Effectiveness of RANS in predicting indoor airborne viral transmission: A critical evaluation against LES

K. Choudhary; K.A. Krishnaprasad; Sudhanshu Pandey; N. Zgheib; J.S. Salinas; M.Y. Ha; S. Balachandar

doi:10.1016/j.compfluid.2023.105845

Effectiveness of RANS in predicting indoor airborne viral transmission: A critical evaluation against LES

K. Choudhary, K.A. Krishnaprasad, Sudhanshu Pandey, N. Zgheib (Corresponding Author), J.S. Salinas, M.Y. Ha (Corresponding Author), S. Balachandar (Corresponding Author)

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4 Citations (Scopus)

Abstract

We investigate the dispersal of droplet nuclei inside a canonical room of size 10×10×3.2m ³ with a four-way cassette air-conditioning unit placed at the center of the ceiling. We use Reynolds averaged Navier–Stokes (RANS) simulations with three flow rates corresponding to air changes per hour (ACH) values of 2.5, 5, and 10. The room setup as well as the operating conditions are chosen to match those of a recent high-fidelity large eddy simulation (LES) study. We use statistical overloading with a total of one million droplet nuclei being initially distributed randomly with uniform probability within the room. Six nuclei sizes are considered ranging in radius from 0.1 to 10μm (166,667 nuclei per size). The simulations are one-way coupled and employ the Langevin equations to model sub-grid motion. The flow and particle statistics are compared against the reference LES simulations, and we find that the RANS k−ɛ realizable model may be used as a computationally cheaper alternative to LES for predicting pathogen concentration in confined spaces albeit, with potentially increased statistical discrepancy.

Original language	English
Article number	105845
Journal	Computers and Fluids
Volume	256
DOIs	https://doi.org/10.1016/j.compfluid.2023.105845
Publication status	Published - 30 Apr 2023
MoE publication type	A1 Journal article-refereed

Keywords

Correction to well-mixed model
Covid-19
Indoor air quality
Indoor airborne transmission
Large eddy simulation (LES)
RANS simulation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.compfluid.2023.105845

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title = "Effectiveness of RANS in predicting indoor airborne viral transmission: A critical evaluation against LES",

abstract = "We investigate the dispersal of droplet nuclei inside a canonical room of size 10×10×3.2m 3 with a four-way cassette air-conditioning unit placed at the center of the ceiling. We use Reynolds averaged Navier–Stokes (RANS) simulations with three flow rates corresponding to air changes per hour (ACH) values of 2.5, 5, and 10. The room setup as well as the operating conditions are chosen to match those of a recent high-fidelity large eddy simulation (LES) study. We use statistical overloading with a total of one million droplet nuclei being initially distributed randomly with uniform probability within the room. Six nuclei sizes are considered ranging in radius from 0.1 to 10μm (166,667 nuclei per size). The simulations are one-way coupled and employ the Langevin equations to model sub-grid motion. The flow and particle statistics are compared against the reference LES simulations, and we find that the RANS k−ɛ realizable model may be used as a computationally cheaper alternative to LES for predicting pathogen concentration in confined spaces albeit, with potentially increased statistical discrepancy.",

keywords = "Correction to well-mixed model, Covid-19, Indoor air quality, Indoor airborne transmission, Large eddy simulation (LES), RANS simulation",

author = "K. Choudhary and K.A. Krishnaprasad and Sudhanshu Pandey and N. Zgheib and J.S. Salinas and M.Y. Ha and S. Balachandar",

note = "Funding Information: We gratefully acknowledge support from NSF, USA (EAGER Grant no. 2134083 ), LG Electronics, Korea (Grant no. C2021017165 ) and University of Florida Informatics Institute, USA . Publisher Copyright: {\textcopyright} 2023 Elsevier Ltd",

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AU - Choudhary, K.

AU - Krishnaprasad, K.A.

AU - Pandey, Sudhanshu

AU - Zgheib, N.

AU - Salinas, J.S.

AU - Ha, M.Y.

AU - Balachandar, S.

N1 - Funding Information: We gratefully acknowledge support from NSF, USA (EAGER Grant no. 2134083 ), LG Electronics, Korea (Grant no. C2021017165 ) and University of Florida Informatics Institute, USA . Publisher Copyright: © 2023 Elsevier Ltd

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N2 - We investigate the dispersal of droplet nuclei inside a canonical room of size 10×10×3.2m 3 with a four-way cassette air-conditioning unit placed at the center of the ceiling. We use Reynolds averaged Navier–Stokes (RANS) simulations with three flow rates corresponding to air changes per hour (ACH) values of 2.5, 5, and 10. The room setup as well as the operating conditions are chosen to match those of a recent high-fidelity large eddy simulation (LES) study. We use statistical overloading with a total of one million droplet nuclei being initially distributed randomly with uniform probability within the room. Six nuclei sizes are considered ranging in radius from 0.1 to 10μm (166,667 nuclei per size). The simulations are one-way coupled and employ the Langevin equations to model sub-grid motion. The flow and particle statistics are compared against the reference LES simulations, and we find that the RANS k−ɛ realizable model may be used as a computationally cheaper alternative to LES for predicting pathogen concentration in confined spaces albeit, with potentially increased statistical discrepancy.

AB - We investigate the dispersal of droplet nuclei inside a canonical room of size 10×10×3.2m 3 with a four-way cassette air-conditioning unit placed at the center of the ceiling. We use Reynolds averaged Navier–Stokes (RANS) simulations with three flow rates corresponding to air changes per hour (ACH) values of 2.5, 5, and 10. The room setup as well as the operating conditions are chosen to match those of a recent high-fidelity large eddy simulation (LES) study. We use statistical overloading with a total of one million droplet nuclei being initially distributed randomly with uniform probability within the room. Six nuclei sizes are considered ranging in radius from 0.1 to 10μm (166,667 nuclei per size). The simulations are one-way coupled and employ the Langevin equations to model sub-grid motion. The flow and particle statistics are compared against the reference LES simulations, and we find that the RANS k−ɛ realizable model may be used as a computationally cheaper alternative to LES for predicting pathogen concentration in confined spaces albeit, with potentially increased statistical discrepancy.

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KW - Indoor air quality

KW - Indoor airborne transmission

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KW - RANS simulation

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Effectiveness of RANS in predicting indoor airborne viral transmission: A critical evaluation against LES

Abstract

Keywords

UN SDGs

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