23 citations · 55 across the 16 of their papers we have counts for
17 papers
Predicting the Elastic Properties of a Cemented Granular Material during Chemical Damage (Debonding)
Alexandre Sac-Morane, Maria Olarte-Garzon, Philipp Braun +3
While underground reservoirs emerge as essential elements to face global warming, these systems represent complex multi-physical and multiscale problems. The considered injection o…
Is Seismic Forecasting Possible with Physics-based AI?
Victoria Keane, Manolis Veveakis, Thomas Poulet
Slow slip events within subduction zones offer a unique window into earthquake prediction. The subducting plate drives dehydration reactions in the fault, causing cyclical slip and…
Brittle-to-ductile fracturing transition: A chemo-mechanical phase-field framework
Fanyu Wu, Chong Liu, Manolis Veveakis +1
In chemically reactive environments, the mechanical integrity of geomaterials is fundamentally compromised by solid matrix dissolution. In this study, we propose a fully coupled ch…
Predicting cement microstructure and mechanical properties in hydrating cement paste with a Phase-Field model
Alexandre Sac-Morane, Katerina Ioannidou, Manolis Veveakis +1
Predicting the evolving microstructure of hydrating cement is essential for understanding and modeling its mechanical property development. Physics-based continuum approaches offer…
Probabilistic Spatial Interpolation of Sparse Data using Diffusion Models
Valerie Tsao, Nathaniel W. Chaney, Manolis Veveakis
The large underlying assumption of climate models today relies on the basis of a "confident" initial condition, a reasonably plausible snapshot of the Earth for which all future pr…
Learning Latent Hardening (LLH): Enhancing Deep Learning with Domain Knowledge for Material Inverse Problems
Qinyi Tian, Winston Lindqwister, Manolis Veveakis +1
Advancements in deep learning and machine learning have improved the ability to model complex, nonlinear relationships, such as those encountered in complex material inverse proble…