A continuum approach for predicting segregation in flowing polydisperse granular materials

Conor P. Schlick, Austin B. Isner, Ben J. Freireich, Yi Fan, Paul B. Umbanhowar, Julio M. Ottino, Richard M. Lueptow

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Segregation of polydisperse granular materials occurs in many natural and industrial settings, but general theoretical modelling approaches with predictive power have been lacking. Here we describe a model capable of accurately predicting segregation for both discrete and continuous particle size distributions based on a generalized expression for the percolation velocity. The predictions of the model depend on the kinematics of the flow and other physical parameters such as the diffusion coefficient and the percolation length scale, quantities that can be determined directly from experiment, simulation or theory and that are not arbitrarily adjustable. The model is applied to heap and chute flow, and the resulting predictions are consistent with experimentally validated discrete element method (DEM) simulations. Several different continuous particle size distributions are considered to demonstrate the broad applicability of the approach.

Original languageEnglish
Pages (from-to)95-109
Number of pages15
JournalJournal of Fluid Mechanics
Volume797
DOIs
StatePublished - Jun 25 2016
Externally publishedYes

Funding

This research was funded by NSF grant CMMI-1000469 and The Dow Chemical Company. We thank K. Jacob for helpful discussions concerning polydisperse granular flows in industrial settings.

Keywords

  • complex fluids
  • granular media
  • mixing

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