Skip to content
naulon
Not checkedNot checked for notices yet.

Granular Temperature and Segregation in Dense Sheared Particulate Mixtures

Kimberly M. Hill, Yi Fan

KONA Powder and Particle Journal · 2016

doi:10.14356/kona.2016022 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

In gravity-driven flows of different-sized (same density) particles, it is well known that larger particles tend to segregate upward (toward the free surface), and the smaller particles downward in the direction of gravity. Alternatively, when the particles are of the same size but different density, lighter particles tend to segregate upward and heavier particles, downward. When particles differ in both size and density, true of most mixtures of interest in industry and nature, the details are complicated and no rule based on gravity alone has captured the segregation behaviours. Gradients of granular temperature and kinetic stress (i.e., energy and stress associated with velocity fluctuations) offer alternative segregation driving forces, but have, until recently, been discounted as these dynamics are relatively small in dense flows. Recently, gradients in kinetic stress have been shown to play a significant role in segregating densely sheared particle mixtures, even where the kinetic stress is a relatively small percentage of the total stress. We review recent modelling advances accounting for this effect and validation in computational experiments. We show how this framework may be useful in capturing the complicated segregation phenomenology that emerges for dense sheared flows of particles different in both size and density.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.