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dc.contributor.authorPerez Guisado, Ion
dc.contributor.authorARRAZOLA, PEDRO JOSE
dc.contributor.authorMadariaga, Aitor
dc.contributor.authorCUESTA ZABALAJAUREGUI, MIKEL
dc.contributor.authorSoriano Moreno, Denis
dc.date.accessioned2020-10-06T14:53:24Z
dc.date.available2020-10-06T14:53:24Z
dc.date.issued2021
dc.identifier.issn0020-7403en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=160058en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/1848
dc.description.abstractMachining operations affect the properties of the final surface layer, and these can impact on its functional per- formance, particularly on fatigue behaviour. Among the properties of the machined surface, surface topography is one major parameter affecting fatigue behaviour. The literature review has demonstrated that stress concen- tration factors K t of the surface provide a more reliable estimation of the impact on the fatigue behaviour of machined components. Finite Element (FE) simulations can accurately calculate the stress concentration factor of machined surfaces, but they incur a high computational cost. Recent advances have shown that analytical models can reliably determine stress concentration factors of 2D roughness profiles. However, analytical models that predict stress concentration factors of 3D surface topographies are still lacking. This paper is aimed at devel- oping an analytical method to calculate the stress concentration factor K t of 3D surfaces generated by machining operations. To validate the model, a specimen of 7475-T7351 aluminium alloy was face milled and its surface topography was characterised using an Alicona IFG4 profilometer. Stress concentration factors were calculated in the selected surface regions using the proposed analytical model, and later compared to results obtained by FE simulations. The mean difference in the stress concentration factor K t calculated by the proposed analytical and FE models is of 1.53%. Importantly, the developed analytical model reduces the computing time by 3000 times compared to FE models, and enables the analysis of larger surfaces.en
dc.description.sponsorshipGobierno Vascoes
dc.language.isoengen
dc.publisherElsevier Ltd.en
dc.rights© 2020 Elsevier Ltd.en
dc.subjectSurface topographyen
dc.subjectStress concentration factoren
dc.subjectFatigueen
dc.subjectModellingen
dc.titleAn analytical approach to calculate stress concentration factors of machined surfacesen
dcterms.accessRightshttp://purl.org/coar/access_right/c_f1cfen
dcterms.sourceInternational Journal of Mechanical Sciencesen
local.contributor.groupMecanizado de alto rendimientoes
local.description.peerreviewedtrueen
local.identifier.doihttps://doi.org/10.1016/j.ijmecsci.2020.106040en
local.relation.projectIDGV/Elkartek 2019/KK-2019-00077/CAPV/Superficies multifuncionales en la frontera del conocimiento/FRONTIERS Ven
local.embargo.enddate2023-01-31
local.source.detailsVol. 190. N. artículo 106040, 2021en
oaire.format.mimetypeapplication/pdf
oaire.file$DSPACE\assetstore
oaire.resourceTypehttp://purl.org/coar/resource_type/c_6501en
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaen


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