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dc.contributor.authorCaicedo Silva, Manuel Alejandro
dc.contributor.authorMroginski, Javier L.
dc.contributor.authorToro, Sebastian
dc.contributor.authorRaschi Schaw, Marcelo
dc.contributor.authorHuespe, Alfredo Edmundo
dc.contributor.authorOliver Olivella, Xavier
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2018-03-06T11:57:29Z
dc.date.available2019-03-01T01:30:30Z
dc.date.issued2019-09
dc.identifier.citationCaicedo, M., Mroginski, J., Toro, S., Raschi, M., Huespe, A., Oliver, J. High performance reduced order modeling techniques based on optimal energy quadrature: application to geometrically non-linear multiscale inelastic material modeling. "Archives of computational methods in engineering", Setembre 2019, vol. 26, núm. 4, p. 771-792.
dc.identifier.issn1134-3060
dc.identifier.otherhttps://www.researchgate.net/publication/323249277_High_Performance_Reduced_Order_Modeling_Techniques_Based_on_Optimal_Energy_Quadrature_Application_to_Geometrically_Non-linear_Multiscale_Inelastic_Material_Modeling
dc.identifier.urihttp://hdl.handle.net/2117/114852
dc.description.abstractA High-Performance Reduced-Order Model (HPROM) technique, previously presented by the authors in the context of hierarchical multiscale models for non linear-materials undergoing infinitesimal strains, is generalized to deal with large deformation elasto-plastic problems. The proposed HPROM technique uses a Proper Orthogonal Decomposition procedure to build a reduced basis of the primary kinematical variable of the micro-scale problem, defined in terms of the micro-deformation gradient fluctuations. Then a Galerkin-projection, onto this reduced basis, is utilized to reduce the dimensionality of the micro-force balance equation, the stress homogenization equation and the effective macro-constitutive tangent tensor equation. Finally, a reduced goal-oriented quadrature rule is introduced to compute the non-affine terms of these equations. Main importance in this paper is given to the numerical assessment of the developed HPROM technique. The numerical experiments are performed on a micro-cell simulating a randomly distributed set of elastic inclusions embedded into an elasto-plastic matrix. This micro-structure is representative of a typical ductile metallic alloy. The HPROM technique applied to this type of problem displays high computational speed-ups, increasing with the complexity of the finite element model. From these results, we conclude that the proposed HPROM technique is an effective computational tool for modeling, with very large speed-ups and acceptable accuracy levels with respect to the high-fidelity case, the multiscale behavior of heterogeneous materials subjected to large deformations involving two well-separated scales of length.
dc.format.extent22 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Materials i estructures
dc.subject.lcshAlloys--Mathematical models
dc.subject.otherHigh-Performance Reduced Order Modeling (HPROM)
dc.subject.otherMultiscale Modeling
dc.subject.otherComputational Homogenization
dc.subject.otherReduced Order Quadrature (ROQ)
dc.subject.otherCOMP-DES-MAT Project
dc.subject.otherCOMPDESMAT Project
dc.titleHigh performance reduced order modeling techniques based on optimal energy quadrature: application to geometrically non-linear multiscale inelastic material modeling
dc.typeArticle
dc.subject.lemacAliatges -- Propietats mecàniques
dc.contributor.groupUniversitat Politècnica de Catalunya. RMEE - Grup de Resistència de Materials i Estructures en l'Enginyeria
dc.identifier.doi10.1007/s11831-018-9258-3
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11831-018-9258-3
dc.rights.accessOpen Access
local.identifier.drac22004025
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/320815/EU/Advanced tools for computational design of engineering materials/COMP-DES-MAT
local.citation.authorCaicedo, M.; Mroginski, J.; Toro, S.; Raschi, M.; Huespe, A.; Oliver, J.
local.citation.publicationNameArchives of computational methods in engineering
local.citation.volume26
local.citation.number4
local.citation.startingPage1
local.citation.startingPage771
local.citation.endingPage22
local.citation.endingPage792


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