Abstract:
The sudden outbreak of coronavirus (COVID-19) has infected over 100 million people and led to over two million deaths (data in January 2021), posing a significant threat to global human health. As a potential carrier of the novel coronavirus, the exhaled airflow of infected individuals through coughs is significant in virus transmission. The research of detailed airflow characteristics and velocity distributions is insufficient because most previous studies utilize particle image velocimetry (PIV) with low frequency. This study measured the airflow velocity of human coughs in a chamber using PIV with high frequency (interval: 1/2986 s) to provide a detailed validation database for droplet propagation CFD simulation. Sixty cough cases for ten young healthy nonsmoking volunteers (five males and five females) were analyzed. Ensemble-average operations were conducted to eliminate individual variations. Vertical and horizontal velocity distributions were measured around the mouth area. Overall cough characteristics such as cough duration time (CDT), peak velocity time (PVT), maximum velocities, and cough spread angle were obtained. The CDT of the cough airflow was 520–560 m s, while PVT was 20 m s. The male/female averaged maximum velocities were 15.2/13.1 m/s. The average vertical/horizontal cough spread angle was 15.3°/13.3° for males and 15.6°/14.2° for females. In addition, the spatial and temporal distributions of ensemble-averaged velocity profiles were obtained in the vertical and horizontal directions. The experimental data can provide a detailed validation database the basis for further study on the influence of cough airflow on virus transmission using computational fluid dynamic simulations.
