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Title:Monitoring, modeling, and hybrid simulation—an integrated Bayesian-based approach to high-fidelity fragility analysis
Author(s):Li, Jian
Director of Research:Spencer, Billie F., Jr.
Doctoral Committee Chair(s):Spencer, Billie F., Jr.
Doctoral Committee Member(s):Elnashai, Amr S.; Agha, Gul A.; Song, Junho
Department / Program:Civil & Environmental Eng
Discipline:Civil Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Fragility analysis
Structural Health Monitoring
Wireless Smart Sensor
Time Synchronization
Hybrid simulation
Multiple-Support Excitation
System identification
Output decoupling
Seismic risk assessment
Abstract: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 research aims to develop a systematic Bayesian-based framework to estimate high-fidelity fragility functions by integrating monitoring, modeling, and hybrid simulation, with the final goal of improving the accuracy of seismic risk assessment to support both pre- and post-disaster decision-making. In particular, this research addresses the following five aspects of the problem: (1) monitoring with wireless smart sensor networks to facilitate efficient and accurate pre- and post-disaster data collection, (2) new modeling techniques including innovative system identification strategies and model updating to enable accurate structural modeling, (3) hybrid simulation as an advanced numerical-experimental simulation tool to generate highly realistic and accurate response data for structures subject to earthquakes, (4) Bayesian-updating as a systematic way of incorporating hybrid simulation data to generate composite fragility functions with higher fidelity, and 5) the implementation of an integrated fragility analysis approach as a part of a seismic risk assessment framework. This research not only delivers an extensible and scalable framework for high-fidelity fragility analysis and reliable seismic risk assessment, but also provides advances in wireless smart sensor networks, system identification, and pseudo-dynamic testing in civil engineering applications.
Issue Date:2013-05-24
Rights Information:Copyright 2013 Jian Li
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05

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