• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • View Item
  • Home
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Parametric Curves Metamodelling Based on Data Clustering, Data Alignment, POD-Based Modes Extraction and PGD-Based Nonlinear Regressions

Article dans une revue avec comité de lecture
Article dans une revue avec comité de lecture
Author
CHAMPANEY, Victor
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
PASQUALE, Angelo
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccAMMAR, Amine
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
CHINESTA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]

URI
http://hdl.handle.net/10985/22377
DOI
10.3389/fmats.2022.904707
Date
2022-06
Journal
Frontiers in Materials

Abstract

In the context of parametric surrogates, several nontrivial issues arise when a whole curve shall be predicted from given input features. For instance, different sampling or ending points lead to non-aligned curves. This also happens when the curves exhibit a common pattern characterized by critical points at shifted locations (e.g., in mechanics, the elasticplastic transition or the rupture point for a material). In such cases, classical interpolation methods fail in giving physics-consistent results and appropriate pre-processing steps are required. Moreover, when bifurcations occur into the parametric space, to enhance the accuracy of the surrogate, a coupling with clustering and classification algorithms is needed. In this work we present several methodologies to overcome these issues. We also exploit such surrogates to quantify and propagate uncertainty, furnishing parametric stastistical bounds for the predicted curves. The procedures are exemplified over two problems in Computational Mechanics.

Files in this item

Name:
PIMM_FM_2022_CHAMPANEY.pdf
Size:
36.17Mb
Format:
PDF
View/Open

Collections

  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)

Related items

Showing items related by title, author, creator and subject.

  • A separated representation involving multiple time scales within the Proper Generalized Decomposition framework 
    Article dans une revue avec comité de lecture
    PASQUALE, Angelo; ccAMMAR, Amine; FALCÓ, Antonio; PEROTTO, Simona; CUETO, Elías; DUVAL, Jean-Louis; CHINESTA, Francisco (Springer Science and Business Media LLC, 2021-11-26)
    Solutions of partial differential equations can exhibit multiple time scales. Standard discretization techniques are constrained to capture the finest scale to accurately predict the response of the system. In this paper, ...
  • Surrogate parametric metamodel based on Optimal Transport 
    Article dans une revue avec comité de lecture
    TORREGROSA, Sergio; CHAMPANEY, Victor; AMMAR, Amine; HERBERT, Vincent; CHINESTA, Francisco (Elsevier B.V., 2021-11-30)
    The description of a physical problem through a model necessarily involves the introduction of parameters. Hence, one wishes to have a solution of the problem that is a function of all these parameters: a parametric ...
  • Hybrid twins based on optimal transport 
    Article dans une revue avec comité de lecture
    TORREGROSA, Sergio; CHAMPANEY, Victor; ccAMMAR, Amine; HERBERT, Vincent; CHINESTA, Francisco (Elsevier BV, 2022-10)
    Nowadays data is acquiring an indisputable importance in every field including engineering. In the past, experimental data was used to calibrate state-of-the art models. Once the model was optimally calibrated, numerical ...
  • Learning data-driven reduced elastic and inelastic models of spot-welded patches 
    Article dans une revue avec comité de lecture
    REILLE, Agathe; CHAMPANEY, Victor; DAIM, Fatima; TOURBIER, Yves; HASCOET, Nicolas; GONZALEZ, David; CUETO, Elias; DUVAL, Jean Louis; CHINESTA, Francisco (EDP Sciences, 2021)
    Solving mechanical problems in large structures with rich localized behaviors remains a challenging issue despite the enormous advances in numerical procedures and computational performance. In particular, these localized ...
  • Parametric analysis and machine learning-based parametric modeling of wire laser metal deposition induced porosity 
    Article dans une revue avec comité de lecture
    LOREAU, Tanguy; CHAMPANEY, Victor; HASCOET, Nicolas; LAMBARRI, Jon; MADARIETA, Mikel; GARMENDIA, Iker; CHINESTA, Francisco (Springer Science and Business Media LLC, 2022-04)
    Additive manufacturing is an appealing solution to produce geometrically complex parts, difficult to manufacture using traditional technologies. The extreme process conditions, in particular the high temperature, complex ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales