4.2 Article

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

Journal

MECHANICS & INDUSTRY
Volume 22, Issue -, Pages -

Publisher

EDP SCIENCES S A
DOI: 10.1051/meca/2021031

Keywords

Model Order Reduction; Spot-Welds; Machine Learning; Artificial Intelligence; Data-Driven Mechanics

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This study proposes a data-driven technique for learning the rich behavior of local patches in large structures with localized behaviors, and integrating it into a standard coarser description at the structure level to solve mechanical problems. This approach allows localized behaviors to impact the global structural response without needing an explicit description of fine scale behaviors.
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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