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The research on slope stability of open-pit mine has always been a key technical problem that plagues safe production, and it is also an important research topic in geotechnical engineering. Changshanhao open-pit mine is the largest gold mine in northern China. The increasing mining depth has led to various slope instability problems. Based on the background of ' 2021·10 landslide ' in the northeast stope, this paper carries out a new round of slope stability evaluation and disaster prevention countermeasures from the strategic height of the future development of the mining area. Firstly, the site engineering geological survey is carried out by using scanline method, and the main structural characteristics such as faults are summarized, and the comprehensive zoning map of engineering geology is established to reveal the failure mode of the slope in northeast stope are planar sliding and wedge sliding. Secondly, based on the principle of slope classification analysis, the study area is divided into overall slope, combined step slope and step slope, and the structural plane is matched with it. The stability of mining slope is preliminarily evaluated by stereographic projection method and Q-slope method. Approximately 13.9% of the area was classified as high-risk. Finally, the three-dimensional calculation model of the stope is established, and the FLAC3D is used to invert the landslide to reveal the influence mechanism of the fault on the slope stability. Combined with the analytical solution and the numerical solution, a suggestion is made to optimize the slope angle by raising the boundary., which lays a foundation for the sustainable and safe mining of the mine. [ABSTRACT FROM AUTHOR]

To address the issues of large anomalous triangulations, invalid interpolations, and uneven boundary interpolations in kriging interpolation, we propose research on a coal seam modeling construction method based on improved kriging interpolation. The work methodology assumes that by introducing kriging interpolation and analyzing its problems, we improve the interpolation method via a local interpolation algorithm for large anomalous triangulations, an optimization algorithm for locally redundant interpolation points, and a nonuniform boundary adaptive local interpolation algorithm. These improvements allow the interpolation method to better reflect the variability and realistic nature of coal seams. The research results indicate that applying this method to the construction of the Dananhu No. 2 open-pit mine coal seam model has improved the issue of coal seam transition stiffness, such as abnormal large-area triangulation in areas with significant elevation differences. This approach appropriately reduces the memory space usage without altering the coal seam morphology (which saves approximately 27,000 KB of memory, equivalent to the space occupied by 4 out of 21 coal seams). It has also prevented inaccuracies in boundary line positioning and transitions caused by too low a density of points on the coal seam reserve boundary line, resulting in smoother model transitions at the boundaries that better align with the actual coal seam change trends, the error rate in coal quality estimation decreased by 62.69%. This study provides data support for mining planning and reduces costs. This method can be extended to the construction of all mine models. [ABSTRACT FROM AUTHOR]

The abandonment of stone quarries establishes a quarry lake ecosystem that includes soil, water, fish, and vegetarian cover. The activity concentrations (ACs) of natural radionuclides in the waters of several quarry lakes worldwide have not been investigated. In addition, the features of radionuclides, such as distribution, seasonal variability, and health risks, have not been studied. In this study, the ACs of 226Ra, 234U, and 238U were measured in a typical quarry lake in Vietnam with an area of approximately 4000 m2. The average ACs of 226Ra, 234U, and 238U were 8.3, 13.8, and 17.7 mBq L−1, respectively. The ratios of 226Ra/234U, 226Ra/238U, and 234U/238U were 0.47, 0.6, and 0.79, respectively. A linear correlation was found between ACs and water depth. The ACs predicted by the QWASI (Quantitative Water, Air, Sediment Interaction) model agree with the measured values. [ABSTRACT FROM AUTHOR]

In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic mixed-integer programming framework (SMIP) is presented for the long-term production scheduling optimization problem (LTPSOP) in open-pit mines. The objective function maximizes the net present value and minimizes the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. The current study has proposed a hybrid model to solve the LTPSOP with the incorporation of augmented Lagrangian relaxation (ALR) and the human mental search metaheuristic algorithm (HMS). The ALR function is formulated and the HMS is used to update the Lagrange multipliers. Besides, a Gaussian process machine learning method is applied to estimate the grade in a mineral deposit. The results obtained from a supercomputer have indicated that the ALR–HMS method conducted on real case studies generates 18.29% and 31.56% more cumulative net present value; 9.75% and 13.98% larger pit size than the conventional method, respectively. Finally, while improving the solvability and optimality gap, the analysis of the outcomes has demonstrated that the proposed model yields a near-optimal solution with a rational time. [ABSTRACT FROM AUTHOR]

Abstract To address the issues of large anomalous triangulations, invalid interpolations, and uneven boundary interpolations in kriging interpolation, we propose research on a coal seam modeling construction method based on improved kriging interpolation. The work methodology assumes that by introducing kriging interpolation and analyzing its problems, we improve the interpolation method via a local interpolation algorithm for large anomalous triangulations, an optimization algorithm for locally redundant interpolation points, and a nonuniform boundary adaptive local interpolation algorithm. These improvements allow the interpolation method to better reflect the variability and realistic nature of coal seams. The research results indicate that applying this method to the construction of the Dananhu No. 2 open-pit mine coal seam model has improved the issue of coal seam transition stiffness, such as abnormal large-area triangulation in areas with significant elevation differences. This approach appropriately reduces the memory space usage without altering the coal seam morphology (which saves approximately 27,000 KB of memory, equivalent to the space occupied by 4 out of 21 coal seams). It has also prevented inaccuracies in boundary line positioning and transitions caused by too low a density of points on the coal seam reserve boundary line, resulting in smoother model transitions at the boundaries that better align with the actual coal seam change trends, the error rate in coal quality estimation decreased by 62.69%. This study provides data support for mining planning and reduces costs. This method can be extended to the construction of all mine models.

To address the requirements for left-side driving and the issue of smoothing efficiency for long-distance transportation routes of mining dump trucks in open-pit mine environments, a path planning method that combines a left-side driving hybrid A* algorithm based on Clothoid curve expansion with a smoothing algorithm that minimizes the diagonal vector norm of discrete points is proposed. Initially, Clothoid curves are used instead of traditional circular arcs in the hybrid A* node expansion search process, ensuring the continuity of curvature and meeting the requirements for curvature change rate limitations in the hybrid A* search path. The left-side driving rules are then applied to improve both the cumulative cost and heuristic cost within the hybrid A* framework, incorporating left-turn costs and collision attraction costs to ensure the path veers leftward and follows along the left side of the map border. The heuristic cost is adjusted based on the relation of the expansion direction to the nearest point on the map border, facilitating a heuristic cost map that favors left-side driving and generates a rough global path for leftward travel. Finally, by integrating quadratic programming techniques with the objective of minimizing the diagonal vector norm of discrete points under movement constraints along the coordinate axes, a smoothing optimization model is constructed to smooth the global path. To prevent the curvature from exceeding the vehicle's steering response capability during the smoothing process, a tunnel reduction technique for the feasible region of high-curvature points is employed, limiting the smooth movement of high-curvature points. The results show that the proposed method can generate a global path suitable for left-side driving rules in mining areas, which follows the left side boundary of the map. The heuristic cost improvement significantly reduces the number of nodes expanded by the hybrid A*, favoring the implementation of left-side driving. The discrete point path smoothing method effectively enhances the smoothness of the global path, aiding in vehicle control and tracking. Moreover, thanks to Clothoid curve expansion and the feasible region tunnel reduction technique, the method can effectively handle high-curvature paths, such as loading and unloading, without curvature exceeding limits. Comparing the planning times for paths of different lengths, the path smoothing algorithm significantly reduces the total planning time, with a 4-kilometer path smoothing process requiring only 76 milliseconds. The execution of left-side planning and the reduction in planning time improve the adaptability of the path planning for mining area scenarios.

Abstract Rock and soil strength profoundly influences the stability of open-pit mine slopes. Traditional slope design, based on limited drilling data, often disregards inherent uncertainties. Effectively utilizing new sample information from mining operations poses a challenge, hindering dynamic and differentiated design for the entire perimeter slope. To address this, we propose a dynamic optimization method considering rock mass strength uncertainty for the entire perimeter slope. Our approach involves designing slope angles separately in different zones, while thoroughly considering decision-makers' preferences. Furthermore, we delegate the final adjustment authority of slope angles within the safety permissible range to on-site decision-makers. Compared to traditional methods, our dynamic design method incorporates rock mass strength uncertainty into slope evaluation while also accounting for decision-makers' safety and economic preferences. Through a case study of a specific open-pit mine, our proposed dynamic design method increases the overall slope angle by approximately 2.5°, fully accommodating the influence of on-site decision-making preferences on slope design. This article introduces a new method of dynamic optimization of open-pit mine slope based on simplified observation method, which improves the flexibility of decision-making and realizes the differential design of the whole surrounding slope.

Rock and soil strength profoundly influences the stability of open-pit mine slopes. Traditional slope design, based on limited drilling data, often disregards inherent uncertainties. Effectively utilizing new sample information from mining operations poses a challenge, hindering dynamic and differentiated design for the entire perimeter slope. To address this, we propose a dynamic optimization method considering rock mass strength uncertainty for the entire perimeter slope. Our approach involves designing slope angles separately in different zones, while thoroughly considering decision-makers' preferences. Furthermore, we delegate the final adjustment authority of slope angles within the safety permissible range to on-site decision-makers. Compared to traditional methods, our dynamic design method incorporates rock mass strength uncertainty into slope evaluation while also accounting for decision-makers' safety and economic preferences. Through a case study of a specific open-pit mine, our proposed dynamic design method increases the overall slope angle by approximately 2.5°, fully accommodating the influence of on-site decision-making preferences on slope design. This article introduces a new method of dynamic optimization of open-pit mine slope based on simplified observation method, which improves the flexibility of decision-making and realizes the differential design of the whole surrounding slope. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Coal mining has a certain influence on and causes disturbances in groundwater. To investigate the variation trend of groundwater around the open-pit mine in grassland area, taking Shengli No. 1 open-pit mine as an example, the impact and variation trend of groundwater level in Quaternary aquifer around the mine area was studied by using the data of hydrological monitoring wells. The results show that the water level around the mining area varies from one year to the next. Since 2008, the water level has experienced a process of reduction, stability and increase. Compared with the background water level value, the current water level of each monitoring well is lower than the background water level. The influence radius calculated by Kusakin formula ranges from 94.15 m to 906.80 m, and the aquifer is heterogeneous. On the basis of the correlations between changes in waterline in monitoring wells and the stope distance, the disturbance radius of open-pit mining on surrounding diving water in grassland area is less than 2000 m. Based on the comprehensive analysis of the alteration of diving waterline and its influencing factors, the main factors affecting the variation in the phreatic water level are atmospheric precipitation, evaporation, groundwater usage and dewatering water. All factors act on the diversification of diving water level synthetically. The internal waste dump of an open-pit mine has a positive effect on the surrounding groundwater recovery. The aim of this study is to reveal the impact of open-pit mining on surrounding groundwater and providing scientific basis for future mining in other open-pit mines. [ABSTRACT FROM AUTHOR]

Mining can significantly alter landscapes, impacting wildlife and ecosystem functionality. Natural recovery in open‐pit mines is vital for habitat restoration and ecosystem re‐establishment, although few empirical studies have examined this process. Here, we assessed temporal and spatial responses of small rodents at the community, population, and individual levels during natural mine recovery. We examined the abundance, reproductive potential, and individual health of small rodents at active mines and at former mine sites left to recover naturally for approx. 10 and 20 years. We also assessed the effects of disturbance on rodent recovery processes at three distances from the mine boundary. Rodent numbers peaked after 10–13 years of recovery and exhibited the strongest male bias in the sex ratio. The Chinese white‐bellied rat (Niviventer confucianus) was the most abundant species, achieving its highest population abundance at sites abandoned for 10–13 years and thriving at locations closer to the mine boundary. Only Chevrier's field mouse exhibited morphological responses to the mine recovery category. Ectoparasite load was unaffected by mine or distance‐disturbance categories. Both Chevrier's field mouse (Apodemus chevrieri) and the South China field mouse (Apodemus draco) were affected significantly by vegetation layer cover during recovery succession. Our study highlights the complexities of ecological succession, with a peak in abundance as pioneer communities transition toward a climax seral stage. Careful prior planning and active site management are necessary to optimize abandoned mine recovery. Efforts to accelerate mine recovery through technical restoration should promote conditions that initiate and perpetuate the establishment and succession of wildlife assemblages. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model's potential to transform open-pit mining operations by using intelligent planning. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The prediction of dust concentration in open-pit mine is a critical foundation for minimising dust pollution. In order to improve the prediction accuracy of dust concentration in an open-pit mine, the combined prediction algorithm model of GA-LSSVM and Elman-Adaboost based on the integration of error reciprocal approach was investigated. Firstly, the monitoring equipment of dust concentration and meteorological factors was installed in the open-pit mine site to collect important data, and the distribution law of dust concentration, meteorological and production intensity data was analyzed. The mutual information feature screening algorithm was utilised to efficientlyly remove the redundant and disruptive model prediction performance. The characteristic variables, according to the importance of information, select four indicators of stripping amount, temperature, humidity and wind direction, and then determine the input variables of the prediction model. The dust concentration prediction model was then developed using the genetic algorithm optimised least squares support vector machine (GA-LSSVM) and the Elman neural network optimised adaptive enhancement algorithm (Elman-Adaboost) models. The final prediction results were integrated using the error reciprocal method, and then the combined prediction model of dust concentration in open-pit mine in winter was constructed. Finally, the sample data is divided into a training set and a testing set in a 7:3 ratio to predict dust concentration, and the model evaluation index and test method are proposed. The results show that, using PM2.5 as an example, the model’s input variables are historical PM2.5 concentration data and external environmental factors selected based on mutual information. The evaluation indexes of the model include the correlation coefficient R2, root mean square error RMSE, and standard deviation SD. The combined model had an R2 of 0.893, RMSE of 11.697, and SD of 22.174. Compared to the GA-LSSVM model and Elman-Adaboost models, the R2 increased by 24.5% and 41.2% respectively, while the RMSE decreased by 31.0% and 36.7% respectively. When compared to the original sample data set SD (23.528), it is evident that the combined model clearly has higher prediction accuracy.

So as to extend the application of upper bound limit analysis for slope stability in open-pit mine, this paper analyzed failure mechanism of rock mass when shear failure occurred based on plastic mechanics principles, and combined with discrete mathematical theory and least square principle to propose a visualization method of logarithmic spiral. At the same time, the visualization method was applied to engineering practice for slope stability in open-pit mine, and cycle algorithm of stability analysis for open-pit mine slope was proposed through energy balance conditions, then stability analysis results were evaluated reasonably through uniting with limit equilibrium method. The results show that visualization method of logarithmic spiral proposed in this paper is highly consistent with original curve, and can ensure correlation coefficient square is greater than 0.9995. What is more, upper bound limit analysis method has a superhigh accuracy in slope engineering. At the same time, the most dangerous sliding surface obtained by this method can satisfy the requirements of velocity separation, which solved velocity problems during the process of slope evolution. Therefore, the method proposed in this paper has a stronger application in the field of open-pit mining.

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations. [ABSTRACT FROM AUTHOR]

The reasonable filling performance of backfill is a prerequisite for the promotion and application of end slope filling mining in open-pit mines. A four-factor, three-stage test was designed to investigate the effects of aggregate gradation, cement-to-sand ratio, fly ash content, and slurry concentration on the working and mechanical properties of backfill. The filling body aggregate originated from the stripping waste rock of an open-pit mine. The main rocks were fine sandstone, marl and mudstone. Results show that, slump is primarily influenced by slurry concentration, aggregate gradation, fly ash content and cement-sand ratio. The 7-day compressive strength is mainly affected by the cement-sand ratio, slurry concentration, fly ash content, and aggregate gradation. The influence on 28-day compressive strength decreases in the following order: cement-sand ratio, aggregate gradation, fly ash content, and slurry concentration. After comprehensive analysis, the optimal ratios are determined as follows: aggregate gradation of 0.4, cement-sand ratio 1:6, fly ash content 20%, and slurry concentration 72%. The conclusions obtained in this study demonstrate the feasibility of using waste rock as a filling material in mines. [ABSTRACT FROM AUTHOR]

In order to study the influence of reclamation of open-pit coal mine dump on soil physical properties, the dump platform of Heidaigou open-pit mine in Zhungeer Banner, Ordos City, Inner Mongolia Autonomous Region, was as the research object. The difference of physical properties in 0-60 cm soil layer among natural landform (ZR), unreclaimed dump (WF) and 5-year reclaimed dump (FK) in mining area were analyzed, the effects of reclamation on soil physical properties of dump were studied by variance analysis and principal component analysis. The results showed that the soil bulk density and gravel content of unreclaimed dumps were significantly higher than those of reclaimed dumps and natural landforms, while the soil moisture content, saturated moisture content and field water holding capacity were lower than those of reclaimed dumps and natural landforms, among which the field water holding capacity was significantly different from those of reclaimed dumps and natural landforms. The correlation analysis and regression equation fitting analysis showed that the gravel content in soil affected soil bulk density and water holding capacity. Reclamation made the soil bulk density and gravel content decrease, and the soil moisture content, saturated water content and field water holding capacity increase. With the increase of soil depth, the soil unit weight, moisture content and saturated moisture content of the dump showed an increasing trend, while the field water holding capacity and gravel content showed a decreasing trend. The comprehensive scores of the 40-60 cm soil of 5-year reclaimed dump, 40-60 cm soil of natural landformand 20-40 cm soil of 5-year reclaimed dump were ranked as 1st, 2nd and 3rd, respectively, which indicated that the reclamation of the dump could improve the soil and optimize the soil texture. The depth of soil improvement by plants could reach 60 cm soil layer in the case of 5 years of reclamation of the dump. Above results provided certain guiding for reclamation work in mining area. [ABSTRACT FROM AUTHOR]

The collapse of open-pit coal mine slopes is a kind of severe geological hazard that may cause resource waste, economic loss, and casualties. On 22 February 2023, a large-scale collapse occurred at the Xinjing Open-Pit Mine in Inner Mongolia, China, leading to the loss of 53 lives. Thus, monitoring of the slope stability is important for preventing similar potential damage. It is difficult to fully obtain the temporal and spatial information of the whole mining area using conventional ground monitoring technologies. Therefore, in this study, multi-source remote sensing methods, combined with local geological conditions, are employed to monitor the open-pit mine and analyze the causes of the accident. Firstly, based on GF-2 data, remote sensing interpretation methods are used to locate and analyze the collapse area. The results indicate that high-resolution remote sensing can delineate the collapse boundary, supporting the post-disaster rescue. Subsequently, multi-temporal Radarsat-2 and Sentinel-1A satellite data, covering the period from mining to collapse, are integrated with D-InSAR and DS-InSAR technologies to monitor the deformation of both the collapse areas and the potential risk to dump slopes. The D-InSAR result suggests that high-intensity open-pit mining may be the dominant factor affecting deformation. Furthermore, the boundary between the collapse trailing edge and the non-collapse area could be found in the DS-InSAR result. Moreover, various data sources, including DEM and geological data, are combined to analyze the causes and trends of the deformation. The results suggest that the dump slopes are stable. Meanwhile, the deformation trends of the collapse slope indicate that there may be faults or joint surfaces of the collapse trailing edge boundary. The slope angle exceeding the designed value during the mining is the main cause of the collapse. In addition, the thawing of soil moisture caused by the increase in temperature and the reduction in the mechanical properties of the rock and soil due to underground voids and coal fires also contributed to the accident. This study demonstrates that multi-source remote sensing technologies can quickly and accurately identify potential high-risk areas, which is of great significance for pre-disaster warning and post-disaster rescue. [ABSTRACT FROM AUTHOR]

Objectives: On February 22, 2023, a large area of slope collapsed in Xinjing Open-Pit Mine, Inner Mongolia Autonomous Region, China. In order to prevent this kind of disaster scientifically, it is necessary to carry out fine monitoring of slope stability in large open-pit mine, so as to obtain the temporal and spatial characteristics of slope deformation comprehensively, and take corresponding prevention measures. Methods: The full scatterer interferometric synthetic aperture radar (FS-InSAR) technique was applied for detailed monitoring of Xinjing Open-Pit Mine, with 24 Sentinel-1 synthetic aperture radar images acquired from September 9, 2021 to August 11, 2022. Fine ground deformation of Xinjing Open-Pit Mine was obtained, and the temporal and spatial distribution characteristics of the deformation were analyzed. Results: For the low-coherence open-pit area, the FS-InSAR technique can obtain fine surface deformation with a density of 4 758 points per km². The deformation anomaly signal of bottom acceleration had appeared since February 2022, before the collapse occurred. The deformation at the bottom of the west side of the south slope is the most serious, with deformation rate more than 200 mm/a, and there is a collapse risk. Conclusions: The FS-InSAR technique can fully retrieve the spatial-temporal distribution of slope deformation before collapse disaster in open-pit mines, which is of great significance for mine safety production in the future. [ABSTRACT FROM AUTHOR]

Among the slope hazards caused by rainfall, not all of them occur directly during storm washout, and the wetting–drying cycles' effect on the rainfall–evaporation process is an important cause of shallow slope instability. In this study, taking the slope of the open-pit coal mine dumps in Cam Pha, in the Quang Ninh region of Vietnam, as the research object, we carry out experiments on the physical properties of the rock body under different wetting–drying cycles, as well as numerical analyses. The results show that the wetting–drying cycles significantly affect the physical and mechanical parameters and permeability of the rock body. In the process of the wetting–drying cycle, a transient saturated zone occurs on the surface of the slope, and the range of the unsaturated zone inside the slope body decreases with the increase in the number of wetting–drying cycles. Moreover, the infiltration line keeps moving downward, but the rate of downward movement is slowed down by the decrease in the gradient of matrix suction affected by rainfall. Under the influence of the wetting–drying cycles, the slope displacement, plastic zone, and maximum shear strain increment range gradually approach the slope surface with the wetting–drying cycles, and the displacement peak gradually increases. A dump is a site for the centralized discharge of mining waste, formed by the crushing and stockpiling of the original rock formation. Bang Nau is the name of the dump considered in this study. After multiple rainfall events, the slope stability under five wetting–drying cycles decreases from 1.721 to 1.055, and the landslide mode changes from a whole landslide to a single-step shallow landslide, with a certain landslide risk. It is necessary to strengthen the slope stability as the landslide risk is very high, and it is necessary to strengthen the monitoring and inspection of the slope. [ABSTRACT FROM AUTHOR]

To study the stability of open-air slope with fault under seepage, this paper uses FLAC3D numerical simulation technology to establish a mechanical model of the sliding body under fault action, and deduce the expression of the stability coefficient of the longitudinal slope, to simulate the stability of the slope with fault under seepage action. The results show that the sensitivity analysis is carried out on four influencing factors such as elastic modulus of rock mass strength, cohesion, internal friction Angle, and tensile strength of rock mass. By analyzing the displacement, stress, strain and safety factor of slope under different working conditions of these four factors, the sensitivity analysis curve of each parameter is obtained. It can be seen from the sensitivity analysis curve that the cohesion of rock mass has the greatest influence on the slope stability, and the elastic modulus has the least influence on the slope stability. The main influencing factors of slope stability are different at different excavation stages. In the early stage of excavation, the main factor affecting slope stability is fault, which gradually changes to seepage in the later stage. This study provides a scientific basis for the future analysis of open-pit slope stability. [ABSTRACT FROM AUTHOR]

Abstract A large number of burnt rocks in some open-pit mines in Xinjiang, Inner Mongolia and Ningxia have a great influence on the blasting effect. For this kind of rock, through the analysis of physical and chemical changes, combined with ANSYS/LS-DYNA and PFC 2D numerical simulation software, a burnt rock model with multiple joint cracks and irregular distribution is constructed to simulate the blasting process of burnt rock under the combined action of stress wave and detonation gas. The results show that the fracture of rock mass affects the propagation of blasting cracks in the fracture area, resulting in stress concentration and stress hindrance. The action time of stress wave is reduced, and the energy of blasting gas is partially absorbed by the fracture, resulting in uneven stress on the burnt rock bench and seriously affecting the bench blasting effect.

Due to the use of heavy industry equipment and frequent mining activities, the rock strata and the surface of Dexing Copper Mine were prone to settlement and deformation. In order to accurately analyze the time series settlement variation of the surface, this paper used Small Baseline Subset InSAR (SBAS-InSAR) technology to obtain 23 Sentinel-1A orbit SAR images covering Dexing Copper Mine for temporal settlement monitoring. The monitoring results show that there are three obvious settlement funnels within the mining area, and the total settlement area is about 7.63 km2, located in the southwest of the Copper Factory, the southwest of Fujiawu Stope and between Duyang Lake and the Copper Factory, the maximum cumulative settlement in the area is −1131.9 mm, and the maximum annual average settlement rate is −375.5 mm/a. In order to analyze the change trend of settlement in mining area timely and accurately, make full use of monitoring data to carry out disaster prevention and warning in mining area, and solve the problem that the prediction accuracy of traditional settlement prediction model is not high, this paper proposes a time series settlement prediction model that takes into account the periodic and seasonal variation of settlement-EMD-ARIMA (Empirical Mode Decomposition-Autoregressive Integrated Moving Average Model), further, perform retrospective predictive analysis of the monitoring data. The results show that compared with the traditional GM (1,1) and ARIMA models, the average RMSE of EMD-ARIMA model is increased by 78.5% and 49.5%, and the average MAE is increased by 74.4% and 52.4%, respectively. The average MAPE increased by 81.2% and 47.9%, respectively. It shows that the EMD-ARIMA model has high prediction accuracy, strong stability and adaptability, and can be used to predict the time series data of mining settlement, which can provide scientific guidance for the safety production of mining areas.

A large number of burnt rocks in some open-pit mines in Xinjiang, Inner Mongolia and Ningxia have a great influence on the blasting effect. For this kind of rock, through the analysis of physical and chemical changes, combined with ANSYS/LS-DYNA and PFC 2D numerical simulation software, a burnt rock model with multiple joint cracks and irregular distribution is constructed to simulate the blasting process of burnt rock under the combined action of stress wave and detonation gas. The results show that the fracture of rock mass affects the propagation of blasting cracks in the fracture area, resulting in stress concentration and stress hindrance. The action time of stress wave is reduced, and the energy of blasting gas is partially absorbed by the fracture, resulting in uneven stress on the burnt rock bench and seriously affecting the bench blasting effect. [ABSTRACT FROM AUTHOR]

The application of an old open-pit lignite mine as an auxiliary reservoir for the supply of the city of La Coruña has involved a detailed analysis of the chemical quality of the vertical profile. The study has shown that a stratified lake is formed where the shape of the filling (first with groundwater and later surface waters from the nearby rivers were added) has influenced the formation of the lake profile. The Meirama mine is an open-pit brown lignite mine located in NW Spain. Exploitation ended in March 2008, leaving a pit of approximately 146 hm3 with a maximum depth of 205 m. The rehabilitation of the pit consisted of the creation of a lake that will serve as an auxiliary water reservoir for the city of La Coruña. The filling process lasted approximately 8 years (March 2008–May 2016) with subterranean and surface contributions from the environment. The formation of an invariant chemocline and a seasonal thermocline was observed. Therefore, in this work, (the first of a series of two articles), an analysis of the evolution of various physicochemical parameters, elements, and compounds at certain heights (the surface, the first 2 m (2 mbs), at 59 masl, and at the bottom (2 masl)). In this first article, the physicochemical parameters of pH, dissolved oxygen, temperature, and some metallic elements (iron and manganese) are analysed. From the analyzed parameters it can be seen the creation of a surface thermocline and a chemocline at a depth of 59 masl with the beginning of the formation of anoxic conditions of the bottom of the pit through the consumption of oxygen. [ABSTRACT FROM AUTHOR]

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Due to the large size of open-pit mines' long-term production scheduling (OPMPS) problem in large-scale deposits, it is challenging to solve that problem as the mixed integer linear programming (MILP) model. This study used an approach of the genetic algorithm (GA) to tackle this challenge. So, in a small hypothetical deposit, based on the blocks in the ultimate pit limit and scenarios with 2–6 phases, net present values (NPV) and computational times obtained from the GA and MILP model were compared to evaluate the GA. Also, the GA was applied to a large-scale deposit to determine the efficiency of the GA in real deposits. The maximum NPV was obtained for the four-phase scenario in the hypothetical deposit and the six-phase scenario in the large-scale deposit. Although the GA's NPV decreased slightly compared to the global optimum solution from the MILP model, the computational time was significantly reduced. [ABSTRACT FROM AUTHOR]

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Copyright of Industrial Minerals & Processing / Huagong Kuangwu yu Jiagong is the property of Industrial Minerals & Processing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Over the past decades, numerical modelling has become a powerful tool for rock mechanics applications. However, the accurate estimation of rock mass input parameters remains a significant challenge. Machine learning (ML) tools have recently been integrated to enhance and accelerate numerical modelling processes. In this paper, we demonstrate the novel use of ML tools for calibrating a state-of-the-art three-dimensional (3D) finite-element (FE) model of a kinematic structurally controlled failure event in an open-pit mine. The failure event involves the detachment of a large wedge, thus allowing for the accurate identification of the geometry of the rock joints. FE models are automatically generated according to estimated ranges of joint input parameters. Subsequently, ML tools are used to analyze the synthetic data and calibrate the strength parameters of the rock joints. Our findings reveal that a relatively small number of models are needed for this purpose, rendering ML a highly useful tool even for computationally demanding FE models. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to quantitatively analyze the roughness of the bench floor during open-pit mine blasting, this study proposes a real-time measuring method for the three-dimensional terrain of the bench floor during the excavation process. Real-time monitoring is conducted at the boundary and discrete internal points of the workbench floor during electric shovel operation, utilizing real-time kinematic global navigation satellite system (RTK-GNSS) positioning technology. An improved convex hull algorithm is introduced to automatically extract the optimal boundary of discrete point clouds based on their spatial distribution characteristics. This study establishes a digital elevation model (DEM) using five interpolation algorithms for 3D terrain visualization simulation. Through cross-validation, a comparative analysis of the DEM accuracy, the simulation results of the ordinary kriging interpolation algorithm were found to be optimized. The optimized interpolation algorithm is applied to simulate the 3D terrain in the Dexing open-pit copper mine, and the relevant terrain parameters were calculated. This dataset can serve as a precise foundation for the real-time path planning of elevation blasting design and ground leveling operations.

The monitoring of open-pit mining and reclamation activities is an important part of ecological protection across various countries. Among the many methods of monitoring open-pit mining areas, satellite remote sensing is the most widely used and effective. However, few works have been conducted to map open-pit mines over a larger geographical scale, or have considered complex land cover types, or a wide variety of mine properties. This work proposes a framework for mapping open-pit mines for areas over complex land cover and mining properties, including preprocessing, classification, and postprocessing steps. First, the pixels that did not contain mines were masked, second the mines were divided into two categories according to their spectral characteristics, then the selected samples and classified to obtain the classification results of mines, and third mis-classified pixels were removed. This work used Landsat images and Google Earth Engine to map the open-pit mines over Shanxi in 5-year steps from 2000 to 2020. The average producer and user accuracy of the results was found to be 79.4% and 83.2% respectively. The experimental results showed that open-pit mining areas in Shanxi first increased and subsequently decreased over the past twenty years. Additionally, the new preprocessing, classification, and postprocessing workflow was found to be effective, especially in environments with more vegetative cover.

Over the past decades, numerical modelling has become a powerful tool for rock mechanics applications. However, the accurate estimation of rock mass input parameters remains a significant challenge. Machine learning (ML) tools have recently been integrated to enhance and accelerate numerical modelling processes. In this paper, we demonstrate the novel use of ML tools for calibrating a state-of-the-art three-dimensional (3D) finite-element (FE) model of a kinematic structurally controlled failure event in an open-pit mine. The failure event involves the detachment of a large wedge, thus allowing for the accurate identification of the geometry of the rock joints. FE models are automatically generated according to estimated ranges of joint input parameters. Subsequently, ML tools are used to analyze the synthetic data and calibrate the strength parameters of the rock joints. Our findings reveal that a relatively small number of models are needed for this purpose, rendering ML a highly useful tool even for computationally demanding FE models.

Objective To address the problem of geological environment destruction in the Ⅳ mining area of Zhangjiagou Limestone Mine in Lintao County, Gansu Province, the spraying regreening technology was used to carry out ecological restoration and management in the test mining area. Methods In this study, 6 kinds of ecological soils with different formulations of foreign soil, organic nutrient soil, soil improvement material compound, and fertilizer and others were selected for planting experiments conducted in the open-pit mine test area and laboratory at the same time, so as to analyse plant growth characteristics under different humidity levels and different mixing ratios of 4 herbs and 2 shrubs. Results The results showed that the formulation of ecological soil affected the growth process of plants.The plant community was more stable when the percentage of foreign soil, organic nutrient soil, soil improvement material compound, and fertilizer and others were 40%, 36%, 20% and 4%, respectively, of the ecological soil and the grass seeds were planted. The plant community with a herb to shrub ratio of 40∶1 was more stable under environmental conditions of 17% to 30% humidity, while the plant community with a herb to shrub ratio of 20∶1 was more stable under the environmental conditions of 30% to 44% humidity. Conclusion The research results can provide a reference for ecological restoration and management of open-pit mines.

The deformation of open-pit mine slopes is influenced by various factors such as geological structure, hydrogeological conditions, mining activities, etc., making the prediction model complex. It is difficult to accurately capture all influencing factors. At present, a large number of monitoring devices are deployed around the slope of open-pit mines to record real-time displacement data of open-pit mine slopes. The data has the features of high-dimensional, temporal correlation, and nonlinear. Traditional slope stability analysis methods cannot effectively predict slope deformation without knowing other conditions and only data, it is necessary to use a data-based model to predict the displacement data of open-pit mine slopes in advance for slope stability analysis. In order to solve the above problems, a deformation prediction model for open-pit mine slopes based on the golden jackal optimized multilayer perception machine (GJO-MLP) is proposed. Each agent in GJO is independent of each other and can accelerate the training process of optimizing MLP through parallel computing. GJO can combine the nonlinear modeling and feature extraction capabilities of MLP, making the optimized MLP more advantageous in dealing with complex problems. To test the feasibility and effectiveness of GJO-MLP, GJO-MLP is compared and analyzed with ant colony algorithm optimization based MLP (ACO-MLP), gravity search algorithm optimization based MLP (GSA-MLP), and differential evolution algorithm optimization based MLP (DE-MLP). The simulation results on six datasets show that under the same experimental conditions, GJO-MLP shows better optimization performance compared to the other three algorithms. The slope deformation prediction model based on GJO-MLP is applied to the slope deformation prediction of Baorixile open-pit mine and Huapingzi slope deformation prediction. The results show that under the same conditions, compared to the other three algorithms, the slope deformation prediction model based on GJO-MLP not only show better predictive performance in predicting slope deformation data, but also has better feasibility and robustness.

Coal mining has a certain influence on and causes disturbances in groundwater. To investigate the variation trend of groundwater around the open-pit mine in grassland area, taking Shengli No. 1 open-pit mine as an example, the impact and variation trend of groundwater level in Quaternary aquifer around the mine area was studied by using the data of hydrological monitoring wells. The results show that the water level around the mining area varies from one year to the next. Since 2008, the water level has experienced a process of reduction, stability and increase. Compared with the background water level value, the current water level of each monitoring well is lower than the background water level. The influence radius calculated by Kusakin formula ranges from 94.15 m to 906.80 m, and the aquifer is heterogeneous. On the basis of the correlations between changes in waterline in monitoring wells and the stope distance, the disturbance radius of open-pit mining on surrounding diving water in grassland area is less than 2000 m. Based on the comprehensive analysis of the alteration of diving waterline and its influencing factors, the main factors affecting the variation in the phreatic water level are atmospheric precipitation, evaporation, groundwater usage and dewatering water. All factors act on the diversification of diving water level synthetically. The internal waste dump of an open-pit mine has a positive effect on the surrounding groundwater recovery. The aim of this study is to reveal the impact of open-pit mining on surrounding groundwater and providing scientific basis for future mining in other open-pit mines.

In mining, deposits are divided into blocks, forming the basis for open-pit mine planning, covering production and haulage route planning. Current studies often stage optimization and lack the consideration of road capacity, leading to suboptimal solutions. A novel approach integrates production scheduling and haulage route planning through a bilevel optimization model. The upper-level model integrates ore mining constraints to establish a mixed-integer production scheduling model, minimizing haulage costs. Spatiotemporal correlation constraints for block mining are determined using a two-stage algorithm. The lower-level model incorporates road capacity, forming a haulage route optimization model based on multicommodity network flow. A solution algorithm with a distance penalty strategy facilitates feedback between the upper and lower levels, achieving optimal solutions. Tested on a real open-pit coal mine with over 5 million blocks, this approach reduces haulage costs by 10.06% compared to stage optimization. Additionally, this approach allows for adjusting haulage demand in both temporal and spatial dimensions, effectively preventing road congestion. This study advances rational mining processes and enhances the efficiency of open-pit mining haulage systems.

Open-pit mining is a cornerstone of industrial raw material extraction, yet it is fraught with safety concerns due to rough operating conditions. The advent of Industry 4.0 has introduced advanced technologies such as AI, the IoT, and autonomous systems, setting the stage for a paradigm shift towards unmanned mining operations. With this study, we addressed the urgent need for safe and efficient production based on intelligent unmanned mining systems in open-pit mines. A collaborative production planning model was developed for an intelligent unmanned system comprising multiple excavators and mining trucks. The model is formulated to optimize multiple objectives, such as total output, equipment idle time, and transportation cost. A multi-objective optimization approach based on the genetic algorithm was employed to solve the model, ensuring a balance among conflicting objectives and identifying the best possible solutions. The computational experiments revealed that the collaborative production planning method significantly reduces equipment idle time and enhances output. Moreover, with the proposed method, by optimizing the configuration to include 6 unmanned excavators, 50 unmanned mining trucks, and 4 unloading points, a 92% reduction in excavator idle time and a 44% increase in total output were achieved. These results show the model’s potential to transform open-pit mining operations by using intelligent planning.