Optimization of air supply parameters for stratum ventilation based on proper orthogonal decomposition.

Abstract

Under the current COVID-19 epidemic conditions, stratum ventilation can provide treated fresh air directly into the human breathing zone, improving the air quality for inhalation. However, in the design of air supply parameters for stratum ventilation, the traditional trial-and-error and experimental methods are inefficient and time consuming, and they cannot be used to identify the optimal air supply parameters from a large number of parameters. Therefore, in this paper, the inverse design method based on proper orthogonal decomposition (POD) was applied to the design of ventilation parameters for a room with stratum ventilation. Predicted mean vote (PMV), predicted percentage dissatisfied (PPD) and droplet nuclei concentration in the human breathing zone were selected as design objectives to optimize air supply parameters. The transmission of COVID-19 was controlled by reducing the concentration of droplet nuclei in the respiratory area. The results show that, compared with the trial-and-error method, the inverse design method based on POD is more than 90% faster. POD method can greatly expand the sample size. Considering the dispersion of exhaled droplet nuclei in the room, the appropriate stratum ventilation parameters can reduce the concentration of fine droplet nuclei by more than 20% compared with the traditional design parameters.