Two-Dimensional Discrete Element Theory for Rough Particles
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VIEW THE REPLYPublication: International Journal of Geomechanics
Volume 9, Issue 1
Abstract
The surfaces of real sands are often rough and a discrete element modeling of rough granulates is very important to understand the behavior of real sands. This paper presents a two-dimensional discrete element method (DEM) to capture the roughness of particles. The model consists of two parts: equations governing the motion of rough particles and mechanical contact models controlling rough-contact behavior. The key point of the theory is that the assumption in the original DEM proposed by Cundell and Strack in 1979 that a pair of particles are in single-point contact, is here replaced by that the particles are in rough contact over a width. By making the idealization that the contact width is homogeneously distributed with a finite-number of the normal/tangential basic elements (BEs) (each BE is composed of spring, dashpot, slider, or divider), we relate the governing equations to local equilibrium and also establish a rolling contact model together with normal/tangential contact models. The three main features of the theory are that: two physical parameters need to be introduced in the theory to represent particle roughness in comparison to the original DEM; rolling stiffness, rolling viscous-damping parameter, and rolling strength due to roughness are all linked with their respective counterparts in the normal direction in a simple and complete formula through these two parameters; the equations governing motion of rough particles satisfy the local equilibrium condition. The present theory was incorporated into a DEM code to investigate the mechanical response of the material of different roughness, particularly the angle of internal friction . Twenty-four DEM simulations showed that predicted by the theory was significantly increased in comparison to the standard DEM prediction.
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Acknowledgments
The work in this paper was initiated at Université Laval, financially supported by the NSERC,NSERC Canada, and in the U.K. with assistance of EPSRC Grant No. EPSRC-GBGR/R85792/01, U.K. The main work was completed with financial support of NSF, China Grant No. NSFC50679057; Fund for Chinese Researchers Returning from Overseas with Grant No. 2007-1108; Pujiang Talents Project, Shanghai, China with Grant No. UNSPECIFIED06PJ14088; and “863” Project, China with Grant No. UNSPECIFIED2006AA11Z102. All the support, particularly that from China, is greatly appreciated. In addition, the writers would like to thank the first writer’s MSc student, Jin Sun from Tongji University, for his assistance in sorting out the DEM postanalysis data in this paper.
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Received: Aug 25, 2005
Accepted: Aug 28, 2007
Published online: Jan 1, 2009
Published in print: Jan 2009
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