We revisit the grid-point requirement estimates in Choi and Moin [“Grid-point requirements
for large eddy simulation: Chapman's estimates revisited,” Phys. Fluids 24, 011702 (2012)] …

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 …

A wall model for large-eddy simulation (LES) is proposed by devising the flow as a
combination of building blocks. The core assumption of the model is that a finite set of simple …

In this work, a data-driven wall model for turbulent flows over periodic hills is developed
using the feedforward neural network (FNN) and data from wall-resolved large-eddy …

This review discusses the recent application of artificial intelligence (AI) algorithms in five
aspects of computational fluid dynamics: aerodynamic models, turbulence models, some …

The large-eddy simulation of wall-bounded turbulent flows at high Reynolds numbers is
made more efficient by the use of wall models that predict the wall shear stress, allowing …

This survey investigates wall modeling in large-eddy simulations (LES) using data-driven
machine-learning (ML) techniques. To this end, we implement three ML wall models in an …

Conventional empirical turbulence modeling is progressive: one begins by modeling simple
flows and progressively works towards more complex ones. The outcome is a series of …

Constant-coefficient spatial gradient models (SGMs) are proposed for the sub-grid scale
(SGS) closure in large-eddy simulation (LES) of turbulence. The model coefficients are …

Estimates of grid-point and time-step requirements exist for many canonical flows but not for
stratified wakes. The purpose of this work is to fill in this gap. We apply the basic meshing …