A well conditioned method of fundamental solutions for laplace equation

Detalhes bibliográficos
Autor(a) principal: Antunes, Pedro R. S.
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.2/11856
Resumo: The method of fundamental solutions (MFS) is a numerical method for solving boundary value problems involving linear partial differential equations. It is well known that it can be very effective assuming regularity of the domain and boundary conditions. The main drawback of the MFS is that the matrices involved typically are ill-conditioned and this may prevent to achieve high accuracy. In this work, we propose a new algorithm to remove the ill conditioning of the classical MFS in the context of Laplace equation defined in planar domains. The main idea is to expand the MFS basis functions in terms of harmonic polynomials. Then, using the singular value decomposition and Arnoldi orthogonalization we define well conditioned basis functions spanning the same functional space as the MFS's. Several numerical examples show that this approach is much superior to previous approaches, such as the classical MFS or the MFS-QR.
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spelling A well conditioned method of fundamental solutions for laplace equationThe method of fundamental solutions (MFS) is a numerical method for solving boundary value problems involving linear partial differential equations. It is well known that it can be very effective assuming regularity of the domain and boundary conditions. The main drawback of the MFS is that the matrices involved typically are ill-conditioned and this may prevent to achieve high accuracy. In this work, we propose a new algorithm to remove the ill conditioning of the classical MFS in the context of Laplace equation defined in planar domains. The main idea is to expand the MFS basis functions in terms of harmonic polynomials. Then, using the singular value decomposition and Arnoldi orthogonalization we define well conditioned basis functions spanning the same functional space as the MFS's. Several numerical examples show that this approach is much superior to previous approaches, such as the classical MFS or the MFS-QR.The research was partially supported by FCT, Portugal, through the scientific project UIDB/00208/2020.SpringerRepositório AbertoAntunes, Pedro R. S.2023-03-23T01:30:22Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.2/11856eng1017-1398info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-16T15:40:37Zoai:repositorioaberto.uab.pt:10400.2/11856Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:51:11.365999Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A well conditioned method of fundamental solutions for laplace equation
title A well conditioned method of fundamental solutions for laplace equation
spellingShingle A well conditioned method of fundamental solutions for laplace equation
Antunes, Pedro R. S.
title_short A well conditioned method of fundamental solutions for laplace equation
title_full A well conditioned method of fundamental solutions for laplace equation
title_fullStr A well conditioned method of fundamental solutions for laplace equation
title_full_unstemmed A well conditioned method of fundamental solutions for laplace equation
title_sort A well conditioned method of fundamental solutions for laplace equation
author Antunes, Pedro R. S.
author_facet Antunes, Pedro R. S.
author_role author
dc.contributor.none.fl_str_mv Repositório Aberto
dc.contributor.author.fl_str_mv Antunes, Pedro R. S.
description The method of fundamental solutions (MFS) is a numerical method for solving boundary value problems involving linear partial differential equations. It is well known that it can be very effective assuming regularity of the domain and boundary conditions. The main drawback of the MFS is that the matrices involved typically are ill-conditioned and this may prevent to achieve high accuracy. In this work, we propose a new algorithm to remove the ill conditioning of the classical MFS in the context of Laplace equation defined in planar domains. The main idea is to expand the MFS basis functions in terms of harmonic polynomials. Then, using the singular value decomposition and Arnoldi orthogonalization we define well conditioned basis functions spanning the same functional space as the MFS's. Several numerical examples show that this approach is much superior to previous approaches, such as the classical MFS or the MFS-QR.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-03-23T01:30:22Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.2/11856
url http://hdl.handle.net/10400.2/11856
dc.language.iso.fl_str_mv eng
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dc.publisher.none.fl_str_mv Springer
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