18 citations · 19 across the 3 of their papers we have counts for
3 papers
Machine-learning-assisted Blending of Data-Driven Turbulence Models
Mourad Oulghelou, Soufiane Cherroud, Xavier Merle +1
We present a machine learning-based framework for blending data-driven turbulent closures in the Reynolds-Averaged Navier-Stokes (RANS) equations, aimed at improving their generali…
Space-dependent Aggregation of Stochastic Data-driven Turbulence Models
Soufiane Cherroud, Xavier Merle, Paola Cinnella +1
A stochastic Machine-Learning approach is developed for data-driven Reynolds-Averaged Navier-Stokes (RANS) predictions of turbulent flows, with quantified model uncertainty. This i…
Space-dependent turbulence model aggregation using machine learning
Maximilien de Zordo-Banliat, Grégory Dergham, Xavier Merle +1
In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined fo…