2026-09-18T20:39:17Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/44294 2023-07-11 col_2142_5131 col_2142_14770 com_2142_5130 com_2142_3518 com_2142_234

Spencer, Billie F., Jr. Spencer, Billie F., Jr. Elnashai, Amr S. Agha, Gul A. Song, Junho Li, Jian 2013-05-24T22:06:50Z 2013-05-24T22:06:50Z 2013-05 2013-05-24T22:06:50Z 2013-05 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. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2013-04-08T21:40:33Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 2 Li_Jian.docx: 15960005 bytes, checksum: 7a01bc8bf77796d728f64b9af3b35576 (MD5) Li_Jian.pdf: 18002545 bytes, checksum: 69ab493b377609053ade18f88a9923eb (MD5) Made available in DSpace on 2013-05-24T22:06:50Z (GMT). No. of bitstreams: 3 Jian_Li.pdf: 17981374 bytes, checksum: c03295b56b02c47bc1cf6227072fd242 (MD5) Li_Jian.docx: 15942888 bytes, checksum: 939edb738d4e624ab85c1bb7d34948c8 (MD5) license.txt: 4056 bytes, checksum: 72bd95ffc056f146299b028b14d961b9 (MD5) http://hdl.handle.net/2142/44294 en Copyright 2013 Jian Li Fragility analysis Structural Health Monitoring Wireless Smart Sensor Time Synchronization Hybrid simulation Multiple-Support Excitation System identification Output decoupling Seismic risk assessment Monitoring, modeling, and hybrid simulation—an integrated Bayesian-based approach to high-fidelity fragility analysis text Civil & Environmental Eng 1251 Civil Engineering 0106 University of Illinois at Urbana-Champaign Dissertation Ph.D. PHD:Civil Engineering -UIUC 10KS0106PHD