Data from experiments and direct simulations of turbulence have historically been used to
calibrate simple engineering models such as those based on the Reynolds-averaged Navier …

In computational fluid dynamics simulations of industrial flows, models based on the
Reynolds-averaged Navier–Stokes (RANS) equations are expected to play an important …

Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering
turbulent flow simulations. However, RANS predictions may have large discrepancies due to …

This work presents a review and perspectives on recent developments in the use of machine
learning (ML) to augment Reynolds-averaged Navier-Stokes (RANS) and large eddy …

Turbulence modeling is a critical component in numerical simulations of industrial flows
based on Reynolds-averaged Navier-Stokes (RANS) equations. However, after decades of …

A modeling paradigm is developed to augment predictive models of turbulence by effectively
using limited data generated from physical experiments. The key components of the current …

Reynolds-averaged Navier–Stokes simulations represent a cost-effective option for practical
engineering applications, but are facing ever-growing demands for more accurate …

Turbulence closure models are central to a good deal of applied computational fluid
dynamical analysis. Closure modeling endures as a productive area of research. This …

This paper presents a novel and promising approach to turbulence model formulation, rather
than putting forward a particular new model. Evolutionary computation has brought symbolic …

Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict
fluid flows, despite their acknowledged deficiencies. Not only do RANS models often …