报告题目：Primal-Dual Weak Galerkin (PDWG) Methods for Partial Differential Equations

报告时间：2021年6月14日，星期一，上午9:00－11:00

腾讯会议ID：551 896 172

报告人：Chunmei Wang，Texas Tech University

报告摘要: 

The essential idea of PDWG is to interpret the numerical solutions as a constrained minimization of some functionals with constraints that mimic the weak formulation of the PDEs by using weak derivatives. The resulting Euler-Lagrange formulation results in a symmetric scheme involving both the primal variable and the dual variable (Lagrangian multiplier). PDWG method is applicable to several challenging problems for which existing methods may have difficulty in applying; these problems include the second order elliptic equations in nondivergence form, Fokker-Planck equation, elliptic Cauchy problems, div-curl systems, etc. An abstract framework for PDWG will be presented and discussed for its potential in other scientific applications.

报告人简介：

Chunmei Wang has been an assistant professor in the Department of Mathematics & Statistics at Texas Tech University since 2018. Prior to that, she was an assistant professor at Texas State University from 2016 to 2018, and a visiting assistant professor at Georgia Tech from 2014 to 2016. She received a B.Sc. at Soochow University in 2004, an M.Sc. at Soochow University in 2007, and a Ph.D. at Nanjing Normal University in 2014. Her research focuses on applied and computational mathematics with a focus on weak Galerkin finite element methods.