Abstract

Vibro-fluidized beds can improve the solids drying characteristics by enhancing the gas-solid contacting. In this study, experiments in a pseudo-2D vibro-fluidized bed setup are performed in order to better understand this improved drying behavior of binary solids mixtures. A coupled particle image velocimetry-infrared thermography technique is applied. Furthermore, a machine learning algorithm is used to characterize the bed segregation and mixing dynamics under the influence of mechanical vibration. Significant changes in bed hydrodynamics and various impacts on segregation and mixing characteristics were observed for vibrational oscillations corresponding to low values of acceleration compared to gravitational acceleration. Larger vibration accelerations result in significantly increased solids mixing compared to a static gas-fluidized bed due to enhanced meso-scale particle agitation.