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RANS/LES coupling for industrial applications

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RANS/LES COUPLING FOR INDUSTRIAL APPLICATIONS

S. Benhamadouche, Y. Fournier and F. Billard

EDF R&D, Dept MFEE, 6 quai Watier, 78401 Chatou Cedex,

France

e-mail: sofiane.benhamadouche@edf.fr ABSTRACT

Several attempts of hybrid RANS/LES can be found in the literature. While Labourasse and Sagaut [6] decompose the velocity field in three parts: a mean flow, a resolved fluctuation and a subgrid fluctuation, solving the mean flow with a RANS model and deriving the fluctuations from a LES approach, Temmerman et al. [10] use a two-layer method that utilizes a RANS approach close to the wall and LES in the outer region without feedback from LES to RANS. Another popular method in aeronautic simulations, which combines RANS and LES, is the Dettached Eddy Simulation (DES) developed firstly by Spalart et al. [9] in which the eddy viscosity switches from a LES to RANS one depending on the turbulent length-scale and the grid spacing. Schlüter et al. [8] recently developed an approach similar to what is presented herein allowing multi-code simulations with CHIMPS. In the present work, a new implementation of code-code coupling, in order to couple turbulence models on separate overlapping unstructured grids, is presented. This work has been mainly carried out in the framework of the Desider European project.

The method allows to couple, on the one hand, two RANS models, coupling for example a low Reynolds approach at the wall with a High Reynolds model in the outer region, and on the other hand, RANS and LES.

Both RANS and LES approaches (Benhamadouche and Laurence [2]) are used in the in-house EDF CFD tool code_Saturne (Archambeau et al. [1]) since several years. The available turbulence models in the code are: LES (standard Smagorinsky and Dynamic), k-ε (standard, v²-f), k-ω-SST, RSM (LRR and SSG).

The Synthetic Eddy Method (SEM, see Jarrin et al. [4]) is utilized to generate unsteady boundary conditions for LES going from RANS data. For RANS/RANS coupling, the continuity of the velocity, the Reynolds stresses and the dissipation rate is insured.

The data exchange between the different runs is based on MPI. The LES solver sends first the coordinates of a points-cloud to the RANS solver (RANS solver identifies the cell which contains the points sent by LES). Then, the RANS solver interpolates the value of a RANS variable to the LES point. Finally, the RANS solver sends the interpolated data to LES solver.

The present approach has been validated on the channel flow at Re*=395 (see Kim et al. [5]) by performing normal and tangential coupling separately (in the tangential coupling, the LES domain starts at y+=50). The preliminatry tests where successuful and it has been shown that the SEM is not only able to sustain turbulence in the stream-wise direction of channel flow using LES but it also reproduces satisfactory tangential fluctuations mandatory for LES to give a well represented logarithmic region.

The final paper will include simulations with an industrial configuration such as a T-junction case often used to predict thermal fatigue phenomena, involving both tangential and normal couplings.

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Moreover, the potential of the method introduced herein is wide as it can handle moving meshes (Chimera method) which is very interesting for fluid structure interaction problems.

REFERENCES

[1]

Archambeau, F. Méchitoua, N. and Sakiz, M. Code_Saturne : a finite volume code for the computation of turbulent incompressible flows – industrial applications. Int. J. on Finite Volumes (electronic journal). 2004.

[2]

Benhamadouche, S. and Laurence, D. LES, Coarse LES, and Transient RANS Comparisons on The Flow Across Tube Bundle, Int. J. Heat and Fluid Flow, 4: 470-479, 2003.

[3]

N Jarrin, S. Benhamadouche, Y. Addad, D. Laurence, Synthetic turbulence inflow condition for large-eddy simulation, Turbulence, Heat and Mass Transfer 4, Antalya, Turkey (2003), to appear in Progress in Computational Fluid Dynamics (2005).

[4]

N Jarrin, S. Benhamadouche and D. Laurence, Inflow Conditions for Large-Eddy Simulation Using a New Vortex Method, In 4th International Symposium on Turbulence

and Shear Flow Phenomena (TSFP4), Williamsburg, 2005.

[5]

J. Kim, P. Moin, and R. Moser , Turbulence Statistics in Fully Developed Channel Flow at Low Reynolds Number. J. Fluid Mech. Vol 177, pp. 133-166,1897.

[6]

E. Labourasse and P. Sagaut. Reconstruction of Turbulent Fluctuations Using a Hybrid RANS/LES Approach. J. of Computational Physics, 182: 301-336, 2002.

[7]

T. Lund, X. Wu and D. Squires. Generation of turbulent inflow data for spatially-developing boundary layer simulations. J. of Computational Physics, 186: 652-665, 1998.

[8]

J.U. Schlüter, X. Wu, E. v. d. Weide, S. Hahn, M. Herrmann, J. J. Alonso and H. Pitsch. A python approach to multi-code simulations: CHIMPS. Center for Turbulence Research Annual Research Briefs, 2005

[9]

P.R. Spalart, W.-H. Jou, M. Strelets and S.R. Almaras. Comments on the feasibility of LES for wings, and on a hybrid RANS/LES approach. In Advances in DNS/LES, edited by C. Liu and Z. Liu (Greyden Press, Colombus), p 137, 1998.

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