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Research Abstracts Online
January 2010 - March 2011

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University of Minnesota Twin Cities
College of Science and Engineering
Department of Civil Engineering
St. Anthony Falls Laboratory

PI: Kimberly M. Hill

Computational Models for Particle-Laden Mixtures

The Discrete Element Method (DEM) is the most commonly used model for dense granular flow. The method models granular materials by approximating interparticle forces, summing the forces on every particle at every time step to find accelerations, and numerically integrating to solve for particle motion. The DEM method represents granular physics of dry granular systems reasonably well. Further, it allows a simple framework for exploring the effect of interparticle forces on system dynamics. In this way, it allows for an exploration of the particle-scale physics responsible for macroscopic behavior of granular systems and particle-laden flow. The short‐term goal of this project is to continue to build on a DEM code developed by the researchers to understand some of the basic physics of mixtures including small- and large-scale segregation tendencies and how the resulting particle size and density distributions influence the rheology of granular flows. In the previous period, they have built on this to include the effects of fluids using simple models for unsaturated and saturated flows. From the work on dry flows, they derived a model for the rheology of binary mixtures as it depends on certain parameters related to the particle size distribution. They have also developed a zeroth-order model for shear‐induced segregation. The next period will build on this work to understand how more complicated and intermediate range forces affect the rheology and segregation tendencies. Collaborative work with geomorphologists performing large-scale field and experimental work will help the researchers determine the applicability for a wider range of geological systems including debris flows. The long-term goal of the research is to use the results from various DEM studies to develop a predictive constitutive model for dense granular mixtures, ultimately for dry and moist granular materials.

Group Members

Marisa Palucis, Visiting Researcher
Fan Yi, Graduate Student
Bereket Towoldebrhan Yohannes, Graduate Student
Jiafeng Zhang, Mechanical Science and Engineering, College of Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois