A predictive, size-dependent continuum model for dense granular flows

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 w...

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Bibliographic Details
Main Authors: Henann, David Lee (Contributor), Kamrin, Kenneth N. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: National Academy of Sciences (U.S.), 2013-10-04T12:09:31Z.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Henann, David Lee  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Mechanical Engineering  |e contributor 
100 1 0 |a Henann, David Lee  |e contributor 
100 1 0 |a Kamrin, Kenneth N.  |e contributor 
700 1 0 |a Kamrin, Kenneth N.  |e author 
245 0 0 |a A predictive, size-dependent continuum model for dense granular flows 
260 |b National Academy of Sciences (U.S.),   |c 2013-10-04T12:09:31Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/81299 
520 |a 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. 
520 |a Massachusetts Institute of Technology. Dept. of Mechanical Engineering 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the National Academy of Sciences