9 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 9 cited
A physics-informed deep neural network for surrogate modeling in classical elasto-plasticity
Mahdad Eghbalian, Mehdi Pouragha, Richard Wan
In this work, we present a deep neural network architecture that can efficiently approximate classical elasto-plastic constitutive relations. The network is enriched with crucial p…
cs.CE2020★ 1 cited
Multiscale Modeling of Elasto-Plasticity in Heterogeneous Geomaterials Based on Continuum Micromechanics
Mahdad Eghbalian, Mehdi Pouragha, Richard Wan
In this paper, we investigate some micromechanical aspects of elasto-plasticity in heterogeneous geomaterials. The aim is to upscale the elasto-plastic behavior for a representativ…