The k-
ω model solves for the turbulent kinetic energy, 
k, and for the dissipation per unit turbulent kinetic energy, 
ω. 
ω is also commonly know as the specific dissipation rate. The CFD Module has the Wilcox revised 
k-
ω model (
Ref. 1)
 
     (3-94)

 (3-95)

 (3-96)

where in turn Ωij is the mean rotation-rate tensor
 
    
    and Sij is the mean strain-rate tensor
 
    
    Pk is given by 
Equation 3-78. The following auxiliary relations for the dissipation, 
ε, and the turbulent mixing length, 
l∗, are also used:
 
     (3-97)

The implementation of the k-
ω model relies on the same concepts as the 
k-
ε model (
Ref. 10). This means that the following approximations have been used:
 
    
    where lr is the limit given by the realizability constraints (
Equation 3-83 and 
Equation 3-84).
 
    
    
    
     (3-98)

 (3-99)

where δw is the distance to the nearest wall, 
κv, is the von Kárman constant (default value 0.41), 
U|| is the velocity parallel to the wall and 
B is a constant that by default is set to 5.2. Menter and others (
Ref. 9) suggested the following smooth blending expressions for 
ω and 
uτ:
 
     (3-100)

 (3-101)

These expression can be combined with the lift-off concept shown in Figure 3-7 which gives 
δw = hw/2. The wall condition for 
ω is given by 
Equation 3-100 and the conditions for the momentum equations are a no-penetration condition 
u ⋅ n = 0 and a shear stress condition
 
     (3-102)

The k-equation formally fulfills 

 both at the wall and in the log-layer, so this condition is applied for all 
δw+.
 
    The system given byEquation 3-85 through 
Equation 3-102 are, however, nonlinear in 
uτ and not very stable. To circumvent this, a variable 
u∗, log is introduced (see 
Ref. 10 and 
Ref. 11) such that
 
     (3-103)

 (3-104)

Equation 3-104 is in turn is used to calculate an alternative dimensionless wall distance
 
     (3-105)

Equation 3-104 is used instead of 
uτ in the expression for 
ωlog and 
Equation 3-105 is used instead of 
δw+ in the expression for 
uτlog. The traction condition in 
Equation 3-102 is replaced by
 
     (3-106)

The resulting wall resolution, δw+, is available as the postprocessing variable 
Delta_wPlus.
 
    
    When Wall Treatment is set to Wall functions, wall boundaries are treated with the same type of boundary conditions as for the 
k-
ε model (see 
Wall Functions) with 
Cμ replaced by 

 and the boundary condition for 
ω given by
 
     (3-107)

The k-
ω turbulence model can be integrated all the way down to the wall and is consistent with the no-slip condition 
u = 0. Since all velocities must disappear on the wall, so must 
k. Hence, 
k=0 on the wall.
 
    
     (3-108)

To avoid the singularity at the wall, ω is not solved for in the cells adjacent to a solid wall. Instead, its value is prescribed by 
Equation 3-108 (using the variable 
ωw, which only exists in those cells). Accurate solutions in the near-wall region require that,
 
     (3-109)

where uτ is the friction velocity which is calculated from the wall shear-stress 
τw,
 
     (3-110)

The boundary variable Distance to cell center in viscous units, 
lplus_cc, is available to ensure that the mesh is fine enough. According to 
Equation 3-109, 

 should be about 
0.5. Observe that very small values of 

 can reduce the convergence rate.
 
    Since the ωw requires the wall distance, a wall distance equation must be solved prior to solving a 
k-
ω model with low-Reynolds-number wall treatment.
 
    
    
    
    
    The k-
ω model applies absolute scales of the same type as the 
k-
ε model (see 
Scaling for Time-Dependent Simulations) except that the scale for 
ω is given by
 
    
    
    The k-
ω model can in many cases give results that are superior to those obtained with the 
k-
ε model (
Ref. 1). It behaves, for example, much better for flat plate flows with adverse or favorable pressure gradients. However, there are two main drawbacks. The first is that the 
k-
ω model can display a relatively strong sensitivity to free stream inlet values of 
ω. The other is that the 
k-
ω model is numerically less robust than the 
k-
ε model.