000060665 001__ 60665
000060665 005__ 20200221144220.0
000060665 0247_ $$2doi$$a10.1007/s11831-016-9197-9
000060665 0248_ $$2sideral$$a96705
000060665 037__ $$aART-2016-96705
000060665 041__ $$aeng
000060665 100__ $$aIbañez, R.
000060665 245__ $$aA Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity
000060665 260__ $$c2016
000060665 5060_ $$aAccess copy available to the general public$$fUnrestricted
000060665 5203_ $$aStandard simulation in classical mechanics is based on the use of two very different types of equations. The first one, of axiomatic character, is related to balance laws (momentum, mass, energy, ...), whereas the second one consists of models that scientists have extracted from collected, natural or synthetic data. Even if one can be confident on the first type of equations, the second one contains modeling errors. Moreover, this second type of equations remains too particular and often fails in describing new experimental results. The vast majority of existing models lack of generality, and therefore must be constantly adapted or enriched to describe new experimental findings. In this work we propose a new method, able to directly link data to computers in order to perform numerical simulations. These simulations will employ axiomatic, universal laws while minimizing the need of explicit, often phenomenological, models. This technique is based on the use of manifold learning methodologies, that allow to extract the relevant information from large experimental datasets.
000060665 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T88$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2014-51844-C2-1-2-R$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-72365-EXP
000060665 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000060665 590__ $$a5.061$$b2016
000060665 591__ $$aCOMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS$$b5 / 105 = 0.048$$c2016$$dQ1$$eT1
000060665 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b1 / 100 = 0.01$$c2016$$dQ1$$eT1
000060665 591__ $$aENGINEERING, MULTIDISCIPLINARY$$b2 / 85 = 0.024$$c2016$$dQ1$$eT1
000060665 592__ $$a1.191$$b2016
000060665 593__ $$aComputer Science Applications$$c2016$$dQ1
000060665 593__ $$aApplied Mathematics$$c2016$$dQ1
000060665 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000060665 700__ $$aAbisset-Chavanne, E.
000060665 700__ $$aAguado, J.V.
000060665 700__ $$0(orcid)0000-0003-3003-5856$$aGonzalez, D.$$uUniversidad de Zaragoza
000060665 700__ $$0(orcid)0000-0003-1017-4381$$aCueto, E.$$uUniversidad de Zaragoza
000060665 700__ $$aChinesta, F.
000060665 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000060665 773__ $$g(2016), [11 pp.]$$pArch. comput. methods eng.$$tARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING$$x1134-3060
000060665 8564_ $$s2406523$$uhttps://zaguan.unizar.es/record/60665/files/texto_completo.pdf$$yPostprint
000060665 8564_ $$s90802$$uhttps://zaguan.unizar.es/record/60665/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000060665 909CO $$ooai:zaguan.unizar.es:60665$$particulos$$pdriver
000060665 951__ $$a2020-02-21-13:14:26
000060665 980__ $$aARTICLE