3 papers
physics.flu-dyn2024
Mean Mesh Adaptation for Efficient CFD Simulations with Operating Conditions Variability
Hugo Dornier, Olivier P Le Maître, Pietro M Congedo +3
When numerically solving partial differential equations, for a given problem and operating condition, adaptive mesh refinement (AMR) has proven its efficiency to automatically buil…
stat.ML2022
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)
Paul Novello, Gaël Poëtte, David Lugato +2
In this paper, we are interested in the acceleration of numerical simulations. We focus on a hypersonic planetary reentry problem whose simulation involves coupling fluid dynamics…
physics.comp-ph2021
A Taylor Based Sampling Scheme for Machine Learning in Computational Physics
Paul Novello, Gaël Poëtte, David Lugato +1
Machine Learning (ML) is increasingly used to construct surrogate models for physical simulations. We take advantage of the ability to generate data using numerical simulations pro…