Artificial Neural Network Approach to Segregation Characteristic of Binary Heterogeneous Mixtures in Promoted Gas Solid Fluidized Beds

Abstract

Binary mixtures of particles of same size but of different densities are fluidized in a 15cm diameter column with a perforated plate distributor with two co-axial promoters. In the present work an attempt has been made to study the fluidization and the segregation characteristic of solids of same size but density-variant in terms of segregation distance. The dimensionless segregation distance has been correlated with other dimensionless groups relating the various system parameters viz. ratio of the density of jetsam particles to that of flotsam, initial static bed height, height of layer of particles above the bottom grid, superficial gas velocity and average density of the mixture on the basis of dimensional analysis approach for both un-promoted and promoted beds. Correlations have also been developed with the above system parameters by using Artificial Neural Network approach for different types of fluidized beds and thus the findings with respect to both the approaches have been compared with each other. The segregation distance values for promoted beds have also been compared here with that of un-promoted bed in this work.