most citedA Divide-and-Conquer Machine Learning Approach for Modelling Turbulent Flows

15 citations · 15 across the 2 of their papers we have counts for

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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★ 15 cited

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.…