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Examining the smooth and nonsmooth discrete element approaches to granular matter
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Computing Science. (HPC2N)
Umeå University, Faculty of Science and Technology, Department of Computing Science. (HPC2N)
2014 (English)In: International Journal for Numerical Methods in Engineering, ISSN 0029-5981, E-ISSN 1097-0207, Vol. 97, no 12, 878-902 p.Article in journal (Refereed) Published
Abstract [en]

The smooth and nonsmooth approaches to the discrete element method (DEM) are examined from a computational perspective. The main difference can be understood as using explicit versus implicit time integration. A formula is obtained for estimating the computational effort depending on error tolerance, system geometric shape and size, and on the dynamic state. For the nonsmooth DEM (NDEM), a regularized version mapping to the Hertz contact law is presented. This method has the conventional nonsmooth and smooth DEM as special cases depending on size of time step and value of regularization. The use of the projected Gauss-Seidel solver for NDEM simulation is studied on a range of test systems. The following characteristics are found. First, the smooth DEM is computationally more efficient for soft materials, wide and tall systems, and with increasing flow rate. Secondly, the NDEM is more beneficial for stiff materials, shallow systems, static or slow flow, and with increasing error tolerance. Furthermore, it is found that just as pressure saturates with depth in a granular column, due to force arching, also the required number of iterations saturates and become independent of system size. This effect make the projected Gauss-Seidel solver scale much better than previously thought.

Place, publisher, year, edition, pages
John Wiley & Sons, 2014. Vol. 97, no 12, 878-902 p.
Keyword [en]
discrete element method;multibody dynamics, granular media, contact, explicit time integration, linear solvers
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-87019ISI: 000331358000002OAI: oai:DiVA.org:umu-87019DiVA: diva2:710790
Available from: 2014-04-08 Created: 2014-03-18 Last updated: 2017-12-05Bibliographically approved
In thesis
1. Accelerated granular matter simulation
Open this publication in new window or tab >>Accelerated granular matter simulation
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Accelererad simulering av granulära material
Abstract [en]

Modeling and simulation of granular matter has important applications in both natural science and industry. One widely used method is the discrete element method (DEM). It can be used for simulating granular matter in the gaseous, liquid as well as solid regime whereas alternative methods are in general applicable to only one. Discrete element analysis of large systems is, however, limited by long computational time. A number of solutions to radically improve the computational efficiency of DEM simulations are developed and analysed. These include treating the material as a nonsmooth dynamical system and methods for reducing the computational effort for solving the complementarity problem that arise from implicit treatment of the contact laws. This allow for large time-step integration and ultimately more and faster simulation studies or analysis of more complex systems. Acceleration methods that can reduce the computational complexity and degrees of freedom have been invented. These solutions are investigated in numerical experiments, validated using experimental data and applied for design exploration of iron ore pelletising systems.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2015. 14 p.
Keyword
discrete element method, nonsmooth contact dynamics, multibody dynamics, granular media, simulation, projected Gauss-Seidel, validation, iron ore pellets, pelletising balling circuit, model reduction, design optimization
National Category
Other Physics Topics Computational Mathematics
Identifiers
urn:nbn:se:umu:diva-110164 (URN)978-91-7601-366-3 (ISBN)
Public defence
2015-11-12, Naturvetarhuset, N460, Umeå universitet, Umeå, 13:00 (English)
Opponent
Supervisors
Funder
VINNOVA, 2014-01901
Note

This work has been generously supported by Algoryx Simulation, LKAB (dnr 223-

2442-09), Umeå University and VINNOVA (2014-01901).

Available from: 2015-10-22 Created: 2015-10-15 Last updated: 2015-10-22Bibliographically approved

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