40 citations · 40 across the 1 of their papers we have counts for
3 papers · 1 filter
Bayesian Optimization of the GEKO Turbulence Model for Predicting Flow Separation Over a Smooth Surface
Nikhila Kalia, Ryley McConkey, Eugene Yee +1
This paper applies Bayesian-optimization-RANS (turbo-RANS) to improve Reynolds-averaged Navier-Stokes (RANS) turbulence models for a converging-diverging channel, a case with adver…
Deep Structured Neural Networks for Turbulence Closure Modelling
Ryley McConkey, Eugene Yee, Fue-Sang Lien
Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to…
A curated dataset for data-driven turbulence modelling
Ryley McConkey, Eugene Yee, Fue-Sang Lien
The recent surge in machine learning augmented turbulence modelling is a promising approach for addressing the limitations of Reynolds-averaged Navier-Stokes (RANS) models. This wo…