(647f) Comparative Analysis of Drag Model Predictions for Fluidized Bed Applications

A stream of liquid or gas can be used to suspend granular materials into a fluidized state. Such fluidized beds of particles are commonplace in industrial operation because of their efficient mass, momentum and energy transfer, for example, fluidized beds are commonly used for catalyzing reactions, mixing, and heat transfer operations. Such industrial processes could benefit from the physical insights and predictions generated via models of fluid and solid-particle flows. The drag force is the momentum exchange between the fluid and solid particles that causes fluidization, and therefore correctly modeling the drag force is particularly important to accurate fluidized bed predictions. Currently, a gamut of drag models exist. Prior works have shown that the predicted fluidized bed behavior depends on the drag model selected. Additionally, while individual reports generally identify an accurate drag formulation for a specific experimental comparison, a single drag model demonstrating consistent accuracy across these previous studies does not exist. Hence, it is not clear which drag model is appropriate for a given application, a priori. Furthermore, a link between the drag model formulation and the macro-scale prediction of fluidized bed behavior is currently lacking. Here, simulations of fluidized bed behavior are presented for varied system conditions and drag model formulations. The aim of this work is to develop an understanding of expected variability in macro-scale predictions of fluidization due to permutations in the model inputs. The uncertainty in fluidized bed prediction resulting from changing the drag model formulation is quantified and explored across a wide parameter space is presented.