2023/08/24 by Sebastian Rodriguez, Rodriguez, Sebastian, Angelo Pasquale +7 · 1 citation
Engineering · Physics and Astronomy · #Applied Physics (physics.app-ph) #Composite Material Mechanics #Computational Engineering #Elasticity and Material Modeling #FOS: Computer and information sciences #FOS: Physical sciences #Finance #Model Reduction and Neural Networks #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2308.12928
openalex publication_date 2023/08/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Within the framework of computational plasticity, recent advances show that the quasi-static response of an elasto-plastic structure under cyclic loadings may exhibit a time multiscale behaviour. In particular, the system response can be computed in terms of time microscale and macroscale modes using a weakly intrusive multi-time Proper Generalized Decomposition (MT-PGD). In this work, such micro-macro characterization of the time response is exploited to build a data-driven model of the elasto-plastic constitutive relation. This can be viewed as a predictor-corrector scheme where the prediction is driven by the macrotime evolution and the correction is performed via a sparse sampling in space. Once the nonlinear term is forecasted, the multi-time PGD algorithm allows the fast computation of the total strain. The algorithm shows considerable gains in terms of computational time, opening new perspectives in the numerical simulation of history-dependent problems defined in very large time intervals.