Computational fluid dynamics challenge on indoor dispersion of pathogen-laden aerosols

This paper presents and discusses the results of the “2024 International Computational Fluid Dynamics Challenge on the long-range indoor dispersion of pathogen-laden aerosols” aimed at assessing the ability of different computational codes and turbulence models to reproduce the dispersion of particles produced by a turbulent natural convection flow enclosed in a room sized cubical cavity. A total of 12 research groups from ten different countries have conducted 15 simulations of the same flow configuration by solving the Reynolds averaged Navier–Stokes (RANS) equations, the unsteady Reynolds averaged Navier–Stokes (URANS) equations or using scale adaptive simulations (SAS), large-eddy simulations (LES), or hybrid (URANS-LES) techniques. Results for the velocity field and the particle dispersion provided by the different simulations are compared extensively, including the reference results provided by a direct numerical simulation (DNS). In general, LES and hybrid methods reproduce the time-averaged flow field correctly, the spatial distribution of the turbulence kinetic energy, and the particle dispersion. The performance of SAS is similar to that of LES and hybrid methods while the predictions of the RANS and URANS simulations exhibit larger deviations with respect to DNS. In general, the particle dispersion is better reproduced by simulations that capture correctly the spatial distribution of the turbulence kinetic energy.

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Publication Details

Journal
Physics of Fluids
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0252665
Citations
8
Primary Topic
Infection Control and Ventilation
Type
article
Field-Weighted Citation Impact
12.15

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article

Computational fluid dynamics challenge on indoor dispersion of pathogen-laden aerosols

Gábor Janiga, David F. Fletcher, R. Castilla, Matjaž Hriberšek et al.
8 citations
Physics of Fluids
Infection Control and Ventilation
12.15
article

Computational fluid dynamics challenge on indoor dispersion of pathogen-laden aerosols

Gábor Janiga, David F. Fletcher, R. Castilla, Matjaž Hriberšek, Cristian Marchioli, Mercè García-Vílchez, Shriram Sankurantripati, Francisco José de Souza, Kiao Inthavong, Jure Ravnik, Paul Steinmann, Florent Duchaine, Natalie Jüngling, Douglas Fontes, N. P. C. Marques, Jordi Pallarès, Akim Lavrinenko, Pedro Javier Obando Vega, Bruño Fraga, Alexandre Fabregat, Jana Wedel, Salvatore Cito, Jennifer Niessner, Gabriele Mosca, Aleksandra Monka, Nejc Vovk, Manuel Martínez, Bruno Santos, Naomi Mestre-Curto, Leo Amari
article en
8 citations

Abstract

This paper presents and discusses the results of the “2024 International Computational Fluid Dynamics Challenge on the long-range indoor dispersion of pathogen-laden aerosols” aimed at assessing the ability of different computational codes and turbulence models to reproduce the dispersion of particles produced by a turbulent natural convection flow enclosed in a room sized cubical cavity. A total of 12 research groups from ten different countries have conducted 15 simulations of the same flow configuration by solving the Reynolds averaged Navier–Stokes (RANS) equations, the unsteady Reynolds averaged Navier–Stokes (URANS) equations or using scale adaptive simulations (SAS), large-eddy simulations (LES), or hybrid (URANS-LES) techniques. Results for the velocity field and the particle dispersion provided by the different simulations are compared extensively, including the reference results provided by a direct numerical simulation (DNS). In general, LES and hybrid methods reproduce the time-averaged flow field correctly, the spatial distribution of the turbulence kinetic energy, and the particle dispersion. The performance of SAS is similar to that of LES and hybrid methods while the predictions of the RANS and URANS simulations exhibit larger deviations with respect to DNS. In general, the particle dispersion is better reproduced by simulations that capture correctly the spatial distribution of the turbulence kinetic energy.

Physics of FluidsVol. 37(2)
University of Udine (IT), The University of Sydney (AU), Friedrich-Alexander-Universität Erlangen-Nürnberg (DE), University of Maribor (SI), Heilbronn University (DE), 6WIND (France) (FR), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (FR), Universitat Rovira i Virgili (ES), University of Birmingham (GB), Universidade Federal de Uberlândia (BR), RMIT University (AU), Westmont College (US), Otto-von-Guericke-Universität Magdeburg (DE), Universitat Politècnica de Catalunya (ES)
National Computational Infrastructure, Australian Government, Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Grand Équipement National De Calcul Intensif, National Cancer Institute
Openalex Percentile: Top 1%
Infection Control and Ventilation
12.15
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