On the Interface Positioning in a Zonal Detached Eddy Simulation (ZDES) of a Spatially Developing Flat Plate Turbulent Boundary Layer

  • Nicolas RenardEmail author
  • Sébastien Deck
Conference paper
Part of the Notes on Numerical Fluid Mechanics and Multidisciplinary Design book series (NNFM, volume 130)


Hybrid RANS/LES methods may be used as Wall-Modeled Large Eddy Simulations to predict wall-bounded turbulent dynamics at a computational cost compatible with complex applications. The present study investigates the sensitivity to the RANS/LES interface position in one such method, the mode III of the ZDES technique (see Deck, Theor Comput Fluid Dyn 26(6):523–550, 2012 [2]). A canonical spatially developing flat plate boundary layer is simulated over a wide range of Reynolds numbers \(3{,}150\,\le \,Re_\theta \,\le \,14{,}000\) at a low Mach number enabling comparisons with the incompressible case. The method is assessed on relatively coarse meshes and is compared to a Wall-Resolved Large Eddy Simulation together with experimental data. The influence of the interface position on skin friction prediction and the ratio of the resolved to modeled turbulent friction is discussed in the framework of the FIK identity (Fukagata, K., Iwamoto, K., Kasagi, N.: Contribution of Reynolds stress distribution to the skin friction in wall-bounded flows. Phys. Fluids 14, L73 (2002) [7]). The mean velocity and Reynolds stresses profiles are analyzed, including spectral analysis of the streamwise velocity and Reynolds shear stress.


Large Eddy Simulation Streamwise Velocity Coarse Mesh Reynolds Shear Stress Interface Position 
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The authors wish to thank all the people involved in the past and present evolution of the FLU3M code. Pierre Sagaut, Romain Laraufie and Pierre-Élie Weiss are warmly acknowledged for very stimulating discussions. The fine mesh WRLES computation was made thanks to the HPC resources from GENCI-CINES (Project ZDESWALLTURB, Grant 2012-[c2012026817]). The thesis of Nicolas Renard is partly funded by the French defense procurement agency DGA.


  1. 1.
    Choi, J.I., Edwards, J., Baurle, R.: Compressible boundary-layer predictions at high Reynolds number using hybrid LES/RANS methods. AIAA J. 47(9), 2179–2193 (2009)CrossRefGoogle Scholar
  2. 2.
    Deck, S.: Recent improvements of the zonal detached eddy simulation (ZDES) formulation. Theoret. Comput. Fluid Dyn. 26(6), 523–550 (2012). doi: 10.1007/s00162-011-0240-z CrossRefGoogle Scholar
  3. 3.
    Deck, S., Renard, N., Laraufie, R., Sagaut, P.: Zonal detached eddy simulation (ZDES) of a spatially developing flat plate turbulent boundary layer over the Reynolds number range \(3{,}150 \le Re_\theta \le 14{,}000\). Phys. Fluids 26, 025–116 (2014)CrossRefGoogle Scholar
  4. 4.
    Deck, S., Renard, N., Laraufie, R., Weiss, P.E.: Large scale contribution to mean wall shear stress in high Reynolds number flat plate boundary layers up to \(Re_\theta \) =13,650. J. Fluid Mech. 743, 202–248 (2014). doi: 10.1017/jfm.2013.629
  5. 5.
    Deck, S., Weiss, P., Pamiès, M., Garnier, E.: Zonal detached eddy simulation of a spatially developing flat plate turbulent boundary layer. Comput. Fluids 48, 1–15 (2011). doi: 10.1016/j.compfluid.2011.03.09 CrossRefzbMATHGoogle Scholar
  6. 6.
    DeGraaff, D., Eaton, J.: Reynolds number scaling of the flat-plate turbulent boundary layer. J. Fluid Mech. 422, 319–346 (2000)Google Scholar
  7. 7.
    Fukagata, K., Iwamoto, K., Kasagi, N.: Contribution of Reynolds stress distribution to the skin friction in wall-bounded flows. Phys. Fluids 14, L73 (2002)CrossRefGoogle Scholar
  8. 8.
    Hamba, F.: Log-layer mismatch and commutation error in hybrid RANS/LES simulation of channel flow. Int. J. Heat Fluid Flows 30, 20–31 (2009)CrossRefGoogle Scholar
  9. 9.
    Jarrin, N., Benhamadouche, S., Laurence, D., Prosser, R.: A synthetic-eddy-method for generating inflow conditions for large eddy simulation. Int. J. Heat Fluid Flows 27, 585–593 (2006)CrossRefGoogle Scholar
  10. 10.
    Keating, A., Piomelli, U.: A dynamic stochastic forcing method as a wall-layer model for large-eddy simulation. J. Turbul. 7(12), 1–24 (2006)MathSciNetGoogle Scholar
  11. 11.
    Laraufie, R., Deck, S.: Assessment of Reynolds stresses tensor reconstruction methods for synthetic inflow conditions. Application to hybrid RANS/LES methods. Int. J. Heat Fluid Flow 42, 68–78 (2013)CrossRefGoogle Scholar
  12. 12.
    Laraufie, R., Deck, S., Sagaut, P.: A dynamic forcing method for unsteady turbulent inflow conditions. J. Comput. Phys. 230(23): 8647–8663 (2011). doi: 10.1016/
  13. 13.
    Marusic, I., Mathis, R., Hutchins, N.: High Reynolds number effects in wall turbulence. Int. J. Heat Fluid Flow 31, 418–428 (2010)CrossRefGoogle Scholar
  14. 14.
    Mary, I., Sagaut, P.: Large eddy simulation of flow around an airfoil near stall. AIAA J. 40(6), 1139–1145 (2002)CrossRefGoogle Scholar
  15. 15.
    Nagib, H., Chauhan, K., Monkewitz, P.: Approach to an asymptotic state for zero pressure gradient turbulent boundary layers. Philos. Trans. R. Soc. A 365, 755–770 (2007)CrossRefzbMATHGoogle Scholar
  16. 16.
    Nikitin, N.V., Nicoud, F., Wasistho, B., Squires, K.D., Spalart, P.R.: An approach to wall modeling in large-eddy simulations. Phys. Fluids 12(7), 1629–1632 (2000)CrossRefGoogle Scholar
  17. 17.
    Pamiès, M., Weiss, P., Garnier, E., Deck, S., Sagaut, P.: Generation of synthetic turbulent inflow data for large eddy simulation of spatially evolving wall-bounded flows. Phys. Fluids 21, 045103 (2009)CrossRefGoogle Scholar
  18. 18.
    Park, G.I., Moin, P.: An improved dynamic non-equilibrium wall-model for large eddy simulation. Phys. Fluids 26, 015–108 (2014)CrossRefGoogle Scholar
  19. 19.
    Piomelli, U.: Wall-layer models for large-eddy simulations. Prog. Aerosp. Sci. 44, 437–446 (2008)CrossRefGoogle Scholar
  20. 20.
    Piomelli, U., Balaras, E.: Wall-layer models for large-eddy simulations. Annu. Rev. Fluid Mech. 34, 348–374 (2002)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Rajamani, B., Kim, J.: A hybrid-filter approach to turbulence simulation. Flow Turbul. Combust. 85, 421–441 (2010)CrossRefzbMATHGoogle Scholar
  22. 22.
    Sánchez-Rocha, M., Menon, S.: An order-of-magnitude approximation for the hybrid terms in the compressible hybrid RANS/LES governing equations. J. Turbul. 12(16), 1–22 (2011)MathSciNetGoogle Scholar
  23. 23.
    Shur, M., Spalart, P., Strelets, M., Travin, A.: A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities. Int. J. Heat Fluid Flows 29(6), 1638–1649 (2008)CrossRefGoogle Scholar
  24. 24.
    Shur, M., Spalart, P., Strelets, M., Travin, A.: A rapid and accurate switch from RANS to LES in boundary layers using an overlap region. Flow Turbul. Combust. 86, 179–206 (2011)CrossRefzbMATHGoogle Scholar
  25. 25.
    Spalart, P., Allmaras, S.: A one equation turbulence model for aerodynamic flows. La Recherche Aérospatiale 1, 5–21 (1994)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.ONERAThe French Aerospace LabMeudonFrance

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