A GenEO Domain Decomposition method for Saddle Point problems

We introduce an adaptive element-based domain decomposition (DD) method for solving saddle point problems defined as a block two by two matrix. The algorithm does not require any knowledge of the constrained space. We assume that all sub matrices are sparse and that the diagonal blocks are spectrall...

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Main Authors: Nataf, Frédéric, Tournier, Pierre-Henri
Format: Article
Language:English
Published: Académie des sciences 2023-03-01
Series:Comptes Rendus. Mécanique
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Online Access:https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.175/
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author Nataf, Frédéric
Tournier, Pierre-Henri
author_facet Nataf, Frédéric
Tournier, Pierre-Henri
author_sort Nataf, Frédéric
collection DOAJ
description We introduce an adaptive element-based domain decomposition (DD) method for solving saddle point problems defined as a block two by two matrix. The algorithm does not require any knowledge of the constrained space. We assume that all sub matrices are sparse and that the diagonal blocks are spectrally equivalent to a sum of positive semi definite matrices. The latter assumption enables the design of adaptive coarse space for DD methods that extends the GenEO theory (Spillane et al., 2014) to saddle point problems. Numerical results on three dimensional elasticity problems for steel-rubber structures discretized by a finite element with continuous pressure are shown for up to one billion degrees of freedom.
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spelling doaj-art-ee419badfea24572aa09d0e73ce281992025-02-07T13:46:20ZengAcadémie des sciencesComptes Rendus. Mécanique1873-72342023-03-01351S166768410.5802/crmeca.17510.5802/crmeca.175A GenEO Domain Decomposition method for Saddle Point problemsNataf, Frédéric0https://orcid.org/0000-0003-2813-3481Tournier, Pierre-Henri1Laboratoire J.L. Lions, Sorbonne Université, 4 place Jussieu FranceLaboratoire J.L. Lions, Sorbonne Université, 4 place Jussieu FranceWe introduce an adaptive element-based domain decomposition (DD) method for solving saddle point problems defined as a block two by two matrix. The algorithm does not require any knowledge of the constrained space. We assume that all sub matrices are sparse and that the diagonal blocks are spectrally equivalent to a sum of positive semi definite matrices. The latter assumption enables the design of adaptive coarse space for DD methods that extends the GenEO theory (Spillane et al., 2014) to saddle point problems. Numerical results on three dimensional elasticity problems for steel-rubber structures discretized by a finite element with continuous pressure are shown for up to one billion degrees of freedom.https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.175/domain decomposition methodnearly incompressible elasticityhigh performance computingsaddle point problemcoarse spacemultiscale finite elementSchur complement
spellingShingle Nataf, Frédéric
Tournier, Pierre-Henri
A GenEO Domain Decomposition method for Saddle Point problems
Comptes Rendus. Mécanique
domain decomposition method
nearly incompressible elasticity
high performance computing
saddle point problem
coarse space
multiscale finite element
Schur complement
title A GenEO Domain Decomposition method for Saddle Point problems
title_full A GenEO Domain Decomposition method for Saddle Point problems
title_fullStr A GenEO Domain Decomposition method for Saddle Point problems
title_full_unstemmed A GenEO Domain Decomposition method for Saddle Point problems
title_short A GenEO Domain Decomposition method for Saddle Point problems
title_sort geneo domain decomposition method for saddle point problems
topic domain decomposition method
nearly incompressible elasticity
high performance computing
saddle point problem
coarse space
multiscale finite element
Schur complement
url https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.175/
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