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Massachusetts Institute of Technology

Stochastic and deterministic models for dense granular flow

Abstract

dc:description.abstract

Granular materials such as sand or gravel surround us everyday and yet remain poorly understood. In this thesis, two models are developed for dense granular flow, each capable of predicting flows with accuracy in multiple environments. The models are based on differing perspectives of grain-level dynamics, with one deriving flow from a stochastic mechanism and the other from a deterministic deformation law. The Stochastic Flow Rule (SFR): This work models granular flow as a sequence of localized collective grain displacements. As in the Spot Model for drainage (Bazant 2001), grain clusters move as dictated by "spots" which travel through the material as biased random-walkers. The SFR derives spot motion directly from the material stresses, thus generalizing and extending the Spot Model beyond drainage to any quasi-2D geometry with a computable stress field. Limit-State Mohr-Coulomb Plasticity is used to approximate the stress profile in a slow flowing granular assembly. The SFR then describes quantitatively how to convert the slip-line field and stresses into the necessary parameters to fully define a spot's random trajectory through the material and generate a steady flow profile. Results are compared to known flow data. Nonlinear Granular Elasto-Plasticity: This work models granular deformation at the meso-scale as a deterministic consequence of the local stresses and state parameters. Recently proposed models for granular elasticity (Jiang and Liu 2003) and plastic flow (Jop et al. 2006) are combined into one universal granular continuum law, capable of predicting both flowing regions and stagnant zones simultaneously in any arbitrary 3D flow geometry.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Mathematics.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2008

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kamrin, Kenneth Norman
Advisor dc:contributor.advisor
  • Martin Z. Bazant.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/43736
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/43736

Chain of custody

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Base URL
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Last updated
2026-07-22
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citation

Kamrin, Kenneth Norman. Stochastic and deterministic models for dense granular flow. Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/43736