3 papers
cs.LG2025
Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs
Ishan Khurjekar, Indrashish Saha, Lori Graham-Brady +1
Systems governed by partial differential equations (PDEs) require computationally intensive numerical solvers to predict spatiotemporal field evolution. While machine learning (ML)…
cond-mat.mtrl-sci2025
Numerical and data-driven modeling of spall failure in polycrystalline ductile materials
Indrashish Saha, Lori Graham-Brady
Developing materials with tailored mechanical performance requires iteration over a large number of proposed designs. When considering dynamic fracture, experiments at every iterat…
cond-mat.mtrl-sci2023
Prediction of local elasto-plastic stress and strain fields in a two-phase composite microstructure using a deep convolutional neural network
Indrashish Saha, Ashwini Gupta, Lori Graham-Brady
Design and analysis of inelastic materials requires prediction of physical responses that evolve under loading. Numerical simulation of such behavior using finite element (FE) appr…