will be sent to specially designed software for bridge Experts, bridge design departments and managers can set up a warning value for the monitoring, where when data exceeds the corresponding warning value, the system will automatically alarm to remind the managers 3.2 Software design of system health monitoring Wireless sensor is primarily for data acquisition and transmission of the bridge During the © ASCE 689 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 testing, the data communication can be performed between a single wireless acceleration sensor and the back-end server In a bridge cluster of health monitoring system, a local sensor is essential for data transfer to the gateway The signal is then transferred to the backend server Based to the subsystem monitoring, transmission subsystem design, and data analysis methods, the specific software subsystems are established Software subsystem will contact all hardware devices from the logic and function together and realize the data analysis; in addition, the software subsystems were open to bridge maintenance personnel, where the latter could view all the monitoring data via the software and help the expert make a data analysis for bridge health assessment The following Figure 3.3 describes the framework for the entire software subsystem Figure Overall framework of software system 3.2.1 Software subsystem framework The bridge structural health monitoring system software is constructed mainly to achieve three functions: data collection and analysis, health assessment and classification, and system management and decision-making The system is therefore divided into three subsystems, where the function frames are as shown in Figure The data processing subsystem collects data from sensors and gateways that are deployed on the bridge, and makes a combination of data and simple analysis The health assessment subsystem is set up based on the data acquisition subsystem of the monitoring data, which can analyze and evaluate the health of the bridge, and finally give a health assessment report Based on the health assessment report, the management decision subsystem makes the decision and judgment, and generates the inspection maintenance decision In addition, the management decision system can also send the data and information of the system to other management departments for analysis and reference The above system structure is divided according to function, the whole software system can also be divided into three parts: Embedded software, server software and client software The embedded software is used for sensor and video network software Server software refers to being deployed in data center server in the background service software, where its function is to conduct the background data analysis, evaluation and analysis, and management decision analysis Client software is the software for highway maintenance, which has a user interface so © ASCE 690 Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved that the staff can directly conduct the operation Figure Software system by application object The functions and relations between the three parts are shown in Figure The node in embedded software is responsible for data collection and processing through a particular network protocol The data will be transmitted to the server connected to the gateway Server software to receive the network data analysis and conversion, the data storage to the database, and according to the project model for data analysis and mining The client application software is customized for a particular application scenario, which displays the collection data and analysis results, and controls the status of the nodes and the network The server software is set between the client application software and embedded software, to ensure that their respective changes not affect each other Figure The structure of data processing subsystem © ASCE 691 Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved 3.2.2 Subsystem of data processing Data processing subsystem collects data from the sensors deployed on the bridge System will merge data and simple analysis of these data The structure of data processing subsystem is as shown in Figure The bottom layer is the data acquisition network constitute by sensors The top layer is the data collection, data fusion and analysis module of the background server The first part is the embedded software system which is used for the sensor node and the video monitoring equipment The software of the video monitoring system is relatively simple The main function is to transmit video data, receive system commands, and control the cloud platform of the monitor equipment Figure The structure of server software The second part is the software deployed on the server of the data center The structure is as shown in Figure By the operation layering and data abstracting, the common interface accessing the data is obtained to achieve effective separation of client software and the underlying data, which improves the system's versatility and scalability The data processing flow of the server side is shown in Figure 10 Figure 10 The data processing flow of the server © ASCE 692 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 The main function of the server software includes: 1) Data abstraction: process different types of network nodes and cache pretreatment data packet 2) Data parsing / conversion: parse the underlying packet, extract the desired data, and convert data from sensors and monitor into the corresponding standard unit 3) Data access: store data in the database, and provides the basic access interface to the data; 4) Data analysis/fusion/Mining: data depth processing, and according to the target application of the engineering model to extract and mine useful information; 5) Client interface: provide universal access interface for the upper layer application software, and hide the details of the data processing 3.2.3 Health assessment subsystem The main function of health assessment subsystems is a combination of monitoring data and structure engineering model to forecast the structural damage, also assessment and grading of the current state structure of health, and, according to the results of the prediction and evaluation to build safety warning mechanism of bridge structure, to warning for the possible risk of structure, the evaluation and grading results are available for management system to make maintenance decisions Health assessment subsystem includes several modules as follows: 1) Damage identification Health assessment system analyzes monitoring data, where the results are combined with the corresponding method to identify the damage of structure Damage identification is a series of method including the structural damage identification method based on the inherent frequency, structural damage identification method based on computational intelligence, structural damage identification method based on stiffness matrix and the flexibility matrix, and structural damage identification method based on model modification 2) Structure evaluation System evaluate and analyzes bridge according to the national standard or the user specified standard in advance, including the strength evaluation of the structure or component, stiffness evaluation of the structure or component and crack condition assessment of structures or components Based on the evaluation results, we can judge the carrying capacity of bridge structure 3) Health grading According to the results of evaluation and forecast of the whole bridge and component, the bridge health grade can be obtained System is built in a series of component and unit database, according to the predefined specifications to grading and evaluate structure for early warning according to the setting 3.3.4 Management decision-making subsystem Management decision subsystem make decisions and judgments according to the test data of health assessment report and data acquisition system, then produce the inspection maintenance decision Its main functions include systematic and automated multidimensional data storage, multidimensional data display and mining and inspection maintenance decision analysis Management decision system can be divided into server-side and client-side Server software has all kinds of database management of the whole monitoring system, and is used to manage the data access and storage of the whole system Management decision system can automatically analyze according to the health rating of bridge structure, and produce the inspection maintenance plan submitted to the operator for audit It will produce daily maintenance plan after approval Management decision-making system not only has the server software, also contains the © ASCE 693 Transportation Research Congress 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved client software, where the client software is mainly used for monitoring data visualization, the network topology and node control, the query of output result of each subsystem and the manual intervention for operation of the system, etc Client software uses a generic interface to access the database It shows data with multiple forms, such as time curve, histogram and scattergram, etc Users can know the status of structure timely from the information of node, and formulate reasonable repair and maintenance plan to ensure the healthily operation of bridge 3.3.5 Result show The bridge structural health monitoring system based on IOT is designed, which can detect the change of bridge health by remote monitoring and controlling, and provide flexible information services for the bridge maintenance and management The system could display a variety of bridge state data, analyze data, assess the health status The analysis results can be provided for bridge maintenance and management to make scientific decisions The background results show real-time data, history data, data analysis and history data, which provides rich measurement data of bridge structure for managers It also provides status information like signal intensity, electric quantity information of every sensor node，in order to maintain the network later Vibration data of one sensor node is shown in Fig.11: Figure 11 Vibration data of one sensor node CONCLUSIONS In this paper, based on previous research on wireless acceleration sensor and Internet of Things (IOT) concept, a bridge health monitoring system is designed, which has low-power consumption and strong remote data transmission ability This system can visualize the data, dynamically monitor bridge health Since most existing sensors have big problems in terms of power consumption during data transfer, a fully functional low-power consumption wireless acceleration sensor system is established, which solves the problem of frequent sensor battery © ASCE 694 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; all rights reserved Transportation Research Congress 2016 replacements Compared with the traditional method of bridge health monitoring, the new system has the following advantages: The bridge health monitoring technology based on IOT is established without suspended bridge operation in terms of data collection and without artificial field acquisition It can also read, store and process data automatically The data collection will be remotely transmitted The long-term periodic detection and real-time monitoring of the bridge structures could be obtained The wireless sensor is used in the system whose body is small and is convenient for installation Meanwhile, the battery consumption problem is solved because of the Ultralow power consumption Wireless acceleration sensor has the advantages in data acquisition, processing, and transmission Wireless sensor is convenient for monitoring multiple bridges using the gateway, which greatly saves human resources and improves the efficiency of the bridge cluster monitoring The bridge health monitoring system using wireless acceleration sensors based on Internet of Things are new and innovative, which provides a new reliable way to real-time monitor the bridge structure state However, due to the current technology, there are still some limitations A multi-functional, comprehensive, widely applicable health monitoring system should be considered in future studies ACKNOWLEDGEMENT This paper is supported by the state high-tech research and development plans (863), Grant No.2014AA110402 REFERENCES Chen Jun , Chen Feng, Chen Wei (2013) “A bridge cluster health monitoring system based on 3G wireless sensor network.” Journal of Jinan university (natural science), 1, 57-58 Guo M, Motamed A, Tan YQ, Bhasin A (2016) “Investigating the Interaction between Asphalt Binder and Fresh and Simulated RAP Aggregate” Materials & Design, 105: 25-33 Guo M, Tan YQ, Zhou SW (2014) “Multiscale Test Research on Interfacial Adhesion Property of Cold Mix Asphalt” Construction and Building Materials, 68: 769-776 Hou, Y., Wang, L., Yue, P., Pauli, T and Sun, W (2014) “Modeling Mode I Cracking Failure in Asphalt Binder by Using Nonconserved Phase-Field Model.” Journal of Materials in Civil Engineering, 26(4), 684-691 Hou, Y., Yue, P., Wang, L and Sun, W (2015) “Fracture Failure in Crack interaction of Asphalt Binder by Using a Phase Field Approach.” Materials and Structures, 48(9): 2997-3008 Hai-hong Wu (2011) “The Enter of 3G Applications into the Era of the Internet of Things.” Journal of Changchun Normal University He Xiang-cheng, Gu Yunlin, Cao Yun-gang, (2012) “The Internet of things technology application in our country highway disasters monitoring and prevention.” ChengShi Jianshe LiLun Yan Jiu, (18), 2095-2104 Jin LR, You Ting, Lv ML, et al (2014) “Bride Security Monitoring and Warning System Research Based on IOT.” Science & Technology Vision, 7, 53-54,32 Ling Y U, Zhu J H, Chan T H T (2009) “A LabVIEW-based data acquisition system for bridge health monitoring.” Journal of Jinan University, 30(5):465-468 Sui L Y, Chen Z H, Li W, et al (2014) “Study on Monitoring and Safety Early Warning Technology of Bridge Health Based on Internet of Things Technology.” Applied Mechanics © ASCE 695 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/04/19 Copyright ASCE For personal use only; 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Transportation, Beijing Univ of Civil Engineering and Architecture; Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing 100044 Beijing Urban Transportation Infrastructure. .. Transportation, Beijing Univ of Civil Engineering and Architecture; Beijing Urban Transportation Infrastructure Engineering Technology Research Center, Beijing 100044 School of Civil Engineering and Transportation,