Multi-objective Optimization of a Spouted Bed

Abstract

Performance of the gas-solid spouted bed benefits from solid's uniformity structure (UI) with lower pressure drop (PD). Spouted bed system needs to be optimized to achieve the maximum performance.Therefore; the focus of this work is to maximize the UI and to minimize the PD along the bed. Three selected decision variables are affecting these objectives that are; gas' velocity, particle's density and particle's diameter. Steady-state measurements were carried out to study the effect of the decision variables on UI and PD in the 60^° conical shape spout-air bed with the diameter of 3 inches and height of 36 inches. Radial concentration of particles (glass and steel beads) at various elevations of the bed under different flow patterns were measured using sophisticated optical probes. High- accuracy pressure transducer monitored the pressure drop across the bed. Solid's density has found the effective variable on both UI and PD.  Multi-objective   genetic algorithm (GA) has found the best stochastic technique for highly nonlinear hybrid spouted system. The reliability of optimization search can be enhanced by adaptation of the GA's operators. Optimum results have 14 sets of new operating conditions would improve the efficiency of the bed. Maximum UI obtained with high-density steel beads, and minimum PD could obtain with low-density glass beads at low gas' velocity. It was observed that the gas' velocity was the sensitive variable for UI and PD changing.

Keywords: Genetic algorithm; Optimization; Pressure drop; Spouted bed; Uniformity index.