Turbulence modeling

Turbulence modeling is the construction and use of a model to predict the effects of turbulence. A turbulent fluid flow has features on many different length scales, which all interact with each other. A common approach is to average the governing equations of the flow, in order to focus on large-scale and non-fluctuating features of the flow. However, the effects of the small scales and fluctuating parts must be modelled.^[1]

Closure problem

The Navier–Stokes equations govern the velocity and pressure of a fluid flow. In a turbulent flow, each of these quantities may be decomposed into a mean part and a fluctuating part. Averaging the equations gives the Reynolds-averaged Navier–Stokes (RANS) equations, which govern the mean flow. However, the nonlinearity of the Navier–Stokes equations means that the velocity fluctuations still appear in the RANS equations, in the nonlinear term $-\rho \overline{\upsilon_i^\prime \upsilon_j^\prime}$ from the convective acceleration. This term is known as the Reynolds stress, $R_{ij}$.^[2] Its effect on the mean flow is like that of a stress term, such as from pressure or viscosity.

To obtain equations containing only the mean velocity and pressure, we need to close the RANS equations by modelling the Reynolds stress term $R_{ij}$ as a function of the mean flow, removing any reference to the fluctuating part of the velocity. This is the closure problem.

Eddy viscosity

Joseph Valentin Boussinesq was the first to attack the closure problem, by introducing the concept of eddy viscosity. In 1887 Boussinesq proposed relating the turbulence stresses to the mean flow to close the system of equations. Here the Boussinesq hypothesis is applied to model the Reynolds stress term. Note that a new proportionality constant $\nu_t > 0$, the turbulence eddy viscosity, has been introduced. Models of this type are known as eddy viscosity models or EVM's.

$-\overline{\upsilon_i^\prime \upsilon_j^\prime} = \nu_t\left (\frac{\partial\bar\upsilon_i}{\partial x_j}+\frac{\partial\bar\upsilon_j}{\partial x_i} - \frac{2}{3}\frac{\partial \bar\upsilon_k}{\partial x_k}\delta_{ij} \right )-\frac{2}{3}K \delta_{ij}$

Which can be written in shorthand as

$-\overline{\upsilon_i^\prime \upsilon_j^\prime} = 2\nu_tS^*_{ij}-\frac{2}{3}K\delta_{ij}$

where $S^*_{ij}$ is the traceless mean rate of strain tensor

$\nu_t$ is the turbulence eddy viscosity

$K = \frac{1}{2}\overline{\upsilon_i' \upsilon_i'}$ is the turbulence kinetic energy

and $\delta_{ij}$ is the Kronecker delta.

In this model, the additional turbulence stresses are given by augmenting the molecular viscosity with an eddy viscosity.^[3] This can be a simple constant eddy viscosity (which works well for some free shear flows such as axisymmetric jets, 2-D jets, and mixing layers).

Prandtl's mixing-length concept

Later, Ludwig Prandtl introduced the additional concept of the mixing length, along with the idea of a boundary layer. For wall-bounded turbulent flows, the eddy viscosity must vary with distance from the wall, hence the addition of the concept of a 'mixing length'. In the simplest wall-bounded flow model, the eddy viscosity is given by the equation:

$\nu_t = \left|\frac{\partial u}{\partial y}\right|l_m^2$

where:

$\frac{\partial u}{\partial y}$ is the partial derivative of the streamwise velocity (u) with respect to the wall normal direction (y);

$l_m$ is the mixing length.

This simple model is the basis for the "law of the wall", which is a surprisingly accurate model for wall-bounded, attached (not separated) flow fields with small pressure gradients.

More general turbulence models have evolved over time, with most modern turbulence models given by field equations similar to the Navier-Stokes equations.

Smagorinsky model for the sub-grid scale eddy viscosity

Among many others , Joseph Smagorinsky (1964) proposed a useful formula for the eddy viscosity in numerical models, based on the local derivatives of the velocity field and the local grid size:

$\nu_t = \Delta x \Delta y \sqrt{\left(\frac{\partial u}{\partial x}\right)^2 + \left(\frac{\partial v}{\partial y}\right)^2 + \frac{1}{2}\left(\frac{\partial u}{\partial y} + \frac{\partial v}{\partial x}\right)^2}$

Spalart–Allmaras, k–ε and k–ω models

The Boussinesq hypothesis is employed in the Spalart–Allmaras (S–A), k–ε (k–epsilon), and k–ω (k–omega) models and offers a relatively low cost computation for the turbulence viscosity $\nu_t$. The S–A model uses only one additional equation to model turbulence viscosity transport, while the k models use two.

Common models

The following is a list of commonly employed models in modern engineering applications.

• Spalart–Allmaras (S–A)
• k–ε (k–epsilon)
• k–ω (k–omega)
• SST (Menter’s Shear Stress Transport)
• Reynolds stress equation model

References

Notes

1. Ching Jen Chen, Shenq-Yuh Jaw (1998), Fundamentals of turbulence modeling, Taylor & Francis
2. Andersson, Bengt; et al. (2012). Computational fluid dynamics for engineers. Cambridge: Cambridge University Press. p. 83. ISBN 978-1-107-01895-2.
3. John J. Bertin, Jacques Periaux, Josef Ballmann, Advances in Hypersonics: Modeling hypersonic flows

Other

• Townsend, A.A. (1980) "The Structure of Turbulent Shear Flow" 2nd Edition (Cambridge Monographs on Mechanics), ISBN 0521298199
• Bradshaw, P. (1971) "An introduction to turbulence and its measurement" (Pergamon Press), ISBN 0080166210
• Wilcox C. D., (1998), "Turbulence Modeling for CFD" 2nd Ed., (DCW Industries, La Cañada), ISBN 0963605100