Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Artificial ground freezing of underground mines in cold regions using thermosyphons with air insulation

Current practice of underground artificial ground freezing(AGF)typically involves huge refrigeration systems of large economic and environmental costs.In this study,a novel AGF technique is proposed deploying available cold wind in cold regions.This is achieved by a static heat transfer device called thermosyphon equipped with an air insulation layer.A refrigeration unit can be optionally integrated to meet additional cooling requirements.The introduction of air insulation isolates the thermosyphon from ground zones where freezing is not needed,resulting in:(1)steering the cooling resources(cold wind or refrigeration)towards zones of interest;and(2)minimizing refrigeration load.This design is demonstrated using well-validated mathematical models from our previous work based on two-phase enthalpy method of the ground coupled with a thermal resistance network for the thermosyphon.Two Canadian mines are considered:the Cigar Lake Mine and the Giant Mine.The results show that our proposed design can speed the freezing time by 30%at the Giant Mine and by two months at the Cigar Lake Mine.Further,a cooling load of 2.4 GWh can be saved at the Cigar Lake Mine.Overall,this study provides mining practitioners with sustainable solutions of underground AGF.

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining.Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations.As a result,a reliable roof fall prediction model is essential to tackle such challenges.Different parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research issue.The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls.Data acquired for 37 mines is limited due to several restrictions,which increased the likelihood of incompleteness.Fuzzy logic is a technique for coping with ambiguity,incompleteness,and uncertainty.Therefore,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters.The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

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.

Solution to the Horizontal Crossing Problem of Transportation System at Key Points in Open-Pit Mines

In order to reduce the horizontal crossing transportation problems between coal trucks and stripping trucks,large and small vehicles,and transport trucks and belt conveyors at key points of open pit mine in production,the separate transportation mode of underpass bridge and overpass steel trestle is proposed to optimize the open pit development transportation system,so as to solve the practical problems that the horizontal cross of transport vehicles causes vehicle blockage,affects production schedule and production safety.The results show that the horizontal crossing road can be changed into a separate type of overpass steel trestle,which can realize the classified transportation of large and small vehicles,reduce the traffic density,make vehicles with different functions go their own way,eliminate the hidden danger of traffic accidents,and improve the production efficiency.

Evaluation of Convolutional-Long Short-Term Memory Model in Predicting Surface Displacement of Underground Mines

Surface stability is essential in underground mines health management systems. Unexpected Surface displacement in underground mines could lead to loss of lives, injuries, and economic losses. To reduce or neutralise the adverse effects of surface displacement, it is vital to monitor and accurately predict them and unravel their mechanisms. In recent years, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) have proven effective in predicting complex problems. However, CNN neglects the dynamic dependency of the input in the temporal dimension, which affects surface displacement features. The Convolutional-LSTM model can dynamically learn the temporal dependency among input features via the feedback connections in the LSTM to improve accurate captures of surface displacement features. This study focused on evaluating the C-LSTM model in predicting surface displacement of underground mines and assessed the predictive capabilities and generalisation strength of using hybridised ANN models. Geodetic and geotechnical data gathered from a Gold Mine in Ghana was used. The three models were tested on experimental data collected at Monitoring Scan Point 3. It was observed from the prediction output that all the methods could provide applicable and practical results. However, using indicators like root mean square error (RMSE) and correlation coefficient (R) in assessing the output of the prediction, the C-LSTM had the best prediction output. This study contributes to the advancement of accurate and efficient prediction of surface displacement of underground mines, ultimately enhancing and assisting safety operations.

Mineralogy,microstructures and geomechanics of rock salt for underground gas storage

Rock salt has excellent properties for its use as underground leak‐proof containers for the storage of renewable energy.Salt solution mining has long been used for salt mining,and can now be employed in the construction of underground salt caverns for the storage of hydrogen gas.This paper presents a wide range of methods to study the mineralogy,geochemistry,microstructure and geomechanical characteristics of rock salt,which are important in the engineering of safe underground storage rock salt caverns.The mineralogical composition of rock salt varies and is linked to its depositional environment and diagenetic alterations.The microstructure in rock salt is related to cataclastic deformation,diffusive mass transfer and intracrystalline plastic deformation,which can then be associated with the macrostructural geomechanical behavior.Compared to other types of rock,rock salt exhibits creep at lower temperatures.This behavior can be divided into three phases based on the changes in strain with time.However,at very low effective confining pressure and high deviatoric stress,rock salt can exhibit dilatant behavior,where brittle deformation could compromise the safety of underground gas storage in rock salt caverns.The proposed review presents the impact of purity,geochemistry and water content of rock salt on its geomechanical behavior,and thus,on the safety of the caverns.

Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

Application of open-pit and underground mining technology for residual coal of end slopes

Given the conditions of residual coal from the boundary of a flat dipping open-pit mine,which uses strip areas mining and inner dumping with slope-covering,we propose an open-pit and underground integrated mining technology for residual coal of end slopes.In the proposal a conveyance road and ventilation conveyance near the slope are built,corresponding to the pit mining area and the surface coal mine dump,as well as an interval haulage tunnel and air-inlet tunnel.The outcome shows that such mining method may reduce the effect to slope stability from underground mining,it does not affect the dumping advance and has a high recovery rate of residual coal resources.The working face is timbered by single hydraulic props,transported by a scraper conveyor and supported by coal walls.This method of mining is one of layered top coal caving,with high resource recovery,low production cost where positive economic benefit can be realized.

Fire behavior of mining vehicles in underground hard rock mines

The results from a number of investigations and fire experiments are presented and analyzed in order to characterize the fire behavior of mining vehicles in underground hard rock mines. The analysis also includes fire safety and fire protection measures with respect to the mining vehicle fire behavior.Earlier studies on fires in underground hard rock mines have shown that vehicles or mobile equipment are the dominant sources of fire. A better knowledge about the fire behavior of vehicles in underground hard rock mines is therefore needed. During the analysis the direction and flow rate of the ventilation in a drift was found to have a significant impact on the fire behavior, causing for example flame tilt with rapid fire spread. The shielded sections of a vehicle will be less affected by the ventilation flow resulting in for example a decreased flame spread. It was also found that spray fires may result in considerable heat release rate but are generally of shorter duration and will not make any significant contributions to the overall heat release rate of the fully developed vehicle fire. The fire duration of a loader tire from a full-scale fire experiment was found to be at least 200 min and will largely determine the total fire duration of the vehicle. A different scenario with different conditions with for example a slower flame spread resulted in an even longer fire duration. The radiative and convective fraction will be a key factor when determining the heat transfer mechanisms involved in a fire and will vary from material to material.Calculations show that the radiative fraction of the tire fires on two mining vehicles is significantly lower than found in earlier experiments. The design and construction of the mining vehicle will have an important impact on the fire behavior and could possibly mitigate the consequences of a fire and allow fire personnel to extinguish a fire that otherwise would have had a too high heat release rate.

Numerical simulation study of the influence on stability of slope by underground mining under opencast coal mine slope

In view of the study on mining transferred from open-pit to underground, the research on the problem of the stabil- ity of slope is less. This article combined the actual situation of the Gaohai Coal Mine in Fuxin City and set up a three-dimensional model of the part of Huizhou open-pit slope by the finite difference software. Through the three-dimensional numerical simulation study of the influence on the stability of slope by underground mining, the basic characteristics of the open-pit slope deformation and the situation of basic stability were discussed. The simulation results of the mining slope of the displacement and deformation analysis of the state for mining provide a reference to the slope stability research.

Evaluation of the impact of commodity price change on mine plan of underground mining

Fluctuations in commodity prices should influence mining operations to continually update and adjust their mine plans in order to capture additional value under new market conditions. One of the adjustments is the change in production sequencing. This paper seeks to present a method for quantifying the net present value(NPV) that may be directly attributed to the change in commodity prices. The evaluation is conducted across ten copper price scenarios. Discrete event simulation combined with mixed integer programming was used to attain a viable production strategy and to generate optimal mine plans. The analysis indicates that an increase in prices results in an increased in the NPV from$96.57M to $755.65M. In an environment where mining operations must be striving to gain as much value as possible from the rights to exploit a finite resource, it is not appropriate to keep operating under the same mine plan if commodity prices alter during the course of operations.

Safety analysis of Sormeh underground mine to improve sublevel stoping stability

In underground mines,sublevel stoping is used among a variety of different methods for mining an orebody,which creates large underground openings.In this case,the stability of these openings is affected by a number of factors,including the geometrical characteristics of the rock and mining-induced stresses.In this study,a sensitivity analysis was conducted with the numerical,squat pillar,and Mathews stability methods using the Taguchi technique to properly understand the influence of geometric parameters and stress on stope stability according to Sormeh underground mine data.The results show a full factorial analysis is more reliable since stope stability is a complex process.Furthermore,the numerical results indicate that overburden stress has the most impact on stope stability,followed by stope height.However,the results obtained with Mathews and squat pillar methods show that stope height has the greatest impact,followed by overburden stress and span.It appears that these methods overestimate the impact of stope height.Therefore,it is highly recommended that Mathews and squat pillar methods should not be used in high stope that is divided with several sill pillars.Nonetheless,Mathews method cannot accurately predict how the sill pillar impacts the stope stability.In addition,numerical analysis shows that all geometric parameters affect the roof safety factor,whereas the sill pillar has no significant influence on the safety factor of the hanging wall,which is primarily determined by the stope height–span ratio.

Study on the Law of the Movement and Damage to Slope with the Combination of Underground Mining and Open-Pit Mining

Under circumstances in which both underground mining and open-pit mining are employed, the mining effects of two approaches will be superposed and the mining slope will receive several induced stress fields, which makes the sliding mechanism and deformation law of slope rock mass more complicated. This paper, targeting at the east slope of Antaibao Mine with the joint employment of underground mining and open-pit mining, aims to study the moving law of the slope rock mass and the damage mechanism to the overburden of the goaf by numerical simulation. It is supposed that models of possible damage to the slope could be explored for guidance to safety-production of the mine.

Research on pumped storage and complementary energy development models for abandoned mines in China

Within the framework of achieving carbon neutrality,various industries are confronted with fresh challenges.The ongoing process of downsizing coal industry operations has evolved into a new phase,with the burgeoning proliferation of abandoned mines posing a persistent issue.Addressing the challenges and opportunities presented by these abandoned mines,this paper advocates for a scientific approach centered on the advancement of pumped storage energy alongside gas-oil complementary energy.Leveraging abandoned mine tunnels to establish pumped storage power stations holds significant ecological and economic importance for repurposing these sites.This initiative not only serves as an effective means to restore the ecological balance in mining regions but also provides an environmentally friendly approach to repurposing abandoned mine tunnels,offering a blueprint for economically viable pumped storage power stations.This article delineates five crucial scientific considerations and outlines seven primary models for the utilization of abandoned mine sites,delineating a novel,comprehensive pathway for energy and power development that emphasizes multi-energy complementarity and synergistic optimization within abandoned mines.

Optimal mining sequence for coal faces under a bedding slope:insight from landslide prevention

Repetitive mining beneath bedding slopes is identified as a critical factor in geomorphic disturbances, especially landslides and surface subsidence. Prior research has largely concentrated on surface deformation in plains due to multi-seam coal mining and the instability of natural bedding slopes, yet the cumulative impact of different mining sequences on bedding slopes has been less explored. This study combines drone surveys and geological data to construct a comprehensive three-dimensional model of bedding slopes. Utilizing FLAC3D and PFC2D models, derived from laboratory experiments, it simulates stress, deformation, and failure dynamics of slopes under various mining sequences. Incorporating fractal dimension analysis, the research evaluates the stability of slopes in relation to different mining sequences. The findings reveal that mining in an upslope direction minimizes disruption to overlying strata. Initiating extraction from lower segments increases tensile-shear stress in coal pillar overburdens, resulting in greater creep deformation towards the downslope than when starting from upper segments, potentially leading to localized landslides and widespread creep deformation in mined-out areas. The downslope upward mining sequence exhibits the least fractal dimensions, indicating minimal disturbance to both strata and surface. While all five mining scenarios maintain good slope stability under normal conditions, recalibrated stability assessments based on fractal dimensions suggest that downslope upward mining offers the highest stability under rainfall, contrasting with the lower stability and potential instability risks of upslope downward mining. These insights are pivotal for mining operations and geological hazard mitigation in multi-seam coal exploitation on bedding slopes.

Smelting,Underground Mining,Smoking,and Lung Cancer:A Case-Control Study in a Tin Mine Area

An increased risk of lung cancer in the Dachang tin mine of Guangxi has been reported.To investigate the factors contributing to the excessive risk of lung cancer,we conducted a matched case-control study in the mine area and analyzed the effects of multiple factors,such as living and housing conditions,occupational exposure,and smoking,with the methods of conditional logistic regression.The case series consisted of 69 patients with primary bronchial cancer,55 of whom had died.The control series consisted of 138 individuals,55 of whom were deceased.The results showed that the factors contributing to the excessive risk of lung cancer in the mine area related mainly to occupational exposure.The significant risk factors were time of exposure to smelting,time of exposure to underground mining,and age at which underground mining was begun.In study model II where living controls were used,daily consumption of cigarettes was an additional risk factor.Furthermore,there was a synergistic action among these factors.The relation of the risk factors to lung cancer is discussed.1989 Academic Press.Inc.

3DMine软件在罗河铁矿测量中的应用

在地下矿山测量中,3DMine软件具有高效处理数据、直观反映采空区或其他井下巷道实际情况、准确提供充填空间体积与质量等优势。通过分析3DMine在罗河地下铁矿的建模过程和模型剖面,进一步判断采空区体积以及超欠挖情况。结果表明,相较于传统测量方式,3DMine软件能更加便捷直观地分析矿山数据,并且各类数据利用率也较高。同时也证明了3DMine矿业软件在矿山生产过程中具备巨大优势,并为地下矿山测量技术的发展提供了有益参考。

Failure characteristics and its influencing factors of talus-derived rock mass during open-pit mining

The failure characteristic of talus-derived rock mass continues to challenge quantitative hazard assessments in open-pit mining. Physical model test was used to assess the failure modes and mechanisms on talus-derived rock mass. The different types of failure modes of the talus-derived rock mass were introduced and a possible failure mechanism relation between the failure zone and the structure of the talus-derived rock mass was also shown. The physical model test results indicate that the rainfall has significant influence on the stability and failure modes of talus-derived rock mass during open-pit mining. The development of the seepage area caused by rainfall initiates the localized failure in that particular area, and the initiation of localized instability is mainly induced by stress changes concentrated in the seepage area.