FUNDAMENTAL INVESTIGATION ON VENTILATION METHODS OF INDOOR AIR FOR PREVENTING INFECTIONS BY COMPUTATIONAL FLUID DYNAMICS ANALYSIS

Droplets including virus such as COVID-19 are easily influenced by the indoor airflow and spreading around everywhere. In general, areas with higher residence time of airflow in the room are more likely to have droplets. Therefore, it is important for predicting the infection risk to use the residence time. In this study, office models with ventilation devices are used and volume-averaged residence time is evaluated as indoor air quality. After making typical office models for the ventilation, indoor air flow motions were predicted by Computational Fluid Dynamics (CFD). By setting the proper boundary conditions for ventilation, effects of ventilation methods for ventilation devices were obtained. It was found that 1) by controlling the operation of devices, ventilation ability can be evaluated by calculating volume-averaged residence time, 2) the value of volume-averaged residence time depends on the degree of angles of device inlets, and 3) volume-averaged residence time for most areas can be decreased by opening a door.