A method, employing optical image analysis, has been developed to predict the net apparent density and the distribution of particle density as a function of size for a polysize powder which contains a significant proportion of cavernous particles. For a given batch of material, provided that the probability and size of cavitation can be described as a size-dependent function, the model closely predicts the powder properties for any size distribution expressed in terms of the Rosin-Rammler function generated from sizing data that has been obtained using either optical (laser) or gravimetric (sieving) techniques. The method has been applied to atomised ferrosilicon powder, which is widely used in dense medium separation (DMS) processes, to yield data of technological importance to DMS, by quantifying the distribution of particle density, in addition to the net apparent powder density.
ASJC Scopus subject areas
- Chemical Engineering(all)