2026-02-24
Roman J. Jędrzejczyk et al.
Methane plays a significant role in intensifying the greenhouse effect, possessing a global warming potential more than twenty times greater than that of CO 2 when measured on a carbon-dioxide-equivalent basis. Hence, identifying efficient methods to mitigate methane emissions is crucial for safeguarding the environment, ensuring economic viability, and maintaining practicality. Globally, research initiatives are dedicated to crafting an effective catalyst system for methane oxidation, which involves developing catalysts, comprehending their characteristics, and determining the best way of bonding them to structural supports to enhance functionality. Notably, systems that incorporate metals from the non-noble d-block of the periodic table as the active element, supplemented by small amounts of noble metals like palladium to boost their efficacy, are showing significant promise. The VAM-PiRE project, a collaborative endeavour involving the Technology Transfer and Promotion Centre in Katowice, the Central Mine Institute National Research Institute, and Jagiellonian University in Kraków, aims to develop a high-performance modular reactor that leverages these active catalysts. Preliminary results from this project are encouraging, suggesting that this novel strategy could be effectively upscaled and integrated into mine ventilation systems to reduce methane emissions with simultaneous cold production for air-conditioning purposes.
2026-01-17
2026-01-01
Hussein A. Saleem
Underground mine ventilation is crucial for ensuring worker safety, air quality, and operational efficiency. Effective optimization of ventilation systems reduces energy consumption, enhances airflow distribution, and minimizes risks associated with harmful gases and fire hazards. This study proposed an integrated framework combining the Hardy Cross (HC) method, Monte Carlo (MC) simulations, and machine learning (ML) techniques to optimize the ventilation system at the Jabal Sayid mine in Saudi Arabia. The HC method was employed to provide deterministic baseline airflow calculations, while the MC simulations accounted for uncertainties in resistance values and environmental conditions, generating probabilistic distributions of key parameters. Among the five ML algorithms tested (ANN, RF, GB, SVM, and LSTM), the LSTM model demonstrated superior predictive accuracy, particularly for dynamic, time-dependent parameters. The hybrid HC-MC-ML model integrated these approaches to achieve comprehensive ventilation optimization. Results indicated a 12.8% reduction in airflow resistance, leading to enhanced fan efficiency and a significant improvement in energy consumption. For instance, fan system efficiency increased by up to 7% in combined operations, while resistance values consistently decreased across all scenarios. Additionally, the hybrid model effectively managed exhaust gas emissions, maintaining pollutant concentrations within permissible limits by dynamically adjusting airflow routes. The findings demonstrate that the HC-MC-ML framework not only improved energy efficiency but also ensured safe and sustainable mine ventilation.
2026-01-01
Augusto A. T. Toledo et al.
In short-term mine planning for deposits characterized by multiple variables, sequential diglines are generated with an emphasis on maintaining consistent grade distributions across mining periods. This research integrates an array of mineral variables, including deleterious elements, to facilitate the establishment of excavation geometries that enable precise grade and volume control within operational production zones. Through the systematic application of geostatistical analysis coupled with process optimization, geological risks associated with grade uncertainties are minimized, and an optimized operational sequence for the extraction of mineral blocks is pursued. The main point of this approach is maintaining grade distributions aligned with the historical mean grade, with low variability. The use of genetic algorithms optimizes block selection by incorporating the location, interaction, and efficiency of shovels as seed points. The results demonstrate that the methodology generates weekly schedules that enhance the stationarity of grade distribution, thereby improving operational efficiency and reducing risks
2026-01-01
Gera Techane Mengistu et al.
Elevated levels of heavy metals in surface water can lead to the degradation of water quality, especially in mining areas where tailing dams are sources of heavy metal pollution. This study focuses on evaluating the concentrations of heavy metals in surface water near the Legadembi tailings dams. The mean concentrations (in µg/L) of various heavy metals including: arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), molybdenum (Mo), nickel (Ni), lead (Pb), antimony (Sb), selenium (Se), thallium (Tl), uranium (U), vanadium (V), tungsten (W), zinc (Zn), and zirconium (Zr) were determined: 79.7, 0.15, 162.3, 0.66, 18.1, 0.01, 22.5, 55.7, 0.30, 3.3, 2.6, 0.01, 0.49, 1.7, 136.1, 5.7, and 0.32, respectively. Moreover, the concentrations of metals in the surface water exhibit a temporal or seasonal variation, which makes the study interesting. Overall, the results indicate that the concentrations of heavy metals generally decrease as the distance from the tailings dam increases, signifying the downstream dilution effect. Nevertheless, it was observed that dams two and three surpassed both national and international standards for certain heavy metals, such as As, Co, and W. These dams, which are accessible to domestic animals, would pose a potential health risk to humans and animals.
2025-10-23
Patrick Adeniyi Adesida et al.
This study aimed to evaluate rock fragmentation risk indexes and develop a predictive model for the median size of fragment ( X 50 ) using the Rock Engineering System (RES). The methodology includes the analysis of 15 significant parameters of rock properties and blast design, which are considered to be important to rock fragmentation from 30 selected blast sites. These parameters include rock type, hardness, blast-hole diameter, charge weight, blast pattern, and others that control fragmentation results. Statistical analysis was performed to validate the RES-based model developed from these parameters. The model exhibited a strong predictive capacity, evidenced by a high correlation coefficient ( R ² = 0.922) with a low associated p -value (1.27E-13). In comparison, error analysis methods were used to evaluate the performance of the RES model against other models, including statistical, Kuz-Ram and modified Kuz-Ram. The outcomes showed that the RES model achieved the best accuracy, and the VAF , RMSE , MAPE , and MAE were 93.57%, 1.46 cm, 3.112% and 1.73 cm, respectively. This re-emphasises the model's reliability and effectiveness with regard to predicting the fragmentation result. The RES-based model has a good prospect as a tool for assisting in blast design and optimisation of fragmentation and, consequently, the efficiency of mining and construction.
2025-10-01
Long Quoc Nguyen et al.
This study conducts a thorough review of the current scientific literature on the application of geospatial methods in the assessment of mining-induced displacement. The scope of research included technologies for determining deformation, subsidence, and landslide in mining areas. Global Navigation Satellite Systems, Unmanned Aerial Vehicles, Terrestrial Laser Scanners, Remote Sensing, and fusion methods are approaches used to solve the research objectives. Additionally, the paper also mentions some advantages, disadvantages, and scope of application of these methods. The investigation revealed that the displacement detection method most commonly used at the moment is satellite radar interferometry.
2025-10-01
Weidong Pan et al.
With the increasing intensity of coal resource exploitation in China, the geological conditions of the working face are becoming more and more complex, and the bottom plate breakage (bottom bulge) and water inrush disasters caused by pressurized water mining are becoming more prominent. This article is based on the 21605 working face of Xin’an Coal Mine in Zaozhuang Mining Group. Through theoretical analysis and numerical calculations, the characteristics and scope of coal seam floor failure in the working face are obtained. Especially, the electrode cable direct current detection system designed through self-optimization was used for actual testing. Research shows that the bottom plate of the 21605 working face exhibits the theoretical characteristics of “lower three zones”, with a maximum failure depth of 12.6m, lagging behind the coal wall of the working face by 25m. Propose measures for preventing and controlling water inrush from the bottom plate, including initial isolation and control, mid-term dynamic observation, full process grouting reinforcement, and exposure of key prevention measures. The optimized detection system has a short preparation period, convenient detection, strong adaptability, good stability, and high accuracy, providing important technical means for the safety of pressurized water mining and bottom plate detection.