Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/53318

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dc.contributor.authorKhalfallah, Alipor
dc.contributor.authorAlves, J. L.por
dc.contributor.authorOliveira, Marta Cristinapor
dc.contributor.authorMenezes, Luís Filipepor
dc.date.accessioned2018-03-23T12:10:41Z-
dc.date.available2018-03-23T12:10:41Z-
dc.date.issued2015-
dc.identifier.issn1569-190Xpor
dc.identifier.urihttps://hdl.handle.net/1822/53318-
dc.description.abstractThis work presents an investigation into the effect of the number and type of experimental input data used in parameter identification of Hill’48, Barlat’91 (Yld91) and Cazacu and Barlat’2001 (CB2001) yield criteria on the accuracy of the finite element simulation results. Different sets of experimental data are used to identify the anisotropy parameters of two metal sheets, exhibiting different anisotropic behaviour and hardening characteristics: a mild steel (DC06) and an aluminium alloy (AA6016-T4). Although it has been shown that the CB2001 yield criterion can lead to an accurate description of anisotropic behaviour of metallic sheets, its calibration requires a large set of experimental input data. A calibration procedure is proposed for CB2001 based on a reduced set of experimental data, i.e. where the results are limited to three uniaxial tensile tests, combined with artificial data obtained using the Barlat’91 yield criterion. Evaluation of the predictive capacity of the studied yield criteria, calibrated using different sets of experimental data, is made by comparing finite element simulation results with experimental results for the deep drawing of a crossshaped part. A satisfying agreement is observed between experimental and numerical thickness distributions, with a negligible effect of the number and type of experimental data for the Hill’48 and Yld91 yield criteria. On the contrary, CB2001 calibration is quite sensitive to the experimental data available, particularly biaxial values. Nevertheless, CB2001 calibration based on the combination of effective and artificial experimental data achieves satisfying results, which in the worst case are similar to the ones obtained with the Yld91.por
dc.description.sponsorshipThe authors gratefully acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) via the projects PTDC/EMS-TEC/1805/2012 and PEst-C/EME/UI0285/2013 and by FEDER funds through the program COMPETE – Programa Operacional Factores de Competitividade, under the project CENTRO-07-0224-FEDER-002001 (MT4MOBI). The first author is also grateful for the Post-Doc grant.por
dc.language.isoengpor
dc.publisherElsevier 1por
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/127168/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/COMPETE/127168/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/COMPETE/132998/PTpor
dc.rightsopenAccesspor
dc.subjectConstitutive modellingpor
dc.subjectParameter identificationpor
dc.subjectPlastic anisotropypor
dc.subjectSheet metal formingpor
dc.titleInfluence of the characteristics of the experimental data set used to identify anisotropy parameterspor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionwww.elsevier.com/locate/simpatpor
oaire.citationStartPage15por
oaire.citationEndPage44por
oaire.citationVolume53por
dc.identifier.eissn1878-1462por
dc.identifier.doi10.1016/j.simpat.2015.02.007por
dc.subject.fosEngenharia e Tecnologia::Engenharia Mecânicapor
dc.description.publicationversioninfo:eu-repo/semantics/publishedVersionpor
dc.subject.wosScience & Technologypor
sdum.journalSimulation Modelling Practice and Theorypor
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