75374 20200228103845.0 doi 10.1063/1.5008205 sideral 104335 ART-2017-104335 eng (orcid)0000-0001-7639-6767 Badías, A. Universidad de Zaragoza Local proper generalized decomposition 2017 Access copy available to the general public Unrestricted Local model order reduction methods provide better results than global ones to problems with intricate manifold solution structure. A posteriori methods (e.g. Proper Orthogonal Decomposition) have been many times applied locally, but a priori methods (e.g. Proper Generalized Decomposition) have the difficulty of determining the manifold structure of the solution in a previous way. We propose three strategies for estimating the appropriate size of the local sub-domains where afterwards local PGD (l-PGD) is applied. It can be seen as a sort of a priori manifold learning or non-linear dimensionality reduction technique. Finally, three examples support the work. info:eu-repo/grantAgreement/ES/CICYT/DPI2014-51844-C2-1-R info:eu-repo/grantAgreement/ES/DGA/T88 info:eu-repo/grantAgreement/ES/MINECO/DPI2015-72365-EXP 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 (orcid)0000-0003-3003-5856 González, D. Universidad de Zaragoza (orcid)0000-0002-9135-866X Alfaro, I. Universidad de Zaragoza Chinesta, F. (orcid)0000-0003-1017-4381 Cueto, E. Universidad de Zaragoza 5004 605 Universidad de Zaragoza Dpto. Ingeniería Mecánica Área Mec.Med.Cont. y Teor.Est. 1896, 1 (2017), 170007 [6 pp.] AIP conf. proc. AIP Conference Proceedings 0094-243X 1353046 http://zaguan.unizar.es/record/75374/files/texto_completo.pdf Versión publicada 84819 http://zaguan.unizar.es/record/75374/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:75374 articulos driver 2020-02-28-10:16:53 ARTICLE