Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-21T16:54:25.445Z Has data issue: false hasContentIssue false

Preservation of statistical properties in large-eddy simulation of shear turbulence

Published online by Cambridge University Press:  14 November 2007

P. GUALTIERI
Affiliation:
Dipartimento di Meccanica e Aeronautica, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy
C. M. CASCIOLA
Affiliation:
Dipartimento di Meccanica e Aeronautica, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy
R. BENZI
Affiliation:
Dipartimento di Fisica e INFM, Università di Roma, Tor Vergata, Via della Ricerca scientifica 1, 00133 Roma, Italy
R. PIVA
Affiliation:
Dipartimento di Meccanica e Aeronautica, Università di Roma La Sapienza, Via Eudossiana 18, 00184 Roma, Italy

Abstract

We discuss how large-eddy simulation (LES) can be properly employed to predict the statistics of the resolved velocity fluctuations in shear turbulence. To this purpose an a posteriori comparison of LES data against filtered direct numerical simulation (DNS) is used to establish the necessary conditions that the filter scale LF must satisfy to achieve the preservation of the statistical properties of the resolved field. In this context, by exploiting the physical role of the shear scale LS, the Kármán–Howarth equation allows for the assessment of LES data in terms of scale-by-scale energy production, energy transfer and subgrid energy fluxes. Even higher-order statistical properties of the resolved scales such as the probability density function of longitudinal velocity increments are well reproduced, provided the relative position of the filter scale with respect to the shear scale is properly selected. We consider here the homogeneous shear flow as the simplest non-trivial flow which fully retains the basic mechanism of turbulent kinetic energy production typical of any shear flow, with the advantage that spatial homogeneity implies a well-defined value of the shear scale while numerical difficulties related to resolution requirements in the near wall region are avoided.

Type
Papers
Copyright
Copyright © Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Antonia, R. A., Djenidi, L. & Spalart, P. R. 1994 Anisotropy of the dissipation tensor in a turbulent boundary layer. Phys. Fluids 6 (7), 24752479.CrossRefGoogle Scholar
Baggett, J. S., Jimenez, J. & Kravshenko, A. K. 1997 Resolution requirements in large-eddy simulation of shear flows. CTR Annu. Res. Briefs.Google Scholar
Benzi, R., Amati, G., Casciola, C. M., Toschi, F. & Piva, R. 1999 Intermittency and scaling laws for wall bounded turbulence. Phys. Fluids 11, 1284.CrossRefGoogle Scholar
Biferale, L. & Procaccia, I. 2005 Anisotropy in turbulent flows and in turbulent transport. Phys. Rep. 414(2–3), 1150.CrossRefGoogle Scholar
Cabot, W. & Moin, P. 1999 Aproximate wall boudary conditions in the large eddy simulation of high Reynolds number. Flow Turbulence. Combust. 63, 269291.CrossRefGoogle Scholar
Carati, D., Winckelmans, G. S. & Jeanmart, H. 2001 On the modelling of the sub-grid scale and filtered-scale stress tensors in large-eddy simulation. J. Fluid Mech. 441, 119138.CrossRefGoogle Scholar
Casciola, C. M., Gualtieri, P., Benzi, R. & Piva, R. 2003 Scale by scale budget and similarity laws for shear turbulence. J. Fluid Mech. 476, 105114.CrossRefGoogle Scholar
Casciola, C. M., Gualtieri, P., Jacob, B. & Piva, R. 2005 Scaling properties in the production range of shear dominated flows. Phys. Rev. Lett. 95, 225245.CrossRefGoogle ScholarPubMed
Cerruti, S. & Meneveau, C. 2000 Statistics of filtered velocity in grid and wake turbulence. Phys. Fluids 12 (5), 11431165.CrossRefGoogle Scholar
Champagne, F. H., Harris, V. G. & Corrsin, S. 1970 Experiments on nearly homogeneous turbulent shear flow. J. Fluid Mech. 41, 81139.CrossRefGoogle Scholar
Chow, F. K. & Moin, P. 2003 A further study of numerical errors in large-eddy simulatios. J. Comput. Phys. 184, 366380.CrossRefGoogle Scholar
Corrsin, S. 1958 On local isotropy in turbulent shear flow. NACA R & M 58B11.Google Scholar
Domaradsky, J. A. & Loh, K. C. 1999 The subgrid-scale estimation model in the physical space representation. Phys. Fluids 11 (8), 23302342.CrossRefGoogle Scholar
Domaradsky, J. A. & Saiki, E. M. 1997 A subgrid-scale model based on the estimation of unresolved scales of turbulence. Phys. Fluids 9 (7), 21482164.CrossRefGoogle Scholar
Durbin, P. A. & Speziale, C. G. 1997 Local anisotropy in strained turbulence at high Reynolds number. Trans. ASME I: J. Fluid Engng 113, 707709.Google Scholar
Ferchichi, M. & Tavoularis, S. 2000 Reynolds number effects on the fine structure of uniformly shared turbulence. Phys. Fluids 12 (11), 29422953.CrossRefGoogle Scholar
Freitag, M. & Klein, M. 2006 An improved method to assess the quality of large eddy simulation in the context of implicit filtering. J. Turbulence 7 (40), 112.CrossRefGoogle Scholar
Frisch, U. 1995 Turbulence. Cambridge University Press.CrossRefGoogle Scholar
Garg, S. & Warhaft, Z. 1998 On the small scale structures of simple shear flow. Phys. Fluids 10 (3), 662673.CrossRefGoogle Scholar
Ghosal, S. 1996 An analysis of numerical error in large-eddy simulations of turbulence. J. Comput. Phys. 125, 187206.CrossRefGoogle Scholar
Gualtieri, P., Casciola, C. M., Benzi, R., Amati, G. & Piva, R. 2002 Scaling laws and intermittency in homogeneous shear flow. Phys. Fluids 14 (2), 583596.CrossRefGoogle Scholar
Guerts, B. J. 1997 Inverse modeling for large-eddy simulation. Phys. Fluids 9 (12), 35853588.CrossRefGoogle Scholar
Guerts, B. J. & Frohlich, J. 2002 A framework for predicting accuracy limitations in large-eddy simulation. Phys. Fluids 14 (6), L41L44.CrossRefGoogle Scholar
Guerts, B. J. & Holm, D. D. 2003 Regularization modeling for large-eddy simulation. Phys. Fluids 15 (1), L13L16.CrossRefGoogle Scholar
Gullibrand, J. & Chow, F. K. 2003 The effect of numerical errors and turbulence models in large-eddy simulations of channel flow, with and without explicit filtering. J. Fluid Mech. 495, 323341.CrossRefGoogle Scholar
Harris, V. G., Graham, J. A. H. & Corrsin, S. 1977 Further experiments in nearly homogeneous turbulent shear flow. J. Fluid Mech. 81, 657687.CrossRefGoogle Scholar
Jacob, B., Biferale, L., Iuso, G. & Casciola, C. M. 2004 Anisotropic fluctuations in turbulent shear flows. Phys. Fluids 16 (11), 41354142.CrossRefGoogle Scholar
Jimenez, J. & Moser, R. D. 2000 Large-eddy simulation: where are we and what can we expect? AIAA J. 4, 605612.CrossRefGoogle Scholar
Kang, H. S., Chester, S. & Meneveau, C. 2003 Decaying turbulence in active-grid-generated flow and comparison with large-eddy simulation. J. Fluid Mech. 480, 129160.CrossRefGoogle Scholar
Kida, S. & Tanaka, M. 1994 Dynamics of vortical structures in homogeneous shear flow. J. Fluid Mech. 274, 4368.CrossRefGoogle Scholar
Klein, M. 2005 An attempt to assess the quality of large eddy simulation in the context of implicit filtering. Flow Turbulence Combust. 75, 133166.CrossRefGoogle Scholar
Kolmogorov, A. N. 1941 The local structure of turbulence in incompressible viscous fluid for very large Reynolds number. Dokl. Akad. SSSR 434.Google Scholar
Kurien, S. & Sreenivasan, K. R. 2002 Anisotropic scaling contributions to high-order structure functions in high-Reynolds-number turbulence. Phys. Rev. E 62 (2), 22062212.Google Scholar
Langford, J. A. & Moser, R. D. 1999 Optimal LES formulations for isotropic turbulence. J. Fluid Mech. 398, 321346.CrossRefGoogle Scholar
Lee, M. J., Kim, J. & Moin, P. 1990 Structure of turbulence at high shear rate. J. Fluid Mech. 216, 561583.CrossRefGoogle Scholar
Lesieur, M. & Metais, O. 1996 New trends in large eddy simulation of turbulence. Annu. Rev. Fluid Mech. 28, 4582.CrossRefGoogle Scholar
Lilly, D. K. 1967 The representation of small scale turbulence in numerical simulation experiments. Proc. IBM Scientific Computing Symp. Environ. Sci.Google Scholar
Marati, N., Casciola, C. M. & Piva, R. 2004 Energy cascade and spatial fluxes in wall turbulence. J. Fluid Mech. 521, 191215.CrossRefGoogle Scholar
Mathew, J., Lechner, R., Foysi, H., Sesterhenn, J. & Friedrich, R. 2003 An explicit filtering method for large eddy simulation of compressible flows. Phys. Fluids 15 (8), 22792289.CrossRefGoogle Scholar
Mathew, J., Foysi, H. & Friedrich, R. 2006 A new approach to LES based on explicit filtering. Intl J. Heat Fluid Flow 27, 595602.CrossRefGoogle Scholar
Meneveau, C. 1994 Statistics of turbulence subgrid-scales stresses: necessary conditions and experimental tests. Phys. Fluids 6 (2), 815833.CrossRefGoogle Scholar
Meneveau, C. & Katz, J. 2000 Scale-invariance and turbulence models for large eddy simulation. Annu. Rev. Fluid Mech. 32, 132.CrossRefGoogle Scholar
Meyers, J., Guerts, B. J. & Baelmans, M. 2003 Database analysis of errors in large-eddy simulation. Phys. Fluids 15 (6), 27402755.CrossRefGoogle Scholar
Moin, P. 2002 Advances in large eddy simulation methodology for complex flows. Intl J. Heat Fluid Flow 23, 710720.CrossRefGoogle Scholar
Moin, P. & Apte, S. V. 2006 Large-eddy simulation of realistic gas turbine combustors. AIAA J. 44 (4), 698708.CrossRefGoogle Scholar
Piomelli, U. & Balaras, E. 2000 Wall-layer models for large-eddy simulations. Annu. Rev. Fluid Mech. 34, 349374.CrossRefGoogle Scholar
Piomelli, U., Moin, P. & Ferziger, J. H. 1988 Model consistency in large eddy simulation of turbulent channel flow. Phys. Fluids 31 (7), 18841891.CrossRefGoogle Scholar
Pope, S. B. 2000 Turbulent Flows. Cambridge University Press.CrossRefGoogle Scholar
Pope, S. B. 2004 Ten questions concerning the large eddy simulation of turbulent flows. New J. Phys. 6, 124.CrossRefGoogle Scholar
Pumir, A. 1996 Turbulence in homogeneous shear flow. Phys. Fluids 8 (11), 31123127.CrossRefGoogle Scholar
Pumir, A. & Shraiman, B. 1994 Persistent small scale anisotropy in homogeneous shear flow. Phys. Rev. Lett. 75 (11), 31143117.CrossRefGoogle Scholar
Rogallo, R. S. 1981 Numerical experiments in homogeneous turbulence. NASA TM 81315.Google Scholar
Rogers, M. M. & Moin, P. 1987 The structure of the vorticity field in homogeneous turbulent flows. J. Fluid Mech. 176, 3366.CrossRefGoogle Scholar
Rohr, J. J., Itsweire, E. C., Helland, K. N. & VanAtta, C. W. Atta, C. W. 1988 An investigation of the growth of turbulence in a uniform-mean-shear flow. J. Fluid Mech. 187, 133.CrossRefGoogle Scholar
Rose, W. G. 1966 Results of an attempt to generate a homogeneous turbulent shear flow. J. Fluid Mech. 25, 97120.CrossRefGoogle Scholar
Saddoughi, S. G. & Veeravalli, S. V. 1994 Local isotropy in turbulent boundary layer at high Reynolds number. J. Fluid Mech. 268, 333372.CrossRefGoogle Scholar
Shen, X. & Warhaft, Z. 2000 anisotropy of small scale structures in High Reynolds number (Reλ ~ 1000) turbulent shear flow. Phys. Fluids 12 (11), 29762989.CrossRefGoogle Scholar
Shumacher, J. 2001 Derivative moments in stationary homogeneous shear turbulence. J. Fluid Mech. 441, 109118.CrossRefGoogle Scholar
Shumacher, J. 2004 Relation between shear parameter and Reynolds number in statistically stationary turbulent shear flows. Phys. Fluids 16 (8), 30943102.CrossRefGoogle Scholar
Shumacher, J. & Eckhardt, B. 2000 On statistically stationary homogeneous shear turbulence. Europhys. Lett. 52, 627632.CrossRefGoogle Scholar
Shumacher, J., Sreenivasan, K. R. & Yeung, P. K. 2003 Derivative moments in turbulent shear flows. Phys. Fluids 15 (1), 8490.CrossRefGoogle Scholar
Smagorinsky, J. 1963 General circulation experiments with the primitive equations. I. The basic experiments. Mon. Weather Rev. 91.2.3.CO;2>CrossRefGoogle Scholar
de Souza, F. A., Nguyen, V. D. & Tavoularis, S. 1995 The structure of highly sheared turbulence. J. Fluid Mech. 303, 155167.CrossRefGoogle Scholar
Spalart, P. R. 1988 Direct simulation of a turbulent boundary layer uo to R = 1410.. J. Fluid Mech. 187, 6198.CrossRefGoogle Scholar
Stolz, S. & Adams, N. A. 1999 An approximate deconvolution procedure for large-eddy simulation. Phys. Fluids 11 (7), 16991701.CrossRefGoogle Scholar
Stolz, S., Adams, N. A. & Kleiser, L. 2001 An approximate deconvolution procedure for large-eddy simulationi with application to incompressible wall-boubnded flows. Phys. Fluids 13 (4), 9971015.CrossRefGoogle Scholar
Tavoularis, S. & Corrsin, S. 1981 a Experiments in nearly homogeneous turbulent shear flow with a uniform mean temperature gradient. Part 1. J. Fluid Mech. 104, 311347.CrossRefGoogle Scholar
Tavoularis, S. & Corrsin, S. 1981 b Experiments in nearly homogeneous turbulent shear flow with a uniform mean temperature gradient. Part 2. The fine structure. J. Fluid Mech. 104, 349367.CrossRefGoogle Scholar
Tavoularis, S. & Karnik, U. 1989 Further experiments on the evolution of turbulent stresses and scales in uniformly sheared turbulence. J. Fluid Mech. 204, 457478.CrossRefGoogle Scholar
Townsend, A. A. 1956 The Structure of Turbulent Shear Flow. Cambridge University Press.Google Scholar
Vasilyev, O., Lund, T. S. & Moin, P. 1998 A general class of commutative filters for LES in complex geometries. J. Comput. Phys. 146, 82104.CrossRefGoogle Scholar
Warhaft, Z. & Shen, X. 2002 On higher order mixed structure functions in laboratory shear flow. Phys. Fluids 14 (7), 24322438.CrossRefGoogle Scholar
Winckelmans, G. S., Wray, A. A. & Jeanmart, H. 2001 Explicit-filtering large-eddy simulation using the tensor-diffusivity model supplemented by a dynamic Smagorinsky term. Phys. Fluids 13 (5), 13851403.CrossRefGoogle Scholar
Yakhot, V. 2003 A simple model for self-sustained oscillations in homogeneous shear flow. Phys. Fluids 15 (2), L17L20.CrossRefGoogle Scholar