Improved Parallel Preconditioners for Multidisciplinary Topology Optimisations

dc.authorid Akay, Hasan U/0000-0003-2574-9942
dc.authorid Sivas, Abdullah Ali/0000-0002-5263-1889
dc.authorscopusid 24532717000
dc.authorscopusid 6701403522
dc.authorscopusid 23994437100
dc.authorscopusid 57190301046
dc.authorwosid Akay, Hasan U/ABI-3992-2020
dc.authorwosid Manguoglu, Murat/ABB-6236-2020
dc.authorwosid Sivas, Abdullah Ali/ABD-7944-2020
dc.contributor.author Akay, H. U.
dc.contributor.author Oktay, E.
dc.contributor.author Manguoglu, M.
dc.contributor.author Sivas, A. A.
dc.contributor.other Automotive Engineering
dc.date.accessioned 2024-07-05T14:29:36Z
dc.date.available 2024-07-05T14:29:36Z
dc.date.issued 2016
dc.department Atılım University en_US
dc.department-temp [Akay, H. U.] Atilim Univ, Dept Mech Engn, Ankara, Turkey; [Oktay, E.] EDA Engn Design & Anal Ltd Co, ODTU Teknokent, Ankara, Turkey; [Manguoglu, M.] Middle East Tech Univ, Dept Comp Engn, Ankara, Turkey; [Manguoglu, M.; Sivas, A. A.] Middle East Tech Univ, Inst Appl Math, Ankara, Turkey en_US
dc.description Akay, Hasan U/0000-0003-2574-9942; Sivas, Abdullah Ali/0000-0002-5263-1889 en_US
dc.description.abstract Two commonly used preconditioners were evaluated for parallel solution of linear systems of equations with high condition numbers. The test cases were derived from topology optimisation applications in multiple disciplines, where the material distribution finite element methods were used. Because in this optimisation method, the equations rapidly become ill-conditioned due to disappearance of large number of elements from the design space as the optimisations progresses, it is shown that the choice for a suitable preconditioner becomes very crucial. In an earlier work the conjugate gradient (CG) method with a Block-Jacobi preconditioner was used, in which the number of CG iterations increased rapidly with the increasing number processors. Consequently, the parallel scalability of the method deteriorated fast due to the increasing loss of interprocessor information among the increased number of processors. By replacing the Block-Jacobi preconditioner with a sparse approximate inverse preconditioner, it is shown that the number of iterations to converge became independent of the number of processors. Therefore, the parallel scalability is improved. en_US
dc.description.sponsorship Turkish Academy of Sciences [TUBA-GEBIP/2012-19]; Scientific and Technological Research Council of Turkey [EDA/TUBITAK-TEYDEB/3120299] en_US
dc.description.sponsorship This work was partially supported by The Turkish Academy of Sciences for a Distinguished Young Scientist Award [grant number M.M./TUBA-GEBIP/2012-19] and The Scientific and Technological Research Council of Turkey [grant number EDA/TUBITAK-TEYDEB/3120299]. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.1080/10618562.2016.1205737
dc.identifier.endpage 336 en_US
dc.identifier.issn 1061-8562
dc.identifier.issn 1029-0257
dc.identifier.issue 4 en_US
dc.identifier.scopus 2-s2.0-84979030191
dc.identifier.scopusquality Q3
dc.identifier.startpage 329 en_US
dc.identifier.uri https://doi.org/10.1080/10618562.2016.1205737
dc.identifier.uri https://hdl.handle.net/20.500.14411/538
dc.identifier.volume 30 en_US
dc.identifier.wos WOS:000382939400003
dc.identifier.wosquality Q4
dc.institutionauthor Akay, Hasan Umur
dc.language.iso en en_US
dc.publisher Taylor & Francis Ltd en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 1
dc.subject Topology optimisation en_US
dc.subject parallel methods en_US
dc.subject parallel scalability en_US
dc.subject iterative solvers en_US
dc.subject preconditioners en_US
dc.subject conjugate gradient en_US
dc.subject Block-Jacobi en_US
dc.subject sparse approximate inverse en_US
dc.title Improved Parallel Preconditioners for Multidisciplinary Topology Optimisations en_US
dc.type Article en_US
dc.wos.citedbyCount 0
dspace.entity.type Publication
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