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Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas

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Abstract

Noxious atmospheric releases may originate from both accidents and malicious activities. They are a major concern for public authorities or first responders who may wish to have the most accurate situational awareness. Nonetheless, it is difficult to reliably and accurately model the flow, transport, and dispersion processes in large complex built-up environments in a limited amount of time and resources compatible with operational needs. The parallel version of Micro-SWIFT-SPRAY (PMSS) is an attempt to propose a physically sound and fast response modelling system applicable to complicated industrial or urban sites in case of a hazardous release. This paper presents and justifies the choice of the diagnostic flow and Lagrangian dispersion models in PMSS. Then, it documents in detail the development of the parallel algorithms used to reduce the computational time of the models. Finally, the paper emphasizes the preliminary model validation and parallel performances of PMSS based on data from both wind tunnel (Evaluation of Model Uncertainty) and in-field reduced-scale (Mock Urban Setting Test) and real-scale (Oklahoma City) experimental campaigns.

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Authors and Affiliations

  1. MOKILI, 53 rue Dareau, 75014, Paris, France

    Olivier Oldrini

  2. CEA, DAM, DIF, 91297, Arpajon, France

    Patrick Armand & Christophe Duchenne

  3. ARIA Technologies, 92100, Boulogne-Billancourt, France

    Christophe Olry & Jacques Moussafir

  4. ARIANET, 20128, Milan, Italy

    Gianni Tinarelli

Authors
  1. Olivier Oldrini
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  2. Patrick Armand
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  3. Christophe Duchenne
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  4. Christophe Olry
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  5. Jacques Moussafir
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  6. Gianni Tinarelli
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Correspondence to Olivier Oldrini.

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Oldrini, O., Armand, P., Duchenne, C. et al. Description and preliminary validation of the PMSS fast response parallel atmospheric flow and dispersion solver in complex built-up areas. Environ Fluid Mech 17, 997–1014 (2017). https://doi.org/10.1007/s10652-017-9532-1

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  • DOI: https://doi.org/10.1007/s10652-017-9532-1

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