Recent Development in Hydrodynamic and Heat Transfer Characteristics in the Three-phase Fluidized-bed System

Abstract

The effect of several characteristics on hydrodynamic performance and heat transfer phenomena has been studied extensively.  A review of most of the previous correlations for various parameters in gas-liquid-solid fluidization systems was investigated. CFD could be used to understand the complicated hydrodynamics of fluidization Gas-liquid-solid fluidized beds are broadly utilized in the petrochemical, pharmaceutical, refining, food, biotechnology, and environmental industries. Due to complex phenomena, such as the particle-particle, liquid-particle, particlebubble interactions, complex hydrodynamics, and heat transfer of three-phase (gas-liquid-solid) fluidized beds, they are incompletely understood. The ability to accurately predict the essential characteristics of the fluidized-bed system, such as hydrodynamics, individual phase mixing, and heat transfer parameters, is necessary for its successful design and operation. This paper investigates the pressure drop, minimum fluidization velocity, phase holdup, heat-transfer coefficient of a fluidized bed reactor, heat transfer studies, CFD simulation, and the effect of these parameters on the extent of fluidization. Many variables (fluid flow rate, particle density and size, fluid inlet, and bed height) affect the fluidizing quality and performance of the fluidization process. The hydrodynamics parameters, mixing of phases, and the behavior of heat transfer with various modes of fluidization were investigated to predict hydrodynamics parameters. Several publications have demonstrated the utility of (CFD) in explaining the hydrodynamics, heat, and mass transfer of fluidized beds. Principles of measurement, details of the experimental configurations, and the applied techniques by various researchers are also presented. Feng's model was statistically validated using experimental data that was both time-averaged and time-dependent. Furthermore, this model successfully predicted the instantaneous flow structures, which should provide strategies for the best design, scale-up, and operation in fluidized bed columns. The divergence between the simulated and observed values can be reduced by better understanding the fluidized bed's nature.