화학공학소재연구정보센터
Chemical Engineering and Processing, Vol.39, No.2, 129-139, 2000
Performance of wire mesh mist eliminator
An experimental study was made to measure the performance of wire mesh mist eliminator as a function of broad ranges of operating and design conditions. The experiments were carried out in an industrial scale layered type demister pad made of 316 L stainless steel wires. The demister performance was evaluated by droplet separation efficiency, vapor pressure drop of wet demister, and flooding and loading velocities. These variables were measured as a function of vapor velocity (0.98-7.5 m/s), packing density (80.317-208.16 kg/m(3)), pad thickness (100-200 cm), wire diameter (0.2-0.32 mm), and diameter of captured droplets (1-5 mm). All the measurement results lie in ranges where, in practice, the wire mesh mist eliminator predominates. The experimental results indicate that the separation efficiency increases with both the maximum diameter of capture water droplets and the vapor velocity and with the decrease of wire diameter. The pressure drop for the dry demister is relatively low and depends only on the vapor velocity. The pressure drop increases linearly up to the loading point, thereafter; the rate of increase is larger. Beyond the flooding point, the increase rate is significant even for the slightest rise in the vapor velocity. The flooding velocity diminishes with the beef-up of the packing density and with the decrease of the wire diameter. Three empirical correlations were developed as a function of the design and operating parameters for the separation efficiency, pressure drop for the wet demister in the loading range, and the flooding and loading velocities. These correlations are sufficiently accurate for practical calculations and demister design. The temperature depression corresponding to the pressure drop in a wire mesh mist eliminator systems installed in a typical multi stage flash desalination plant was estimated from the developed correlation. A good agreement was obtained between the design values and the correlation predictions.