Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Development of a geometallurgical framework for iron ores - A mineralogical approach to particle-based modeling
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Minerals and Metallurgical Engineering. (Mineral processing)ORCID iD: 0000-0002-5979-5608
2017 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Utveckling av ett geometallurgiskt ramverk för järnmalmer - Ett mineralogiskt angreppssätt till partikelbaserad modellering. (Swedish)
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.

Place, publisher, year, edition, pages
Luleå University of Technology, 2017. , p. 107
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords [en]
Geometallurgy, process simulation, breakage characterization, ore texture, iron ore, modal mineralogy
National Category
Mineral and Mine Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-62515ISBN: 978-91-7583-860-1 (print)ISBN: 978-91-7583-861-8 (electronic)OAI: oai:DiVA.org:ltu-62515DiVA, id: diva2:1085691
Public defence
2017-05-09, F531, F-hus, Luleå University of Technology Campus, Luleå, 10:00 (English)
Opponent
Supervisors
Available from: 2017-04-05 Created: 2017-03-30 Last updated: 2017-11-24Bibliographically approved
List of papers
1. Analysis of mineral grades for geometallurgy: Combined element-to-mineral conversion and quantitative X-ray diffraction
Open this publication in new window or tab >>Analysis of mineral grades for geometallurgy: Combined element-to-mineral conversion and quantitative X-ray diffraction
2015 (English)In: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 82, p. 25-35Article in journal (Refereed) Published
Abstract [en]

Knowledge of the grade of valuable elements and its variation is not sufficient for geometallurgy. Minerals define not only the value of the deposit, but also the method of extraction and concentration. A number of methods for obtaining mineral grades were evaluated with a focus on geometallurgical applicability, precision and trueness. For a geometallurgical program, the number of samples to be analyzed is large, therefore a method for obtaining mineral grades needs to be cost-efficient, relatively fast, and reliable. Automated mineralogy based on scanning electron microscopy is generally regarded as the most reliable method for analyzing mineral grades. However, the method is time demanding and expensive. Quantitative X-ray diffraction has a relatively high detection limit, 0.5%, while the method is not suitable for some base and precious metal ores, it still provides significant details on gangue mineral grades. The application of the element-to-mineral conversion has been limited to the simple mineralogy because the number of elements analyzed limits the number of calculable mineral grades. This study investigates a new method for the estimation of mineral grades applicable for geometallurgy by combining both the element-to-mineral conversion method and quantitative X-ray diffraction with Rietveld refinement. The proposed method not only delivers the required turnover for geometallurgy, but also overcomes the shortcomings if quantitative X-ray diffraction or element-to-mineral is used alone

National Category
Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
urn:nbn:se:ltu:diva-29511 (URN)10.1016/j.mineng.2015.04.023 (DOI)000362617800004 ()2-s2.0-84942190839 (Scopus ID)304b2a4f-f491-4bf6-8d10-14bc9b45181c (Local ID)304b2a4f-f491-4bf6-8d10-14bc9b45181c (Archive number)304b2a4f-f491-4bf6-8d10-14bc9b45181c (OAI)
Conference
Process Mineralogy : 17/11/2014 - 19/11/2014
Note

Validerad; 2015; Nivå 1; 20150616 (andbra)

; Konferensartikel i tidskriftAvailable from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved
2. Developing a particle-based process model for unit operations of mineral processing: WLIMS
Open this publication in new window or tab >>Developing a particle-based process model for unit operations of mineral processing: WLIMS
2016 (English)In: International Journal of Mineral Processing, ISSN 0301-7516, E-ISSN 1879-3525, Vol. 154, p. 53-65Article in journal (Refereed) 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.

National Category
Metallurgy and Metallic Materials
Research subject
Mineral Processing
Identifiers
urn:nbn:se:ltu:diva-6803 (URN)10.1016/j.minpro.2016.07.001 (DOI)000383937600007 ()2-s2.0-84978300151 (Scopus ID)51940004-00c5-4a57-b700-a8a32111b368 (Local ID)51940004-00c5-4a57-b700-a8a32111b368 (Archive number)51940004-00c5-4a57-b700-a8a32111b368 (OAI)
Note

Validerad; 2016; Nivå 2; 20160815 (andbra)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
3. Ore texture breakage characterization and fragmentation into multiphase particles
Open this publication in new window or tab >>Ore texture breakage characterization and fragmentation into multiphase particles
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The ore texture and the progeny particles after a breakage in the comminution are the missing link between geology and mineral processing in the concept of geometallurgy. A new method called association indicator matrix based on co-occurrence matrix was introduced to analyze the mineral association of ore texture and particles.  The association indicator matrix can be used as a criterion to classify ore texture and analyze breakage behavior of ore texture. Within the study, the outcome of breakage analysis with association indicator matrix was used to generate particle population of iron ore texture after crushing. The particle size of forecasted particles was taken from experimental and frequency of breakage in phases was defined based on association indicator and liberation of minerals. Comparison of liberation distribution of iron oxide minerals from experimental and forecasted population shows a good agreement.

Keywords
Textural characterization, mineral liberation, breakage, particle population
National Category
Mineral and Mine Engineering
Identifiers
urn:nbn:se:ltu:diva-62784 (URN)
Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2017-03-30
4. Process simulation in mineralogy-based geometallurgy of iron ores
Open this publication in new window or tab >>Process simulation in mineralogy-based geometallurgy of iron ores
(English)Manuscript (preprint) (Other academic)
Abstract [en]

The mineral processing simulation models can be classified based on the level that the feed stream to the plant and unit operations is described. The levels of modeling in this context is as bulk, mineral or element by size, and particle. Particle level modeling and simulation utilizes liberation data in the feed stream and is more sensitive to the variations in ore feed quality. Within the paper, results of simulation for two texturally different magnetite ore is demonstrated in bulk, mineral by size and particle level. The models were calibrated for one ore, and all the modeling levels show similar results, but for the other ore, the results differ. This is because, in the bulk level, the model assumes that magnetite, as well as other minerals, do not change their behavior if ore texture and grinding fineness are changed. In the mineral by size level, the assumption is that minerals behave identically in each size fraction even the ore texture changes. In the particle level, the assumption is that similar particles behave in the same way. The particle level approach gives more realistic results, and it can also be used in optimization, thus finding the most optimal processing way for different geometallurgical domains. In iron ores where iron minerals are highly liberated the particle level shows its power in the prediction of impurity levels rather than iron grade and recovery.

Keywords
Geometallurgy, mineral liberation, particles, process modeling, simulation
National Category
Mineral and Mine Engineering
Identifiers
urn:nbn:se:ltu:diva-62785 (URN)
Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2017-03-30

Open Access in DiVA

fulltext(8733 kB)360 downloads
File information
File name FULLTEXT01.pdfFile size 8733 kBChecksum SHA-512
7167712271d1161cdc6ffcd17363e6a80944699fa1fea557350ea7a03f2e504440d0b26d37c1a8612c9ba8f36bd8429b615133b02b7990f598f7077cd734de45
Type fulltextMimetype application/pdf

Authority records BETA

Parian, Mehdi

Search in DiVA

By author/editor
Parian, Mehdi
By organisation
Minerals and Metallurgical Engineering
Mineral and Mine Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 360 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 963 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf