The hybridization of Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation
(LES) methods is seen to be the most promising way to efficiently deal with separated …

Spatial artificial neural network (ANN) models are developed for subgrid-scale (SGS) forces
in the large eddy simulation (LES) of turbulence. The input features are based on the first …

In this work, artificial neural network-based nonlinear algebraic models (ANN-NAMs) are
developed for the subgrid-scale (SGS) stress in large eddy simulation (LES) of turbulence at …

In this work, the subgrid-scale (SGS) stress and the SGS heat flux of compressible isotropic
turbulence are modeled by an artificial neural network (ANN) mixed model (ANNMM), which …

This paper presents an extensive review of existing techniques used in estimating design
wind pressures considering Reynolds number and turbulence effects, as well as a case …

We apply the gene-expression programing (GEP) method to develop subgrid-scale models
for large-eddy simulations (LESs) of turbulence. The GEP model is trained based on …

In this paper, the subgrid-scale (SGS) force and the divergence of SGS heat flux of
compressible isotropic turbulence are modeled directly by an artificial neural network (ANN) …

The subgrid-scale stress (SGS) of large-eddy simulation (LES) is modeled by artificial neural
network-based spatial gradient models (ANN-SGMs). The velocity gradients at neighboring …

The performance of two wall models based on Reynolds-averaged Navier–Stokes is
compared in large-eddy simulation of a high Reynolds number separating and reattaching …

Separating turbulent boundary layers over smooth and rough flat plates are studied by large-
eddy simulations. A suction–blowing velocity distribution imposed at the top boundary of the …