Flow, Turbulence and Combustion

, Volume 98, Issue 3, pp 697–724 | Cite as

Implementation and Evaluation of an Embedded LES-RANS Solver

  • Kameswararao Anupindi
  • Richard D. Sandberg


In the current work, we present the development and application of an embedded large-eddy simulation (LES) - Reynolds-averaged Navier Stokes (RANS) solver. The novelty of the present work lies in fully embedding the LES region inside a global RANS region through an explicit coupling at the arbitrary mesh interfaces, exchanging flow and turbulence quantities. In particular, a digital filter method (DFM) extracting mean flow, turbulent kinetic energy and Reynolds stress profiles from the RANS region is used to provide meaningful turbulent fluctuations to the LES region. The framework is developed in the open-source computational fluid dynamics software OpenFOAM. The embedding approach is developed and validated by simulating a spatially developing turbulent channel flow. Thereafter, flow over a surface mounted spanwise-periodic vertical fence is simulated to demonstrate the importance of the DFM and the effect of the location of the RANS-LES interface. Mean and second-order statistics are compared with direct numerical simulation (DNS) data from the literature. Results indicate that feeding synthetic turbulence at the LES interface is essential to achieve good agreement for the mean flow quantities. However, in order to obtain a good match for the Reynolds stresses, the LES interface needs to be placed sufficiently far upstream, which in the present case was six spoiler heights before the fence. Further, a realistic spoiler configuration with finite-width in the spanwise direction and inclined at 30 degrees was simulated using the embedding approach. As opposed to the vertical fence case this is a genuinely (statistically) three-dimensional case and a very good match with mean and second-order statistics was obtained with the experimental data. Finally, in order to test the present solver for high sub-sonic speed flows the flow over an open cavity was simulated. A good match with reference data is obtained for mean and turbulence profile comparisons. Tones in the pressure spectra were predicted reasonably well and an overall sound pressure level with a maximum deviation of 2.6 d B was obtained with the present solver when compared with the experimental data.


Embedded large-eddy simulation Synthetic turbulence generation Channel flow Vertical fence Inclined spoiler Open cavity 



This work was performed with support from Airbus Group Innovations and BAE Systems through the “Simulations at Off-Design (SimOD) conditions” project. The authors also acknowledge the computational support provided through the IRIDIS4 High Performance Computing Facility at the University of Southampton, and the ARCHER Supercomputer facility at the University of Edinburgh through the UK Turbulence Consortium under EPSRC grant EP/L000261/1. Fruitful discussions with Professor Michael A. Leschziner are gratefully acknowledged. We are grateful to Dr. Lionel Larchevêque for providing us with the open cavity data from his simulations for comparison purposes. We would like to thank the anonymous reviewers for their questions, comments and suggestions that helped to improve the quality of the present paper.


  1. 1.
    Pope, S.B.: Turbulent Flows. Cambridge University Press (2000)Google Scholar
  2. 2.
    Spalart, P.R.: Detached-eddy simulation. Ann. Rev. Fluid Mech. 41, 181–202 (2009)CrossRefzbMATHGoogle Scholar
  3. 3.
    Deck, S.: Recent improvements in the zonal detached eddy simulation (ZDES) formulation. Theor. Comput. Fluid Dyn. 26(6), 523–550 (2012)CrossRefGoogle Scholar
  4. 4.
    Spalart, P.R., Deck, S., Shur, M.L., Squires, K.D., Strelets, M.K., Travin, A.: A new version of detached-eddy simulation, resistant to ambiguous grid densities. Theor. Comput. Fluid Dyn. 20(3), 181–195 (2006)CrossRefzbMATHGoogle Scholar
  5. 5.
    Batten, P., Goldberg, U., Chakravarthy, S.: Interfacing statistical turbulence closures with large-eddy simulation. AIAA J. 42(3), 485–492 (2004)CrossRefGoogle Scholar
  6. 6.
    Fasel, H.F., Von Terzi, D.A., Sandberg, R.D.: A methodology for simulating compressible turbulent flows. J. Appl. Mech. 73(3), 405–412 (2006)CrossRefzbMATHGoogle Scholar
  7. 7.
    Weinmann, M., Sandberg, R.D., Doolan, C.: Tandem cylinder flow and noise predictions using a hybrid RANS/LES approach. Int. J. Heat Fluid Flow 50, 263–278 (2014)CrossRefGoogle Scholar
  8. 8.
    König, D., Meinke, M., Schröder, W.: Embedded LES-to-RANS boundary in zonal simulations. J. Turbul. 11 (2010)Google Scholar
  9. 9.
    Quéméré, P., Sagaut, P.: Zonal multi-domain RANS/LES simulations of turbulent flows. Int. J. Numer. Methods Fluids 40(7), 903–925 (2002)CrossRefzbMATHGoogle Scholar
  10. 10.
    Roidl, B., Meinke, M., Schröder, W.: A zonal RANS–LES method for compressible flows. Comput. Fluids 67, 1–15 (2012)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Zhang, Q., Schröder, W., Meinke, M.: A zonal RANS-LES method to determine the flow over a high-lift configuration. Comput. Fluids 39(7), 1241–1253 (2010)CrossRefzbMATHGoogle Scholar
  12. 12.
    Xiao, H., Jenny, P.: A consistent dual-mesh framework for hybrid LES/RANS modeling. J. Comput. Phys. 231(4), 1848–1865 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  13. 13.
    Mathey, F.: Aerodynamic noise simulation of the flow past an airfoil trailing-edge using a hybrid zonal RANS-LES. Comput. Fluids 37(7), 836–843 (2008)CrossRefzbMATHGoogle Scholar
  14. 14.
    Richez, F., Mary, I., Gleize, V., Basdevant, C.: Zonal RANS/LES coupling simulation of a transitional and separated flow around an airfoil near stall. Theor. Comput. Fluid Dyn. 22(3-4), 305–315 (2008)CrossRefzbMATHGoogle Scholar
  15. 15.
    Roidl, B., Meinke, M., Schröder, W.: A reformulated synthetic turbulence generation method for a zonal RANS–LES method and its application to zero-pressure gradient boundary layers. Int. J. Heat Fluid Flow 44, 28–40 (2013)CrossRefGoogle Scholar
  16. 16.
    Roidl, B., Meinke, M., Schröder, W.: Boundary layers affected by different pressure gradients investigated computationally by a zonal RANS-LES method. Int. J. Heat Fluid Flow 45, 1–13 (2014)CrossRefGoogle Scholar
  17. 17.
    Fröhlich, J., von Terzi, D.: Hybrid LES/RANS methods for the simulation of turbulent flows. Progress Aerosp. Sci. 44(5), 349–377 (2008)CrossRefGoogle Scholar
  18. 18.
    Sagaut, P., Deck, S., Terracol, M.: Multiscale and multiresolution approaches in turbulence. World Scientific (2006)Google Scholar
  19. 19.
    Menter, F.R.: Two-equation eddy-viscosity turbulence models for engineering applications. AIAA J. 32(8), 1598–1605 (1994)CrossRefGoogle Scholar
  20. 20.
    Xie, Z.T., Castro, I.P.: Efficient generation of inflow conditions for large eddy simulation of street-scale flows. Flow, Turb. Comb. 81(3), 449–470 (2008)CrossRefzbMATHGoogle Scholar
  21. 21.
    Klein, M., Sadiki, A., Janicka, J.: A digital filter based generation of inflow data for spatially developing direct numerical or large eddy simulations. J. Comput. Phys. 186(2), 652–665 (2003)CrossRefzbMATHGoogle Scholar
  22. 22.
    Kim, Y., Castro, I.P., Xie, Z.T.: Divergence-free turbulence inflow conditions for large-eddy simulations with incompressible flow solvers. Comput. Fluids 84, 56–68 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  23. 23.
    Lund, T.S., Wu, X., Squires, K.D.: Generation of turbulent inflow data for spatially-developing boundary layer simulations. J. Comput. Phys. 140(2), 233–258 (1998)MathSciNetCrossRefzbMATHGoogle Scholar
  24. 24.
    Touber, E., Sandham, N.D.: Large-eddy simulation of low-frequency unsteadiness in a turbulent shock-induced separation bubble. Theor. Comput. Fluid Dyn. 23(2), 79–107 (2009)CrossRefzbMATHGoogle Scholar
  25. 25.
    Nagano, Y., Pei, C.Q., Hattori, H.: A new low-Reynolds-number one-equation model of turbulence. Flow, Turb. Comb. 63(1-4), 135–151 (2000)CrossRefzbMATHGoogle Scholar
  26. 26.
    OpenFOAM: OpenCFD Ltd., The open source CFD toolbox.
  27. 27.
    Weller, H.G., Tabor, G., Jasak, H., Fureby, C.: A tensorial approach to computational continuum mechanics using object-oriented techniques. Comput. Phys. 12(6), 620–631 (1998)CrossRefGoogle Scholar
  28. 28.
    Medic, G., Kalitzin, G., You, D., Weide, V.D., Alonso, J.J., Pitsch, H.: Integrated RANS-LES computation of an entire gas turbine jet engine. In: 45th AIAA Aerospace Sciences Meeting and Exhibit, pp. 2007–1117 (2008)Google Scholar
  29. 29.
    Schlüter, J.U., Wu, X., Kim, S., Alonso, J.J., Pitsch, H.: Coupled RANS-LES computation of a compressor and combustor in a gas turbine engine. In: Proceedings of 40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Lauderdale (2004)Google Scholar
  30. 30.
    Schlüter, J.U., Wu, X., Kim, S., Shankaran, S., Alonso, J.J., Pitsch, H.: A framework for coupling Reynolds-averaged with large-eddy simulations for gas turbine applications. J. Fluids Eng. 127(4), 806–815 (2005)CrossRefGoogle Scholar
  31. 31.
    Moser, R.D., Kim, J., Mansour, N.N.: Direct numerical simulation of turbulent channel flow up to Re= 590. Phys. Fluids 11(4), 943–945 (1999) []CrossRefzbMATHGoogle Scholar
  32. 32.
    Launder, B.E., Sharma, B.I.: Application of the energy-dissipation model of turbulence to the calculation of flow near a spinning disc. Lett. Heat Mass Transfer 1 (2), 131–137 (1974)CrossRefGoogle Scholar
  33. 33.
    Smagorinsky, J.: General circulation experiments with the primitive equations: I. the basic experiment. Month. Weather Rev. 91(3), 99–164 (1963)CrossRefGoogle Scholar
  34. 34.
    Van Driest, E.R.: On turbulent flow near a wall. J. Aeronaut. Sci. (Inst. Aeronaut. Sci.) 23(11) (2012)Google Scholar
  35. 35.
    Orellano, A., Wengle, H.: Numerical simulation (DNS and LES) of manipulated turbulent boundary layer flow over a surface-mounted fence. Eur. J. Mech.-B/Fluids 19(5), 765–788 (2000)CrossRefzbMATHGoogle Scholar
  36. 36.
    Nedić, J., Ganapathisubramani, B., Vassilicos, J.C., Boree, J., Brizzi, L.E., Spohn, A.: Aeroacoustic performance of fractal spoilers. AIAA J. 50(12), 2695–2710 (2012)CrossRefGoogle Scholar
  37. 37.
    Henshaw, M. J de C.: M219 cavity case: Verification and validation data for computational unsteady aerodynamics. Tech. rep., RTO-TR-26, AC/323 (AVT) TP/19, QinetiQ, UK (2002)Google Scholar
  38. 38.
    Komerath, N.M., Ahuja, K.K., Chambers, F.W.: Prediction and measurement of flows over cavities-A survey. In: 25th AIAA Aerospace Sciences Meeting, vol. 1 (1987)Google Scholar
  39. 39.
    Krishnamurty, K.: Acoustic radiation from two-dimensional rectangular cutouts in aerodynamic surfaces. Tech. rep. NACA TN, 3487 (1955)Google Scholar
  40. 40.
    Rockwell, D., Naudascher, E.: Review–self-sustaining oscillations of flow past cavities. J. Fluids Eng. 100(2), 152–165 (1978)CrossRefGoogle Scholar
  41. 41.
    Roshko, A.: Some measurements of flow in a rectangular cutout. Tech. rep. NACA TN 3488 (1955)Google Scholar
  42. 42.
    Rossiter, J.E.: Wind tunnel experiments on the flow over rectangular cavities at subsonic and transonic speeds. Tech. rep. Ministry of Aviation; Royal Aircraft Establishment; RAE Farnborough (1964)Google Scholar
  43. 43.
    Gloerfelt, X., Bogey, C., Bailly, C., Juve, D.: Aerodynamic noise induced by laminar and turbulent boundary layers over rectangular cavities. AIAA paper 2476 (2002), 1–12 (2002)Google Scholar
  44. 44.
    Larchevêque, L., Sagaut, P., Mary, I., Labbé, O., Comte, P.: Large-eddy simulation of a compressible flow past a deep cavity. Phys. Fluids 15(1), 193–210 (2003)CrossRefzbMATHGoogle Scholar
  45. 45.
    Lawson, S.J., Barakos, G.N.: Computational fluid dynamics analyses of flow over weapons-bay geometries. J. Aircraft 47(5), 1605–1623 (2010)CrossRefGoogle Scholar
  46. 46.
    Rowley, C.W., Colonius, T., Basu, A.J.: On self-sustained oscillations in two-dimensional compressible flow over rectangular cavities. J. Fluid Mech. 455, 315–346 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  47. 47.
    Larchevêque, L., Sagaut, P., Le, T.H., Comte, P.: Large-eddy simulation of a compressible flow in a three-dimensional open cavity at high Reynolds number. J. Fluid Mech. 516, 265–301 (2004)CrossRefzbMATHGoogle Scholar
  48. 48.
    Kim, D.H., Choi, J.H., Kwon, O.J.: Detached eddy simulation of weapons bay flows and store separation. Comput. Fluids 121, 1–10 (2015)CrossRefGoogle Scholar
  49. 49.
    Lawson, S.J., Barakos, G.N.: Review of numerical simulations for high-speed, turbulent cavity flows. Progress Aerosp. Sci. 47(3), 186–216 (2011)CrossRefGoogle Scholar
  50. 50.
    Grace, S.: An overview of computational aeroacoustic techniques applied to cavity noise prediction. AIAA paper 510(2001), 1–13 (2001)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Faculty of Engineering and the EnvironmentUniversity of SouthamptonSouthamptonUK
  2. 2.Department of Mechanical EngineeringUniversity of MelbourneVictoriaAustralia
  3. 3.Department of Mechanical EngineeringIndian Institute of Technology MadrasChennaiIndia

Personalised recommendations