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Dynamic roughness model for large-eddy simulation of turbulent flow over multiscale, fractal-like rough surfaces

Published online by Cambridge University Press:  03 May 2011

W. ANDERSON
Affiliation:
Department of Mechanical Engineering and Center for Environmental and Applied Fluid Mechanics, the Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA
C. MENEVEAU*
Affiliation:
Department of Mechanical Engineering and Center for Environmental and Applied Fluid Mechanics, the Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA
*
Email address for correspondence: meneveau@jhu.edu
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Abstract

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Many flows especially in geophysics involve turbulent boundary layers forming over rough surfaces with multiscale height distribution. Such surfaces pose special challenges for large-eddy simulation (LES) when the filter scale is such that only part of the roughness elements of the surface can be resolved. Here we consider LES of flows over rough surfaces with power-law height spectra Eh(k) ~ kβs (−3 ≤ βs < −1), as often encountered in natural terrains. The surface is decomposed into resolved and subgrid-scale height contributions. The effects of the unresolved small-scale height fluctuations are modelled using a local equilibrium wall model (log-law or Monin–Obukhov similarity), but the required hydrodynamic roughness length must be specified. It is expressed as the product of the subgrid-scale root-mean-square of the height distribution and an unknown dimensionless quantity, α, the roughness parameter. Instead of specifying this parameter in an ad hoc empirical fashion, a dynamic methodology is proposed based on test-filtering the surface forces and requiring that the total drag force be independent of filter scale or resolution. This dynamic surface roughness (DSR) model is inspired by the Germano identity traditionally used to determine model parameters for closing subgrid-scale stresses in the bulk of a turbulent flow. A series of LES of fully developed flow over rough surfaces are performed, with surfaces built using random-phase Fourier modes with prescribed power-law spectra. Results show that the DSR model yields well-defined, rapidly converging, values of α. Effects of spatial resolution and spectral slopes are investigated. The accuracy of the DSR model is tested by showing that predicted mean velocity profiles are approximately independent of resolution for the dynamically computed values of α, whereas resolution-dependent results are obtained when using other, incorrect, α values. Also, strong dependence of α on βs is found, where α ranges from α ~ 0.1 for βs = −1.2 to α ~ 10−5 for βs = −3.

Type
Papers
Copyright
Copyright © Cambridge University Press 2011

References

REFERENCES

Albertson, J. & Parlange, M. 1999 Surface length scales and shear stress: implications for land–atmosphere interaction over complex terrain. Water Resour. Res. 35, 21212132.CrossRefGoogle Scholar
Allen, J., Shockling, M., Kunkel, G. J. & Smits, A. J. 2007 Turbulent flow in smooth and rough pipes. Phil. Trans. R. Soc. Lond. A 365, 699714.Google ScholarPubMed
Allen, T. & Brown, A. R. 2002 Large-eddy simulation of turbulent-separated flow over rough hills. Boundary-Layer Meteorol. 102, 177198.Google Scholar
Anderson, W., Basu, S. & Letchford, C. W. 2007 Comparison of dynamic subgrid-scale models for simulations of neutrally buoyant shear-driven atmospheric boundary layer flows. Environ. Fluid Mech. 7, 195215.Google Scholar
Anderson, W. & Meneveau, C. 2010 A large-eddy simulation model for boundary layer flow over surfaces with horizontally resolved but vertically unresolved roughness elements. Boundary-Layer Meteorol. 137, 397415.CrossRefGoogle Scholar
Andrén, A., Brown, A. R., Graf, J., Mason, P. J., Moeng, C.-H., Nieuwstadt, F. T. M. & Schumann, U. 1993 Large-eddy simulation of the neutrally stratified boundary layer: A comparison of four computer codes. Q. J. R. Meteorol. Soc. 120, 14571484.Google Scholar
Avissar, R. & Pielke, R. A. 1989 A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon. Weath. Rev. 114, 22812296.Google Scholar
Bakken, O. M., Krogstad, P.-A., Ashrafian, A. & Andersson, H. 2005 Reynolds number effects in the outer layer of the turbulent flow in a channel with rough walls. Phys. Fluids 17, 065101.CrossRefGoogle Scholar
Bhaganagar, K. 2008 Direct numerical simulation of unsteady flow in channel with rough walls. Phys. Fluids 20, 101508.Google Scholar
Bhaganagar, K., Kim, J. & Coleman, G. 2004 Effect of roughness on wall-bounded turbulence. Flow Turbul. Combust. 72, 463492.CrossRefGoogle Scholar
Bou-Zeid, E., Meneveau, C. & Parlange, M. B. 2004 Large-eddy simulation of neutral atmospheric boundary layer flow over heterogeneous surfaces: blending height and effective roughness. Water Resour. Res. 40, W02505.Google Scholar
Bou-Zeid, E., Meneveau, C. & Parlange, M. B. 2005 A scale-dependent Lagrangian dynamic model for large-eddy simulation of complex turbulent flows. Phys. Fluids 17, 025105 (618).CrossRefGoogle Scholar
Bou-Zeid, E., Parlange, M. B. & Meneveau, C. 2007 On the parameterization of surface roughness at regional scales. J. Atmos. Sci. 64, 216227.CrossRefGoogle Scholar
Bradshaw, P. 2000 A note on ‘critical roughness height’ and ‘transitional roughness’. Phys. Fluids 12, 16111614.CrossRefGoogle Scholar
Brown, A. R., Hobson, J. M. & Wood, N. 2001 Large-eddy simulation of neutral turbulent flow over rough sinusoidal ridges. Boundary-Layer Meteorol. 98, 411441.CrossRefGoogle Scholar
Brutsaert, W. 2005 Hydrology: An Introduction. Cambridge University Press.Google Scholar
Castro, I. P. 2007 Rough-wall boundary layers: mean flow universality. J. Fluid Mech. 585, 469485CrossRefGoogle Scholar
Castro, I. P., Cheng, H. & Reynolds, R. 2006 Turbulence over urban-type roughness: deductions from wind tunnel measurements. Boundary-Layer Meteorol. 118, 109131.Google Scholar
Chamecki, M., Meneveau, C. & Parlange, M. B. 2009 Large-eddy simulation of pollen transport in the atmospheric boundary layer. J. Aerosol Sci. 40, 241255.Google Scholar
Cheng, H. & Castro, I. P. 2002 Near-wall flow over urban-like roughness. Boundary-Layer Meteorol. 104, 229259.CrossRefGoogle Scholar
Chester, S. & Meneveau, C. 2007 Renormalized numerical simulation of flow over planar and non-planar fractal trees. Environ. Fluid Mech. 7, 195215.CrossRefGoogle Scholar
Chester, S., Meneveau, C. & Parlange, M. B. 2007 Modeling of turbulent flow over fractal trees with renormalized numerical simulation. J. Comput. Phys. 225, 427448.CrossRefGoogle Scholar
Chow, F. K., Street, R. L., Xue, M. & Ferziger, J. H. 2000 Explicit filtering and reconstruction turbulence modeling for large-eddy simulation of neutral boundary layer flow. J. Atmos. Sci. 62, 20582077.Google Scholar
Chow, F. T. & Street, R. L. 2009 Evaluation of turbulence closure models for large-eddy simulation over complex terrain: flow over Askervein Hill. J. Appl. Meteorol. Climatol. 48, 10501065.Google Scholar
Coceal, O., Dobre, A., Thomas, T. G. & Belcher, S. E. 2007 Structure of turbulent flow over regular arrays of cubical roughness. J. Fluid Mech. 589, 375409.Google Scholar
Coceal, O., Thomas, T. G., Castro, I. P. & Belcher, S. E. 2006 Mean flow and turbulence statistics over groups of urban-like cubical obstacles. Boundary-Layer Meteorol. 121, 491519.CrossRefGoogle Scholar
Colebrook, C. F. & White, C. M. 1937 Experiments with fluid friction in roughened pipes. Proc. R. Soc. Lond. A 161, 367381.Google Scholar
Deardorff, J. W. 1970 A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers. J. Fluid Mech. 41, 453480.Google Scholar
Flack, K. A. & Schultz, M. P. 2010 Review of hydraulic roughness scales in the fully rough regime. ASME J. Fluids Engng 132, 041203 (110).Google Scholar
Gal-Chen, T. & Sommerville, R. C. J. 1975 a On the use of a coordinate transformation for the solution of the Navier–Stokes equations. J. Comput. Phys. 17, 209228.Google Scholar
Gal-Chen, T. & Sommerville, R. C. J. 1975 b Numerical solution of the Navier–Stokes equations with topography. J. Comput. Phys. 17, 276310.CrossRefGoogle Scholar
Garratt, J. R. 1977 The Atmospheric Boundary Layer. Cambridge University Press.Google Scholar
Germano, M. 1992 Turbulence: the filtering approach. J. Fluid Mech. 238, 325336.CrossRefGoogle Scholar
Germano, M., Piomelli, U., Moin, P. & Cabot, W. H. 1991 A dynamic subgrid-scale eddy viscosity model. Phys. Fluids A 3, 17601765.Google Scholar
Hobson, J. M., Wood, N. & Brown, A. R. 1999 Large-eddy simulations of neutrally stratified flow over surfaces with spatially varying roughness length. Q. J. R. Meteorol. Soc. 125, 19371958.CrossRefGoogle Scholar
Hurst, D. & Vassilicos, J. C. 2007 Scalings and decay of fractal-generated turbulence. Phys. Fluids 19, 035103.CrossRefGoogle Scholar
Iaccarino, G. & Verzicco, R. 2003 Immersed boundary technique for turbulent flow simulations. Appl. Mech. Rev. 56, 331347.CrossRefGoogle Scholar
Jarvis, P. G., James, G. B. & Landsberg, J. J. 1976 Coniferous forest. In Vegetation and the Atmosphere (ed. Monteith, J. L.), vol. 2, pp. 171240. Academic Press.Google Scholar
Jiménez, J. 2004 Turbulent flow over rough walls. Annu. Rev. Fluid Mech. 36, 173196.Google Scholar
Kaimal, J. C. & Finnigan, J. J. 1994 Atmospheric Boundary Layer Flows: Their Structure and Measurement. Oxford University Press.Google Scholar
Kanda, M., Moriwaki, R. & Kasamatsu, F. 2004 Large-eddy simulation of turbulent organized structures within and above explicitly resolved cube arrays. Boundary-Layer Meteorol. 112, 343368.Google Scholar
Kosović, B. 1997 Subgrid-scale modelling for the large-eddy simulation of high-Reynolds-number boundary layers. J. Fluid Mech. 336, 151182.CrossRefGoogle Scholar
Lilly, D. K. 1966 On the application of the eddy viscosity concept in the inertial subrange of turbulence. NCAR Manuscript 123, 119.Google Scholar
Mandelbrot, B. B. 1982 The Fractal Geometry of Nature. Freeman.Google Scholar
Mason, P. J. & Callen, N. S. 1986 On the magnitude of the subgrid-scale eddy coefficient in large-eddy simulations of turbulent channel flow. J. Fluid Mech. 162, 439462.Google Scholar
Mavriplis, D. J. 1997 Unstructured grid techniques. Annu. Rev. Fluid Mech. 29, 473514.Google Scholar
Meneveau, C. & Katz, J. 2000 Scale-invariance and turbulence models for large-eddy simulation. Annu. Rev. Fluid Mech. 32, 132.CrossRefGoogle Scholar
Mittal, R. & Iaccarino, G. 2005 Immersed boundary methods. Annu. Rev. Fluid Mech. 37, 239261Google Scholar
Monin, A. S. & Obukhov, A. M. 1954 Basic laws of turbulent mixing in the ground layer of the atmosphere. Tr. Geofiz. Inst., Akad. Nauk SSSR 151, 163187.Google Scholar
Nakayama, A., Hori, K. & Street, R. L. 2004 Filtering and LES of flow over irregular rough boundary. Center for Turbulence Res.: Proc. of Summer Prog. 145–156.Google Scholar
Nakayama, A. & Sakio, K. 2002 Simulation of flows over wavy rough boundaries. Center for Turbulence Res., Annu. Res. Briefs, Stanford Univ./NASA Ames Res. Center 313–324.Google Scholar
Nikuradse, J. 1950 Laws of flow in rough pipes. NACA TM 1292.Google Scholar
Orey, S. 1970 Z. Wahrscheinlichkeitstheorie Verw. Geb. 15, 249.CrossRefGoogle Scholar
Orlandi, P. & Leonardi, S. 2006 Direct numerical simulation of channel flow with a rib-roughened wall. J. Turbul. 7 (53), 122.Google Scholar
Orlandi, P. & Leonardi, S. 2008 Direct numerical simulation of three-dimensional turbulent rough channels: parameterization and flow physics. J. Fluid Mech. 606, 399415.CrossRefGoogle Scholar
Orszag, S. A. 1970 Transform method for calculation of vector coupled sums: Application to the spectral form of the vorticity equation. J. Atmos. Sci. 27, 890895.Google Scholar
Passalacqua, P., Porté-Agel, F., Foufoula-Georgiou, E. & Paola, C. 2006 Application of dynamic subgrid-scale concepts from large-eddy simulations to modeling landscape evolution. Water Resour. Res. 42, W06D11.Google Scholar
Phillips, O. M. 1958 The equilibrium range in the spectrum of wind-generated waves. J. Fluid Mech. 4, 426434.Google Scholar
Piomelli, U., Moin, P. & Ferziger, J. H. 1988 Model consistency in large eddy simulation of turbulent channel flows. Phys. Fluids 31, 18841891.Google Scholar
Porté-Agel, F., Meneveau, C. & Parlange, M. B. 2000 A scale-dependent dynamic model for large-eddy simulation: application to a neutral atmospheric boundary layer. J. Fluid Mech. 415, 261284.Google Scholar
Queiros-Conde, D. & Vassilicos, J. C. 2001 Turbulent wakes of 3D fractal grids. In Intermittency in Turbulent Flows (ed. Vassilicos, J. C.), pp. 136166. Cambridge University Press.Google Scholar
Raupach, M. R. 1994 Simplified expressions for vegetation roughness length and zero-plane displacement as functions of canopy height and area index. Boundary-Layer Meteorol. 71, 211216.CrossRefGoogle Scholar
Raupach, M. R., Antonia, R. A. & Rajagopalan, S. 1991 Rough-wall turbulent boundary layers. Appl. Mech. Rev. 44, 125.Google Scholar
Rodriguez-Iturbe, I., Marani, M., Rigon, R. & Rinaldo, A. 1994 Self-organized river basin landscapes: Fractal and multifractal characteristics. Water Resour. Res. 30, 35313539.CrossRefGoogle Scholar
Rodriguez-Iturbe, I. & Rinaldo, A. 1997 Fractal River Basins: Chance and Self-Organization. Cambridge University Press.Google Scholar
Schlichting, H. 1936 Experimentelle Untersuchungen zum Rauhigkeitsproblem. Ing.-Arch. 7, 134.Google Scholar
Schultz, M. P. & Flack, K. A. 2005 Outer layer similarity in fully rough turbulent boundary layers. Exp. Fluids 38, 328340.CrossRefGoogle Scholar
Schultz, M. P. & Flack, K. A. 2007 The rough-wall turbulent boundary layer from the hydraulically smooth to the fully rough. J. Fluid Mech. 580, 381405.CrossRefGoogle Scholar
Schultz, M. P. & Flack, K. A. 2009 Turbulent boundary layers on a systematically-varied rough wall. Phys. Fluids 21, 015104.Google Scholar
Seoud, R. E. & Vassilicos, J. C. 2007 Dissipation and decay of fractal-generated turbulence. Phys. Fluids 19, 105108.Google Scholar
Shaw, R. H. & Schumann, U. 1992 Large-eddy simulation of turbulent flow above and within a forest. Boundary-Layer. Meteorol. 61, 4764.Google Scholar
Shockling, M. A., Allen, J. J. & Smits, A. J. 2006 Roughness effects in turbulent pipe flow. J. Fluid Mech. 564, 267285.Google Scholar
Smagorinsky, J. 1963 General circulation experiments with the primitive equations, Part 1. The basic experiment. Mon. Weath. Rev. 91, 99164.Google Scholar
Smith, F. B. & Carson, D. J. 1977 Some thoughts on the specification of the boundary-layer relevant to numerical modelling. Boundary-Layer. Meteorol. 12, 307330.Google Scholar
Staicu, A., Mazzi, B., Vassilicos, J. C. & van der Water, W. 2003 Turbulent wakes of fractal objects. Phys. Rev. E 67, 066306.Google Scholar
Tsai, J.-L. & Tsuang, B.-J. 2005 Aerodynamic roughness over an urban area and over two farmlands in a populated area as determined by wind profiles and surface energy flux measurements. Agric. Forest. Meteorol. 132, 154170.Google Scholar
Wan, F. & Porté-Agel, F. 2010 A large-eddy simulation study of turbulent flow over multiscale topography. EGU Gen. Assembly, vol. 12, EGU2010-10875.Google Scholar
Xie, Z. T., Coceal, O. & Castro, I. P. 2008 Large-eddy simulation of flows over random urban-like obstacles. Boundary-Layer Meteorol. 129, 123.Google Scholar
Zagarola, M. V. & Smits, A. J. 1998 Mean-flow scaling of turbulent pipe flow. J. Fluid Mech. 373, 3379.Google Scholar