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dc.contributor.authorCapizzi, G.
dc.contributor.authorLo Savio, F.
dc.contributor.authorLa Rosa, G.
dc.contributor.authorLo Sciuto, G.
dc.date.accessioned2017-03-30T06:39:14Z
dc.date.available2017-03-30T06:39:14Z
dc.date.issued2015
dc.identifier.citationCPEE – AMTEE 2015: Joint conference Computational Problems of Electrical Engineering and Advanced Methods of the Theory of Electrical Engineering: 6th – 8th September 2015 Třebíč, Czech Republic, p. IV-4.en
dc.identifier.isbn978-80-261-0527-5
dc.identifier.urihttp://cpee.zcu.cz/AMTEE/ArchivedProceedings.aspx
dc.identifier.urihttp://hdl.handle.net/11025/25746
dc.format1 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherZápadočeská univerzita v Plznics
dc.relation.ispartofseriesCPEE – AMTEE 2013: Joint conference Computational Problems of Electrical Engineering and Advanced Methods of the Theory of Electrical Engineeringen
dc.rights© University of West Bohemiaen
dc.subjectbulge testcs
dc.subjectrekonstrukce 3D obrazucs
dc.subjectneuronové sítěcs
dc.subjecthyperelastické materiálycs
dc.titleCreep assessment in hyperelastic material by 3D neural network reconstructor using bulge testingen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn this paper is presented a new methodology based on Neural Network which, making use of the Bulge Testing able to reconstruct the three-dimensional dome of the bulge test and also to obtain the membrane stress and strain fields of the material under investigation.en
dc.subject.translatedbulge testen
dc.subject.translated3D image reconstructionen
dc.subject.translatedneural networksen
dc.subject.translatedhyperelastic materialsen
dc.type.statusPeer-revieweden
Appears in Collections:CPEE – AMTEE 2015

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