Hostname: page-component-84b7d79bbc-fnpn6 Total loading time: 0 Render date: 2024-07-30T00:54:27.908Z Has data issue: false hasContentIssue false

Dependence of the Smagorinsky-Lilly's Constant on Inertia, Wind Stress, and Bed Roughness for Large Eddy Simulations

Published online by Cambridge University Press:  05 May 2011

W.-H. Chung*
Affiliation:
Department of Civil Engineering, Chinese Military Academy, Fengshan, Taiwan 83059, R.O.C.
*
*Associate Professor
Get access

Abstract

Equations governing large eddy simulations are usually closed by incorporating with the Smagorinsky-Lilly's turbulence model of eddy viscosity. The model contains a so-called filtering length and a Smagorinsky-Lilly “constant” that changes among different researchers. The variation range of the constant is wide and its value is usually determined in a sense of “guessing”. Since the constant is closely related to the magnitude of eddy viscosity, hence to our numerical solutions eventually, setting a more precise and determinate procedure for prescribing the constant seems to be worthy it. The constant, CSL, is first estimated in use of the properties of fluid flow within the inertia subrange. Then, along with a general derivation, the explicit closed-form expression for the constant is presented for steady uniform flows. It is found that, with the analogy between the filtering technique and Reynolds average, CSL may not necessarily be constant but proportional to the Manning n and water depth. Other than the determination of CSL, the vertical flow velocity profile in an infinitely long wide rectangular channel without spiral flow motion is obtained through the use of the Smagorinsky-Lilly's turbulence closure model. It is shown analytically that the velocity profile in unsteady open channel flow can be expressed as a function of an integration function Jn(z) that accounts for wind stress and inertia terms. With the velocity profile, effects of inertia terms, wind stress, and channel bed roughness on CSL are deeply explored in response to the dependence of CSL on Jn(z).

Type
Articles
Copyright
Copyright © The Society of Theoretical and Applied Mechanics, R.O.C. 2006

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

1.Smagorinsky, J., “General Circulation Experiments with the Primitive Equation: I,The Basic Experiment, Monthly Weather Review, 91(3), Mar. (1963).Google Scholar
2.Babajimopoulos, C. and Bedford, K. W., “Formulating Lake Models which Preserve Spetral Statistics,” J. of Hydraul. Div., Proc. of ASCE, 106(HY1), pp. 119 (1980).Google Scholar
3.Bedford, K. W., Spectra Preservation Capabilities of Great Lakes Transport Models, in Transport Models for Inland and Coastal Waters, Fischer, H. B. ed., Academic Press (1981).Google Scholar
4.Antonopoulos-Domis, M., “Large-Eddy Simulation of a Passive Scalar in Isotropie Turbulence,” J. of Fluid Mech., 104, pp. 5579 (1981).CrossRefGoogle Scholar
5.Deardorff, J. W., “The Use of Subgrid Transport Equations in a Three-Dimensional Model of Atmospheric Turbulence,” J. of Fluids Engineering, Transactions of the ASME, pp. 429438 (1973).CrossRefGoogle Scholar
6.Deardorff, J. W., “Three-Dimensional Numerical Study of the Height and Mean Structure of a Heated Planetary Boundary Layer,” Boundary-Layer Meteorology, 7, pp. 81106 (1974).CrossRefGoogle Scholar
7.Bedford, K. W. and Babajimopoulos, C., “Verifying Lake Transport Models with Spectral Statistics,” J. of Hydraul. Div., pp. 2138 (1980).CrossRefGoogle Scholar
8.Mellor, G. L. and Yamada, T., “Development of a Turbulence Closure Model for Geophysical Fluid Problems,” Reviews of Geophysics and Space Physics, 20(4), pp. 851875 (1982).CrossRefGoogle Scholar
9.Lilly, D. K., “The Representation of Small-Scale Turbulence in Numerical Simulation Experiments,” Proc. IBM Sci. Computing Symp. Environmental Sci., IBM Form, pp. 195210 (1967).Google Scholar
10.Champagne, F. H., “The Fine Structure of the Turbulent Velocity Field,” J. of Fluid Mech., 86, pp. 67108 (1978).CrossRefGoogle Scholar
11.Tzvi, G.-C, Mei, X. and Eberhard, K. L., “Estimation of Atmospheric Boundary Layer Fluxes and Other Turbulence Parameters from Doppler Lidar Data,” J. Geop. Res., 97(D17),pp. 1840918423 (1992).Google Scholar
12.Aldama, A. A., Filtering Techniques for Turbulent Flow Simulation, Springer-Verlag, 56 (1990).CrossRefGoogle Scholar
13.Kwak, D., Reynolds, W. C. and Gerziger, J. H., “Three-Dimensional Time Dependent Computation of Turbulent Flow,” Report No. TF-5, Dept. of Mech. Eng., Stanford University (1975).Google Scholar
14.Love, M. D., “Subgrid Modeling Studies with Burger's Equation,” J. Fluid Mech., 100, pp. 87110 (1980).CrossRefGoogle Scholar
15.Schmidt, H. and Schumann, U., “Coherent Structure of the Convective Boundary Layer Derived from Large-Eddy Simulations,” J. of Fluid Mech., 200, pp. 511565, Great Britain (1989).Google Scholar
16.Liao, C.B, Wu, M. F. and Gou, M. H., “Large Eddy Simulation of a Round Jet in a Cross Flow,” M14∼M21, Proceedings of the 13th Hydraulic Engineering Conference, July, Taiwan (2002).Google Scholar
17.Hsu, U. K., Tai, C. H. and Tsai, C. H., “All Speed and High-Resolution Scheme Applied to Three-Dimensional Multi-Block Complex Flowfield System,” Journal of Mechanics, 20, pp. 1325 (2004).CrossRefGoogle Scholar
18.Mason, R. J. and Callen, N. S., “On the Magnitude of the Subgrid-Scale Eddy Coefficient in Large Eddy Simulations of Turbulent Channel Flow,” J.Fluid Mech., 162, pp. 439462 (1986).CrossRefGoogle Scholar
19.Tennekes, H. and Lumley, J. L., The First Course of Turbulence, The MIT Press, Cambridge, Massachusetts and London, England.CrossRefGoogle Scholar
20.Corrsin, S., “Further Generalizations of Onsager's Cascade Model for Turbulent Spectra,” Physics of Fluids, 7, 1156 (1964).CrossRefGoogle Scholar
21.Pao, Y. H., “Structure of Turbulent Velocity and Scalar Fields at Large Wave Numbers,” Physics of Fluids, 8, 1063 (1965).CrossRefGoogle Scholar
22.Friedlander, S. K. and Topper, L., eds., Turbulence: Classical Papers on Statistical Theory, Interscience, New York (1962).Google Scholar
23.Kolmogorov, A. N., C. R. Acad. Sci. U. R. S. S. 30(301) (1941).Google Scholar
24.Kolmogorov, A. N., C. R. Acad. Sci. U. R. S. S. 31(538) (1941).Google Scholar
25.Kolmogorov, A. N., C. R. Acad. Sci. U. R. S. S. 32(16) (1941).Google Scholar
26.Lilly, D. K., “Numerical Simulation of Two-Dimensional Turbulence, High-Speed Computing in Fluid Dynamics,” The Physics of Fluids Supplement II, II–240LL-249, (1969).CrossRefGoogle Scholar
27.Deardorff, J. W., “A Numerical Study of Three-Dimensional Turbulent Channel Flow at Large Reynolds Numbers,” J. Fluid Mech., 41(2), pp. 453480 (1970).CrossRefGoogle Scholar
28.Deardorff, J. W., “On the Magnitude of the Subgrid Scale Eddy Coefficient,” J. of Computational Physics, 7, pp. 120133 (1971).CrossRefGoogle Scholar
29.Panton, R. L., Incompressible Flow, John Wiley & Sons, (1987).Google Scholar
30.Daily, J. W. and Harleman, D. R., Fluid Dynamics,Addison-Wesley Inc. (1973).Google Scholar
31.Lai, Chintu, “Numerical Modeling of Unsteady Open-Channel Flow,” Advances in Hydroscience, 14, Academic Press Inc., pp. 161254 (1986).Google Scholar
32.Aldama, A. Alvaro and Chung, W. H., “Three-Dimensional Numerical Simulation of Flows in Shallow Water Bodies Through the Use of Space and Space-Time Filtering Approaches,” First Progress Report for Grant No. CTS-8908877, Department of Civil Engineering & Operations Research, Princeton University (1991).Google Scholar
33.Roberson, J. A. and Crowe, C.T, Engineering Fluid Mechanics, 2nd ed., Houghton Mifflin Company, Boston (1980).Google Scholar
34.Csanady, G. T., Circulation in the Coastal Ocean, D. Reidei Pub. Co., p. 279 (1982).CrossRefGoogle Scholar
35.Amorocho, J. and Devries, J. J., “A New Evaluation of the Wind Stress Coefficient over Water Surfaces,” J. Geophys. Res., 85, pp. 433442 (1980).CrossRefGoogle Scholar