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A Particle Based Modelling Approach for Predicting Charge Dynamics in Tumbling Ball Mills
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mechanics of Solid Materials.ORCID iD: 0000-0003-0910-7990
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mechanics of Solid Materials.ORCID iD: 0000-0001-5206-6894
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering.ORCID iD: 0000-0002-8032-9388
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mechanics of Solid Materials.ORCID iD: 0000-0001-7895-1058
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2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Wet grinding of minerals in tumbling mills is a highly important process in the mining industry. During grinding in tumbling mills, lifters submerge into the charge and create motions in the ball charge, the lifters is exposed for impacts and shear loads that will wear down the lifters. Increased loading can accelerate the wear and the lining has to be replaced. Replacing the lining is an expensive and time consuming operation that is preferred to be done within planned maintenance stops. Prediction of the charge motion and wear rate for different grinding operations and linings are therefore desirable to predict the lining life.

 

Modelling of wet grinding in tumbling mills that include pulp fluid and its interaction with both the grinding balls and the mill structure is an interesting challenge and some different approaches have been suggested, see [1-2]. For an effective and successful prediction, the numerical model has to be able to handle the pulp fluid and its simultaneous interactions with both the ball charge and the mill structure, in a computationally efficient approach. In this work, the pulp fluids are modelled with a Lagrange based method called incompressible computational fluid dynamics, (ICFD), which gives the opportunity to model free surface flow. This method gives robustness and stability to the fluid model and is efficient as it gives possibility to use larger time steps than the conventional CFD. The ICFD solver can be coupled to other solvers as in this case the finite element method, (FEM) solver for the mill structure and the discrete element method (DEM) solver for the ball charge. The combined ICFD-DEM-FEM model can predict both charge motion and responses from the mill structure, as well as the pulp liquid flow and pressure. The numerical grinding case presented here is validated against experimentally measured driving torque signatures from an instrumented small-scale batch ball mill, see [3]. This approach opens up the possible to predict the volume of the high-energy zone and optimise lifter design and operating conditions. The ICFD solver improve efficiency and robustness for studying wet grinding in tumbling mill systems and can predict the charge dynamics and the wear distribution in such systems.

 

References

[1]   Jonsén, P. et al., (2018). Preliminary validation of a new way to model physical interactions between pulp, charge and mill structure in tumbling mills. Minerals Enginering. Accepted for publication

[2]   Jonsén, P., Stener, J.F., Pålsson, B.I. and Häggblad, H.-Å., (2015). Validation of a model for physical interactions between pulp, charge and mill structure in tumbling mills. Minerals Engineering, Vol. 73, 77–84.

[3]   Jonsén, P. Stener, J. F. Pålsson, B. I. and Häggblad, H.-Å., (2013). Validation of tumbling mill charge induced torque as predicted by simulations. Minerals and Metallurgical Processing, vol. 30, No. 4, 220-225.

Place, publisher, year, edition, pages
Luleå, 2018.
National Category
Applied Mechanics
Research subject
Solid Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-71745OAI: oai:DiVA.org:ltu-71745DiVA, id: diva2:1265546
Conference
13th World Congress in Computational Mechanics
Available from: 2018-11-24 Created: 2018-11-24 Last updated: 2018-12-11

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Jonsén, PärLarsson, SimonPålsson, BertilHammarberg, SamuelLindkvist, Göran
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