Ore Quality Research Articles

Mineralogy and geochemical characteristics of the Ibaga copper ore deposit in Singida-Tanzania: Implication for source of copper mineralization and ore quality

The Ibaga copper deposit in the Nzega-Sekenke terrane is hosted in meta-sedimentary rocks and it has been rudimentarily mined by small scale miners for more than a decade. To study mineralogy and geochemical characteristics of the deposit, samples from outcrops and mining pit were collected for XRD, XRF and ICP-MS analysis. Results show that the ore is composed of chalcopyrite, covellite, cuprite, malachite and azurite as ore minerals; whereas augite, chlorite, actinolite, greenalite, birnessite, quartz, magnetite, berlinite, cristobalite, hematite, calcite and parisite are gangue minerals. The deposit is characterized by Cu (3.2–31.3 wt %), Fe (2.1–25.1 wt %), Ag (0.6–16.6 wt %) and lower concentration of penalized impurities Sb, Bi, As, Cd and (Al2O3 + MgO) than threshold limit set by copper smelters and refineries. The ore shows significant variation of Y/Ho = 21.75–40.00, Zr/Hf = 23.33–58.61 and Nb/Ta = 4.20–27.17. Presence of higher REE values of up to 2000 ppm in sample BG04 due to REE minerals known as parisite indicates that the deposit is potential prospect for REE. Consistent with the granites, the ore has Sm/Nd < 0.24 and enriched in LREE relative to HREE where ∑LREE/∑HREE = 4.7–9.0 and La/Lu = 32–769.3. The scatter plot of δCe versus δEu for ore and rock samples suggests closer genetic relationship between the ore, granite and quartz-sericite-schist. These results imply that the granitic intrusion triggered mineralization by skarnification into meta-sedimentary rocks and subsequently the ore underwent supergene enrichment.

Calcined colemanite as an additive for iron ore sintering process

During sintering process, iron ores, fluxes and coke are agglomerated into a desirable blast furnace feed. The degrading iron ore quality and environmental norms has forced sinter producers to look for additives which can improve the sintering process efficiency. For the current work, use of calcined colemanite as an additive was studied by adding it from 0% to 4% within the sinter raw blend through lab-scale pot trials. During the sintering process, calcined colemanite forms a Calcium Borosilicate (Ca11B2Si4O22) phase at temperature above 400 °C which latter gets dissociated within the liquid melt thus increasing the liquid slag formation. Increasing calcined colemanite up to 2% increases tumbler index from 56.27% to 61.67%, decreasing thereafter to 55.33% at 4% of calcined colemanite. The sinter yield (+5 mm) is also found to be maximum of 89.39% at 2% of calcined colemanite. An increase in calcined colemanite from 0% to 4% increases sintering time from 20 to 26 min, decreasing the overall sinter productivity from 2.35 to 1.99 t/m2/h. Before integrating calcined colemanite within the sintering process at plant scale, its cost and efficacy must be considered. An alternate approach can be combining it with an organic binder where the two can complement each other in providing the required sinter properties.

Modeling, parameter estimation and optimization of fluidized bed-based alternative ironmaking process for CO2 emission reduction

This study presents the development of a comprehensive process model for simulating and optimizing the FINEX process consists of the multi-stage fluidized beds, the melter-gasifier unit, and a gas recycling system. The model is developed using Pyomo, a Python-based open-source software package that provides extensive capabilities for formulating, solving, and analyzing optimization models. It incorporates heat and mass balance equations and captures a wide range of chemical reactions, including the reduction of iron ore by hydrogen and carbon monoxide, the calcination of carbonate materials, the water–gas shift reaction, and coal gasification and combustion. Unknown parameters in the model, such as heat loss in each reactor, the extent of the calcination reaction, and the outlet gas temperature from the melter-gasifier, were estimated to calibrate the model. These parameters were estimated by solving an optimization problem that minimizes the gap between the model and real plant data. The optimized model was employed to investigate various scenarios for minimizing CO2 emissions in the FINEX process. This included assessing the impact of HBI charging rates, iron ore quality, and the integration of a CCUS unit. For each scenario, an optimization problem was formulated to minimize production costs across a range of CO2 tax levels. The optimal solutions revealed the relationships between process economics and CO2 emissions for each variable.

Economics of Electrowinning Iron from Ore for Green Steel Production

The transition to green steel production is pivotal for reducing global carbon emissions. This study presents a comprehensive techno-economic analysis of various green steel production methods, including hydrogen reduction and three different electrolysis techniques: aqueous hydroxide electrolysis (AHE), molten salt electrolysis, and molten oxide electrolysis (MOE). By comparing process flow diagrams, capital and operational expenditures, specific energy consumption, and production footprint, this work provides a high-level assessment of the economic viability of these processes as they mature. The analysis reveals that MOE, despite its ongoing development, offers a promising route for iron production given its ability to process a wide range of ore qualities and the potential to sell electrolyte as a cement product. However, the best balance between deployment ready technology and economic benefit is AHE. Operational challenges are also discussed, such as electrolyte loss and slag handling. We suggest that the sale of by-products like oxygen may not significantly impact the economics due to market saturation. The findings underscore the importance of continued research and development in process optimization to realize the full potential of green steel technologies. All the calculations have been released as supplementary electronic material (MS Excel workbook). The format has been inspired by the techno-economic assessment template (TECHTEST) distributed by the US Dept. of Energy.Graphical

Геолого-геофизическое опробование железных руд гамма-альбедным методом

The standard method of testing iron ores, due to its high labor intensity and low representativeness, cannot serve as a basis for controlling the quality of ores in the process of their extraction and processing. The proposed spectrometric modification of the gamma-albedo method makes it possible to exclude labor-intensive operations for grinding ores, preparing analytical samples (~0.1 mm) and directly chemical analysis for iron. Studies of the spectral distribution of the scattered gamma radiation of the radioisotope source Se-75 (~220 keV) on ores with different iron content revealed critical energies and zones of their displacement depending on the quality of the ore and the energy of the scattered gamma radiation. The found critical energies in the spectral distribution of the albedo of gamma radiation made it possible to choose the optimal energy intervals in the hard (above the critical energy) and soft (below the critical energy) regions of the spectrum in terms of the maximum contrast ratio Ψ of the scattered gamma radiation intensities measured in the selected energy intervals, with a change in the concentration of iron. In the process of testing the proposed modification of the method for monitoring the iron content in partially prepared samples weighing ~ 60 kg, with a particle size of 40 mm, a root-mean-square error of 1.32% abs was achieved.

Evaluating the Chemical Composition and Quality of Magnesite Ore in the Sró Area, Gia Lai Province, Vietnam

Evaluating the Chemical Composition and Quality of Magnesite Ore in the Sró Area, Gia Lai Province, Vietnam

Модернизация технологий месторождений оловянных руд с учетом ретроспективной оценки опыта восстановления потенциала предприятий

The article describes the experience of restoring the potential of enterprises in the tin industry of the Khabarovsk Territory and the Chukotka Autonomous Okrug in difficult mining and geological conditions. The purpose of the study is a retrospective assessment of the experience of improving the technology of mining tin ores in stable rocks. Materials and methods. The goal is achieved through comprehensive research, including analysis and synthesis, comparison of calculated and experimental data, calculations of mass control parameters and measures to improve the quality of ores. Results. The characteristics of the deposits and the features of their location and ore extraction are given. The parameters of the applied development systems with differentiation into variants are detailed. A scheme of options is given with a critical analysis of their advantages and disadvantages so that they can be reproduced in similar conditions. Discussion. The effectiveness of the integration of ore mining processes and equipment for their implementation is shown. The experience of using an arsenal of systems for the development of shallow and inclined deposits in stable host rocks is described. The experimentally obtained dependences of the size of the pillars on the fall of the ore body and the spans of the mine are given. The variants of a promising chamber development system with the delivery of ore by the force of an explosion are detailed. Conclusion. It is shown that the development of tin deposits with the integration of the capabilities of technological processes and equipment ensures effective development of the field while improving the safety of mining operations and extraction of minerals from the subsurface. Resume. It is concluded that the integration of mining processes and equipment for their implementation is a reserve for the implementation of the production program, and the experience of developing tin deposits can be in demand when modernizing existing technologies and designing new deposits of solid minerals. Suggestions for practical applications and directions for future research. Future research will be aimed at addressing issues related to reducing ore losses and dilution, improving the rock pressure management system and increasing the environmental and economic efficiency of the enterprise.

An Arsenic Removal Technology and Its Application in Arsenic-Containing Copper

The usage of copper (Cu) ores containing low or no arsenic (As) has reduced, and Cu ores containing high levels of As have emerged as vital mineral resources for Cu extraction and processing. The quality of the Cu ores has decreased from 1.6% to approximately 1.0%. The proportion of As to Cu in 15% of Cu resources currently reaches 1:5. However, during the extraction and processing of Cu ores, As presents significant environmental harm. Hence, safely and effectively removing As is paramount in Cu smelting and processing, holding substantial importance in fostering environmentally sustainable practices within the Cu extraction and processing industry. This article consolidates the resource distribution of As-containing Cu (ACC) ores, comprehensively and systematically evaluates the present advancements in extracting techniques for these minerals, and identifies the challenges inherent in pyrometallurgical and wet processes for treating ACC deposits. Pyrometallurgy is a simple primary roasting technique and has widespread applicability in the treatment of various ACC minerals. Its disadvantages are the emission of exhaust gas and the high treatment costs associated with it. The wet arsenic removal method boasts advantages including minimal air pollution and a high resource recovery rate, significantly aiding in Cu concentrate recovery; its major drawback is the production of As-containing wastewater. The hydrometallurgical removal of As from ACC mines involves extracting As through leaching. Recently, biometallurgy has presented innovative solutions using specialized microorganisms to bioleach or bioabsorb As, but large-scale industrial applications still lack specific practical implementation. This review explores the underlying causes of the challenges encountered in processing ACC minerals. Additionally, it highlights pyrometallurgical roasting coupled with high-temperature filtration as a pivotal advancement in the extraction and processing of ACC ores.

Strategic planning of open pit mining operations using the Micromine Beyond Optimiser

Modern software products allow to determine the quantity and quality of ore at any point of the deposit and, accordingly, to identify the optimal pit shell using specialized algorithms. Such algorithms make it possible to create the final open pit shell even with a broken bottom for several neighboring ore bodies. Currently, optimization solutions in the mining industry require the determination of the maximum present value of profit or the minimum stated costs. It allows to make strategic planning decisions. Strategic planning of open-pit mining operations in the development of mineral deposits in Ukraine can be implemented using the Micromine Beyond Pit Optimizer. The authors considered the parameters that affect the boundaries of the pit field and the optimization criteria.

Techno-Eco-Efficiency Assessment of Using Recycled Steel Fibre in Concrete

The steel industry is one the three biggest producers of carbon dioxide and it is experiencing technical challenges due to the gradual decrease in the quality of iron ore. Steel is extensively used in the construction industry for structural applications like steel components, while steel fibres are intensively used as additives to concrete in order to improve its performance. It is thus important to consider the use of recycled steel as a replacement for virgin steel in order to address the aforementioned environmental consequences. This paper applies the eco-efficiency framework to determine the economic and environmental implications of the use of recycled fibre in concrete as a replacement for virgin steel. A number of concrete mixes were considered that used virgin, recycled, and treated recycled rebar in concrete. The eco-efficiency framework, which uses a life-cycle assessment approach to calculate the environmental and economic values of concrete mixes in order to determine the portfolio positions of these concrete mixes, was used for comparison purposes and to establish the eco-efficient option(s). Whilst the recovery and recycling process is energy-intensive, the use of recycled steel fibre in reinforced concrete has been found to be eco-efficient and deliver the same level of mechanical performance compared to that obtained using virgin steel fibre. Treating steel fibre could improve its technical performance, but it was found to increase both costs and environmental impacts and was therefore identified as not being eco-efficient.

Does market quality benefit from internationalization? Evidence from Chinese commodity futures markets

Internationalization is the primary way to facilitate the high-quality development of Chinese commodity futures markets. Based on liquidity provision theory, we investigate the impacts of opening to foreign traders on the market quality of China’s 10 commodity futures using the synthetic control method. Specifically, we measure market quality based on activity, liquidity, and price efficiency using tick-by-tick data. We find that opening to foreign traders reduced (improved) the market quality of iron ore (purified terephthalic acid and rapeseed oil) futures significantly and had limited impacts on palm oil, soybean No. 1, soybean No. 2, soybean oil, soybean meal, rapeseed meal, and peanut kernel futures. The competition channel plays a dominant role in the influence mechanism, whereas the adverse selection channel does not play a significant role. We conclude that coke, ferrosilicon, stainless steel, and glass futures have the highest priority to be opened. Our findings have practical significance for implementing the internationalization of commodity futures in emerging countries.

Study on the High-Temperature Interaction between Coke and Iron Ores with Different Layer Thicknesses.

Coke plays a key role as the skeleton of the charge column in BF. The gas path formed by the coke layer in the BF has a decisive influence on gas permeability. At high temperatures, the interface between coke and ore undergoes a melting reaction of coke and a reduction reaction of ore. The better the reducibility of the ore, the more conducive it is to the coupling reaction of ore and coke. The melting loss reaction of coke becomes more intense, and the corresponding strength of coke will decrease, which will affect the permeability of the blast furnace and is not conducive to the smooth operation of the blast furnace. Especially with a deterioration in iron ore quality, BF operation faces severe challenges, which makes it necessary to find an effective way to strengthen BF operation. In this study, a melting-dropping furnace was used to develop and clarify the high-temperature interaction between coke and iron ores with different layer thicknesses. The influencing factors were studied by establishing a gas permeability mathematical model and observing the metallographic microscope images of samples after the coke solution loss reaction. The relationships between coke layer thickness, distribution of gas flow, and pressure drop were obtained. The results showed that, under certain conditions, the gas permeability property of a furnace burden has been improved after the coke layer thickness increased. Upon observing the size of coke particles at the interface reaction site, the degree of melting loss reaction can be determined. A smaller particle size indicates more melting loss reaction. A dripping eigenvalue for molten metal was introduced to evaluate the dynamic changes in the comprehensive dripping properties of molten metal of furnace burden, which showed that the dripping eigenvalue for the molten metal could deteriorate because of the unruly thickness and the coke layer thickness should be limited through considering the operational indicators of the blast furnace.

Simulation and control of ball mills under uncertainty conditions

The article considers a model for monitoring the grinding process in a ball mill, where the ground material itself is involved in grinding. The constructed model takes into account the uncertainties associated with the quality indicators of the processed ore at the beginning and in the process of grinding, the influence of the quality indicators of the ore in terms of particle size and their hardness on the kinetics of grinding. The non-linearity of the technological process and uncertainties are taken into account in the control system aimed at stabilizing the system. The model is presented in the form of four blocks describing the main links of the mill plant. At the output of the model, the participation of the mill, the volume of the sump are determined, and the particle size at the outlet of the hydrocyclone is estimated. The operation of the hydrocyclone control system is demonstrated, which controls the loading density and particle size depending on the change in ore quality.

Reduction characteristics of cold-agglomerated pellets in blast furnace conditions

There is a significant and necessary drive towards reducing CO2 emissions produced by iron and steelmaking industries. Binding Solutions Ltd has developed a technology to contribute to the reduction of CO2 in the short and long term, by introducing a cold-bonded iron ore pellet to the furnace burden. Binding Solutions’ cold-agglomerated pellets, manufactured from magnetite and hematite iron ore, were tested in accordance with ISO standard tests alongside a standard market pellet. ISO standards were developed to assess the quality of lump ore, sinter and hot-bonded or alternatively known as indurated pellets, and there can be anomalies when testing cold-agglomerated pellets by the same methods. Additional test methodology, outside the scope of international standards may be utilised to give a fuller picture of pellet characteristics. The HOSIM test method was used to assess the properties of cold-bonded pellets of different minerologies. Results found that the time needed to reach a set point of reduction for a cold-agglomerated pellet is shorter than for an indurated control pellet. The data also showed that for the same iron ore source, alternate cold agglomeration methods can have a significant impact on the balance of pellet properties.

ЕКОНОМІКО-МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ДИНАМІКИ ЕНЕРГОСПОЖИВАННЯ ЗБАГАЧУВАЛЬНОЇ ФАБРИКИ

The purpose of the work is to establish the dependence of electricity costs on the dynamics of energy consumption from the dynamics of ore supply to the beneficiation plant bunker, namely from the loading period and its duration, and to develop, on the basis of the identified patterns of organizational, technical and economic measures to reduce the energy component of the cost of production of iron ore concentrate at the mining enrichment enterprises. Economic-mathematical methods were used to develop models of the formation of electricity costs on the dynamics of energy consumption, namely: the theory of impulse processes for the development of a model of ore supply to the bunker of the beneficiation factory; operational calculation methods, ore beneficiation theory and power supply theory for the development of a dynamic beneficiation process line model and power consumption model; methods of spectral analysis to identify the dynamic component of active power and electrical energy consumed by the ore beneficiation process; Cost analysis methods were used to calculate electricity costs; economic-mathematical modeling of energy consumption dynamics was performed by computer modeling using the Mathcad software package. An economic-mathematical model of the energy consumption dynamics of the enrichment factory was developed. The regularities of influence of ore loading parameters of beneficiation factory bunkers on the dynamics of the formation of electricity costs during the production of iron ore concentrate have been revealed. Mathematical dependencies of costs for the dynamic component of electrical energy on the time parameters of the process of loading ore into the hopper of the beneficiation factory, namely on the period and time of loading, were obtained. Organizational and economic measures have been developed to load the bunkers of the beneficiation factory, which ensure the saving of electricity. The regularities of influence of ore loading parameters of beneficiation factory bunkers on the dynamics of the formation of electricity costs during the production of iron ore concentrate have been revealed. The principles of building a system of financial incentives for operational and dispatching personnel for saving electricity based on the results of economic and mathematical modeling have been developed. For the first time, it wa s established that the energy component of the production cost of iron ore concentrate depends not only on the quantity and quality of ore, but also on the dynamic parameters of the process of loading ore into the bunkers of the beneficiation factory, while this established dependence has a non-linear nature on the period and time of loading. The proposed measures to save electricity due to the implementation of rational modes of loading bunkers of the beneficia-tion factory with ore can be used in the development of energy saving plans and programs and the development of job instructions for the dispatching staff of the ore beneficiation factory, which will allow to reduce the energy component of the production cost of iron ore concentrate. A system of financial incentives for operational dispatching staff of the beneficiation factory has been developed, which takes into account the saving of electrical energy due to the management of the ore loading of the bunkers of the beneficiation factory and the intensity of the staff’s work.

Challenges and effectiveness of IT tools used in mining for forecasting production parameters

The research examines the challenges and effectiveness of IT tools used in the mining industry for forecasting production parameters, a crucial aspect as mining operations become increasingly complex. Accurate forecasting is essential not only for optimizing efficiency, safety, and profitability but also for managing the high risks associated with the construction and operation of mining plants, which require long-term financial security and flexible production management. The study explores various IT solutions, such as advanced data analytics, machine learning algorithms, and simulation models, employed to predict key production parameters like ore quality, equipment performance, and resource availability. However, significant challenges, such as data quality issues, the integration of diverse data sources, and the need for specialized expertise, pose obstacles to the effective use of these tools. Despite these challenges, the research finds that IT tools can lead to more accurate forecasting, improved decision-making, and enhanced operational planning, provided that technical and organizational hurdles are addressed. The paper also highlights the importance of modern IT tools in mining production scheduling, demonstrating their advantages over older tools like MS Excel. By presenting examples from coal and copper ore deposits, the study shows that these modern tools not only increase the accuracy of production forecasts but also enable the creation of multiple scenarios and the rapid modification of schedules, which are key to maintaining the competitiveness and liquidity of mining companies.

Application of neural networks to predict the quality of iron ore concentrate based on flotation data

This paper presents a study aimed at developing and testing a neural network model for predicting the percentage of silica in iron ore concentrate obtained during flotation. The problem of precise control of the silica content is critical for the mining industry, since the quality of the final product and, accordingly, its market value depend on it. During the study, data was collected from the flotation plant, their preliminary processing was carried out, including standardization and elimination of missing values. The developed neural network model included two hidden layers and was trained on real data. The evaluation of the model quality showed high results, which was confirmed by the metrics of mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2). Additionally, an analysis of the visualizations of the residuals and predicted values confirmed the accuracy and stability of the model. The results of the study demonstrate that the proposed model can be effectively used in production conditions to improve process control and improve product quality in the mining industry.

BENEFICIATION OF FERRUGINOUS MANGANESE ORE OF UM BOGMA LOCALITY, SINAI: COMPARISON BETWEEN CONVENTIONAL REDUCTION ROASTING TECHNIQUES AND MICROWAVE TECHNOLOGY

The increasing demand for high-grade manganese ores in various industries has led to a growing necessity to enhance the quality of lower-grade manganese ores with time. A representative manganese ore was collected from Um Bogma, Sinai, Egypt, and subjected to various characterization methods including X-ray diffraction (XRD), X-ray fluorescence (XRF) and ore microscopy. XRF analysis revealed a low Mn/Fe ratio of 2.81 (as elements), indicating a low ore grade. For suitability in Mn alloy production at the Sinai Manganese Company (SMC) plant in Abu Zenimah, southeast of Sinai, Egypt, this ratio should ideally exceed 5. Additionally, XRD and ore microscopy identified the mineralogical composition of the ore as pyrolusite, hematite, and manganite, with manganese patches embedded in a ferruginous groundmass at the textural scale. Three different reduction roasting techniques were evaluated, involving conventional heating in a furnace utilizing either CO – CO2 or charcoal as reducing agents, alongside reduction roasting with charcoal utilizing microwave technology. Following each technique, magnetic separation was employed, resulting in the production of high-grade manganese concentrates exhibiting high Mn/Fe ratios ranging from 19.8 to 27.45 and substantial Mn recovery rates ranging from 93.86% to 96.76%.

BTPNet: A Probabilistic Spatial-Temporal Aware Network for Burn-Through Point Multistep Prediction in Sintering Process.

Burn-through point (BTP) is a very key factor in maintaining the normal operation of the sintering process, which guarantees the yield and quality of sinter ore. Due to the characteristics of time-varying and multivariable coupling in the actual sintering process, it is difficult for traditional soft-sensor models to extract spatial-temporal features and reduce multistep prediction error accumulation. To address these issues, in this study, we propose a probabilistic spatial-temporal aware network, called BTPNet, which is used to extract spatial-temporal feature for accurate BTP multistep prediction. The BTPNet model consists of two parts: an encoder network and a decoder network. In the encoder network, the multichannel temporal convolutional network (MTCN) is employed to extract the temporal features. Meanwhile, we also propose a novel architectural unit called variables interaction-aware module (VIAM) to extract the spatial features. In the decoder network, to reduce the accumulated errors of the last step prediction, a probabilistic estimation (PE) method is proposed to improve the performance of multistep prediction. Finally, the experimental results on a real sintering process demonstrate the proposed BTPNet model outperforms state-of-the-art multistep prediction models.

Modelling the probability of roof fall using digital tools

Information on rock mass characteristics, encompassing the overall quality of the rock masses and various geological parameters, is crucial in mining operations. This data guides the selection of mining techniques and the design of roof control methods to minimize the risk of flaking. However, the lithology of roof rocks is often so variable that predicting their behaviour, especially when disturbed by mining activities, is challenging. The study begins with a detailed review of existing literature on roof fall mechanisms and predictive modelling techniques. It was described the dataset used, which includes geological, environmental, and operational parameters collected from various mining sites. This article outlines a methodology for conducting detailed studies of the lithology of coal seam roof rocks in roadways and longwalls as mining progresses. According to the research, forecasting the extent of roof rock fall during the planning stage of mining operations can inform the implementation of appropriate countermeasures to minimize this phenomenon before exploitation begins, thereby significantly reducing ongoing mining costs. Block modelling and stratigraphic (mesh) modelling were employed to predict the volume of rockfall that could contaminate the ore in the analysed mining plot. In the future, this proposed methodology could be used to analyse the progression of roof falls, estimate the mass of falling roof rocks, and calibrate a system for continuous measurement of ore quality in mine workings.