4 papers
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…
On the internal architecture of lightweight negative Poisson's ratio (auxetic) metastructures: a review
Ali Rahimi-Lenji, Mohammad Heidari-Rarani, Mohsen Mirkhalaf +1
Development of lightweight materials with enhanced mechanical properties has been a long-standing challenge in science and engineering. Lightweight auxetic metastructures (AMSs) pr…
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…
A novel Taguchi-based approach for optimizing neural network architectures: application to elastic short fiber composites
Mohammad Hossein Nikzad, Mohammad Heidari-Rarani, Mohsen Mirkhalaf
This study presents an innovative application of the Taguchi design of experiment method to optimize the structure of an Artificial Neural Network (ANN) model for the prediction of…