Search Documents

By Xuebin Liu, Yi Shang, Can Zhou, Hongqiu Zhu, Junbo Du

In the neutral leaching process of zinc hydrometallurgy, the pH value directly affects the leaching rate of zinc calcine. However, due to the complex mechanism of the leaching process and frequent fluctuation of working conditions, it is difficult to control the pH value by manual control. Therefore, this study proposes a fuzzy control method based on rule extraction under multiple working conditions, and analyzes the pH control performance. Firstly, the different operating states are classified according to process mechanisms and the Pearson method. Secondly, under the framework of the active learning algorithm, the approximate linear dependence (ALD) method is introduced to iteratively select samples with rule information in the original sample set for manual annotation. Then, the support vector machine (SVM) method is used to extract fuzzy control rules in different working conditions. Finally, a fuzzy rule set is established according to the samples mapped by the support vector. The simulation results based on industrial data show that the proposed method has better control performance than conventional fuzzy control and proportional–integral–derivative (PID) control.

Apr 1, 2024

By Ricardo Oliveira Gallart de Menezes, Claudio Gerheim Porto, Reiner Neumann

The Jiboia heavy mineral sands deposit is a new discovery associated with the São Francisco River delta on the northern coast of Sergipe state. The identified resources are part of the much larger mineralized trend. Mineralization is hosted in paleodunes deposited on Holocene marine terraces (Fig. 1). The dunes are up to 30 m above sea level, and mineralization occur from 6 m above sea level upward. The main ore minerals constitute pseudorutile, ilmenite, zircon, rutile and monazite. This work presents a thorough characterization of the mineralogy and granulometric distribution of the Jiboia orebody.

Apr 1, 2024

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs), as a pivotal part of any surface mining operation, need to evolve from conventional to intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, previously published research works on intelligent FMSs are explored to track the latest status of these third-generation frameworks within the surface mining context. Their underlying models are then compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present work then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Apr 1, 2024

By R. J. Quevedo, Y. A. Sari, S. D. McKinnon

The large scale of cave mines leads to many challenges, including operational logistics and geomechanics design. In current practice, pillar stability assessment relies almost exclusively on stress analysis. However, stability is also affected by other factors including those related to operational aspects of the mining method, the effects of which are difficult to account for during the design stages. In this paper we present a case study of the application of a machine learning approach to evaluate the influence of these operational factors on pillar stability at the Chuquicamata underground cave mine in northern Chile. Due to the likely multi-factorial damage process leading to collapses and considering the different pillar conditions, a tree-based machine learning method was used and analysed to improve the understanding of the relative importance of the various contributing factors. Unlike stress analysis methods, it does not require any a priori knowledge of failure mechanisms, nor the calibration of associated controlling parameters. The proposed random forest model predicted pillar collapses with 80% accuracy despite limited samples to model from. The main contributing factors to collapses were found to be related to available pillar volume, cave front geometry, and time under abutment stress conditions. The effects and interactions of such factors were also studied, showing that careful and improved control over operational conditions can significantly reduce the likelihood of pillar collapses. These conclusions could not have been obtained from stress analysis alone, illustrating the complementary nature of conventional stress analysis and machine learning approaches.

Mar 14, 2024

By J. P. Gouvea

Back-analysis of two mining-induced tremors in 2011 was used to determine a modelling criterion for the entire Klerksdorp Goldfield (i.e., Vaal Reefs region). At that time, most mining operations in the region were owned by AngloGold Ashanti (AGA) and shared many geotechnical similarities. By 2018 AGA had sold off all its Klerksdorp operations to different mining companies, which continued applying the 2011 modelling criterion. As mining activities became more remote, scattered, and isolated, the extraction of isolated blocks of ground and remnants became increasingly necessary. However, the inherited criterion allowed only minimal or no mining activities at these areas. Keeping in mind that safety is the overriding consideration, an innovative numerical modelling approach, which includes the application of peak particle velocity designs, was developed to provide practitioners in the Klerksdorp Goldfield with a suitable criterion to justifiably and safely mine isolated blocks of ground and remnants. This would not always be possible if a conformist approach was used.

Mar 14, 2024

By W. Bendaikha, S. Larbi, A. Ramdane

An oolitic iron ore from Gara Djebilet, Algeria was characterized by X-ray diffraction, scanning electron microscopy, and energy dispersive spectrosopy and the phosphorus distribution between various phases studied. Two ore types were identified – a haematite-dominated, oolitic type and a more massive, magnetite-dominated type. The haematite-dominated ore had a higher phosphorus content, up to 0.6% in the iron oxide minerals, than the magnetite-dominated type (0.3% P). Owing to the very fine-grained texture of the gangue minerals, reducing the phosphorus content to levels suitable for steelmaking (below 0.05% P) by conventiobal means would entail an energyintensive process with a high carbon footprint. Preliminary leaching test work using a sulphurous geothermal water as lixiviant, assisted by solar thermal acceleration, gave very promising results, removing 0.13% of the residual P (or 21.7% removal of total P) from the high-phosphorus oolitic ore.

Mar 14, 2024

By S. Swanepoel, A. V. Cherkaev, Q. G. Reynolds, M. Erwee

Ferrochrome (FeCr) is a vital ingredient in stainless steel production and is commonly produced by smelting chromite ores in submerged arc furnaces. Silicon (Si) is a componrnt of the FeCr alloy from the smelting process. Being both a contaminant and an indicator of the state of the process, its content needs to be kept within a narrow range. The complex chemistry of the smelting process and interactions between various factors make Si prediction by fundamental models infeasible. A data-driven approach offers an alternative by formulating the model based on historical data. This paper presents a systematic development of a data-driven model for predicting Si content. The model includes dimensionality reduction, regularized linear regression, and a boosting method to reduce the variability of the linear model residuals. It shows a good performance on testing data (R2 = 0.63). The most significant predictors, as determined by linear model analysis and permutation testing, are previous Si content, carbon and titanium in the alloy, calcium oxide in the slag, resistance between electrodes, and electrode slips. Further analysis using thermodynamic data and models, links these predictors to electrode control and slag chemistry. This analysis lays the foundation for implementing Si content control on a ferrochrome smelter.

Mar 14, 2024

By I. Ince, S. Kahraman, M. Rostami, B. Dibavar

The density, porosity, and strength of rocks are fundamental in the design of geo-engineering projects. Determining these properties requires the preparation of smooth core samples, which is usually impossible for soft rocks. Besides, only fragmented samples may be available in some projects. A method for predicting rock properties from rock particles such as drilling debris would therefore be useful. This study was undertaken to develop prediction equations for compressive strength (UCS), tensile strength (BTS), density, and porosity values from the crushability index (CI) obtained from rock fragments. The results showed that UCS, BTS, density, and porosity were strongly correlated with the CI. The physical characteristics and strength of rocks may be predicted with the help of the derived equations. The CI test is a valuable tool for estimating rock properties in drilling projects and in situations where core specimens are not available.

Mar 14, 2024

By Kasimcan Koruk, Julian M. Ortiz

A geological model accounting for uncertainties possesses important advantages for resource estimation. Machine learning algorithms (MLAs) employed on multivariate geochemical datasets open up ways to new methodologies for such geological models with ease in comparison to traditional geostatistical methods. This article proposes a two-step MLA with an ensemble implementation to define geological domains and their uncertainties based on geochemical data. The proposed workflow is applied hierarchically on a dataset from a porphyry copper deposit to perform binary classification that can be attributed to alteration domains.

Mar 1, 2024

By M. C. Bekker, T. Govindasamy

The potential benefits of implementing the Last Planner System (LPS) on mining infrastructure projects were explored through two case studies in the South African mining industry. The first part of the study involved measurement of the impact of LPS through earned value techniques on secondary project data. The second part sought to establish the lean construction success factors leading to improvements in construction performance. This was done by means of a research questionnaire distributed to the project owner’s teams, contracted parties, and the LPS facilitators. The results revealed a positive correlation between LPS application and planned percentage complete. However, the performance achieved during the LPS pilot was not sustained. The success factors and benefits considered most evident in the case study pilot differed among the three stakeholder groups. The findings are expected to guide construction stakeholders to better define performance measures and focus on factors required to make LPS implementation more effective in the South African mining sector.

Feb 12, 2024

By S. W. Robertson, M. T. Golela, S. Mxinwa

South Africa has one of the largest Cr-related industries in the world and generates large amounts of Cr-containing smelter dusts. It is normal practice to scrub Cr from the furnace off-gas in water, and to recover the Cr by adsorption, followed by recycling of the loaded adsorbent into the furnace. A study was conducted to find a low-cost adsorbent that is capable of removing sufficient Cr from the solutions generated by scrubbing. The test work focused on the evaluation of different clay minerals (attapulgite, bentonite, and kaolinite) as adsorbents for Cr. Cr(VI) could only be adsorbed after prereduction with e.g. ascorbic acid (ASA). An 80% removal of Cr(VI) could be achieved from a solution containing 20 mg/L Cr using bentonite clay after reduction with ASA. Attapulgite and kaolinite adsorbed less than 55% Cr after reduction with ASA. Both ASA and ferrous salts were found to be suitable reducing agents. The use of acid mine drainage (AMD) was also investigated as a low-cost alternative reducing agent, as AMD usually contains iron. The Cr(VI) reduction potential of the AMD was determined by redox titration against a solution containing 50 mg/L Cr(VI). Studies show that AMD can potentially be used as a reducing agent in a Cr removal process if it is available on site.

Feb 12, 2024

By N. V. Moraka

Calls for transformation in the mining sector are legislated. Whilst the composition of boards in terms of gender diversity and equal representation has improved, little is known on how women directors experience boardrooms. This research investigated the experiences of South African women in male-dominated mining boards. It questions why women remain marginalised in boardrooms, even when they are qualified as the men in their respective fields. The experiences of South African women on male-dominated mining boards were investigated by means of a multiple case study using a qualitative research methodology. Interviews were conducted with 16 women and 12 men serving across six JSE-listed South African mining companies. The findings show that irrespective of their qualification and experience, women,s, contributions are often ignored, and they are assigned to more social roles. Regardless of race, all women experienced gender stereotyping. Strategies are required to ensure that board cultures embrace female talent, where women can effectively contribute to decision-making and maximize their talent. It is argued that gender and identity should be studied in relation to post-colonial history in African countries. Women have multiple, varying identities, and their experiences require a unique investigation that would enable strategies to overcome barriers, through the implementation of an appropriate diversity management programme.

Feb 12, 2024

By J. P. Gouvea, T. R. Stacey

A research project was carried out on a gold mine in the Vaal River region of South Africa (Witwatersrand Basin) to evaluate the effect of two particular aspects of rockbolt installation – the angle of inclination of the bolt relative to the orientation of the rock surface, and the protruding length of the bolt – on the mine’s gully support system. A keyblock analysis approach indicated that these factors do not have an adverse impact on the stability of the strike gullies. This was confirmed by extensive empirical data collected from the case study mine. While safety is the primary concern, cost saving opportunities can be realized through reconsidering historically inherited support standards that are perceived to be correct and appropriate. The research described in this paper sets forth a practical approach, that is easy to implement and repeatable, to evaluate the role of rockbolts in stoping gullies.

Feb 12, 2024

By B. P. von der Heyden, T. Blenkinsop, A. Mamuse

Zimbabwe hosts a varied array of coloured gemstones. With the exception of emerald deposits and several world-class pegmatites, few of the gemstone occurrences have received detailed attention from the scientific or mineral exploration communities. In the present contribution we summarize the status of knowledge of the gemstone deposits and occurrences in Zimbabwe, paying particular attention to the geological settings in which they were formed. Synthesis of this regional geological approach reveals that there may be significant exploration potential for further gemstone occurrences, particularly in the extensive pegmatite fields and in Al-enriched orogenic belts that have undergone greenschist to granulite facies metamorphism. Further socio-economic and developmental initiatives will aid in optimizing the value generation from this important sub-sector.

Feb 12, 2024

By Min Chen, Qinghua Liang, Weishan Yan, Yuan Feng, Shigang Wang

Various coal mine robots (CMRs) and unmanned aerial vehicles (UAVs) are implemented to explore unknown mines for improving the safety and efficiency of mining. It is challenging for CMRs and UAVs to achieve accurate positioning due to the absence of the Global Positioning System (GPS), poor lighting conditions, and similar geometric features in complex mine scenes. LiDAR-based localization and mapping methods are more accurate than others, while long-time running in large-scale scenarios will introduce nonnegligible cumulative errors. This study presents a semantic-aided Li- DAR simultaneous localization and mapping (SLAM) with loop closure, which leverages the uniqueness of mine intersection structure to establish stable semantic loop closure. Specifically, we propose a semantic intersection descriptor of translation and rotation invariance, which encodes 3D point clouds of the same intersection from different positions and viewpoints into a unified image. By using the semantic descriptor, we can construct a constant loop constraint when the same intersection is revisited from different directions to reduce cumulative drift. We provide experimental validation using large data sets collected in two large underground mines, namely, a simulated Edgar mine deployed in ROS Gazebo and a public underground mine data set provided by ETH. Experimental results show that the proposed method has higher localization accuracy and outperforms the existing LiDAR-based SLAM strategies.

Feb 1, 2024

By Jaeheon Lee, Junmo Ahn, Jae-Yeon Kim, Yoo-Jin Kim, Jiajia Wu, Eun-Woo Kim, Jai-Won Byeon, Jun-Jae Lee

The surge in demand for battery materials, coupled with environmental challenges linked to battery disposal, underscores the need to recycle spent lithium-ion batteries (LIBs). Green recycling approaches, in particular, have garnered attention for battery recycling. In this study, a hydrometallurgical method using a synergetic organic lixiviant combining methanesulfonic acid (MSA) and citric acid (CA) as an alternative to inorganic mineral acids was introduced as a green approach to recycle cathode materials of LIBs. The conditions for leaching and recovery processes were optimized. Cathode materials were regenerated using the recovered materials. Moreover, the leaching performance and economic feasibility of this leaching system were compared with those of various other organic acids.

Feb 1, 2024

By S. J. Schatzel, K. M. Ajayi, E. N. Rubinstein, Z. Khademian

This study simulates the impact of a shale gas well casing breach near a longwall mine. Field studies are conducted to measure mining-induced permeability changes over the abutment pillar of a longwall mine, and a geomechanical model is developed in 3DEC, a three-dimensional numerical modeling code, to predict the aperture of fractures in the overburden at the study site. The predicted aperture values are used to determine mining-induced permeabilities, and the results are compared with the field measurements. These aperture values are provided as inputs into fracture flow code (FFC), which generates a stochastic discrete fracture network (DFN) model for the study site and predicts the potential shale gas flow to the mine. Results from 100 DFN realizations are statistically analyzed using the bootstrapping method to compensate for notable variation in fracture geometry. The results show a significant difference between the gas inflow for nearby panels due to increase in the induced permeability during mining of the second panel. The average gas flow to the mine was calculated as 4.72 × 10 m3/s (49 cfm) for a hypothetical breach at the Sewickley horizon during the first panel mining, 8.97 × 10 m3/s (19 cfm) for a hypothetical breach at the Uniontown horizon during the first panel mining, 2.16 × 10 m3/s (458 cfm) for a hypothetical breach at the Sewickley horizon during the second panel mining, and 8.07 × 10 m3/s (171 cfm) for a hypothetical breach at the Uniontown horizon during the second panel mining. Depending on the mine ventilation system, this could result in methane concentrations exceeding regulatory limits. Hence, these findings provide insights into the potential risk of an unconventional gas well casing breach near a longwall mine under shallow cover.

Feb 1, 2024

By MAURICE SUNKPAL, Taghi Sherizadeh, Kutay E. Karadeniz, Dogukan Guner, Samuel Nowak

In this study, various rib bolting scenarios were investigated to better understand the effectiveness of the support systems. A coal mass constitutive model is implemented to a distinct element method (DEM) code, and rib factor-of-safety (RibFOS) analyses were performed by applying strength reduction for the coal matrix and explicitly modeled face cleats. Ribs with various overburden depths and mining heights composed of solid banded bright coal were considered. Different scenarios such as rib bolt length and number of bolts were studied to quantify the effect of primary rib support density on rib stability. As a result of the unsupported coal rib analyses, a decaying exponential relationship is proposed between the mining height-overburden depth and the RibFOS. The developed coal rib models clearly show the coal-rib bolt interaction and illustrate how the addition of rib bolts restricts the movement of the coal rib. The results reveal that the strength-reduction method in DEM code with the coal-mass model can aid in the development of practical primary sup- port charts, which can help in the rib support design process.

Feb 1, 2024

By Connor Meinke, Shaihroz Khan, Kevin Erwin, Rajiv Chandramohan, Muhammad Usman Siddiqui

High-quality sample selection for metallurgical test work is essential to a geometallurgy study, but the large multidimensional dataset makes sample selection a daunting task, as classifying the dataset while respecting its heterogeneity is difficult. This paper presents a streamlined approach for sample selection, utilizing custom-built tools in Python to standardize the methodology, saving time and costs. This approach uses the cumulative sum method, principal component analysis, and k-means clustering method to elegantly cluster the data and select representative samples. A case study is used to demonstrate the effectiveness of the methodology by selecting 40 samples for flotation test work.

Feb 1, 2024

By M. Portal, L. Goicochea

This study is carried out in the Zenit mining concession, which is located in the city of San Pablo in the department of Cajamarca in Peru. The Project has 33 mineralized structures and according to laboratory analyzes we have the presence of gold and silver. The geostatistical evaluation provides an analysis on the distribution of precious metals in the vein. This information is used to improve the efficiency of metal extraction and to reduce costs. The general objective is to evaluate the polymetallic veins (Au and Ag), for which the classification of resources (measured, indicated, and inferred) has been carried out, taking into account the parameters of minimum distance from the composite, corresponding volume and tonnage calculation. In addition, an inventory of estimated geological resources was carried out with the block grades obtained to generate the tonnage-grade curves.

Feb 1, 2024