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dc.contributor.authorPIERQUIN, Antoine
dc.contributor.authorHENNERON, Thomas
dc.contributor.author
 hal.structure.identifier
CLENET, Stephane
13338 Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
dc.date.accessioned2018
dc.date.available2018
dc.date.issued2017
dc.date.submitted2018
dc.identifier.issn0018-9464
dc.identifier.urihttp://hdl.handle.net/10985/12497
dc.description.abstractAmong the model order reduction techniques, the Proper Orthogonal Decomposition (POD) has shown its efficiency to solve magnetostatic and magneto-quasistatic problems in the time domain. However, the POD is intrusive in the sense that it requires the extraction of the matrix system of the full model to build the reduced model. To avoid this extraction, nonintrusive approaches like the Data Driven (DD) methods enable to approximate the reduced model without the access to the full matrix system. In this article, the DD-POD method is applied to build a low dimensional system to solve a magnetostatic problem coupled with electric circuit equations.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.rightsPost-print
dc.subjectData driven
dc.subjectfinite element model
dc.subjectmodel order reduction
dc.titleData-Driven Model Order Reduction for Magnetostatic Problem Coupled with Circuit Equations
dc.identifier.doi10.1109/TMAG.2017.2771358
dc.typdocArticle dans une revue avec comité de lecture
dc.localisationCentre de Lille
dc.subject.halMathématique: Analyse numérique
dc.subject.halSciences de l'ingénieur: Electromagnétisme
dc.subject.halSciences de l'ingénieur: Energie électrique
ensam.audienceNon spécifiée
ensam.page1-4
ensam.journalIEEE Transactions on Magnetics
ensam.peerReviewingOui
hal.identifierhal-01691190
hal.version1
hal.statusaccept


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