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Parametrization and validation of a nonsmooth discrete element method for simulating flows of iron ore green pellets
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0002-0787-4988
Algoryx Simulation AB, Umeå, Sweden.
LKAB R&D, Malmberget, Sweden.
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2015 (English)In: Powder Technology, ISSN 0032-5910, E-ISSN 1873-328X, Vol. 283, 475-487 p.Article in journal (Refereed) Published
Abstract [en]

The nonsmooth discrete element method (NDEM) has the potential of high computational efficiency for rapid exploration of large design space of systems for processing and transportation of mineral ore. We present parametrization, verification and validation of a simulation model based on NDEM for iron ore green pellet flow in balling circuits. Simulations are compared with camera based measurements of individual pellet motion as well as bulk behavior of pellets on conveyors and in rotating balling drum. It is shown that the NDEM simulation model is applicable for the purpose of analysis, design and control of iron ore pelletizing systems. The sensitivity to model and simulation parameters is investigated. It is found that: the errors associated with large time-step integration do not cause statistically significant errors to the bulk behavior; rolling resistance is a necessary model component; and the outlet flow from the drum is sensitive to fine material adhering to the outlet creating a thick coating that narrows the outlet gaps.

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 283, 475-487 p.
Keyword [en]
Granular materials, Discrete element method, Validation, Iron ore pellets, Pelletizing, Balling circuit
National Category
Computational Mathematics Chemical Engineering
Identifiers
URN: urn:nbn:se:umu:diva-109902DOI: 10.1016/j.powtec.2015.05.040ISI: 000361263300051OAI: oai:DiVA.org:umu-109902DiVA: diva2:861474
Available from: 2015-10-16 Created: 2015-10-09 Last updated: 2015-10-29Bibliographically 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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Wang, DaServin, Martin
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