A multilevel Schur complement preconditioner with ILU factorization for complex symmetric matrices

This paper describes a multilevel preconditioning technique for solving complex symmetric sparse linear systems. The coefficient matrix is first decoupled by domain decomposition and then an approximate inverse of the original matrix is computed level by level. This approximate inverse is based on low rank approximations of the local Schur complements. For this, a symmetric singular value decomposition of a complex symmetric matix is used. The block-diagonal matrices are decomposed by an incomplete LDLT factorization with the Bunch-Kaufman pivoting method. Using the example of Maxwells equations the generality of the approach is demonstrated

A multilevel Schur complement preconditioner with ILU factorization for complex symmetric matrices

This paper describes a multilevel preconditioning technique for solving complex symmetric sparse linear systems. The coefficient matrix is first decoupled by domain decomposition and then an approximate inverse of the original matrix is computed level by level. This approximate inverse is based on low rank approximations of the local Schur complements. For this, a symmetric singular value decomposition of a complex symmetric matix is used. The block-diagonal matrices are decomposed by an incomplete LDLT factorization with the Bunch-Kaufman pivoting method. Using the example of Maxwell's equations the generality of the approach is demonstrated

Stress based finite element methods for solving contact problems: comparisons between various solution methods

International audienceThis paper deals with numerical methods for solving unilateral contact problems with friction. Although these problems are usually defined in terms of the displacement, a stress based approach to the problem is developed here. The ‘‘equilibrium” finite elements method is therefore used. Using these elements make it possible to satisfy the local equilibrium condition a priori, but on the other hand, prescribed and contact forces have to be introduced using Lagrangian multipliers. The problem obtained is therefore a non-linear, constrained problem and the global system matrix is non-positive definite. Various solution algorithms are thus proposed and compared. Comparisons between the classical method and that developed here show that the stress formulation gives very satisfactory results in terms of the stresses

Heuristics for implementation of a hybrid preconditioner for interior-point methods

This article presents improvements to the hybrid preconditioner previously developed for the solution through the conjugate gradient method of the linear systems which arise from interior-point methods. The hybrid preconditioner consists of combining two preconditioners: controlled Cholesky factorization and the splitting preconditioner used in different phases of the optimization process. The first, with controlled fill-in, is more efficient at the initial iterations of the interior-point methods and it may be inefficient near a solution of the linear problem when the system is highly ill-conditioned; the second is specialized for such situation and has the opposite behavior. This approach works better than direct methods for some classes of large-scale problems. This work has proposed new heuristics for the integration of both preconditioners, identifying a new change of phases with computational results superior to the ones previously published. Moreover, the performance of the splitting preconditioner has been improved through new orderings of the constraint matrix columns allowing savings in the preconditioned conjugate gradient method iterations number. Experiments are performed with a set of large-scale problems and both approaches are compared with respect to the number of iterations and running time.57959

Fast iterative solvers for thin structures

a b s t r a c t For very large systems of equations arising from 3D finite element formulation, pre-conditioned iterative solvers are preferred over direct solvers due to their reduced memory requirements. However, in the finite-element analysis of thin structures such as beam and plate structures, iterative solvers perform poorly due to the presence of poor quality elements. In particular, their efficiency drops significantly with increase in the aspect ratio of such structures. In this paper, we propose a dual-representation based multi-grid framework for efficient iterative analysis of thin structures. The proposed iterative solvers are relatively insensitive to the quality of the elements since they exploit classical beam and plate theories to spectrally complement 3D finite element analysis. This leads to significant computational gains, as supported by the numerical experiments