Adaptive algorithms for scalar non-convex variational problems

被引:10
作者
Carstensen, C
Plechac, P
机构
[1] Univ Kiel, Math Seminar, D-24098 Kiel, Germany
[2] Heriot Watt Univ, Dept Math, Edinburgh EH14 4AS, Midlothian, Scotland
基金
英国工程与自然科学研究理事会;
关键词
non-convex minimization; young measures; microstructure; a posteriori error estimates; adaptive algorithms; ZZ-estimator;
D O I
10.1016/S0168-9274(97)00089-5
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Since direct numerical solution of a non-convex variational problem (P) yields rapid oscillations, we study the relaxed problem (RP) which is a degenerate convex minimization problem. The classical example for such a relaxed variational problem is the double-well problem. In an earlier work, the authors showed that relaxation is not linked to a loss of information if our main interest concerns the macroscopic displacement field, the stress field or the microstructure. Furthermore, a priori and a posteriori error estimates have been computed and an adaptive algorithm was proposed for this class of degenerate variational problems. This paper addresses the question of efficiency and considers the ZZ-indicator, named after Zienkiewicz and Zhu, and discusses its performance compared with the rigorous indicator introduced by the authors. (C) 1998 Elsevier Science B.V.
引用
收藏
页码:203 / 216
页数:14
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