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Adaptive model reduction for nonsmooth discrete element simulation
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.
2016 (English)In: Computational Particle Mechanics, ISSN 2196-4378, Vol. 3, no 1, p. 107-121Article in journal (Refereed) Published
Abstract [en]

A method for adaptive model order reduction for nonsmooth discrete element simulation is developed and analysed in numerical experiments. Regions of the granular media that collectively move as rigid bodies are substituted with rigid bodies of the corresponding shape and mass distribution. The method also support particles merging with articulated multibody systems. A model approximation error is defined and used to derive conditions for when and where to apply reduction and refinement back into particles and smaller rigid bodies. Three methods for refinement are proposed and tested: prediction from contact events, trial solutions computed in the background and using split sensors. The computational performance can be increased by 5-50 times for model reduction level between 70-95 %.

Place, publisher, year, edition, pages
2016. Vol. 3, no 1, p. 107-121
Keywords [en]
Discrete elements, Nonsmooth contact dynamics, Adaptive model reduction, Merge and split
National Category
Computational Mathematics Physical Sciences
Research subject
Physics
Identifiers
URN: urn:nbn:se:umu:diva-110063DOI: 10.1007/s40571-015-0100-5ISI: 000417454500010OAI: oai:DiVA.org:umu-110063DiVA, id: diva2:860961
Funder
VINNOVA, 2014-01901Available from: 2015-10-14 Created: 2015-10-14 Last updated: 2018-06-07Bibliographically 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. p. 14
Keywords
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: 2018-06-07Bibliographically approved

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Servin, MartinWang, Da

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