【海韵讲座】2021年第29期- Incremental Potential Elastodynamics with Contact: Robust Optimization-based Solvers and Smooth Reformulations
报告题目：Incremental Potential Elastodynamics with Contact: Robust Optimization-based Solvers and Smooth Reformulations
主讲人：蒋陈凡夫，美国加州大学洛杉矶分校数学系助理教授
时间：2021年6月28日（星期一）11:00-12:30
地点：腾讯会议
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会议 ID：855 593 892
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摘要：
Contact is ubiquitous and often unavoidable, and yet modelling contacting systems continues to stretch the limits of available computational tools. In part, this is due to the unique hurdles posed by contact problems. Several intricately intertwined physical and geometric factors make contact computations hard, especially in the presence of friction and nonlinear elasticity. In this talk, our recent work on a new optimization-based finite element solver will be discussed, which is constructed for mesh-based discretizations of nonlinear elastodynamic problems supporting large nonlinear deformations, implicit time-stepping with contact and friction. Built on top of a smooth barrier reformulation and a custom Newton-type optimization, it is a first of its kind "plug-and-play" contact simulation framework that provides convergent and unconditionally feasible intersection-free trajectories. The scheme also enables future studies of differentiable simulations of nonsmooth physics-constrained inverse problems in design, control and robotics.
报告人简介：
Chenfanfu Jiang is an assistant professor of applied mathematics at the University of California, Los Angeles, where he received his Ph.D. degree back in 2015. Jiang is a recipient of the UCLA Edward K. Rice Outstanding Doctoral Student Award (2015), NSF CRII award (2018), and NSF CAREER award (2020). Jiang has published 27 papers in SIGGRAPH or SIGGRAPH Asia. His current research interests include physics-based modeling/simulation and scientific computing. He works on numerical algorithms facilitating advancements in computer graphics, computational physics, and inverse problems (mainly in structural mechanics, vision, and robotics).
邀请人：软件工程系 姚俊峰教授