Continuum modeling of size-segregation and flow in dense, bidisperse granular media: Accounting for segregation driven by both pressure gradients and shear-strain-rate gradients
Harkirat Singh (1), Daren Liu (1), David L. Henann (1) ((1) Brown, University)

TL;DR
This paper develops a continuum model for dense, bidisperse granular flow that accounts for segregation driven by both pressure and shear-strain-rate gradients, validated against DEM simulations across different geometries.
Contribution
It extends previous models by integrating pressure-gradient-driven segregation with shear-driven models within a nonlocal rheology framework, enabling accurate predictions across multiple flow configurations.
Findings
Both pressure and shear-driven forces are essential for accurate segregation modeling.
The coupled continuum model successfully predicts segregation dynamics in inclined plane and shear flows.
Model parameters calibrated with DEM data provide consistent results across different geometries.
Abstract
Dense mixtures of particles of varying size tend to segregate based on size during flow. Granular size-segregation plays an important role in many industrial and geophysical processes, but the development of coupled, continuum models capable of predicting the evolution of segregation dynamics and flow fields in dense granular media across different geometries has remained a longstanding challenge. One reason is because size-segregation stems from two driving forces: (1) pressure gradients and (2) shear-strain-rate gradients. Another reason is due to the challenge of integrating segregation models with rheological constitutive equations for dense granular flow. In this paper, we build upon our prior work, which combined a model for shear-strain-rate-gradient-driven segregation with a nonlocal continuum model for dense granular flow rheology, and append a model for…
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Taxonomy
TopicsGranular flow and fluidized beds · Landslides and related hazards · Soil and Unsaturated Flow
