(368c) Flow Modulation Driven Stratification of Size Bidisperse Granular Mixtures in Quasi-2D Heaps

Authors: 
Deng, Z., Northwestern University
Xiao, H., Northwestern University
Fan, Y., The Dow Chemical Company
McDonald, D., Carnegie Mellon University
Ottino, J. M., Northwestern University
Lueptow, R. M., Northwestern University
Umbanhowar, P. B., Northwestern University
Modelling transient size segregation in granular flow has important applications in various industrial processes such as hopper and silo filling. In this research, we demonstrate, using experiments, discrete element method simulations (DEM), and a continuum model, how temporal modulation of the fill rate can generate ordered stratification in a quasi-2D bounded heap and investigate how the modulation parameters determine the wavelength and streamwise extent of the stratification layers. By temporally modulating the fill rate between fast and slow phases for a size-bidisperse particle mixture, stratified layers of large- and small-particle-rich bands form parallel to the free surface of the heap. The relative influence of the various mechanisms driving the stratification are not yet well understood. To gain physical insight into modulation driven stratification, we develop a simplified transient continuum model for granular size bidisperse modulated flow segregation. The model depends on three kinematic dimensionless obtained from experiments or DEM simulations: the Peclet number, which captures the interplay of advection and diffusion, a second dimensionless parameter that describes the interplay between segregation and advection, and a time scale that represents the ratio of the flow modulation time to the characteristic residence time of the particle in the flowing layer. The model captures the leading order characteristics of the stratification patterns and agrees well with DEM simulations and experiments under similar operating conditions. Funded by The Dow Chemical Company and NSF Grant CBET-1511450.
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