STUDY OF SPREAD OF AEROSOLS DURING DIFFERENT BREATHING CYCLES USING COMPUTATIONAL FLUID DYNAMICS

With COVID-19 having spread so rapidly across the world, detailed physics of transmission of com- municable diseases must be understood to recommend effective preventive measures. Computational fluid dynamics can provide insights into the physics of transport of droplets. Droplets are not only emitted during sneezing and coughing, but also during normal activities such as breathing, speak- ing, and singing. In this paper, different breathing patterns and their effect on the spread of droplets of 1 micron size are studied. It has been found that long steady exhalations, as well as sinusoidal exhalations can cause the droplets to travel greater distances. Also, some observations of the effects of the inhalation cycle and its small region of influence are included in this work. © 2021 by Begell House, Inc.

An investigation for airflow and deposition of PM2.5 contaminated with SAR-CoV-2 virus in healthy and diseased human airway.

This study is motivated by the amplified transmission rates of the SAR-CoV-2 virus in areas with high concentrations of fine particulates (PM2.5) as reported in northern Italy and Mexico. To develop a deeper understanding of the contribution of PM2.5 in the propagation of the SAR-CoV-2 virus in the population, the deposition patterns and efficiencies (DEs) of PM2.5 laced with the virus in healthy and asthmatic airways are studied. Physiologically correct 3-D models for generations 10-12 of the human airways are applied to carry out a numerical analysis of two-phase flow for full breathing cycles. Two concentrations of PM2.5 are applied for the simulation, i.e., 30 µg⋅m-3 and 80 µg⋅m-3 for three breathing statuses, i.e., rest, light exercise, and moderate activity. All the PM2.5 injected into the control volume is assumed to be 100% contaminated with the SAR-CoV-2 virus. Skewed air-flow phenomena at the bifurcations are proportional to the Reynolds number at the inlet, and their intensity in the asthmatic airway exceeded that of the healthy one. Upon exhalation, two peak air-flow vectors from daughter branches combine to form one big vector in the parent generation. Asthmatic airway models has higher deposition efficiencies (DEs) for contaminated PM2.5 as compared to the healthy one. Higher DEs arise in the asthmatic airway model due to complex secondary flows which increase the impaction of contaminated PM2.5 on airways' walls.