Improving the Performance of a Spouted Bed via Uniformity Index Using Stochastic Optimization

Abstract

This work focuses on maximizing the solid's uniformity structure (UI) that could enhance the performance of the spouted bed. Furthermore, UI is affected by operating conditions, which are considered as decision variables of the optimization process. The selected decision variables are; gas velocity, solid's density and solid's diameter. Steady-state measurements were carried out in the 60^° conical shape spout-air bed. Concentration of particles (glass and steel beads) at various elevations of the bed under different flow patterns were measured using sophisticated optical probes. Optimization technique is a powerful tool for selecting the best operating conditions could overcome the instability of the system and improves the uniformity of the particles across the bed. The stochastic global genetic algorithm has found the suitable search for the non-linear hybrid spouted bed. The optimal results indicate that maximum UI is 0.534 could be obtained with; gas velocity of 0.741 m/s, solid's diameter of 1.09 mm and solid's density of 6648.0 Kg/m³. Velocity of gas and diameter of solid particles were observed the sensitive variables with the uniformity index changing.

Keywords: Genetic algorithm, Optimization, Spouted bed, Uniformity index.