000095864 001__ 95864 000095864 005__ 20201022121026.0 000095864 0247_ $$2doi$$a10.1063/1.5112643 000095864 0248_ $$2sideral$$a115942 000095864 037__ $$aART-2019-115942 000095864 041__ $$aeng 000095864 100__ $$0(orcid)0000-0003-3003-5856$$aGonzález, D.$$uUniversidad de Zaragoza 000095864 245__ $$aData-driven correction of models for deformable solids 000095864 260__ $$c2019 000095864 5060_ $$aAccess copy available to the general public$$fUnrestricted 000095864 5203_ $$aUnveiling physical laws from data is seen as the ultimate sign of human intelligence. While there is a growing interest in this sense around the machine learning community, some recent works have attempted to simply substitute physical laws by data. We believe that getting rid of centuries of scientific knowledge is simply nonsense. There are models whose validity and usefulness is out of any doubt, so try to substitute them by data seems to be a waste of knowledge. While it is true that fitting well-known physical laws to experimental data is sometimes a painful process, a good theory continues to be practical and provide useful insights to interpret the phenomena taking place. That is why we present here a method to construct, based on data, automatic corrections to existing models. Emphasis is put in the correct thermodynamic character of these corrections, so as to avoid violations of first principles such as the laws of thermodynamics. These corrections are sought under the umbrella of the GENERIC framework [M. Grmela and H. Ch. Oettinger, Dynamics and thermodynamics of complex fluids. I. Development of a general formalism. Phys. Rev. E 56, 6620, 1997], a generalization of Hamiltonian mechanics to non-equilibrium thermodynamics. This framework ensures the satisfaction of the first and second laws of thermodynamics, while providing a very appealing context for the proposed automated correction of existing laws. In this work we focus on solid mechanics, particularly large strain (visco-) hyperelasticity. 000095864 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T24-17R$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2017-85139-C2-1-R 000095864 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000095864 592__ $$a0.19$$b2019 000095864 593__ $$aPhysics and Astronomy (miscellaneous)$$c2019 000095864 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000095864 700__ $$aChinesta, F. 000095864 700__ $$0(orcid)0000-0003-1017-4381$$aCueto, E.$$uUniversidad de Zaragoza 000095864 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est. 000095864 773__ $$g2113 (2019), 100010 [4 pp.]$$pAIP conf. proc.$$tAIP Conference Proceedings$$x0094-243X 000095864 8564_ $$s107716$$uhttps://zaguan.unizar.es/record/95864/files/texto_completo.pdf$$yPostprint 000095864 8564_ $$s396730$$uhttps://zaguan.unizar.es/record/95864/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000095864 909CO $$ooai:zaguan.unizar.es:95864$$particulos$$pdriver 000095864 951__ $$a2020-10-22-11:04:54 000095864 980__ $$aARTICLE