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6th International ANCRiSST Workshop 2011 Group Discussion – Structural Health Monitoring Asian-Pacific Network of Centers for Research in Smart Structure Technology (ANCRiSST) Dalian, China July 25-26, 2011 Chairs: Chung Bang Yun Department of Civil & Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Kincho H. Law Department of Civil & Environmental Engineering Stanford University Recorder: Kenneth J. Loh Department of Civil & Environmental Engineering University of California, Davis Number of participants in group discussion: 38+
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ANCRiSST 2011 Workshop 2/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 1. Smart Sensors & Sensing Technologies Do we need to develop or improve upon current smart sensing technologies? Yes, visual inspection still remains the current state-of-art Several different categories where sensor development is needed: Optical-based sensors or vision-based sensing Include fusing fiber optic sensing with wireless capabilities New materials and multifunctional materials Multiple engineering functionalities: multi-modal sensing, energy scavenging, environmental monitoring, and actuation/interrogation, among others Self-diagnosing and self-healing materials European Union and select research groups (HIT, DLUT, UM) are very active Need systems-approach for self-healing and self-diagnosis Robotic sensing and associated infrastructure Not only useful for SHM but also for security and gathering various information Bio-inspired sensing still in its infancy Chemical sensors for corrosion Sensors for challenging environments Deep-sea offshore oil platforms, wind turbines, built environment, etc. Use of many not-so-smart or ordinary sensors for densely-distributed sensing
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ANCRiSST 2011 Workshop 3/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 2. Data Informatics and Data Mining What information do we need to sense and how do we process the data? Need new methodology for dealing with different types of sensors and data Current research still dominated by vibration-based monitoring Data fusion problem: global v. local and different types of sensor data Issue of monitoring all members/locations v. critical locations/”hot spots” Objective is to detect damage severity and location Probability of Detection (POD): civil engineers need to start quantifying POD Ex: how big of a crack can you detect, and what is the probability of detecting it? Bio-informatics modeling and data modeling Bio-inspired data interpretation and data mining Biological creatures can autonomously differentiate between the variety of data collected Spooling: fish can extract basic information from many neurons for decision making Machine-learning and data-mining methods for analyzing large data sets Imitate how doctors or professionals diagnose humans Access to existing monitoring data or benchmark models Prof. Li has collected information from damaged bridge structure and will make public Jindo bridge monitoring data will potentially be made to the public late this year Hong Kong Polytechnic University Guang Zhou TV Tower monitoring data on web Talk to ANCRiSST
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ANCRiSST 2011 Workshop 4/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 3. Integrating SHM with Current Methods How does one integrate SHM with current methods? Life cycle cost and life cycle assessment Need to integrate SHM with life cycle cost and assessment to achieve desired life cycle performance Build resilient infrastructure while extending their service life How will climate change affect civil infrastructure Need collaboration across disciplines and research groups Reliability-based SHM Most cases, deterioration is gradual (fatigue, corrosion, loading, etc.) Find probability of failure and predict remaining service life and cost of maintenance Useful for future code development Risk management We know what vibration means, but the general public may not Need ways of communicating to the general public for emergency management Autonomous decision making strategies and communication systems (tsunami) Accurate information is critical Appropriate business models for each particular industry Understand the needs of owners, government agencies, and stakeholders Successful example is dams where it is heavily regulated with SHM
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ANCRiSST 2011 Workshop 5/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 4. Education Structural health monitoring is a multi-disciplinary field of study Some students may only focus on one small aspect of SHM Is the current engineering curricula adequate for training our future students Need online learning or e-learning approaches Sharing of SHM course content and teaching materials Asian-Pacific Summer School (APSS) on Smart Structures Technologies Course contents and all teaching materials from previous years available online After 6 APSS summer schools, a group of researchers will get together to write a textbook
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ANCRiSST 2011 Workshop 6/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 5.1. List of Attendees and Affiliations China: Hui Li (HIT) Guofu Qiao (HIT) Zhichun Zhang (HIT) Wentao Wang (HIT) Dongsheng Li (DLUT) Xiongwei Hu (DLUT) Yuequan Bao (HIT) Minghua Huang (HIT) Binbin Li (DLUT) Wensong Zhou (HIT) Tong Guo (Southeast Univ) Xu-feng Guan (HIT) Ying Lei (Xiamen Univ.) Chunguang Lan (HIT) Yan Yu (DLUT) Jianghua Ran (DLUT) Yanhong Wang (DLUT) Xuefeng Zhao (DLUT) Xijun Ye (South China Univ.) Tianfeng Zhu (South China Univ.) Yong Huang (HIT) Jilin Hou (DLUT) Dongwang Tao Xin Chun Guan (HIT) Yiming Gu
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ANCRiSST 2011 Workshop 7/7 Structural Health Monitoring Working Group Discussion Summary ANCRiSST 2011 Conference: Dalian, China – July 26, 2011 5.2. List of Attendees and Affiliations United States: Kincho Law (Stanford) Ken Loh (UC Davis) Dryver Huston (Univ. of Vermont) Miao Yu (UM College Park) Stephen Wu (Cal. Tech.) Vanessa Heckman (Cal. Tech.) Robin Kim (UIUC) Yongchao Yang (Rich Univ.) Korea: Chung Bang Yun (KAIST) Hyun Myimg (KAIST) Japan: Akira Mita (Keio Univ.) Toshi Oshima (Kitami Inst. of Tech.) United Kingdom: Hua-Peng Chen (Greenwich Univ.)
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