Search Results (504)

Weathering processes gradually alter the physical and mechanical attributes of slope materials, weakening the structural integrity and stability of slopes. This paper presents an in-depth analysis of slope stability in an open-pit mine, emphasizing the pivotal role of weathering effects in determining slope stability. To accurately capture the impact of weathering on slope stability, a comprehensive analysis model was developed, incorporating field observations, laboratory testing, and numerical simulations. The effects of weathering on the mechanical properties of black shale were studied through extensive laboratory tests. The uniaxial compressive strength, shear strength, and modulus of elasticity significantly decreased with increasing weathering, indicating a heightened vulnerability to slope failure. The correlation function between mechanical parameters and weathering time was obtained, providing the basis for evaluating the stability of mine slopes. It was found that more severe weathering conditions were strongly correlated with elevated risks of slope failure, including landslides and collapses. Based on these findings, practical recommendations are provided for slope reinforcement and management strategies, aimed at mitigating slope failure risks and ensuring the safe and efficient operation of the mine. By incorporating weathering effects into slope stability analysis, mine operators can make informed decisions that account for the dynamic nature of slope materials and their susceptibility to weathering, thereby improving overall mine performance and safety. Full article

Open-pit mining seriously damages the original vegetation community and soil layer and disturbs the carbon cycle of vegetation and soil, causing instability in the mining ecosystem and decrease in the carbon sequestration capacity of the mining area. With the deepening of environmental awareness and the influence of related policies, the ecological restoration of open-pit mines has been promoted. The mining ecosystem is distinct owing to the disperse distribution of mines and small scale of single mines. However, the carbon sequestration capability of mines after ecological restoration has not been clearly evaluated. Therefore, this study evaluated the carbon sequestration capacity of restoration mines, taking the mines of the Yangtze River Basin in Jurong City, Jiangsu Province as the research objects. Firstly, the visual effects of the vegetation and soil in their current status were determined through field investigation, the methods for sampling and data collection for the vegetation and soil were selected, and the specific laboratory tests such as the vegetation carbon content and soil organic carbon were clarified. Meanwhile, the evaluation system consisting of three aspects and nine evaluation indexes was established by using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE). The process of evaluation included the following: the establishment of the judgment matrix, calculation of the index weight, determination of the membership function, and establishment of the fuzzy membership matrix. Finally, the evaluation results of the restoration mines were determined with the ‘excellent, good, normal and poor’ grade classification according to the evaluation standards for each index proposed considering the data of the field investigation and laboratory tests. The results indicated that (1) the evaluation results of the mines’ carbon sequestration capacity were of excellent and good grade at a proportion of 62.5% and 37.5%, which was in line with the field investigation results and demonstrated the carbon sequestration capacity of all the restored mines was effectively improved; and (2) the weights of the criterion layer were ranked as system stability > vegetation > soil with the largest value of 0.547, indicating the stability of the system is the main factor in the carbon sequestration capacity of the mines and the sustainability of the vegetation community and the stability of soil fixation on the slope. The proposed evaluation system effectively evaluates the short-term carbon sequestration capability of the restoration mining system according to the visual effects and the laboratory testing results, objectively reflecting the carbon sequestration capacity via qualitative assessment and quantitative analysis. The evaluation method is relatively applicable and reliable for restoration mines and can provide a reference for similar ecological restoration engineering. Full article

Since the 20th century, with the rapid development of the global economy, human demand for fossil energy such as coal has been increasing. In the face of fierce competition, the state and various ministries and commissions have put forward the goals and requirements of building a world-class enterprise, and how to become a world-class open-pit coal mine and establish the corresponding evaluation standards has become an urgent scientific problem to be solved. According to the characteristics of open-pit coal mine production and operation, from the perspective of benchmarking world class, the key factors affecting the construction of world-class open-pit coal mines are extracted by using the fuzzy DEMATEL method, and the comprehensive evaluation index system, evaluation standards, and methods of open-pit coal mines are established, which provides benchmarks and guidelines for the construction of world-class open-pit coal mines and improves the construction level of world-class open-pit coal mines. Full article

Given the global importance and limited availability of phosphate, optimizing the use of this critical resource and minimizing its wastage are of paramount importance. In this context, this paper proposes an innovative architecture for the implementation of an intelligent video surveillance system specifically designed for open-pit phosphate mines. The proposed architecture is designed to meet the overall functional requirements of a surveillance system in the challenging environment of open-pit mining, while aligning with the guidelines of the Mine 4.0 revolution. It incorporates advanced technologies that address the critical challenges of latency, data security, and transparency commonly encountered in traditional monitoring systems. By adopting a multi-layered approach that leverages edge, fog, and cloud computing, coupled with blockchain technology and expert collaboration, our architecture offers a comprehensive framework for efficient data processing at every stage, from initial data acquisition to real-time anomaly detection and decision-making. Full article

Open-pit coal mining offers high resource recovery, excellent safety conditions, and large-scale production. However, the process generates significant dust, leading to occupational diseases such as pneumoconiosis among miners and adversely affecting nearby vegetation through dust deposition, which hinders photosynthesis and causes ecological damage. This limits the transition of open-pit mining to a green, low-carbon model. Among these processes, blasting generates the most dust and has the widest impact range, but the specific amount of dust generated has not yet been thoroughly studied. This study integrates indoor experiments, theoretical analyses, and field tests, employing the Split Hopkinson Pressure Bar (SHPB) system to conduct impact loading tests on coal–rock samples under pressures ranging from 0.13 MPa to 2.0 MPa. The results indicate that as the impact load increases, the proportion of large-sized blocks decreases while smaller fragments and powdered samples increase, signifying intensified sample fragmentation. Using stress wave attenuation theory, this study translates indoor impact loadings to field blast shock waves, revealing the relationship between blasting dust mass fraction and impact pressure. Field tests at the Haerwusu open-pit coal mine validated the formula. Using image recognition technology to analyze post-blast muck-pile fragmentation, the estimated dust production closely matched the calculated values, with an error margin of less than 10%. This formula provides valuable insights for estimating dust production and improving dust control measures during open-pit mine blasting operations. Full article

Small-scale open-pit, non-artisanal mining of low-value ores is an understudied practice despite its widespread occurrence and potential impact on freshwater resources due to mining-induced land-use/cover changes (LUCCs). This research investigates the long-term impacts of andesite mining in Pasuruan, Indonesia, on the Umbulan Spring’s water discharge within its watershed. System Dynamics (SD) modeling captures the systemic and systematic impact of mining-induced LUCCs on discharge volumes and groundwater recharge. Agricultural and reservoir-based land reclamation scenarios then reveal post-mining temporal dynamics. The no-mining scenario sees the spring’s discharge consistently decrease until an inflection point in 2032. With mining expansion, reductions accelerate by ~1.44 million tons over two decades, or 65.31 thousand tons annually. LUCCs also decrease groundwater recharge by ~2.48 million tons via increased surface runoff. Proposed post-mining land interventions over reclaimed mining areas influence water volumes differently. Reservoirs on reclaimed land lead to ~822.14 million extra tons of discharge, 2.75 times higher than the agricultural scenario. Moreover, reservoirs can restore original recharge levels by 2039, while agriculture only reduces the mining impact by 28.64% on average. These findings reveal that small-scale non-artisanal andesite mining can disrupt regional hydrology despite modest operating scales. Thus, evidence-based guidelines are needed for permitting such mines based on environmental risk and site water budgets. Policy options include discharge or aquifer recharge caps tailored to small-scale andesite mines. The varied outputs of rehabilitation scenarios also highlight evaluating combined land and water management interventions. With agriculture alone proving insufficient, optimized mixes of revegetation and water harvesting require further exploration. Full article

This study presents a unique model for assessing the dependability of continuous parts of combined systems in open-pit mining through the application of fuzzy logic. Continuous sub-systems as part of the combined system of coal exploitation in surface mines have the basic function of ensuring safe operation, high capacity with high reliability, and low costs. These subsystems are usually part of the thermal power plant’s coal supply system and ensure stable fuel supply. The model integrates various independent partial indicators of dependability into an expert system specifically designed for evaluating these systems. It deconstructs the complex parameter of system dependability into distinct partial indicators: reliability, maintainability, and logistical support. These indicators are then integrated using fuzzy composition (max-min composition). Historical data from 2018 to 2023 are utilized alongside the fuzzy model to provide a retrospective analysis of system dependability, serving to validate the model’s effectiveness. What sets this model apart from conventional approaches is its consideration of practical dependability indicators, thereby obviating the need for extensive long-term monitoring and data collection to portray the system’s status accurately over time. This model serves as a valuable tool for assisting decision-makers in open-pit mining operations, facilitating planning, exploitation control, and the selection of maintenance strategies to ensure consistent production and cost reduction. Designed for quick assessment, the model relies on expert judgments and assessments to determine system dependability efficiently. Full article

As mining engineering progresses into the deep excavation phase, the intensification of high pressure, high temperature, strong disturbances, and complex geological conditions becomes increasingly prominent. Researchers perform stability analysis on the excavation area to reduce potential safety hazards during the extraction process. Developing a detailed numerical calculation model that accurately reflects the true geological structure is essential for numerical simulation analysis in mining engineering. Based on the excellent 3D geological modeling capabilities of 3D Mine software, this paper introduces a new 3D geological and numerical unified modeling method (3DMine-Rhino-HyperMesh) involving multi-software coupling and details the specific steps and concepts of this modeling approach. Subsequently, using a certain open-pit mine in Panzhihua as a backdrop, a detailed geological and numerical unified model is established, reflecting the true geological structure of the mining area, and the potential failure mechanisms of the mine slope are analyzed. The results indicate that the modeling method aligns well with the actual geological conditions, enhancing the grid quality of the numerical model and offering a new modeling approach for simulating and analyzing large complex geological entities in mining operations. Full article

Human activities play a key role in landscape evolution. Mining is one of the most important of these since it changes large parts of the Earth’s surface. In abandoned mines and quarries, pit lakes are quite common due to water table blocking. These lakes have remarkable ecological characteristics, but they are still poorly understood. Northwestern Spain has a long tradition in the use of slate for roofs. This exploitation, mostly open-pit, has caused a great transformation in the landscape including the generation of pit lakes. In this work, 27 pit lakes in abandoned slate quarries areas have been analysed using orthophotos of different years, UAV (unmanned aerial vehicle) images and field work. In each lake, the topographic context, geomorphological dynamics, morphometric parameters (including depth), pH, and ecological variables were measured. Other uses for these quarry pit lakes and their significance as a new geo-ecological environment are also discussed. The results show different types of pit lakes and, consequently, different potential uses in each case. Only six offer good conditions for recreational uses, whereas the rest (21) show slope instability or poor water quality. Full article

While open-pit mining activities represent one of the human-derived most impactful land cover changes, these changes and the linked restoration processes can be challenging to assess. This article presents a reproducible methodology carried out with cloud processing of satellite images (Google Earth Engine (GEE)) to evaluate the evolution of open-pit mining activities and their restoration in a Mediterranean landscape. For this purpose, the calculation of the normalized differential vegetation index (NDVI) was used to obtain a quantitative parameter to monitor vegetation presence in each extractive area. To validate these results, confusion matrices were performed between the classification obtained in the study and the official land cover mapping, using randomly selected mining areas as test points, with an average accuracy of 88%. According to the methodology used, the surface of areas denuded by mining in the period 1984–2023 has fluctuated over time, with a maximum in 2005 coinciding with the peak of the Spanish construction boom, and a subsequent decrease towards the present. From these results, it can be concluded that Landsat-type data processed using GEE provide a quick and useful tool for monitoring the evolution of mining activity, including restoration trends, becoming particularly valuable for public bodies’ inspections or decision making. Full article

Accurate estimation of the mean fragment size is crucial for optimizing open-pit mining operations. This study presents an approach that combines clustering, hyperparameter optimization, and data augmentation to enhance prediction accuracy using the Xtreme Gradient Boosting (XGBoost) regression model. A dataset of 110 blasts was divided into 97 blasts for training and testing, whereas a separate set of 13 new, unseen blasts was used to evaluate the robustness and generalization of the model. Hierarchical Agglomerative (HA) and K-means clustering algorithms were used, with HA clustering providing a higher cluster quality. To address class imbalance and improve model generalization, a synthetic minority oversampling technique for regression with Gaussian noise (SMOGN) was employed. Hyperparameter tuning was conducted using HyperOpt by comparing Random Search (RS) with the Advanced Tree-structured Parzen Estimator (ATPE). The combination of ATPE with HA clustering and SMOGN in an expanded search space produced the best results, achieving superior prediction accuracy and reliability. The proposed HAC1-SMOGN model, which integrates HA clustering, ATPE tuning, and SMOGN augmentation, achieved a mean squared error (MSE) of 0.0002 and an R² of 0.98 on the test set. This study highlights the synergistic benefits of clustering, hyperparameter optimization, and data augmentation in enhancing machine learning models for regression tasks, particularly in scenarios with class imbalance or limited data. Full article

Prior research has demonstrated that incorporating solid waste from various sources, such as plastics, civil engineering waste, and industrial and mining waste, into pavement and civil works mixes has notable environmental benefits. This includes reducing the over-exploitation of aggregate banks and preventing waste materials from being deposited in open-pit landfills for extended periods. This review focuses on sustainable aggregates produced from solid waste with rheological or mechanical properties suitable for replacing conventional aggregates in asphalt or hydraulic concrete mixtures. The aim is to determine the optimal replacement percentage in the mixture to directly impact pavement performance. This review also delves into the impact on fatigue resistance and permanent deformation based on the type of waste material used in construction. Additionally, using sustainable aggregates presents added benefits for pavement binders, such as inhibiting reflection cracks, reducing traffic noise, and prolonging the service life of the pavement. However, it is crucial to study the percentage of replacement of sustainable aggregates in conjunction with other materials using mathematical models and simulations to ensure a substantial contribution to the sustainability of the construction industry. Full article

Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has increasingly incorporated unmanned driving, real-time information sharing, and intelligent algorithm applications. However, the traditional manual scheduling used for mining transportation often prioritizes output over efficiency and quality, resulting in high operational expenses, traffic jams, and long lines. In this study, a novel scheduling model with multi-objective optimization was created to overcome these problems. Production, demand, ore grade, and vehicle count were the model’s constraints. The optimization goals were to minimize the shipping cost, total waiting time, and ore grade deviation. An enhanced multi-objective beluga whale optimization (IMOBWO) algorithm was implemented in the model. The algorithm’s superior performance was demonstrated in ten test functions, as well as the IEEE 30-bus system. It was enhanced by optimizing the population initialization, improving the adaptive factor, and adding dynamic domain perturbation. The case analysis showed that, in comparison to the other three conventional multi-objective algorithms, IMOBWO reduced the shipping cost from 7.65 to 0.84%, the total waiting time from 35.7 to 7.54%, and the ore grade deviation from 14.8 to 3.73%. The implementation of this algorithm for truck scheduling in open-pit mines increased operational efficiency, decreased operating costs, and advanced intelligent mine construction and transportation systems. These factors play a significant role in the safety, profitability, and sustainability of open-pit mines. Full article

Pre-existing concealed goafs underneath open-pit slopes (PCO-goafs) pose a serious threat to the stability of open-pit slopes (OP-slopes), which is a common problem worldwide. In this paper, the variable weight-target approaching method, equilibrium beam theory, Pratt’s arch theory, and numerical simulation are used to analyze the management solutions and stability of five PCO-goaf groups in the Nannihu molybdenum mine located in Luoyang City, Henan Province, China. The five PCO-goaf groups, numbered 1#, 2#, 3#, 4#, and 5#, are divided into four hazard classes, ranging from extremely poor to good stability. The stability of 1#, 2#, and 4# is poor and must be managed by filling, and the design strength of backfill is 1.2 MPa; caving is used to treat 3# and 5#, and the safe thickness of the overlying roof is calculated to be 10.5–41 m. After treatment, the safety coefficient of the slope is greater than 1.2, indicating that the slope is stable. This study provides insight and guidance for the safe operation of open-pit mines threatened by the existence of PCO-goafs. Full article

This study introduces a novel method utilizing hyperspectral imaging for instantaneous ore-waste analysis of drill cuttings. To implement this technique, we collected samples of drill cuttings at regular depth intervals from five blast holes in an open pit gold mine and subjected them to scanning using a hyperspectral imaging system. Subsequently, we employed two distinct methods for processing the hyperspectral images. A knowledge-based method was used to estimate ore grade within each sampled interval, and a data-driven technique was employed to distinguish the ore and waste for each sample interval. Firstly, leveraging the mixed mineralogical composition of the samples, the Linear Spectral Unmixing (LSU) technique was utilized to predict ore grade for each sample. Additionally, the Gradient Boosting Classifier (GBC) was used as an efficient data-driven approach to classify ore-waste samples. Both methods rendered accurate results when they were compared with results obtained through laboratory X-ray diffraction (XRD) analysis and gold assay analysis for the same sample intervals. Adopting the proposed methodology in open pit mine operations can significantly enhance the process of grade control during blast hole drilling. This includes reducing costs, saving time, minimizing uncertainty in ore grade estimation, and establishing more precise ore-waste boundaries in resource block models. Full article