We exploit the similarity between the mean momentum equation and the mean energy
equation and derive transformations for mean temperature profiles in compressible wall …

Dynamic stall on airfoil is of great importance in engineering applications. In the present
work, Fourier neural operator (FNO) is applied to predict flow fields during the dynamic stall …

Abstract Machine-learned augmentations to turbulence models can be advantageous for
flows within the training dataset but can often cause harm outside. This lack of …

The constants and functions in Reynolds-averaged Navier–Stokes (RANS) turbulence
models are coupled. Consequently, modifications of a RANS model often negatively impact …

Assessing the compliance of a white-box turbulence model with known turbulent knowledge
is straightforward. It enables users to screen conventional turbulence models and identify …

Abstract The baseline Launder–Spalding k− ε model cannot be integrated to the wall. This
paper seeks to incorporate the entire law of the wall into the model while preserving the …

This work aims to incorporate basic calibrations of Reynolds-averaged Navier-Stokes
(RANS) models as part of machine learning (ML) frameworks. The ML frameworks …

This study presents a methodology focusing on the use of computational model and
experimental data fusion to improve the Spalart-Allmaras (SA) closure model for Reynolds …

Abstract Machine learning (ML) techniques have emerged as powerful tools for improving
the predictive capabilities of Reynolds-averaged Navier-Stokes (RANS) turbulence models …

This study focuses on the use of model and data fusion for improving the Spalart-Allmaras
(SA) closure model for Reynolds-averaged Navier-Stokes solutions of separated flows. In …