Mining, Volume 2, Issue 4 (December 2022) – 12 articles

The global challenge for the mining sector is the problem of “decarbonization” of coal mining. The modeling of emission flows of coalmine methane is stipulated by the need to prove the environmental effect of the implemented technological changes. For longwall geotechnology, the dynamics of methane concentration in the gas–air mixture extracted by the degassing system reflects the complex relationship between emission and geomechanical processes in the rock mass. In this regard, the aim of the work was to improve the methods for assessing the steps of caving the main roof when mining gas-coal seams. The method of work consisted of processing experimental data (smoothing—Loess, three-dimensional interpolation, regression—the method of least squares) to obtain reliable response functions in three-dimensional space. When developing algorithms in the Python language, the Vi Improved text editor was used. Graphical representation of the results was carried out in “Gnuplot”. As a result of modeling, it was found that the increase in the span of the main roof from 83 to 220 m (S = 1340–1120 m) in the distance range of 120 m in front of the stoping face line and up to 50 m behind it (L = −120–50 m) leads to an alternating cyclicity of local extrema of the dynamics of methane release, according to a polynomial dependence. This fact is a consequence of the implementation of deformation-wave processes in geo-environments, which produce cyclic nonlinearities in the nature of the aero-gas regime of mine methane emissions into anthropogenically disturbed rock masses. In addition, the influence of the situational geomechanical conditions of the excavation area in the goaf was clarified. This makes it possible to reliably identify the caving steps of the main roof. Full article

This article presents an approach to rockfall hazard assessment for rocky slopes based on a previously published rockfall hazard methodology. The original method is appropriate to high alpine rocky slopes exposed to large scale deformations. It evaluates the parameters related to the geomechanical characterization of rock mass, indications of activity, external influences and event intensity. The original methodology was modified to consider different contexts, including geological, climatic and social environments. Parameters related to external influences were modified; the geometry and characteristics of the slope and the catchment area were introduced. The original methodology and the new proposal were applied to two urban slopes and one railway slope in order to test and compare the methods. The original proposal could not represent the rockfall conditions of these slopes. The new proposal was validated using two mine slopes, whose conditions of stability are known. The results of the analyses with the urban slope and the railway slope were coherent with the situation observed at the field. The validation in the mine slopes showed that this approach is applicable in several situations, being able to determine how hazardous a slope is in relation to rockfall events. Full article

Nowadays, with the advancement of technological innovations and wide implementation of modern mining equipment, research topics on mining equipment management are attracting more and more attention from both academic scholars and industrial practitioners. With this background, this paper comprehensively reviews recent publications in the field of mining equipment management. By analysing the characteristics of open-pit mine production and haulage equipment types, problem definitions, formulation models and solution approaches in the relevant literature, the reviewed papers are classified into three main categories, i.e., shovel–truck (ST); in-pit crushing–conveying (IPCC); and hybrid IPCC-ST systems. Research progress and characteristics in each categorized mining equipment system are discussed and evaluated, respectively. With a thorough assessment of recent research agendas, the significance of developing state-of-the-art mining equipment scheduling/timetabling methodologies is indicated, based on the application of classical continuous-time machine scheduling theory. Promising future research directions and hotspots are also provided for researchers and practitioners in the mining industry. Full article

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