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Abstract In order to study the mechanics, acoustic emission (AE) and electromagnetic emission (EME) response law of bursting liability coal at different loading rates, uniaxial compression tests were carried out on coal mass from Konggu Coal Mine. The corresponding relations among mechanical properties, AE and EME signals in the process of coal failure under loading were analyzed, and the energy evolution law of coal failure with bursting liability under loading rate was discussed. The results show that within a certain range of loading rate, the higher the loading rate, the higher the compressive strength and peak load of bursting liability coal, and the shorter the time for coal to reach the peak load. Under different loading rates, the mechanics, AE and EME signals of coal samples can be well corresponded. When the loading rate is low, the number of blocks destroyed of coal sample is large and the block size is relatively small, and the blocks are mainly scattered around the test platform. When the loading rate is high, the number of damaged blocks is relatively small and the block size is relatively large, and the blocks are far away from the test bench. When loading at a low rate, the internal cracks in coal can be fully developed and connected, and the energy release rate is relatively uniform in the process of loading and failure of coal sample. In the case of high loading rate, the energy release rate of coal sample in the loading process is much smaller than that in the moment of failure. Combining the above test results with the actual situation of the working face, it can be concluded that the total energy stored in the coal of fast mining increases and the threshold of impact decreases compared with that of slow mining. Therefore, under the disturbance of external dynamic load, rapid mining is more likely to induce rock burst.

Irregular upper gobs may increase the risk of rock burst incidents in coal mines. Investigating the rock burst mechanism in the complex mining spatial structure of multi-seam rock bursts is essential for ensuring the safe extraction of coal resources. This study investigated the distribution characteristics of static and dynamic loads on the W1123 working face through a comprehensive approach utilizing theoretical analysis, numerical simulation, and on-site monitoring. The mechanism of rock bursts was analyzed and targeted preventive measures were proposed and applied on-site. The results indicated that the coupled effects of the overlying knife-shape-like gob and thick hard roofs exhibited regional characteristics in the distribution of static and dynamic loads beneath the W1123 working face. When the working face was solely influenced by the “handle” effect of the knife-shape-like gob or concurrently affected by both the “handle” and “blade body”, the lower part of the working face and the coal pillar experienced concentrated static loads and intense dynamic load disturbances. The surrounding rock in the upper gob also demonstrated concentrated static and dynamic loads, with the proximity to the boundary of the knife-shape-like gob resulting in higher dynamic and static loads. When only affected by the “blade body”, the upper surrounding rock of the working face experienced concentrated static loads and was disturbed by dynamic loads. The area of concentrated static loads and dynamic load disturbances in the working face coincided, leading to the manifestation of rock burst from the superposition of dynamic and static loads. Based on the structural characteristics of the knife-shape-like gob, the rock burst types during the mining period of the W1123 working face were sequentially classified as strong dynamic load type, high static load, strong dynamic load type, and high static load type. The risk of rock bursts assessed through on-site monitoring and numerical simulation matched the theoretical analysis outcomes. Rock burst prevention measures were optimized based on the distribution characteristics of static and dynamic loads on the W1123 working face. To mitigate the stress and energy concentration on the roof and coal body, we have enhanced the treatment height and crushing degree of the thick, hard roof while also intensifying coal body blasting and pillar cutting. Following the implementation of these optimized measures, the average event energy released by the surrounding rock of the working face decreased by 54%, and significant energy events were substantially reduced, leading to a significant reduction in the rock burst risk. This study can provide valuable insights for rock burst prevention in mines with irregular upper gobs.

Electromagnetic radiation and vibration monitoring technologies are widely used in the monitoring and early warning of dynamic disasters in underground engineering, which is of great significance to the safe and efficient development of underground engineering. In-depth study of electro-seismic signals is helpful to promote the development of granite mass monitoring and early warning technology. However, the current analysis of electromagnetic radiation and vibration signals (electro-seismic) mainly focuses on the correlation and time-frequency characteristics of signals. There are few studies on the nonlinear dynamic characteristics of granite fracture electro-seismic signals, and the relevant characteristics are not yet clear. Based on this, this paper uses the combination of empirical mode signal (EMD) reconstruction and fractal theory to analyze the chaotic characteristics of electro-seismic signals of granite splitting failure, and reveals the nonlinear dynamic characteristics of electro-seismic signals. The results show that the electromagnetic radiation generated by granite splitting failure is in good agreement with the vibration signal in time, and the frequency spectrum of the electro-seismic signal generated by splitting failure is concentrated in the middle and low frequency band. The box dimension of the effective electromagnetic radiation signal of granite failure is DE=1.6006, and the box dimension of the effective vibration signal is DA=1.5948, and the frequency structure characteristics of the two are highly similar. The effective electromagnetic radiation and vibration signals of granite fracture can be obtained by the EMD decomposition and reconstruction method. It is more accurate to describe the chaotic characteristics of granite fracture electro-seismic signals by using the EMD decomposition and reconstruction to remove the interference of high frequency. The effective electromagnetic radiation on the vibration signal contains more low-frequency and high-energy signals than the original signal, which characterizes the propagation of small cracks. The non-uniformity of the reconstructed electro-seismic signal is significantly higher than that of the initial signal, and the frequency relationship of different energy signals decreases. The reconstructed effective electro-seismic signal is mainly low-frequency and high-energy signals, but the non-uniformity of the vibration signal is greater than that of electromagnetic radiation.

Based on the engineering background of the ultra-close adjacent coal seam group in the deep part of Pingdingshan No.8 coal mine, this paper studies the reasonable layering of bottom pumping roadway under the mining condition of deep ultra-close seam. FLAC3D numerical model is used to simulate the evolution law of the plastic zone, stress field and displacement field of coal seam under different net rock distances between the roof of bottom pumping roadway and Ⅵ16-17 coal seam. The results show that when the net rock distance is 3 m or 5 m, the coal seam above the bottom drainage roadway can be divided into pressure relief zone, stress concentration zone and primary rock stress zone under the influence of mining. When the net rock distance is 8 m or more, the coal seam above the bottom drainage roadway can be divided into pressure relief zone and primary rock stress zone under the influence of mining. The optimal layout of bottom drainage roadway is 8-10 m distance from the retained net rock. After the bottom pumping roadway is mined, the position directly above the roadway has the best pressure relief effect, the coal body in this area is fully deformed, the gas control is easier, is conducive to the support and maintenance of the coal roadway in the later period, and is the best position to arrange the coal roadway. Field monitoring effectively verified the reliability of the bottom pumping roadway in the net rock distance to control the gas outburst risk of the working face near the deep seam group.

Rock mass structure rupture is an important factor that seriously restricts the construction and safe operation of underground space engineering projects such as mines, subways and tunnels. Realizing the identification of rock mass fracture state is one of the hotspots and emphases of current research. In this study, some experiments of sandstone loading failure under different conditions were carried out, the acoustic emission Mel-frequency cepstral coefficient (MFCC) and its fluctuation difference during the whole loading process were extracted, the variation law of the coefficient and its fluctuation difference during the whole loading failure process was studied, and the correlation characteristics of coefficient No.1 (According to the calculation of acoustic emission Mel-frequency cepstral coefficients, it can be seen that a set of acoustic emission Mel-frequency cepstral coefficient includes 12, and coefficient No.1 refers to the first Mel-frequency cepstral coefficient) and its fluctuation difference with the fracture state of sandstone were analyzed. Based on this, a method to identify sandstone fracture state using the Mel-frequency cepstral of acoustic emission was proposed, and the identification criteria was constructed. The identification effect was finally verified. The results show that with loading increase, the coefficient No.1 increases as a whole, and the coefficient value and its discreteness increase significantly in the failure stage and show significant regular fluctuations. The fluctuation difference of the coefficient has the characteristics of periodic variation. The size of the fluctuation difference and its fluctuation can characterize the fracture of sandstone. The overall increase and sudden increase of the fluctuation difference can reflect the macroscopic fracture of sandstone in the unstable deformation and post-peak failure stage, and the sudden increase level of the fluctuation difference can reflect the fracture degree of sandstone. The acoustic emission Mel-frequency cepstral coefficient and its fluctuation difference show good response characteristics to sandstone fracture, which is less affected by different loading conditions, thus they have applicability in reflecting sandstone fracture. The coefficient No.1 and its fluctuation difference have a good correlation with the fracture state of sandstone. The correlation can be divided into three stages as: in the micro-fracture stage of sandstone, the coefficient No.1 and its fluctuation difference are intensively distributed; in the unstable deformation stage just prior to the peak load, the distribution range increases sharply, the overall value increases and the high abnormal value appears; in the post-peak failure stage, the distribution range further increases, the overall value is higher, and more high abnormal values appear. The identification method and criteria of sandstone fracture state were constructed by using the 75% site value and outliers of coefficient No.1 and the 75% site value and outliers of the fluctuation difference of coefficient No.1. The effect of the identification criteria was tested by the confusion matrix of the three-classification model. The accuracy and precision of identification are 90.43% and 94.45%, respectively, which indicate the identification effect is good. The results can provide a reference for the identification of the fracture state of other types of coal and rocks, and for the monitoring and early warning of coal rock instability.

Rockbursts have become a significant hazard in underground mining, underscoring the need for a robust early warning model to ensure safety management. This study presents a novel approach for rockburst prediction, integrating the Mann-Kendall trend test (MKT) and multi-indices fusion to enable real-time and quantitative assessment of rockburst hazards. The methodology employed in this study involves the development of a comprehensive precursory index library for rockbursts. The MKT is then applied to analyze the real-time trend of each index, with adherence to rockburst characterization laws serving as the warning criterion. By employing a confusion matrix, the warning effectiveness of each index is assessed, enabling index preference determination. Ultimately, the integrated rockburst hazard index Q is derived through data fusion. The results demonstrate that the proposed model achieves a warning effectiveness of 0.563 for Q, surpassing the performance of any individual index. Moreover, the model's adaptability and scalability are enhanced through periodic updates driven by actual field monitoring data, making it suitable for complex underground working environments. By providing an efficient and accurate basis for decision-making, the proposed model holds great potential for the prevention and control of rockbursts. It offers a valuable tool for enhancing safety measures in underground mining operations.

In the process of deep mining, the geological type of the mine is complicated. Under the condition of “three heights and one disturbance”, it is easy to cause coal and gas outburst and other coal and rock dynamic disasters near the hidden structure. In order to clarify the mechanism of dynamic disasters induced by hidden structures, taking No.8 Mine in Pingdingshan as the engineering background, the stress-strain evolution characteristics and disaster causing law of normal and reverse faults in different mining directions and their simultaneous existence are studied by numerical simulation, and the influence of different hidden structures on driving face is analyzed. The results show that when driving encounters a single fault, the stress-strain is concentrated in front of the work and inside the fault. Normal faults are more likely to produce stress concentration, and the range of stress concentration is larger. At the same driving distance, the principal strain of the reverse fault is slightly larger than that of the normal fault. With the driving distance increases, when the driving distance increases to 15 m, the stress-strain concentration area gradually coincides, and finally a stress-strain superposition area is formed in the fault area. When driving encounters multiple faults, the stress is concentrated on the structural coal in front of the working face and between the two faults. The superimposed stress-strain distribution is different in the case of normal-reverse faults and reverse-normal faults. In the case of normal-reverse faults, the superimposed stress-strain is mainly distributed near the normal faults. In the case of reverse-normal faults, the stress-strain in structural coal between the two faults also increases significantly. Near the multiple hidden structures dominated by reverse faults and reverse faults, the increase rate of strain energy is larger, which is more conducive to the accumulation of strain energy, and the risk of coal and gas outburst increases. Under the combined action of mining stress, fault structural stress and static stress in the coal rock mass, coal and gas outburst and other coal and rock dynamic disasters are eventually triggered. Multiple hidden structures are more likely to produce stress concentration than single structures, and the risk of coal and rock dynamic disaster increases.

Underground oil reserves are established near the sea, which can reduce the cost of oil transportation and have strong military significance. However, the proximity to the coastline makes it easy for seawater to intrude into the reservoir area, resulting in corrosion of the metal structure in the reservoir area, thus reducing the service life of the reservoir. A simulation study on the risk of seawater intrusion was carried out with an offshore underground oil reserve project as the background. A refined three dimensional hydrogeological model with 15 geological structures such as integrated faults, jointed dense zones and water conduction channels was constructed, and the groundwater seepage field and solute transport field in the reservoir area under the natural state and during the operation period were studied. The study shows that (1) there is no seawater intrusion in the undergroundoilreserve in the natural state. (2) During the operation period, a horizontal water curtain with a distance of 10 m and a diameter of 0.11 m was only set at 25 m above the top of the cavern reservoir, exceeding the cave by 50 m around，which could not effectively prevent seawater intrusion. (3) When the cave reservoir was running for 9 a, the Cl− mole concentration on the southeast side of 3# cavern room exceeded 7 mol/m3, and seawater began to invade the cavern group; when it was running for 22 a to 23 a, the seawater invasion speed was the fastest; when it was running for 41 a, the Cl− mole concentration on the southeast side of 3# cavern room exceeded 143 mol/m3, and the seawater invasion reached the strong corrosion degree of steel; when it was running for 50 a, all the cavern rooms except 1# cavern room were invaded by seawater, 3# and 4# cavity rooms have some areas to reach strong corrosion degree, seawater invasion is the most serious. It is suggested to set up additional facilities such as vertical water curtain to enhance the prevention and control of seawater intrusion. The research results can provide reference for the suppression of seawater intrusion in underground oil reserves in offshore areas.

Abstract Of the 12 wild felid species found in China, Asiatic golden cat (Catopuma temminckii) is one of the least studied species. This medium‐sized cat with a prominently polymorphic coat was once distributed across much of southern China, but is believed to have experienced severe decline and range contraction during the past decades, primarily due to anthropogenic pressures. A lack of knowledge of its current distribution, ecology, and natural history has greatly hindered the implementation of conservation and management actions for this species. In this study, for the first time, we compiled the state‐wide occurrence records (N = 409), mainly from the camera‐trapping surveys, of Asiatic golden cats from 2008 to 2019, and predicted its distribution across the country through species distribution modeling using random forest algorithm. The results showed that the predicted habitats were mainly located in southwest China and suggested a rather low probability of possible current distribution across its vast historic range in central, eastern, and southern China. We divided its current range into four geographic regions (i.e., Qinling Mountains, Hengduan Mountains, East Himalayas, and southern Yunnan region) and considered the cats in each region as a regional population within the country. From the 287 camera‐trapping detections with photographs and/or videos collected across all populations, we identified six coat morphs and determined their occurrence percentages: common golden (47.4%), spotted (20.9%), red (13.6%), dark cinnamon (10.1%), melanistic (7.0%), and gray (1.0%). The complexity of coat morph composition within regional populations showed an increasing gradient from northeast to southwest. Among the four regional populations, the East Himalayas hosted the highest abundance and coat variation with all six morphs recorded. Our study results update the current distribution and coat morphology variations of this elusive cat in China and provide important knowledge to guide future research and conservation planning for this threatened species.

The existing rockburst risk assessment methods generally belong to static assessment method which normally depends on the geological and mining conditions that are revealed prior to mining. There is commonly a certain gap between the assessment results and the real situation. How to combine with the monitoring data in the mining process to get more realistic evaluation results is a problem that needs to be further solved. To this end, this work proposes a static-dynamic coupling rockburst risk assessment method taking into account the geological and mining conditions as well as the monitoring data, and the method has been being applied in typical panels in near-vertical coal seams. Firstly, a static evaluation method used before mining based on the improved comprehensive index method is proposed. The evaluation indicators contained in the comprehensive index method are linearly normalized to obtain the single indicator risk index. The AHP method is used to assign weights to each evaluation indicator, and the weighted summation of all indicator risk indexes is calculated to obtain the risk indexes determined by geological factors and mining technology factors, respectively. Then the weighted mean of the two risk indexes is used as the static evaluation risk index. Secondly, a dynamic evaluation method used during mining by utilizing the monitoring data is constructed. According to the characteristics of microseismic monitoring and borehole stress monitoring and their relationship with rockburst risk, the dynamic evaluation indicators are constructed based on the microseismic energy density and borehole stress variation. The evaluation indicators are linearly normalized to obtain two evaluation indexes. The weighted mean of the two indexes is used as the dynamic evaluation risk index. Finally, the two proposed methods are combined to get a static-dynamic coupling evaluation model. The coupling evaluation risk index is obtained by weighted average of the static evaluation risk index and the dynamic evaluation risk index, and then the risk grade and risk area are determined. The method is applied in +450B3+6 panel of Wudong Coal Mine. Results show that the static evaluation method demarcates 4 medium risk areas and 1 weak risk area before the mining of the panel, the dynamic evaluation method determines that the rock pillar side has high risk level in the mining process of the panel, and the static dynamic coupling evaluation re-evaluates the weak risk area of the static evaluation to the medium risk area. By investigating the monitoring data of support pressure, the numerical simulation results and the rockburst occurrence on site during the mining process of the panel, the evaluation results are verified, and it is found that the static and dynamic coupling evaluation results are more consistent with the actual situation. This work provides a new method and a new idea for the risk assessment of rock burst.

Abstract Coal mines may change from non-outburst mines into coal and gas outburst mines with increasing mining depth. Therefore, scientific and rapid prediction of the coal seam outburst risk and effective prevention and control measures could ensure coal mine safety and production. This study aimed to propose a solid–gas–stress coupling model and assessed its applicability in predicting the coal seam outburst risk. Based on a large amount of outburst case data and the research results of previous scholars, coal and coal seam gas constitute the material basis of outbursts, and gas pressure is the energy source of coal seam outbursts. A solid–gas–stress coupling model was proposed, and a solid–gas–stress coupling equation was established via regression. Among the three major outburst factors, the sensitivity to the gas content during outbursts was the lowest. The causes of coal seam outbursts with a low gas content and the effect of the structure on outbursts were explained. It was theoretically revealed that the coupling of the coal firmness coefficient, gas content and gas pressure determined whether coal seams could experience outbursts. This paper provided a basis for assessing coal seam outbursts and classifying outburst mine types and listed application examples of solid–gas–stress theory.

Rock fracturing is often accompanied by electromagnetic phenomenon. As a vector field, in addition to the intensity that is widely concerned, the generated electromagnetic field also has obvious directionality. To this end, a set of electromagnetic antennas capable of simultaneous three-axis measurement is used to monitor the electromagnetic vector field generated from rock fracturing based on Brazilian tests. The signal amplitude on each axis can represent the magnitude of actual magnetic flux density component on the three axes. The intensity and directional characteristics of electromagnetic signals received at different positions are studied using vector synthesis. The directionality of electromagnetic radiation measured using a three-axis electromagnetic antenna shows that the direction of the magnetic flux intensity generated by rock fracturing tends to be parallel to the crack surface, and the measured signal intensity is greater in a direction closer to the crack surface.

Joints are the weak plane structures in coal. The existence of joints leads to coal failure, with different fracture modes and energy evolution laws. In this paper, the energy evolution and bursting liability index of coal failure with different joint inclination angles (JIAs) are analyzed. The results show that with an increase in joint inclination angle (JIA), the total energy and elastic energy of coal first decrease and then increase and the dissipation energy decreases gradually. The existence of joints changes the bursting liability of coal. With an increase in the JIA, the uniaxial compressive strength (Rc) of coal first decreases and then increases, the dynamic failure time (DT) gradually decreases, and the impact energy velocity index (WST) and the impact energy index (KE) gradually increase. With an increase in the JIA, coal went from tensile failure to shear failure and tension shear mixed failure. After coal failure, the fractal dimension was between 1.7 and 2.4, decreasing first and then increasing; the larger the JIA and the degree of fragmentation, the more energy consumed at the moment of failure and the stronger the bursting liability of coal. The results have a guiding significance for the monitoring and prevention of rock bursts in coal mines.

Abstract Efficient and accurate monitoring and early warning of coal dynamic disaster and other disasters can provide guarantee for the efficient operation of mine transportation system. However, the traditional threshold early warning method often fails to warning some accidents. To address above issues, a new early warning method was proposed based on "quiet period" phenomenon of AE and EMR during fracture. It is found that, a "quiet period" of AE and EMR was present before the load reaches the peak stress, which could be used as one of the precursors to warn the imminent failure of coal and rock specimens. MS and AE signals increased abnormally followed by the phenomenon of "quiet period" before the occurrence of coal dynamic disaster on site, and the decrease of MS events in the "quiet period" is about 57%–88% compared with that in previous abnormal increase stage. During the damage evolution of coal and rock, "quiet period" phenomenon usually occurred at 85%–90% of the peak stress, where the slope of damage parameter curve is almost zero. The "quiet period" of the AE-EMR signals and the low change rate of damage parameter before failure provide a theoretical foundation for the coal dynamic disaster warning based on the "quiet period" precursor found in MS-AE-EMR monitoring system. These findings will help reduce the number of under-reported events and improve early warning accuracy.

Leopard (Panthera pardus) populations on the Chinese Loess Plateau have experienced severe declines and were once on the verge of extinction. Currently, leopards in the Loess Plateau region are mainly scattered in human-dominated fragmented habitats in Shanxi, Shaanxi and Ningxia. The lack of information on the genetic diversity and genetic structure makes difficult to assess the resistance and persistence of this metapopulation to various factors. In this study, we used mitochondrial ND-5 gene sequences and eight microsatellite loci to genetically analyze 97 faecal samples collected from three leopard ranges on the Loess Plateau of China. Among these samples, 62 feces were successfully identified from 22 individuals (6 females, 16 males). Mitochondrial haplotypes showed four different haplotypes and the genetic diversity was moderate (Hd = 0.331, Pi = 0.0036), while SSR showed high diversity (PIC = 0.673). STRUCTURE and TESS analyses revealed that leopard populations on the Loess Plateau appeared to have a distinct population boundary (K = 2) associated with a spatial-geographic barrier (the Yellow River). We estimate that the time of population divergence occurred between 8700 and 8300 years BP. Based on this research, we suggest that the leopard population on both sides of the Yellow River should be divided into two conservation management units to improve the efficiency of conservation management and contribute to the better recovery of the North Chinese leopard population.

The characterization of micro-surface mechanical and electrical properties of the natural rock materials remains inadequate, and their macroscopic performance can be better comprehended by investigating the surface properties. With this purpose, the present research focuses on characterizing the micro-surface morphology, Derjaguin-Muller-Toporov (DMT) modulus, adhesion, and potential of granite, shale, and limestone by employing the atomic force microscope (AFM) as a pioneer attempt. The results show that the micro-surface morphology of the rock fluctuates within hundreds of nanometers, among which the granite micro-surface is comparatively the smoothest, followed by limestone. The morphology of the shale is the roughest, indicating that the regional difference of shale micro-surface is dominant. The distribution of the adhesion on rock micro-surface is uneven; the average adhesion of eight measuring areas for shale is 23.93 nN, accounting for three times of granite and limestone, while the surface DMT modulus of shale is relatively lower than granite and limestone. It is inferred from the obtained results that higher surface adhesion is helpful to the gas adsorption of shale, and the lower surface DMT (elastic) modulus is useful to the formation of fractures and pores. Thus, these two are the micromechanical basis of shale gas adsorption. Additionally, introducing a method to reduce the surface adhesion will benefit the exploration of unconventional resources such as shale gas. The micro-surface of the three types of rocks all shows electricity, with average potential ranging from tens of millivolts to hundreds of millivolts. Besides, the micro-surface potential of the rocks are heterogeneous, and both positive and negative points can be found. The existence and uneven distribution of micro-surface potential provide a robust physical basis for the electromagnetic radiation generated by rock fracture under loading. This study offers a new method for revealing the adsorption characteristics of unconventional gas reservoir rocks and the electromagnetic radiation mechanism of the rock fracture.

Large terrestrial carnivores play a crucial role in the top–down control of terrestrial ecosystems by maintaining ecosystem stability and biodiversity. However, intense interspecific competition typically occurs among large sympatric carnivores, leading to population reduction or extinction. Spatial partitioning through divergent habitat selection mitigates such competition. In this study, we analyzed the main environmental factors influencing the habitat selection and fragmentation of suitable habitats in Xinlong County, Sichuan Province, using 410 infrared cameras from 2015 to 2023. By employing generalized linear and maximum entropy models, we developed an ensemble model to predict the suitable habitat distribution of leopards (Panthera pardus) and wolves (Canis lupus). The results revealed significant disparities in suitable habitat distributions of leopards and wolves as coexisting large carnivores. Leopards prefer understory, whereas wolves prefer high-altitude meadows. Wolves spatially avoid leopards, who secure relatively superior resources and relegate wolves to inferior habitats. Although suitable habitat patches for both species cluster intensely, habitat connectivity remains low owing to pronounced anthropogenic disturbances, which is especially evident in the higher fragmentation of wolf habitats. These results suggest that sympatric large carnivores can reduce spatial competition intensity and promote spatial partitioning by selecting divergently suitable habitats, thereby facilitating species coexistence.

A novel approach for mapping induced fractures and associated lineaments has been introduced based on microseismic data, and thus their contribution towards identification, and prediction of the risk zones which may lead to a collapse or rockburst in a coal mine. By taking Tashan Coal Mine (TCM) in Datong coalfield of China as an example, the real-time microseismic data was acquired for a period of 7 months. The microseismic data was processed using standard processing schemes followed by source location and parameters estimation. The proposed approach utilizes microseismic events, trace them to map the induced fractures, and based on their network to interpret associated lineaments. Based on the configuration, geometry, and network, thousands of fractures were identified which vary in length. Regional lineaments have been interpreted based on the orientation of these fractures. The fractures and lineaments distribution were further correlated with computed microseismic energy distribution. The spatial distribution of microseismic energy helped in identification of a geological discontinuity (fault) that clearly separates the study area into northern and southern parts. The reactivation of this fault may pose significant threats to mass stability, life, and property. The northern half is characterized by more and short length fractures while southern by prolonged and fewer fractures. The upper northern half is dominated by high energy (≥50, 000 J), while the lower part is characterized by variable energy pattern (22,000 to 40, 000 J). It is inferred from the energy-lineaments correlation figure, the northern half describes relatively stronger rock type in comparison to the southern part suggesting different rock deformational behavior. The fractures and lineaments converging towards a single point define risk zones where future collapse or rockburst can be expected. This identification of risk zones provides a strong basis for the real-time prediction of future catastrophic hazards in the coal mines. This study may benefit global underground engineering researchers for hazards prediction and establishing of the early warning systems.

The stress and gas pressure in deep coal seams are very high, and instability and failure rapidly and intensely occur. It is important to study the infrared precursor characteristics of gas-bearing coal instability and failure. In this paper, a self-developed stress-gas coupling failure infrared experimental system was used to analyse the infrared radiation temperature (IRT) and infrared thermal image precursor characteristics of gas-free coal and gas-bearing coal. The changes in the areas of the infrared temperature anomalous precursor regions and the effect of the gas on the infrared precursors were examined. The results show that high-temperature anomalous precursors arise mainly when the gas-free coal fails under loading, whereas the gas-bearing coal has high-temperature and low-temperature anomalous precursors. The area of the high-temperature anomalous precursor is approximately 30%–40% under gas-bearing coal unstable failure, which is lower than the 60%–70% of the gas-free coal. The area of the low-temperature abnormal precursor is approximately 3%–6%, which is higher than the 1%–2% of the gas-free coal. With increasing gas pressure, the area of the high-temperature anomalous precursor gradually decreases, and the area of the low-temperature anomalous precursor gradually increases. The high- and low-temperature anomalous precursors of gas-bearing coal are mainly caused by gas desorption, volume expansion, and thermal friction. The presence of gas inhibits the increase in IRT on the coal surface and increases the difficulty of infrared radiation (IR) monitoring and early warning for gas-bearing coal.

In order to accurately predict the gas concentration, find out the gas abnormal emission in advance, and take effective measures to reduce the gas concentration in time, this paper analyzes multivariate monitoring data and proposes a new dynamic combined prediction method of gas concentration. Spearman’s rank correlation coefficient is applied for the dynamic optimization of prediction indicators. The time series and spatial topology features of the optimized indicators are extracted and input into the combined prediction model of gas concentration based on indicators dynamic optimization and Bi-LSTMs (Bi-directional Long Short-term Memory), which can predict the gas concentration for the next 30 min. The results show that the other gas concentration, temperature, and humidity indicators are strongly correlated with the gas concentration to be predicted, and Spearman’s rank correlation coefficient is up to 0.92 at most. The average R2 of predicted value and real value is 0.965, and the average prediction efficiency R for gas abnormal or normal emission is 79.9%. Compared with the other models, the proposed dynamic optimized indicators combined model is more accurate, and the missing alarm of gas abnormal emission is significantly alleviated, which greatly improves the early alarming accuracy. It can assist the safety monitoring personnel in decision making and has certain significance to improve the safety production efficiency of coal mines.

In order to realize dynamic, continuous, and real-time prediction of coal and gas outburst risk in real time in blasting driving face, an outburst risk prediction method based on the characteristics of gas emission after blasting is proposed. In this study, the causes of abnormal gas concentration in blasting driving face are analyzed, and the identification method of abnormal gas concentration based on weighted K-nearest neighbor (weighted KNN) is proposed. The correlation between gas emission characteristics after blasting and K1 value is analyzed, and the prediction model of outburst risk based on convolutional neural networks (CNN) is established and applied in Jinjia coal mine in China. The results show that the causes of abnormal gas concentration mainly include ventilation stop, blasting operation, sensor adjustment, and other abnormalities. The accuracy of the identification method is 86.1%. Especially, the identification accuracy of blasting operation is 92%. There are strong correlations between the growth rate, peak value, and decay rate of gas concentration after blasting and K1 value, and the maximum correlation coefficient is 0.92. Using the prediction model, 28 times of jet holes and 1 small outburst event are predicted successfully, and the efficiency of the prediction model is 76.39%. By this technology, the utilization rate of gas information is improved, and the relationship between the change characteristics of gas concentration after blasting and the risk of coal seam outburst is established, which is of significant for improving the prediction accuracy and risk management ability of coal and gas outburst.

The presence of a high concentration of Cl− in saltwater will erode the structure and facilities, reducing the stability and service life of the underground oil storage cavern. In order to reduce the risk of seawater intrusion, this paper studies the risk and prevention technology of seawater intrusion based on a case study of a coastal and large-span underground oil storage cavern. A refined three-dimensional hydrogeological model that comprehensively considers permeability coefficient partitions, faults, and fractured zones are constructed. The seepage fields and seawater intrusion risks of the reservoir site in its natural state, during construction, and during operation are examined, respectively. The study quantifies the water inflow and optimizes the seawater intrusion prevention technology. The results indicate that there is no risk of seawater incursion into the cavern under natural conditions. The water inflows after excavating the top, middle, and bottom sections of the main cavern are predicted to be 6797 m3/day, 6895 m3/day, and 6767 m3/day, respectively. During the excavation period, the water supply from the water curtain system is lower than the water inflow of the cavern, providing the maximum water curtain injection of 6039 m3/day. The water level in the reservoir area decreased obviously in the excavation period, but the water flow direction is from the cavern to the sea. Additionally, the concentration of Cl− in the cavern area is less than 7 mol/m3; hereby, there are no seawater intrusion risks. When only the horizontal water curtain system is deployed, seawater intrusion occurs after 18 years of cavern operation. The concentration of Cl− in the southeast of the cavern group exceeds 50 mol/m3 in 50 years, reaching moderate corrosion and serious seawater intrusion. In addition to the horizontal curtain above the cavern, a vertical water curtain system could be added on the southeast side, with a borehole spacing of 10 m and extending to 30 m below the cavern group. This scheme can effectively reduce seawater intrusion risk and extend the service life of the cavern. The findings of this research can be applied as guidelines for underground oil storage caverns in coastal areas to tackle seawater intrusion problems.

Acoustic emission (AE) monitoring is an effective tool to quantify the dynamic damage that may cause heavy casualties and huge property losses in rock engineering. Instead of traditional failure evaluation methods, in this paper, the coal failure mechanism is evaluated in a complicated geological environment under uniaxial compression tests by employing machine learning (ML) and automatic speech recognition (ASR). Taking advantage of the ASR technology, the Mel-frequency cepstrum coefficients (MFCC) were extracted as sample features, while ML was used to paradigm the artificial intelligent evaluation of the failure probability of coal (AIEFPC). Additionally, the five-fold cross-validation method was used to assess the AIEFPC predictive effect incorporating cumulative hits number, cumulative ring count, and amplitude as sample features. The influence of category weight on the prediction effect of AIEFPC on a different category of sample sets has been discussed and analyzed. The results show that AIEFPC has the potential to use the MFCC of the 40 ms AE segment at any time to predict the dangerous state of the coal sample with a prediction accuracy of >85%. The probability value of the hazardous samples is computed through AIEFPC that further helped in evaluating the reliability of the prediction results. It is inferred from the obtained results that a larger category weight value of the hazardous samples can improve the prediction accuracy of AIEFPC than the safe sample. This research provides a new way of effectively predicting the coal failure probability before the damage and failure that can be applied to worldwide case-studies.

The time–frequency characteristics of electromagnetic radiation (EMR) waveform induced by rock fracture are very important to the monitoring and early–warning using the EMR method for the mine rockburst. The empirical wavelet transform (EWT), as a waveform time–frequency analysis method, has the advantages of a clear theoretical basis, convenient calculation, and no modal aliasing. To apply EWT to the field of EMR time–frequency analysis, the operation of Fourier axis segmentation of EWT is improved. In detail, the adaptive selection method for a window width of closing operation and the adaptive determination method of segment number of Fourier axis are proposed for EWT. The Fourier axis obtained by short–time Fourier transform (STFT) is used in the EWT process, rather than that obtained by discrete Fourier transform (DFT), taking a better Fourier axis segmentation effect. The improved EWT together with Hilbert transform (HT) applied to the time–frequency analysis for the EMR waveform of rock fracture, and the time–frequency spectrum obtained by EWT–HT can well describe the time–frequency evolution characteristics. Compared with STFT and Hilbert–Huang transform (HHT), EWT–HT has significant advantages in time–frequency resolution and overcoming modal aliasing, providing a powerful tool for time–frequency analysis for the EMR waveform induced by rock fracture.

In this study, we established a dynamic ejection coal burst model for a coalmine roadway subject to stress, and held that the stress concentration zone at the roadway side is the direct energy source of this ejection. The formation and development of such burst undergoes three stages: (1) instability and propagation of the cracks in the stress concentration zone, (2) emerging of a layered energy storage structure in the zone, and (3) ejection of coal mass or coal burst due to instability. Moreover, we figured out the initial strength of periodic cracks is parallel to the maximal dominant stress direction in the stress concentration zone and derived from the damage strain energy within the finite area of the zone based on the Griffith energy theory. In addition, we analyzed the formation process of the layered energy storage structure in the zone, simplified it as a simply supported restraint sheet, and calculated the minimum critical load and the internally accumulated elastic energy at the instable state. Furthermore, we established a criterion for occurrence of the coal burst based on the variational principle, and analyzed the coal mass ejection due to instability and coal burst induced by different intensity disturbances. At last, with the stratum conditions of Junde Coalmine as the model prototype, we numerically simulated the load displacement distribution of the stress concentration zone ahead of the working face disturbed by the main roof-fracture-induced dynamic load during the mining process as well as their varying characteristics, and qualitatively verified the above model. Keywords: Coal and rock burst, Evolution model, Dynamic ejection, Stress concentration, Layered energy storage structure

This work extends research on the mechanism of electromagnetic radiation (EMR) induced by coal or rock fractures to the category of microscopic dynamic experimental research. A custom-made three-point bending test system and atomic force microscope (AFM) were integrated to obtain the microdynamic loading test system. The notched coal samples were prepared specially. The dynamic propagation of new microcracks in coal samples was measured, and the propagation velocity was calculated. The morphology and electro-mechanical characteristics of new microcracks were tested. More importantly, the causes of the changes in the electro-mechanical characteristics before and after fracture were analyzed, and the effects of these changes on the EMR were discussed. The results showed that the average propagation velocities during the same time interval are 9.5 μm/s, 12.1 μm/s, and 16.2 μm/s. The elastic modulus of the material at the microcrack edge is generally smaller than that of the material in other locations, while the adhesion and deformation are larger. Moreover, the closer the material is to the microcrack, the higher its surface potential. The electrons generated at the microcrack edge and emitted into the atmosphere, which made the greater potentials of the microcrack edge. Many electrons with different velocities and directions migrate in similar parallel-plate capacitors, which are formed by the relative microscale surface of the coal microcrack tip and have different field strengths, resulting in EMR with complex frequencies and different intensities. This study provides a micro-dynamic experimental basis for research on the electromagnetic radiation mechanism.

According to the new stress distribution pattern and the strong strata behaviors as the characteristics of the coal pillars in the close-distance multiseam coal pillar mining, the common characteristics of different types of overlying coal pillars were summarized and analyzed. Moreover, a theoretical model for the mechanism of strong strata behaviors in the close-distance multiseam coal pillar mining was established, which was validated by the monitoring data of seismic computed tomography CT, microseism, and electromagnetic radiation (EMR). Furthermore, the results of the study indicated that the main factors affecting the strong strata behaviors were the static stress concentration caused by the overlying coal pillars and the dynamic disturbance caused by the fracturing and slipping of the overlying coal pillars and roof under the influence of mining. In the case of Xinzhouyao coal mine, the transmitted stress and lateral support pressure of the overlying coal pillars accounted for 78.3% and 16% of the vertical concentrated stress, respectively, and the areas closer to the overlying coal pillars were more susceptible to dynamic load disturbances. The monitoring results of seismic computed tomography CT and EMR demonstrated the static load stress concentration area was distributed near the overlying coal pillar, and the stress concentration degree was greater in the area of superimposed lateral support pressure and advanced support pressure. Moreover, microseismic spatial positioning revealed that the high-energy microseismic events were mainly concentrated near the overlying large coal pillars and roof. The on-site multiparameter detection results were highly consistent with the characteristics of actual strata behaviors and the conclusions of the theoretical model. This method could provide a reference for the quantitative calculation of stress distribution under similar conditions and the identification of the danger zone of strata behaviors.

Roadway deformation and rock burst are the two key challenges faced by the safe operation of coal mines. Aiming at the issue of large deformation of the gob-side roadway under coal pillars in multiseam mining, this study has considered the case of the 8308 panel of Xinzhouyao coal mine in China. Based upon a combination of theoretical analysis, numerical simulations, and engineering practices, the mechanical model of “stress and deformation quantitative calculation of gob-side roadway under overlying coal pillars” was established in this study. The analytical solutions of the vertical stress distribution and the plastic zone of the gob-side roadway under overlying coal pillars were obtained. Finally, the accuracy of the mechanical model was verified using numerical simulations. The results showed that the coal pillar, upright above the gob-side roadway, and the cantilever roof around the gob-side roadway were the main factors leading to stress concentration and deformation around the gob-side roadway. For the particular cases considered in this study, the peak stress of the gob-side roadway could reach 1.8 times of the self-weight stress of overlying strata. The rates of the contribution of the gob-side roadway’s overlying pillar and the cantilever roof around the gob-side roadway to peak stress were 78.3% and 16%, respectively. The obtained results have an essential reference significance for stress calculations and rock burst prevention design of gob-side roadway under overlying coal pillars in multiseam mining.

It is vital to understand the electromagnetic radiation’s time-frequency characteristics in the process of coal and rock failure with different joint angles in order to reveal the generation mechanism of the electromagnetic radiation (EMR) and improve the accuracy of EMR early warning. We studied the time-frequency characteristics of EMR signals of coal samples with different joint angles. The study finds that, (1) with the increase of joint angle, the failure time and peak load of samples decrease first and increase later, and the postpeak failure time decreases gradually. The EMR counts’ peak value showed a slow rise, a sharp rise, and a slow rise in the three intervals of α = 0° to 45°, 45° to 60°, and 60° to 90°, respectively. The accumulated EMR counts showed a steady upward trend. The duration of the EMR waveform, the dominant frequency of the EMR, and the peak number of the frequency spectrum of coal samples are on the rise. (2) As the joint angle increases, the samples’ failure mode changes from the stage fracture dominated by tension cracks to the rapid fracture with the coexistence of shear and tension cracks and finally to the burst fracture which produces a large number of fragments. This is also the main reason for the difference of the EMR generation mechanism and the signal of samples with different joint angles. (3) According to the experimental results, we established the modified formulas for calculating the EMR threshold value and deviation of coal and rock with joints under different stress environments and revealed that the longer the EMR waveform duration, the higher the dominant frequency, and the more the number of spectrum peaks, the greater the burst risk of coal and rock.

In order to reveal the magnetic field response law and mechanism of concrete under load, the variation law of magnetic field intensity (MFI) of concrete samples under uniaxial loading, graded loading and cyclic loading was tested, and the field application scenarios of magnetic field monitoring technology are proposed. The results showed that a magnetic field signal would be generated during the loading failure process of the concrete sample, which was accompanied by the whole loading process. In the uniaxial compression process, MFI showed a steady increase trend, but it would increase rapidly when the load drop occurred in the sample. The stronger the rupture, the more significant the change of MFI. MFI was not linearly proportional to the amount of change in the load drop. MFI around the concrete sample was positively correlated with the load. When the concrete was in the constant load stage, MFI around the concrete remained basically stable. When the main rupture of the concrete sample occurred, MFI reached a peak value, it did not keep at a high level all the time, but decreased rapidly. There are two mechanisms for the generation of the magnetic field in the process of concrete failure under load, namely the piezomagnetic effect and the friction effect, which correspond to the action of the load and the excitation of the fracture, respectively. The former causes the stable increase of MFI, and the effect is related to the influence of the content of the piezoelectric magnetic material in the material composition; the latter leads to a sudden increase of MFI, and the effect is related to the triboelectric effect of the micro-particles of the material. The research results are conducive to the accurate prediction of the concrete magnetic field monitoring, and help promote the development of mine dynamic disaster monitoring and early warning technology.

Aiming at problem of low efficacy of early warning of rock burst in coal mine, a multisystem and multiparameter integrated early warning method based on genetic algorithm (GA) is proposed. In this method, firstly, the temporal-spatial-intensity information of energy incubation process of rock burst is deeply mined, and the multidimensional precursory characteristic parameter system of rock burst is constructed. Secondly, the genetic algorithm is used to train the historical monitoring data to obtain the optimal critical value and fitness value of each precursory characteristic parameter, and then the early warning index WC of each monitoring system is calculated. Finally, the integrated rock burst early warning index IC is obtained by synthesizing the early warning index WC of each system. The value of IC corresponds to the specific rock burst risk level of the mine. This method is applied to Wudong coal mine in Xinjiang, China. Based on the actual situation of the mine, a multidimensional precursory characteristic parameter system of rock burst is constructed, which includes energy deviation (DE), frequency ratio (Fr), frequency deviation (DF), degree of dispersion (DS), and total high value of energy deviation (DH). After analyzing the rock burst danger status and risk level in the monitoring area, the early warning capability of this method is found to reach 0.896. Combining with the specific prevention and control measures corresponding to different rock burst risk levels, it can provide effective guidance for the field work.

Coal and rock dynamic disasters have been the main concern in underground engineering because these seriously threaten the safety of miners and industrial production. Aiming to improve the EMR and AE monitoring technology, the refined nonlinear characteristics of EMR and AE during coal splitting failure are studied using Hilbert-H and multifractal theory, and valuable information pertaining to coal fracture law contained in EMR and AE waveform was revealed. The results show that the EMR and AE of coal splitting failure are related to the process of coal crack propagation. They possess the same initiation time and frequency band, however, the signal duration of EMR is comparatively longer than AE, and the main frequency of AE is higher than EMR. The EMR of coal splitting failure has the same excitation source as AE; nonetheless, the excited forms display different behavior. In terms of signal duration, the distribution of EMR signal is relatively uniform, the proportion of large-signal is less, the amount of information is more than that of AE, and the multifractal characteristics are more complicated. During the coal splitting failure, AE is mainly generated in the process of wall vibration caused by crack propagation, while the generation of EMR includes piezoelectric effect, charge separation, free charge vibration, charge neutralization and other processes, making EMR more complicated than AE and has a relatively low frequency. The research provides an effective method for studying nonlinear refinement characteristics of coal EMR and AE, and can provide an important basis for the study of the mechanism of EMR generation.

Elastic wave velocity is a critical parameter in evaluating rock stability and integrity. Temporal changes in wave velocity during mine dynamic hazards including rockburst and gas outburst might potentially illuminate physical processes associated with stress concentration, crack propagation and fault slip behaviors. Laboratory and theoretical studies predict changes in wave velocity before rock failure; however, these dynamic hazards occur in a range of modes and little is known about precursors for those modes. Here, we show that precursory changes of wave velocity occur in laboratory tests for coal and sandstone samples under cyclic loading. We survey the ultrasonic wave velocity variation using the method of coda wave interferometry and find fluctuations of wave velocity during the cyclic loading corresponding with the stress-strain change, which may be explained by crack nucleation and propagation processes. Our data show that accumulated micro-cracks cause significant reduction of ultrasonic wave velocity and elastic moduli during the transitional phase preceding failure, which suggests that continuous wave speed monitoring might be a means to detect mine dynamic hazards precursors. Keywords: Ultrasound precursors, Wave speed, Coda wave interferometry, Cyclic compression, Damage evolution

Rockburst is a serious hazard in underground engineering, and accurate prediction of rockburst risk is challenging. To construct an intelligent prediction model of rockburst risk with interpretability and high accuracy, three binary scorecards predicting different risk levels of rockburst were constructed using ChiMerge, evidence weight theory, and the logistic regression algorithm. An intelligent rockburst prediction model based on scorecard methodology (IRPSC) was obtained by integrating the three scorecards. The effects of hazard sample category weights on the missed alarm rate, false alarm rate, and accuracy of the IRPSC were analyzed. Results show that the accuracy, false alarm rate, and missed alarm rate of the IRPSC for rockburst prediction in riverside hydropower stations are 75%, 12.5%, and 12.5%, respectively. Setting higher hazard sample category weights can reduce the missed alarm rate of IRPSC, but it will lead to a higher false alarm rate. The IRPSC can adaptively adjust the threshold and weight value of the indicator and convert the abstract machine learning model into a tabular form, which overcomes the commonly black box problems of machine learning model, as well as is of great significance to the application of machine learning in rockburst risk prediction.

Rock bursts pose a significant risk to coal mine operation safety. Thus, accurately discriminating coal bursting liabilities is crucial for predicting and preventing rock burst events. To better understand the effects of a varying bedding angle on the crack propagation rule, failure mode and bursting liability level of coal and coal-rock combinations, we propose an optimized machine learning-based model. Additionally, uniaxial compressive tests are conducted using PFC3D software on samples with different bedding angles. The results indicate that, among the nine light gradient boosting machine discriminant models constructed using three data preprocessing methods and three parameter optimization algorithms, the optimal model is identified as the particle swarm optimization-light gradient boosting machine discriminant model based on Z-score standardization method, which exhibits the best stability and has a F1-score of 93.6%. Bedding has a significant impact on the failure modes of two kinds of samples, resulting in an evident bedding effect on their bursting liability. The uniaxial compression strength and bursting energy index of both samples show a reduction-rising trend with an increasing bedding dip angle. However, the bursting liability level of these samples is not affected by 0°C or 90°C bedding dip angle. Therefore, when assessing the bursting liability of samples, the influence of coal seam bedding and its dip angles should be thoroughly considered. [ABSTRACT FROM AUTHOR]

In order to improve the monitoring and prediction of coal and gas outburst, this paper proposes a new method for dynamic regional prediction of coal and gas outburst using microseismic (MS) monitoring. The theoretical basis of this method is presented. An index evaluation system was established and applied, based on which field tests were carried out in a coal mine. The results show that seismic monitoring with frequency and energy indexes can obtain good results for mining disturbance intensity monitoring and geological structure detection; the regional stress distribution detected by seismic wave tomography is consistent with the theoretical stress field, making its use of great significance for optimizing coal and gas outburst drilling parameters and improving overall tunneling efficiency. This approach overcomes the limitations of traditional methods in the temporal and spatial dimensions and realizes dynamic and continuous monitoring of coal and gas outburst-prone areas.

Early warning of a potential rockburst risk and its area of occurrence helps to take effective and targeted measures to mitigate rockburst hazards. This study investigates the microseismic (MS) spatial-temporal precursory characteristic parameters in a typical steeply inclined and extremely thick coal seam (SIETCS) with high rockburst risk and proposes three spatial/temporal quantification parameters and a spatial-temporal early warning method. Analysis results of temporal parameters show that the sharp-rise-sharp-drop variation in total daily energy and event count can be regarded as a precursor for high energy tremor. The appearance of peak values of both energy deviation (≥20) and event count deviation (≥1) can be regarded as precursors that indicate imminent rockburst danger. A laboratory acoustic emission (AE) experiment reveals that precursor characteristics obtained from the study can be feasibly used to warn the rockburst risk. The spatial evolution laws of spatial parameters show that the high energy density index of MS (EDIM), velocity, velocity anomaly regions correlate well with stress concentration and rockburst risk areas. The field application verifies that the temporal-spatial early warning method can identify the potential rockburst risk in a temporal sequence and rockburst risk areas during the temporal early warning period.

The accurate detection of coal seam stress field effectively prevents coal and gas outbursts. This study uses wave velocity, wave velocity anomaly coefficient, and wave velocity gradient as indicators to identify stress anomalies in coal seam. The results show that these three indicators of wave velocity are all positively correlated with load, while changes in the wave velocity anomaly coefficient and wave velocity gradient are more gentle than those of wave velocity. The degree of damage of coal can be judged by the wave velocity anomaly coefficient, while the transition between high and low stress zones can be identified by the wave velocity gradient. In areas affected by geological structures such as valleys and mountain tops, the coal seam wave velocity and wave velocity anomaly coefficient may exhibit anomalies. The comparative analysis of wave velocity and its derived indicators can reveal the stress state and coal structure of coal seamwith higher accuracy, identify the areas affected by geological structures such as valleys and mountain tops, and determine the boundary of the stress relief zone after hydraulic fracturing. Combined with the actual geological structure characteristics of coal seam, it can accurately identify the stress disturbance region of coal seam and achieve the purpose of predicting coal and gas outbursts. [ABSTRACT FROM AUTHOR]

The magnitude and frequency of induced seismicity increase as mining excavation reaches greater depth, leading to the increasingly severe damage to roadways caused by highenergy seismic waves. To comprehensively simulate the damage caused by dynamic loads, a synchrosqueezing transform and empirical mode decomposition method was developed, which effectively decomposed raw seismic wave signals into transverse and longitudinal components. This novel method produced more accurate results in terms of velocity, displacement, rock yielding patterns, and reflecting theoretically orthogonal oscillating directions of transverse and longitudinal waves compared to using raw mixed waves at the seismic source. Under the disturbance of transverse and longitudinal waves, the vertical displacement was much higher than horizontal displacement at the top position of the roadway, while the horizontal displacement was greater at the sidewalls. The particle vibration velocity, displacement and yielding zone of the surrounding rock of roadway were proportional to the energy level of seismic, while inversely proportional to the sourceroadway distance. The proportion of damage attributed to transverse waves increased with the energy level, ranging from 75.8% to 85.8%. Eventually, a roadway dynamic support design was optimized based on the proposed seismic wave processing and modeling methodology. The methodology offers guidance for roadway dynamic support design, with the goal of averting excessive or insufficient support strength. [ABSTRACT FROM AUTHOR]

The steeply inclined and extremely thick coal seams (SIETCS) under the condition of gob filling frequently suffer from the occurrence of rockbursts. Figuring out the mechanisms of rockbursts under this condition for taking targeted measures to mitigate rockburst hazards in SIETCS is of great significance. Using the typical SIETCS with an average dip angle of 87° at Wudong Coal Mine (WCM) as a case study, a mechanical model and elastic deformation energy (EDE) function of a “steeply inclined suspended roof structure” was developed, and the influence factors were analyzed by theoretical analysis. Simultaneously, the rockburst risk assessment was carried out based on the theory of a rockburst start-up. The pressure relief measures are optimized by comparing the pressure relief effects of three kinds of destress blasting schemes. The results indicate that the damage characteristics of rockburst are mainly floor heave, the sidewall’s inward deformation and roof subsidence. The damage degree of headentry on the roof side is more severe than that of tailentry, and the resultant impacts showed the directionality from the roof side to the coal side. The steeply inclined and suspended roof breakage is one of the main causes for the occurrence of rockbursts. The EDE of the roof increases with an increasing dip angle of the coal seam from 0° to 72.6° and then decreases as the dip angle increases. Furthermore, that increase is accompanied by the decrease of the lateral pressure coefficient and the supporting force coefficient. The EDE stored in the roof is sufficient to cause roof breakage and induce rockburst after the complete roof exceeds a certain length. The mechanism of rockburst in SIETCS for fully mechanized top-coal caving mining under gob filling conditions was proposed, i.e., “high compressive stress concentration plus breakage of the suspended roof-induced stress” rockburst, and this is further verified by ground destruction, microseismic (MS) monitoring and numerical modeling. The results also indicate that alternate deep and shallow hole-blasting modes are more suitable for pressure relief in SIETCS.