dc.contributor.author | Cernuda, Carlos | |
dc.contributor.author | Llavori, Inigo | |
dc.contributor.author | Zavoianu, Alexandru-Ciprian | |
dc.contributor.author | Aguirre, Aitor | |
dc.contributor.author | Zabala, Alaitz | |
dc.contributor.author | Plaza, Jon | |
dc.date.accessioned | 2025-04-15T11:12:00Z | |
dc.date.available | 2025-04-15T11:12:00Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-1-7281-8956-7 | en |
dc.identifier.issn | 1946-0759 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=162596 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/6961 | |
dc.description.abstract | This work presents a critical analysis of the suitability of surrogate models for finite element method application. A case study of a finite element method (FEM) structural problem was selected in order to test the performance of surrogate algorithms. A simple design of experiments (DoE) approach, based on 1D kernel density estimations, is employed to construct a representative pool of real FEM simulations, which becomes the dataset for five different surrogate models, two linear and three non-linear, whose most relevant hyperparameters were tuned (model selection). Results in a real bushing case study show that surrogate models can accurately mimic FEM simulations outcomes, in this case four types of stiffnesses (axial, radial, torsion, and cardanic). | es |
dc.language.iso | eng | en |
dc.publisher | IEEE | en |
dc.rights | © 2020 IEEE | en |
dc.subject | Design of Experiments | en |
dc.subject | Surrogate model | en |
dc.subject | Finite Element Method | en |
dc.subject | Bushing | en |
dc.subject | Support vector regression | en |
dc.subject | Random Forest | en |
dc.title | Critical Analysis of the Suitability of Surrogate Models for Finite Element Method Application in Catalog-Based Suspension Bushing Design | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) | en |
local.contributor.group | Análisis de datos y ciberseguridad | es |
local.description.peerreviewed | true | en |
local.description.publicationfirstpage | 829 | en |
local.description.publicationlastpage | 936 | en |
local.identifier.doi | https://doi.org/10.1109/ETFA46521.2020.9212166 | en |
local.source.details | 25. Vienna, 8-11 septiembre 2020 | en |
oaire.format.mimetype | application/pdf | en |
oaire.file | $DSPACE\assetstore | en |
oaire.resourceType | http://purl.org/coar/resource_type/c_c94f | en |
oaire.version | http://purl.org/coar/version/c_ab4af688f83e57aa | en |
oaire.funderName | Gobierno Vasco | en |
oaire.funderIdentifier | https://ror.org/00pz2fp31 / http://data.crossref.org/fundingdata/funder/10.13039/501100003086 | en |
oaire.fundingStream | Elkartek 2019 | en |
oaire.awardNumber | KK-2019-00022 | en |
oaire.awardTitle | Tratamiento de esfuerzos aleatorios de fatiga y optimización topológica de componentes elastómeros anti-vibratorios para la suspensión del automóvil (FATIGUE) | en |
oaire.awardURI | Sin información | en |