Erregistro soila

dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.contributor.authorARRAZOLA, PEDRO JOSE
dc.contributor.otherMalkorra Sarasola, Irati
dc.contributor.otherSouli, Hanéne
dc.contributor.otherSalvatore, Ferdinando
dc.contributor.otherRech, Joël
dc.contributor.otherRolet, Jason
dc.contributor.otherMathis, Aude
dc.date.accessioned2023-05-26T08:02:18Z
dc.date.available2023-05-26T08:02:18Z
dc.date.issued2022
dc.identifier.issn2212-8271en
dc.identifier.otherhttps://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=172556en
dc.identifier.urihttps://hdl.handle.net/20.500.11984/6084
dc.description.abstractDrag finishing is one of the mass finishing processes that enhances surface roughness on complex and rough parts produced by additive manufacturing. This paper proposes a model to simulate abrasive media flowing around the part at a macroscopic scale based on an original rheological model inspired by civil engineering techniques. The correlation between the evolution of the surface roughness and numerical results reveals the high sensitivity of the process to media’s rheological behaviour and the surface orientation of the surface regarding media flow. This model provides a better understanding of the physical mechanisms (chip formation or plastic deformation) induced at the surface during polishing, and it helps choosing the optimal finishing conditions.en
dc.language.isoengen
dc.publisherElsevier B.V.en
dc.rights© 2022 The Authors. Published by Elsevier B.V.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPolishingen
dc.subjectdrag finishingen
dc.subjectsurface roughnessen
dc.subjectRheologyen
dc.subjectNumerical simulationen
dc.titleNumerical modelling of the drag finishing process at a macroscopic scale to optimize surface roughness improvement on additively manufactured (SLM) Inconel 718 partsen
dcterms.accessRightshttp://purl.org/coar/access_right/c_abf2en
dcterms.sourceProcedia CIRP.en
local.contributor.groupMecanizado de alto rendimientoes
local.description.peerreviewedtrueen
local.description.publicationfirstpage648en
local.description.publicationlastpage653en
local.identifier.doihttps://doi.org/10.1016/j.procir.2022.01.002en
local.contributor.otherinstitutionhttps://ror.org/01rk35k63es
local.contributor.otherinstitutionhttps://ror.org/0199zgv94es
local.contributor.otherinstitutionNaval Group CESMANes
local.source.detailsVol. 108. N. C. Pp. 648-653, 2022en
oaire.format.mimetypeapplication/pdfen
oaire.file$DSPACE\assetstoreen
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94fen
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85en


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Attribution-NonCommercial-NoDerivatives 4.0 International
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