Enhance Eigenvalue Approximation by Gradient Recovery
主 题: Enhance Eigenvalue Approximation by Gradient Recovery
报告人: 张智民 教授 (北京计算科学研究中心/Wayne State University)
时 间: 2012-11-08 16:00-17:00
地 点: 理科一号楼1418
Eigenvalues of partial differential equations and their numerical approximations are important research subjects, simply because of their wide application in sciences. We propose to enhance the eigenvalue approximation by post-processing the numerical data from a general purpose finite element software. This prost-processing procedure for the second-order differential operators is called gradient recovery and its computational complexity is of order O(N), where N is the number of unknowns. Both self-adjoint and non-self-adjoint operators will be discussed.
