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dc.creatorBuljak, Vladimir
dc.creatorCocchetti, Giuseppe
dc.creatorCornaggia, Aram
dc.creatorMaier, Giulio
dc.date.accessioned2022-09-19T18:32:27Z
dc.date.available2022-09-19T18:32:27Z
dc.date.issued2018
dc.identifier.issn0025-6455
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/2895
dc.description.abstractSmall Punch Tests (SPT) are, at present, frequently employed for diagnostic analyses of metallic structural components and are considered in codes of practice because the damage generated by miniature specimen extraction is small (quasi-non-destructive tests). This paper contains a description of the following contributions for improvement in the state-of-the-art of SPT practice: assessment of material parameters through inverse analysis, made faster and more economical by employing model reduction through a Proper Orthogonal Decomposition (POD) procedure. The methodology is developed to assess material parameters entering into diverse constitutive models, thus resulting in a more flexible identification framework, capable of addressing different kinds of material behaviour. Within the paper, real experimental data are used and comparisons of computed stress-strain curves with experimentally measured ones, through typical tensile tests, show an excellent agreement.en
dc.publisherSpringer, Dordrecht
dc.relationEuropean Union under REA grant [PITN-GA-2013-606878]
dc.relationItalian National Academy Accademia Nazionale dei Lincei, Centro Linceo Interdisciplinare "Beniamino Segre"
dc.rightsrestrictedAccess
dc.sourceMeccanica
dc.subjectStructural diagnosisen
dc.subjectSmall Punch Testen
dc.subjectProper Orthogonal Decompositionen
dc.subjectMaterial characterizationen
dc.subjectInverse analysisen
dc.subjectElastoplastic parameters identificationen
dc.titleParameter identification in elastoplastic material models by Small Punch Tests and inverse analysis with model reductionen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage3829
dc.citation.issue15
dc.citation.other53(15): 3815-3829
dc.citation.rankM22
dc.citation.spage3815
dc.citation.volume53
dc.identifier.doi10.1007/s11012-018-0914-3
dc.identifier.scopus2-s2.0-85056330007
dc.identifier.wos000450517500013
dc.type.versionpublishedVersion


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