American Association for Aerosol Research - Abstract Submission

AAAR 38th Annual Conference
October 5 - October 9, 2020

Virtual Conference

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The Significant of Turbulence Stochastic Accuracy in Simulation of Aerosol Transmission

AMIR A. MOFAKHAM, Goodarz Ahmadi, Clarkson University

     Abstract Number: 464
     Working Group: The Role of Aerosol Science in the Understanding of the Spread and Control of COVID-19 and Other Infectious Diseases

Abstract
As a result of the ongoing COVID-19 pandemic, attention has been given to numerical simulation of aerosol transport and dispersion to assess the risk of human-to-human airborne virus transmission. The respiratory droplets emitted by an infected person via coughing, sneezing, talking, and breathing interact with ventilation airflows that are typically in the state of turbulent motion. To model particle-laden turbulent airflows, commonly a RANS turbulence model is used which requires using a turbulence stochastic model to include the turbulence dispersion effects on micro and nano-droplets. However, the default turbulence stochastic model of commercial CFD software is usually unable to correctly predict the turbulence fluctuating velocity field. A series of simulation results were presented where the results of the default turbulence stochastic model of commercial CFD software are compared with the improved Continuous Random Walk (CRW) and Discrete Random Walk (DRW) stochastic model. It was shown that the new improved CRW and DRW models correctly predict the aerosol dispersion and deposition in various passages, while the default model could lead to several orders of magnitude errors for certain size ranges. Therefore, the new model could be used to provide technical guidance on respiratory virus transmission such as SARS-CoV-2.