Showing physics.flu-dynShow all
3 papers · 1 filter
physics.flu-dyn2025
Uncertainty and Error Quantification for Data-Driven Reynolds-Averaged Turbulence Modelling with Mean-Variance Estimation Networks
Anthony Man, Mohammad Jadidi, Amir Keshmiri +2
Amid growing interest in machine learning, numerous data-driven models have recently been developed for Reynolds-averaged turbulence modelling. However, their results generally sho…
physics.flu-dyn2024
A Divide-and-Conquer Machine Learning Approach for Modelling Turbulent Flows
Anthony Man, Mohammad Jadidi, Amir Keshmiri +2
In this paper, a novel zonal machine learning (ML) approach for Reynolds-averaged Navier-Stokes (RANS) turbulence modelling based on the divide-and-conquer technique is introduced.…
physics.flu-dyn2024
Non-Unique Machine Learning Mapping in Data-Driven Reynolds Averaged Turbulence Models
Anthony Man, Mohammad Jadidi, Amir Keshmiri +2
Recent growing interest in using machine learning for turbulence modelling has led to many proposed data-driven turbulence models in the literature. However, most of these models h…