Abstract
The von Karman length scale is able to reflect the size of the local turbulence structure. However, it is not suitable for the near wall region of wall-bounded flows, for its value is almost infinite there. In the present study, a simple and novel length scale combining the wall distance and the von Karman length scale is proposed by introducing a structural function. The new length scale becomes the von Karman length scale once local unsteady structures are detected. The proposed method is adopted in a series of turbulent channel flows at different Reynolds numbers. The results show that the proposed length scale with the structural function can precisely simulate turbulence at high Reynolds numbers, even with a coarse grid resolution.
Similar content being viewed by others
References
Chapman, D.R.: Computatisnal aerodynamics development and outlook. AIAA J. 17, 1293–1313 (1979)
Choi, H., Moin, P.: Grid-point requirements for large eddy simulation: Chapman’s estimates revisited. Phys. Fluids 24, 011702 (2012)
Piomelli, U.: Wall-layer models for large-eddy simulations. Prog. Aerosp. Sci. 44, 437–446 (2008)
Spalart, P.R., Jou, W.H., Strelets, M.K., et al.: Comments on the feasibility of LES for wings, and on a hybrid RANS/LES approach. Advances in DNS/LES. In: Liu, C., Liu, Z. (eds.) First AFOSR International Conference on DNS/LES (1997)
Spalart, P.R., Deck, S., Shur, M.L., et al.: A new version of detached-eddy simulation, resistant to ambiguous grid densities. Theor. Comput. Fluid Dyn. 20, 181–195 (2006)
Travin, A.K., Shur, M.L., Sparlart, P.R. et al.: Improvement of delayed detached-eddy simulation for LES with wall modelling. In: ECCOMAS CFD 2006: Proceedings of the European Conference on Computational Fluid Dynamics, Egmond aan Zee, Netherlands (2006)
Shur, M.L., Sparlart, P.R., Strelets, M.K., et al.: A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities. Int. J. Heat Fluid Flow 2(9), 1638–1649 (2008)
Nikitin, N.V., Nicoud, F., Wasistho, B., et al.: An approach to wall modeling in large-eddy simulations. Phys. Fluids 12, 1629–1632 (2000)
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 14, 28–40 (2013)
Piomelli, U., Balaras, E., Pasinato, H.D., et al.: The inner–outer layer interface in large-eddy simulations with wall-layer models. Int. J. Heat Fluid Flow 24, 538–550 (2003)
Patil, S., Tafti, D.: Wall modelled large eddy simulations of complex high Reynolds number flows with synthetic inlet turbulence. Int. J. Heat Fluid Flow 33, 9–21 (2012)
Nicoud, F., Baggett, J.S., Moin, P., et al.: Large eddy simulation wall-modeling based on suboptimal control theory and linear stochastic estimation. Phys. Fluids 13, 2968–2984 (2001)
Laraufie, R., Deck, S.: Assessment of Reynolds stresses tensor reconstruction methods for synthetic turbulent inflow conditions. Application to hybrid RANS/LES methods. Int. J. Heat Fluid Flow 42, 68–78 (2013)
Davidson, L., Dahlström, S.: Hybrid LES-RANS: An approach to make LES applicable at high Reynolds number. Int. J. Comput. Fluid D 19, 415–427 (2005)
Menter, F.R., Kuntz, M., Bender, R.: A scale-adaptive simulation model for turbulent flow predictions. In: Conference of 41st Aerospace Sciences Meeting and Exhibit, Reno, Nevada (2003)
Menter, F.R., Egorov, Y.: A scale adaptive simulation model using two-equation models. In: Conference of 43rd AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada (2005)
Menter, F.R., Egorov, Y.: The scale-adaptive simulation method for unsteady turbulent flow predictions. Part 1: theory and model description. Flow Turbul. Combust. 85, 113–138 (2010)
Menter, F.R.: Eddy viscosity transport equations and their relation to the k-\(\varepsilon \) model. J. Fluid Eng. 119, 876–884 (1997)
Davidson, L.: Evaluation of the SST-SAS model: channel flow, asymmetric diffuser and axi-symmetric hill. In: Wesseling, P., Onate, E., Periaux, J. (eds.) European Conference on Computational Fluid Dynamics (2006)
Egorov, Y., Menter, F.R., Lechner, R., et al.: The scale-adaptive simulation method for unsteady turbulent flow predictions. Part 2: Application to complex flows. Flow Turbul. Combust. 85, 139–165 (2010)
Menter, F.R., Garbaruk, A., Smirnov, P., et al.: Scale-Adaptive Simulation with Artificial Forcing. Progress in Hybrid RANS-LES Modelling. Springer, Berlin (2010)
Spalart, P.R., Allmaras, S.R.: A one equation turbulence model for aerodynamic flows. In: Conference of 30th Aerospace Sciences Meeting and Exhibit, Reno, NV, USA (1992)
Menter, F.R., Egorov, Y., Rusch, D.: Steady and unsteady flow modelling using the k-\(\surd \) kL model. In: Hanjalic K., Nagano Y., Jakirlic S. (eds.) Proceedings of the Fifth International Symposium on Turbulence, Heat and Mass Transfer, Dubrovnik, Croatia, 25–29 September, 2006. Begell House, New York (2006)
Xu, J.L., Hu, N., Gao, G.: A High-Fidelity Turbulence Length Scale for Flow Simulation. Progress in Hybrid RANS-LES Modelling. Springer, Berlin (2012)
Vreman, A.W.: An eddy-viscosity subgrid-scale model for turbulent shear flow: algebraic theory and applications. Phys. Fluids 16, 3670–3681 (2004)
Xu, J.L., Gao, G., Yang, Y.: A RANS/LES hybrid model based on local flow structure. Acta Aeronaut. Sin. 35, 2992–2999 (2014)
Moser, R.D., Kim, J., Mansour, N.N.: Direct numerical simulation of turbulent channel flow up to \(Re=590\). Phys. Fluids 11, 943–945 (1999)
Piomelli, U., Balaras, E., Pasinato, H., et al.: The inner–outer layer interface in large-eddy simulations with wall-layer models. Int. J. Heat Fluid Flow 24, 538–550 (2003)
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)
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Dr. Philippe Spalart.
Rights and permissions
About this article
Cite this article
Xu, J., Li, M., Zhang, Y. et al. Wall-modeled large eddy simulation of turbulent channel flow at high Reynolds number using the von Karman length scale. Theor. Comput. Fluid Dyn. 30, 565–577 (2016). https://doi.org/10.1007/s00162-016-0399-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00162-016-0399-4