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Developing a particle-based process model for unit operations of mineral processing: WLIMS
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.
Antal upphovsmän: 32016 (Engelska)Ingår i: International Journal of Mineral Processing, ISSN 0301-7516, E-ISSN 1879-3525, Vol. 154, s. 53-65Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Process models in mineral processing can be classified based on the level of information required from the ore, i.e. the feed stream to the processing plant. Mineral processing models usually require information on total solid flow rate, mineralogical composition and particle size information. The most comprehensive level of mineral processing models is the particle-based one (liberation level), which gives particle-by-particle information on their mineralogical composition, size, density, shape i.e. all necessary information on the processed material for simulating unit operations. In flowsheet simulation, the major benefit of a particle-based model over other models is that it can be directly linked to any other particle-based unit models in the process simulation. This study aims to develop a unit operation model for a wet low intensity magnetic separator on particle property level. The experimental data was gathered in a plant survey of the KA3 iron ore concentrator of Luossavaara-Kiirunavaara AB in Kiruna. Corresponding feed, concentrate and tailings streams of the primary magnetic separator were sampled, assayed and mass balanced on mineral liberation level. The mass-balanced data showed that the behavior of individual particles in the magnetic separation is depending on their size and composition. The developed model involves a size and composition dependent entrapment parameter and a separation function that depends on the magnetic volume of the particle and the nature of gangue mineral. The model is capable of forecasting the behavior of particles in magnetic separation with the necessary accuracy. This study highlights the benefits that particle-based models in simulation offer whereas lower level process models fail to provide.

Ort, förlag, år, upplaga, sidor
2016. Vol. 154, s. 53-65
Nationell ämneskategori
Metallurgi och metalliska material
Forskningsämne
Mineralteknik
Identifikatorer
URN: urn:nbn:se:ltu:diva-6803DOI: 10.1016/j.minpro.2016.07.001ISI: 000383937600007Scopus ID: 2-s2.0-84978300151Lokalt ID: 51940004-00c5-4a57-b700-a8a32111b368OAI: oai:DiVA.org:ltu-6803DiVA, id: diva2:979689
Anmärkning

Validerad; 2016; Nivå 2; 20160815 (andbra)

Tillgänglig från: 2016-09-29 Skapad: 2016-09-29 Senast uppdaterad: 2018-07-10Bibliografiskt granskad
Ingår i avhandling
1. Development of a geometallurgical framework for iron ores - A mineralogical approach to particle-based modeling
Öppna denna publikation i ny flik eller fönster >>Development of a geometallurgical framework for iron ores - A mineralogical approach to particle-based modeling
2017 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Alternativ titel[sv]
Utveckling av ett geometallurgiskt ramverk för järnmalmer - Ett mineralogiskt angreppssätt till partikelbaserad modellering.
Abstract [en]

The demands for efficient utilization of ore bodies and proper risk management in the mining industry have resulted in a new cross-disciplinary subject called geometallurgy. Geometallurgy connects geological, mineral processing and subsequent downstream processing information together to provide a comprehensive model to be used in production planning and management. A geometallurgical program is an industrial application of geometallurgy. Various approaches that are employed in geometallurgical programs include the traditional way, which uses chemical elements, the proxy method, which applies small-scale tests, and the mineralogical approach using mineralogy or the combination of those. The mineralogical approach provides the most comprehensive and versatile way to treat geometallurgical data. Therefore it was selected as a basis for this study.

For the mineralogical approach, quantitative mineralogical information is needed both for the deposit and the process. The geological model must describe the minerals present, give their chemical composition, report their mass proportions (modal composition) in the ore body and describe the ore texture. The process model must be capable of using mineralogical information provided by the geological model to forecast the metallurgical performance of different geological volumes and periods. A literature survey showed that areas, where more development is needed for using the mineralogical approach, are: 1) quick and inexpensive techniques for reliable modal analysis of the ore samples; 2) ore textural characterization of the ore to forecast the liberation distribution of the ore when crushed and ground; 3) unit operation models based on particle properties (at mineral liberation level) and 4) a system capable of handling all this information and transferring it to production model. This study focuses on developing tools in these areas.

A number of methods for obtaining mineral grades were evaluated with a focus on geometallurgical applicability, precision, and trueness. A new technique developed called combined method uses both quantitative X-ray powder diffraction with Rietveld refinement and the Element-to-Mineral Conversion method. The method not only delivers the required turnover for geometallurgy but also overcomes the shortcomings if X-ray powder diffraction or Element-to-Mineral Conversion were used alone.

Characterization of ore texture before and after breakage provides valuable insights about the fracture pattern in comminution, the population of particles for specific ore texture and their relation to parent ore texture. In the context of the mineralogical approach to geometallurgy, predicting the particle population from ore texture is a critical step to establish an interface between geology and mineral processing. A new method called Association Indicator Matrix developed to assess breakage pattern of ore texture and analyze mineral association. The results of ore texture and particle analysis were used to generate particle population from ore texture by applying particle size distribution and breakage frequencies. The outcome matches well with experimental data specifically for magnetite ore texture.

In geometallurgy, process models can be classified based on in which level the ore, i.e. the feed stream to the processing plant and each unit operation, is defined and what information subsequent streams carry. The most comprehensive level of mineral processing models is the particle-based one which includes practically all necessary information on streams for modeling unit operations. Within this study, a particle-based unit operation model was built for wet low-intensity magnetic separation, and existing size classification and grinding models were evaluated to be used in particle level. A property-based model of magnetic beneficiation plant was created based on one of the LKAB operating plants in mineral and particle level and the results were compared. Two different feeds to the plant were used. The results revealed that in the particle level, the process model is more sensitive to changes in feed property than any other levels. Particle level is more capable for process optimization for different geometallurgical domains.

Ort, förlag, år, upplaga, sidor
Luleå University of Technology, 2017. s. 107
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Nyckelord
Geometallurgy, process simulation, breakage characterization, ore texture, iron ore, modal mineralogy
Nationell ämneskategori
Mineral- och gruvteknik
Identifikatorer
urn:nbn:se:ltu:diva-62515 (URN)978-91-7583-860-1 (ISBN)978-91-7583-861-8 (ISBN)
Disputation
2017-05-09, F531, F-hus, Luleå University of Technology Campus, Luleå, 10:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2017-04-05 Skapad: 2017-03-30 Senast uppdaterad: 2017-11-24Bibliografiskt granskad

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Parian, MehdiLamberg, PerttiRosenkranz, Jan

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