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Learning data-driven reduced elastic and inelastic models of spot-welded patches

Article dans une revue avec comité de lecture
Author
REILLE, Agathe
CHAMPANEY, Victor
DAIM, Fatima
TOURBIER, Yves
133641 Technocentre Renault [Guyancourt]
300520 RENAULT
HASCOET, Nicolas
GONZALEZ, David
95355 Universidad de Zaragoza = University of Zaragoza [Saragossa University] = Université de Saragosse
ccCUETO, Elias
95355 Universidad de Zaragoza = University of Zaragoza [Saragossa University] = Université de Saragosse
DUVAL, Jean Louis
ccCHINESTA SORIA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
564849 ESI Group [ESI Group]

URI
http://hdl.handle.net/10985/20416
DOI
10.1051/meca/2021031
Date
2021
Journal
Mechanics & Industry

Abstract

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 behaviors need for extremely fine descriptions, and this has an associated impact in the number of degrees of freedom from one side, and the decrease of the time step employed in usual explicit time integrations, whose stability scales with the size of the smallest element involved in the mesh. In the present work we propose a data-driven technique for learning the rich behavior of a local patch and integrate it into a standard coarser description at the structure level. Thus, localized behaviors impact the global structural response without needing an explicit description of that fine scale behaviors.

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