Part One - Characterization and analysis of iron ore

The basic characteristics of iron ore, including assimilation, fluidity, cohesive phase strength and the ability to produce calcium ferrite, are often used to evaluate the sintering properties of iron ore and guide the optimization of iron ore blending. Six kinds of common iron ore used in a steel company in China were selected in this work. The basic characteristics of the single iron ore and blended iron ores were studied, as well as the difference between weighted averages of basic characteristic index of single iron ores and the real value of basic characteristic index of blended iron ore under different ore blending ratios. The results shew that the liquid phase liquidity, cohesive phase strength and calcium ferrite formation ability had a significant linear positive correlation with SiO2 content. The weighted average of basic characteristic index of single iron ore cannot fully reflect the actual blended iron ore properties. The optimization of the blending ratio can be achieved through the detection of the basic characteristics of the mixed iron ore, combined with the basic characteristics of iron ores.

This study aims to understand the effect of sintering at 1623 K on the reaction characteristics of iron ores. By investigating the reaction characteristics of nine different iron ores with disparate properties, new reactivity indices including the iron ore reactivity index (IRI) and iron ore blending reactivity index (IBRI) independent of the sample size are derived based on the melt penetration depth of preformed cubicalironore tablets. Furthermore, the effect of sintering on the reactivity of iron ore is also identified. Using a rapid heating/cooling infrared furnace equipment, duplicate iron ore reaction tests are conducted to increase the reproducibility of the results. The case of a high IBRI in the sintering process increases the product yield and average particle size of the sinter. When the IBRI increases by 0.1, the product yield increases by 0.4% and the average size of the sintered ore increases by 0.1 mm. The results show that the degree of reaction between iron ore and additives can be estimated during the iron ore blending step and be easily applied in managing commercial‐scale sinter production and quality.

Concentrates have advantages of high ferrous grade, less harmful impurities and lower price. However, the small size and poor granulation behavior of concentrates could deteriorate the permeability of the sinter bed and reduce sinter productivity, thus making it difficult to use concentrates effectively. Therefore, in order to strengthen the granulation behavior of concentrates, granulation experiments were carried out and experiment samples made with one kind of concentrates and five kinds of fine iron ores were produced in this paper. Then, the effects of water absorbility and wettability of fine iron ores on granulation behavior of concentrates were investigated. Furthermore, optimized ore blending recipes were proposed to strengthen the granulation behavior of concentrates by sinter pot tests. Results show that the granulation behavior of concentrates was improved for the samples exhibiting high maximum capillary water and small contact angle in fine iron ores. Compared with the scheme of blending ores containing 15 mass% concentrate, the growth index of quasi-particles increased by 20.62% in the case of iron ore BR-2 replacing half of iron ore BR-1, the vertical sintering speed went up from 26.32 to 29.26 mm min−1, the productivity increased from 1.95 to 2.20 t m−2 h−1. The growth index of the quasi-particles increased by 30% when using iron ore AR-2 to replace half of iron ore AR-1. The vertical sintering speed and the productivity of sinter improved to 29.82 mm min−1 and 2.24 t m−2 h−1, respectively. The results help to improve the granulation behavior of concentrates by optimizing the blending ore recipes, based on the characteristics of fine iron ores, and thus use these concentrates more efficiently in the sintering process.

A textural approach to the geometallurgical characterisation of iron ores helps better predict ore behaviour during downstream processing. Therefore, a robust, automated, objective method for the textural characterisation of iron ores is relevant to both research and industry needs. Utilisation of an optical image analysis (OIA) technique allows reliable and consistent identification of different iron oxide and oxy-hydroxide minerals, e.g. haematite, kenomagnetite, hydrohematite, both vitreous and ochreous goethite. CSIRO Mineral4/Recognition4 OIA system automatically identifies particle sections with different textures and assigns these sections to defined textural groups. Furthermore, novel developments in the system have enabled the automatic identification of different textural forms and morphologies of the same mineral, e.g. martite and microplaty haematite in iron ore; primary and secondary haematite or different types of Silico-Ferrite of Calcium and Aluminium (SFCA) in sinter as well as segmentation of different phases with the same reflectivity like Inert Maceral Derived Components (IMDC) from Reactive Maceral Derived Components (RMDC) in coke.The high resolution and imaging speed of the OIA system makes it possible for users to significantly reduce the cost and subjectivity of iron ore characterisation with a simultaneous increase in the accuracy of mineral identification. Extra software modules have been developed to meet research and industry demands for enhanced productivity. The addition of a ‘Multiple Block Imaging’ module enables image acquisition for sets of polished blocks at a time, rather than separate imaging of individual blocks. The ‘Multiple Set Processing’ module allows the processing up to 20 groups of sets simultaneously, where every group can contain up to 20 different sets of images that share the same analysis profile. The added modules enable analyses to be performed over many hours without the need for operator intervention, thus increasing equipment utilisation and reducing operator time.These new developments, together with the improvement of previously available features, e.g. identification of non-opaque minerals, automated textural classification, automated particle separation, automated correction of mineral maps and on-line measurement, means that OIA can provide a unique, reliable, industry and research focused tool for iron ore, sinter and coke characterisation.

Concentration characteristics of an ore are very critical to the estimation of cut-off grade of a deposit. A mathematical model that can lead to their quick prediction will significantly enhance ore reserve estimation, mine planning and the economy of the mining venture as a whole. In this paper attempts have been made to establish a functional relationship between ore grades and concentration characteristics of Itakpe Iron ore. The Wilcoxon signed rank test has been used to establish a significant level of correspondence between actual values and values obtained from the model. The model has shown that the performance characteristics of the processing plant and the grade of the ore both play vital roles in deciding the concentration characteristics of an ore. ©JASEM

The Per Geijer iron oxide apatite deposits are important potential future resources for Luossavaara-Kiirunavaara Aktiebolag (LKAB) which has been continuously mining magnetite/hematite ores in northern Sweden for over 125 years. Reliable and quantitative characterization of the mineralization is required as these ores inherit complex mineralogical and textural features. Scanning electron microscopy-based analyses software, such as mineral liberation analyzer (MLA) provide significant, time-efficient analyses. Similar elemental compositions of Fe-oxides and, therefore, almost identical backscattered electron (BSE) intensities complicate their discrimination. In this study, MLA and Raman imaging are compared to acquire mineralogical data for better characterization of magnetite and hematite-bearing ores. The different approaches demonstrate advantages and disadvantages in classification, imaging, discrimination of iron oxides, and time consumption of measurement and processing. The obtained precise mineralogical information improves the characterization of ore types and will benefit future processing strategies for this complex mineralization.

Sintering tests of 17 different systems of iron ores with 20% CaO were carried out in air atmosphere at 1 300°C for 2min. Some of them were also subjected to the pot sinter tests to clarify the relation between assimilative characteristics of iron ores and sinter qualities under uniform size distribution of iron ores and the same sintering conditions.The results obtained are as follows:(1) Volume shrinkage degree e, regarded as an index of the assimilative characteristics of iron ore has close correlation with contents of goethite, SiO2 and FeO in iron ore.(2) The increase of the value of e tends to increase formation of locally enhanced liquid phase which causes a weak structure and results in a decrease of sinter strength.(3) The JIS reducibility index (RI) deteriorates with the increase of the value of e. This is because, if the value of e is larger, the enhanced liquid phase causes the formation of fused-type microstructure and the decrease of micropores.(4) The value of e is not sufficient to define their relationship with the reduction degradation index (RDI). Original iron ores can be divided into two groups; one tend to improve RDI and the other liable to deteriorate RDI. The index which is calculated from their characteristic value shows good correlation with RDI.

Influence of Iron Ore Characteristics on FeO Formation During Sintering

The mineralogical characteristics of iron ores can influence their high temperature sintering performance. In this study, eight iron ore samples from Brazil, Australia, and South Africa were characterized by their chemical composition, mineral types, particle morphology, and gangue dispersity. Meanwhile the influence rules between the mineralogical characteristics and the high temperature characteristics were evaluated and analyzed. The results showed that the effect of SiO2 on assimilation characteristic of iron ores was relatively complex, Al2O3 and LOI of iron ores had negative correlation with assimilation temperature of iron ores, the dense slab-flaky mineral granule restrained to the assimilation characteristics of iron ores; liquid phase of iron ores with high SiO2 content and low Al2O3 content had high fluidity, and the higher dispersity of gangue minerals in iron ores was good to the fluidity of liquid phase.

Purpose. Choice of a method for treating the iron ore of the Khanguet mine depending on its characterization. Methodology. This work is focused on the study on physicochemical and mineralogical characterization of the poor iron ore of Khanguet mine, using multiple analysis techniques (X-ray diffraction, X-ray fluorescence, scanning electron microscope and optical microscope), to identify the chemical composition and mineral phases of the ore. The study also focused on the possibility of enrichment, using the electrostatic separation process. For this purpose, two main parameters are studied, such as, the voltage between the electrodes and the rotation speed of the roll. Findings. The results of the characterization show the possibility of using the process of electrostatic separation for the enrichment of the Khanguet ore, which allows increasing the content of Fe2O3 up to 58.46%. Originality. The originality of this work is the possibility to use the electrostatic treatment process for the poor iron ore of the Khanguet iron mine. Practical value. This study shows that the results obtained by the process of electrostatic treatment of ore are very significant; this technique makes it possible to obtain a concentrate with an iron content of 58.46% and to bring an added value to the company and the steelmaking industry, on the one hand, and, on the other hand, to eliminate reserves of these poor iron ores stored near the mining site, which is harmful for the environment.

In India, during mining and ore processing, ore fine generation is a common phenomenon, in which more than 60% of process ore becomes discarded material. To explore the alternative of high-grade ores, mutual replacement with the utility of dump ore fines is the best way. With this perspective, Kiruburu iron ore mine (Iron Ore No.1) and Meghataburu iron ore mine (Iron Ore No.2) dumped fines were chosen for a Blaine no. investigation, in the connection of firing temperatures, to get optimum desirable physical properties, Cold Compression Strength (C.C.S.),and Apparent Porosity (A.P.), with physico-chemical properties, Reducibility Degradation Index (R.D.I.), and Reducibility Index (R.I.). To characterize pellet properties with input variables, a microstructure phase study has been conducted using a scanning electron microscope (S.E.M.), energy dispersive spectroscopy (EDS), and X-ray diffraction analysis (XRD). The Iron Ore No.1 and 2 fine pellets survey showed good, desirable properties, at the Blaine no., of 1678 cm2/g and 2311 cm2/g (corresponding to 200 mesh size), and the best results are attained at a firing temperature of 1300 °C. Thermal kinetic analysis of the heating of pellets has been done to knowthe activation energy of different ore characteristics. The results showed that Iron Ore No.2 pellets have high activation energy.

The process line of concentrating iron ore materials is considered as a sequence of connected concentration units, some of which partially return ore materials to the previous unit. The output product of the final concentration unit in the process line is the end product of the whole line. Characteristics of ore, such as distribution of ore particles by size and distribution of iron content by size classes, are considered. Processing of iron ore materials by process units (a cycle, a scheme) is characterised by a separation characteristic – namely the function of extracting elementary fractions depending on physical properties of ore particles. The results of fraction analysis of ore samples in different points of the process line provide an experimental definition of separation characteristics and numerical values of the Rosin–Rammler equation factors. To identify dependencies that cannot be analytically described, the hybrid approach accompanied by the Takagi–Sugeno fuzzy models, in accompaniment with triangular membership functions determining fuzzy sets in preconditions, are used. To identify fuzzy sets in rule preconditions, triangular membership functions are used. Introduction of a-priori data on iron ore concentration as constraints for model parameters is a promising trend of further research, since it enables increased accuracy of identification despite limited availability of experimental data.

The micro-sintering method was used to determine the sintering basic characteristics of iron ore with Zn contents from 0 to 4%, the influence mechanism of Zn on sintering basic characteristics of iron ore was clarified by means of thermodynamic analysis and first-principles calculations. The results showed that (1) increasing the ZnO and ZnFe2O4 content increased the lowest assimilation temperature (LAT) but decreased the index of liquid phase fluidity (ILF) of iron ore. The addition of ZnS had no obvious effect on LAT but increased the LIF of iron ore. (2) ZnO and ZnFe2O4 reacted with Fe2O3 and CaO, respectively, during sintering, which inhibited the formation of silico-ferrite of calcium and aluminum (SFCA). The addition of ZnS accelerated the decomposition of Fe2O3 in the N2 atmosphere; however, the high decomposition temperature limited the oxidation of ZnS, so the presence of ZnS had a slight inhibitory effect on the formation of SFCA. (3) The Zn concentrated in hematite or silicate and less distributed in SFCA and magnetite in the form of solid solution; meanwhile, the microhardness of the mineral phase decreased with the increase in Zn-containing solid solution content. As the adsorption of Zn on the SFCA crystal surface was more stable, the microhardness of SFCA decreased more. The decrease in microhardness and content of the SFCA bonding phase resulted in a decrease in the compressive strength of the sinter.

Low Temperature Reduction Degradation Characteristics of Sinter, Pellet and Lump Ore

In order to solve the rapid decision of ore blending scheme in iron ore sintering process, the prediction model of the basic sintering characteristics of mixed iron ore and sinter quality has been established by three algorithms including the support vector machines, BP neural network and general regression neural network. The results show, the model based on support vector machine algorithm is better, which can accurately predict the basic sintering characteristics and sinter quality indexes; the accuracy of prediction for assimilation temperature, liquid fluidity and the binding phase strength are 90 % , 93% and 91 % respectively, based on the physical and chemical properties of raw material, and the accuracy of prediction for the drum strength and productivity are 89% and 88%, based on the basic sintering characteristics of mixed iron ore and technical parameters.