10th International Aerosol Conference September 2 - September 7, 2018 America's Center Convention Complex St. Louis, Missouri, USA
Abstract View
Numerical Simulation of a Parallel-plate Separator for PM2.5
TAKUTO YONEMICHI, Koji Fukagata, Kentaro Fujioka, Tomoaki Okuda, Keio University
Abstract Number: 153 Working Group: Instrumentation
Abstract Particulate matter suspended in air such as PM2.5 has adverse effects on human health by depositing on respiratory tracts. Measurement of charging states of PM2.5 and charge distribution of ambient aerosol have been carried out because charged particles deposit on the respiratory tracts more than non-charged particles. Okuda et al. (2015) developed a parallel plate particle separator (PPPS) in order to classify PM2.5 for measurement of charging state of individual particles. The PPPS consists of three sections: the inlet section, classification section, and exit section. The inlet section consists of three conduits. Particles are introduced from the central conduit, whereas clean air is supplied from the other two. When the particles flow in the classification section, they are moved toward the electrodes by the Coulomb force. Finally, they are classified by their charging states at the exit section consisting of three conduits similar to the inlet section. However, this device has uncertainty in classification performance: some particles flow out to unexpected exits. Therefore, improvement of this performance is needed for a more accurate measurement.
In the present study, dispersion of submicron particles in the PPPS is numerically analyzed by means of the Lagrangian particle tracking method including a model of the Brownian diffusion in order to reveal the mechanisms of the classification uncertainty. Further, a parametric study is made in order to find the optimal condition which decreases the classification uncertainty.
The results show that 7.5% of total particles flow out to the unexpected exits due to the Brownian diffusion. Decreasing flow rate of the central inlet for aerosol and increasing flow rate of the other inlets for clean air dramatically improves the classification performance. The outflow of particles to the unexpected exits becomes 0.0% when the flow rate of the aerosol is less than 84% compared to that in the base case. This improvement is in good agreement with experimental observation. In addition, it is found that similar improvement can be attained by narrowing the central inlet.
Reference Okuda, T., Gunji, Y. and Lenggoro, I. W., “Measurement of the electrostatic charging state of individual particles in ambient aerosol using Kelvin probe force microscopy”, Earozoru Kenkyu30, 190-197 (2015). (in Japanese)