Convergence of natural adaptive least squares finite element methods

被引:13
|
作者
Carstensen, Carsten [1 ]
Park, Eun-Jae [2 ]
Bringmann, Philipp [1 ]
机构
[1] Humboldt Univ, Inst Math, Unter Linden 6, D-10099 Berlin, Germany
[2] Yonsei Univ, Dept Computat Sci & Engn, Seoul 03722, South Korea
基金
新加坡国家研究基金会;
关键词
OPTIMALITY; STANDARD;
D O I
10.1007/s00211-017-0866-x
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The first-order div least squares finite element methods provide inherent a posteriori error estimator by the elementwise evaluation of the functional. In this paper we prove Q-linear convergence of the associated adaptive mesh-refining strategy for a sufficiently fine initial mesh with some sufficiently large bulk parameter for piecewise constant right-hand sides in a Poisson model problem. The proof relies on some modification of known supercloseness results to non-convex polygonal domains plus the flux representation formula. The analysis is carried out for the lowest-order case in two-dimensions for the simplicity of the presentation.
引用
收藏
页码:1097 / 1115
页数:19
相关论文
共 50 条