PIV Visualization of a Sinusoidal EHD Confinement Flow Induced by Variation in Ion Density for Electrostatic Particle Clustering

MD EYASIN HOSSAIN, Eric Monsu Lee, Northern Illinois University

     Abstract Number: 51
     Working Group: Control and Mitigation Technology

Abstract
Fine particulate matter, commonly known as PM2.5, is accountable for around four million deaths worldwide due to cardiovascular diseases. Fabric filters have been utilized for particle pollution control in industrial and indoor settings. However, the maintenance cost of fabric filters is high as particle accumulation on filters can lead to higher pressure drop and energy consumption as well as the growth of biological organisms and the generation of airborne pathogens. Electrostatic precipitators (ESPs) are an alternative approach widely used in the power industry, mainly for collecting coal fly ash. ESPs can achieve more than 99% of particle collection efficiency but also suffer from low collection efficiency of PM2.5 and ozone generation. Therefore, ongoing research is toward developing modern ESPs to control PM2.5 with minimal ozone emission. The optimization of discharge and collection electrodes substantially impacts the ion distribution and thus the collection of particles in an ESP. Earlier works mostly centered on modifying the geometry of collection electrodes with less focus on discharge electrodes. This study centers on the collective behavior of unipolar charged particles in a longitudinal wire-plate ESP by inducing variation in ion density through discharge electrode modification. It is hypothesized that the modified discharge electrode could create a sinusoidal flow, promoting electrostatic particle clustering and ultimately enhancing the particle collection efficiency of PM2.5. A 2D-2C Particle Image Velocimetry (PIV) enabled by a double pulse laser (532 nm) with a sCMOS camera will be utilized for observing the collective behavior of charged DEHS oil particles. MatLab and PIVview will analyze images collected in terms of averaged velocity field and vorticity. The anticipated outcomes encompass a better understanding of the EHD flow dynamics through discharge electrode optimization to improve PM2.5 capture by electrostatic particle clustering.