3 citations · 4 across the 7 of their papers we have counts for
8 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,…
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…
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…
Accelerating Multiphase Flow Simulations with Denoising Diffusion Model Driven Initializations
Jaehong Chung, Agnese Marcato, Eric J. Guiltinan +4
This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics-based simulations, aiming at reducing the computational costs of f…
Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization
Agnese Marcato, Daniel O'Malley, Hari Viswanathan +2
Recreating complex, high-dimensional global fields from limited data points is a grand challenge across various scientific and industrial domains. Given the prohibitive costs of sp…
Generating Multiphase Fluid Configurations in Fractures using Diffusion Models
Jaehong Chung, Agnese Marcato, Eric J. Guiltinan +3
Pore-scale simulations accurately describe transport properties of fluids in the subsurface. These simulations enhance our understanding of applications such as assessing hydrogen…
Learning a General Model of Single Phase Flow in Complex 3D Porous Media
Javier E. Santos, Agnese Marcato, Qinjun Kang +4
Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures an…