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Title
Application of material constitutive and friction models parameters identified with AI and ALE to a CEL orthogonal cutting modelAuthor
xmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
https://ror.org/02qnnz951Version
http://purl.org/coar/version/c_970fb48d4fbd8a85
Rights
© 2023 The Authors. Published by Elsevier B.V.Access
http://purl.org/coar/access_right/c_abf2Publisher’s version
https://doi.org/10.1016/j.procir.2023.03.053Published at
Procedia CIRP Vol 117. Pp. 311-316, 2023Publisher
Elsevier B.V.Keywords
CuttingFinite element method (FEM)
Predictive model
Abstract
The identification of input parameters for funite element modelling of the cutting process is still a complex task as the experimental testing equipment cannot reach its combined levels of strains, st ... [+]
The identification of input parameters for funite element modelling of the cutting process is still a complex task as the experimental testing equipment cannot reach its combined levels of strains, strain rates and temperatures. Inverse identification using Artificial Intelligence method provides a relevant alternative. In this paper, material constitutive and friction models parameters identified with an Efficient Global Optimization algorithm and an ALE orthogonal cutting model are introduced in a CEL model. Assessment of the differences in the results due to the formulation and dependence of parameters identification to the finite element model are then performed. [-]
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Gobierno Vascoxmlui.dri2xhtml.METS-1.0.item-projectID
info:eu-repo/grantAgreement/GV/Elkartek 2022/KK-2022-00001/CAPV/Desarrollos en la nanoescala para manufactura y asistencia sanitaria/NG22Collections
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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International
