Exploration of Multi-Fidelity Co-Kriging Meta-Modeling for Global Structural Response through Real-Time Hybrid Simulation
发布者:陈再现   编辑:海洋工程学院   发布时间:2022年12月03日

报告题目:Exploration of Multi-Fidelity Co-Kriging Meta-Modeling for Global Structural Response through Real-Time Hybrid Simulation

报告人:陈城博士/教授

时间:121011:00-12:30

线下集中收看讨论地点:研究院1号楼北621会议室

线上参会腾讯会议号:178-329-264(密码:921044

Abstract:

Real-time hybrid simulation (RTHS) provides a cyber-physical technique for large- or full-scale experiments in size limited laboratories when parts of the structure are difficult for accurate modeling. Traditional practice of RTHS assumes deterministic structural properties therefore could not account for uncertainties in global response prediction in an efficient and effective way. Previous studies have shown that meta-modeling enables efficient uncertainty quantification through limited number of expensive physical experiments or computational simulation. More recent studies indicate that multi-fidelity Co-Kriging can achieve better accuracy with fewer experiments or less simulation. This study presents an experimental study of the influence of low-fidelity model accuracy on Co-Kriging meta-modeling for uncertainty quantification. Laboratory RTHS through are considered as high-fidelity (HF) simulation and conducted in parallel with low-fidelity (LF) computational simulation of the same structure. The Co-Kriging meta-modeling is then applied to integrate multi-fidelity simulation to render accurate response prediction over the entire sample space of uncertainty input variables. Different parameter values are used for same computational model to emulate different LF simulation for Co-Kriging meta-modeling. RTHS tests are conducted for a single-degree-of-freedom (SDOF) structure with self-centering viscous damper (SC-VD). The Co-Kriging meta-models established from experimental results are then evaluated through validation tests and further compared with corresponding Kriging meta-models. A multi-fidelity Co-Kriging with LF model updating is further proposed to improve the convergence and accuracy in response estimation for uncertainty quantification.

Dr. Cheng Chen:

Professor of Civil Engineering, San Francisco State University. Dr Chen received his B.S. degree in 1999 and M.S. degree in 2002 from Tongji University. After he received his Ph.D. degree in Structural engineering from Lehigh University in 2007, he served as post-doctoral research associate and research engineer at the Lehigh NEES RTMD Site in 2008 and 2009. He is currently a professor of Civil Engineering in the School of Engineering at San Francisco State University. His research interests focus on advanced experimental techniques and seismic hazard mitigation. Dr. Chen has published over 100 academic papers, including more than 60 papers in SCI journals, and the papers have been cited more than 1,900 times (google scholar). Focusing on the advanced experimental methods of engineering structures, Dr. Chen has made significant achievements in basic theories, technological innovations and application innovations.


编辑审核:海洋工程学院