From the 1 of 12 linked papers with an AI index.
12 papers
Heuristic Learning for Active Flow Control Using Coding Agents
Paul Garnier, Jonathan Viquerat, Elie Hachem
The paper proposes a heuristic learning approach using coding agents to directly discover explicit, interpretable feedback controllers for active flow control, achieving performanc…
Physics-Informed Coarsening for Multigrid Graph Neural Surrogates
Amir Bazzi, David Cardinaux, Ramy Nemer +3
Learning-based surrogates for partial differential equations have recently matched the accuracy of classical solvers while achieving orders-of-magnitude speedups, predominantly in…
Dripping-onto-droplet capillary breakup
Ricardo El Khoury, Kindness Isukwem, Elie Hachem +1
This experimental, numerical, and theoretical study investigates the capillary thinning and breakup of Newtonian filaments formed following the coalescence of a millimetric-nozzle-…
Mesh Based Simulations with Spatial and Temporal awareness
Paul Garnier, Vincent Lannelongue, Elie Hachem
Machine Learning surrogates for Computational Fluid Dynamics (CFD), particularly Graph Neural Networks (GNNs) and Transformers, have become a new important approach for acceleratin…
Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessment
Paul Garnier, Pablo Jeken-Rico, Vincent Lannelongue +11
Intracranial aneurysms remain a major cause of neurological morbidity and mortality worldwide, where rupture risk is tightly coupled to local hemodynamics particularly wall shear s…
Predicting Grain Growth in Polycrystalline Materials Using Deep Learning Time Series Models
Eliane Younes, Elie Hachem, Marc Bernacki
Grain Growth strongly influences the mechanical behavior of materials, making its prediction a key objective in microstructural engineering. In this study, several deep learning ap…