Numerical evaluation of respiratory droplet removal by an ionic wind-driven electrostatic device in an indoor environment

Abstract

A novel method by utilizing self-pumped electrostatic droplet collectors is proposed to remove respiratory droplets in a room. The ionic wind flow pattern and droplet migration and removal process in a room were numerically predicted by the Eulerian-Lagrangian method. The coupling between the corona discharge, air flow and droplet migration processes was realized in the numerical model. Results demonstrate that a circulation flow pattern across the whole room is generated with a velocity magnitude of 1 m s−1. The droplet removal time is mainly governed by the migration of droplets from a specific position to the inlet of the electrostatic droplet collector. The turbulent dispersion of droplets greatly enhances the droplet migration and reduces the droplet removal time by 70 % for droplets with an initial diameter of 20 μm. More than 99 % droplets suspended in the room with a characteristic size of 5 m can be removed in 200 s with a power consumption of about 150 W. Compared with the droplet free deposition, the electrostatic droplet collection method reduces the droplet removal time by more than 90 %.