2002
DOI: 10.1007/s00466-002-0331-1
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Near-wall function for turbulence closure models

Abstract: The Wall Function for large eddy simulation (LES) proposed by Cabot is extended to the turbulence closure models. Predicted results are discussed and compared with well-documented experimental results. The model with Cabot's Wall Function significantly reduces the computing resources (CPU and storage) required and in most cases improves predicted results.

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Cited by 8 publications
(3 citation statements)
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“…Moreover, the Reliable k-ε turbulence model [14] together with the wall function [15] was used to calculate the turbulence viscosity, μ t , and make the governing equations closed.…”
Section: Governing Equations and Numerical Methodsmentioning
confidence: 99%
“…Moreover, the Reliable k-ε turbulence model [14] together with the wall function [15] was used to calculate the turbulence viscosity, μ t , and make the governing equations closed.…”
Section: Governing Equations and Numerical Methodsmentioning
confidence: 99%
“…In order to relax at least in part the above constraints, some authors included the pressure gradient to modify the conventional WFs. Such are the "non-equilibrium" WFs of Ng et al [14] (available in FLUENT CFD code). We followed here the arguments of Craft et al [2] and derived more general wall functions for the velocity and temperature, based on a single assumption that the non-dimensional eddy viscosity varies linearly with the distance from the wall, which was found to hold reasonably well even in strongly nonequilibrium flows.…”
Section: Velocity Fieldmentioning
confidence: 99%
“…Through a similar development, the adjoint equations, their boundary conditions as well as new terms in the sensitivity derivatives can be derived. The adjoint wall function technique could even be applied to flow solvers coupled with Large Eddy Simulation (LES) models (namely, their wall functions based variants, [27][28][29][30]), provided that the adjoint to the LES pde's are available.…”
Section: Introductionmentioning
confidence: 99%