4 papers
A Foundation Model for Material Fracture Prediction
Agnese Marcato, Aleksandra Pachalieva, Ryley G. Hill +14
Accurately predicting when and how materials fail is critical to designing safe, reliable structures, mechanical systems, and engineered components that operate under stress. Yet,…
Attention-Based Reconstruction of Full-Field Tsunami Waves from Sparse Tsunameter Networks
Edward McDugald, Arvind Mohan, Darren Engwirda +2
We investigate the potential of an attention-based neural network architecture, the Senseiver, for sparse sensing in tsunami forecasting. Specifically, we focus on the Tsunami Data…
Discrete Spatial Diffusion: Intensity-Preserving Diffusion Modeling
Javier E. Santos, Agnese Marcato, Roman Colman +2
Generative diffusion models have achieved remarkable success in producing high-quality images. However, these models typically operate in continuous intensity spaces, diffusing ind…
Developing a Foundation Model for Predicting Material Failure
Agnese Marcato, Javier E. Santos, Aleksandra Pachalieva +10
Understanding material failure is critical for designing stronger and lighter structures by identifying weaknesses that could be mitigated. Existing full-physics numerical simulati…