Abstract

The study of aerosol dispersion in indoor environments is essential to understanding and mitigating airborne virus transmission, such as SARS-CoV-2. Computational Fluid Dynamics (CFD) has emerged as a valuable tool for investigating aerosol dispersion, providing an alternative to costly experimental methods. In this study, we investigated the performance of four (4) Reynolds-averaged Navier-Stokes (RANS) turbulence models in predicting aerosol dispersion from a human body coughing in a small, ventilated indoor environment. We compared the Standard, RNG, Realizable k-ϵ models and the SST k- ω model using the same boundary conditions. We initially observed that the horizontal distance of the coughed aerosols after 10.2s dispersion time was substantially shorter with the standard k-ϵ turbulence compared to the other three turbulence models compared to the SST k-ω model, the RNG, and realizable k-ϵ models exhibit a high degree of similarity in their dispersion patterns. Specifically, we observed that the aerosols dispersed horizontally faster with the RNG and Realizable k-ϵ models. In conclusion, when compared to qualitative data from the literature, our observations exclude the standard k-ϵ turbulence. However, to select the most appropriate turbulence model for capturing the cough flow and aerosol dispersion dynamics, further detailed validation against both quantitative and qualitative data is needed.

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