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dc.contributor.authorBurczynski, T.
dc.contributor.authorDlugosz, A.
dc.date.accessioned2020-07-02T16:18:55Z
dc.date.available2020-07-02T16:18:55Z
dc.date.issued2013
dc.identifier.isbn978-84-941407-6-1
dc.identifier.urihttp://hdl.handle.net/2117/192341
dc.description.abstractThis paper proposes a multiobjective optimization approach for designing selected coupled-field models. The optimization method is based on evolutionary algorithm (EA). Proposed technique overtakes one of the most popular multiobjective evolutionary algorithm NSGAII [5,6] on several benchmark and engineering problems. Coupling between electrical, thermal and mechanical fields is considered. Finite element method (FEM) is used to simulate direct coupled problems numerically. The software packages based on FEM are adapted to create the optimization system. Suitable interfaces between optimization algorithm and the FEM software are created. They use internal script languages embedded in preprocesors of the FEM systems. Different types of functionals are formulated on the basis of the results obtained from coupled-field analysis. Functionals depending on the volume of the structure are also proposed. Parametric NURBS curves are used to model some optimized structures. Numerical examples for bi-objective and three-objective optimization problems are presented.
dc.format.extent12 p.
dc.language.isoeng
dc.publisherCIMNE
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits
dc.subject.lcshFinite element method
dc.subject.lcshCoupled problems (Complex systems) -- Numerical solutions
dc.subject.othermultiobjective optimization, evolutionary algorithm, multiphysics, actuators, MEMS, finite element method.
dc.titleIntelligent computing in optimization of coupled problems
dc.typeConference report
dc.subject.lemacElements finits, Mètode dels
dc.rights.accessOpen Access
local.citation.contributorCOUPLED V
local.citation.publicationNameCOUPLED V : proceedings of the V International Conference on Computational Methods for Coupled Problems in Science and Engineering :
local.citation.startingPage387
local.citation.endingPage398


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