PIV and statistical analysis of a swirling bed process carried out using a hybrid model of axial blade distributor

Abstract

An air distributor is a major component of industrial fluidized beds and its design significantly affects the quality of fluidization. In this study, a hybrid design of an annular distributor was tested for swirling fluidized beds (SFBs). Using this distributor design, a bed was operated in its uniform swirling regime of operation. A high-speed imaging method was used to capture images of the fluidized bed of particles. These images were processed using a binary cross-correlation technique and analyzed through particle image velocimetry (PIV) software. The velocity vector fields and corresponding velocity magnitudes at different locations in the bed were obtained for different bed weights, blade inclination angles, and superficial air velocities (SAVs). The Response Surface Analysis program was used to predict the bed velocity statistically. The statistical confidence interval for the bed velocity ranged from 0.49485 to 0.49998. The statistical fit and experimental values of the bed velocities were 0.49741 and 0.538 m/s, respectively. Almost identical bed weights and superficial velocities were inferred through experimental and statistical analyses; however, a small difference of 6.4° was noticed in the blade inclination angles.