5 citations · 5 across the 3 of their papers we have counts for
3 papers
physics.comp-ph2026
A comparative study of transformer models and recurrent neural networks for path-dependent composite materials
Petter Uvdal, Mohsen Mirkhalaf
Accurate modeling of Short Fiber Reinforced Composites (SFRCs) remains computationally expensive for full-field simulations. Data-driven surrogate models using Artificial Neural Ne…
cs.CE2024
Test-time data augmentation: improving predictions of recurrent neural network models of composites
Petter Uvdal, Mohsen Mirkhalaf
Recurrent Neural Networks (RNNs) have emerged as an interesting alternative to conventional material modeling approaches, particularly for nonlinear path dependent materials. Remar…
cond-mat.mtrl-sci2023★ 5 cited
Augmentation of scarce data -- a new approach for deep-learning modeling of composites
Hon Lam Cheung, Petter Uvdal, Mohsen Mirkhalaf
High-fidelity full-field micro-mechanical modeling of the non-linear path-dependent materials demands a substantial computational effort. Recent trends in the field incorporates da…