题目：工程数值模拟中的反问题和不确定性量化
Title：Inverse Modeling and Uncertainty Quantification in Complex Physical Systems
报告人（Speaker）：
Heng Xiao
Virginia Tech
Assistant Professor
Aerospace & Ocean Engineering
Dr. Heng Xiao (肖恒) is an Assistant Professor in the Department of Aerospace and Ocean Engineering at Virginia Tech. He obtained a bachelor's degree in Civil Engineering (2003) from Zhejiang University, China, a master's degree in Mathematics (2005) from the Royal Institute of Technology (KTH), Sweden, and a Ph.D. degree in Civil Engineering (2009) from Princeton University, USA. Before joining Virginia Tech in 2013 as a faculty member, he worked as a postdoctoral researcher at Swiss Federal Institute of Technology (ETH) Zurich, Switzerland, from 2009 to 2012. His current research interests lie in two areas: (1) development of novel algorithms for high-fidelity simulations of particle-laden flows and turbulent flows, and (2) inverse modeling and uncertainty quantification in fluid dynamics and other complex physical systems. See https://sites.google.com/a/vt.edu/hengxiao/
摘要（Abstract）：
Numerical models of complex physical system are playing increasing important roles in engineering decision making. Examples applications include design of critical infrastructure and safety assessment of nuclear power plants. In this talk, I will give an overview of the sources of errors and uncertainty in numerical models of engineering system, including input uncertainties and model-form uncertainties. I will then present an ensemble Kalman filtering approach for inferring model parameters and quantifying model-form uncertainties in numerical simulations. Two example applications will be discussed: (1) inferring model uncertainties in turbulent flow simulations and (2) inferring flow speed and water depth of a tsunami based on its sediment deposits. Moreover, I will briefly introduce another research topic pursed in my group, i.e., particle-resolved simulations of sediment transport based on Computational Fluid Dynamics / Discrete Element Method (CFD/DEM)
Researchgate Virginia Tech
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浙江大学防灾工程研究所
浙江省岩土力学与工程学会