Predicting binary-solid fluidized bed behavior using averaging approaches

The present study reports new experimental data on the expansion as well as the layer-inversion behavior of liquid-fluidized beds containing two particle species with almost 10-fold difference in the size and a significant difference in the density. The packing models, which are generally used for predicting the porosity of the packing of particle mixtures, are used here to describe the expansion and the phenomenon of the layer-inversion. Predictions of different averaging models, including the property-averaging model, the serial model, and various packing models, are compared with the present data as well as the layer-inversion data reported in the literature. The overall predictive capability of packing models is found to be superior.