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Conference Papers Year : 2023

A data-driven solver scheme for inelastic problems


We review the data-driven computing paradigm for inelastic problems. We extend an efficient graph search algorithm for the data search by thermodynamic constraints and a rate independent history parametrization based on the mechanical work increment. In addition, we propose a strategy how to use commercial solvers in the framework. Finally, we demonstrate the proposed method with a numerical example featuring 2-d continuum plasticity.
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licence : CC BY NC ND - Attribution - NonCommercial - NoDerivatives

Dates and versions

hal-04112354 , version 1 (01-06-2023)


Attribution - NonCommercial - NoDerivatives



Erik Prume, Laurent Stainier, Michael Ortiz, Stefanie Reese. A data-driven solver scheme for inelastic problems. 92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM), Aug 2022, Aachen, Germany. ⟨10.1002/pamm.202200153⟩. ⟨hal-04112354⟩
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