Using mesoscale drag model-augmented coarse-grid simulation to design fluidized bed reactor: Effect of bed internals and sizes

• Applicability of different mesoscale drags for predicting hydrodynamics over all flow regimes. • Applying the optimal drag model to design bed internals and quantify bed size effects. • The proposed nature-inspired snowflake-type internal significantly improves fluidization quality. • Proposing a preliminary correlation to quantify the bed size-dependent effect. This work systematically investigates the applicability of our recently developed three mesoscale drag models for predictions of hydrodynamics over extensive flow regimes ranging from bubbling, turbulent, rapid to full-loop fluidization. Subsequently, we try to apply the suitable mesoscale model for designing bed internals and quantifying bed size effects in a dense turbulent fluidized bed reactor. It is found that the optimized nature-inspired snowflake-type internal scheme contributes to breaking up the bubbles effectively and thereby weakening the degree of the particle clustering near the wall significantly. This phenomenon can enhance the uniform solid hold-up distribution (A ∼25% reduction of its nonuniformity) and improve the fluidization quality. Moreover, the bed size evidently affects the gas–solid fluidization characteristics and we thereby propose a preliminary correlation to quantify this size-dependent effect. This work may contribute to facilitating the CFD design practice of multiphase reactors from an art to science.