Journal of Computational and Applied Mathematics2022,Vol.40618.DOI:10.1016/j.cam.2021.113926

A recovery-based a posteriori error estimator of the weak Galerkin finite element method for elliptic problems

Liu, Ying Wang, Gang Wu, Mengyao Nie, Yufeng
Journal of Computational and Applied Mathematics2022,Vol.40618.DOI:10.1016/j.cam.2021.113926

A recovery-based a posteriori error estimator of the weak Galerkin finite element method for elliptic problems

Liu, Ying 1Wang, Gang 1Wu, Mengyao 1Nie, Yufeng1
扫码查看

作者信息

  • 1. Northwestern Polytech Univ
  • 折叠

Abstract

In this paper, we propose a recovery-type a posteriori error estimator of the weak Galerkin finite element method for the second order elliptic equation. The reliability and efficiency of the estimator are analyzed by a discrete H-1-norm of the exact error. The estimator is further used in the adaptive weak Galerkin algorithm on the triangular, quadrilateral and other polygonal meshes. Numerical results are provided to demonstrate the effectiveness of the adaptive mesh refinement guided by this estimator. (C) 2021 Elsevier B.V. All rights reserved.

Key words

Weak Galerkin finite element method/Weak gradient recovery/A posteriori error estimator/Adaptive algorithm/POLYNOMIAL PRESERVING RECOVERY/INTERFACE PROBLEMS/GRADIENT/SUPERCONVERGENCE/APPROXIMATION/EQUATIONS

引用本文复制引用

出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
被引量3
参考文献量39
段落导航相关论文