Adaptive multigrid for finite element computations in plasticity

Abstract The solution of the system of equilibrium equations is the most time-consuming part in large-scale finite element computations of plasticity problems. The development of efficient solution methods are therefore of utmost importance to the field of computational plasticity. Traditionally, direct solvers have most frequently been used. However, recent developments of iterative solvers and preconditioners may impose a change. In particular, preconditioning by the multigrid technique is especially favorable in FE applications. The multigrid preconditioner uses a number of nested grid levels to improve the convergence of the iterative solver. Prolongation of fine-grid residual forces is done to coarser grids and computed corrections are interpolated to the fine grid such that the fine-grid solution successively is improved. By this technique, large 3D problems, invincible for solvers based on direct methods, can be solved in acceptable time at low memory requirements. By means of a posteriori error estimates the computational grid could successively be refined (adapted) until the solution fulfils a predefined accuracy level. In contrast to procedures where the preceding grids are erased, the previously generated grids are used in the multigrid algorithm to speed up the solution process. The paper presents results using the adaptive multigrid procedure to plasticity problems. In particular, different error indicators are tested.

[1]  Harold Liebowitz,et al.  Examples of adaptive FEA in plasticity , 1995 .

[2]  Nils-Erik Wiberg,et al.  Adaptive FE-Simulations In 3D Using Multigrid Solver , 2003 .

[3]  O. C. Zienkiewicz,et al.  Recovery procedures in error estimation and adaptivity. Part II: Adaptivity in nonlinear problems of elasto-plasticity behaviour , 1999 .

[4]  Gene H. Golub,et al.  A Note on Preconditioning for Indefinite Linear Systems , 1999, SIAM J. Sci. Comput..

[5]  David R. Owen,et al.  A non-nested Galerkin multi-grid method for solving linear and nonlinear solid mechanics problems , 1997 .

[6]  H. Saunders,et al.  Finite element procedures in engineering analysis , 1982 .

[7]  O. Axelsson Iterative solution methods , 1995 .

[8]  D. Brandt,et al.  Multi-level adaptive solutions to boundary-value problems math comptr , 1977 .

[9]  J. Z. Zhu,et al.  The finite element method , 1977 .

[10]  J. Hall,et al.  The multigrid method in solid mechanics: Part I—Algorithm description and behaviour , 1990 .

[11]  Peter Bettess,et al.  ERROR ESTIMATES AND ADAPTIVE REMESHING TECHNIQUES IN ELASTO–PLASTICITY , 1997 .

[12]  R. Fletcher Practical Methods of Optimization , 1988 .

[13]  J. Z. Zhu,et al.  The superconvergent patch recovery and a posteriori error estimates. Part 1: The recovery technique , 1992 .

[14]  Mark F. Adams,et al.  Parallel multigrid solvers for 3D unstructured finite element problems in large deformation elasticity and plasticity , 2000 .

[15]  Ivo Babuška,et al.  Validation of A-Posteriori Error Estimators by Numerical Approach , 1994 .

[16]  I. Duff,et al.  Direct Methods for Sparse Matrices , 1987 .

[17]  Jun Zhang,et al.  Enhanced multi-level block ILU preconditioning strategies for general sparse linear systems , 2001 .

[18]  Richard Barrett,et al.  Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods , 1994, Other Titles in Applied Mathematics.

[19]  Claes Johnson,et al.  Computational Differential Equations , 1996 .