报告题目：Data-driven computational multiscale methods and applications
报告人：Prof. Eric Chung The Chinese University of Hong Kong
邀请人：李秋齐
时间：2022 年 5 月 25 日 (星期三) 4:20-5:20 PM
报告形式：在线报告 ( Zoom 会议）
Zoom 会议号：794 6714 4906
密码：0525
入会链接：https://us04web.zoom.us/j/79467144906?pwd=RCAIcmy6J7b4gc1fFMovWnzIKnaRV.1
报告摘要
Many practical problems, especially those arising from geosciences, have multiscale features due to medium
heterogeneities, nonlinearity and coupling of multiple models. The goal of multiscale methods or numerical
upscaling techniques is to compute the solutions of these complicated problems efficiently by constructing
coarse scale equations for some dominant components of the solutions. In this talk, we will present the latest
development of a class of multiscale methods, which make use of solutions of local problems to obtain coarse
scale equations and have rigorous convergence theories. For nonlinear problems, the macroscopic parameters
in the coarse scale equations can be computed efficiently by the use of deep learning techniques. We will
discuss the general concepts and present some applications.
专家简介
Eric T. Chung is a Professor in the Department of Mathematics in The Chinese University of Hong Kong. He obtained PhD degree
from University of California at Los Angeles. His Ph.D. thesis advisor is Prof. Bjorn Engquist. His research interests are Discontinuous
Galerkin Methods, Computational Wave Propagation, Fluid Flow in Heterogeneous Media, Multiscale Model Reduction Techniques,
Adaptivity for Multiscale Problems, Domain Decomposition Methods, Seismic Imaging and Travel Time Tomography.
个人主页 https://www.math.cuhk.edu.hk/ tschung/
