Boundary-Layer Meteorology

, Volume 135, Issue 1, pp 133–150 | Cite as

Comparison Between Large-Eddy Simulation and Reynolds-Averaged Navier–Stokes Computations for the MUST Field Experiment. Part II: Effects of Incident Wind Angle Deviation on the Mean Flow and Plume Dispersion

  • A. Dejoan
  • J. L. Santiago
  • A. Martilli
  • F. Martin
  • A. Pinelli
Article

Abstract

Large-eddy simulations (LES) and Reynolds-averaged Navier–Stokes (RANS) computations of pollutant dispersion are reported for the Mock Urban Setting Test (MUST) field experiment flow. In particular we address the effects of incident wind angle deviation on the mean velocity and on the mean concentration fields. Both computational fluid dynamical methods are assessed by comparing the simulation results with experimental field data. The comparative analysis proposes to relate the plume deflection with the flow channelling effects. The results show that the plume deflection angle varies with the altitude. As the ground is approached the plume is shown to be almost aligned with the street canyon direction and independent of the incident wind directions considered. At higher altitudes well above the obstacles, the plume direction is aligned with the mean wind direction as in dispersion over flat terrain. The near-ground plume deflection is the consequence of a strong channelling effect in the region near the ground. The mean concentration profiles predicted by LES and RANS are both in good qualitative agreement with experimental data but exhibit discrepancies that can be partly explained by the influence of small incident wind angle deviation effects. Compared to RANS, LES predicts a higher channelling and thus a higher deflection of the plume. Results on the fluctuating intensity of the concentration obtained from LES show a satisfactory agreement with experiments. This information is not available from RANS for which only the mean concentration modelling is considered.

Keywords

Channelling effects Large-eddy simulation MUST experiment Reynolds-averaged Navier–Stokes Plume deflection 

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References

  1. Bezpalcova K (2007) Physical modelling of flow and dispersion in an urban canopy. PhD thesis, Faculty of Mathematics and Physics, Charles University, Prague, 193 ppGoogle Scholar
  2. Biltoft CA (2001) Customer report for Mock Urban Setting Test (MUST). DPG document WDTC-TP-01-028, West Desert Test Center, U.S. Army Dugway Porving Ground, Dugway, Utah, 58 ppGoogle Scholar
  3. Camelli FE, Lohner R, Hanna SR (2005) VLES Study of MUST experiment. In: 43rd AIAA Aerospace Meeting and Exhibit, January 10–13, Reno, Nevada, paper 1279Google Scholar
  4. Cole T, Li X, Eising C, Princevac M (2006) Turbulence and channeling in a simple urban environment. In: AMS 17th symposium on boundary layer and turbulence, San DiegoGoogle Scholar
  5. Jasak H (1996) Error analysis and estimation for the finite volume method with applications to fluid flow. PhD thesis, Imperial College, University of London, 394 ppGoogle Scholar
  6. Kim JJ, Baik JJ (2004) A numerical study of the effects of ambient wind direction on flow and dispersion in urban street canyons using the RNG k-epsilon turbulence model. Atmos Environ 38: 3039–3048CrossRefGoogle Scholar
  7. Leitl B, Bezpalcova K, Harms F (2007) Wind tunnel modelling of the MUST experiment. In: 11th international conference on harmonisation within atmospheric dispersion modelling for regulatory purposes, Cambridge, July 2–5, UK, 5 ppGoogle Scholar
  8. Milliez M, Carissimo B (2007) Numerical simulations of pollutant dispersion in an idealized urban area for different meteorological conditions. Boundary-Layer Meteorol 122: 321–342CrossRefGoogle Scholar
  9. Neto AS, Grand D, Metais O (1993) A numerical investigation of the coherent vortices in turbulence behind a backward-facing step. J Fluid Mech 256: 1–25CrossRefGoogle Scholar
  10. Santiago JL, Martilli A, Martin F (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. Boundary-Layer Meteorol 122: 609–634CrossRefGoogle Scholar
  11. Santiago JL, Dejoan A, Martilli A, Martin F, Pinelli A (2010) Comparison between large-eddy simulation and Reynolds-averaged Navier–Stokes computations for the MUST field experiment. Part I: study of the flow for an incident wind directed perpendicularly to the front array of the containers. Boundary-Layer Meteorol. doi:10.1007/s10546-010-9466-3
  12. Tominaga Y, Stathopoulos T (2007) Turbulent Schmidt numbers for CFD analysis with various types of flow field. Atmos Environ 41: 8091–8099CrossRefGoogle Scholar
  13. Yee E, Biltoft CA (2004) Concentration fluctuation measurements in a plume dispersing through a regular array of obstacles. Boundary-Layer Meteorol 111: 363–415CrossRefGoogle Scholar
  14. Yee E, Gailis RM, Hill A, Hilderman T, Kiel D (2006) Comparison of wind tunnel and water-channel simulations of plume dispersion through a large array of obstacles with a scales field experiment. Boundary-Layer Meteorol 121: 389–432CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • A. Dejoan
    • 1
  • J. L. Santiago
    • 2
  • A. Martilli
    • 2
  • F. Martin
    • 2
  • A. Pinelli
    • 1
  1. 1.Energy DepartmentResearch Center for Energy, Environment and Technology (CIEMAT)MadridSpain
  2. 2.Environment DepartmentResearch Center for Energy, Environment and Technology (CIEMAT)MadridSpain

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