14 citations · 15 across the 2 of their papers we have counts for
2 papers
cs.CE2022★ 14 cited
A graph-based probabilistic geometric deep learning framework with online enforcement of physical constraints to predict the criticality of defects in porous materials
Vasilis Krokos, Stéphane P. A. Bordas, Pierre Kerfriden
Stress prediction in porous materials and structures is challenging due to the high computational cost associated with direct numerical simulations. Convolutional Neural Network (C…
cs.CE2020★ 1 cited
A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features
Vasilis Krokos, Viet Bui Xuan, Stéphane P. A. Bordas +2
Multiscale computational modelling is challenging due to the high computational cost of direct numerical simulation by finite elements. To address this issue, concurrent multiscale…