Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces

Hoque, Shamia; Omar, Firoza B.

doi:10.3390/ijerph16050800

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Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces

Shamia Hoque

^* and

Firoza B. Omar

Department of Civil and Environmental Engineering, University of South Carolina, 300 Main Street, Columbia, SC 29208, USA

Author to whom correspondence should be addressed.

Int. J. Environ. Res. Public Health 2019, 16(5), 800; https://doi.org/10.3390/ijerph16050800

Received: 16 January 2019 / Revised: 24 February 2019 / Accepted: 28 February 2019 / Published: 5 March 2019

(This article belongs to the Section Environmental Science and Engineering)

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Abstract

Cross-contamination between occupants in an indoor space may occur due to transfer of infectious aerosols. Computational fluid dynamics (CFD) provides detailed insight into particle transport in indoor spaces. However, such simulations are site-specific. This study couples CFD with statistical moments and establishes a framework that transitions site-specific results to generating guidelines for designing “healthy” indoor spaces. Eighteen cases were simulated, and three parameters were assessed: inlet/outlet location, air changes per hour, and the presence/absence of desks. Aerosol release due to a simulated “sneeze” in a two-dimensional ventilated space was applied as a test case. Mean, standard deviation, and skewness of the velocity profiles and particle locations gave an overall picture of the spread and movement of the air flow in the domain. A parameter or configuration did not dominate the values, confirming the significance of considering the combined influence of multiple parameters for determining localized air-flow characteristics. Particle clustering occurred more when the inlet was positioned above the outlet. The particle dispersion pattern could be classified into two time zones: “near time”, <60 s, and “far time”, >120 s. Based on dosage, the 18 cases were classified into three groups ranging from worst case scenario to best case scenario. View Full-Text

Keywords: respiration; dead zones; dispersion; dosage; breathing zone; office

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

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Hoque, S.; Omar, F.B. Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces. Int. J. Environ. Res. Public Health 2019, 16, 800. https://doi.org/10.3390/ijerph16050800

AMA Style

Hoque S, Omar FB. Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces. International Journal of Environmental Research and Public Health. 2019; 16(5):800. https://doi.org/10.3390/ijerph16050800

Chicago/Turabian Style

Hoque, Shamia, and Firoza B. Omar. 2019. "Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces" International Journal of Environmental Research and Public Health 16, no. 5: 800. https://doi.org/10.3390/ijerph16050800

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Coupling Computational Fluid Dynamics Simulations and Statistical Moments for Designing Healthy Indoor Spaces

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