Book of abstracts - 14th WCCM & ECCOMAS Congress 2020
Ouvrage scientifique
Auteur
CHINESTA SORIA, FranciscoABGRALL, RémiALLIX, OlivierNÉRON, DavidKALISKE, MichaelRésumé
No abstract
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Article dans une revue avec comité de lectureMUNOZ, David; TORREGROSA JORDAN, Sergio; ; CHINESTA SORIA, Francisco (Elsevier BV, 2024-01)
The Proper Generalized Decomposition (PGD) is a Model Order Reduction framework that has been proposed to be able to do parametric analysis of physical problems. These parameters may include material properties, boundary ...
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Manifold learning for coherent design interpolation based on geometrical and topological descriptors Article dans une revue avec comité de lectureMUNOZ, David; ALLIX, Olivier; CHINESTA SORIA, Francisco; RÓDENAS, Juan José (2023)
In the context of intellectual property in the manufacturing industry, know-how is referred to practical knowledge on how to accomplish a specific task. This know-how is often difficult to be synthesised in a set of rules ...
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Article dans une revue avec comité de lecture; ; ; ; ; ;CHINESTA SORIA, Francisco (Taylor & Francis, 2019)
The main objective of this study is to combine the statistical shape analysis with a morphing procedure in order to generate shape-parametric finite element models of tissues and organs and to explore the reliability and ...
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Article dans une revue avec comité de lecture; ; ; ; ; ;CHINESTA SORIA, Francisco (Elsevier, 2019)
Background and objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response ...
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Article dans une revue avec comité de lecture;CHINESTA SORIA, Francisco; CUETO, Elias (Elsevier, 2021)
We present a method for the data-driven learning of physical phenomena whose evolution in time depends on history terms. It is well known that a Mori-Zwanzig-type projection produces a description of the physical phenomena ...