Boundary-Layer Meteorology

, Volume 139, Issue 3, pp 457–485 | Cite as

Estimation of Roughness Parameters Within Sparse Urban-Like Obstacle Arrays

  • Byung-Gu Kim
  • Changhoon Lee
  • Seokjun Joo
  • Ki-Cheol Ryu
  • Seogcheol Kim
  • Donghyun You
  • Woo-Sup Shim
Article

Abstract

We conduct wind-tunnel experiments on three different uniform roughness arrays composed of sparsely distributed rectangular cylinders for the estimation of surface parameters. Roughness parameters such as the roughness length z0 and zero-plane displacement d are extracted using a best-fit approximation of the measured wind velocity. We also perform a large-eddy simulation (LES) to confirm that four sampling points are sufficient to surrogate a space average above the canopy layer of the sparse roughness arrays. We propose a new morphological model from a systematic analysis of experimental data on the arrays. The friction velocity predicted by the proposed model agrees well with the peak value of the measured Reynolds shear stress \({(-\left<\overline{u'w'}\right>)^{0.5}}\). The proposed model is further validated in an additional wind-tunnel experiment conducted on a scaled configuration of a real urban area exposed to four wind directions. The proposed model is found to perform very well particularly in the estimation of the friction velocity, readily leading to a better estimation of turbulence, which is essential for an accurate prediction of pollutant dispersion.

Keywords

Morphological method Roughness parameters Surface parameters Urban dispersion 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bentham T, Britter R (2003) Spatially averaged flow within obstacle arrays. Atmos Environ 37(15): 2037–2043CrossRefGoogle Scholar
  2. Britter R, Hanna S (2003) Flow and dispersion in urban areas. Annu Rev Fluid Mech 35(1): 469–496CrossRefGoogle Scholar
  3. Cheng H, Castro I (2002a) Near wall flow development after a step change in surface roughness. Boundary-Layer Meteorol 105(3): 411–432CrossRefGoogle Scholar
  4. Cheng H, Castro I (2002b) Near wall flow over urban-like roughness. Boundary-Layer Meteorol 104(2): 229–259CrossRefGoogle Scholar
  5. Christen A, Rotach M, Vogt R (2009) The budget of turbulent kinetic energy in the urban roughness sublayer. Boundary-Layer Meteorol 131(2): 193–222CrossRefGoogle Scholar
  6. Cionco RM (1965) A mathematical model for air flow in a vegetative canopy. J Appl Meteorol 4(4): 517–522CrossRefGoogle Scholar
  7. Coceal O, Thomas T, Castro I, Belcher S (2006) Mean flow and turbulence statistics over groups of urban-like cubical obstacles. Boundary-Layer Meteorol 121(3): 491–519CrossRefGoogle Scholar
  8. Coceal O, Thomas T, Belcher S (2007) Spatial variability of flow statistics within regular building arrays. Boundary-Layer Meteorol 125(3): 537–552CrossRefGoogle Scholar
  9. Counihan J (1971) Wind tunnel determination of the roughness length as a function of the fetch and the roughness density of three-dimensional roughness elements. Atmos Environ (1967) 5(8): 637–642CrossRefGoogle Scholar
  10. Grimmond C, Oke T (1999) Aerodynamic properties of urban areas derived from analysis of surface form. J Appl Meteorol 38(9): 1262–1292CrossRefGoogle Scholar
  11. Hagishima A, Tanimoto J, Nagayama K, Meno S (2009) Aerodynamic parameters of regular arrays of rectangular blocks with various geometries. Boundary-Layer Meteorol 132(2): 315–337CrossRefGoogle Scholar
  12. Hanna S, Britter R (2002) Wind flow and vapor cloud dispersion at industrial and urban sites. CCPS, New York, p 208Google Scholar
  13. Hanna S, Tehranian S, Carissimo B, Macdonald R, Lohner R (2002) Comparisons of model simulations with observations of mean flow and turbulence within simple obstacle arrays. Atmos Environ 36(32): 5067–5079CrossRefGoogle Scholar
  14. Hanna S, Brown M, Camelli F, Chan S, Coirier W, Hansen O, Huber A, Kim S, Reynolds R (2006) Detailed simulations of atmospheric flow and dispersion in downtown Manhattan. Bull Am Meteorol Soc 87: 1713–1726CrossRefGoogle Scholar
  15. Inagaki A, Kanda M (2008) Turbulent flow similarity over an array of cubes in near-neutrally stratified atmospheric flow. J Fluid Mech 615: 101–120CrossRefGoogle Scholar
  16. Iyengar AKS, Farell C (2001) Experimental issues in atmospheric boundary layer simulations: roughness length and integral length scale determination. J Wind Eng Ind Aerodyn 89: 1059–1080CrossRefGoogle Scholar
  17. Jackson PS (1981) On the displacement height in the logarithmic velocity profile. J Fluid Mech 111: 15–25CrossRefGoogle Scholar
  18. Jiménez J (2004) Turbulent flows over rough walls. Annu Rev Fluid Mech 36(1): 173–196CrossRefGoogle Scholar
  19. Kastner-Klein P, Rotach M (2004) Mean flow and turbulence characteristics in an urban roughness sublayer. Boundary-Layer Meteorol 111(1): 55–84CrossRefGoogle Scholar
  20. Lettau H (1969) Note on aerodynamic roughness parameter estimation on the basis of roughness element description. J Appl Meteorol 8: 828–832CrossRefGoogle Scholar
  21. Macdonald R (2000) Modelling the mean velocity profile in the urban canopy layer. Boundary-Layer Meteorol 97(1): 25–45CrossRefGoogle Scholar
  22. Macdonald R, Griffiths R, Hall D (1998) An improved method for the estimation of surface roughness of obstacle arrays. Atmos Environ 32(11): 1857–1864CrossRefGoogle Scholar
  23. Macdonald R, Carter S, Slawson P (2000) Measurements of mean velocity and turbulence statistics in simple obstacle array at 1:200 scale. Thermal Fluids Report 2000–1, University of Waterloo, Canada, 130 ppGoogle Scholar
  24. Macdonald RW, Carter Schofield S, Slawson PR (2002) Physical modelling of urban roughness using arrays of regular roughness elements. Water Air Soil Pollut Focus 2(5): 541–554CrossRefGoogle Scholar
  25. Martilli A (2009) On the derivation of input parameters for urban canopy models from urban morphological datasets. Boundary-Layer Meteorol 130(2): 301–306CrossRefGoogle Scholar
  26. McDermott R, McGrattan K, Hostikka S, Floyd J (2009) Fire dynamics simulator (version 5) technical reference guide volume 2: verification. National Institute of Standards and Technology, 75 ppGoogle Scholar
  27. McGrattan K, Hostikka S, Floyd J, Baum H, Rehm R, Mell W, McDermott R (2009a) Fire dynamics simulator (version 5) technical reference guide volume 1: mathematical model. National Institute of Standards and Technology, 108 ppGoogle Scholar
  28. McGrattan K, Hostikka S, Floyd J, McDermott R (2009b) Fire dynamics simulator (version 5) technical reference guide volume 3: validation. National Institute of Standards and Technology, 298 ppGoogle Scholar
  29. Petersen R (1997) A wind tunnel evaluation of methods for estimating surface roughness length at industrial facilities. Atmos Environ 31(1): 45–57CrossRefGoogle Scholar
  30. Ploss A, Castro I, Cheng H (2000) The surface region of rough wall boundary layers. In: Dopazo C (ed) Advances in turbulence VIII. International Center for Numerical Methods in Engineering, pp 455–459Google Scholar
  31. Raupach MR, Thom AS, Edwards I (1980) A wind-tunnel study of turbulent flow close to regularly arrayed rough surfaces. Boundary-Layer Meteorol 18(4): 373–397CrossRefGoogle Scholar
  32. Raupach MR, Coppin PA, Legg BJ (1986) Experiments on scalar dispersion within a model plant canopy, Part I: the turbulence structure. Boundary-Layer Meteorol 35(1): 21–52CrossRefGoogle Scholar
  33. Rotach M (2001) Simulation of urban-scale dispersion using a Lagrangian stochastic dispersion model. Boundary-Layer Meteorol 99(3): 379–410CrossRefGoogle Scholar
  34. Roth M (2000) Review of atmospheric turbulence over cities. Q J Roy Meteorol Soc 126(564): 941–990CrossRefGoogle Scholar
  35. Santiago JL, Martilli A (2010) A dynamic urban canopy parameterization for mesoscale models based on computational fluid dynamics Reynolds-averaged Navier-Stokes microscale simulations. Boundary-Layer Meteorol 137(3): 417–439CrossRefGoogle Scholar
  36. Schlichting H, Gersten K (2000) Boundary-layer theory, 8th edn. Springer, Germany, p 799Google Scholar
  37. Shah KB (1998) Large eddy simulations of flow past a cubic obstacle. PhD thesis, Stanford University, 212 ppGoogle Scholar
  38. Snyder WH, Castro IP (2002) The critical Reynolds number for rough-wall boundary layers. J Wind Eng Ind Aerodyn 90(1): 41–54CrossRefGoogle Scholar
  39. Stull R (1988) An introduction to boundary layer meteorology. Kluwer Academic Publisher, The Netherlands, p 666Google Scholar
  40. Tamura T (2008) Towards practical use of LES in wind engineering. J Wind Eng Ind Aerodyn 96(10–11): 1451–1471CrossRefGoogle Scholar
  41. Theurer W (1993) Dispersion of ground-level emissions in complex built-up areas. PhD thesis, Doctoral thesis, Department of Architecture, University of Karlsruhe, GermanyGoogle Scholar
  42. Theurer W, Baechlin W, Plate EJ (1992) Model study of the development of boundary layers above urban areas. J Wind Eng Ind Aerodyn 41(1–3): 437–448CrossRefGoogle Scholar
  43. Visual Numerics Inc.: (1997) IMSL STAT/LIBRARY: Fortran subroutines for statistical applications. Visual Numerics Inc., TexasGoogle Scholar
  44. Werner H, Wengle H (1992) Large-eddy simulation of turbulent flow over and around a cube in a plate channel. In: Turbulent shear flows: selected papers from the eighth international symposium on turbulent shear flows, vol 8. Springer-Verlag, Berlin, pp 155–168Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Byung-Gu Kim
    • 1
    • 2
  • Changhoon Lee
    • 1
    • 3
  • Seokjun Joo
    • 4
  • Ki-Cheol Ryu
    • 4
  • Seogcheol Kim
    • 5
  • Donghyun You
    • 1
    • 6
  • Woo-Sup Shim
    • 7
  1. 1.Department of Computational Science and EngineeringYonsei UniversitySeoulKorea
  2. 2.LG ElectronicsSeoulKorea
  3. 3.Department of Mechanical EngineeringYonsei UniversitySeoulKorea
  4. 4.TESolutionAnseong, Kyungi-doKorea
  5. 5.Boolt SimulationSeoulKorea
  6. 6.Department of Mechanical EngineeringCarnegie Mellon UniversityPittsburghUSA
  7. 7.Agency for Defense DevelopmentDaejeonKorea

Personalised recommendations