A Computational Model to Predict Pressure Drop and Droplet Removal Efficiency of Chevron Mist Eliminator

Abstract

Abstract Chevron mist eliminators are widely used in industry to remove liquid droplets from gas streams. A major application of these devices is in the flue gas desulfurization (FGD) of coal burning power plants. Before the exhaust gas is released to the atmosphere, liquid droplets entrained in the gas must be removed. A chevron mist eliminator relies on droplet inertia to cause the droplets to impinge on a surface where they are collected and drained away. The droplet removal efficiency is the critical design parameter of the mist eliminator. Pressure drop and flow capacity is also of major importance. The droplet removal efficiency, pressure drop, and flow capacity have been investigated experimentally by several investigators. The experimental results were obtained using an air-water system of gas and fluid droplets. This paper presents the results of a study using computational fluid dynamics to model the two-phase flow through the mist eliminator. Droplet removal efficiency and pressure drop were determined and compared with the experimental results. Three-stage chevron mist eliminator with 45° angle to flow was modeled. Comparison of the model results with previous experimental results indicated that the model is reasonably accurate. The model predicts pressure drop and the diameter at which 95% of droplets are removed with reasonably good accuracy. However, calculated droplet removal efficiencies of droplets with diameters less than 20μm did not agree well with experiments. The main advantage of the proposed model is that it can be used to predict droplet removal efficiencies for gas streams whose properties differ appreciably from that of an air-water system. Actual gas streams properties are input to the computational model. Therefore, the present model provides an effective and useful design tool.