A predictive, size-dependent continuum model for dense granular flows
Name
Hennan-2013-A predictive, size-dependent continuum model for dense granular flows.pdf
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1.08 MB
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Adobe PDF
Checksum (MD5)
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Author(s)
Henann, David Lee
Kamrin, Kenneth N.
Date Issued
March 2013
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Henann, D. L., and K. Kamrin. “A predictive, size-dependent continuum model for dense granular flows.” Proceedings of the National Academy of Sciences 110, no. 17 (April 23, 2013): 6730-6735.
Version
Final published version
Abstract
Dense granular materials display a complicated set of flow properties, which differentiate them from ordinary fluids. Despite their ubiquity, no model has been developed that captures or predicts the complexities of granular flow, posing an obstacle in industrial and geophysical applications. Here we propose a 3D constitutive model for well-developed, dense granular flows aimed at filling this need. The key ingredient of the theory is a grain-size-dependent nonlocal rheology—inspired by efforts for emulsions—in which flow at a point is affected by the local stress as well as the flow in neighboring material. The microscopic physical basis for this approach borrows from recent principles in soft glassy rheology. The size-dependence is captured using a single material parameter, and the resulting model is able to quantitatively describe dense granular flows in an array of different geometries. Of particular importance, it passes the stringent test of capturing all aspects of the highly nontrivial flows observed in split-bottom cells—a geometry that has resisted modeling efforts for nearly a decade. A key benefit of the model is its simple-to-implement and highly predictive final form, as needed for many real-world applications.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1219153110
