Spectral ACMS: A robust localized Approximated Component Mode Synthesis Method

Fuente: arXiv
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Auteurs principaux: Madureira, Alexandre L., Sarkis, Marcus
Format: Preprint
Publié: 2017
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author Madureira, Alexandre L.
Sarkis, Marcus
author_facet Madureira, Alexandre L.
Sarkis, Marcus
contents We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients. The methods are of Galerkin type and follow the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into \emph{multiscale} and \emph{fine} subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based on corners used on primal iterative substructuring methods, to functions of global minimal energy. This approach delivers quasi-optimal a priori error energy approximation with respect to the mesh size, but it is not robust with respect to high-contrast coefficients. In a second method, edge modes based on local generalized eigenvalue problems are added to the corner modes. As a result, optimal a priori error energy estimate is achieved which is mesh and contrast independent. The methods converge at optimal rate even if the solution has minimum regularity, belonging only to the Sobolev space $H^1$.
format Preprint
id arxiv_https___arxiv_org_abs_1709_04044
institution arXiv
publishDate 2017
record_format arxiv
spellingShingle Spectral ACMS: A robust localized Approximated Component Mode Synthesis Method
Madureira, Alexandre L.
Sarkis, Marcus
Numerical Analysis
65N55, 65N30
We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\infty$ coefficients. The methods are of Galerkin type and follow the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into \emph{multiscale} and \emph{fine} subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based on corners used on primal iterative substructuring methods, to functions of global minimal energy. This approach delivers quasi-optimal a priori error energy approximation with respect to the mesh size, but it is not robust with respect to high-contrast coefficients. In a second method, edge modes based on local generalized eigenvalue problems are added to the corner modes. As a result, optimal a priori error energy estimate is achieved which is mesh and contrast independent. The methods converge at optimal rate even if the solution has minimum regularity, belonging only to the Sobolev space $H^1$.
title Spectral ACMS: A robust localized Approximated Component Mode Synthesis Method
topic Numerical Analysis
65N55, 65N30
url https://arxiv.org/abs/1709.04044