(368e) Modeling Segregation in Granular Flows with Overlapping Particle Size Distributions

Unwanted demixing is a widespread problem in bulk solids processing. In the past, a combination of trial and error, small scale experiments, and continuum models have been used to estimate and negate the effects of bulk material segregation. Recent advances in continuum modeling of segregation in size multidisperse and polydisperse systems have only been applied to systems whose species particle size distributions (PSDs) are non-overlapping, whereas mixtures in industrial bulk solids processing are composed of constituent species of broad and overlapping size distributions. We study changes in segregation behavior as a result of overlap between species PSDs by using a series of discrete element method (DEM) simulations of a bounded heap with two species with overlapping log-normal size distributions. Surprisingly, a continuum based model that treats the mixtures as consisting of just two different particle sizes corresponding to the means of the log-normal distributions is able to quantitatively reproduce the degree of mixing from the DEM simulations for overlapping PSDs. We test this simple bidisperse model in cases of broad, overlapping, and varied size distributions to determine when it fails, and we resolve any discrepancies between it and the overlapping continuous distributions using a minimum set of independent model parameters. Funded by Procter & Gamble.