Detailed study on the behavior of improved beam t-junctions modeling for the characterization of tubular structures, based on artificial neural networks trained with finite element models

dc.contributor.author	Badea, F.
dc.contributor.author	Pérez Fernández, Jesús Ángel
dc.contributor.author	Olazagoitia, J. L.
dc.date.accessioned	2021-07-26T07:50:16Z
dc.date.available	2021-07-26T07:50:16Z
dc.date.issued	2021
dc.identifier.citation	Mathematics, 9(9) (2021); doi:10.3390/math9090943
dc.identifier.issn	2227-7390
dc.identifier.uri	http://hdl.handle.net/10651/59966
dc.description.sponsorship	This research was partially funded by the Agencia Estatal de Investigación [grant RETOS 2018-RTI2018-095923-B-C22] and by the Cátedra Global Nebrija-Santander en Recuperación de Energía en el Transporte de Superficie.
dc.language.iso	eng
dc.relation.ispartof	Mathematics
dc.rights	© 2021 los autores
dc.rights	CC Reconocimiento 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105335948&doi=10.3390%2fmath9090943&partnerID=40&md5=b79bf3ea8771134e4c61289089e2746e
dc.title	Detailed study on the behavior of improved beam t-junctions modeling for the characterization of tubular structures, based on artificial neural networks trained with finite element models
dc.type	journal article
dc.identifier.doi	10.3390/math9090943
dc.relation.projectID	AEI/RETOS 2018-RTI2018-095923-B-C22
dc.relation.publisherversion	http://dx.doi.org/10.3390/math9090943
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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