Mining

This study describes the direct and indirect effects of mining on the karst of the Bakony Region. For this, the results of geological and mining research of the last century, the results of hydrological research of fifty years, as well as the investigations of several decades on the karst of the mountain region are used. Direct effects include the exploitation of filling materials (limonite, kaolinite, manganese ore, and bauxite) from paleokarst features, dolomite rubble, activities exploring or destroying cavities, and the pollution of cavity systems with mining waste (dirt). An indirect effect is karst water extraction. Mining activities (coal and quarrying) resulting in the development of pseudokarstic features are also mentioned here. It can be stated that the effects on the karst and karst features may be permanent and even renewing, but the original state may also have returned or can be expected in the near future. Damages may be local or regional. A regional effect is the decrease in karst water level, which has the most significant effect on the environment, but it has already reached its original state by now. Full article

The important role of ventilation in underground mines is to ensure safety and adequate environmental conditions in all accessible areas of a mine. This research aims to develop low-cost solutions for monitoring ventilation parameters in underground mines using the Internet of Things (IoT). A comparison between standard measuring equipment and a new low-cost wearable monitoring device prototype was performed, and the variables measured in an underground mine were pressure, temperature, and relative humidity. The results in all surveys indicate that the wearable monitoring device prototype can properly be used for continuous monitoring of the underground environment. The standard measurement devices for underground mines should continuously be used by mining companies as requested by local legislation. The low-cost wearable monitoring device developed should be viewed as a redundant measurement device for operators’ safety. The constant innovations in technology can support mining operators in anticipating problems, improving productivity, ensuring safety, and meeting standards at low investments. Full article

This article presents an investigation of ground movement measurements based on a combination of TerraSAR-X and Sentinel-1 data, in opposite tracks, aiming to detect ground de-formation of the remaining dikes of Germano mine, after the Fundão dam collapse. The differential interferometry technique SBAS (Small Baseline Subset) was applied to obtain the deformation of the surface in different Line of Sight (LoS), in order to carry out the vector decomposition and generate the deformation measurements in the vertical and horizontal directions. A set of 37 single-look complex (SLC) images of TerraSAR-X (TSX), acquired during the period from 19 February 2016 to 15 May 2017, and 37 SLC images of Sentinel-1, acquired from 8 February 2016 to 15 May 2017, were used to perform this investigation. For the TerraSAR-X interferometric processing, a coherence threshold of 40%, 4 looks in range and 2 looks in azimuth, 1200 m of atmospheric filter, and 10 % of max normal baseline of the critical were used. For the Sentinel-1 interferometric processing a coherence threshold of 26%, 8 looks in range and 2 looks in azimuth, 1200 m of atmospheric filter, and 20% of the of max normal baseline of the critical were used. For both sensors a digital elevation model generated by Pleiades 1-A was used for removing the topographic phase component. The final results were consistent with the topographic in situ measurements, providing key information to make crucial decisions regarding risks, or even mitigation, repairs or emergency response, as well as for a better understanding of the on-going instability phenomena affecting the dikes and dams. Full article

The difficulty of effectively planning and assigning weekly activities has a significant influence on the long-term productivity of an underground mine. It is an especially difficult task to choose the best places for operations inside an underground gold mine. It cannot be resolved by only selecting the levels with the highest grade of ore because the underground mine’s ore transport network has a range of capacity limitations that may prohibit the immediate mining of all the levels with the highest grade. To solve this scheduling difficulty, we formulated a new mixed-integer network flow model of the problem of weekly allocating mining operations in an underground gold mine such that the total gold mined (in ounces) was maximized subject to the transportation capacity constraints. The model was applied to an underground gold mine in Red Lake, Ontario, Canada. The results were compared to those of two greedy heuristic models that were designed to represent the decision-making heuristics that are currently used at the mine. It was found that the new model yielded solutions that improved upon the two greedy heuristics by 14.7% and 6.0%, respectively. The results of this research illustrate that the development of this optimization model can support decisions to improve a gold mine’s productivity. Full article

Automation has been changing the mining industry for the past two decades. Material handling is a critical task in a mining operation, and truck-shovel handling systems are the primary method for surface mining. Mines have deployed autonomous trucks, and their positive impact on both production and safety has been reported. This paper aims to study the extent to which autonomous and operator-assisted loading units could improve different aspects of a mining operation. Four different levels of automation ranging from operator-assisted swing and return to fully autonomous for a shovel were considered. A discrete event simulation model was developed and verified using detailed data from a shovel monitoring system. Later, the developed model was deployed to assess how each of the proposed technologies could improve productivity and efficiency. Results show that up to a 41% increase in production can be achieved. Both mining companies and equipment manufacturers can use the methodology and results of this study for future decision-making and product development. Full article

The problem of dump recultivation associated with sulfide ore mining is always a challenge for ecologists. A special case is the Arctic, where the specific climate and short vegetative period mean that any traces of such activities can persist for many years. The Monchepluton massif is a Paleoproterozoic, layered Platinum Group Element (PGE) intrusion, which is located in NE Scandinavia, beyond the Arctic Circle. This intrusion is mainly composed of ultramafic and alkaline rocks, represented by dunites, harzburgites, orthopyroxenites, norites, and gabbronorites. In these rocks, there is mineralization of the oxide ores Cr, Fe, and Ti, as well as the sulfide ores Cu, Ni, Fe, and PGE. The massifs of this intrusion were mined in the 20th century. The traces of intensive mining in the area are still visible today. The purpose of this study was to demonstrate the state of the environment and propose its rehabilitation. The authors carried out an inventory of the mining facilities and studies of the area’s rocks, soils, plants, and waters. The results of these studies unequivocally show that the current condition of the site indicates the conditions for an ecological disaster. The most important polluting factor is the presence of metallurgical plants, which are responsible for acid rain and soil pollution. Another threat is uncontrolled mine water outflows. Due to the specific climatic conditions and the vegetation found in the area, the process of rehabilitating the area may be costly and lengthy. Full article

This study illustrates the application of conditional simulations to calculate the uncertainty associated with the thickness of bauxite ores. The bauxite deposit of Rondon do Pará in northern Pará State, Brazil, is characterized by a well-defined lateritic profile, with the ore being composed of two sequential horizons: massive bauxite and ferruginous bauxite. This study used ore thickness data from 1.005 drillholes with different grid spacing. Drillhole intervals of both types of bauxite ore were accumulated, converting the database from 3D to 2D. Sequential Gaussian simulation produced probability maps calculated from certain confidence intervals, which permits obtaining the uncertainty associated with estimates in thickness. Results show that in portions with the same regular drillhole spacing there are different ranges of uncertainty and variability, which could be useful to support resource classification, associating different confidence intervals to resource classes. This analysis could also guide the drilling program for resource conversion in order to optimize costs, indicating areas where there is greater uncertainty and would need to be densified. The incorporation of this information into the resource model could be very helpful for supporting subsequent studies of economic evaluation and risk analyses with respect to this type of deposit or similarly in mineral exploration. Full article

The blasting operation considerably influences the overall productivity of opencast mines, especially when blasting results in oversized fragments that impact the operations ranging from excavation to milling. In this work, a numerical analysis of blasting performance was implemented to optimize the blasting parameters and improve the fragmentation of the hard rock in a copper open pit mine site in Brazil. In this paper, the methodology comprised data collection, 3D numerical model construction for blasting optimization using Blo-Up software, calibration with historical data, and predictive analysis, including testing two different blast designs. With the objective of achieving a desired P₈₀ size of the blasting fragmentation, the results indicate an optimized calibrated model with an overall error equal to 4.0% using a Swebrec distribution fitted to the model data. The optimal P₈₀ size of the resulting muckpile was equivalent to ~0.53 m for the hard rock copper fragments, which was close to the desired P₈₀ size. Full article

In this study, the employment of the gene expression programming (GEP) technique in forecasting models on sustainable construction materials including mineral admixtures and civil engineering quantities (e.g., compressive strength), was investigated. Compared to the artificial neural networks (ANN) based formulations, which are often too complicated to be used, GEP-based derived models provide estimation equations that are reasonably simple and may be used for practical design purposes and even for hand calculations. Many popular models, such as best-fitted curves based on regression analyses, multi-linear regression (MLR), multinomial logistic regression (MNLR), and multinomial variate regression (MNVR), can also be used for construction materials properties modeling. However, due to the nonlinearity and complexity of the target properties, the models established using linear regression analyses may not reveal the precise behavior. Additionally, regression models lack generality, and this comes from the fact that some functions are defined for regression in classical regression techniques; while in the GEP approach, there is no predefined function to be considered, and it reproduces or omits various combinations of parameters to provide the formulation that fits the experimental outcomes. If the input parameters can be evaluated through simple laboratory or rapid measurements, and also a comprehensive experimental database is made available, the models can be constructed with optimal flexibility. Flexibility in choosing the complexity and fitness functions, such as RMSE, MAE, and MSE, might lead to better performance of the approach and well-capturing the governing pattern behind the material’s characteristics. There may be minor inaccuracies with this technique; however, the explicit mathematical expressions, which can be easily implemented in the design and analysis process, may cover the minor inaccuracies compared to ANN, support vector machine (SVM), and other intelligent approaches. Based on the presented study, sometimes it would be better to provide more than one GEP model and consider different combinations of input contributing variables to afford the possible initial feed for a more settled and comprehensive model. Mostly, GEP’s strengths as a superior machine learning technique in modeling the behavior of construction materials including mineral admixtures, leading to innovative solutions in civil engineering, have been presented. Full article

This article describes the results of a study on the Zn-Pb heap, which is located in the center of the city of Ruda Śląska. The heap dates back to the 19th century but was rediscovered in the 21st century and abandoned. Located in the center of the city, it is eroded and contributes to the spreading of pollutants. The authors performed a study on the components of the dump using microscopic observations and geochemical analyses. The results indicate that the components of the heap are mobile, mainly due to the infiltration of meteoric waters affecting the contamination of soils and plants. The present work is devoted to a review of the state of the environment in the area of the heap and a proposal for its reclamation by covering it with an isolation layer or moving it to a protected place away from the city center. It is possible, in the future, to build an Environmental Education Center, for education and the monitoring of enrivonmental problems in Upper Silesia. Full article

Vipingo quarry in Kilifi county, Kenya, is one of the quarries supplying coral limestone for limestone manufacturing in the coastal region. Due to its close proximity to the Indian ocean, the semidiurnal ocean tides tend to have an influence on the stability of the quarry slopes adjacent to the shoreline. Finite element numerical analysis using the generalized Hoek–Brown criterion is conducted to assess the stability condition of the slopes followed by slope-angle optimization to determine the safest overall slope angle as well as analyzing the stability of the slopes due to action of varying ocean tides. The optimum overall slope angles for various excavation depths are found to be 52° for 20 m, 46° for 30 m, 42° for 40 m, and 39° for 50 m, which are the same even with varying distance of the slope face from the shoreline. A parametric analysis shows that there is no significant effect of the tides on slope stability for excavations above the water table, but as the quarry gets deeper, the slope stability is affected. A sensitivity factor (ζ) is introduced, being a measure of how much the slope safety factor is reduced as a result of the semidiurnal tidal action. Full article

The main purpose of the study was the absorption of heavy metals in the leaves of forest tree species, which were planted in two different plots for forestry use and environmental restoration. Four species were studied Pinus brutia, Robinia pseudoacaccia, Quercus trojana and Fraxinus ornus. Forty-eight leaf samples were collected which consisted of six samples from each species at each plot. The heavy metal concentrations in the leaves were measured for the following nine heavy metals: iron (Fe), copper (Cu), chromium (Cr), nickel (Ni), cadmium (Cd), manganese (Mn), zinc (Zn), cobalt (Co) and lead (Pd). The determinative estimation of metal concentration was carried out in the clear filtrate, using ICP-OES. Statistically significant differences in the concentrations of the heave metals were found among the species, as well as between the two plots. It was only in Robinia peudoacacia’s leaves that the cadmium concentration showed a statistical difference among the other species. The same applied for manganese in Quercus trojana’s leaves and zinc for Pinus brutia. The careful selection and planting of the appropriate forest tree species provides for an overall improvement in the environment in heavy metal polluted sites, such as those resulting from thermal power plants. Full article

Gold mining is a significant strategic sector for local, regional, and national economies. The rapid development of coexisting camp-type artisanal and small-scale gold mining (C-ASGM) and large-scale mining (LSM) accelerates the environmental and health risks associated with mercury pollution; however, transformations of coexisting sites have not been well quantified. This study used remote sensing (the PlanetScope smallsat constellations systems) to investigate the development of coexisting C-ASGM and LSM sites in Gorontalo, Indonesia, from 2019 to 2022. The results show a positive increase in the extent of barren land across all study zones, resulting from a road network construction connecting the southern port to major mining sites. Notably, greater landcover transformations in the C-ASGM sites after 2020 were attributed to the dumping of underground soils excavated using a shaft-mining method. The findings of this study expand our understanding of the rapid development of coexisting mining operations and quantify significant mining-induced environmental changes. These findings are anticipated to assist in timely monitoring and identification of development areas, rates, and volumes, together with the existing C-AGSM’s reactions associated with LSM’s massive developments. This also helps to detect possible local-level socioenvironmental impacts from massive land shape changes, leading to human disasters, including landslides and floods. Full article

Many factors influence the fatigue state of human beings, and fatigue has a significant adverse effect on the health and safety of the haulage operators in the mine. Among various fatigue monitoring systems in mine operations, currently, the Percentage of Eye Closure (PERCLOS) is common. However, work and other environmental factors influence the fatigue state of haul truck drivers; PERCLOS systems do not consider these factors in their modeling of fatigue. Therefore, modeling work and environmental factors’ impact on individual operations fatigue state could yield interesting insights into managing fatigue. This study provides an approach of using operational data sets to find the leading indicators of the operators’ fatigue. A machine learning algorithm is used to model the fatigue of the individual. eXtreme Gradient Boosting (XGBoost) algorithm is chosen for this model because of its efficiency, accuracy, and feasibility, which integrates multiple tree models and has stronger interpretability. A significant number of negative and positive samples are created from the available data to increase the number of datasets. Then, the results are compared with other existing models. A selected algorithm, along with a big data set was able to create a comprehensive model. The model was able to find the importance of the individual factors along with work and environmental factors among operational data sets. Full article

This paper presents the machine learning (ML) method, a novel approach that could be a profitable idea to optimize fleet management and achieve a sufficient output to reduce operational costs, by diminishing trucks’ queuing time and excavators’ idle time, based on the best selection of the fleet. The performance of this method was studied at the Zenouz kaolin mine to optimize the type of loader and the number of trucks used to supply the processing plant’s ore demands. Accordingly, five years’ data, such as dates, weather conditions, number of trucks, routes, loader types, and daily hauled ore, were collected, adapted, and processed to train the following five practical algorithms: linear regression, decision tree, K-nearest neighbour, random forest, and gradient boosting algorithm. By comparing the results of the algorithms, the gradient boosting decision tree algorithm was determined to be the best fit and predicted test data values with 85% accuracy. Subsequently, 11,322 data were imported into the machine as various scenarios and daily hauled minerals as output results were predicted for each working zone individually. Finally, the data which had the minimum variation from the selected required scheduled value, and its related data concerning loader type and the number of demanded trucks, were indicated for each day of the working year. Full article

Rock is constantly subjected to stress and thermal conditions. Thermal-induced micro-cracks will be generated as a result of different thermal expansion gradations between different minerals. This characteristic was investigated in this paper by studying the micro-properties of Sudbury norite via CT scanning and the image processing method. A novel filtering method, maximum–minimum shadow filtering (MMSF), was developed in this study to highlight the thermal-induced micro-cracks in Sudbury Igneous Complex (SIC) norite after different temperature treatments. Based on quantitative analysis, the areal percentages of biotite, felspar, quartz, and small amounts of metal minerals were determined. It was also found that small-scale micro-cracks were first observed in the middle of biotite grains at a temperature of 400 °C. The cracks further propagated and extended with the temperature increase. In addition, the orientations of cracks either remained at the same distribution or became more evenly distributed with the rising temperature. A linear relationship was found between the average porosity of SIC norite and the temperature. Moreover, the anisotropic properties between vertical and horizontal directions of norite were also noticeable. Overall, the paper presented a quantitative study on the effects of thermal treatment and the anisotropic properties of SIC norite. Methodology and findings from this paper will be a significant reference for future studies regarding the thermal impacts on norite and similar rocks. Full article

Despite their significance in numerous applications, many critical minerals and metals are still considered minor. Since most of them are not found alone in mineral deposits, their co- or by-production depends on the production of base metals and other major commodities. In many cases, the concentration of the minor metals is low enough not to be considered part of the production. Hence, their supply is not always secured, their availability decreases, and their criticality increases. Many researchers have addressed this issue, but no one has set actual impact factors other than economic ones that should determine the production of these minor commodities. This study identified several parameters, the number and diversity of which gave birth to developing a computational tool using a multi-criteria-decision analysis model based on the Analytical Hierarchical Process (AHP) and Python. This unprecedented methodology was applied to evaluate the production status of different commodities in a polymetallic deposit located in Chovdar, Azerbaijan. The evaluation outcomes indicated in quantifiable terms the production potentials for several commodities in the deposit and justified the great perspectives of this tool to evaluate all kinds of polymetallic deposits concerning the co- and by-production of several minor critical raw materials. Full article

The excavation of tunnels in brittle rocks with high in-situ strengths under large deviatoric stresses has been shown to exhibit brittle failure at the periphery of tunnels parallel to the maximum in-situ stress. This failure can either occur instantaneously or after several hours due to the strength degradation that is implicitly and indirectly considered in typical brittle constitutive models. While these models are powerful tools for engineering analyses, they cannot predict the time at which brittle rupture occurs, but rather, they show a possible failure pattern occurring instantaneously. In this paper, a model referred to as the long-term strength (LTS) model is introduced and implemented into FLAC2D. The model is built as a modified version of the CVISC model, introduced by Itasca, by adding a strength decay function. This function is developed from lab-scale time-to-failure (TTF) data. The LTS model is verified against its corresponding analytical solution using a constant stress creep lab test and implemented into a tunnel-scale model using the geometry, stress, and geologic conditions from the Atomic Energy of Canada Limited Underground Research Laboratory (AECL URL). The results of the LTS tunnel model are then compared to an identical model using the Cohesion Weakening Friction Strengthening (CWFS) approach. Full article

The use of the lithium-ion battery (LIB) in both traction and stationary applications has become ubiquitous. It is essential that retired LIBs are wisely treated, with a basis in the concept of the circular economy, to mitigate primary resource use. A closed-loop repurposing and recycling treatment is required. Thus, using the concept of total material requirement as an indicator of natural resource use based on mining activity, a dynamic material flow analysis was executed considering the degradation of the battery, its lifespan, and demand patterns under several scenarios. Then, the effect of circularity on the savings in global natural resource use involved across the entire lifecycles of LIBs was evaluated. It was found that the global resource use for LIBs will increase to between 10 and 48 Gt in 2050. Circularity has the potential to contribute to an 8–44% reduction in the global resource use associated with LIBs in 2050. It was also found that a longer lifespan in the years leading up to 2050 would have a greater impact on the reduction of resource use for LIBs, despite the lower effectiveness of circularity, because it would reduce the demand for LIBs. Full article