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Numerical study of flow characteristics and pollutant dispersion using three RANS turbulence closure models

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Abstract

The flow characteristics and pollutant dispersion around building are investigated numerically using three RANS turbulence closure models, i.e. Standard k–ɛ model, Realizable k–ɛ and RNG k–ɛ model. Two physical configurations are considered in this study: a single isolated obstacle and two obstacles forming an idealized street canyon. Numerical simulations are performed with OpenFOAM® source code which utilise the finite volume method to solve the transport equations of mass, momentum, turbulent kinetic energy and turbulent dissipation rate. When numerical results were compared to wind tunnel experiments, it was found that the RNG k–ɛ turbulence model yielded the best agreement with experimental data. Moreover, the coefficients of the RNG k–ɛ turbulence model were adapted to better predict the flow characteristics in the urban boundary layer. The results obtained using the appropriate model show good agreement with experimental measurements for velocity flow profile and turbulent kinetic intensity. The prediction of pollutant dispersion reveals that in addition to the Reynolds number, the emission location plays an important role in the pollutant concentration distribution.

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Authors and Affiliations

  1. Laboratoire de Mécanique, Physique et Modélisation Mathématique, Université de Médéa, Médéa, Algeria

    L. Ben Ramoul & A. Korichi

  2. GRESPI EA 4694, University of Reims Champagne-Ardenne, 51687, Reims Cedex 2, France

    C. Popa & G. Polidori

  3. Laboratoire de recherche en Turbulence, Département Mécanique et Ingénierie Industrielle, Université de Toronto, Toronto, Canada

    H. Zaidi

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  1. L. Ben Ramoul
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  2. A. Korichi
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  4. H. Zaidi
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  5. G. Polidori
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Correspondence to C. Popa.

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Ben Ramoul, L., Korichi, A., Popa, C. et al. Numerical study of flow characteristics and pollutant dispersion using three RANS turbulence closure models. Environ Fluid Mech 19, 379–400 (2019). https://doi.org/10.1007/s10652-018-9628-2

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  • DOI: https://doi.org/10.1007/s10652-018-9628-2

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