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Estimator reduction and convergence of adaptive BEM

A posteriori error estimation and related adaptive mesh-refining algorithms have themselves proven to be powerful tools in nowadays scientific computing. Contrary to adaptive finite element methods, convergence of adaptive boundary element schemes is, however, widely open. We propose a relaxed notio...

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Detalles Bibliográficos
Autores principales: Aurada, Markus, Ferraz-Leite, Samuel, Praetorius, Dirk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: North-Holland 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3587349/
https://www.ncbi.nlm.nih.gov/pubmed/23482248
http://dx.doi.org/10.1016/j.apnum.2011.06.014
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author Aurada, Markus
Ferraz-Leite, Samuel
Praetorius, Dirk
author_facet Aurada, Markus
Ferraz-Leite, Samuel
Praetorius, Dirk
author_sort Aurada, Markus
collection PubMed
description A posteriori error estimation and related adaptive mesh-refining algorithms have themselves proven to be powerful tools in nowadays scientific computing. Contrary to adaptive finite element methods, convergence of adaptive boundary element schemes is, however, widely open. We propose a relaxed notion of convergence of adaptive boundary element schemes. Instead of asking for convergence of the error to zero, we only aim to prove estimator convergence in the sense that the adaptive algorithm drives the underlying error estimator to zero. We observe that certain error estimators satisfy an estimator reduction property which is sufficient for estimator convergence. The elementary analysis is only based on Dörfler marking and inverse estimates, but not on reliability and efficiency of the error estimator at hand. In particular, our approach gives a first mathematical justification for the proposed steering of anisotropic mesh-refinements, which is mandatory for optimal convergence behavior in 3D boundary element computations.
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spelling pubmed-35873492013-03-06 Estimator reduction and convergence of adaptive BEM Aurada, Markus Ferraz-Leite, Samuel Praetorius, Dirk Appl Numer Math Article A posteriori error estimation and related adaptive mesh-refining algorithms have themselves proven to be powerful tools in nowadays scientific computing. Contrary to adaptive finite element methods, convergence of adaptive boundary element schemes is, however, widely open. We propose a relaxed notion of convergence of adaptive boundary element schemes. Instead of asking for convergence of the error to zero, we only aim to prove estimator convergence in the sense that the adaptive algorithm drives the underlying error estimator to zero. We observe that certain error estimators satisfy an estimator reduction property which is sufficient for estimator convergence. The elementary analysis is only based on Dörfler marking and inverse estimates, but not on reliability and efficiency of the error estimator at hand. In particular, our approach gives a first mathematical justification for the proposed steering of anisotropic mesh-refinements, which is mandatory for optimal convergence behavior in 3D boundary element computations. North-Holland 2012-06 /pmc/articles/PMC3587349/ /pubmed/23482248 http://dx.doi.org/10.1016/j.apnum.2011.06.014 Text en © 2012 Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/3.0/ Open Access under CC BY-NC-ND 3.0 (https://creativecommons.org/licenses/by-nc-nd/3.0/) license
spellingShingle Article
Aurada, Markus
Ferraz-Leite, Samuel
Praetorius, Dirk
Estimator reduction and convergence of adaptive BEM
title Estimator reduction and convergence of adaptive BEM
title_full Estimator reduction and convergence of adaptive BEM
title_fullStr Estimator reduction and convergence of adaptive BEM
title_full_unstemmed Estimator reduction and convergence of adaptive BEM
title_short Estimator reduction and convergence of adaptive BEM
title_sort estimator reduction and convergence of adaptive bem
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3587349/
https://www.ncbi.nlm.nih.gov/pubmed/23482248
http://dx.doi.org/10.1016/j.apnum.2011.06.014
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