Presentation

www.numeca.com 

Towards a succesful implementation of 

DES strategies in industrial RANS solvers 

L. Temmerman, Temmerman, 

Ch. Hirsch 

Acknowledgements 

The DESider project (Detached Eddy Simulation for Industrial Aerodynamics) is a collaboration between 

Alenia, ANSYS-AEA, Chalmers University, CNRS-Lille, Dassault, DLR, EADS Military Aircraft, 

EUROCOPTER Germany, EDF, FOI-FFA, IMFT, Imperial College London, NLR, NTS, NUMECA, ONERA, 

TU Berlin, and UMIST. The project is funded by the European Community represented by the CEC, Research 

Directorate-General, in the 6th Framework Programme, under Contract No. AST3-CT-2003-502842.


Aim: 

To adapt a RANS solver to perform DES/LES computations 

Code overview 

Modeling 

Calibration 

Applications 

Concluding remarks 

DESider workshop, Corfou, Corfou, 

17-18 17 18 June ‘07 

Outline 

2


Compressible, co-located finite-volume 

Diffusive term: second order central 

Inviscid term: 

Central scheme with scalar dissipation (Jameson et al, 1981) 


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Code overview 

Central scheme with matrix dissipation (Swanson and Turkel, 1992) 

Upwind scheme (Roe, 1981) 

Low Mach number pre-conditionning 

4 th order Runge-Kutta smoother 

Acceleration with local time-stepping, residual smoothing and 

multi-grid 

Time-marching: implicit second-order backward differencing 

Turbulence models: Spalart-Allmaras, k-ε Yang-Shi, Menter SST 

3


Two DES models: 

Spalart-Allmaras based (Shur et al, 1999) 

Menter SST based (Travin et al, 2002) 


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min ( d C Δ) 

Δ = max( 

Δx, 

Δy, 

Δz) 

l DES = w, 

DES 

l RANS 

= k 

0. 

5 

/ 

CDES 

= 0. 

65 

( l C Δ) 

l DES = min RANS , DES 

( C ω ) 

C = F C ) 

DES 

1 

μ 

k −ω 

k −ε 

DES + ( 1− 

F1 

CDES 

( Δx, 

Δy 

Δz) 

Δ = max , 

k −ω 

k −ε 

C = 0. 

78 C 

= 0. 

61 

DES 

DES 

DES modelling 

4



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Calibration of LES mode 

Purpose: ensure that the code returns a LES solution whenever 

required 

Calibration tool: decay of isotropic turbulence 

Benchmark data from Comte-Bellot and Corrsin (1971) 

Initial conditions: 

Velocity fields obtained from inverse 

Fourier transform 

Initial fields for turbulent quantities 

obtained from freezing the velocity fields 

Comparisons of energy spectra and the 

energy decay allows to calibrate model 

constants and to evaluate the level of 

numerical dissipation 

5



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Influence of the numerical scheme 


6



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Influence of the modeling and effect of varying the model and 

numerical parameters 

7


List of applications: 

NACA0021 aerofoil with high angle of attack 

Flow over a descending bump in a closed duct 

Ahmed car body with 25 o slant 

All these cases have been considered within the DESider project 


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Applications 

8


Experiment of Katrina Swalwell 

(Monash University): 

Mean static pressure 

distribution on aerofoil 

Time histories of forces 


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Application 1: NACA0021 aerofoil 

Low mach number flow (M = 0.11) at 60 o angle of attack (Re = 270,000 

based on freestream velocity and chord length) 

Grid made of 141 x 101 x 36 (approx. 510,000 cells - L z = 1 c - Δz = 

0.0278 c) 

Δt = 4.554 10 -5 s (Δt U o /c = 0.0125) 

Averaged sample: T U o / c = 177 

Modelling: SA-DES 

9


Pressure coefficient distribution 


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C L 

C D 

Exp. 0.921 1.547 

Comp. 1.020 1.679 

Lift and drag coefficients 

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PSD for the lift coefficient PSD for the tangential force 

coefficient 

11



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Correct prediction of C p distribution. Mean lift and drag 

coefficients are over-estimated 

Forces PSD: main frequencies are captured at the correct 

locations 

Animation shows nice unsteadiness in the aerofoil wake 

Results are satisfactory although: 

Spanwise extent is too small (4 chords recommended) 

Sampling duration is too short (at least 400 convective 

time units) 

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Application 2: Bump in closed duct 

Flow over a bump, inside a duct (rectangular section) 

Experimental data (ONERA) from the DESider Consortium: 

Pressure distribution along different lines and pressure spectra 

on the lower wall 

LDV and PIV measurements at different locations of the flow 

Inflow conditions 

Flow conditions: 

Incompressible flow 

Reynolds = 1,236,000 (based 

on a bump height 0.138 m and a 

reference velocity of 8 m/s) 

Modelling: SA-DES 

Grid made of 320 x 120 x 148 cells (3,907,200) 

Averaged sample: 3540 Δt (T Uo / c = 205.2) 

Δt = 10-3 s (Δt Uo /c = 5.797 10-2 ) 

13


Mean streamlines and 

separation zone 


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Iso-contours Iso contours of λ2 criterion 

Exp. Comp. 

Reattachment point ≈ 0.625 ≈ 0.47 

14



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Streamwise velocity and shear stress profiles at 

x = 0.35 m in the centre plane 

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Streamwise velocity and shear stress profiles at 

x = 0.92 m in the centre plane 

16



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The agreement between the experiment and the computation is 

not too good with the flow reattaching too early 

The main features of the flow are however captured 

DDES modification may improve the solution 

17



17-18 17 18 June ‘07 

Application 3: Ahmed body with 25 o slant angle 

Ahmed body: generic car body with slant angle of 25 o 

Experimental data from Becker et al (2000): 

available from Ercoftac database (case C. 82 ) 

LDA and hot wire measurements available 

Pressure measurements on the body rear 

Incompressible flow 

Reynolds number 768,000, based on a reference velocity of 40 m/s 

and a body height of 288 mm 

Modeling: SA-DES and SST-DES 

Grid: 

3,000,000 cells (SA-DES) 

4,500,000 cells (SST-DES) 

Δt = 10 -3 s 

18


z (mm) 

380 

360 

340 

320 

300 

280 

260 


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Experiments 

SA-DES 

SST-DES 

240 

-263 -243 -223 -203 -183 -163 -143 -123 -103 -83 -63 -43 -23 -3 17 37 

x (mm) 

Streamwise velocity profiles along the slant 

19



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Instantaneous snapshot of the wake (iso ( iso-contours contours 

of the vorticity magnitude – obtained with SST- SST 

DES) 

20



17-18 17 18 June ‘07 


Computations are unsteady with many structures in the wake 

Both simulations fail to predict the mean flow on the slant: 

SA-DES: the flow remains re-attached 

SST-DES: too strong recirculation zone on the slant 

… we see a strong influence of the underlying model in this 

case 

Failure to predict correctly the flow may be due to several 

factors: grid inadequacy, case more suitable for DDES, too much 

numerical dissipation? 

21



17-18 17 18 June ‘07 

Concluding remarks 

Once calibrated, the RANS solver is able to return LES-type 

solutions 

NACA0021 results are good, considering the limitations of the 

computations 

DESider Bump: 

Experimental and computational data do not agree too well 

Main flow features still correctly predicted 

Ahmed body: 

Failure to correctly predict the flow re-circulation on the slant 

Strong influence of the underlying RANS model of the DES on 

the results for this particular case 

Results are good for the case for which DES has been designed, not 

so for the others => some improvements needed (DDES, additional 

modifications) 

22

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