DC FieldValueLanguage
dc.contributor.authorYin, Jiacong-
dc.contributor.authorVoß, Heinrich-
dc.contributor.authorChen, Pu-
dc.date.accessioned2020-07-29T12:44:22Z-
dc.date.available2020-07-29T12:44:22Z-
dc.date.issued2013-02-28-
dc.identifier.citationComputers and Structures (119): 115-124 (2013)de_DE
dc.identifier.issn0045-7949de_DE
dc.identifier.urihttp://hdl.handle.net/11420/6911-
dc.description.abstractThis paper improves the eigenpair approximations obtained from the automated multilevel substructuring (AMLS) method by subspace iterations. Two variants of AMLS hybrid Subspace Iteration Method (AMLS-SIMa and AMLS-SIMb) are proposed. AMLS-SIMa is a derivative of the basic subspace iteration by utilizing the AMLS approximations as initial vectors. AMLS-SIMb further takes advantage of the AMLS transformed block diagonal stiffness matrix to avoid factorization of the original stiffness matrix. Numerical experiments show that: (a) the error of AMLS approximate eigenpairs can be significantly reduced with just a few iteration steps; (b) AMLS-SIMb is more efficient than AMLS-SIMa with less execution time. © 2013 Elsevier Ltd. All rights reserved.en
dc.language.isoende_DE
dc.publisherElsevierde_DE
dc.relation.ispartofComputers & structuresde_DE
dc.subjectAMLSde_DE
dc.subjectEigenvaluede_DE
dc.subjectEigenvectorde_DE
dc.subjectSubspace iterationde_DE
dc.subject.ddc004: Informatikde_DE
dc.subject.ddc510: Mathematikde_DE
dc.titleImproving eigenpairs of automated multilevel substructuring with subspace iterationsde_DE
dc.typeArticlede_DE
dc.type.diniarticle-
dcterms.DCMITypeText-
tuhh.abstract.englishThis paper improves the eigenpair approximations obtained from the automated multilevel substructuring (AMLS) method by subspace iterations. Two variants of AMLS hybrid Subspace Iteration Method (AMLS-SIMa and AMLS-SIMb) are proposed. AMLS-SIMa is a derivative of the basic subspace iteration by utilizing the AMLS approximations as initial vectors. AMLS-SIMb further takes advantage of the AMLS transformed block diagonal stiffness matrix to avoid factorization of the original stiffness matrix. Numerical experiments show that: (a) the error of AMLS approximate eigenpairs can be significantly reduced with just a few iteration steps; (b) AMLS-SIMb is more efficient than AMLS-SIMa with less execution time. © 2013 Elsevier Ltd. All rights reserved.de_DE
tuhh.publisher.doi10.1016/j.compstruc.2013.01.004-
tuhh.publication.instituteMathematik E-10de_DE
tuhh.type.opus(wissenschaftlicher) Artikel-
dc.type.driverarticle-
dc.type.casraiJournal Article-
tuhh.container.volume119de_DE
tuhh.container.startpage115de_DE
tuhh.container.endpage124de_DE
dc.identifier.scopus2-s2.0-84874706167-
local.status.inpressfalsede_DE
datacite.resourceTypeJournal Article-
datacite.resourceTypeGeneralText-
item.languageiso639-1en-
item.creatorGNDYin, Jiacong-
item.creatorGNDVoß, Heinrich-
item.creatorGNDChen, Pu-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.creatorOrcidYin, Jiacong-
item.creatorOrcidVoß, Heinrich-
item.creatorOrcidChen, Pu-
item.mappedtypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
crisitem.author.deptMathematik E-10-
crisitem.author.orcid0000-0003-2394-375X-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
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