most citedBayesian Optimization of the GEKO Turbulence Model for Predicting Flow Separation Over a Smooth Surface

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

physics.flu-dyn2025

Kolmogorov-Arnold Networks for Turbulence Anisotropy Mapping

Nikhila Kalia, Ryley McConkey, Eugene Yee +1

This study evaluates the generalization performance and representation efficiency (parsimony) of a previously introduced Tensor Basis Kolmogorov-Arnold Network (TBKAN) architecture…

physics.flu-dyn2025★ 1 cited

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…

physics.flu-dyn2024

Realizability-Informed Machine Learning for Turbulence Anisotropy Mappings

Ryley McConkey, Nikhila Kalia, Eugene Yee +1

Within the context of machine learning-based closure mappings for RANS turbulence modelling, physical realizability is often enforced using ad-hoc postprocessing of the predicted a…