On the Convergence of Adaptive Finite Element Methods

State of the art simulations in computational mechanics aim reliability and efficiency via adaptive finite element methods (AFEMs) with a posteriori error control. The a priori convergence of finite element methods is justified by the density property of the sequence of finite element spaces which essentially assumes a quasi-uniform mesh-refining. The advantage is guaranteed convergence for a large class of data and solutions; the disadvantage is a global mesh refinement everywhere accompanied by large computational costs. AFEMs automatically refine exclusively wherever the refinement indication suggests to do so and so violate the density property on purpose. Then, the a priori convergence of AFEMs is not guaranteed automatically and, in fact, crucially depends on algorithmic details. The advantage of AFEMs is a more effective mesh accompanied by smaller computational costs in many practical examples; the disadvantage is that the desirable error reduction property is not always guaranteed a priori. Efficient error estimators can justify a numerical approximation a posteriori and so achieve reliability. But it is not clear from the start that the adaptive mesh-refinement will generate an accurate solution at all. This paper discusses particular versions of an AFEMs and their analyses for error reduction, energy reduction, and convergence results for linear and nonlinear problems. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

[1]  I. Hlavácek,et al.  Mathematical Theory of Elastic and Elasto Plastic Bodies: An Introduction , 1981 .

[2]  Claes Johnson,et al.  Adaptive finite element methods in computational mechanics , 1992 .

[3]  Rolf Rannacher,et al.  A posteriori error control in finite element methods via duality techniques: Application to perfect plasticity , 1998 .

[4]  Ricardo H. Nochetto,et al.  Convergence of Adaptive Finite Element Methods , 2002, SIAM Rev..

[5]  W. Han,et al.  Plasticity: Mathematical Theory and Numerical Analysis , 1999 .

[6]  R. Verfürth,et al.  Edge Residuals Dominate A Posteriori Error Estimates for Low Order Finite Element Methods , 1999 .

[7]  E. Zeidler Nonlinear functional analysis and its applications , 1988 .

[8]  Carsten Carstensen,et al.  Averaging techniques for reliable a posteriori FE-error control in elastoplasticity with hardening , 2003 .

[9]  Rüdiger Verfürth,et al.  A posteriori error estimation and adaptive mesh-refinement techniques , 1994 .

[10]  Carsten Carstensen,et al.  Domain decomposition for a non-smooth convex minimization problem and its application to plasticity , 1997 .

[11]  王东东,et al.  Computer Methods in Applied Mechanics and Engineering , 2004 .

[12]  J. Oden,et al.  A Posteriori Error Estimation in Finite Element Analysis: Oden/A Posteriori , 2000 .

[13]  Carsten Carstensen,et al.  An Adaptive Mesh-Refining Algorithm Allowing for an H1 Stable L2 Projection onto Courant Finite Element Spaces , 2004 .

[14]  C. Carstensen QUASI-INTERPOLATION AND A POSTERIORI ERROR ANALYSIS IN FINITE ELEMENT METHODS , 1999 .

[15]  Rolf Rannacher,et al.  A posteriori error estimation and mesh adaptation for finite element models in elasto-plasticity , 1999 .

[16]  I. Babuska,et al.  The finite element method and its reliability , 2001 .

[17]  Carsten Carstensen,et al.  Numerical analysis of primal elastoplasticity with hardening , 2000 .

[18]  W. Dörfler A convergent adaptive algorithm for Poisson's equation , 1996 .

[19]  Wolfgang Dahmen,et al.  Adaptive Finite Element Methods with convergence rates , 2004, Numerische Mathematik.

[20]  Andreas Veeser,et al.  Convergent adaptive finite elements for the nonlinear Laplacian , 2002, Numerische Mathematik.