Experimental and simulation study of compose panels inelastic behavior using Artificial Neural Networks

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datacite.alternateIdentifier.citationINFORMES DE LA CONSTRUCCION,Vol.72,,2020
datacite.alternateIdentifier.doi10.3989/ic.70957
datacite.creatorBarreto Cordero, Wilmer
datacite.creatorPicón Rodríguez, Ricardo
datacite.date2020
datacite.subject.englishDamage
datacite.subject.englishArtificial Neural Networks
datacite.subject.englishno lineal behavior
datacite.subject.englishcompose panels
datacite.subject.englishno traditional structures
datacite.subject.englishpermanent displacement
datacite.subject.englishexperimental test subject to bending
datacite.titleExperimental and simulation study of compose panels inelastic behavior using Artificial Neural Networks
dc.date.accessioned2021-04-30T17:07:20Z
dc.date.available2021-04-30T17:07:20Z
dc.description.abstractThe analysis of complex structures, such as panels composed of various materials, is difficult to model due to the variability in the mechanical properties of the materials. The foregoing, coupled with non-linearity in the behavior of materials, makes the application of traditional numerical methods difficult and highly demanding in computational time. The present work introduces a less conventional technique like the artificial neural networks (ANN) for the modeling of the permanent deformation and damages in a compose slab subjected to flexion. 400 ANN models were trained and verified, which were able to model the non-linearity of the structural element, successfully reproduce the damages due to cracking and buckling of the panel, as well as reproduce the global permanent deformation of the element.
dc.identifier.urihttp://repositoriodigital.uct.cl/handle/10925/4101
dc.language.isoes
dc.publisherCONSEJO SUPERIOR INVESTIGACIONES CIENTIFICAS-CSIC
dc.sourceINFORMES DE LA CONSTRUCCION
oaire.resourceTypeArticle
uct.catalogadorWOS
uct.indizacionSCI
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