K-Omega Model

The K-Omega turbulence model is a two-equation model that solves transport equations for the turbulent kinetic energy k and the specific dissipation rate ω —the dissipation rate per unit turbulent kinetic energy ( ωε/k )—in order to determine the turbulent eddy viscosity.

The book by D.C. Wilcox [328] is the most comprehensive reference on the K-Omega model, discussing the origin of the model, comparing it to other models, and presenting the latest version of the model. As the originator of the K-Omega model, Wilcox claims the superiority of his model over the K-Epsilon model, and the superiority of the Omega transport equation over other scale equations.

One reported advantage of the K-Omega model over the K-Epsilon model is its improved performance for boundary layers under adverse pressure gradients. Perhaps the most significant advantage, however, is that it may be applied throughout the boundary layer, including the viscous-dominated region, without further modification. Furthermore, the standard K-Omega model can be used in this mode without requiring the computation of wall distance.

The biggest disadvantage of the K-Omega model, in its original form, is that boundary layer computations are sensitive to the values of ω in the free-stream. This translates into extreme sensitivity to inlet boundary conditions for internal flows, a problem that does not exist for the K-Epsilon models. The K-Omega model variants included in Simcenter STAR-CCM+ have been modified in an attempt to address this shortcoming.

Model Variants

Two variants of the K-Omega model are implemented in Simcenter STAR-CCM+:

Model Variant Abbreviation
Standard K-Omega SKO
SST K-Omega SSTKO
Standard K-Omega

Wilcox revised his original model in 1998, and then in 2006, to account for several perceived deficiencies in the original version (1988). These revisions include:

  • A revised set of model coefficients
  • Two corrections to account for sensitivity to free-stream/inlet conditions, both based on products of k and ω. The first model, introduced in 1998, is a modification of the turbulent kinetic energy equation. The more recent revision [329] is the introduction of a cross-diffusion term that is similar to that used in the SST K-Omega model.
  • A correction to improve the free-shear-flow spreading rates of the model
  • A compressibility correction
  • Low-Reynolds number corrections that allow the K-Omega model to be better applied in the prediction of low-Reynolds number and transitional flows

However, the validation results published in Wilcox’s book are typically for two-dimensional, primarily parabolic, flows. Until further validations for complex flows are widely published, the corrections should be used with caution. Therefore, each correction is included as an option in Simcenter STAR-CCM+.

SST K-Omega

The problem of sensitivity to free-stream/inlet conditions was addressed by Menter [323], who recognized that the ε transport equation from the Standard K-Epsilon model could be transformed into an ω transport equation by variable substitution.

The transformed equation looks similar to the one in the Standard K-Omega model, but adds an additional non-conservative cross-diffusion term containing the dot product kω. Inclusion of this term in the ω transport equation potentially makes the K-Omega model give identical results to the K-Epsilon model. Menter suggested using a blending function (which includes functions of wall distance) that would include the cross-diffusion term far from walls, but not near the wall. This approach effectively blends a K-Epsilon model in the far-field with a K-Omega model near the wall. Purists may object that the blending function crossover location is arbitrary, and could obscure some critical feature of the turbulence. Nevertheless, the fact remains that this approach cures the biggest drawback to applying the K-Omega model to practical flow simulations.

Menter also introduced a modification to the linear constitutive equation and named the model containing this modification the SST (shear-stress transport) K-Omega model. However, the linear relation between the Reynolds stresses and the mean strain rate tends to strongly under predict the anisotropy of turbulence. Turbulence is anisotropic in most complex flows—for example in strong swirl, streamline curvature, shear layer, or boundary layer flows. The anisotropy of the Reynolds stresses not only affects the flow field but also the turbulent transport of scalars (temperature, concentration, passive scalar).

To account for anisotropy of turbulence, Simcenter STAR-CCM+ offers the following non-linear constitutive relations:

  • Quadratic—as suggested by Spalart [325].
  • Cubic—as proposed by Wallin and Johansson [327] and further improved by Hellsten [322]

The cubic constitutive relation is derived from a Reynolds stress transport model and, thus, represents an Explicit Algebraic Reynolds Stress Model (EARSM). Reynolds stress transport models perform much better than eddy viscosity models in anisotropic turbulence, but are often unstable when used in complex flows. Therefore, the cubic model is a good compromise between the two.

The SST model has seen fairly wide application in the aerospace industry, where viscous flows are typically resolved, and turbulence models are applied throughout the boundary layer.

Relation for Turbulent Viscosity

The turbulent eddy viscosity μ t is calculated as:

1. EQUATION_DISPLAY
μ t = ρ k T
(1207)

where:

  • ρ is the density.
  • T is the turbulent time scale.

The turbulent time scale is calculated using Durbin's realizability constraint [321] or the Vorticity Limiter realizability option [310] which is only applicable to Volume of Fluid (VOF) multiphase wave flow.

The turbulent time scale for turbulent eddy viscosity is calculated as:
Model Variant T T with Durbin Scale Limiter Realizability Option T with Vorticity Limiter Realizability Option
SKO
2. EQUATION_DISPLAY
α * ω
(1208)
3. EQUATION_DISPLAY
min ( α * ω , C T 3 S )
(1209)
4. EQUATION_DISPLAY
min ( α * ω , C T 3 S , β * α β λ 2 W 2 S 2 1 ω )
(1210)
SSTKO
5. EQUATION_DISPLAY
min ( α * ω , a 1 S F 2 )
(1211)
6. EQUATION_DISPLAY
min ( 1 max ( ω / α * , ( S F 2 ) / a 1 ) , C T 3 S )
(1212)
7. EQUATION_DISPLAY
min ( 1 max ( ω α * , S F 2 a 1 , λ 2 β β * α S 2 W 2 ω ) , C T 3 S )
(1213)
where:

F 2 is a blending function calculated as:

8. EQUATION_DISPLAY
F 2 = tanh ( ( max ( 2 k β * ω d , 500 ν d 2 ω ) ) 2 )
(1214)

where:

For SSTKO, Menter’s original model [323] uses the modulus of the vorticity tensor rather than S . This slight modification extends the applicability of the model beyond aerodynamic applications. Furthermore, Durbin’s realizability constraint is used instead of Menter’s proposal—that turbulent production be limited to some multiple of the dissipation.

Transport Equations

The transport equations for the kinetic energy k and the specific dissipation rate ω are:

9. EQUATION_DISPLAY
t(ρk)+∇⋅(ρkv¯)=∇⋅[(μ+σkμt)k]+Pkρβ*fβ*(ωkω0k0)+Sk
(1215)
10. EQUATION_DISPLAY
t(ρω)+∇⋅(ρωv¯)=∇⋅[((μ+σωμt)ω]+Pωρβfβ(ω2ω02)+Sω
(1216)

where:

Production Terms

The formulation of the production terms Pk and Pω depends on the K-Omega model variant:

Model Variant Pk Pω
SKO Gk+Gb Gω
SSTKO Gk+Gnl+Gb Gω+Dω

where:

  • the contributions to the production terms are:
    Description Formulation where:
    Gk Turbulent production
    11. EQUATION_DISPLAY
    μtfcS2-23ρk∇⋅v¯-23μt(∇⋅v¯)2
    (1217)
    • fc is the curvature correction factor given by Eqn. (1287).
    Gb Buoyancy production
    12. EQUATION_DISPLAY
    β μtPrt(T¯g)
    (1218)
    • β is the coefficient of thermal expansion. For constant density flows using the Boussinesq approximation, β is user-specified. For ideal gases, β is given by β=-1ρρT¯
    • Prt is the turbulent Prandtl number.
    • T¯ is the mean temperature.
    • g is the gravitational vector.
    Gnl "Non-linear" production
    13. EQUATION_DISPLAY
    ( T RANS , N L ) : v ¯  
    (1219)
    Gω Specific dissipation production
    SKO:
    14. EQUATION_DISPLAY
    ρα[(α*S2-23(∇⋅v¯)2)-23ω∇⋅v¯]
    (1220)
    SSTKO:
    15. EQUATION_DISPLAY
    ρ γ [ ( S 2 - 2 3 ( ∇⋅ v ¯ ) 2 ) - 2 3 ω ∇⋅ v ¯ ]
    (1221)
    Dω

    Cross-diffusion term

    16. EQUATION_DISPLAY
    2ρ(1-F1)σω21ωkω
    (1222)

Model Coefficients

Coefficient SKO SSTKO
a1 - 0.31
α 0.52 -
α* 1
17. EQUATION_DISPLAY
F1α1*+(1-F1)α2*
(1223)
α1* - 1
α2* - 1
β 0.072
18. EQUATION_DISPLAY
F1β1+(1-F1)β2
(1224)
β1 - 0.075
β2 - 0.0828
β* 0.09 0.09
γ -
19. EQUATION_DISPLAY
F1γ1+(1-F1)γ2
(1225)
γ1 -
20. EQUATION_DISPLAY
β1β*-σω1κ2β*
(1226)
γ2 -
21. EQUATION_DISPLAY
β2β*-σω2κ2β*
(1227)
κ - 0.41
σk 0.5
22. EQUATION_DISPLAY
F1σk1+(1-F1)σk2
(1228)
σk1 - 0.85
σk2 - 1
σω 0.5
23. EQUATION_DISPLAY
F1σω1+(1-F1)σω2
(1229)
σω1 - 0.5
σω2 - 0.856
CT 0.6 0.6
λ 2 β β * α 0.075 0.075

The blending function F1 combines the near-wall contribution of a coefficient with its value far away from the wall and is defined as:

24. EQUATION_DISPLAY
F1=tanh([min(max(k0.09ωd,500νd2ω),2kd2CDkω)]4)
(1230)

where:

  • d is the distance to the wall.
  • ν is the kinematic viscosity.
  • CDkω=max(1ωkω,10-20) (cross-diffusion coefficient)