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Process simulations in mineralogy-based geometallurgy of iron ores
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.ORCID-id: 0000-0002-5979-5608
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Mineralteknik och metallurgi.
2018 (engelsk)Inngår i: Transactions of the Institution of Mining and Metallurgy Section C - Mineral Processing and Extractive Metallurgy, ISSN 0371-9553, E-ISSN 1743-2855Artikkel i tidsskrift (Fagfellevurdert) Epub ahead of print
Abstract [en]

Mineral processing simulation models can be classified based on the level that feed stream to the plant and unit models are described. The levels of modelling in this context are: bulk, mineral or element by size, and particle. Particle level modelling and simulation utilises liberation data in the feed stream and is more sensitive to the variations in ore quality, specifically ore texture. In this paper, simulations for two texturally different magnetite ores are demonstrated at different modelling levels. The model parameters were calibrated for current run-of-mine ore and then in the simulation applied directly to the other ore. For the second ore, the simulation results vary between the different levels. This is because, at the bulk level, the model assumes minerals do not change their behaviour if ore texture or grinding fineness are changed. At the mineral by size level, the assumption is that minerals behave identically in each size fraction even if the ore texture changes. At the particle level, the assumption is that similar particles behave in the same way. The particle level approach gives results that are more realistic and it can be used in optimisation, thus finding the most optimal processing way for different geometallurgical domains.

sted, utgiver, år, opplag, sider
Taylor & Francis, 2018.
HSV kategori
Forskningsprogram
Mineralteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-70357DOI: 10.1080/25726641.2018.1507072OAI: oai:DiVA.org:ltu-70357DiVA, id: diva2:1238416
Tilgjengelig fra: 2018-08-13 Laget: 2018-08-13 Sist oppdatert: 2018-08-13

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Parian, MehdiLamberg, PerttiRosenkranz, Jan

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