Segregation in dense sheared flows: Gravity, temperature gradients, and stress partitioning

K. M. Hill, Danielle S. Tan

Research output: Contribution to journalArticlepeer-review

83 Scopus citations

Abstract

It is well-known that in a dense, gravity-driven flow, large particles typically rise to the top relative to smaller equal-density particles. In dense flows, this has historically been attributed to gravity alone. However, recently kinetic stress gradients have been shown to segregate large particles to regions with higher granular temperature, in contrast to sparse energetic granular mixtures where the large particles segregate to regions with lower granular temperature. We present a segregation theory for dense gravity-driven granular flows that explicitly accounts for the effects of both gravity and kinetic stress gradients involving a separate partitioning of contact and kinetic stresses among the mixture constituents. We use discrete-element-method (DEM) simulations of different-sized particles in a rotated drum to validate the model and determine diffusion, drag, and stress partition coefficients. The model and simulations together indicate, surprisingly, that gravity-driven kinetic sieving is not active in these flows. Rather, a gradient in kinetic stress is the key segregation driving mechanism, while gravity plays primarily an implicit role through the kinetic stress gradients. Finally, we demonstrate that this framework captures the experimentally observed segregation reversal of larger particles downward in particle mixtures where the larger particles are sufficiently denser than their smaller counterparts.

Original languageEnglish (US)
Pages (from-to)54-88
Number of pages35
JournalJournal of Fluid Mechanics
Volume756
DOIs
StatePublished - Oct 2014

Keywords

  • granular media
  • mixing
  • multiphase and particle-laden flows

Fingerprint

Dive into the research topics of 'Segregation in dense sheared flows: Gravity, temperature gradients, and stress partitioning'. Together they form a unique fingerprint.

Cite this