75375 20181004100710.0 doi 10.1063/1.5008201 sideral 104336 ART-2017-104336 eng Ibañez, R. A manifold learning approach to data-driven computational materials and processes 2017 Access copy available to the general public Unrestricted Standard 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. 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 universal laws while minimizing the need of explicit, often phenomenological, models. They are based on manifold learning methodologies. info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Abisset-Chavanne, E. Aguado, Jose Vicente (orcid)0000-0003-3003-5856 Gonzalez, David Universidad de Zaragoza (orcid)0000-0003-1017-4381 Cueto, Elias Universidad de Zaragoza Duval, Jean Louis Chinesta, Francisco 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 1896, 1 (2017), 170003 [5 pp.] AIP conf. proc. AIP Conference Proceedings 0094-243X 1519733 http://zaguan.unizar.es/record/75375/files/texto_completo.pdf Versión publicada 66954 http://zaguan.unizar.es/record/75375/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:75375 articulos driver 2018-10-04-08:07:01 ARTICLE