Deep Mining Research Articles

Multi-Objective Optimization for Controlling Conflicts in Roadway Surrounding Rock Induced by Floor Stress-Relief Groove

This paper studies the effectiveness of the stress-relief groove on the floor of deep coal roadway and determines the influence of the stress-relief groove parameters on the surrounding rock through qualitative analysis. Based on the displacement conflict problem, evaluation indicators were established, and the optimal solution set was obtained. The innovations of this research include: 1. For geotechnical numerical simulations, novel stress monitoring and plastic zone monitoring techniques have been introduced to accurately reflect the condition of the surrounding rock; 2. The effects of floor relief grooves in deep roadway on surrounding rock have been analyzed, and the advantages and utilities of central and corner relief grooves have been determined; 3. The usability of small datasets has been enhanced by applying SEGA to optimize machine learning models with data augmentation techniques; 4. Multi-objective optimization algorithms have been applied to geotechnical engineering, providing valuable references for decision making. The results demonstrate that multi-objective optimization can significantly enhance the effectiveness of surrounding rock control, resolve conflicts, and achieve more reasonable construction plans. This research provides new theoretical foundations and practical guidance for deep mine roadway-surrounding rock control.

Numerical Investigation with Failure Characteristic Analysis and Support Effect Evaluation of Deep-Turning Roadways

In recent years, tunnel-boring machines (TBMs) have been widely applied in deep coal mining. Turning is an inevitable challenge in TBM tunneling, and a TBM turning roadway exhibits greater instability than a straight roadway, as engineering experience has indicated. This study aimed to explore the failure mechanism and evaluate the support performance of a deep-turning roadway. Several numerical models were established to investigate the deformation of the roadway, the stress distribution, and the failure zone of the surrounding rocks under different tunneling conditions. The results show that the tunneling depth influences the failure pattern of the turning roadway: deep tunneling with high in situ stress can cause asymmetric failure of the turning roadway, while shallow tunneling with low in situ stress does not. Moreover, the change in turning radius, namely the change in roadway geometry, does not influence the stability of the turning roadway. In addition, the support actions for both the straight and turning roadways do not differ significantly, and the amount of controlled deformation of the surrounding rocks is proportional to their natural deformation.

Identification of apple watercore based on ConvNeXt and Vis/NIR spectra

This paper proposes a method for discriminating between normal apples and watercore apples using visible/near-infrared spectroscopy technology, which combines Gramian Angular Fields (GAF) encoding technology and the ConvNeXt deep learning network. The existing feature extraction methods for visible/near-infrared spectroscopy data do not perform deeper information mining on the extracted features, which results in the quality of the established model being entirely determined by the extracted features. Additionally, the process of building a visible/near-infrared spectroscopy data classification model is complex and time-consuming, and the accuracy of the established model is not high. To address these issues, the experimental visible/near-infrared spectroscopy data of apples was first transformed into two-dimensional images using Gramian Angular Summation Fields (GASF) and Gramian Angular Difference Fields (GADF) with sizes of 64, 128, 256, and 512. These images were then input into the ConvNeXt network, and the performance of different encoding methods and sizes was compared. The results showed that, under the conditions provided in this paper, the GADF encoding method with a size of 256 achieved the highest classification accuracy of 98.48%. Next, ResNet, EfficientNet, and RegNet deep learning networks were selected to classify the encoded images under the same conditions. The results above indicate that the apple variety discrimination method based on GAF encoding technology and ConvNeXt network combined with visible/near-infrared spectroscopy technology can achieve deep information mining of visible/near-infrared spectroscopy data and provide a relatively simple method for establishing qualitative classification models of visible/near-infrared spectroscopy. This method has a relatively excellent discrimination effect between normal apples and watercore apples.

Characteristics of rock strength failure and identification of hazardous areas in the roof of deep mining stope

Characteristics of rock strength failure and identification of hazardous areas in the roof of deep mining stope

Mechanism and prevention of coal bursts in gob-side roadway floor under thick and hard roof in the deep mining area of Ordos

The complex stress environment in deep roadways, often exacerbated by thick and hard strata, frequently precipitates coal bursts, posing significant safety hazards. This paper investigates the mechanisms and preventive methods for coal bursts in the gob-side roadway floor (GSRF) under thick and hard roof in the Ordos region, China. First, the stress-distributing characters of GSRF were analyzed then a stress calculation formula was derived. A mechanical model was developed to determine the critical stress for buckling failure of the roadway floor strata. Criteria for the bursting instability of GSRF were then established. The lateral static load from the adjacent gob, the advancing static load from the working face, and the disturbance load from overlying thick and hard roof fractures combine to transmit high loads and energy to the roadway floor via the “roof → rib → floor” pathway, causing increased stress concentration and energy accumulation. When the conditions satisfy the criteria for bursting instability, coal bursts can occur on the roadway floor. To mitigate dynamic load disturbances, the paper proposes roof regional fracturing and abrasive water jet axial roof cutting. Hydraulic reaming of gutters in the roadway ribs and deep hole blasting at the roadway bottom corners are offered to alleviate the static loads on the surrounding rock. The implementation of targeted prevention measures for dynamic and static loads effectively reduces coal bursts in GSRF. These findings offer an example of preventing and controlling coal bursts in other mines of the Ordos region with comparable geological conditions.

Study on the mechanism and prevention system of creep induced instability of isolated coal pillars considering time effect

In response to the frequent occurrence of impact events in isolated coal pillars between the upper (lower) mountain areas of mining areas under conditions without obvious mining disturbance, this study takes multiple isolated coal pillar impact events that occurred in Zhaolou Coal Mine and Gengcun Coal Mine as examples. It conducts a mechanism study on the creep-induced impact ground pressure of isolated coal pillars considering the time effect. The occurrence of such impact ground pressure accidents often exhibits significant “lag” and “spontaneity”. Due to the unclear mechanism of occurrence and the difficulty in grasping the unloading timing, this type of impact ground pressure has become a typical hidden disaster, posing a serious threat to the deep mining of coal mines. Based on the analysis of the creep mechanical properties of coal and rock mass, the uniaxial compression acoustic emission creep test of coal body, and the FLAC3D numerical simulation, a creep instability impact mechanical model of coal and rock mass is established. This model reveals the mechanism of creep instability impact and the stress evolution law of coal and rock mass during creep. The mechanical and energy criteria for the occurrence of impact ground pressure in isolated coal pillars under the action of unstable creep are proposed. The study shows that the action of high ground stress is a necessary condition for the occurrence of "lag-type" impact ground pressure in isolated coal pillars. Long-term unstable creep will weaken the support strength of the entry. When the elastic energy accumulated in the isolated coal pillar exceeds its ultimate bearing capacity, impact instability will occur. Based on the mechanism of occurrence of such impact accidents, targeted deep hole blasting unloading measures are proposed, providing a good reference value for the prevention and control of "lag-type" impact ground pressure accidents in isolated coal pillars.

Study on Coal Seam Roof Failure Based on Optical Fiber Acoustic Sensing and the Parallel Electrical Method

As China enters the stage of deep coal mining, the accidents caused by roof failure pose increasingly serious threats. Current research on roof failure zones often use single methods, but single geophysical data may result in multisolution issues during interpretation. This paper employed similar simulation experiments, exploring the strain failure characteristics and the changes in apparent resistivity caused by stress variations, taking the 11-3106 working face of a mining area as the research object. Through optical fiber strain and apparent resistivity, the locations and degrees of fracture in postmining rock strata were identified. The feasibility of using distributed optical fiber sensing and the parallel electrical method for qualitative and quantitative analysis of mining-induced fractures was verified. The results showed that optical fiber strain increased significantly at the location of rock fracture, with apparent resistivity anomalies rising correspondingly. The peak strain region corresponded well with the region of apparent resistivity anomalies. In a similar simulation with a geometric ratio of 1:100, the height of the caving zone was measured to be 31.65 cm, with a caving-to-mining ratio of 6.33. In the field working face, the caving zone height was 29.47 m, with a caving-to-mining ratio of 6.01, consistent with the actual conditions of the 11-3106 working face.

Block method of mining quarry fields as a tool to reduce environmental impact in conditions of intensification of production

Relevance. The intensification of open-pit mining in the coal basins of the Russian Federation is accompanied by an increase in negative impact on the environment. Directly in Kuzbass, the environment is exposed to the impact of the coal industry, especially when conducting open-pit mining using deep mining systems, with external dumping, which is accompanied by the withdrawal of a large amount of undisturbed land. The block method of mining quarry fields, well known in mining, has been rarely implemented in existing and planned quarry fields. The general line of its application is the lack of a unified approach to the design of block parameters, including environmental and economic assessment of the impact of this technological solution on the environment. Aim. Reduce environmental payments of mining enterprises with justified parameters of blocks for the development of quarry fields of promising inclined and steeply dipping coal deposits. Methods. Systematic generalization of the actual situation of mining operations in open-pit mines using the block method of mining quarry fields, the method of options and technical and economic modeling using spreadsheets. Results and conclusions. The authors have proposed the ecological and economic criteria for assessing the application of the block method of quarry field development. This allows us to study the patterns of change in environmental indicators. Using the example of the Krasnobrodskoe open-pit mine, the costs of environmental payments for the use of land resources, emissions and dusting are calculated for two options different from the design documentation. Based on the calculation results, the authors proved the efficiency of applying the block procedure for developing promising coal deposits, allowing us to reduce the costs for environmental impact by 22.5 and 63%, respectively, when changing the length of the initial block along the bottom from 2.2 to 1.4 km. From which it follows that the combined ecological and economic indicators allow us to fully assess the feasibility of applying the method for calculating block parameters, which is generally reflected in reduction in the costs for negative impact on the environment.

Monitoring stress-induced brittle rock mass damage for preventative support maintenance

Stress-induced brittle fracturing near an excavation boundary results in a volume increase, known as bulking. Excessive bulking places added demand on the rock support, which, if not detected and addressed through preventative support maintenance (i.e., proactively added reinforcement), can cause the support to fail, leading to a safety hazard and costly production delays for underground mining operations. For caving mines, these project risks are exacerbated during cave establishment due to the large abutment stress from undercutting that redistributes and concentrates stresses near excavations critical for production. This paper reports the findings from research conducted to develop and improve geotechnical monitoring practices to support preventative support maintenance in deep mining operations. This research uses a unique geotechnical monitoring database collected for the Deep Mill Level Zone panel cave mine. The data was collected across a large footprint during the mine's ramp-up period and represents an initial step toward best practices for data collection at cave mines operating in high-stress environments. Borehole camera surveys supplemented by multi-point borehole extensometers have been used to determine the depth of stress fracturing in pillar walls as a function of the distance away from the undercut. Convergence measurements and LiDAR scanning are used to characterize the corresponding rock mass bulking. The results show that the interpretation of monitoring data can be used to identify the long-term depth of stress fracturing and bulking trends in response to undercut advances. These show that direct measures of stress-induced fracturing damage provide an early indication of excavations vulnerable to bulking and that LiDAR scanning is an effective method for capturing the onset of bulking and anticipating local areas likely to experience greater deformation demand as bulking progresses. Proactive and strategic geotechnical monitoring based on the long-term depth of stress-induced fracturing trends is proposed to assist with preventative support maintenance practices.

Experimental Investigation on Rock Failure Characteristics of Large-Span Goafs Using Digital Image Correlation Analysis and Acoustic Emission Monitoring

Rockmass in deep mining is highly susceptible to large-scale collapses under high stress and blast-induced disturbances, leading to casualties and economic losses. To investigate the evolution characteristics of goaf instability and the types of seismic sources that induce instability, an experiment on goaf instability was designed under uniaxial compression conditions based on actual mining operations. The entire experimental process was monitored using digital image correlation analysis and acoustic emission monitoring. By calculating the digital speckle field on the surface of the rock specimen during the experiment, the evolution characteristics of the deformation and strain fields from the beginning of loading to complete failure were analyzed. The study explored the dynamic behavior of cracks from initiation to propagation and eventually inducing large-scale collapse. The results show that the instability process of the goaf begins with the formation of tensile cracks. As stress increases, shear cracks occur in the specimen, leading to macroscopic failure. Furthermore, based on the differences in overall microfracture types measured by RA-AF characteristic parameters during specimen failure, large amplitude acoustic emission events corresponding to the formation of dominant macroscopic cracks were selected, and the focal mechanisms of these events were inverted. The results indicate that shear failure sources are significantly more prevalent than tensile failure sources in acoustic emission events leading to goaf instability. These findings can provide useful guidance for the support design and the prevention and control of rockmass instability disasters.

Analysis of Fracture Modes and Acoustic Emission Characteristics of Low‐Frequency Disturbed Water‐Bearing Soft Rock With Different Cyclic Initial Value

ABSTRACTIn the complex geological environment of deep mining area, water‐bearing soft rock is more prone to damage and destruction by low‐frequency disturbance. In this paper, the dynamic–static combination test was conducted on the basis of uniaxial compression test by using creep dynamic disturbance impact loading system and acoustic emission technique. The test results show that with the increase of the initial value of disturbance loading, the fracture morphology of sandstone gradually changes from a single major crack to multiple cracks coexisting, and some saturated sandstones lose the bearing capacity in the process of disturbance, presenting a cone‐shaped fracture surface. The increase of the initial value of the disturbance changes the bearing capacity of the sandstone, and the peak energy of acoustic emission reaches the maximum value when the initial value of the disturbance is 80% UCS. The results of the study can provide some reference for the stability analysis of deep water‐rich soft rock mines.

An analytical approach for evaluation of conveyor exit strategies in open-pit mines

Transportation is the most expensive task in deep open-pit mining operations. An In-Pit Crushing and Conveying (IPCC) system, as an alternative to the conventional shovel-truck system, requires precise planning to avoid wasting high capital expenditures on trucks. The decision to fit a conveyor system into the pit design is challenging and needs to be addressed in the literature. Further optimisation of the IPCC system requires choosing an appropriate conveyor exit strategy. Conveyor exit schemes include a Dedicated Ramp Slot (DRS), an Existing Ramping System, an inclined tunnel and High-Angle Conveyors (HAC). This paper provides an analytical approach to compare the cost of different conveyor exit strategies in open-pit mines. The results indicate that for a depth up to 100 m, the Present Value of Cost (PVC) for the DRS is the least. For the cases deeper than 300 m, the HAC has the least PVC. Sensitivity analysis showed that for the depths between 100 and 300 m, a more accurate and detailed definition of parameters is needed. Besides, in most cases, the HAC provides the lowest payback period and the highest internal rate of return among the alternatives.

Stress Field Comparison in Deep Coal Mines: Roof Cutting Versus Traditional Methods

Stress Field Comparison in Deep Coal Mines: Roof Cutting Versus Traditional Methods

Deep mining reveals the diversity of endogenous viral elements in vertebrate genomes

Integration of viruses into host genomes can give rise to endogenous viral elements (EVEs), which provide insights into viral diversity, host range and evolution. A systematic search for EVEs is becoming computationally challenging given the available genomic data. We used a cloud-computing approach to perform a comprehensive search for EVEs in the kingdoms Shotokuvirae and Orthornavirae across vertebrates. We identified 2,040 EVEs in 295 vertebrate genomes and provide evidence for EVEs belonging to the families Chuviridae, Paramyxoviridae, Nairoviridae and Benyviridae. We also find an EVE from the Hepacivirus genus of flaviviruses with orthology across murine rodents. In addition, our analyses revealed that reptarenaviruses and filoviruses probably acquired their glycoprotein ectodomains three times independently from retroviral elements. Taken together, these findings encourage the addition of 4 virus families and the Hepacivirus genus to the growing virus fossil record of vertebrates, providing key insights into their natural history and evolution.

Shear creep deformation of rock fracture distrubed by dynamic loading

The long-term stability of jointed rock masses is usually dominated by fault activation, which may be triggered by the dynamic disturbance generated by blasting during mining activities, leading to the occurrence of disasters such as landslides in open-pit and rockbursts in deep mining. The initial stress and dynamic disturbance are key factors that strongly affect the shear creep behavior of rock fractures. In this work, the shear failure instability of rock fractures of sandstone under creep-impact loading was experimentally investigated by using a creep-impact test machine, which allows for applying creep loading and an additional dynamic disturbance on rock fractures. Three stages of shear creep deformation, creep strain rate, and time-to-failure are examined under different creep stress levels and impact energies. Experimental results show that the tangential and normal creep rates increase with the increase of creep stress and impact energy, but the increment of tangential creep rate is higher than that of the normal creep rate. The time-to-failure of the creeping specimen is shortened under high creep stress and large impact energy, while the time-to-failure after the last dynamic disturbance of the specimen is determined by the total impact energy and creep stress level. By using high-speed photography, it is found that the failure types of rock depend on the magnitude of impact energy and creep stress level; that is, rock mainly slides with low stress levels and shears off with high stress levels. In addition, under different impact energy and creep stress levels, the variation of height is between 0.38 and 0.52, while the defined fracture factor, which describes the degree of failure of serrations, is between 0.30 and 0.54. The findings can provide deep insight into the fault sliding mechanism caused by mining activities, which provides theoretical support for the safe mining of ore in fault fracture zones.

Investigation of Load Characteristics and Stress-Energy Evolution Laws of Gob-Side Roadways Under Thick and Hard Roofs

The stress environments of gob-side roadways (GSRs) are becoming increasingly complex during deep coal mining under thick and hard roofs. This leads to strong strata behaviors, including roadway floor heave, roof subsidence, and even coal bursts. Among them, coal bursts pose the greatest threat to production safety in coal mines. Coal bursts in a GSR strongly correlate with the load characteristics and stress-energy evolution laws of the roadway. This study analyzes the roof structures of double working faces (DWFs) during the initial weighting stage (IWS) and full mining stage (FMS) of gob-side working faces (GSWFs). This study also explores how varying roof structures affect the stability of GSRs. Three-dimensional roof structure models of DWFs and mechanical models of dynamic and static loads superposition on a GSR throughout the IWS and FMS of a GSWF were developed. An analysis identified the primary stress sources affecting the GSR throughout various mining stages of the GSWF. Subsequently, the principle of “three-load” superposition was developed. A novel method was proposed to quantify the stress state in the GSR surrounding rock across different mining stages of the GSWF. The method quantitatively characterizes the load of the GSR surrounding rock. Based on this, the criterion for judging the burst failure of the roadway was established. Numerical simulations are used to analyze the stress-energy evolution laws of the working face, coal pillar, and GSR surrounding rock during the mining process of the GSWF. These findings offer valuable references for studying and preventing coal bursts in GSRs under equivalent geological situations.

Research on mechanism and practice of expansion‐induced fracturing and pressure relief in deep coal mines

Research on mechanism and practice of expansion‐induced fracturing and pressure relief in deep coal mines

LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks

BackgroundLong non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations.ResultsIn this paper, we propose a prediction method for the lncRNA-disease association relationship, named LDAGM, which is based on the Graph Convolutional Autoencoder and Multilayer Perceptron model. The method first extracts the functional similarity and Gaussian interaction profile kernel similarity of lncRNAs and miRNAs, as well as the semantic similarity and Gaussian interaction profile kernel similarity of diseases. It then constructs six homogeneous networks and deeply fuses them using a deep topology feature extraction method. The fused networks facilitate feature complementation and deep mining of the original association relationships, capturing the deep connections between nodes. Next, by combining the obtained deep topological features with the similarity network of lncRNA, disease, and miRNA interactions, we construct a multi-view heterogeneous network model. The Graph Convolutional Autoencoder is employed for nonlinear feature extraction. Finally, the extracted nonlinear features are combined with the deep topological features of the multi-view heterogeneous network to obtain the final feature representation of the lncRNA-disease pair. Prediction of the lncRNA-disease association relationship is performed using the Multilayer Perceptron model. To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. Through a gate mechanism, it controls the flow of information between each hidden layer in the Multilayer Perceptron model, aiming to achieve optimal feature extraction from each hidden layer.ConclusionsParameter analysis, ablation studies, and comparison experiments verified the effectiveness of this method, and case studies verified the accuracy of this method in predicting lncRNA-disease association relationships.

Statistical analysis of thermally induced pre-existing microcracks and their influence on fracture behaviours of granite rock

Rocks containing varying degrees of microcracks have a significant influence on their mechanical behavior. Understanding the effect of pre-existing microcracks (PEMs) on rock fracture mechanisms has scientific and practical value in areas such as geothermal energy, nuclear waste disposal and deep mining. We employed a thermally induced approach to create PEMs in granite rock, and quantified characteristic parameters of PEMs by visualization methods, focusing on the quantitative relationships between the PEMs and the mechanical strength and acoustic emission (AE) properties of the rock. We find that the distribution characteristics of thermally induced PEMs obey a lognormal distribution, and the length of individual thermally induced PEMs is almost independent of temperature. The density and orientation of PEMs together determine the variation of the longitudinal wave velocity and rock strength, with the effect of microcrack density dominating. The AE signal suggests that PEMs can affect the fracture behavior and fracture mechanism, depending on the relative dominance of pre-existing and stress-induced microcracks. The AF-RA values show that PEMs lead to an important shift in the fracture mechanism of the rock. When the microcrack density is low, tensile mode dominates the rock failure. Conversely, the shear mechanism dominates the rock fracture.

Distance-regularized level set inversion of magnetic data

Inversion is one of the key and difficult issues in potential field data processing and interpretation, and high-precision inversion has long been a popular research topic. We develop the distance-regularized level set inversion of the magnetic data (DRLSI-M) method. A double-well function is introduced into the objective function of the level set inversion, and we take advantage of its mathematical properties to minimize the gradient of the level set function so that it reaches a minimum value at points 0 and 1. As a result, the distance-regularized term not only replaces the costly reinitialization process so that the level set function maintains a signed distance property but also stabilizes the evolution of the level set function. When solving for the minimum value of the objective function, we transform the optimization problem into an initial-boundary value problem and solve it with the finite-difference method. The distance-regularized level set inversion method and the reinitialization level set inversion method are tested using three models: a single-level-set double-inclined plate model, a double-level-set double-inclined plate model, and a multiple-level-set three-cuboid model. Through model tests, the soundness of our method is verified and compared with the reinitialization level set inversion method. Our method avoids the limitations such as low efficiency and instability caused by the reinitialization of the level set inversion method. Furthermore, we apply our method for the inversion of aeromagnetic data from the Jinchuan copper-nickel mine. The results are consistent with the known geologic information, thus validating the practicality and effectiveness of DRLSI-M. The distance-regularized level set inversion method provides a theoretical basis for deep mine exploration.