most citedPySimFrac: A Python Library for Synthetic Fracture Generation, Analysis, and Simulation

2 citations · 4 across the 6 of their papers we have counts for

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physics.geo-ph2024

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…

physics.geo-ph20241 cited

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…

physics.geo-ph2023

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…

physics.geo-ph20232 cited

PySimFrac: A Python Library for Synthetic Fracture Generation, Analysis, and Simulation

Eric Guiltinan, Javier E. Santos, Prakash Purswani +1

In this paper, we introduce Pysimfrac, a open-source python library for generating 3-D synthetic fracture realizations, integrating with fluid simulators, and performing analysis.…

physics.geo-ph2023

Characterizing the impacts of multi-scale heterogeneity on solute transport in fracture networks

Matthew R. Sweeney, Jeffrey D. Hyman, Daniel O'Malley +4

We model flow and transport in three-dimensional fracture networks with varying degrees of fracture-to-fracture aperture/permeability heterogeneity and network density to show how…