Numerical analysis of airflow dynamics generated by human coughing based on PIV experimental results

Respiratory infections are transmitted by droplets and droplet nuclei generated by human coughing, sneezing, and talking. Droplets and droplet nuclei come out of the mouth simultaneously with airflow, and their dispersion characteristics are important to understand the transmission route of infection. It is crucial to understand the dispersion characteristics of droplets and droplet nuclei dispersion and infection routes through numerical analysis. The present study aims to provide boundary conditions of the computational fluid dynamics (CFD) model to confirm the prediction accuracy of CFD analysis of human coughing based on the experimental results of particle image velocimetry (PIV). The projection area of the mouth, which is the boundary condition of airflow generated by human coughing, was assumed as an ellipse shape, major axis length was 43.2 mm (1.7 in), and the ratio of the major and minor axis was 4. Because the air velocity corresponding to the boundary condition of the mouth in the CFD model cannot be derived directly from the PIV results, the time-series airflow distribution was analyzed by introducing a correction factor, and the boundary condition with the smallest error with the experimental result was inversely derived. As a result, the airflow generated by coughing with CFD analysis could be reproduced with an RMSE of 0.38–0.42 m/s (1.25–1.38 ft/s) compared to the ensemble average obtained in the experiment. This study provides detailed modeling techniques and boundary conditions of numerical simulation for analyzing the airflow characteristics generated by human coughing. In addition, it is expected that the risk and route of infection caused by human coughing can be predicted through CFD analysis by additionally measuring the size distribution of droplets and droplet nuclei and introducing Lagrangian analysis.