An efficient preconditioned Krylov subspace method for large-scale finite element equations with MPC using Lagrange multiplier method
Abstract
Purpose
The purpose of this paper is to propose an efficient iterative method for large-scale finite element equations of bad numerical stability arising from deformation analysis with multi-point constraint using Lagrange multiplier method.
Design/methodology/approach
In this paper, taking warpage analysis of polymer injection molding based on surface model as an example, the performance of several popular Krylov subspace methods, including conjugate gradient, BiCGSTAB and generalized minimal residual (GMRES), with diffident Incomplete LU (ILU)-type preconditions is investigated and compared. For controlling memory usage, GMRES(m) is also considered. And the ordering technique, commonly used in the direct method, is introduced into the presented iterative method to improve the preconditioner.
Findings
It is found that the proposed preconditioned GMRES method is robust and effective for solving problems considered in this paper, and approximate minimum degree (AMD) ordering is most beneficial for the reduction of fill-ins in the ILU preconditioner and acceleration of the convergence, especially for relatively accurate ILU-type preconditioning. And because of concerns about memory usage, GMRES(m) is a good choice if necessary.
Originality/value
In this paper, for overcoming difficulties of bad numerical stability resulting from Lagrange multiplier method, together with increasing scale of problems in engineering applications and limited hardware conditions of computer, a stable and efficient preconditioned iterative method is proposed for practical purpose. Before the preconditioning, AMD reordering, commonly used in the direct method, is introduced to improve the preconditioner. The numerical experiments show the good performance of the proposed iterative method for practical cases, which is implemented in in-house and commercial codes on PC.
Keywords
Acknowledgements
The authors would like to acknowledge the financial support from the National Natural Science Foundation Council of China (Grant No. 51125021, 51105152), the Major State Basic Research Project of China (Grant No. 2012CB025900) and the Shenzhen Basic Research Fund (Grant No. JC201005280644A, JC201105160599A).
Citation
Hu, Z., Zhang, S., Zhang, Y., Zhou, H. and Li, D. (2014), "An efficient preconditioned Krylov subspace method for large-scale finite element equations with MPC using Lagrange multiplier method", Engineering Computations, Vol. 31 No. 7, pp. 1169-1197. https://doi.org/10.1108/EC-03-2013-0077
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited