Experimental gas-fluidized bed drying study on the segregation and mixing dynamics for binary and ternary solids

Abstract

Fluidized bed drying is an evolving process: The bed hydrodynamics, including the segregation and mixing tendencies, and its interplay with mass and heat transfer change in time. In this study, pseudo-2D fluidized bed experiments are performed using binary (50/50%) and ternary (33.3/33.3/33.3%) solids mixtures. A coupled particle image velocimetry infrared thermography technique provides local solids velocity and temperature fields. Furthermore, a machine learning algorithm is applied to characterize the bed segregation and mixing dynamics. Significant hydrodynamic changes and various segregation and mixing tendencies due to the evaporation of water from the porous γ-Al2O3 material were observed. A competition between size and density-based segregation and mixing dynamics resulted in changing bed configurations, which are correlated to the local solids drying behavior. Besides, it showed that drying of wider size distributions could lead to more complex efficient process operation.