Mining, Volume 3, Issue 2 (June 2023) – 13 articles

The greatest challenges for contemporary and future natural resource production are sociotechnical by nature, from public perceptions of mining to responsible mineral supply chains. The term sociotechnical signals that engineered systems have inherent social dimensions that require careful analysis. Sociotechnical thinking is a prerequisite for understanding and promoting social justice and sustainability through one’s professional practices. This article investigates whether and how two different projects enhanced sociotechnical learning in mining and petroleum engineering students. Assessment surveys suggest that most students ended the projects with greater appreciation for sociotechnical perspectives on the interconnection of engineering and corporate social responsibility (CSR). This suggests that undergraduate engineering education can be a generative place to prepare future professionals to see how engineering can promote social and environmental wellbeing. Comparing the different groups of students points to the power of authentic learning experiences with industry engineers and interdisciplinary teaching by faculty. Full article

Integrated Optimization can find optimized solutions for a project to define open pit and mine scheduling with greater reliability. This work aims to demonstrate how the insertion of geometallurgical variables can significantly change the financial return of a project. Two geometallurgical variables are considered in mine planning simulations. Specific energy corresponds to the energy consumed in the comminution of the ore, and process recovery measures the percentage of metal incorporated into the product. Three scenarios were developed considering an iron ore deposit. In the Base Case (BC) scenario, the recovery was fixed, and the specific energy of comminution was not considered. GeoMet1 considers the variable recovery varying for each block. GeoMet2 considered both recovery and specific energy as variables varying for each block. GeoMet1 and GeoMet2 presented Net Present Value (NPV), respectively, as 3.68% and 13.57% lower than the BC. This overestimation of the BC results can be viewed as an optimistic case of mine planning that is very common in the mining industry. These results show that the use of specific energy and recovery variables is fundamental to obtaining more reliable mine planning. Full article

In this research, data analytics and machine learning were used to identify the performance metrics of loaders and haul trucks during mining operations. We used real-time collected data from loaders and haul trucks operating in multiple quarries to broaden the scope of the study and remove bias. Our model indicates relationships between multiple variables and their impacts on production in an operation. Data analysis was also applied to ground engagement tools (GET) to identify key preventative maintenance schedules to minimize production impact from capital equipment downtime. Through analysis of the loader’s data, it was found there is an efficient cycle time of around 35 s to 40 s, which yielded a higher payload. The decision tree classifier algorithm created a model that was 87.99% accurate in estimating the performance of a loader based on a full analysis of the data. Based on the distribution of production variables across each type of loader performing in a similar work environment, the Caterpillar 992K and 990K were the highest-yielding machines. Production efficiency was compared before and after maintenance periods of ground engaging tools on loader buckets. With the use of maintenance and production records for these tools, it was concluded that there was no distinguishable change in average production and percentage change in production value before and after maintenance days. Full article

Mining-induced subsidence can have significant environmental and infrastructural impacts, making subsidence engineering a crucial consideration. However, the unique nature of salt caverns and the increasing demand for reliable subsidence prediction models in the context of energy storage require special attention. This study provides a comparative analysis of existing prediction models and highlights their advantages and disadvantages to determine the most appropriate approach. The study primarily focuses on theoretically developing an empirical influence function for asymmetrical subsidence prediction. It significantly contributes to the field by correcting and extending the existing method, providing a generalized solution applicable to any type of asymmetrical distribution around the cavern. Future research directions include implementing the proposed model in relation to real-world data. The insights gained from this study can help advance subsidence prediction models in the field of salt cavern energy storage, addressing a significant need in the industry. Full article

Blasting operations in open-pit mines generally have various management strategies relating to flyrock. There are empirical models for calculating the flyrock distance, but due to the complexity and uncertainty of rock properties and their interactions with blasting properties, there are still no models that can predict the flyrock distance that may be applicable across mining operations in general. In this regard, the Jajarm bauxite mine complex was used as a case study. The purpose of this study was to develop and evaluate different methods that can predict flyrock distance. For this purpose, soft computing models were developed using generalized regression neural network (GRNN), gene expression programming (GEP) and genetic-algorithm-based GRNN (GA-GRNN) methods. To obtain statistical models, multivariable regression was applied in the form of linear and nonlinear equations. A flyrock index was introduced using a classification system developed by incorporating fuzzy decision-making trial and evaluation methods (fuzzy DEMATEL). In order to achieve this goal, the data of 118 blasts in eight mines of the Jajarm bauxite complex were collected and used. Following this, four performance benchmarks were applied: the coefficient of determination (R²), variance accounted for (VAF), root-mean-square error (RMSE) and mean absolute percentage error (MAPE). The performance of the models was evaluated, and they were compared with each other as well as with the most common previous empirical models. The obtained results indicate that the GA-GRNN model has a higher performance in predicting the flyrock distance in actual cases compared to the other models. At first, data on factors that were the main cause of flyrock (and had a direct impact on it) were collected and classified from different blasts. Then, using the collected data, 19 different combinations were established, which can be used to provide the appropriate predictive equation. The purpose of this work is to more accurately predict flyrock and prevent heavy damage to buildings and mining machines across the mining complex. Full article

With the understanding that the mining industry is an important and necessary part of the production chain, we argue that the future of mining must be sustainable and responsible when responding to the increasing material demands of the current and next generations. In this paper, we illustrate how concepts, such as inclusiveness and the circular economy, can come together in new forms of mining—what we call inclusive urban mining—that could be beneficial for not only the mining industry, but for the environmental and social justice efforts as well. Based on case studies in the construction and demolition waste and WEEE (or e-waste) sectors in Colombia and Argentina, we demonstrate that inclusive urban mining could present an opportunity to benefit society across multiple echelons, including empowering vulnerable communities and decreasing environmental degradation associated with extractive mining and improper waste management. Then, recognizing that most engineering curricula in this field do not include urban mining, especially from a community-based perspective, we show examples of the integration of this form of mining in engineering education in first-, third- and fourth-year design courses. We conclude by providing recommendations on how to make inclusive urban mining visible and relevant to engineering education. Full article

This work aims to prepare and characterize the unburned carbon obtained from gasification residues and evaluate its application as an adsorbent for the removal of textile dye contaminants. The results of physical and chemical properties showed a specific mass of 2.05 g/cm³, surface area of 23.983 g/cm², and diameter and pore volume of 0.844 nm and 2.262 cm³/g, respectively. These properties, along with the point of zero charge and chemical bonds present on the surface, favored the adsorption of cationic dyes. The adsorption results showed great potential for the removal of methylene blue, crystal violet, and basic fuchsin if compared with bromocresol green, and indigo carmine. The maximum removal values obtained for methylene blue were up to 99% and the kinetic adsorption was faster at the beginning of the process, reaching the equilibrium in less than 5 min. The results obtained through the adsorption isotherms showed a maximum adsorption capacity of 333.33 and 476.19 mg/g, at the temperature of 291 and 328 K, respectively. The satisfactory results showed that the use of unburned carbon is a cost-effective and eco-friendly alternative to reusing the residue from gasification and also contributes to the decontamination of watercourses. Full article

Here, we present a numerical model for simulating the formation and evolution of the gas and dust cloud that forms after the detonation of high explosive charges in boreholes. This model provides a possible method for converting a substance ejected from an explosion funnel into discrete particles (smaller particles and stones) and calculating the movement of these condensed particles and their interaction with the air–gas flow; this method uses the framework of equations for multiphase media motion. For modeling of borehole explosion, we focused on the parameters of commercial blasting that are carried out at the Lebedinsky open pit. The results of simulating the initial stage of a borehole explosion with a mass of 1000 kg are presented in this paper. These results demonstrate the evolution of a gas and dust cloud, the change in the mass of particles of different sizes in the air over time, and their spatial distribution. Full article

One of the best technologies available for metal removal from mining effluents is the precipitation of metals as sulfides. However, the high cost and difficulty in managing reagents limit its widespread application. Recent literature suggests the use of sulfur-reducing bacteria (S°RB) as a safe and effective alternative to producing H₂S. Nevertheless, direct substrates for S°RB are high-cost low molecular compounds. This research aimed to evaluate the ability to produce sulfides by sulfur-reducing consortia in fixed-bed bioreactors using complex organic substrates. Consortia enriched using cellulose or Spirulina as electron donors were phylogenetically characterized by fluorescent in situ hybridization. Microorganisms belonging to Bacteria and Archaea were involved, being the most representative of the δ-Proteobacterias. The results obtained in test tube culture indicated that these consortia could use cellulose and Spirulina in alkaline conditions, resulting in high sulfide production. Upflowed fixed-bed bioreactors were implemented to establish optimal parameters., resulting in H₂S volumetric productivities ranging from 1.94 to 2.94 mol/m³∙day. In conclusion, an active biomass with significant sulfidogenic activity can be generated in bioreactors under an upflowed regime using cellulose or Spirulina. Full article

Few studies have been published on the analysis and correlation of data from process mineralogical studies of gold ore employing artificial neural networks (ANNs). This study aimed to analyse and investigate the correlations obtained by the technological characterization of auriferous ore using an ANN called self-organizing map (SOM) to support geometallurgical studies. The SOM is a data analysis technique in which patterns and relationships within a database are internally derived and the outputs are visual, assisting in the understanding of data in the representation of 2D maps. In the representation generated, it was possible to establish that the variables of accessibility, exposed perimeter, median gold grain diameter (D50), and SiO₂ and arsenic contents have strong positive correlations. Regarding geometallurgy, this study shows that SOM can identify large-scale spatial chemical–mineralogical gold ore patterns, which can help define the most relevant indicator variables for mineral processing. Full article

From the rupture of the Fundão dam in Mariana–MG, there are tailings still present at the bottom of the plant that must be recovered. The flocculation followed by sedimentation operation can be applied as a unit operation in this recovering process. Instead of using conventional inorganic coagulants, bio-based coagulants offer some advantages, due to their low toxicity and biodegradability. Nonetheless, the use of bio-based coagulants in the mining industry is not established yet, due to the complex parameters that must be taken in consideration. This study analyzes the influence of the pH and flocculant concentration, which are the variables of the 2² full factorial design. The pH value for the batch sedimentation process was defined ranging from 5 to 9. Tanfloc, a tannin-based coagulant, was used as a coagulant agent. The results indicate a strong dependence on the coagulant concentration, and a recommended 15 g/L dosage with pH varying from 6 to 8. From batch sedimentation, it was possible to determine an exponential model for the sedimentation with an excellent fitting (R² = 0.997). The sedimentation efficiency calculated is 65.6%. These results confirm the potential use of bio-based materials in mining tailing treatments. In addition, they can be used in equipment sizing and simulations of the sedimentation operation. Full article

Gold mining has serious negative environmental impacts, especially due to pollution emanating from tailings storage facilities (TSFs, tailings dams, slimes dams). The most important forms of pollution from TSFs are acid mine drainage (AMD) and high levels of potentially toxic elements (PTEs). AMD arises from the high levels of pyrite in the mining ores, which become oxidised in the TSFs where the pyrite is exposed to atmospheric oxygen. The sulphate produced from oxidation of the sulphide in the pyrite dissolves in water to form sulphuric acid, a very strong acid. pH levels in the extremely low range of 3–4 are common. At such low pH the mobilities of numerous metallic PTEs present in gold mine tailings become extremely high, causing them to move into the environment in AMD. AMD acidifies soils to very low pH levels at which the mobility and plant-availability of metallic PTEs are very high, causing toxicities. Very disconcerting is that AMD and PTE pollution is in some cases continueing unabated at high rates even more than 70 years after a mine has been abandoned. Rehabilitation of TSFs to contain AMD and PTEs within them is very expensive and there seems to be reluctance to fully commit to their rehabilitation. Rehabilitation of TSFs is also extremely difficult. There does not yet seem to be any guidelines for their effective rehabilitation. Full article

Potash fertilizer production is one of the most important economic activities. Historically, potash mining has had a significant impact on the environment, often with catastrophic consequences. The purpose of this paper is to summarize the results of studies on the environmental impact of potash mining using the example of the Verkhnekamskoe potash deposit. The deposit is located in the central part of the Solikamsk depression in the Pre-Ural foredeep (Perm Krai, Russia). All the main features and problems of underground mining of water-soluble ores and potassium fertilizer production are considered using the example of one of the world’s largest potash deposits. This paper looks into the specifics of the material composition of waste, its disposal, underground mining issues associated with the solubility of salts, and the risks of groundwater inflow into the mine workings, which causes flooding of mines. The results of all surveys show that potash mining affects the atmosphere, surface water, groundwater, soil, and vegetation. The most effective measure to reduce the adverse environmental impact of potash mining at the Verkhnekamskoe Deposit is hydraulic backfilling of mine chambers, which protects the underground mines from flooding, minimizes ground subsidence, and reduces the area of potash waste. Full article