A Manifold Learning Approach to Data-Driven Computational Mechanics
A Manifold Learning Approach to Data-Driven Computational Mechanics Ruben Ibanez, Emmanuelle Abisset-Chavanne, Jose Vicente Aguado, David Gonzalez, Elías Cueto, Francisco Chinesta To cite this version: Ruben Ibanez, Emmanuelle Abisset-Chavanne, Jose Vicente Aguado, David Gonzalez, Elías Cueto, et al.. A Manifold Learning Approach to Data-Driven Computational Mechanics. 13e colloque national en calcul des structures, Université Paris-Saclay, May 2017, Giens, Var, France. hal-01926477 HAL Id: hal-01926477 https://hal.archives-ouvertes.fr/hal-01926477 Submitted on 19 Nov 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. CSMA 2017 13ème Colloque National en Calcul des Structures 15-19 Mai 2017, Presqu’île de Giens (Var) A Manifold Learning Approach to Data-Driven Computational Me- chanics R. Ibañez1, E. Abisset-Chavanne1, J.V. Aguado1, D. Gonzalez2, E. Cueto2, F. Chinesta1 1 ICI Institute, Ecole Centrale Nantes, {Ruben.Ibanez-Pinillo,Emmanuelle.Abisset-Chavanne,Jose.Aguado-Lopez,Francisco.Chinesta}@ec-nantes.fr 2 Aragon Institute of Engineering Research, Universidad de Zaragoza, Spain, {gonzal;ecueto}@unizar.es Résumé — Standard simulation in classical mechanics is based on the use of two very different types of equations.
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