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12 Turbulence Modelling and Numerical Flow Simulation 67<br />

12.4 Direct Numerical Simulation<br />

Reliably solving (12.1) without any additional turbulence and/or transition<br />

model in a DNS requires accurate numerical methods, which do not inhibit<br />

significant artificial viscosity. Spectral methods, which provide very accurate<br />

spatial discretization have been used successfully in the past mainly for simple<br />

geometries. Besides spectral methods, finite difference methods based on<br />

second- or fourth-order accurate central difference schemes are widely used<br />

for DNS of turbulent flows. They are in general easily applicable in complex<br />

computational domains. Further, as pointed out by Choi et al. [1] it is possible<br />

to obtain “spectral” accuracy if the first and second order moments of<br />

the velocity fluctuations are considered for the same number of grid points.<br />

12.5 Statistical Turbulence Modelling<br />

The unknown Reynolds stress tensor 〈u ′′<br />

i u′′ j 〉 in (12.2) is a symmetric tensor,<br />

which, for statistically three-dimensional flows, contains six different elements.<br />

In most applied flow problems 〈u ′′<br />

i u′′ j 〉 is approximated using one- or two equation<br />

turbulence models. One popular two equation turbulence model is the<br />

so-called (k, ω)-model by Wilcox [9] (ω does not correspond to the vorticity).<br />

This model which allows to predict seperated flows better than the well-known<br />

(k, ω)-model reads:<br />

−〈u ′′<br />

i u ′′<br />

j 〉 = νt2〈Sij〉− 2<br />

3 kδij, νt = k 〈u′′ i<br />

, k =<br />

ω u′′<br />

2<br />

i 〉<br />

, ω = ε<br />

cµk<br />

(12.3)<br />

with the unknown properties k and ω. Closure is obtained solving the following<br />

transport equation for these two unknowns and using a set of empirical<br />

constants (cµ, σk,cω1,cω2, σω).<br />

〈ui〉 ∂k k<br />

= cµ<br />

∂xi<br />

2<br />

ε 2〈Sij〉〈Sij〉 + 1<br />

Reτ<br />

〈ui〉 ∂ω<br />

= cω12〈Sij〉〈Sij〉−cω2ω<br />

∂xi<br />

2 + 1<br />

Reτ<br />

∂(1 + νt ∂k<br />

σkν ) ∂xi<br />

∂xi<br />

∂(1 + νt ∂ω<br />

σων ) ∂xi<br />

∂xi<br />

− ε, (12.4)<br />

. (12.5)<br />

In Fig. 12.1 the mean axial velocity component and the mean pressure computed<br />

by Frahnert and Dallmann [2] in a RANS calculation of the fully<br />

developed turbulent channel flow with the (k, ω)-model are compared to the<br />

DNS results of Kim et al. [4] for a Reynolds number Reτ = uτH/ν = 360<br />

(uτ denotes the friction velocity and H the channel height). While the profiles<br />

of the mean axial velocity component 〈u〉 in Fig. 12.1 compare very well, the<br />

mean pressure distributions in Fig. 12.1b reveal strong discrepancies. Considering<br />

the comparison of the turbulence intensities in Fig. 12.2, which are the<br />

four different components of the Reynolds stress tensor, good agreement is<br />

obtained for the Reynolds stress 〈u ′<br />

v ′<br />

〉, but the normal stresses 〈u ′ ′<br />

2 〉, 〈v 2〉<br />

and 〈w ′ 2 〉 compare rather poorly.

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