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A Study on the Characteristics of Flows around Building Groups Using a CFD Model

CFD 모델을 이용한 건물군 주변의 흐름 특성 연구

  • Lee, Hankyung (Department of Environmental Atmospheric Sciences, Pukyong National University) ;
  • Kim, Jae-Jin (Department of Environmental Atmospheric Sciences, Pukyong National University) ;
  • Lee, Young-Gon (Applied Meteorology Research Division, National Institute of Meteorological Research)
  • 이한경 (부경대학교 환경대기과학과) ;
  • 김재진 (부경대학교 환경대기과학과) ;
  • 이영곤 (국립기상과학원 응용기상연구과)
  • Received : 2015.04.16
  • Accepted : 2015.06.16
  • Published : 2015.09.30

Abstract

In this study, the characteristics of flows around building groups are investigated using a computational fluid dynamics (CFD) model. For this, building groups with different volumetric ratios in a fixed area are considered. As the volumetric ratio of the building group increases, the region affected by the building group is widened. However, the wind-speed reduced area rather decreases with the volumetric ratio near the ground bottom (z ${\lesssim}$ 0.7H, here, H is the height of the building group) and, above 0.7H, it increases. As the volumetric ratio decreases (that is, space between buildings was widened), the size of recirculation region decreases but flow recovery is delayed, resulting in the wider wind-speed reduced area. The increase in the volumetric ratio results in larger drag force on the flow above the roof level, consequently reducing wind speed above the roof level. However, above z ${\gtrsim}$ 1.7H, wind speed increases with the volumetric ratio for satisfying mass conservation, resultantly increasing turbulent kinetic energy there. Inside the building groups, wind speed decreased with the volumetric ratio and averaged wind speed is parameterized in terms of the volumetric ratio and background flow speed. The parameterization method is applied to producing averaged wind speed for 80 urban areas in 7 cities in Korea, showing relatively good performance.

Keywords

References

  1. Baik, J.-J., J.-J. Kim, and H. J. Fernando, 2003: A CFD model for simulating urban flow and dispersion. J. Appl. Meteorol., 42, 1636-1648. https://doi.org/10.1175/1520-0450(2003)042<1636:ACMFSU>2.0.CO;2
  2. Baik, J.-J., S. B. Park, and J.-J. Kim, 2009: Urban flow and dispersion simulation using a CFD model coupled to a mesoscale model. J. Appl. Meteorol. Clim., 48, 1667-1681. https://doi.org/10.1175/2009JAMC2066.1
  3. Britter, R. E., and S. R. Hanna, 2003: Flow and dispersion in urban areas. Annu. Rev. Fluid Mech., 35, 469-496. https://doi.org/10.1146/annurev.fluid.35.101101.161147
  4. Brown, M. J., R. E. Lawson, D. S. DeCroix, and R. L. Lee, 2001: Comparison of centerline velocity measurements obtained around 2D and 3D building arrays in a wind tunnel. Int. Soc. Environ. Hydraulics, Tempe, AZ.
  5. Byon, J. Y., Y. J. Choi, and B. G. Seo, 2010: Evaluation of urban weather forecast using WRF-UCM (Urban Canopy Model) over Seoul. Atmosphere, 20, 13-26 (in Korean with English abstract).
  6. Chu, A. K. M., R. C. W. Kwok, and K. N. Yu, 2005: Study of pollution dispersion in urban areas using Computational Fluid Dynamics (CFD) and Geographic Information System (GIS). Environmental Modelling & Software, 20, 273-277. https://doi.org/10.1016/S1364-8152(04)00127-6
  7. Franke, J., A. Hellsten, K. H. Schlunzen, and B. Carissimo, 2011: The COST 732 Best Practice Guideline for CFD simulation of flows in the urban environment:a summary. Int. J. Environ. Pollut., 44, 419-427. https://doi.org/10.1504/IJEP.2011.038443
  8. Gross, G., 2014: On the parametrization of urban land use in mesoscale models. Bound.-Layer Meteor., 150, 319-326. https://doi.org/10.1007/s10546-013-9863-5
  9. Kanda, M., A. Inagaki, T. Miyamoto, M. Gryschka, and S. Raasch, 2013: A new aerodynamic parametrization for real urban surfaces. Bound.-Layer Meteor., 148, 357-377. https://doi.org/10.1007/s10546-013-9818-x
  10. Kim, I. S., and Coauthors, 2003: The influence of around micrometeorology by development of Namak new town. Environ. Eng. Res., 5, 597-604.
  11. Kim, J.-J., 2007: The effects of obstacle aspect ratio on surrounding flows. Atmosphere, 17, 381-391 (in Korean with English abstract).
  12. Kim, J.-J., and J.-J. Baik, 2009: Effects of street-bottom and building-roof heating on flow in three-dimensional street canyons. Atmosphere, 27, 51-527 (in Korean with English abstract).
  13. Kim, J.-J., E. Pardyjak, D. Y. Kim, K. S. Han, and B. H. Kwon, 2014: Effects of building-roof cooling on flow and air temperature in urban street canyons. Asia-Pac. J. Atmos. Sci., 50, 365-375. https://doi.org/10.1007/s13143-014-0023-8
  14. Kim, M. J., R. J. Park, and J.-J. Kim, 2012: Urban air quality modeling with full O 3-NOx-VOC chemistry: Implications for O 3 and PM air quality in a street canyon. Atmos. Environ., 47, 330-340. https://doi.org/10.1016/j.atmosenv.2011.10.059
  15. Kwak, K. H., J.-J. Baik, Y. H. Ryu, and S. H. Lee, 2015: Urban air quality simulation in a high-rise building area using a CFD model coupled with mesoscale meteorological and chemistry-transport models. Atmos. Environ., 100, 167-177. https://doi.org/10.1016/j.atmosenv.2014.10.059
  16. Kwon, A. R., and J.-J. Kim, 2014: Improvement of building-construction algorithm for using GIS data and analysis of flow and dispersion around buildings. Korean J. Remote Sens., 30, 731-742. https://doi.org/10.7780/kjrs.2014.30.6.4
  17. Lee, J. H., J. W. Choi, and J.-J. Kim, 2009: The effects of an urban renewal plan on detailed air flows in an urban area. J. Korea Assoc. Geographic Inform. Studies, 12, 69-81.
  18. Lee, Y. S., and J.-J. Kim, 2011: Effects of an apartment complex on flow and dispersion in an urban area. Atmosphere, 21, 95-108 (in Korean with English abstract).
  19. Macdonald, R. W., R. F. Griffiths, and D. J. Hall, 1998: An improved method for the estimation of surface roughness of obstacle arrays. Atmos. Environ., 32, 1857-1864. https://doi.org/10.1016/S1352-2310(97)00403-2
  20. Neofytou, P., M. Haakana, A. Venetsanos, A, Kousa, J. Bartzis, and J. Kukkonen, 2008: Computational fluid dynamics modelling of the pollution dispersion and comparison with measurements in a street canyon in Helsinki. Environmental Modeling & Assessment, 13, 439-448. https://doi.org/10.1007/s10666-007-9110-x
  21. Sabatino, S., R. Buccolieri, B. Pulvirenti, and R. Britter, 2007: Simulations of pollutant dispersion within idealised urban-type geometries with CFD and integral models. Atmos. Environ., 41, 8316-8329. https://doi.org/10.1016/j.atmosenv.2007.06.052
  22. Santiago, J. L., A. Martilli, and F. Martin, 2007: CFD simulation of airflow over a regular array of cubes. Part I: Three-dimensional simulation of the flow and validation with wind-tunnel measurements. Bound.-Layer Meteor., 122, 609-634. https://doi.org/10.1007/s10546-006-9123-z
  23. Toparlar, Y., B. Blocken, P. Vos, G. J. F. van Heijst, W. D. Janssen, T. van Hooff, H. Montazeri, and H. J. P. Timmermans, 2015: CFD simulation and validation of urban microclimate: A case study for Bergpolder Zuid, Rotterdam. Build. Environ., 83, 79-90. https://doi.org/10.1016/j.buildenv.2014.08.004
  24. You, K. P., 2005: Wind tunnel experiment about effect of protection against wind according to the variation porosity of wind fence. Architectural, 21, 109-116.
  25. Zheng, M. H., Y. R. Guo, X. Q. Ai, T. Qin, Q. Wang, and J. M. Xu, 2010: Coupling GIS with CFD modeling to simulate urban pollutant dispersion. Mechanic Automation and Control Engineering (MACE), 2010 International Conference, 1785-1788.

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