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报告题目：Monitoring, modeling, and hybrid simulation – an integrated Bayesian-based approach to high-fidelity fragility analysis
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主讲人：李健 助理教授，堪萨斯大学土木，环境与建筑工程学院
主讲人简介：
李健，博士，美国堪萨斯大学土木，环境与建筑工程系助理教授，博士生导师，主要从事结构健康监测和地震工程研究。分别于2005年本科和2007年硕士毕业于哈尔滨工业大学和哈工大深圳研究生院。于2013年博士毕业于伊利诺伊大学香槟分校并于同年加入堪萨斯大学。发表学术论文被SCI收录17篇。主持美国联邦公路管理局（FHWA）与7个州交通部（State DOT）共同资助的交通集合基金计划（Transportation Pooled Fund）1项，共同主持美国国家合作公路研究计划（NCHRP）1项，以及堪萨斯交通部研究计划1项。2015年入选美国土木工程师学会ASCE ExCEEd Fellow.
报告摘要：
Fragility functions are one of the key technical ingredients in seismic risk assessment. The derivation of fragility functions has been extensively studied in the past; however, large uncertainties still exist, mainly due to limited collaboration between the interdependent components involved in the course of fragility estimation. This presentation introduces a systematic Bayesian-based framework to derive high-fidelity fragility functions by integrating monitoring (wireless sensor networks), modeling (advanced system identification), and hybrid simulation, with the final goal of improving the accuracy of seismic risk assessment to support both pre- and post-disaster decision-making. Each component, as well as the integrated framework, has been validated through the derivation of the fragility functions for a reinforced concrete highway overcrossing bridge. This research not only delivers an extensible and scalable framework for high-fidelity fragility analysis, but also brings advances to wireless smart sensor networks, system identification, and pseudo-dynamic testing in civil engineering applications.
日 期：2016年8月4日（星期四）
时 间：09:00-11:00
地 点：综合实验3号楼3楼会议室
