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Article: ONLINE ADAPTIVE ALGORITHM FOR CONSTRAINT ENERGY MINIMIZING GENERALIZED MULTISCALE DISCONTINUOUS GALERKIN METHOD

TitleONLINE ADAPTIVE ALGORITHM FOR CONSTRAINT ENERGY MINIMIZING GENERALIZED MULTISCALE DISCONTINUOUS GALERKIN METHOD
Authors
Keywordsconstraint energy minimization
discontinuous Galerkin method
multiscale finite element method
online adaptivity
Issue Date2023
Citation
Multiscale Modeling and Simulation, 2023, v. 21, n. 1, p. 168-193 How to Cite?
AbstractIn this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method. Combining the technique of oversampling, one makes use of the information of the current residuals to adaptively construct basis functions in the online stage to reduce the error of multiscale approximation. A complete analysis of the method is presented, which shows the proposed online enrichment leads to a fast convergence from multiscale approximation to the fine-scale solution. The error reduction can be made sufficiently large by suitably selecting oversampling regions and the number of oversampling layers. Further, the convergence rate of the enrichment algorithm depends on a factor of exponential decay regarding the number of oversampling layers and a user-defined parameter. Numerical results are provided to demonstrate the effectiveness and efficiency of the proposed online adaptive algorithm.
Persistent Identifierhttp://hdl.handle.net/10722/327684
ISSN
2023 Impact Factor: 1.9
2023 SCImago Journal Rankings: 1.028
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPun, Sai Mang-
dc.contributor.authorCheung, Siu Wun-
dc.date.accessioned2023-04-12T04:05:03Z-
dc.date.available2023-04-12T04:05:03Z-
dc.date.issued2023-
dc.identifier.citationMultiscale Modeling and Simulation, 2023, v. 21, n. 1, p. 168-193-
dc.identifier.issn1540-3459-
dc.identifier.urihttp://hdl.handle.net/10722/327684-
dc.description.abstractIn this research, we propose an online basis enrichment strategy within the framework of a recently developed constraint energy minimizing generalized multiscale discontinuous Galerkin method. Combining the technique of oversampling, one makes use of the information of the current residuals to adaptively construct basis functions in the online stage to reduce the error of multiscale approximation. A complete analysis of the method is presented, which shows the proposed online enrichment leads to a fast convergence from multiscale approximation to the fine-scale solution. The error reduction can be made sufficiently large by suitably selecting oversampling regions and the number of oversampling layers. Further, the convergence rate of the enrichment algorithm depends on a factor of exponential decay regarding the number of oversampling layers and a user-defined parameter. Numerical results are provided to demonstrate the effectiveness and efficiency of the proposed online adaptive algorithm.-
dc.languageeng-
dc.relation.ispartofMultiscale Modeling and Simulation-
dc.subjectconstraint energy minimization-
dc.subjectdiscontinuous Galerkin method-
dc.subjectmultiscale finite element method-
dc.subjectonline adaptivity-
dc.titleONLINE ADAPTIVE ALGORITHM FOR CONSTRAINT ENERGY MINIMIZING GENERALIZED MULTISCALE DISCONTINUOUS GALERKIN METHOD-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1137/21M1402625-
dc.identifier.scopuseid_2-s2.0-85151162444-
dc.identifier.volume21-
dc.identifier.issue1-
dc.identifier.spage168-
dc.identifier.epage193-
dc.identifier.eissn1540-3467-
dc.identifier.isiWOS:000986209700002-

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