Resumen: 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. Idioma: Inglés DOI: 10.1063/1.5008205 Año: 2017 Publicado en: AIP Conference Proceedings 1896, 1 (2017), 170007 [6 pp.] ISSN: 0094-243X Financiación: info:eu-repo/grantAgreement/ES/CICYT/DPI2014-51844-C2-1-R Financiación: info:eu-repo/grantAgreement/ES/DGA/T88 Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2015-72365-EXP Tipo y forma: Article (Published version) Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)
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