A semi-infinite beam theoretical model on predicting rock slope subsidence induced by underground mining

When the mining goaf is close to the cliff,rock slope subsidence induced by underground mining is significantly affected by its boundary conditions.In this study,an analytical method is proposed by considering the key strata as a semi-infinite Euler-Bernoulli beam rested on a Winkler foundation with a local subsidence area.The analytical solutions of deflection are derived by analyzing the boundary and continuity conditions of the cliff.Then,the analytical solutions are verified by the results from experimental tests,FEM and InSAR,respectively.After that,the influence of changing parameters on deflections is studied with sensitivity analysis.The results show that the distance between goaf and cliff significantly affects the deflection of semi-infinite beam.The response of semi-infinite beam is obviously determined by the length of goaf and the bending stiffness of beam.The comparisons between semi-infinite beam and infinite beam illustrate the ascendancy of the improved model in such problems.

Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring

The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.

InSAR-derived surface deformation characteristics and mining subsidence parameters in mountain coal mines

Mining-induced surface deformation disrupts ecological balance and impedes economic progress.This study employs SBAS-InSAR with 107-view of ascending and descending SAR data from Sentinel-1,spanning February 2017 to September 2020,to monitor surface deformation in the Fa’er Coal Mine,Guizhou Province.Analysis on the surface deformation time series reveals the relationship between underground mining and surface shifts.Considering geological conditions,mining activities,duration,and ranges,the study determines surface movement parameters for the coal mine.It asserts that mining depth significantly influences surface movement parameters in mountainous mining areas.Increasing mining depth elevates the strike movement angle on the deeper side of the burial depth by 22.84°,while decreasing by 7.74°on the shallower side.Uphill movement angles decrease by 4.06°,while downhill movement angles increase by 15.71°.This emphasizes the technology's suitability for local mining design,which lays the groundwork for resource development,disaster prevention,and ecological protection in analogous contexts.

Experimental investigation of the inhibition of deep-sea mining sediment plumes by polyaluminum chloride

Deep-sea sediment disturbance may occur when collecting polymetallic nodules,resulting in the creation of plumes that could have a negative impact on the ecological environment.This study aims to investigate the potential solution of using polyaluminum chloride(PAC)in the water jet.The effects of PAC are examined through a self-designed simulation system for deep-sea polymetallic nodule collection and sediment samples from a potential deep-sea mining area.The experimental results showed that the optimal PAC dose was found to be 0.75 g/L.Compared with the test conditions without the addition of PAC,the presence of PAC leads to a reduction in volume,lower characteristic turbidity,smaller diffusion velocity,and shorter settling time of the plume.This indicates that PAC inhibits the entire development process of the plume.The addition of PAC leads to the flocculation of mm-sized particles,resulting in the formation of cm-sized flocs.The flocculation of particles decreases the rate of erosion on the seabed by around 30%.This reduction in erosion helps to decrease the formation of plumes.Additionally,when the size of suspended particles increases,it reduces the scale at which they diffuse.Furthermore,the settling velocity of flocs(around 10^(-2) m/s)is much higher that of compared to sediment particles(around 10^(-5) m/s),which effectively reduces the amount of time the plume remains in suspension.

Ground response and failure mechanism of gob-side entry by roof cutting with hard main roof

This study is the result of long-term efforts of the authors’team to assess ground response of gob-side entry by roof cutting(GSERC)with hard main roof,aiming at scientific control for GSERC deformation.A comprehensive field measurement program was conducted to determine entry deformation,roof fracture zone,and anchor bolt(cable)loading.The results indicate that GSERC deformation presents asymmetric characteristics.The maximum convergence near roof cutting side is 458 mm during the primary use process and 1120 mm during the secondary reuse process.The entry deformation is closely associated with the primary development stage,primary use stage,and secondary reuse stage.The key block movement of roof cutting structure,a complex stress environment,and a mismatch in the supporting design scheme are the failure mechanism of GSERC.A controlling ideology for mining states,including regional and stage divisions,was proposed.Both dynamic and permanent support schemes have been implemented in the field.Engineering practice results indicate that the new support scheme can efficiently ensure long-term entry safety and could be a reliable approach for other engineering practices.

Identified the hydrochemical and the sulfur cycle process in subsidence area of Pingyu mining area using multi-isotopes combined with hydrochemistry methods

Groundwater serves as an important water source for residents in and around mining areas.To achieve scientific planning and efficient utilization of water resources in mining areas,it is essential to figure out the chemical formation process and the ground water sulfur cycle that transpire after the coal mining activities.Based on studies of hydrochemistry and D,^(18)O-H_(2)O,^(34)S-SO_(4)isotopes,this study applied principal component analysis,ion ratio and other methods in its attempts to reveal the hydrogeochemical action and sulfur cycle in the subsidence area of Pingyu mining area.The study discovered that,in the studied area,precipitation provides the major supply of groundwater and the main water chemistry effects are dominated by oxidation dissolution of sulfide minerals as well as the dissolution of carbonate and silicate rocks.The sulfate in groundwater primarily originates from oxidation and dissolution of sulfide minerals in coal-bearing strata and human activities.The mixed sulfate formed by the oxidation of sulfide minerals and by human activities continuously recharges the groundwater,promoting the dissolution of carbonate rock and silicate rock in the process.

A review of monitoring,calculation,and simulation methods for ground subsidence induced by coal mining

Subsidence data acquisition methods are crucial to mining subsidence research and an essential component of achieving the goal of environmentally friendly coal mining.The origin and history of the existing methods of field monitoring,calcula-tion,and simulation were introduced.It summarized and analyzed the main applications,flaws and solutions,and improve-ments of these methods.Based on this analysis,the future developing directions of subsidence data acquisition methods were prospected and suggested.The subsidence monitoring methods have evolved from conventional ground monitoring to combined methods involving ground-based,space-based,and air-based measurements.While the conventional methods are mature in technology and reliable in accuracy,emerging remote sensing technologies have obvious advantages in terms of reducing field workload and increasing data coverage.However,these remote sensing methods require further technological development to be more suitable for monitoring mining subsidence.The existing subsidence calculation methods have been applied to various geological and mining conditions,and many improvements have already been made.In the future,more attention should be paid to unifying the studies of calculation methods and mechanical principles.The simulation methods are quite dependent on the similarity of the model to the site conditions and are generally used as an auxiliary data source for subsidence studies.The cross-disciplinary studies between subsidence data acquisition methods and other technologies should be given serious consideration,as they can be expected to lead to breakthroughs in areas such as theories,devices,software,and other aspects.

Forecasting the Academic Performance by Leveraging Educational Data Mining

The study aims to recognize how efficiently Educational DataMining(EDM)integrates into Artificial Intelligence(AI)to develop skills for predicting students’performance.The study used a survey questionnaire and collected data from 300 undergraduate students of Al Neelain University.The first step’s initial population placements were created using Particle Swarm Optimization(PSO).Then,using adaptive feature space search,Educational Grey Wolf Optimization(EGWO)was employed to choose the optimal attribute combination.The second stage uses the SVMclassifier to forecast classification accuracy.Different classifiers were utilized to evaluate the performance of students.According to the results,it was revealed that AI could forecast the final grades of students with an accuracy rate of 97%on the test dataset.Furthermore,the present study showed that successful students could be selected by the Decision Tree model with an efficiency rate of 87.50%and could be categorized as having equal information ratio gain after the semester.While the random forest provided an accuracy of 28%.These findings indicate the higher accuracy rate in the results when these models were implemented on the data set which provides significantly accurate results as compared to a linear regression model with accuracy(12%).The study concluded that the methodology used in this study can prove to be helpful for students and teachers in upgrading academic performance,reducing chances of failure,and taking appropriate steps at the right time to raise the standards of education.The study also motivates academics to assess and discover EDM at several other universities.

Tailings Dam Mining, Theoretical Considerations, and Circular Economy: A Review

Mining in tailings dams has emerged as a strategic alternative for mining companies for both economic and environmental reasons. Owing to technological limitations in recent decades, many of these dams have high metal contents, emphasizing the need to evaluate the quality of these residues, especially considering the technological advancements in current concentration plants. An economic viability analysis associated with reusing these materials is crucial. From an environmental point of view, improving mining techniques for dams by considering both safety and feasibility is an advantageous option in decommissioning processes and alignment in the circular economy. In this context, representing these tailings in terms of grade quality and granulometry, as well as the associated contaminants, is essential. Geostatistical estimation and simulation methods are valuable tools for modeling tailings bodies, but they require a reliable sampling campaign to ensure acceptably low errors. From an operational perspective, tailings recovery can be conducted via dry methods, such as mechanical excavation, or hydraulic methods, such as dredging or hydraulic blasting. Dredging is a commonly used method, and cutter suction dredgers, which require pumping to transport fragmented material, are the most commonly used tools. In this paper, some practical applications of geostatistical methods for resource quantification in tailings dams will be discussed. Additionally, the main mining methods for tailings recovery in dams will be presented. Emphasis will be given to the dredging method, along with the key analysis parameters for sizing dredgers, pumps, and pipelines.

Monitoring large-area mining subsidence by GNSS based on IGS stations

In order to monitor large-area mining subsidence accurately, a high-precision global navigation satellite system （GNSS） monitoring network was established based on the nearby international GNSS service （IGS） stations taken as reference points. Given the non-linear motions of IGS stations, the robust Kalman filtering （RKF） model was presented to determine the datum of multi-period monitoring network considering the velocity and weekly solution of IGS stations. The theory proposed was applied to monitoring mining subsidence in northern Anhui coal mine in China. According to the case study, the RKF model to establish monitoring datum is better than the prediction method and the weekly solution from IGS analysis centers （ACs）, and the corresponding precision of deformation can reach up to millimeter level with 4 h observation. The research provides an efficient and accurate approach for monitoring large-area mining subsidence.

Mechanism of subsidence-buckling and instability of slopes in thick-layered rigid rock under mining

The deformation and failure of mining slopes in layered rocks predominantly result from shear landslides.However,the instability process of the Pusa rock avalanche in Guizhou,China,revealed a unique damage phenomenon:prominent breaking and toppling of rock blocks occurred in the central section of the mountain,with a lack of commonly observed shear landslide features.This paper aims to investigate the underlying reasons behind this distinctive damage pattern.The study employs various methods including geological survey,UAV aerial survey,physical simulation,and discrete element numerical simulation.The findings indicate that the geological conditions,characterized by a hard upper layer and a soft lower layer along with underground mining activities,play a significant role in triggering the landslide.Furthermore,the presence of a columnar structured rock mass emerges as the primary factor influencing the instability of the Pusa rock avalanche.To elucidate the mining failure mechanism of the rock mass with vertical joints,we propose a"subsidence-buckling"failure model.Following the subsidence and collapse of the roof rock mass in the goaf,the columnar rock mass in the upper and middle portions of the slope undergoes deflection and deformation,forming a three-hinged arch structure.This structural configuration converts the pressure exerted by the overlying rock mass into both vertical pressure and lateral thrust.Under the influence of external loads,the slope experiences buckling failure,ultimately leading to instability upon fragmentation.By shedding light on these findings,this study contributes to a better understanding of the spatiotemporal evolution of mining slope fractures and their impact on slope stability.

Spatial prediction of soil organic carbon in coal mining subsidence areas based on RBF neural network

A quantitative research on the effect of coal mining on the soil organic carbon(SOC)pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-carbon mining.Moreover,the spatial prediction model of SOC content suitable for coal mining subsidence area is a scientific problem that must be solved.Tak-ing the Changhe River Basin of Jincheng City,Shanxi Province,China,as the study area,this paper proposed a radial basis function neural network model combined with the ordinary kriging method.The model includes topography and vegetation factors,which have large influence on soil properties in mining areas,as input parameters to predict the spatial distribution of SOC in the 0-20 and 2040 cm soil layers of the study area.And comparing the prediction effect with the direct kriging method,the results show that the mean error,the mean absolute error and the root mean square error between the predicted and measured values of SOC content predicted by the radial basis function neural network are lower than those obtained by the direct kriging method.Based on the fitting effect of the predicted and measured values,the R^(2) obtained by the radial basis artificial neural network are 0.81,0.70,respectively,higher than the value of 0.44 and 0.36 obtained by the direct kriging method.Therefore,the model combining the artificial neural network and kriging,and considering environmental factors can improve the prediction accuracy of the SOC content in mining areas.

Instability mechanism of mining roadway passing through fault at different angles in kilometre-deep mine and control measures of roof cutting and NPR cables

The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.

An improved influence function method for predicting subsidence caused by longwall mining operations in inclined coal seams

Prediction of surface subsidence caused by longwall mining operation in inclined coal seams is often very challenging. The existing empirical prediction methods are inflexible for varying geological and mining conditions. An improved influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, the original Knothe function has been transformed to produce a continuous and asymmetrical subsidence influence function. The empirical equations for final subsidence parameters derived from col- lected longwall subsidence data have been incorporated into the mathematical models to improve the prediction accuracy. A number of demonstration cases for longwall mining operations in coal seams with varying inclination angles, depths and panel widths have been used to verify the applicability of the new subsidence prediction model.

Subsidence control and farmland conservation by solid backfilling mining technology

Solid backfilling mining technology, which decreases the height of fissure zone and caving zone, and alleviates the subsidence, is a new technology for farmland conservation. Based on the situation analysis of farmland destruction in mining area, three ways for farmland protection were proposed. In order to improve the feasibility of this technology, the limited filling materials should be used to increase resources recovery ratio, and then the surplus materials could be backfilled into goaf. An index, namely farmland conservation ability, was put forward to optimize the ways for farmland conservation. At last, the Wanbei coal mine was taken as a case for farmland conservation. It was shown that 3240 t dull coal was substituted and 52 hm2 farmland was conserved by solid backfilling mining in this coal mine.

The influence of inter-band rock on rib spalling in longwall panel with large mining height

In order to improve rib stability,failure criteria and instability mode of a thick coal seam with inter-band rock layer are analysed in this study.A three-dimensional mechanical model is established for the rib by considering the rock layer.A safety factor is defined foy the rib,and it is observed that the safety factor exhibits a positive correlation with the thickness and strength of the inter-band rock.A calculation method for determining critical parameters of the rock layer is presented to ensure the rib stability.It is revealed that incomplete propagation of the fracture at the hard rock constitutes a fundamental prerequisite for ensuring the rib stability.The influence of the position of the inter-band rock in the coal seam on failure mechanism of the rib was thoroughly investigated by developing a series of physical models for the rib at the face area.The best position for the inter-band rock in the coal seam is at a height of 1.5 m away from the roof line,which tends to provide a good stability state for the rib.For different inter-band rock positions,two ways of controlling rib by increasing supports stiffness and flexible grouting reinforcement are proposed.

Quantitative evaluation of soil erosion of land subsided by coal mining using RUSLE

Based on a RUSLE model, we identified the key factors of the impact on soil erosion induced by coal min- ing subsidence. We designed a method for predicting/.S factors of a mining subsidence basin, using ana- lytical GIS spatial technology. Using the Huainan mining area as an example, we calculated the modulus of erosion, its volume and classified the grade of soil erosion for both the original area and the subsidence basin. The results show that the maximum modulus of erosion and the volume of erosion of the subsi- dence basin without water logging would increase by 78% and 23% respectively compared with the ori- ginal situation. The edge of the subsidence basin, where the land subsidence was uneven, is subject to the greatest acceleration in soil erosion. In the situation of water logging after subsidence, the maximum modulus of erosion would decrease if the accumulated slope length were reduced. This maximum mod- ulus around the water logged area within the subsidence basin is equal to that without water logging, while the total volume of erosion decreases. Therefore, mining subsidence aggravates soil erosion espe- cially at the edge of basins where water and soil conservation measures should be taken.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

Sustainable Mining in the Era of Artificial Intelligence

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

Evaluation of roof cutting by directionally single cracking technique in automatic roadway formation for thick coal seam mining

Automatic roadway formation by roof cutting is a sustainable nonpillar mining method that has the potential to increase coal recovery,reduce roadway excavation and improve mining safety.In this method,roof cutting is the key process for stress relief,which significantly affects the stability of the formed roadway.This paper presents a directionally single cracking(DSC)technique for roof cutting with considerations of rock properties.The mechanism of the DSC technique was investi-gated by explicit finite element analyses.The DSC technique and roof cutting parameters were evaluated by discrete element simulation and field experiment.On this basis,the optimized DSC technique was tested in the field.The results indicate that the DSC technique could effectively control the blast-induced stress distribution and crack propagation in the roof rock,thus,achieve directionally single cracking on the roadway roof.The DsC technique for roof cutting with optimized parameters could effectively reduce the deformation and improve the stability of the formed roadway.Field engineering application verified the feasibility and effectiveness of the evaluated DSC technique for roof cutting.